Being the standard-of-care for four decades, cisplatin-based chemotherapy is highly efficient in treating germ cell tumors (GCT). However, often refractory patients present with a remaining (resistant) yolk-sac tumor (YST(-R)) component, resulting in poor prognosis due to lack of novel treatment options besides chemotherapy and surgery. The aim of this study was to identify novel targets for the treatment of YST by deciphering the molecular mechanisms of therapy resistance. Additionally, we screened the cytotoxic efficacy of a novel antibody-drug-conjugate targeting CLDN6 (CLDN6-ADC), as well as pharmacological inhibitors to target specifically YST.Protein and mRNA levels of putative targets were measured by flow cytometry, immunohistochemical stainings, mass spectrometry of formalin-fixed paraffin-embedded tissues, phospho-kinase arrays, or qRT-PCR. Cell viability, apoptosis and cell cycle assays of GCT and non-cancerous cells were performed using XTT cell viability assays or Annexin V / propidium iodide flow cytometry, respectively. Druggable genomic alterations of YST(-R) tissues were identified by the TrueSight Oncology 500 assay.+ GCT cells in comparison with non-cancerous controls. In a cell line-dependent manner, either an accumulation in the G2 / M cell cycle phase or a mitotic catastrophe was observed. Based on mutational and proteome profiling, this study identified drugs targeting the FGF, VGF, PDGF, mTOR, CHEK1, AURKA, or PARP signaling pathways as promising approaches to target YST. Further, we identified factors relevant for MAPK signaling, translational initiation and RNA binding, extracellular matrix-related processes as well as oxidative stress and immune response to be involved in therapy resistance.We demonstrated that treatment with a CLDN6-ADC enhanced apoptosis induction specifically in CLDN6In summary, this study offers a novel CLDN6-ADC to target GCT. Additionally, this study presents novel pharmacological inhibitors blocking FGF, VGF, PDGF, mTOR, CHEK1, AURKA, or PARP signaling for the treatment of (refractory) YST patients. Finally, this study shed light on the mechanisms of therapy resistance in YST.The online version contains supplementary material available at 10.1186/s10020-023-00636-3. Germ cell tumors (GCT) are the most common solid tumors among young men aged between 17 and 45 years  expression profiles , high MDM2 levels, and phosphorylation-dependent translocation of p21 from the nucleus to the cytoplasm  YST to further increase therapy efficacy.The tetraspanin membrane protein CLDN6 has been identified as a cancer-associated cell surface biomarker, which is rarely expressed in healthy adult tissues   against CLDN6 to examine the cytotoxicity and specificity to target GCT.Beyond that, since specifically YST cells represent the remaining non-responsive component in refractory GCT, we further aimed at deciphering the molecular mechanisms resulting in the formation of cisplatin-resistant YST. This approach was chosen for the identification of putative multikinase inhibitor-based therapeutic options, which are already in clinical trials and / or approved for the treatment of other tumor entities.FOXA2, SOX17, APOA1 / A2 / B, ALB, FGA / B / G, and GATA3 / 4 / 6 . Additionally, we found similarities in signaling pathway activities when comparing YST and HCC   regarding expression of endodermal factors like https://imagej.nih.gov/ij/)  cell lines were cultured as described previously and summarized in Additional file 2B antibody  has been conjugated to MMAE via the drug-linker OSu-Glu-vc-PAB (CLDN6-Glu-vc-PAB-MMAE) by Levena Biopharma , resulting in an antibody-drug-ratio of at least 1 : 3.Anti-human CLDN6 monoclonal mouse IgGDNA and RNA were extracted from tumor enriched 2 × 5 µm formalin-fixed, paraffin-embedded (FFPE) slices using the ˋInnuPREP FFPE DNA Kit´ on the ˋInnuPure C16 System´  or the ˋMaxwell RNA extraction kit´  according to manufacturer’s recommendations, respectively.DNA libraries were prepared using the hybrid capture-based ˋTruSight Oncology 500 Library Preparation Kit´  following ˋIllumina’s TruSight Oncology 500 Reference Guide´  and sequenced on an ˋIllumina NextSeq 500´ instrument. FastQ files were analyzed using ‘CLC Genomics Workbench’ . The reads were mapped on hg19 followed by an initial variant calling.For sample preparation, a modified FFPE tissue lysis protocol of Ikeda et al. was applied   for principal component analyses (PCA) (Gerst and Hölzer https://david.ncifcrf.gov)    was used to generate dot plots  has been used to screen for the absorption, distribution, metabolism, excretion and toxicity features of tested drugs  GCT cohort was analyzed using cBioportal  derived from SEM (TCam-2), EC , CC , and an EC-YST-intermediate (1411H) , which were comparable to those of non-cancerous control cells   and induced apoptosis in most CLDN6+ GCT(-R) cells  in comparison to the monoclonal antibody alone  , 2102EP, NCCIT(-R), JAR, JEG-3(-R), 1411H), but not in CLDN6− cells , BRCA2 (c.7397T > C), IL7R , and SPTA1 (c.5077A > C) were observed in all YST-R samples. Furthermore, CHEK1, FGF6, FGF23, and KRAS were amplified, but with a low fold change (max 2.2), and SNVs were detected in FGFR4 (c.1162G > A), KMT2A (c.10841T > C), NTRK1 , and TSC2  in at least 50 % of the evaluated samples  tissues n = 6) were performed to identify druggable genomic alterations. We detected a mean of 3.2 mut / Mb (0.8 - 5.6 mut / Mb) in the YST-R samples, though, the tumor mutational burden (TMB) did not correlate to the microsatellite instability score ) , 1411H) has been performed to identify signaling molecules and putative YST-specific targets, which were not present in non-cancerous control cells (MPAF)  were noted in ABL1, FGFR1 / 4, FLT4, MTOR, PARP, PDK1, RET, while CSK, EGFR, ERBB2, and RAF1 harbored missense mutations , Nintedanib FGFR1 - 3), AZD7762, MK-8776 (both CHEK1), and Rapamycin (mTOR) as potential inhibitory drugs to target YST(-R) , Nintedanib , Sorafenib , Talazoparib (PARP1 / 2), OSU-03012 (PDK1), AZD4547 (FGFR1 - 3), AZD7762 (CHEK1), or Rapamycin (mTOR) resulted in LDOf the four tested YST-like cell lines, the GCT72 and 1411H showed the highest apoptosis induction under most conditions, while the female NOY-1(-R) were the least sensitive YST-like cells Fig. E. Induct2 = 0.95)  and p53 S15, S46) were seen in GCT72-R cells, while activity of ERK1 / 2 , FGR (Y412), GSK3α / β (S21 / S9), p38α (T180 / Y182), p53 (S392), PDGFRβ (Y751), SRC (Y419), STAT5a / b (Y694 / Y699), WNK1 (T60), and YES (Y426) was reduced in the resistant subline  cells  inhibitors or an ADC targeting CLDN6.Additional file 1: Figure S1. A) Mutational status and mRNA expression profile of CLDN6 in the GCT TCGA (The Cancer Genome Atlas) cohort as analyzed through https://www.cbioportal.org/. B) XTT cell viability assays of CLDN6 antibody, CLDN6-ADC, or MMAE treated GCT cell lines and non-cancerous fibroblasts (MPAF) (24  - 96 h). C) Raw flow cytometry data indicating cell cycle distributions of GCT cell lines and MPAF treated with either CLDN6 antibody alone (red), CLDN6-ADC (green), or MMAE (blue) in comparison with untreated controls (grey). D) Immunohistochemical evaluation of CLDN6 in YST-R tissues (n = 10).Additional file 2: Figure S2. A) Raw human phospho-kinase array of various cell lysates . Corresponding membrane layout with the most prominent dots (marked in red) was used for quantification using ImageJ as shown in Fig. ACTB and GAPDH were used as housekeeping genes. C) Raw data and D) densitometric evaluation of GCT72(-R) cells treated with AZD7762, Danusertib, Nintedanib, OSU-03012, or SNS-314  in comparison to the solvent control (DMSO).Additional file 3: Figure S3. A, B) Mutational status (A) and mRNA expression profiles (B) of potential targets to treat YST as found in the TCGA GCT cohort.Additional file 4: Figure S4. A) XTT cell viability assays of GCT72 cells treated with indicated drugs for 24 - 96 h. B) XTT cell viability assays of GCT cell lines GCT72(-R), NOY-1(-R), 1411H, and non-cancerous fibroblasts (MPAF) treated with indicated drugs for 24 - 96 h. C) Raw flow cytometry data of cell cycle distributions of GCT cell lines and MPAF treated with indicated drugs in comparison with solvent controls.Additional file 5: Table S1. List of used A) cell lines, B) inhibitors, C), oligonucleotides, and D) antibodies.Additional file 6: Data S1. Raw and processed mass spectrometry data of YST(-R) tissues and TSO assay data.Additional file 7: Data S2. Structures and ADMET  prediction of AZD4647, AZD7762, Danusertib, Nintedanib, OSU-03012, SNS-314, Sorafenib and Talazoparib as analyzed by the `ADMETlab 2.0’ web platform (https://admet.scbdd.com/).


