Premature infants are exceptionally vulnerable to nutrition-related diseases, and the utilization of standardized feeding guidelines may reduce nutritional practice variation, which can promote growth. Nutritional risk screening is the first step for standardized nutrition advice. However, risk screening tools specific for following up preterm infants are scarce. Hence, our study aimed to develop and evaluate a standardized Nutritional Risk Screening Tool for Preterm Infants  from birth to corrected age four months old.z-scores of the body weight, length, or head circumference to identify significant predictors of underweight, stunting, or microcephaly. We then combined significant predictors to produce models for predicting underweight, stunting, or microcephaly by multivariate logistic regression analysis. In the evaluation phase, the area under the curve (AUC), sensitivity, specificity, and correlation coefficient by Spearman's correlation analysis (rs) between the risk classifications by NRSP subscale 1 and the classifications of the z-scores of the body weight, length, or head circumference were calculated to assess the validity of the screening tool. Intellectual development levels between high and low nutritional risk infants were statistically compared.This study was a two-phase  study. Initially, we used the Delphi expert consultation method to create NRSP subscale 1. Then, a professional panel interviewed the participated preterm infants using the screening tool, measured anthropometric parameters, and conducted an intellectual development test on the interview day and remeasured anthropometric parameters 2 weeks or 1 month after the first interview. In the development phase, we cross-tabulated the responses to the screening tool with the classifications of p < 0.001), sensitivity was 0.667, specificity was 0.941, rs = 0.407 (p < 0.001); AUC was 0.794 , sensitivity was 0.500, specificity was 0.953, rs = 0.339 (p < 0.001); AUC was 0.831 , sensitivity was 0.889, specificity was 0.643, rs = 0.215 (p = 0.001) in predicting underweight, stunting, and microcephaly on the interview day, respectively. AUC was 0.905 , sensitivity was 0.500, specificity was 0.905, rs = 0.504 (p < 0.001); AUC was 0.738 , sensitivity was 0.429, specificity was 0.848, rs = 0.382 (p < 0.001); AUC was 0.664 , sensitivity was 0.455, specificity was 0.809, rs = 0.169 (p = 0.037) in predicting underweight, stunting, and microcephaly 2 weeks or 1 month after the first interview, respectively. Gross motor development quotients (DQs) , fine motor DQs , and verbal DQs  were higher in low nutritional risk infants than high-risk ones.A total of 219 and 244 preterm infants were included to two phases, respectively. AUC was 0.936 (95% CI: 0.860–1.000, NRSP subscale 1 was acceptable and reliable in predicting underweight, but the validity in predicting stunting or microcephaly was slightly mild. Further investigations are required to authenticate NRSP subscale 1's effectiveness. Premature infants are exceptionally vulnerable to nutrition-related diseases, such as protein-energy malnutrition, iron deficiency, and metabolic bone disease , 2, 3, 4However, standardized nutritional risk screening and nutrition advice for preterm infants upon discharge is not widely performed in China . Moreovez-score of body weight or length were significant predictors of growth failure in early childhood [Nutrients required for catch-up growth are sufficient energy, protein, vitamins, and minerals , 14. Stuhildhood . ConsequInitially, a professional panel of five pediatric medical staff qualified no less than attending physicians designed the item pool. The item pool was then reviewed using the Delphi expert consultation method. Eight experts with qualifications of at least associate chief physician or associate professor specializing in pediatrics or nutriology were individually invited to assess the manuscript through email. In the first review, experts used a Likert scale  to evaluate each item's importance and proposed suggestions for the screening tool. We excluded items with a mean score of less than 4. The professional panel then revised the screening tool according to the experts' recommendations. Thereafter, the experts were asked to re-evaluate the validity of each item of the screening tool. Eventually, we retained items agreed by all experts only to construct NRSP subscale 1.This study was composed of two phases: the development phase and the evaluation phase. The development phase occurred from August to December 2020, while the evaluation phase was from January to May 2021. Participants were enrolled from the Child Healthcare Department of Foshan Women and Children Hospital by convenience sample. Recruitment of participants to both phases was based on the following inclusion and exclusion criteria. We recruited preterm infants  aged from birth to corrected age four months old who undertook physical examination in the Child Healthcare Department of Foshan Women and Children Hospital. On the other hand, preterm infants who were diagnosed with metabolic diseases and required a special diet were excluded from the study. This study protocol was reviewed and approved by the Medical Ethics Committees of Foshan Women and Children Hospital, approval number FSFY-MEC-2020-028.All parents of the participating preterm infants had given their written informed consent before the interview. Five qualified healthcare workers face-to-face interviewed the caregivers using standardized guiding words and marked their choices. After the interview, the preterm infants would undergo anthropometric measurement based on standardized techniques and the intellectual development test (for preterm infants of corrected age from GA 40 weeks to 4 months) by the “Developmental Scale for Children aged 0–6 years of China.” The intellectual development level was described as the development quotient , including gross motor index, fine motor index, adaptability index, verbal index, and social communication index. For example, for a preterm infant of corrected age 1 month whose gross motor could reach the level of term infants at 1 month, his gross motor mental age was 1 month, and his DQ was 100 (1/1). Two weeks or 1 month after the first interview, the preterm infants' anthropometrics were measured again. z-Scores of (birth) weight, length, or head circumference were calculated based on the Fenton 2013 growth chart (for preterm infants of corrected age before GA 40 weeks) or WHO growth chart (for preterm infants of corrected age from GA 40 weeks to 4 months). Clinical and anthropometric data were recorded into a spreadsheet and double-checked daily.A subsample of 20% of participants in the development phase was interviewed on the same day by two healthcare workers independently to evaluate the inter-rater reliability. Another 20% of participants were reinterviewed after a week to evaluate the test-retest reliability. The agreement was on a reliability level of more than 80% (data not shown).z-score of body weight, length, and head circumference, which were measured on the interview day and 2 weeks or 1 month after the first interview. “Underweight/stunting/microcephaly at present” was defined as a z-score of body weight/length/head circumference on the interview day < −2. “Underweight/stunting/microcephaly next time” was described as a z-score of body weight/length/head circumference on the day 2 weeks or 1 month after the first interview < −2.The nutritional risk outcomes of NRSP subscale 1 were the classifications of t test or as median and interquartile range and analyzed by the Kruskal-Wallis test. At the same time, categorical data were presented as frequencies and percentages and analyzed by the χ2 test or Fisher's exact test.Statistical analysis was carried out using IBM SPSS, version 25.0. Normal distributed continuous data were described as mean and standard deviation values and analyzed by one-way analysis of variance or Student's z-scores of body weight, length, or head circumference, respectively, by univariate analysis to identify factors that significantly predicted underweight, stunting, or microcephaly. We then assigned a score to significant factors based on their relationship with body weight, length, and head circumference growth. For example, factors with no significant relationship with underweight, stunting, or microcephaly were scored as zero , whereas factors with a significant relationship were scored as 1  or 2 . Factors recognized in the literature as having a direct impact on growth were scored similarly. For example, vitamin D supplement 400–800 IU/day for body length growth, “6–7 days per week” was scored as zero, “4–5 days per week” was scored as 0.5, “1–3 days per week” was scored as 1, whereas “none” was scored as 2. We then combined predictors to generate a model that would best predict underweight, stunting, or microcephaly using multivariate logistic regression analysis. The area under the curve (AUC) was used to assess the models' effectiveness in predicting underweight, stunting, or microcephaly, while the cutoff values were determined using the Youden index.We compared demographic data of participants of the two phases. We used data from the development phase to assign items scores and produce models to predict nutritional risk. Responses to the screening tool were cross-tabulated with the classifications of rs) between risk classification by NRSP subscale 1 and the z-score classification of body weight, length, or head circumference will be calculated.Moreover, we utilized data from the evaluation phase to accurately evaluate the validity of the screening tool. AUC, sensitivity, specificity, and correlation coefficient by Spearman's correlation analysis  and current diseases .Part 2 incorporated information about the feeding practices of preterm infants. For example, milk intake per kilogram of weight per day, breastfeeding exclusivity, formulae milk preparation as instructed, nutritional fortifier use , special formulae use , the presence of feeding difficulty, and whether each feed duration exceeded 30 min.z-scores of (birth) weight/length/head circumference, and the presence of a descending pattern in z-score of body weight or length or head circumference (z-score on the interview day minus z-score last time < −0.2). Items of the NRSP subscale 1 are shown in Tables Part 3 discussed the nutrients supplements such as vitamin D, vitamin A, iron element, and outdoor hours per week. Part 4 involved anthropometric assessment, including z-score of body weight had a significant relationship with the classification of z-score of body weight on the interview day. However, birth weight and length, current diseases, nutritional fortifiers use, and feeding difficulty correlated significantly with the classification of z-score of body length on the interview day. Meanwhile, birth head circumference, current diseases, milk intake per day, nutritional fortifiers and special formulae use, feeding difficulty, vitamin D supplement, and the decrease in z-score of head circumference showed correlation with the classification of z-score of head circumference on the interview day.Our study found that birth weight and length, current diseases, milk intake per day, nutritional fortifiers and special formulae use, feeding difficulty, and the decrease in z-score of body weight on the day 2 weeks or 1 month after the first interview. At the same time, results exhibited a significant association between birth weight and length, body weight and length on the interview day, current diseases, and feeding difficulty with the classification of z-score of body length on the day 2 weeks or 1 month after the first interview. Simultaneously, birth head circumference, body weight, length and head circumference on the interview day, current diseases, milk intake per day, special formulae use, feeding difficulty, the decrease in z-score of head circumference related to the classification of z-score of head circumference on the day 2 weeks or 1 month after the first interview. Results of responses to the NRSP subscale 1 compared with the z-scores classification of body weight, length, and head circumference were shown in Table Furthermore, the analysis showed that birth weight and length, body weight and length on the interview day, current diseases, milk intake per day, nutritional fortifier and special formulae use, feeding difficulty, and iron supplement had a significant relationship with the classification of z-scores of birth weight and length, current diseases, milk intake, nutritional fortifier use, special formulae use, feeding difficulty, and the decrease in z-score of body weight. The model for predicting “stunting at present” included factors of birth weight and length, current diseases, milk intake, nutritional fortifier use, feeding difficulty, vitamin D supplement, and outdoor hours per week. The model for predicting “microcephaly at present” included factors of birth head circumference, current diseases, milk intake, nutritional fortifier use, special formulae use, feeding difficulty, vitamin D supplement, and the decrease in z-score of head circumference.After multivariate logistic regression analysis (data not shown), elements of each item were assigned scores Table  by panelz-score of head circumference.The model for predicting “underweight next time” was composed of factors of birth weight and length, body weight and length on the interview day, current diseases, milk intake, nutritional fortifier use, special formulae use, feeding difficulty, and iron element supplement. The model for predicting “stunting next time” included factors of birth weight and length, body weight and length on the interview day, current diseases, milk intake, nutritional fortifier use, feeding difficulty, vitamin D supplement, and outdoor hours per week. The model for predicting “microcephaly next time” covered factors of birth head circumference, head circumference on the interview day, current diseases, milk intake, nutritional fortifier use, special formulae use, feeding difficulty, vitamin D supplement, and the decrease in AUCs of models to predict underweight and stunting were all above 0.700, sensitivities were 0.429–0.667, specificities were 0.848–0.953, and correlation coefficients were 0.339–0.504. AUCs of models to predict microcephaly were above 0.664, sensitivities were 0.455–0.889, specificities were 0.643–0.809, and correlation coefficients were 0.169–0.215. Results were shown in Table p = 0.005), gross motor DQs , fine motor DQs , and verbal DQs  were with statistical significance. Results are shown in Table A total of 413 preterm infants from the development and evaluation phases underwent an intellectual development test. There was a discrepancy in the distribution of different GAs between the high and low nutritional risk groups. However, corrected age was used when calculating DQ; therefore, it was suggested that the difference mentioned above might not affect the result. DQs of low nutritional risk preterm infants were all higher than those of high nutritional risk preterm infants, but only differences of full-scale DQs   and the rs 0.407–0.504) than stunting or microcephaly (rs < 0.4). That was because the body length or head circumference growth was regulated by genetic factors, social and economic environment, nutrition, health status, cerebral development, and skull thickness [z-scores classifications of body weight, length, or head circumference and the nutritional risk classification by NRSP subscale 1 was relatively low, we could still benefit from the screening tool. As genetic factors, social and economic environments are not easy to change; however, improving health status or nutrition intake is feasible.We also found that NRSP subscale 1 was more effective in predicting underweight . We found the screening tool relatively reliable. Moreover, the screening tool's questions and guiding words were elaborately modified by a professional panel and experts. We expect it aiding in standardizing the process of nutritional risk screening in preterm infants' follow-up. Nevertheless, further investigations are required to establish the screening tool's effectiveness within different healthcare settings, such as community health services.This study protocol was reviewed and approved by the Medical Ethics Committees of Foshan Women and Children Hospital, approval number FSFY-MEC-2020-028. All parents of the participating preterm infants had given their written informed consent before the interview.The authors have no conflicts of interest to declare.This work was supported by Guangdong Medical Science and Technology Research Fund Project, grant number A2020472.X.H. and Y.Z. proposed and designed the study. X.H., C.W., S.H., P.G., and Y.Z. drafted the item pool. X.H., C.W., and S.H. carried out the study. X.H. and Z.J. performed the statistical analysis and were co-first authors. X.H., Z.J., and B.N. drafted and revised the manuscript. All the authors read and approved the final manuscript.All data generated or analyzed during this study are included in this article. Further inquiries can be directed to the corresponding author.


Although small for gestational age (SGA) is a serious problem worldwide, the association of dietary patterns before and during pregnancy with SGA risk is unclear. We evaluated this association among Japanese pregnant women using three methods: reduced rank regression (RRR) and partial least squares (PLS), methods for extracting dietary patterns that can explain the variation of response variables, and principal component analysis (PCA), a method for extracting dietary patterns of the population.Between July 2013 and March 2017, 22,493 pregnant women were recruited to the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study, a population-based prospective birth cohort study in Japan. Information on dietary intake was obtained using food frequency questionnaires, and dietary patterns were extracted using RRR, PLS, and PCA. Information on birth weight was obtained from obstetric records, and the birth weight SD score and SGA were defined by the method of the Japan Pediatric Society. The associations of dietary patterns with birth weight SD score and SGA risk were investigated using multiple linear regression and multiple logistic regression, respectively.A total of 17,728 mother-child pairs were included. The birth weight SD score was 0.15 ± 0.96, and the prevalence of SGA was 6.3%. The dietary patterns extracted by RRR and PLS were similar and characterized by a high intake of cereals and fruits and a low intake of alcoholic and non-alcoholic beverages in both pre- to early pregnancy and from early to mid-pregnancy. Higher adoption of the RRR and PLS patterns in both periods was associated with an increased birth weight SD score and lower risk of SGA. In contrast, the PCA1 pattern was not associated with birth weight SD score or SGA risk in either period. Although the PCA2 pattern was associated with increased birth weight SD score from early to mid-pregnancy, no other associations with birth weight SD score or SGA risk were observed.The dietary pattern with a high intake of cereals and fruits and a low intake of alcoholic and non-alcoholic beverages before and during pregnancy was associated with a decreased SGA risk in Japan.The online version contains supplementary material available at 10.1186/s12937-022-00808-7. Small for gestational age (SGA) is defined as a birth weight below the 10th percentile of the reference birth weight by sex and weeks of gestation in a region –4. In JaMaternal nutritional status is considered one of the most important factors in healthy fetal development , 7. HoweOne of the major methods for extracting dietary patterns is principal component analysis (PCA). PCA derives a linear function of food intake that best explains the variation in food intake and can reflect people’s actual dietary patterns . HoweverSeveral reports have investigated the association between dietary patterns and SGA in pregnant women using PCA. Knudsen et al. reported in a prospective study in Denmark that the “health-conscious pattern” characterized by a high intake of vegetables, fruits, fish, and poultry was associated with a lower risk of SGA . ThompsoHowever, to date, there has been one report that used RRR to evaluate the association between dietary patterns and SGA in pregnant women. A prospective study in China by Liu et al. reported that a dietary pattern characterized by a high intake of legumes, soy products, vegetables, and animal products and a low intake of wheat and oil was associated with a lower risk of SGA . HoweverThis study used data from the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study (TMM BirThree Cohort Study), which is a population-based prospective birth cohort study conducted by the Tohoku Medical Megabank Organization (ToMMo). This study aimed to facilitate the resolution of medical issues following the Great East Japan Earthquake of March 11, 2011, and the details of the study described previously . BrieflyBirth weight, sex of the child, parity, and gestational age at birth were obtained from obstetric records at birth. The birth weight SD score was defined as the SD of the distribution of birth weight considering the sex of the child, parity, and gestational age at birth in accordance with the method of the Japan Pediatric Society and SGA was defined as a birth weight below the 10th percentile of Japanese infants .Details of dietary information are described in Supporting information Details of dietary patterns are described in Supporting information Details of potential confounders are described in Supporting information P for trend for continuous variables and by χ2 test or Cochran-Armitage test for categorical variables.Participants’ background attributes are presented as mean ± SD for continuous variables and as frequency (percentage) for categorical variables. Comparisons of the background attributes stratified by dietary patterns were assessed by ANOVA and The association of each dietary pattern with birth weight SD score was assessed using multiple regression analysis. The association between each dietary pattern and SGA risk was assessed using logistic regression analysis. In model 1, we adjusted for maternal age, pre-pregnancy BMI, educational qualification, annual household income, smoking habits, drinking habits, and folic acid supplement consumption habits. We did not adjust for maternal weight gain during pregnancy in model 1 because we assumed that maternal weight gain might be an intermediate variable between dietary patterns and outcomes. However, in model 2, we adjusted for maternal weight gain to estimate the association between dietary patterns and the outcomes, independent of maternal weight gain. The missing values for the confounding variables were complemented using the multivariate completion method with chained equations, where the missing data were assumed to be random, using the mice package in R . The numn = 18,667). RRR, PLS, and PCA were also performed in the included subjects stratified by maternal characteristics such as maternal age (< 30 and ≥ 30 years), annual household income , and educational qualification . We also performed RRR, PLS, and PCA in subjects without gestational diabetes mellitus (GDM) to exclude possible confounding of the effects of GDM on SGA risk .To assess the robustness of the extracted dietary patterns, we performed some sensitivity analyses. To evaluate the possibility of selection bias, RRR, PLS, and PCA were performed, and dietary patterns were reextracted with the excluded subjects who had available data on dietary intake and incidence of SGA .A total of 17,728 mother-child pairs were included in the analysis. Approximately two-thirds (67.4%) of mothers were over 30 years old, with a mean pre-pregnancy BMI of 21.6 ± 3.4 kg/mThe factor loadings and explained variation of the dietary patterns extracted by RRR, PLS, and PCA from pre- to early pregnancy and from early to mid-pregnancy are shown in Table The explained variation in the predictive variables (food groups) was lower for RRR than PCA, and PLS was in between . The explained variation in the response variable (birth weight SD score) was higher for RRR than PCA, and PLS was in between .P for trend < 0.001 from pre- to early pregnancy, β [Quartile 4 vs. Quartile 1] 0.12 , P for trend < 0.001 from early to mid-pregnancy; risk of SGA: odds ratio [OR] [Quartile 4 vs. Quartile 1] 0.83 , P for trend = 0.02 from pre- to early pregnancy, OR [Quartile 4 vs. Quartile 1] 0.85 , P for trend = 0.04 from early to mid-pregnancy).The associations of each dietary pattern with birth weight SD score and SGA from pre- to early pregnancy and from early to mid-pregnancy are shown in Table P for trend < 0.001 from pre- to early pregnancy, β [Quartile 4 vs. Quartile 1] 0.14 , P for trend < 0.001 from early to mid-pregnancy; risk of SGA: OR [Quartile 4 vs. Quartile 1] 0.77 , P for trend = 0.003 from pre- to early pregnancy, OR [Quartile 4 vs. Quartile 1] 0.76 , P for trend = 0.001 from early to mid-pregnancy).Higher adoption of the PLS pattern in both periods was significantly associated with higher birth weight SD scores and lower risk of SGA in adjusted model 2 , the pattern was not associated with the risk of SGA.The PCA1 pattern was not significantly associated with birth weight SD score or SGA risk in either period. The PCA2 pattern from pre- to early pregnancy was not associated with birth weight SD scores and SGA risk. Although higher adoption to the PCA2 pattern from early to mid-pregnancy was significantly associated with higher birth weight SD scores in adjusted model 2  (data not shown). In subjects with an educational qualification of university graduate or above, the association of the RRR and PLS patterns in both periods with birth weight SD score and SGA risk was stronger than that in the main analysis. These individuals had lower pre-pregnancy BMI and weight gain during pregnancy than those in the main analysis (data not shown). Undereating owing to the desire to stay slim among Japanese women is a problem leading to a downward trend in the birth weights of infants . It mighWe also performed RRR, PLS, and PCA in subjects without GDM and found that the food groups that characterized the dietary patterns were almost the same as those in the main analysis  , 29. RegIn several previous studies on dietary patterns derived from PCA, the “Healthy Japanese pattern” with high intake of vegetables, fruits, legumes, mushrooms, seaweed, and seafood was extracted as a typical dietary pattern of the Japanese people and was associated with a lower risk of hypertension, diabetes, cardiovascular disease, physical dysfunction, and mortality . EpidemiThe PCA2 pattern was characterized by a high intake of dairy products, eggs, vegetables, and legumes (only from early to mid-pregnancy) and a low intake of cereals and meat. This dietary pattern was similar to the “Western dietary pattern: characterized by high intake of dairy products, eggs, vegetables, fruits, and cereals” in a previous study among Japanese pregnant women . Thus, tIn general, the dietary pattern extracted by PCA reflects people’s actual dietary conditions, while it may have little association with the outcomes. However, although the dietary patterns extracted by RRR or PLS do not necessarily reflect people’s actual dietary conditions, they are more likely to be associated with the outcomes. Therefore, although the actual dietary patterns of the pregnant women in this study were not associated with SGA, the dietary patterns revealed by RRR and PLS may be useful as a benchmark for future ideal dietary patterns to prevent SGA.Regarding nutrient intake, the dietary patterns extracted by RRR and PLS were characterized by a high intake of carbohydrates, vitamin B1, vitamin C, beta-cryptoxanthin, and copper . Supplementary Table 8. Associations of dietary patterns with birth weight SD score and SGA with the excluded subjects who had available data on dietary intake and incidence of SGA . Supplementary Table 9. The characteristics of the 17,728 mothers who were analyzed and the 4765 mothers who were excluded from the analysis. Supplementary Table 10. Factor loadings and explained variation of dietary patterns identified using RRR, PLS and PCA in subjects without gestational diabetes mellitus . Supplementary Table 11. Associations of dietary patterns with birth weight SD score and SGA in subjects without gestational diabetes mellitus .Additional file 2.