Following the publication of this article , concernLanes 1–4 of the Fig 3B HMGB1 panel appear similar to the Fig 4A HMGB1 panel (left) when rotated 180°The Fig 4A HMGB1 panel (right) appears similar to the Fig 4A Tubulin panel (right) when rotated 180°The Fig 3B and Fig 4A western blot results report Tubulin controls, but the article’s methodology section reports β-actin primers and antibodies instead.○ M6 , M6/mock , and M6/Mock ○ M6/S2  and M3 The following panels appear to partially overlap despite being used to represent different experimental conditions:In addition to these concerns, it has come to the journal’s attention that several cell lines reported in this study have been reported to be misclassified or contaminated. Specifically,The HepG2 cell line reported in this study as a human hepatocellular carcinoma cell line has been misclassified, and should be reported as a hepatoblastoma cell line instead [The BEL-7404 cell line reported in this study as a human hepatocellular carcinoma cell line is a contaminated cell line, and has since the publication of this study been shown to be a HeLa derivative cell line instead .The L02 cell line reported in this study as a normal (non-cancerous) hepatocyte line is a contaminated cell line, and has since the publication of this study been shown to be a HeLa derivative cell line instead .The first author commented that the image overlap was the result of errors during figure preparation and provided underlying data and updated figures. Furthermore, the first author stated that they omitted to include the use of tubulin in the methodology section, but this did not clarify why the study’s methodology reports on the use of β-actin instead, when no β-actin results have been presented in this study. In response to the contaminated cell line concerns, the first author states that the BEL-7404 and L02 cell lines were sent to a company for identification, but they did not provide further specification regarding the company or the identification procedure, and they did not provide evidence to confirm the cell lines used were not contaminated.The first author provided underlying image data for the results presented in Figs 3, 4, 6, and 7, but the individual level data underlying the results in these figures were not provided for editorial review.PLOS ONE Editors retract this article.In light of the concerns affecting multiple figure panels that question the reliability of these image data, as well as the concerns pertaining to the contamination of cell lines including the control cell line that questions the reliability of the overall results, the JX did not agree with the retraction. YD, JH, QL, YL, WN, YZhang, YZhu, LC, and BC either did not respond directly or could not be reached.


Canine pulmonary adenocarcinoma (PAC) resembles human lung tumors in never-smokers, but it is rarer than human pulmonary adenocarcinoma. Therefore, research on canine PAC is challenging. In the present study, we successfully established various novel canine PAC cell lines from a single lesion in a dog, including two parent cell lines and fourteen cloned cell lines, and characterized their cellular properties in vitro. Several of these cell lines showed epithelial–mesenchymal transition (EMT)-like and/or cancer stem cell (CSCs)-like phenotypes. We additionally assessed the sensitivity of the cells to vinorelbine in vitro. Three clonal lines, two of which showed EMT- and CSC-like phenotypes, were resistant to vinorelbine. Furthermore, we evaluated the expression and activation status of EGFR, HER2, and Ras signaling factors. The findings indicated that the cell lines we established preserved the expression and activation of these factors to varying extents. These novel canine PAC cell lines can be utilized in future research for understanding the pathogenesis and development of treatments for canine PAC. Canine pulmonary adenocarcinoma (PAC) is the most frequently encountered tumor (87.1%), followed by sarcoma (7.6%), adenoma (3.2%), and pulmonary neuroendocrine tumor (1.5%) in dogs with primary pulmonary mass4. Locoregional tumors spread to other lung areas or lymph nodes, and distant metastasis via hematogenous and lymphatic routes are common in canine lung tumors. Metastasis is a crucial prognostic factor. In one study, the rates of local vascular or lymphatic invasion and distant metastases were 71% and 23%, respectively5. Surgical resection is the first choice of treatment, and patients without metastasis appear to have a favorable prognosis. However, the prognosis for advanced disease is very poor, and the median survival time has been reported to be less than 1 year6. In humans, cisplatin-based chemotherapy combined with surgery is available and effective in patients with non-small-cell lung cancer7. However, the efficacy of chemotherapy in dogs with lung tumors remains unclear. In a previous study, two of seven canine PAC cases partially responded to vinorelbine, a vinca alkaloid with high transferability to the lung tissue8. Toceranib, a multi-target tyrosine kinase inhibitor, has been reported to be partially effective in some canine PAC cases10. However, reliable clinical trials with larger sample sizes are lacking because cases of naturally developed PAC are rare. Moreover, only a few types of canine PAC cell lines are currently available13, and their cellular characteristics have not been clearly described. Therefore, a novel experimental model is required for further research on canine PAC.Canine primary lung tumors share clinicopathologic features with human lung tumors in never-smokers but is rare compared with that in humans15. Once EMT occurs, tumor cells migrate from the primary lesion to release circulating tumor cells into the bloodstream. Subsequently, mesenchymal–epithelial transition occurs, followed by metastasis. In human breast and pancreatic cancer models, EMT has been reported to be indispensable for lung metastasis, and it contributes to chemoresistance17. Other reports have also described the contribution of EMT to chemoresistance in human oncology18. Although the role of EMT in metastasis is still under discussion, the importance of EMT in cancer therapy in dogs has been described in a previous review19.Epithelial–mesenchymal transition (EMT) is a key event in tumor progression and metastasis. During EMT, tumor cells acquire mesenchymal phenotypes, including fibroblast-like morphology, high motility, and vimentin expression, resulting from the downregulation of epithelial hallmarks, including adhesion properties and E-cadherin expression20. CSCs are small subsets with extensive self-renewing properties that drive tumorigenesis in tumor tissues, and they are crucial factors in tumor metastasis, recurrence, and chemoresistance22. CSCs have mesenchymal properties and invasive features, the hallmarks of EMT. CSCs can be detected using various techniques, including surface antigen analysis such as CD133 analysis, colony- or sphere-formation assays, aldehyde assays, and side population (SP) assays with Hoechst 3334223 or Vybrant DyeCycle Violet (DCV)24. CSCs have been detected in various types of human tumors24. In canine tumors, CSCs have been detected in mammary carcinoma26, osteosarcoma27, and PAC11.The relationship between EMT and cancer stem cells (CSCs), which are tumor-initiating cells, has been investigated28. The epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor 2 (HER2), the preferred heterodimer partner of EGFR, are cell surface receptor tyrosine kinases (RTK), and their activation promotes tumor cell proliferation. Their activating mutation and overexpression have been observed in various types of tumors, including human lung cancer30. In canine PAC, the activation of EGFR and HER2 has been reported in tumor tissue33. The small G protein, Ras, is an oncogenic factor. Its activating mutation has been detected in various types of tumors, including human and canine PAC35. Prenylated Ras translocates from the cytoplasm to the membrane, and it is activated by RTK, such as EGFR. Subsequently, activated Ras stimulates the downstream mitogen-activated protein kinase (MAPK) and phosphoinositide-3 kinase (PI3K) pathways, which promote cell proliferation. These factors are recognized as potent therapeutic targets in malignant tumors, including PAC36; however, they have not been sufficiently investigated in canine PAC.In humans, personalized treatment for PAC is based on the molecular subtypes of oncogene mutations and activation of tumor-associated proteinsIn the present study, we established two