Sunitinib is one of the first‐line targeted drugs for metastatic renal cell carcinoma (RCC) with dual effects of antiangiogensis and proapoptosis. Sam68 , is found being involved in cell apoptosis. This article reveals that Sam68 impacts the sensitivity to sunitinib by mediating the apoptosis of RCC cells. Immunohistochemical staining indicated that the Sam68 expression levels in sunitinib sensitive tumor tissues were markedly higher than those in sunitinib resistant tumor tissues. Sunitinib induced RCC cell apoptosis in a concentration‐dependent manner and inhibited the expression of total and phosphorylated Sam68 (p‐Sam68). Downregulation of Sam68 expression inhibited RCC cell apoptosis induced by sunitinib. While upregulation of Sam68 expression could enhance apoptosis induced by sunitinib. Xenograft models showed that tumors in the Sam68‐knockdown group did not shrink as much as those in the control group after treatment with sunitinib for 4 weeks. Together, our results suggest that Sam68 expression is associated with the sensitivity of ccRCC patients to sunitinib. Sam68 may promote cell apoptosis induced by sunitinib, and the Sam68 expression level may be a biomarker for predicting sunitinib sensitivity in ccRCC patients. Sam68 expression is associated with the sensitivity to sunitinib in ccRCC patients. Upregulation or downregulation the expression of Sam68 in RCC cells affected apoptosis induced by sunitinib. Sam68 may be a potential target for sunitinib, and may be a biomarker for predicting sunitinib sensitivity in ccRCC patients. High expression and cytoplasmic localization of Sam68 were significantly correlated with poor overall survival in patients with RCC.22.1Forty‐seven patients with relapsed/metastatic RCC who underwent operations or biopsies and were histopathologically diagnosed, were then treated with sunitinib at Sun Yat‐sen University Cancer Center from 2010 to 2018. According to the Response Evaluation Criteria In Solid Tumors (RECIST 1.1), patients with evaluation of Complete Response (CR) and Partial Response (PR) were classified into the sunitinib sensitive group, while patients with evaluation of Stable Disease (SD) and Progress Disease (PD) were classified into the sunitinib resistant group. All patients signed an informed consent form before the study. Paraffin‐embedded samples of patient tumors and the clinical information of patients were obtained for research purposes with the approval of the Institutional Research Ethics Committee of Sun Yat‐sen University Cancer Center.2.2Immunohistochemistry (IHC) was employed to detect Sam68 protein expression in 47 human RCC tissues with the human Sam68 antibody . The immunohistochemistry procedure was performed according to the manufacturer's instructions. The immunostaining intensity of the tissue sections was measured by FIJI software.2.32.The human normal renal tubular epithelial cell line HK2 was cultured in DMEM/F12  supplemented with 10% fetal bovine serum . The human embryonic kidney cell line 293 T and RCC cell lines 769P, NC‐65, ACHN, SKRC39, and UMRC6 were cultured in DMEM , while Caki‐1 and 786O cells were cultured in RPMI 1640  supplemented with 10% fetal bovine serum. Cells were obtained from the American Type Culture Collection  and incubated at 37°C and 5% CO2.4http://t.cn/S44oNe; created by Sigma‐Aldrich, Darmstadt, Germany), synthesized , and then subcloned into pLKO.1 carriers to construct Sam68 knockdown plasmids. Transfections were performed with Lipofectamine 3000  according to the manufacturer's instructions. Stably transfected cell lines were selected with 0.5 μg/mL puromycin for more than 10 days.The PCR‐amplified human Sam68 coding sequence was subcloned into the pBABE retroviral vector and then the Sam68 overexpression plasmid was constructed. Sam68 short hairpin RNA (shRNA) oligonucleotides  were designed on the website (2.5https://www.ncbi.nlm.nih.gov/tools/primer‐blast/). The primer sequences were as follows: Sam68 forward: 5′‐AAAGAGCGAGTGCTGATACCT‐3′, reverse: 5′‐TGAGCCCTTTCCCA ATACAGA‐3′; β‐Actin forward: 5′‐CTTCGCGGGCGACGAT‐3′, reverse: 5′‐CCACATAGG AATCCTTCTGACC‐3′.Total RNA was extracted from cell lines using TRIzol reagent , and 2 μg of RNA from each sample was acquired for reverse transcription. Then, the products were used for cDNA synthesis according to the manufacturer's instructions, and qRT‐PCR was adopted to assess the fold changes in Sam68 mRNA expression. The mRNA expression of the housekeeping gene beta actin (β‐Actin) was applied to normalize the geometric mean for each sample. Primers for Sam68 and β‐Actin were generated and verified using the Primer‐BLAST modules on the National Center for Biotechnology Information (NCBI) website . A bicinchoninic acid (BCA) assay kit  was applied for protein quantification following the manufacturer's instructions. Western blotting was carried out according to standard methods described in the manufacturer's protocol. In brief, equal amounts of proteins mixed with 5× sodium dodecyl sulfate‐polyacrylamide gel electrophoresis (SDS‐PAGE) loading buffer  were heated in a metal bath at 100°C for 10 min, electrophoresed through 10% SDS‐PAGE gels and electrotransferred onto polyvinylidene fluoride (PVDF) membranes . After the membranes were blocked in blocking solution containing 5% skim milk for 1 h at room temperature, they were incubated with certain primary antibodies  overnight at 4°C, and then incubated with corresponding secondary antibodies  for 1 h at room temperature. The protein bands were visualized using an enhanced chemiluminescence (ECL) substrate . Anti‐β‐Actin antibody was used as the loading control. The intensities of bands were detected and quantified by ImageJ software.2.750) of sunitinib treatment for 48 h in HK2, NC‐65 Caki‐1, 769P and SKRC39 cells were then calculated.Cells were seeded into 96‐well plates at 2000 cells/well and allowed to attach overnight. Vehicle dimethyl sulfoxide  or sunitinib  was added to the medium at different concentrations for the following days. After 24, 48 or 72 h, CCK‐8 reagents  were added to each well and then incubated at 37°C for 2 h. Absorbances at 450 nm were read using an automated plate reader. The half maximal inhibitory concentrations  and 4′, 6‐diamidino‐2‐phenylindole . Apoptosis rates were measured by flow cytometry and analyzed by FlowJo software.To analyze cell apoptosis levels, cells were seeded into 6‐well plates at 1 × 102.96) transfected with control shRNA (sh‐Control) or Sam68 shRNA (sh‐Sam68) were subcutaneously injected into the rear back region of each mouse. When tumors reached 70‐100 mm3 at an average of 28 days later, each group of mice was randomized into two subgroups (n = 5 each) and treated with 0.5% carboxymethylcellulose sodium  or sunitinib  by gavage. Tumor volume was measured every 2–3 days and calculated as follows: volume = length×(width)2/2. The mice were euthanized 4 weeks after sunitinib treatment, and then tumors were resected and subsequently weighed. All animal experimental procedures were approved by the Laboratory Animal Ethics Committee of Sun Yat‐sen University Cancer Center.Six‐week‐old female BALB/c nude mice were obtained from Beijing Vital River Laboratory Animal Technology Company , randomized into two groups and anesthetized. NC‐65 cells  but not in the sunitinib resistant RCC and non‐ccRCC subgroup  of patients after sunitinib treatment initiation and Sam68 immunohistochemical OD were then investigated in the sunitinib resistant cohort and the two corresponding subgroups. TTP was positively correlated with the Sam68 immunohistochemical OD values in the ccRCC subgroup  was decreased gradually in both NC‐65 and Caki‐1 cells treated with an increasing dose of sunitinib, while the total Src protein levels were hardly affected Figure . This reAs Sam68 is a substrate of Src, we further assessed the potential effects of sunitinib on Sam68. Western blotting showed that total Sam68 protein and phosphorylated Sam68 (p‐Sam68) levels decreased in a dose dependent manner with sunitinib Figure . FurtherThese results suggested that sunitinib inhibits the expression and activity of Sam68. Sam68 might be a potential target of sunitinib, and play a crucial role in the effect induced by sunitinib in RCC cells.3.3To further confirm the impact of Sam68 in the sunitinib treatment of RCC, HK2, 769P and SKRC39 cells were used to constructed exogenous Sam68‐overexpression cell line while Caki‐1 and NC‐65 cells were selected to established Sam68‐knockdown cell lines Figure B. Stably3.450 values of sunitinib treatment for 48 h were significantly decreased in HK2, 769P and SKRC39 cells while Sam68 expressions were upregulated, and notably increased in NC‐65 or Caki‐1 Sam68‐knockdown cells  and contribute to a high rate of cell apoptosis. When Sam68 was downregulated, the impact of sunitinib on Bcl‐x alternative splicing was reduced. Bcl‐x(S) was not increased and Bcl‐x(L) was not obviously decreased. As a result, cell apoptosis induced by sunitinib was attenuated. On the basis of these results, we reveal that the apoptotic effect induced by sunitinib in RCC tumor cells, at least in part, is regulated by nuclear Sam68 mediated modulation of the alternative splicing of Bcl‐x. These could be critical factors to consider, when selecting the best targeted drugs for RCC patients who accept sunitinib treatment. However, these findings still require further clinical investigation in a larger cohort to confirm their accuracy and practicability and further experiments are needed to verify the molecular mechanism.In summary, our study demonstrated that Sam68 expression is strikingly associated with the apoptotic effect of sunitinib and may be a biomarker for sunitinib sensitivity in ccRCC patients.There are no potential conflicts of interest to disclose.ZSW, YLP, and LBX performed the experiments, analyzed the data, and wrote the manuscript. ZLZ, FJZ, and CPY conceived the study, participated in the study design and revised the manuscript. PD provided patients information. JW prepared the human samples and paraffin section. ZL and KN collected the clinical data. MHD, NW, WWS, and ZYL help with the main experiments. All authors approved the final version of the manuscript.This study was with the approval of the Institutional Research Ethics Committee of Sun Yat‐sen University Cancer Center and the Laboratory Animal Ethics Committee of Sun Yat‐sen University Cancer Center.Figure S1Click here for additional data file.Figure S2Click here for additional data file.Data S3Click here for additional data file.