types of canine PAC cell lines under different culture conditions from a dog with naturally occurring PAC. Fourteen cloned cell lines with various morphological characteristics were established by single-cell cloning. We assessed their proliferative capacities in vitro and their characteristics, focusing on the EMT and CSC phenotypes. Additionally, sensitivity to vinorelbine in vitro was assessed. Finally, we evaluated the expression of several tumor-associated proteins.We initiated two primary cultures from canine PAC tissue under different culture conditions, and named them CPACd-p and CPACr-p cell lines. They were cultured in complete media based on Dulbecco’s modified Eagle’s medium (DMEM) and Roswell Park Memorial Institute (RPMI) 1640 medium, respectively, and were successfully purified and propagated for more than 50 passages.Next, we cloned CPACd-p and CPACr-p using a limiting-dilution method. Fifty-three and thirty-four clones were successfully obtained from the CPACd-p and CPACr-p cells, respectively. Seven clones were selected from each of these groups according to their morphology and subculture intervals. The other clones which were not selected had similar characters to the selected clones. Only the 14 clones that were realistic in terms of number of analyses were used in subsequent experiments. The selected cloned cells were propagated for more than 30 passages .Images obtained under a light microscope are shown in Fig. Additionally, we measured the doubling time of each cell line Table . No signP = 0.00074; Fig. P = 0.0022; Fig. Since some cell lines showed a mesenchymal-like morphology, we hypothesized that EMT occurred in these cell lines. First, we assessed the expression of the epithelial and mesenchymal markers, E-cadherin and vimentin, respectively, in the tumor tissue and in each cell line Fig. A. E-cadhP = 0.0071; Fig. To assess the CSC phenotype, we first evaluated the sphere-forming abilities of the cell lines Fig. A,B. CPACP = 0.0099). CPACd-AB4, CPACd-AC12, CG11, and all cloned cell lines from CPACr-p, except for CPACr-DC3, were less sensitive to vinorelbine than their parent cell lines. In contrast, CPACd-AE3 and CPACd-BB4 were more sensitive than the parent cell line CPACd-p. The IC50 values of vinorelbine in CPACd-AB4, CPACd-AC12, and CPACd-CG11 were higher than 10 µM, suggesting that these cell lines were resistant to vinorelbine treatment. In contrast, CPACd-BB4, CPACr-p, and CPACr-DC3 were relatively sensitive , characterized by cells displaying both mesenchymal and epithelial characteristics, is recognized as a part of the EMT process38. Therefore, it is plausible that partial, rather than complete, EMT has occurred in CPACd-AB4 and CPACd-CG11. Partial EMT is believed to be regulated by tumor microenvironmental factors39 and can enhance invasive properties, generate circulating tumor cells and cancer stem cells, and confer chemoresistance40. In human PAC cells, the GRHL2 gene has been implicated in the maintenance of stable partial EMT41, although the detailed mechanisms remain incompletely understood. The cell lines we have established exhibit stable partial EMT, suggesting the potential for elucidating the mechanisms responsible for stabilizing partial EMT and developing therapeutics targeting partial EMT.EMT is associated with malignancy and is considered a crucial therapeutic target22. In the present study, we assessed CSC properties using two different methods: sphere-formation and SP assays with DCV. CPACd-AB4, CPACd-CG11, and CPACr-AD4 showed relatively high sphere-forming ability and SP population; however, in CPACd-AE3, CPACd-DC10, CPACr-AH4, and CPACr-BH12, the results of the two assays were not concordant. Assessing CSC-associated antigens is widely used for detecting CSCs. In human oncology, several antigens are used as CSC markers, including CD44, CD133, CD24, and EpCAM; however, the expression patterns appear to vary with respect to tumor origin22. Although CD44 and CD133 expression have been previously assessed in a xenograft model of canine PAC, their utility as CSC markers has not been indicated42. In human PAC, these two antigens have been reported to have poor diagnostic value in CSC detection43. Reliable markers for the detection of CSCs may be determined by further assessment using developed canine PAC cell lines.CSCs are a subset of tumor cells characterized by self-renewal, differentiation capacity, and chemoresistance. These properties make CSCs crucial targets for tumor therapy20. In our study, CPACd-AB4 and CPACd-CG11 showed both EMT and CSC phenotypes. Several transcription factors are associated with the development of EMT and maintenance of CSCs. Transforming growth factor-β (TGF-β) has pleiotropic functions in tumor progression44. In epithelial cells, TGF-β acts as a tumor suppressor by inhibiting cell growth and inducing apoptosis. In contrast, in the advanced stages of tumorigenesis, TGF-β induces EMT and stimulates cell proliferation and survival in tumor cells45. TGF-β overexpression has been reported to be associated with malignancy in human tumors46. In human liver tumor cells, autocrine stimulation of TGF-β was reported to induce EMT47. Importantly, EMT stimulated by TGF-β induces the selection and expansion of CSCs49. Moreover, previous reports have indicated that MAPK and PI3K signaling play important roles in EMT or the maintenance of CSCs by EMT53. In our study, relatively high phosphorylation of Erk1/2 and expression of vimentin were observed in CPACr-AH4 and CPACr-DC3. However, Erk1/2 phosphorylation did not appear to correlate with cellular motility. CPACd-AB4 induced phosphorylation of Akt at a relatively high level; however, the other cell lines with CSC phenotypes did not show high phosphorylation of Akt. Further assessment of other signals, including the TGF-β signal, is needed to reveal the detailed mechanism of EMT and CSCs in the canine PAC. On the other hand, Andriani et al. demonstrated that the differences in susceptibility to CSCs induction by TGF-β were dependent on the balance between epithelial and mesenchymal features and cells developing partial EMT exhibit the highest sensitivity in human PAC cells54. The cell lines we have established, exhibiting varying degrees of EMT, hold significant potential possibilities as models for elucidating the association between CSCs and EMT.EMT and CSCs are closely linked55. Chemotherapy-resistant cells contribute to relapse. Although few reports are available for canine cases, chemotherapies, including vindesine, mitoxantrone, vinorelbine, and toceranib, are not fully effective57. Additionally, the mechanisms of resistance have not been elucidated. In the present study, the sensitivity to vinorelbine differed among the cell lines. CPACr-p and the clones, appeared to be relatively sensitive to vinorelbine, and Ras prenylation levels were lower than that in CPACd-p and cloned cell lines. This finding indicates that Ras signaling may be related to the mechanism that determines susceptibility to vinorelbine. However, Erk1/2 and Akt signaling may not be involved in the mechanisms common to these cell lines. Importantly, cell lines with EMT- and CSC-like phenotypes, such as CPACd-AB4 and CPACd-CG11, were resistant to vinorelbine. This finding indicates that EMT and stemness may contribute to chemoresistance in canine PAC. In contrast, although CPACd-AC12 showed resistance to vinorelbine, it showed poor expression of EMT and CSCs phenotypes. Additional studies using the cell lines we have established may reveal the mechanisms of resistance to vinorelbine, not only in canine but also in human PAC.Canine PAC resembles human lung tumors in never-smokers. Adjuvant chemotherapy, including vinorelbine, is indicated for patients with lung cancer. However, in some lung tumors that are intrinsically resistant to chemotherapy, acquired resistance has been shown to develop rapidly even in initial responders29. Also, in canine PAC, previous reports showed overexpression or activation of RTKs33, but the utility as therapeutic targets has not been established. In our findings, the established cell lines expressed EGFR and HER2 at various levels. Therefore, some of these cell lines might retain the expression of RTKs, which could be beneficial for the development of targeted therapies focusing on RTKs. On the other hand, in human lung cancer, drug resistance to EGFR inhibitors has also become a significant concern58. Due to the high similarity between PAC in humans and dogs, further evaluation of cellular characteristics associated with RTKs of these