GA was an independent determinant of plasma cortisol levels at birth. SGA infants had a high plasma cortisol level at birth; resulting in speculation that a high plasma cortisol level at birth may predict abnormal neurological outcomes.There are no study reports to clarify the association between gestational age (GA) or anthropometric values at birth, and plasma cortisol levels in the blood of preterm infants at birth and at one month of age. This hospital-based retrospective cohort study included infants born at <37 weeks’ gestation between 2019 and 2021. First, the association between plasma cortisol level and GA or anthropometric values at birth  was identified by regression and multiple regression analyses. Second, plasma cortisol levels in the umbilical cord at birth and at one month of age were compared between small-for-gestational age (SGA) and non-SGA infants. Sixty-one preterm infants were enrolled (SGA: 24 and non-SGA: 37). Plasma cortisol levels at birth were significantly associated with GA. Plasma cortisol levels at one month of age were associated with GA and birth head circumference SDS. Plasma cortisol levels at birth were significantly higher in SGA than non-SGA ( Cortisol is an essential hormone for the maintenance of human health. During the fetal period, cortisol promotes organ maturation, whereas excess cortisol suppresses organ development. During the fetal period, maternal active cortisol is converted into inactive cortisone by 11β-hydroxysteroid dehydrogenase-2 (11βHSD2) in the placenta to prevent the influx of maternal active cortisol into the fetus. However, under stresses, such as poor nutrition and hypoxia, 11βHSD2 activity in the placenta is suppressed and maternal active cortisol flows into the fetus ,4. Fetal growth parameters, such as the body weight standard deviation score (SDS) and head circumference SDS, have been used as indicators to assess poor intrauterine nutrition . PreviouThis retrospective cohort study was approved by the Ethics Committee of Nihon University Itabashi Hospital . All preterm infants born by cesarean section at Nihon University Itabashi Hospital between September 2019 and June 2021 were enrolled in the study. Written informed consent was provided by the parents. Blood samples of the infants at birth  and at 1 month of age were obtained for routine laboratory tests for various medical reasons. After the relevant laboratory tests were performed, the residual blood samples were used to measure plasma cortisol levels. The exclusion criteria were prenatal diagnosis of monochorionic twins, severe congenital heart malformation, and chromosomal abnormalities. Preterm infants, who were born between 22 and 36 weeks after conception, were then divided into three groups based on Japanese neonatal anthropometric charts for GA at birth : birth wBlood samples were collected from the umbilical vein immediately after birth and from vein puncture at 1 month of age (median [minimum-maximum]: 28 (25–49) days after birth), and blood samples at 1 month of age were collected between 8 and 9 a.m. before feeding. Plasma cortisol levels were measured using the electrochemiluminescence immunoassay method, as previously reported . The difShortly after birth, a 10% sugar solution was initiated at a water quantity (WQ) of 50–60 mL/kg/day. Thereafter, the WQ was increased by approximately 10 mL/kg/day, considering daily weight gain or loss, urine output, and insensible excretion. In the case of infusion alone, the WQ was maintained at 100–120 mL/kg/day. Depending on the infant’s condition, enteral feeding (exclusive breast feeding) was initiated, the infusion was tapered and the feeding volume was maintained at a WQ of 130 mL/kg/day with enteral feeding alone. After 35 weeks of corrected GA, infants were fed independently if possible.Maternal clinical factors included maternal age at birth, pre-pregnancy body mass index (BMI), weight gain during pregnancy, maternal height, placental weight, multiple births, the development of hypertensive disorder of pregnancy (HDP) and gestational diabetes mellitus (GDM), presence of chorioamnionitis, and prepartum intramuscular betamethasone use (two intramuscular injections of 12 mg are administered 24 h apart to pregnant women at high risk of preterm birth before 33 weeks and 6 days according to our management policy). HDP is defined as hypertension (blood pressure ≥ 140/90 mmHg) during pregnancy . GDM is 2), and p-values were calculated. Multiple regression analysis was performed using plasma cortisol levels at birth and at 1 month of age and Δ cortisol levels as objective variables, and GA and each anthropometric SDS at birth as explanatory variables. Study 1: To clarify the association between GA or anthropometric values  at birth with plasma cortisol levels at birth and at 1 month of age in preterm infants, regression analysis was performed to linearly compare GA or each anthropometric SDS at birth and plasma cortisol levels at birth and at 1 month of age. Δ cortisol levels, coefficient of determination , and During the study period, 61  preterm infants were enrolled. Of the non-SGA infants, 35 were AGA and 2 were LGA. The clinical characteristics of the enrolled infants and their mothers are presented in 2 = 0.154, p = 0.0018 and R2 = 0.146, p = 0.0024, respectively).2 = 0.078, p = 0.029; p < 0.05, p = 0.015).Plasma cortisol levels in umbilical blood and at 1 month of age, and Δ cortisol levels were significantly positively correlated with GA A–C. Δ cop = 1.000). No significant difference between the two groups was found with respect to the timing of betamethasone use (p = 0.113). In the SGA group, fetal distress was the most common cause for delivery . In the non-SGA group, threatened preterm delivery was the most common cause for delivery .Mothers who delivered at least one SGA infant were included in the SGA group. Maternal complications, such as multiple births, HDP, GDM, and chorioamnionitis were not significantly different between the two groups . No signAs expected, BW, BL, and birth head circumference were significantly lower in the SGA group than in the non-SGA group. No significant differences were found in the GA .p = 0.010). However, there were no significant differences in plasma cortisol levels at 1 month of age and Δ cortisol levels between the two groups. Plasma cortisol levels at birth and at 1 month of age were plotted based on GA in SGA and non-SGA infants . A compaIn the present study, we observed that in preterm infants, plasma cortisol levels at birth and at 1 month of age were positively correlated with GA. Importantly, plasma cortisol levels at 1 month of age were positively correlated with head circumference SDS at birth. SGA infants had significantly higher plasma cortisol levels at birth than non-SGA infants; however, this significant difference disappeared at 1 month of age.Most of the cortisol in maternal blood is inactivated by 11βHSD2 in the placenta to maintain fetal blood cortisol levels at approximately 10% of the maternal levels . Hence, GA is known to affect fetal cortisol levels ,25. SimiIn fetal growth restriction, blood flow to the limbs decreases, height decreases, and weight gain decreases. However, vital organs, such as the brain and adrenal glands, are prioritized . SGA infSGA infants had significantly higher plasma cortisol levels at birth than non-SGA infants; fetal distress was the most common cause of preterm birth in SGA infants, which was more common than in non-SGA infants. Previous studies reported that the HPA axis is affected by fetal distress, undernutrition, maternal infection, and strict diet ,31. ExceOur results revealed that plasma cortisol levels at 1 month of age were not significantly different between the SGA and non-SGA groups. Iwata et al. reported that cortisol levels in saliva were higher in the non-SGA group than in the SGA group after 14 days of age . The reaOur study had some limitations. First, because this was a single-center study with a short duration, the number of infants in the cohort was limited. Second, this study included all preterm infants born by cesarean section with a high percentage of prenatal dexamethasone administrations to pregnant women, which was a major limitation. Słabuszewska-Jóżwiak et al. reported that there was no difference in umbilical cord blood cortisol levels between cesarean and vaginal delivery, but umbilical cord blood cortisol levels were significantly lower in scheduled cesarean section delivery than in vaginal delivery, possibly due to less distress involved in uterine contractions during delivery compared to vaginal delivery . In thisGA is an independent determinant of plasma cortisol levels at birth. SGA infants had a high plasma cortisol level at birth; resulting in speculation that a high plasma cortisol level at birth may be associated with abnormal neurological outcome. Further follow-up studies using a large cohort are required to confirm this result.


An excessive rise in maternal lipids during pregnancy may have detrimental impacts on maternal and fetal health leading to adverse pregnancy outcomes. However, knowledge gaps exist with respect to the association between lipid biomarkers and birth outcomes.N = 25) with mid-pregnancy fasting serum samples collected at 22–28 weeks of gestation and birth outcome data. Serum was analyzed for conventional lipid profile  and lipoprotein subclass distribution, including particle number (nM) and size (nm), for very low-density lipoprotein (VLDL)/chylomicron (CM), low density lipoprotein (LDL), and high-density lipoprotein (HDL), by nuclear magnetic resonance spectroscopy.We conducted a secondary data analysis of healthy pregnant women  and gestational age (weeks), were assessed using multivariable linear regression, adjusted for pre-pregnancy BMI.p > 0.05) with birth outcomes, every 1-unit increment in large VLDL/CM particles (nM) and VLDL/CM size (nm) was associated with an increase in birth weight . Among the HDL subclass parameters, a 1-unit (nM) increase in the concentration of total HDL-particles was associated with a reduced birth weight  after adjustment for maternal pre-pregnancy BMI.Although conventional lipids were not associated (The preliminary results of this pilot study suggest that total particle concentrations of VLDL/CM and HDL in mid-pregnancy have divergent associations with birth weight, potentially reflecting the specific roles of these lipoprotein particles with respect to placental function and fetal growth. To support placental development and optimal nutrient transfer to the growing fetus, a physiological rise in maternal blood lipids is observed during pregnancy, exemplified by transient but substantial increases in triglycerides TG, ~ 200–400%), total-cholesterol TC, ~ 25–50%), low-density lipoprotein cholesterol LDL-C, ~ 70%), and high-density lipoprotein cholesterol  , 2. Howe00–400%, –50%, low0%, and hAs blood lipid assessment is not a routine component of obstetrical care , there aThis study was a secondary analyses of serum samples and birth outcome data collected as part of a previous pregnancy pilot cohort to examine the reinforcing value of high-energy-dense foods during pregnancy (not published). All procedures were approved by the Institutional Review Board at the University at Buffalo STUDY00001381). The cohort consisted of 25, 18–35-year-old pregnant women with singleton gestations, recruited within the greater Buffalo, New York area between 2018–2019 through flyer distribution, social media posts, and local urban obstetrics clinics  was calculated as weight in kilograms divided by the square of height in meters. At mid-pregnancy between gestation weeks 22–28, a fasting blood sample was collected by a blood draw technician. A birth outcome questionnaire administered at a home visit within 7 days of birth was used to collect information on infant variables  and pregnancy complications .Following a blood clotting period of 30 min at room temperature, maternal serum samples were separated by centrifugation at 3000 × g for 20 min and stored at -80 °C. TC, HDL-C, direct LDL-C, and TG were measured by direct automated enzymatic assay using diagnostic reagent kits, calibrators, and quality controls. Direct assessment of lipoprotein subclass distribution, including particle number (nM) and size (nm), for very low density lipoprotein (VLDL)/chylomicron (CM), low density lipoprotein (LDL), and high density lipoprotein (HDL), was conducted by nuclear magnetic resonance spectroscopy (NMR) using automated signal acquisition followed by computational analysis and proprietary signal processing algorithms  . The diap < 0.05), as estimated by linear regression, were included in the adjusted model. Two models were used in the analysis: (i) Model 1 was the crude model with second trimester lipid exposure only; and (ii) Model 2 adjusted for maternal pre-pregnancy BMI (the only significant confounder). All analyses were conducted using SAS version 9.4 . Statistical significance was set at a two-sided alpha level of p < 0.05.Associations between maternal second trimester lipids and continuous birth outcomes including birth weight (g) and gestational age (weeks) were assessed using multivariable linear regression. We considered maternal age and pre-pregnancy BMI as potential confounders that could affect both maternal pregnancy lipid status and birth outcomes. Significant confounders (n = 1), no pregnancy complications were reported and mean infant birth weight and gestational age at delivery was 3543 ± 333 g and 39.28 ± 0.89 weeks, respectively.Mothers included in this study were mainly Caucasian (92%), highly educated (92% college educated), and overweight or obese according to pre-pregnancy BMI (60%) Table . With thp > 0.05) to birth weight or gestational age  (Table p = 0.03) after adjustment for maternal pre-pregnancy BMI (Table p < 0.05) with gestational age.Standard lipid profile measures, including cholesterol , TG, and apoB were unrelated  were associated with increased infant birth weight while total HDL particles were associated with reduced birth weight. This divergent lipoprotein-specific association may reflect the unique functional roles of VLDL and HDL lipoproteins in maternal fuel metabolism and placental/fetal development during pregnancy.Pregnancy is associated with adaptive changes in the metabolism of the large triglyceride-rich lipoproteins including chylomicrons of intestinal origin and VLDL which transport de novo synthesized lipids from the liver. By late pregnancy, serum TG increases by 200–400% due to a decrease in insulin sensitivity. The subsequent influx in adipose-derived fatty acids to the liver results in an estrogen-induced increase in VLDL production and secretion . MaternaInterestingly, neither maternal TG nor VLDL subclass parameters in mid-pregnancy were associated with gestation age. Previous work has reported that elevated maternal TG concentration in pre-pregnancy  and earlnd trimester [Although total and LDL-C concentrations increase substantially throughout gestation, the rise in maternal HDL-C is relatively minor and has been reported to peak in the 2rimester , 25. Therimester –28. Alterimester  reportedrimester , 30.Outside of pregnancy, HDL is most typically recognized as a cardioprotective mediator of reverse cholesterol transport. However, during pregnancy, HDL has a range of other diverse functions that may specifically influence placental metabolism and fetal growth, as recently reviewed by Woollett et al. . First, In conclusion, the preliminary results of this pilot study suggest that total particle concentrations of VLDL/CM and HDL in mid-pregnancy have divergent associations with birth weight, potentially reflecting the specific roles of these lipoprotein particles with respect to placental function and fetal growth. However, our findings must be interpreted with caution given several limitations including a small sample size potentially reflecting a type-1 statistical error, lack of statistical power to examine effect modification by infant sex, collection of birth outcome data with a maternal-reported birth outcome questionnaire, restriction of our analyses to one mid-pregnancy timepoint, and a lack of diversity with respect to race/ethnicity and education. Despite these limitations, our findings can inform future work to examine how the trajectory of lipoprotein distribution across pregnancy influences birth outcomes in a larger and more diverse longitudinal cohort.


DPAGT1, and this disorder currently lacks effective therapies. To identify potential therapeutic targets for DPAGT1-CDG, we performed CRISPR knockout screens in Drosophila cells for genes associated with better survival and glycoprotein levels under DPAGT1 inhibition. We identified hundreds of candidate genes that may be of therapeutic benefit. Intriguingly, inhibition of the mannosyltransferase Dpm1, or its downstream glycosylation pathways, could rescue two in vivo models of DPAGT1 inhibition and ER stress, even though impairment of these pathways alone usually causes CDGs. While both in vivo models ostensibly cause cellular stress (through DPAGT1 inhibition or a misfolded protein), we found a novel difference in fructose metabolism that may indicate glycolysis as a modulator of DPAGT1-CDG. Our results provide new therapeutic targets for DPAGT1-CDG, include the unique finding of Dpm1-related pathways rescuing DPAGT1 inhibition, and reveal a novel interaction between fructose metabolism and ER stress.Partial loss-of-function mutations in glycosylation pathways underlie a set of rare diseases called Congenital Disorders of Glycosylation (CDGs). In particular, DPAGT1-CDG is caused by mutations in the gene encoding the first step in N-glycosylation,  DPAGT1, by using the fruit fly model organism, Drosophila melanogaster. Using inhibitory drugs, we perform two cell-based screens with CRISPR technology to determine which genes are important under DPAGT1 inhibition. We then used a living fly, that models DPAGT1-CDG in the eye, in order to determine which of the top screened genes can improve its impaired eye development. Surprisingly, we found that inhibiting other CDG-causing genes, such as our top hit Dpm1, could improve our DPAGT1-CDG cell and fly models. In addition, loss of certain metabolism genes, and changes in diet, also improved the DPAGT1-CDG model. This study finds multiple new genes and pathways implicated in DPAGT1-CDG and lays the groundwork for new CDG therapies.Sugar modifications are important to proper protein folding and function. The biological pathways that control these sugar modifications are called glycosylation pathways. When these pathways are disrupted, such as through genetic mutation, it can cause rare developmental disorders called Congenital Disorders of Glycosylation (CDGs). Most CDGs lack any treatment options, and little is known about interacting genes or pathways that might improve these disorders. Here, we study DPAGT1-CDG which involves mutations in the enzyme-encoding gene,  Glycosylation comprises a variety of sugar-based co- or post-translational modifications that occur primarily in the endoplasmic reticulum (ER) and Golgi apparatus . It inclAlg7 in Drosophila, hereafter referred to as DPAGT1). In humans, partial loss-of-function mutations in DPAGT1 can cause DPAGT1-CDG (CDG-Ij) with symptoms including seizures and developmental delay, among others [DPAGT1 are also associated with congenital myasthenic syndrome due to hypoglycosylated acetylcholine receptors [DPAGT1 mutant cell lines also show an increased level of chronic ER stress, autophagy, and have signs of senescence [Of the glycosylation pathways, N-linked glycosylation is critical for proper protein folding and function ,5. Inhibg others ,12. Mutaeceptors ,14. Inhieceptors ,16 and ieceptors . DPAGT1-nescence .DPAGT1 can also lead to improper N-glycosylation and may underlie some cancer phenotypes [DPAGT1 expression or downstream phenotypes can potentially be used to develop new therapeutic options [As with most CDGs, there are only symptomatic treatment options and no causative therapeutics available for DPAGT1-CDG ,19. Any enotypes . One alt options –23. More options .DPAGT1. These screens identify novel genes involved in modifying cellular and physiological outcomes associated with DPAGT1 inhibition and increased ER stress. Of note, we find that knockout of multiple GPI anchor biosynthesis genes improves survival and cell surface glycoprotein levels in Drosophila S2 cells associated with DPAGT1 inhibition and ER stress from tunicamycin. In addition, we find that the mannosyltransferase Dpm1 is one of the strongest modifier genes and inhibition of Dpm1 vastly improves cell survival under the loss of DPAGT1 function and ER stress. We provide evidence that this effect likely occurs through the combined role of Dpm1 in O-mannosylation, N-glycosylation, and GPI anchor biosynthesis pathways. Importantly, the majority of our top candidate genes validate in in vivo models of DPAGT1 inhibition and ER stress. In addition, results from the cell screens suggest that fructose metabolism might affect the loss of DPAGT1 function, and we observed altered fructose metabolism in the in vivo DPAGT1 model, suggesting that dietary fructose supplementation may hold