established cell lines could potentially be applied to the research aimed at overcoming resistance to RTK inhibitors in human lung cancer.The molecular characterization of canine PAC remains limited in comparison to human lung cancer. In human NSCLC, EGFR and HER2 have been shown to be overexpressed and recognized as significant therapeutic targets37. These experiments can possibly further clarify the EMT and CSC phenotypes and the detailed mechanisms underlying these phenotypes. Third, cell lines with various properties may not reflect the heterogeneity in tumor tissue but an in vitro selective pressure during the culture process. However, this possibility is difficult to be excluded. Finally, we have not been able to verify whether the established cell lines represent a general profile of canine pulmonary adenocarcinoma. However, given the absence of a defined general profile for canine PAC, it is difficult to say that. Further comparative investigation using whole-genome analysis and epigenetics methods between the established cell lines and tumor tissues from other dogs may substantiate the representativeness of these cell lines in canine PAC.The present study had several limitations. First, we did not perform transplantation in mice. Second, we did not assess the transcription factors associated with EMT, including Zeb, SNAIL, and SLUGIn conclusion, we successfully generated novel canine PAC cell lines with various characteristics. Moreover, we assessed the cellular properties in vitro, focusing on the EMT and CSC phenotypes. Our results indicate that EMT and stemness may play a role in resistance to vinorelbine. We also elucidated that the established cell lines exhibit varying levels of expression and activity of RTKs and Ras signaling factors. Therefore, these cell lines will facilitate the development of novel therapeutic strategies targeting EMT, CSCs, and intracellular signaling pathways and elucidation of the contribution of tumor heterogeneity to tumor biology, including chemoresistance, in human and canine PAC.A 14-year-old neutered male Maltese dog weighting 4.1 kg presented with a mass in the right posterior lung lobe. The mass was 2 cm in diameter, and metastatic lesions were absent according to diagnostic imaging, including computed tomography. The neoplasm was surgically resected and histopathologically diagnosed as a pulmonary adenocarcinoma . Further clinical information is described in Supplementary information file. Fresh tissue samples were collected, in accordance with the informed written consent of the owner and the approval of the Ethical Committee of Okayama University of Science , and the methods were performed in accordance with the relevant guidelines and regulations of Okayama University of Science and ARRIVE guidelines.2 incubator. Once the cell culture reached 80–90% confluence, they were repeatedly sub-cultured with 0.25% trypsin solution at a 1:4 dilution. The cell lines were named CPACd-p and CPACr-p and were cultured in DMEM- or RPMI-1640-based media, respectively. The cell lines were maintained for more than 50 passages.Tumor tissues were washed with saline and minced (1 mm). The tumor fragments were disaggregated with dispase  at 37 °C for 5 h with continuous agitation. After washing with phosphate buffered saline (PBS), the digested tissue was resuspended in DMEM  or RPMI-1640 , which are usually used in culture of various tumor cells as basic media, containing 10% deactivated fetal bovine serum , 100 U/mL penicillin , and 100 µg/mL streptomycin . Cell suspensions were maintained at 37 °C in a humidified 5% CO59. Cells were seeded at 500 cells/well in a 24-well plate and maintained until 90% confluence under the conditions described above. The cells were then seeded at a density of 1 cell/well in a 96-well plate (384 wells). The plates were examined under a microscope immediately after dispensing the cells and culturing. Wells suspected of containing more than one cell or multiple colonies were not cultured. After 30 passages, based on cellular morphology and subculture intervals, seven lines, which were realistic in terms of number of analyses, were selected from the cloned cell lines derived from CPACd-p and CPACr-p. These cell lines, including the parent cell lines, tested negative for mycoplasma contamination .The cell lines were cloned from CPACd-p and CPACr-p cells after 20 passages using the limiting dilution method5 cells/well on microcover glasses. At 80–90% confluence, the cells were fixed with methanol and stained with Wright–Giemsa stain . The glasses were captured under a light microscope at 40 × and 400 × magnifications. Each experiment was repeated at least thrice.Microcover glasses  were placed in the wells of a 12-well plate. The glasses were coated with type I collagen . The cells were then seeded and cultured in a plate at a density of 1 × 104 cells/well in a 24-well plate. After 24, 48, 72, and 96 h, the viable cells were counted using a hemocytometer with 0.5% trypan blue solution. Doubling time was calculated during the logarithmic growth phase (24–96 h) according to the following formula.The cells were seeded at 1.0 × 10Each experiment was performed in triplicate and repeated at least thrice.60, and a canine hemangiosarcoma cell line, Re1261, were also utilized as epithelial and mesenchymal controls, respectively. CHMp-13a and Re12 were kindly provided by Dr. T. Nakagawa  and Dr. H. Sakai , respectively. The results of CHMp-13a and Re12 were exclusively presented in the Supplementary Information file. Cells were lysed with NP40 lysis buffer  supplemented with an EDTA-free protease inhibitor cocktail  and a phosphatase inhibitor cocktail . Twenty micrograms of protein were subjected to sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) and transferred onto polyvinylidene fluoride (PVDF) membranes . The membranes were blocked for 1 h with 5% low-fat milk in Tris-buffered saline  containing 0.01% Tween 20 and then incubated with each primary antibody overnight at 4 °C, followed by incubation with HRP-conjugated secondary antibody for 1 h at 24 °C. The primary and secondary antibodies are listed in Supplementary Table In addition to the samples from the CPAC cell lines, protein samples from a canine mammary gland tumor cell line, CHMp-13a5 cells/well in a 24-well plate and cultured. After reaching 100% confluence, the cell monolayers were manually scratched with a sterile 200 µL pipette tip and washed with PBS to remove suspended cells. The adherent cells were cultured for 12 h. Cell migration was observed and captured under a light microscope at 40 × magnification. The migration ability was calculated relative to a gap area at 0 h. Each experiment was performed in triplicate and repeated at least thrice.To evaluate the migratory ability of each cell line, a wound-healing scratch assay was performed. The cells were seeded at 3.0 × 105 cells in 500 µL of serum-free media was added to the upper chamber. Seven hundred and fifty microliters of medium supplemented with 10% FBS were added to the lower chamber. After 20 h of incubation, non-migrating cells on the upper surface of the membrane were removed using a cotton swab. The inserts were fixed and stained with methanol and Wright–Giemsa stain . The number of migrating and invading cells was counted under a light microscope at 400 × magnification. Each experiment was performed in triplicate and repeated at least thrice.To evaluate the migration and invasion abilities of each cell line, a Boyden chamber assay was performed. Culture inserts with 8 µm pore size  were set on a 24-well companion plate (Corning). Matrigel  was added to the upper chamber and incubated for 2 h at 37 °C. Subsequently, the wells were washed with PBS. Wells without the Matrigel layer were used to count the migrating cells. A cell suspension containing 2.5 × 1062. Cells were seeded at 2000 cells/mL in an ultra-low attachment 24-well plate (Corning). These cells were cultured in serum-free DMEM/F12  supplemented with bovine serum albumin , 5 mM HEPES , 100 U/mL penicillin , 100 µg/mL streptomycin , 20 ng/mL human recombinant EGF , 10 ng/mL human recombinant bFGF (Peprotech), and 1% B27 supplement . EGF, bFGF, and B27 supplement were used to stabilise the formation and maintenance of sphere. DMEM/F12 medium supplemented with 2 ng/mL EGF and 1 ng/mL bFGF was added to the culture every other day for 10 days. Spheres were counted under a light microscope at 40 × magnification. Each experiment was performed in triplicate and repeated at least thrice.To evaluate the self-renewal activity of each cell line, a sphere-formation assay was performed using the protocol described in a previous report with a slight modification5) were labeled with 5 µM DCV alone or in combination with 50 µM verapamil . After 90 min of incubation at 37 °C, the labeled cells were washed with ice-cold PBS three times and analyzed by flow cytometer  and FlowJo software version v10.8.1 . Each experiment was repeated at least thrice.To detect the side population of each cell line, the cells were stained with DCV (Thermo Fisher Scientific) and analyzed by flow cytometer. Cells  for 48 h. Subsequently, cell counting kit-8  was added. After 2 h of incubation, the absorbance was determined at 450 nm using an SH-1300 microplate reader . The percentage of absorbance was calculated against the absorbance for untreated cells (control). Each experiment was performed in triplicate and repeated at least thrice.To evaluate the antiproliferative effect of vinorelbine on each cell line, a WST-8 assay was performed. Cells were seeded at 0.5 × 10P < 0.05.All data are presented as the mean ± standard deviation (SD). The normality and homogeneity of variances were verified using the Shapiro–Wilk and Bartlett's tests, respectively. Statistical comparisons between the CPACd-p and CPACr-p cell lines were performed using the unpaired Student’s t-test. Statistical comparisons between the parent and cloned cell lines were performed by one-way ANOVA with Dunnett’s multiple comparison post hoc test using Bell Curve for Excel . Differences were considered statistically significant at Supplementary Information.


Treatment and relevant targets for breast cancer (BC) remain limited, especially for triple-negative BC (TNBC). We identified 6091 proteins of 76 human BC cell lines using data-independent acquisition (DIA). Integrating our proteomic findings with prior multi-omics datasets, we found that including proteomics data improved drug sensitivity predictions and provided insights into the mechanisms of action. We subsequently profiled the proteomic changes in nine cell lines (five TNBC and four non-TNBC) treated with EGFR/AKT/mTOR inhibitors. In TNBC, metabolism pathways were dysregulated after EGFR/mTOR inhibitor treatment, while RNA modification and cell cycle pathways were affected by AKT inhibitor. This systematic multi-omics and in-depth analysis of the proteome of BC cells can help prioritize potential therapeutic targets and provide insights into adaptive resistance in TNBC.  •Proteomic analysis of 76 breast cancer cell lines and 9 lines with perturbation.•Machine learning-based multi-omics predicts breast cancer cells’ sensitivity to 90 drugs.•Longitudinal proteomic profiling provides insights into drug resistance. Here we present a deep proteome resource of 76 human breast cancer cell lines. Each cell line included four replicates. Then we built machine learning models using these multi-omics data to predict BC cells’ sensitivity to 90 drugs. We further performed longitudinal proteomic profiling of 9 cell lines perturbed by three drugs. Together, this study presents the so far most comprehensive proteomic investigation of BC cell lines and uncovered novel molecular insights for TNBC cells. Breast cancer (BC) is the second most common cancer in the world and the most common in women, with a mortality rate ranking fourth among all malignancies . In the HER2 (ERBB2) gene amplification and high levels of HER2 expression. Basal lines lack ER, PR, and HER2 expression.The search for novel drug targets in BC has benefited from multiple well-characterized BC cell lines . These cRecent genomic profiling studies have revealed potential novel targets for BC , 6. HoweRecent advances in data-independent acquisition (DIA)-based quantitative proteomic techniques  have enaIn this study, we applied our optimized PCT-DIA method to analyze the proteomes of 76 BC cell lines, including 39 TNBC samples. By integrative analysis of our proteomic results with genomic and transcriptomic data, we generated a model to predict the drug response of these BC cells to 90 compounds, including known BC drugs. We then further profiled over 400 BC proteomes from cells perturbed by three drugs that had been prioritized based on our multi-omics modeling of drug response. This unique proteomic dataset allowed us to identify proteins whose expression patterns change in response to these drugs, as well as potential biomarkers for drug resistance in TNBC.t test or one-way ANOVA for differentially expressed analysis and Pearson correlation test for correlation analysis, which are described in figure legends and methods where relevant.The first part of this study is the generation of the BR76 proteomic dataset where we collected 302 proteomic raw files for 76 BC cell lines. Each cell line was analyzed with three biological replicates and the third biological replcates was further subjected to one technical replicate. This BR76 proteomic dataset was then combined with the published genomic and transcriptomic datasets  to predim/z) and 30 ms for each window, respectively. The DIA window schemes were optimized to 66 variable windows. The instrument was operated in a high-sensitivity mode.PCT-DIA analysis was performed as previously described . Fresh cThe DIA MS raw data were processed using the DIA-NN (1.7.15) against an established spectral library that contains 194,899 proteotypic peptide precursors and 10,323 proteotypic SwissProt proteins  . DetaileIn total, 8952 proteins were identified with a 54.6% missing rate of the whole proteome. We then removed two outlier samples with extremely low protein identification numbers as revealed by PCA plots. After further removing the proteins with over 90% missing rate, 6091 proteins remained, with a 34.7% missing rate of the whole data set. In the meantime, the batch effect across all samples and the reproducibility of the measurement were evaluated by PCA plots and the coefficient of variation of all biological and technical replicates .We used a flexible network algorithm to develop a multivariate linear model to predict the effect of each compound in 76 BC cell lines using genomics, transcriptomics, and proteomics datasets, as previously described .The “glmnet” R package was utilized for elastic network analysis, incorporating nested cross-validation. Our analysis included the following aspects: point mutations (123 mutations), RNAseq , proteomic data sets (6091 proteins), and RPPA , which were used as input. The “impute.knn” function in the Bioconductor imputes the missing values.The detailed processes were outlined below. First, an “internal” cross-validation was performed. In this step, a set of multi-omic data from 59 cell lines was employed to determine the optimal hyperparameters (α and λ) for the elastic network. The elastic network parameters α and λ were selected by minimizing cross-validation errors within the “internal” pipeline . The selected α and λ parameters were then applied to the run of the 200 elastic network algorithms, with each time using a random subset of data obtained from 90% of the available cell lines. Then, the obtained 200 coefficient vectors were averaged, and the predicted values were sorted according to the magnitude of the average coefficient weight. To select predictors suitable for application to new data of finite size, standard linear regression and 10-fold cross-validation are used to evaluate the set of pre-k-ary predictors (by averaging coefficient weights). The cross-validation error within one standard deviation of the minimum cross-validation error, k, was set to a minimum. As part of the “external” pipeline, leave-one-way cross-validation is applied throughout the process to obtain a reliable estimate of the performance of the new data. Specifically, the elastic network model obtained using the remaining data (and the above steps) predicted the drug response of each cell line. Finally, the predicted response value was correlated with the actual response value, and for any drug/data combination, the prediction accuracy was evaluated using the Pearson correlation between the observed and the predicted drug responses .2.BT549, Hs578T, ZR75, and MDA-MB-231 cell lines were cultured in DMEM/F-12 medium ; MDA-MB-468 was maintained in L15 medium ; T47D was adapted in DMEM medium ; MCF7, MX-1, and SK-BR-3 were kept in 1640 medium . These media were all supplemented with 10% fetal bovine serum  and penicillin-streptomycin (HyClone) and incubated at 37 °C with 5% CO50) was determined using the MTT cell proliferation assay following the manufacturer’s recommendations  were obtained using Multiscan Spectrum (BioTek).Half-maximal inhibitory concentration  with every drug and (ii) showed a fold-change greater than two between the last and first time points. We then searched for pathways including these proteins using KEGG pathways in STRING database. Prioritization was given to pathways that were consistently dysregulated in at least three out of five TNBC cell lines and at least two out of four non-TNBC cell lines.The proteins were clustered in TNBC and non-TNBC cell lines using Mfuzz . We onlyA). This panel in our study shares 29 lines with the CCLE proteomics study (31 BC cell lines) (A) were obtained after quality filtering. Using stringent quantitative criteria as described in the supplemental Table S1B) across all samples with a 34.7% missing rate of 6091 proteins quantified in all samples. For each sample, we quantified an average count of around 4000 proteins , and the log10 transformed peptide intensities showed a normal distribution .We collected the 76 BC cell lines  characteFig. 