therapeutic promise for these patients. Taken together, we identify numerous new candidate DPAGT1 modifier genes, using Drosophila flies and cells, that are potential therapeutic targets and report the remarkable finding that impairing CDG genes in parallel can result in an improved overall phenotype.Here we present two genome-wide CRISPR screens for genes that modify phenotypes associated with reduced function of DPAGT1 function and ER stress, we performed a cell-based, genome-wide CRISPR/Cas9 knockout screen . Briefly, we used genome-wide single guide RNA (sgRNA) libraries transfected into a Drosophila S2 cell line to generate a pool of cells in which each cell carried gene knockouts , hexosamine enzymes Gfat2  and mmy , the insulin-degrading enzyme Ide , and the glycolytic kinase Pfk  and the kinase/phosphatase Pfrx  , the hexosamine enzyme Oscillin , and the transporter-related genes Rab6  and Rab40  (Tables 1151 gene knockouts (8.7% of genes tested) increased resistance to DPAGT1 inhibition at an lfc value of ≥0.5, while 251 gene knockouts (1.9% of genes tested) increased sensitivity to DPAGT1 inhibition at an lfc value of ≤-0.5 . Top res) Tables . Top senDrosophila orthologs of known CDG genes. To explore this further, we queried all known Drosophila CDG orthologs and a CDG genetic panel [Many top candidate genes are ic panel ,28 , and is also important in glycosylation pathways [Drosophila orthologs, We performed Gene Ontology (GO) analysis on all candidate genes with an absolute lfc ≥ 0.5 compared to untreated cells Tables  and S3. pathways . To furtDrosophila cells as described above. Again, cells were either untreated or exposed to Tun and fluorescently-labeled with Concanavalin A (ConA), which binds cell surface glycoproteins [Tun inhibition of DPAGT1 results in reduction of specific glycoproteins from the cell surface such as AchR ,31 and Cproteins ,35. CellUnder DPAGT1 inhibition, knockout of multiple genes was able to rescue cell surface glycoproteins to the levels observed in untreated cells . We consPIG") genes encode a diverse class of enzymes that build the GPI sugar chain [PIG genes were among the 209 hits, and all had at least 3 sgRNAs combined from both replicates, placing them in the top ~22% of candidate genes. One of these is PIG-A (PIGA), which was also a hit in the survival screen (lfc = 0.81). The other four were PIG-S (PIGS), PIG-B (PIGB), PIG-H (PIGH), and PIG-O (PIGO). Notably, these five PIG genes are spread throughout the entire GPI anchor biosynthesis process: PIGH and PIGA are both components of the initial GPI-GlcNAc transferase complex that attaches GlcNAc to phosphatidylinositol. PIGB performs an intermediate mannosylation step. PIGO attaches an ethanolamine after PIGB. PIGS is part of the final GPI-transamidase complex which attaches the GPI anchor to a protein. Given their diverse functions, spanning two separate enzyme complexes, it is likely that GPI anchor biosynthesis as a whole can influence the phenotype. Remarkably, the data suggest that impairment of GPI anchor biosynthesis, a process that is typically known to create cell surface glycoproteins, can rescue cell surface glycoprotein levels under DPAGT1 inhibition.GO analysis of the 209 genes that restore cell surface glycoprotein levels indicated that "GPI anchor biosynthetic process" GO:0006506), "glycolipid metabolic process" (GO:0006664), and "inositol metabolic process" (GO:0006020) were the top enriched categories . Thus, a substantial percentage of gene knockouts that restore cell surface glycoproteins also increase resistance. Nevertheless, as the majority of genes that cause increased resistance did not have this effect , the consistent rescue of cell surface glycoprotein levels is not required to increase resistance to DPAGT1 inhibition.We hypothesized that some genes rescue the cell survival phenotype  by rescuin vivo, we created a DPAGT1 disease model in Drosophila that expresses DPAGT1 RNAi in the eye—causing a small, rough eye phenotype  from the survival and ConA screen . Usis FDR<0.0 from then Tables . We usedin vivo effects that were consistent with the outcome from the cell screens, but others had no effect or even the opposite effect (DPAGT1 model (PEK (PERK)  and Hrd3 (SEL1L) .Many of these candidate genes had e effect . HoweverT1 model . For exaPfk (lfc = 1.47) and Pfrx (lfc = 1.74), as they have the highest lfc values in the glycolytic pathway from the survival screen. Pfrx was also a hit in the ConA screen . On the other hand, in the nucleotide sugar synthesis pathway, RNAi against transaminase-encoding Gfat2, despite causing resistance (lfc = 4.68), did not significantly affect the DPAGT1 model , improved the DPAGT1 model (+28.8%). These differences from the cell screen may be caused by the differing biology of simple replicating cells compared to an in vivo eye model which has to pass through multiple stages of development and differentiation.We also tested A screen . MatchinT1 model . MoreovePmm2 rescued the DPAGT1 model eye size , important for bioavailability of downstream dolichol phosphate mannose (Dol-P-Man) [DPAGT1 model eye size  showed the strongest rescue of the DPAGT1 model phenotypes   is most critical for improving DPAGT1 deficiency. In sum, while loss of DPM1 is normally detrimental to cells and patients [Dpm1 improved the DPAGT1 model.We tested RNAi against genes encoding four enzymes in GDP-mannose synthesis, Pmm2, Mpi, CG3792, and Dpm1. One RNAi line against  +22.2%, . Mpi RNAe -9.7%, , though l-P-Man) ,42, did eye size  Figs. Ho +82.5%)  Figs. Dpynthesis –46  and rescues cell surface glycoproteins   Figs  Tables. T1 model  Figs.rotated abdomen  or twisted  rescued eye size in both the DPAGT1  and ER stress  models  models  Figs. ThAlg3 (ALG3) and Alg12 (ALG12) improved eye size in both the DPAGT1  and ER stress  models. However, RNAi against Alg9 (ALG9) did not affect either model , and the mannosyltransferases PIG-B  and PIG-M . A second PIG-M RNAi line had a small negative effect (-5.7%). RNAi lines against the mannosyltransferase PIG-V (PIGV) did not have a significant effect. Surprisingly, RNAi against PIG-A was detrimental to the DPAGT1 model . Unlike the previous two pathways tested, the ER stress model was not as consistent with the DPAGT1 model, though it also had an overall beneficial effect . RNAi against CG6659 did not affect eye size in either model; however, here we note an increased chance of a false negative as only one RNAi line and one gene from this pathway were examined (DPAGT1 function or ER stress.C-mannosylation is a less common type of glycosylation that involves the addition of mannose to tryptophan found in thrombospondin type 1 repeats . The foumportant ). In Droexamined  Figs. ThDPAGT1 inhibition and ER stress. Notably, RNAi against any single gene in these three pathways never reached the same magnitude of rescue provided by Dpm1 RNAi (+62.1%)—with the closest being tw (+45.9%) and PIG-M (+31.9%) RNAi  RNAi . This suDPAGT1 inhibition, including the aforementioned enzymes Pfk (lfc = 1.47) and Pfrx (lfc = 1.74), as well as the dehydrogenase Gapdh1 , phosphoglycerate mutase Pglym87 , and pyruvate kinase CG12229 , among others    . In contd -2.4%) . While tDPAGT1 inhibition identified using a cell-based CRISPR screen. Testing these candidate genes in vivo validated many of the strongest hits and demonstrated that knockdown of GPI anchor biosynthesis and downstream DPM1/Dpm1 glycosylation pathways can rescue the effects of DPAGT1 deficiency and ER stress. Even though single gene mutations in these pathways are associated with specific CDGs, knockdown of many of these genes paradoxically improved negative phenotypes associated with DPAGT1 inhibition and ER stress both in vitro and in vivo.Here, we report hundreds of new candidate genes that modify the effects of DPAGT1 inhibition. Similar mechanisms are utilized in the response to ER stress, where the UPR will reduce protein synthesis in response to ER stress, giving the cell time to recover [DPAGT1 function is by freeing up cellular machinery that helps fold or degrade misfolded proteins. One such pathway is the calnexin/calreticulin (CNX/CRT) cycle, a process that ensures the proper folding of N-glycosylated proteins in the ER [DPAGT1 function. ER-associated degradation (ERAD) involves the recognition, translocation, and ubiquitination/degradation of misfolded proteins in the ER through the use of different enzyme complexes [Hrd3 was a strong hit in the cell survival screen . Finally, as Hrd3 RNAi only improved the DPAGT1 model, but had either no effect or worsened the ER stress model, this suggests another difference between the mechanism of stress between each model and how that stress may be ameliorated. Overall, this might provide a novel approach to DPAGT1-CDG or other glycosylation disorders, where a therapy might be designed to slow down global glycosylation and/or globally activating proteostasis machinery, to allow impacted cells more time to repair or clear misfolded proteins.One hypothesis for this outcome is that impairing glycosylation pathways might slow down the overall synthesis of glycoproteins, thereby allowing cells to better withstand  recover ,62. Anotn the ER . Recentln the ER . In one omplexes . One comomplexes . Hrd3 wal screen , and it T1 model . DeficieDPAGT1 model, each one could provide a good therapeutic target for DPAGT1-CDG. Although targeting DPM1 itself might be a useful approach, targeting a downstream gene may be better in practice to reduce the effects of elimination of all glycosylation pathways. For example, knockdown of POMT2/tw almost reached the same level of rescue as Dpm1 alone (+45.9% vs. +62.1%), while targeting POMT2 would perturb only O-mannosylation. O-mannosylation affects cadherins, plexins, and alpha-dystroglycan, among other proteins [Dpm1 might increase the pool of dolichol-phosphate available for DPAGT1 to utilize (including under inhibition). While this would not explain why inhibiting glycosylation pathways downstream of Dpm1 also improves DPAGT1 inhibition, it could be partially responsible for why loss of Dpm1 alone causes stronger rescue than loss of any of its downstream pathways. Alternatively, another hypothesis is that DPAGT1 inhibition may increase flux of dolichol-phosphate through Dpm1 to cause excessive glycosylation, which is then turned off under Dpm1 inhibition in order to cause its rescue effect. However, given that tunicamycin strongly reduced binding of ConA, which binds to mannose/glucose moieties in glycoproteins [Because independent perturbations of three downstream Dpm1-dependent glycosylation pathways alone were capable of partially rescuing the proteins , and is proteins . Thus, lproteins ,71, it iMpi (MPI), another gene in the GDP-mannose pathway, worsened the DPAGT1 and ER stress models , which also rescued cell surface glycoproteins in the ConA screen. PEK knockdown also improved the in vivo DPAGT1 model. PEK encodes a protein kinase essential to the cellular ER stress response. Other genes encoding ER stress sensor proteins, Xbp1 and ATF6 [PEK leads to increased survival is that ER-stress-induced apoptotic-related gene expression might be lower in these cells, which may allow them time to grow and repair despite being stressed. While Drosophila lacks the ATF4 downstream pro-apoptotic target CHOP, Drosophila Crc can activate apoptosis by downregulation of the anti-apoptotic E3 ubiquitin ligase XIAP/Diap1 [PERK, knockout of crc does provide resistance (lfc = 0.75). Interestingly, Crc is also a co-activator of the hormone receptor FXR/EcR [FXR/EcR also provides resistance (lfc = 2.9). Thus, part of the resistance from PEK and crc knockout might result from its connection to ecdysone signaling.The strongest candidate gene from the cell screen with improved survival under and ATF6 , did notand ATF6 . One hypAP/Diap1 . Similar FXR/EcR , and sig lfc = 0.. Interes FXR/EcR . KnockouPIG-A, Pfrx, and PEK, which may hint at the mechanisms through which these gene pathways lead to survival. It is possible that loss of a specific protein leads to both Tun resistance and cell surface glycoprotein rescue in these overlapping genes. For example, perturbing GPI anchor biosynthesis genes can improve cell survival, cell surface glycoproteins, and in vivo models of DPAGT1 inhibition, which could