1l lines) , 44 linel lines) . Only twl lines)  are incll lines) , 28. Whil lines) , 17, 18,l lines) A were obA). All replicates consistently yielded comparable protein and peptide identifications. The numbers of peptides identified per protein were highly consistent across the replicates with a CV <10% . Regarding protein quantification, the correlation among technical replicates (median r = 0.93) was slightly higher than that among biological replicates (median r = 0.91), and much higher than that among non-replicate samples (r = 0.74). The median CVs across different abundance level were all lower than 0.2 . Next, we subjected these proteins for the downstream analysis. The protein intensity distribution identified from these DIA files was highly consistent . Principal component analysis (PCA) revealed a mild batch effect in signal intensities in group 4 only, probably because these samples were analyzed by a different mass spectrometer . PCA plots of the cell line proteomic data exhibited minimal batch effect after batch correction using “limma R” package . Within the dataset, we identified 16 proteins overlapping with the PAM50 gene panel, which is a well-known breast cancer classifier (D). We then computed the average protein intensities of the four groups for subsequent analyses. Comparing the gene-wise correlation of RNA-seq (D) (C) (A), which agrees with previous observations , re, reA). A-seq (D) C (5), an (D) (C) A, which rvations . The mRNrvations , 31, 32 rvations . Should ata sets .Fig. 2MuB. Then we analyzed the top ten protein complex pairs with the highest correlation at both protein and transcription levels. They exhibited a higher correlation at the protein level than that at the transcription level (D), while that at the transcript level were associated with the processes such as endoplasmic reticulum to Golgi vesicle-mediated transport, actin nucleation, protein localization and fatty acid beta-oxidation (E). Notably, fatty acid beta-oxidation was the common pathway detected at both protein and transcription levels. Two exemplar protein complexes (C) include the HADHA/B which are potential prognostic biomarkers for BC . Of note, this analysis was based on all molecules measured in each dataset. Although the discriminative power of the transcriptome is not optimal because of the inclusion of the entire transcriptome containing 29,140 transcripts, the selection of differentially expressed transcripts  could well resolve the two groups (A). We identified 771 differentially expressed proteins (DEP)s in TNBC versus non-TNBC cell lines (B). Those DEPs were significantly enriched in 12 differentially activated pathways using Ingenuity Pathway Analysis (IPA) (C), including extracellular matrix, metabolism, and immunity network relationship. We also compared with the proteomic data of BC patients (B and C). The data indicated that proteome data obtained from cell lines are also potentially informative to the clinic.In analyzing molecular patterns unique to TNBC cells, we found that the DIA data outperformed RNA-seq and RPPA datasets in distinguishing TNBC samples from the 76 cell line samples based on 29,140 transcripts, 218 proteins identified by RPPA and 6091 proteins identified by DIA, respectively A. Of noto groups A. We idell lines B. Those is (IPA) C, includpatients , B and CD). These 38 DEPs participated in multiple biological processes (D) that are known to be involved in BC progression (E). Additionally, FASN (D–F).We next selected the 38 most significant DEPs to clearly distinguish TNBC cell lines D. These rocesses D that argression , 42. In gression , indicatgression , fatty agression , glutathgression , and clugression . These pgression E. Additily, FASN , ITGB4 , RNAseq , proteomic data sets (6091 proteins), and RPPA  (A). For any drug and data combination, the prediction accuracy was evaluated using the Pearson correlation between the observed and the predicted drug responses. The overall predictive power of the DIA proteomic data was slightly lower than that of the RNA-seq data, but superior to that of the gene mutations (B). The relatively low predictive power of the mutation data might be attributable to the low numbers of mutations detected, which likely reflects the relatively low levels of single-nucleotide variants found in breast cancer  A. For anutations B. The ret cancer .Fig. 4MuC); more information is provided in Fig. 4D). We then focused on the EGFR and Akt-mTOR signaling pathway which is crucial for many cancers including BC. Among the three EGFR inhibitors, Lapatinib exhibited the best performance. The molecules associated with the response to these three drugs  are listed in Fig. 4E). These proteins are mainly involved in cell cytoskeleton, signal transduction, and apoptosis, indicating that these biological processes might be associated with the response to the respective drugs. In particular, AKT inhibitors (such as GSK650394) have been suggested as a treatment for BRCA1-deficient BCs . For each drug/cell line combination, we first determined the IC50 (B). The cell line was then treated with each drug at its IC50 concentration for 4, 12, 24, 48, and 72 h. Three biological replicates were generated, and lysates of the respective samples were analyzed by DIA-MS (A). A total of 5621 SwissProt proteins were identified in 432 samples with a 33.6% missing rate of 5621 proteins identified in all samples . The high Pearson correlation value among the replicates, as shown in supplemental Fig. S5A demonstrated the high reproducibility of the experiment and MS measurement. In the PCA analysis of each drug, the luminal lines were well separated from the TNBC samples, indicating that the variance in BC subtypes introduces more significant variations than the drug perturbations (E).Based on our multi-omics modeling of drug response predictions, we next investigated the effect of drug-induced perturbations on the proteomes of BC cell lines. In particular, we aimed to identify protein modules mediating the response to specific drug treatments and explore the mechanisms to reverse drug resistance. We focused on the three targeted therapy drugs with the strongest correlation of half-maximal inhibitory concentration (IC50) values with multi-omic data: lapatinib, MK-2206, and everolimus. We examined their effects on nine BC cell lines: SKBR3, T47D, MCF7, Hs578T, ZR75, BT549, MDA-MB-231, MDA-MB-468, and MX-1 A. For eathe IC50 B. The cey DIA-MS A. A totaC and D; A. The hirbations E.Fig. 5PB–D). In Figure 5F, the proteins shown in red, including five proteins for lapatinib, 18 proteins for everolimus, and 12 proteins for MK-2206, were positively correlated with IC50 values, therefore they potentially contribute to drug resistance. In contrast, there are several proteins in blue, including 23 proteins for lapatinib, 11 proteins for everolimus, and 20 proteins for MK-2206. Their expression levels were negatively correlated with the IC50 values, therefore they might be correlated with drug sensitivity. Among the proteins that positively correlated with drug resistance, several have been reported to be associated with therapy response. For example, hexokinase 2 (HK2) is required for tumor progression . Aligning the proteomic data with biological pathways, the results showed that lapatinib and everolimus induced distinct metabolic responses in TNBC and non-TNBC cell lines, respectively . This result is in line with previous studies highlighting metabolism as a hallmark of cancer . The TCA cycle occurs in mitochondria, which were reported to be dysregulated at baseline in metastatic, compared with non-metastatic, TNBC .To compare the protein patterns that differed in drug response between TNBC and non-TNBC cell lines, we used Mfuzz and differential expression analysis. We identified 252 proteins with the opposite dynamic patterns between TNBC and non-TNBC cell lines . To identify the key protein determinants contributing to the response to lapatinib, MK-2206, and everolimus in TNBC cells, we compared the persistently dysregulated proteins (PDPs) after the drug treatment in TNBC and non-TNBC cell lines. We found 483 PDPs in over 60% of TNBC cell lines treated with MK-2206, while there were only 173 PDPs for everlolimus and 172 PDPs for lapatinib (C). Hence, MK-2206 treatment induced the most significant differences between the TNBC and non-TNBC cell lines at the proteome level. The set of affected proteins mainly included proteins involved in ribosome biogenesis, RNA polymerase, spliceosome, and the cell cycle (B). Among these, DNA (cytosine-5)-methyltransferase-1 (DNMT1) was significantly downregulated only in the TNBC cell lines (C). AKT has been reported to reduce DNA methylation via modulating the phosphorylation of DNMT1, and DNMT1 inhibition could also reduce the activity of AKT signaling . DUS2 is involved in tRNA modification and affects the stability of mtRNA  synthase [NAD(P)+]-like (DUS2) and DNA topoisomerase 2-alpha (TOP2A) C. DUS2 iof mtRNA . Separatof mtRNA . Notablyof mtRNA , 65.Collectively, the proteins and related pathways that we identified through analyses of these large datasets lay the foundation for future studies into potential TNBC treatment. Our observations are further reinforced by previous work on the implications of these proteins and pathways in cancer development.We collected high-quality proteomics data on 76 BC cell lines with four replicates using PCT-DIA and integrated these data with genomics and transcriptomics for drug sensitivity prediction. We observed that proteomic data improved the sensitivity prediction of multiple drugs in BC. Our analysis identified 38 proteins specifically expressed in TNBC cell lines, which were validated using independent data. Our DIA dataset contributes to the effective prediction of drug response in multi-omics modeling experiments. Additionally, we performed time-course analyses investigating protein dynamics to identify proteins and pathways that are specifically dysregulated in TNBC lines and might yield insight into adaptive drug resistance in TNBC. Although lapatinib and everolimus elicited few changes in TNBC cells, MK-2206 resulted in significant changes including ones involving RNA modification and cell cycle pathways. Our data showed significant changes in DUS2, DNMT1, and TOP2A following MK-2206 treatment in TNBC. These observations warrant future investigation to explore their suitability as drug targets or biomarkers.Although this multi-omics study included a relatively large number of samples, as well as biological and technical replicates, it did not include phosphorylation data. However, this limitation does not compromise the relevance and accuracy of our main findings. The primary focus of this publication was to report on this rich proteomic dataset and conduct an initial, exploratory bioinformatic analysis of the dataset. It is outside the scope of the intended work, and therefore a limitation, to conduct in-depth experimental validation of reported biomarkers; this work is left for future study.The 76 breast cancer cell DIA data are deposited in Pride (PXD004701), the protein matrix is included as This article contains T. G. and Y. Z. are shareholders of Westlake Omics Inc. R. A. holds shares in Biognosys. W. G. are employees of Westlake Omics Inc. The remaining authors declare no competing interests.


Four-dimensional (4D) printing is an innovative additive manufacturing technology used to fabricate structures that can evolve over time when exposed to a predefined environmental stimulus. 4D printed objects are no longer static objects but programmable active structures that accomplish their functions thanks to a change over time in their physical/chemical properties that usually displays macroscopically as a shapeshifting in response to an external stimulus. 4D printing is characterized by several entangled features , structure geometry, and applied stimulus entities) that need to be carefully coupled to obtain a favorable fabrication and a functioning structure. Overall, the integration of micro-/nanofabrication methods of biomaterials with nanomaterials represents a promising approach for the development of advanced materials. The ability to construct complex and multifunctional triggerable structures capable of being activated allows for the control of biomedical device activity, reducing the need for invasive interventions. Such advancements provide new tools to biomedical engineers and clinicians to design dynamically actuated implantable devices. In this context, the aim of this review is to demonstrate the potential of 4D printing as an enabling manufacturing technology to code the environmentally triggered physical evolution of structures and devices of biomedical interest. Additive manufacturing (AM) technologies  printing”) have been widely exploited in many interdisciplinary research fields  due to their excellent repeatability and capacity to construct complex structures with precise geometry control ,2. AM prD printinIn the last decades, different innovations have been introduced in AM, such as multi-material and multi-scale AM, in which different AM technologies are combined to fabricate heterogeneous structures ,5, in siMore in detail, 4D printing was introduced in 2013 by Dr. Skyler Tibbits  to denotTherefore, the key points of 4D printing are: (i) active materials  or combinations of different materials; (ii) external stimuli ; and (iii) AM technologies, which act as an enabling tool that allows the exact positioning of a precise quantity of one or more stimulus-responsive materials in predetermined locations without restrictions on the complexity of the geometry ,13,14. T−1. Moreover, laser printing technology has been used in synergy with 4D printing to convert graphene oxide into graphene-based composites [Using two dimensional (2D) nanomaterials , 4D-printed nanocomposites have been used to design shape-programming objects. For example, Wei et al.  used 4D mposites . This lamposites ,20.Using responsive materials and the related stimuli for their activation, it is possible to physically program many morphological transformations enabled by the proper organization guaranteed by AM. However, designing a new structure via 4D printing is a complex problem. Indeed, it is influenced by several variables  that need to be properly combined to achieve a functional structure. Moreover, the knowledge of the material’s behavior and interactions, the correct stimulus, and the printing parameters are fundamental elements that increase the complexity of the problem and that need to be considered and deeply understood. In this context, mathematical modeling is a very useful tool to determine the combination of variables that leads to the maximum and desired transformation of the 4D-printed structures ,22.Since 2013, when 4D printing was introduced, this fabrication strategy has seen fast growth in many sectors, including smart textiles, autonomous and soft robotics, biomedical devices, electronics, and tissue engineering (TE). This is due to its advantages over static AM, such as the possibility of an easier fabrication of complex 3D structures that are fabricated as flatted objects and then achieve their 3D conformation after actuation, thus reducing the encumbrance of the objects, and the exploitation of reliable alternatives to electrical energy , capable of remote control without the use of cumbersome wiring, thus leading to the use of 4D printed structures in severe environments .In this review, we aim at providing an overview of 4D printing as a new additive manufacturing technology in the biomedical field. In the first part, a brief introduction to stimuli-responsive materials with a special focus on natural polymers and nanomaterials will be provided, along with a description of the achievable transformations and mathematical modeling. Then, applications of 4D printing in bioengineering  will be discussed, reporting relevant examples from the recent literature.In many applications, 4D printing exploits active materials, namely materials