indicate that loss of a specific GPI-anchored protein improves these phenotypes. As a different example, loss of PEK also improves these metrics under DPAGT1 inhibition, which suggests the importance of ER stress and/or apoptosis to these phenotypes given the role of PEK noted above [The majority of genes for which knockout increased resistance to Tun did not overlap with hits from the cell surface glycoprotein ConA screen . This sued above . As all in vivo. We believe this is primarily driven by differences in the biology of single cells vs. whole, developing organisms, but it is also possible some opposite results are driven by false discovery. In CRISPR knockout screens, false discovery can be due to off-targeting, poor guide RNA efficiency, or incomplete knockout [Diap1 was a strong hit in our screen, yet loss of Diap1 alone is known to kill S2 cells [Diap1, and 6 of them were in enriched at LFC = 0.5 in the Tun-treated population. As each guide is unique, it is unlikely this is being driven by off-targets . One possibility is that, in rare circumstances, some cells have only single allelic knockout of Diap1, and that this heterozygosity may improve Tun survival.Not every gene from the cell screens validated knockout –79. We eknockout . Howeverknockout . For exaS2 cells , so thisDPAGT1 deficiency. For example, another enriched GO pathway from the ConA screen was "inositol metabolic process" (GO:0006020)  . Inositoynthesis . Activatte cycle ,83. PerhDPAGT1 and ER stress models, and this might be explained by the disease mechanism of each model. The DPAGT1 model ostensibly works by reducing the amount of functional DPAGT1 enzyme (similar to Tun treatment), and DPAGT1 enzymatic activity utilizes UDP-GlcNAc, which is a product of fructose-6-phosphate metabolism through the hexosamine pathway . A subline expressing SpCas9 and containing an attP integration site, S2R+/NPT005/MT-Cas9 (PT5/Cas9), was described previously [eviously ,85 and iTunicamycin  dissolved in DMSO was serially diluted 2-fold into growth media in 96-well plates. Then, cells were added such that each well contained 10,000 cells in 100 μL. Plates were incubated at 25°C for 4 days and then relative cell titers were determined using Cell Titer Glo (Promega) and a luminescence plate reader (SpectraMax) according to the manufacturer’s instructions.Drosophila CRISPR genome-wide knockout library was previously described and is available from Addgene (134582–4) [-expressing cell library was established, 1000 cells per sgRNA were subcultured in each passage to maintain the expected diversity of the sgRNA library. The cells were exposed to 590 nM tunicamycin  for 30 days, passaging the same number of cells (~8×107) to four new 15 cm dishes every 4 days. Following the final passage, aliquots of the cells were collected, and their genomic DNA was extracted using a Zymo Quick-gDNA Miniprep kit . DNA fragments containing the sgRNA sequences were amplified by PCR using at least 1000 genomes per sgRNA as template for each sample. The in-line barcoding strategy and sequences were as previously described [count subprogram, using standard parameters with 22 bp 5’ trimming and median-normalizing each sublibrary to 10,000 reads. The median log2 fold-change reported throughout was calculated from this data directly by measuring log2 of treated readcount divided by untreated readcount and then determining the median value among all sgRNAs targeting the same gene. For the volcano plot, the log2 fold-change and robust rank aggregation (RRA) p-value measures were determined using MAGeCK version 0.5.9.4 software, test subprogram, using standard parameters.The 34582–4) ,85. In bescribed , count sDrosophila genes), the cells were again subjected to treatment with tunicamycin (590 nM) in normal growth medium for 1 week. Next, 1×108 cells were placed into suspension in 10 mL and labeled live with 10 μg/mL Alexa Fluor 647 Conjugated Concanavalin A (Thermo # C21421) for at least 2 hours by diluting the stock 1:500 into full growth medium at room temperature with occasional inversion. 1 mL aliquots of labeled cells were transferred individually to 5 mL 40 μm filter-cap vials to mechanically declump the cells. Cells were then subjected to fluorescence-activated cell sorting (FACS) using a Sony MA900 FACS machine guided by gates established by tunicamycin-untreated cells stained in parallel and unstained cells. Approximately 1% of cells that exhibited the greatest intensity of staining in the AlexaFluor 647-A filter (corresponding to the average intensity of tunicamycin-untreated cells) were sorted into full growth media. Gating was reestablished after each 1 mL to account for increased uptake of the dye over the course of the experiment (~6 hours). Finally, collected cells were transferred to a 6-well dish well and gently spun down at 100 x g for 10 min and their genomic DNA was extracted using the Zymo Quick-gDNA Miniprep kit, then subjected to PCR and Illumina sequencing as described. Amplicon sequencing was carried out at the MGH DNA core. A readcount table was prepared from raw sequencing files using MAGeCK version 0.5.9.4, count subprogram, using standard parameters with 22 bp 5’ trimming. Readcounts were sorted to reveal genes in the top 1000 of all sgRNAs (minimum of 4 or more sgRNAs).After generating puromycin-resistant pools of cells expressing a genome-wide library CRISPR sgRNA library  and was characterized previously [GMR-GAL4 and G69DUAS-Rh1 on the second chromosome and has been previously described [All flies in this study were maintained at room temperature and fed a standard fly diet based on the Bloomington Drosophila Stock Center Standard Cornmeal Medium with malt and without soy flour (unless otherwise noted). Stocks obtained from the Bloomington Drosophila Stock Center and the Vienna Drosophila Resource Center  were useeviously . The "ERescribed –51.DPAGT1 model was generated as follows. The eya composite-GAL4 and UAS-Alg7 RNAi line (BDSC #53264) were crossed to create an eya composite-GAL4/UAS-Alg7 RNAi (III) line. This line was then crossed to a balancer +/TM3, Dfd-YFP, Sb (III) and progeny were examined for crossover events. Progeny with small, rough eyes and Sb were collected, maintained for stability of the phenotype, and referred to as the DPAGT1 model /TM3, Dfd-YFP, Sb).The 2 anesthesia, then placed on ice and transferred to -80°C for later imaging. Eyes were imaged at 3x magnification (Leica EC3 Camera). Eye area was determined as previously described [Dpm1, the BDSC 50713 RNAi line was lethal in the DPAGT1 model and its control  were collected under COescribed . All mea control , and stuTo make the glucose- and fructose-supplemented media, our standard media was melted in a microwave and maintained at 95°C on a stir plate. We used this melted media as-is for the control and added glucose or fructose to a final concentration of 100mM to a separate set of vials and stirred until it was fully dissolved to a total volume of ~8.5ml/vial. The sugar adds approximately 0.6 calories/tube . For the CDG gene overlap analysis, we used the DIOPT ortholog finder (https://www.flyrnai.org/cgi-bin/DRSC_orthologs.pl) [Genetic overlap representation factors and probability statistics were calculated via "Nematode bioinformatics" (logs.pl)  and analDrosophila genes, and using the default parameters  [H. sapiens (via http://www.pantherdb.org/).Gene Ontology (GO) analysis was performed with the PANTHER Overrepresentation test using the "GO biological process complete" data set, compared to all ry Rate) ,91. We aEye size comparisons were analyzed using the Student’s t test. When comparing groups of RNAi lines to a single control, Bonferroni multiple testing correction was used. Venn diagram and graphs of eye size comparisons were made using the statistical software R .S1 FigDPAGT1 and ER stress models are shown here. This also includes representative images from the RNAi line-specific controls for each cross. RNAi lines used, including specific stock numbers, are included to the left of each image set. Quantification of these eye crosses are included in Representative images from two replicates of RNAi line crosses to both the (TIF)Click here for additional data file.S2 Figeya composite-GAL4 and GMR-GAL4 control lines are shown here. This also includes representative images from the RNAi line-specific controls for each cross. RNAi lines used, including specific stock numbers, are included to the left of each image set.Representative images from two replicates of RNAi line crosses to both the (TIF)Click here for additional data file.S3 FigDPAGT1 and ER stress models are shown here. This also includes representative images from the RNAi line-specific controls for each cross. RNAi lines used, including specific stock numbers, are included to the left of each image set. Quantification of these eye crosses is included in Representative images from two replicates of RNAi line crosses to both the (TIF)Click here for additional data file.S4 Figeya composite-GAL4 and GMR-GAL4 control lines are shown here. This also includes representative images from the RNAi line-specific controls for each cross. RNAi lines used, including specific stock numbers, are included to the left of each image set.Representative images from two replicates of RNAi line crosses to both the (TIF)Click here for additional data file.S5 FigFly gene names are listed, as these genes are derived from the S2 CRISPR knockout guide RNA library. All resistance and sensitivity metrics are based on lfc values from the survival screen.(PDF)Click here for additional data file.S1 TableThe first tab includes the raw sgRNA enrichment scores (tunicamycin-vs-untreated) 4–8, as well as the median values of those sgRNAs used in subsequent analyses. The second tab includes the adjusted lfc values and p-values used to create the volcano plot in (XLSX)Click here for additional data file.S2 TableThe first tab includes the full list of human CDGs derived from The Essentials of Glycobiology and Invitae panel, the derived fly orthologs via their DIOPT score, a finalized list removing duplicate orthologs alongside their lfc value from the survival screen, and finally the overrepresentation test analysis performed. The second tab includes human CDGs for which no fly ortholog was found at a DIOPT score of <5.(XLSX)Click here for additional data file.S3 TableThis includes the output of the PANTHER gene list analysis from the combined input of resistance and sensitivity candidate genes at an lfc of ≥0.5 or ≤-0.5 from the survival screen in (XLSX)Click here for additional data file.S4 TableThe first tab includes only genes that had at least one sgRNA in the highest ~1% of fluorescence of all sgRNAs in two biological replicates. This includes information on specific guides, and the final list of genes found (FBgn number and Fly gene name). The second tab is the raw data from the ConA experiment, including information on specific guide RNAs and their abundance in either replicate.(XLSX)Click here for additional data file.S5 TableThis includes the output of the PANTHER gene list analysis from the input of candidate genes that improved ConA phenotypes in (XLSX)Click here for additional data file.S6 TableThis includes the list of resistance candidate genes from the survival screen , all hit(XLSX)Click here for additional data file.S7 TableDPAGT1 and ER stress model are listed here. This table includes information on the Drosophila gene (name and FBgn number), closest human ortholog, the reasoning on why the gene was tested , if the gene was a hit in one or both screens, the specific RNAi stock used in each cross, as well as the related pathway function. % change in eye size, confidence interval (derived from the standard deviation of change and listed N), as well as the Student’s t test p-value are indicated for each replicate.Quantitative results of all RNAi cross replicates to both the (XLSX)Click here for additional data file.S8 Tableeya composite-GAL4 and GMR-GAL4 control lines and DPAGT1 and ER stress models. % change in eye size, confidence interval (derived from the standard deviation of change and listed N), as well as the Student’s t test p-value are indicated for each replicate.This lists the data on two replicates of the sugar feeding experiments on the (XLSX)Click here for additional data file.


Hepatic cysts are benign liver lesions and are often asymptomatic. Large hepatic cysts may cause jaundice and portal hypertension; however, they rarely cause gastrointestinal obstruction. Symptomatic cysts require treatment, and when malignancy is suspected, cyst puncture for pathological examination of the fluid may pose a risk of dissemination. Herein, we describe a case of xanthogranuloma arising from a large hepatic cyst that was causing duodenal obstruction. Thus, cyst puncture was performed for emergency decompression. Cytological examination of the puncture fluid revealed no malignant findings. Hence, laparoscopic deroofing was performed to treat the hepatic cyst. As the cyst and duodenal wall were firmly adherent, the cyst wall was left behind without dissection from the duodenum. A two-stage approach of cyst puncture followed by surgery may be an option for patients requiring urgent treatment for potentially malignant hepatic cysts. Hepatic cysts are mostly benign, asymptomatic, incidentally diagnosed, and do not require intervention. Treatment is indicated when they become symptomatic, cause complications or demonstrate rapid growth , 2. SeveA 75-year-old bedridden woman presented to our hospital with chief complaints of epigastric pain, anorexia and a palpable mass in the epigastric region. She had a history of surgery for meningioma, but no history of abdominal surgery. Ultrasonography revealed a well-defined large cystic lesion with a long diameter of approximately 150 mm in the left liver lobe. Contrast-enhanced computed tomography showed a giant hepatic cyst with an irregular mass in liver segment 4, 20 × 16 cm in size .The hepatic cyst compressed the stomach, duodenum, pancreas and gallbladder, and the descending part of the duodenum was difficult to identify because of severe thinning caused by the compression. On magnetic resonance imaging, the giant cyst showed low signal intensity on T1-weighted and high signal intensity on T2-weighted images, and there was a solid component with a high signal on diffusion-weighted images on the dorsal side of the cyst .Upper gastrointestinal endoscopy showed severe duodenal stenosis due to compression from outside of the wall, which was the cause of gastric pain and anorexia .The differential diagnosis included a simple liver cyst, hepatic mucinous cystic tumor and hepatic xanthogranuloma. Although we could not rule out malignancy of the intracystic tumor, we considered that hepatic resection would be too invasive for the patient. Therefore, we planned to perform laparoscopic cyst drainage to prevent dissemination and, subsequently, hepatic resection or laparoscopic deroofing depending on the puncture fluid cytology findings.However, during hospitalization, the patient developed dehydration, acute renal failure, electrolyte imbalance and impaired consciousness. C-reactive protein level was elevated (9.61 mg/dL), indicating intracystic infection. As emergency treatment, percutaneous puncture drainage of the cyst was performed to decompress the stomach and duodenum .A total of 1400 mL of purulent fluid was drained, and cytology of the drainage fluid showed no malignant findings. The gastrointestinal obstruction symptoms improved, enabling oral food intake; thus, we decided to perform laparoscopic deroofing of the hepatic cyst.We used three ports  was under 40 (36.8), suggesting that hepatectomy would potentially be too invasive for the patient . To reduIn the deroofing procedure, the cyst was opened into the peritoneal cavity, and a portion of the wall was excised flush with the adjacent liver parenchyma. However, the cyst wall tightly adhered to the duodenum. As dissection of structures tightly adherent to the duodenum was a risk factor for secondary organ injury in cases of gallbladder-duodenal fistulas , we diviIn conclusion, a two-stage approach of cyst puncture followed by surgery may be an option for patients requiring urgent treatment for potentially malignant hepatic cysts.


The hallmark of hyperparathyroidism is hypersecretion of parathyroid hormone (PTH) which results in hypercalcemia and hypophosphatemia. While hypercalcemia due to malignancy is often brought about by PTH-related protein in adults, PTH-producing tumors are quite rare in clinical practice. Additionally, from the point of embryology, it is very difficult to examine ectopic PTH-producing tissue such as ectopic parathyroid glands. Furthermore, clear histopathological criteria are not present.A 57-year-old woman was referred to our hospital for hypercalcemia. Her parathyroid hormone (PTH) level was elevated, but there were no enlarged parathyroid glands. Although 99mTc-MIBI confirmed a localized and slightly hyperfunctioning parathyroid tissue in the anterior mediastinum, it was not typical as hyperfunctioning parathyroid. We finally diagnosed her as ectopic PTH-producing cyst-like tumor with venous sampling of PTH. She underwent anterosuperior mediastinal ectopic PTH-producing cyst-like tumor resection. It is noted that intact-PTH concentration of the fluid in the cyst was very high . Based on histopathological findings, we finally diagnosed her as ectopic PTH-producing parathyroid cyst inside the thymus. After resection of anterosuperior mediastinal thymus including ectopic PTH-producing parathyroid cyst, calcium and intact-PTH levels were decreased, and this patient was discharged without any sequelae.We should know the possibility of superior mediastinal ectopic PTH-producing parathyroid cyst inside the thymus among subjects with ectopic PTH-producing parathyroid glands. Particularly when the cyst is present in the superior mediastinum, it is necessary to do careful diagnosis based on not only positive but also negative findings in 99mTc-MIBI. It is noted that the patient’s bloody fluid in the cyst contained 19,960,000 pg/mL of intact-PTH, and its overflow into blood stream resulted in hyperparathyroidism and hypercalcemia. Moreover, in such cases, the diagnosis is usually confirmed after through histological examination of ectopic PTH-producing parathyroid glands. We think that it is very meaningful to let clinicians know this case.The online version contains supplementary material available at 10.1186/s12902-022-01256-4. Hallmark of hyperparathyroidism is hypersecretion of parathyroid hormone (PTH) which results in hypercalcemia and hypophosphatemia , 2. PTH Here, we report a case of ectopic PTH-producing parathyroid cyst inside the thymus. It is noted that the patient’s bloody fluid in the cyst contained 19,960,000 pg/mL of intact-PTH, and its overflow into blood stream resulted in hyperparathyroidism and hypercalcemia. We think that it is very meaningful to let clinicians know this case.4 /μL; hemoglobin, 15.4 g/dL; platelet, 17.8 × 104 /μL. Liver function was within normal range, but she had slight renal dysfunction (creatinine (CRE), 0.89 mg/dL; blood urea nitrogen (BUN) 15 mg/dL, aspartate aminotransferase (AST), 22 U/L; alanine transaminase (ALT), 12 U/L; alkaline phosphatase (ALP), 79 U/L; γ-glutamyl transpeptidase (γ-GTP), 25 U/L; lactate dehydrogenase (LDH), 178 U/L). Her electrolyte data showed elevated calcium and decreased phosphates as follows: sodium, 140 mmol/L; potassium 3.5 mmol/L; chloride 103 mmol/L; inorganic phosphorus 2.0 mg/dL; calcium 14.7 mg/dL; magnesium 1.8 mg/dL. In addition, she had elevated PTH level: intact-PTH, 547 pg/mL; PTHrP, < 1.0 pmol/L; 1.25(OH)2 vitamin D, 71.9 pg/mL; 25-dihydroxy vitamin D, 10.2 ng/mL.A 57-year-old woman was referred to our hospital for recent diagnosis of hypercalcemia. Her history included hypertension at age 56 and she was taking no medication. She had no family history. On physical examination, she had symptoms of appetite loss and 4 kg of decreased body weight for a few months. Her height and body weight were 158.9 cm and 48.5 kg. Her vital signs were: temperature, 36.5 °C; blood pressure, 110/72 mmHg; heart rate, 110 beats/min; oxygen saturation, 98% (room air). Laboratory data were as follows: white blood cell count, 5620 /μL (neutrophil 74.1%); red blood cell count, 504 × 10Ultrasound examination of the parathyroid did not detect enlarged parathyroid gland Fig. A. We perShe underwent anterosuperior mediastinal ectopic PTH-producing cyst-like tumor resection . It is noted that intact-PTH concentration in the fluid in the cyst was very high  Fig. A. As shoHere, we report a case with elevation of serum PTH concentration, but not PTHrP, resulting in hypercalcemia and hyperparathyroidism, which was caused by ectopic PTH-producing parathyroid cyst inside the thymus. It is very difficult to examine ectopic PTH-producing tissue, and there are no clear histopathological criteria. Therefore, understanding the normal process of parathyroid development might provide useful information about how and why ectopic parathyroid adenomas and/or cysts are formed. Generally, the parathyroid glands develop in tandem with the thymus in the third pharyngeal pouch and with the ultimobranchial bodies in the fourth pharyngeal pouch. After then, the combined parathyroid-thymus primordial migrates posteriorly and/or ventrally and separates from each other. After the separation, the parathyroids finish migrating and form two sets of bilateral parathyroid glands, while the thymic lobes migrate to the anterior mediastinum –9. ThereWhen we examine patients with hyperparathyroidism, most cases are primary hyperparathyroidism, which is currently the most common cause of hypercalcemia. Therefore, we usually perform imaging examinations, such as ultrasonography, CT, or MRI of the neck. In imaging tests, approximately 95% of primary hyperparathyroidism is observed as a simple sporadic parathyroid gland . UltrasoEctopic parathyroid glands are any parathyroid glands which are not just around the thyroid gland and account for only 15% of all parathyroid adenomas. Moreover, a few percentages of them are present in mediastinal or substernal region, and about 80% of mediastinal cases of ectopic parathyroid glands are around the thymus . In subjClear criteria to diagnose ectopic parathyroid adenoma or cyst are not present. Parathyroid cysts, which account for less than 1% of cystic neck mass , are alsIn our case, we performed various imaging examinations for hypercalcemia and hyperparathyroidism. First, the lesion was not detected as a simple sporadic parathyroid gland in ultrasonography and CT of the neck, although a cystic mass with a uniform low absorptive area was detected and peripheral contrast effects were observed in CT and enhanced CT. Therefore, we started screening ectopic parathyroid glands and suspected with ectopic superior mediastinal parathyroid cyst. 99mTc-MIBI confirmed a localized and slightly hyperfunctioning parathyroid tissue in the superior mediastinum only in an early phase which is not typical, although 99mTc-MIBI is often useful for functional ectopic parathyroid glands. MRI showed high signal on T1-weighted images, and we diagnosed fluid cyst in enhanced CT and MRI. We had a little evidence to make a clear diagnosis for ectopic functional parathyroid cyst. Somatostatin receptor scintigraphy was negative and the location of superior mediastinal cyst was difficult in FNA. Since 90% of parathyroid cysts are non-functioning and 99mTc-MIBI was not typical as hyperfunctioning parathyroid in this case, we could not deny that this fluid cyst did not contain PTH. Therefore, we performed venous sampling of PTH and found that superior mediastinal cyst was functional PTH-producing cyst. Since the patient’s serum calcium and intact-PTH level decreased to within the normal range after removal of the thymus including ectopic parathyroid cyst, suggesting that diagnosis was appropriately performed.Since pathohistological diagnosis of ectopic PTH-producing tumors is very difficult, there are few cases in which the presence of PTH secretion from thymoma is shown . ClassifIn this case, intact-PTH concentration of the fluid inside the cyst was very high , which led to hyperparathyroidism and hypercalcemia. Most important point in this case was histopathological diagnosis of PTH-producing cell. Immunohistochemical staining of this tissue was not positive for cytokeratin AE1/AE3 and MIC-2, which indicated that this tumor was not thymoma and there was no evidence of malignancy. In addition, the formation of cavity of cyst was surrounded by parathyroid cell which was inside the thymus and fatty tissue clearly showed that this tumor was superior mediastinal ectopic PTH-producing parathyroid cyst inside the thymus. In this case, the patient suffered from hyperparathyroidism and hypercalcemia in adulthood. These results suggest that stored PTH in the cyst overflew into blood stream, leading to hyperparathyroidism and hypercalcemia.We should bear in mind the possibility of superior mediastinal ectopic PTH-producing parathyroid cyst inside the thymus among subjects with ectopic PTH-producing parathyroid glands. Particularly when the cyst is present in the superior mediastinum, it is necessary to do carefully diagnosis based on not only positive but also negative findings in 99mTc-MIBI. Moreover, in such cases, the diagnosis is usually confirmed after through histological examination of ectopic PTH-producing parathyroid glands.Additional file 1: Supplementary Fig. 1. Venous sampling of PTH. Intact-PTH levels showed a step up in the territory of the central left branchiocephalic vein compared with both right and left subclavian vein and right atrium , corresponding to the anatomic localization of the cystic-like tumor in previous imaging studies.