that undergo useful, predictive, reproducible, and macroscopic physical or chemical changes in their properties as a consequence of an environmental change ,23. WhilWith the rapid progress of 4D printing, the prevalence of eco-friendly, sustainable smart polymers from natural sources is gaining great interest in the field ,25,26. TMoreover, exploiting natural biomaterials allows for the expansion of the library of possible bioinks/biomaterial inks, thanks to the variety of natural building blocks, such as peptides, amino acids, and deoxyribonucleic acid (DNA) sequences.In the following paragraphs, the active polymers, with a deep focus on natural polymers, used in 4D printing will be analyzed and classified in relation to the involved stimulus.Currently, one of the most investigated methods to achieve shape-changing in 4D printing is temperature responsiveness. A thermo-responsive material can employ exogenous temperature changes as stimulus to achieve a particular shape transformation or can be activated by heating through the Joule effect due to electrical current flow. The easiest form of temperature-responsiveness is thermal expansion, which leads to the volume expansion of a structure as a consequence of a temperature increase. In this context, there are also a few materials that exhibit the opposite behavior, undergoing contraction with an increase in temperature . Among tTaking a step forward, changes in temperature can induce variations in wettability and solubility alterations of materials, as for poly(N-isopropylacrylamide) (PNIPAAm), poly(methyl vinyl ether), and poly ,32.An easy method that fosters the temporal shape transition of 4D-printed structures is humidity responsiveness. The phenomenon refers to the inherent swelling feature observed in both synthetic and natural hydrogels . HydrogeAnother category of active materials are pH-responsive polymers. They can vary their rheological characteristics, such as viscosity and shear modulus, in response to changes in the pH or ion concentration of the surrounding environment ,23,38. EMoreover, pH can be utilized to promote the self-assembly of peptide hydrogels made of the alternation of natural amino acids, increasing the mechanical and rheological properties of the substance by promoting the creation of intra-molecular sheets or alpha-helices ,42.In light-sensitive materials, the applied optical stimulation , and near-infrared (NIR) light) is converted into other responses, usually mechanical ones . The chrIt is crucial to emphasize that in numerous works, light is employed as a substitute technique to heat the 4D structure in specific spots. Consequently, the rise in temperature brought on by the lights is the true stimulus that causes the shape-shifting ,49.Polythiophene and poly(2-hydroxyethyl methacrylate) are some examples of electrically responsive materials characterized by intrinsic electrical conductivity. Their shape and size can be regulated by the intensity and direction of an external electric field ,51.Coulombic, electrophoretic, electroosmotic, and piezoelectric processes are some examples of the electrical interactions that can take place in a material to produce electric field responsiveness . AdditioMagnetic fields, in addition to electrical fields, are frequently utilized for triggering shape changes in 4D-printed structures. Uncontactable remote manipulation using magnetic fields is effective and safe . SimilarSMPs are a widely utilized class of smart polymers that are crucial for 4D printing in the biomedical industry ,24. TheiPolylactic acid (PLA) and acrylonitrile butadiene styrene (ABS) are the most commonly used temperature-responsive SMPs ,25, wherIn the literature, there are different attempts to define a taxonomy of shape-changing structures that can be obtained with 4D printing. Here, starting from the classification provided by Nam and Pei , an advaFour-dimensional printing is influenced by several entangled variables, such as the entity of the applied stimulus, the spatial deposition of different material(s), and their properties. Those variables need to be carefully coupled to obtain a favorable fabrication and a functioning structure, making the design of a new structure via 4D printing a complex problem. In this contest, the development of an appropriate mathematical model is essential for the success of the 4D printing process ,79,80. MAn appropriate mathematical model for 4D printing comprises four main elements: (i) the final desired shape , dictated by the application of the 4D printed object; (ii) the spatial deposition of the involved material(s), i.e., the initial shape. This aspect closely depends on the employed AM technology and on the material processability; (iii) material properties and responsiveness to the applied stimulus; and (iv) entities of the applied stimulus.Mathematical models can be divided into two main categories: forward problems and inverse problems. The forward problems aim at determining the final shape of the structure and are more oriented toward discovering concepts. A glaring example of a forward problem is the use of lumped parameter models to study the shape evolution of SMPs. For instance, the standard linear solid model  was exploited by Yu et al. to quantitatively model the energy storage and release process achieved during the multiple shape transformation in SMPs .In inverse problems, the final state is known, and the user aims to find out how to obtain it by defining the initial geometries and spatial deposition of material(s) . Thus, inverse problems are more application-oriented. A brilliant example of an inverse problem can be found in the study of Gladman et al. , in whicAnalytical models represent the mathematical formulation of a certain mechanical or biophysical system or phenomenon, thus being extremely used in the mathematical modeling of 4D printing . ExampleSoft actuators, also referred to as bioactuators, are highly deformable structures characterized by ease of movement that can be activated by external stimuli to generate the desired motion and forces/torques . They arA milestone example of this use of 4D printing for soft actuators is provided by Liu et al. . The aut−1, thus possessing a highly efficient mechanism of locomotion. This was achieved using the cell contractive forces and the anisotropic friction of the supporting structure.Taking a step forward, Chan et al.  fabricatNative tissues exhibit complex 3D structures and microarchitectures, as well as unique functions that are achieved through dynamic changes in tissue conformation . TherefoThe 4D-bioprinted scaffolds can improve the functionality of the scaffold by simplifying its seeding and the fabrication of structures capable of adapting to the complex 3D shapes of the human body or providing appropriate stimuli to promote cell differentiation and activities ,101.For example, in the context of bone TE, it is difficult for traditional 3D static scaffolds to have a good match with the sharp edge shape of bone defects, thus often leading to incomplete edge and material absorption ,103. In Moving to a diverse anatomical district, Kim et al.  4D-bioprFocusing on the same tissue  and shape-morphing strategies, Ding et al.  fabricatTaking a step forward, Yang et al.  fabricatFinally, thinking about patient-adaptable soft tissues such as blood vessels, Luo and colleagues created an effective approach to manufacturing scaffolds with fine topologies combining 4D printing, fused deposition modeling (FDM), and crosslinkable shape memory linear copolyesters . These 4A medical device is any article manufactured to be used in human beings with the final aim of diagnosis, prevention, monitoring, prediction, prognosis, treatment, or alleviation of disease, injury, or disability, as proposed by the Global Harmonization Task Force and reported in official legislation as European Regulation 745/2017 ,107. 4D In previous works, we exploited the temperature responsiveness of regenerated silk (RS) for the fabrication of two devices to be used in intestinal surgery applications ,59. The Drug delivery systems play a critical role in the pharmaceutical industry by ensuring that medications are administered to patients effectively and with precise control. 4D printing can also be applied to drug delivery systems, where printed structures release drugs in a controlled manner. In this context, 4D printing possesses several advantages if compared with traditional manufacturing techniques . Indeed, 4D printing offers a number of benefits, including the possibility to obtain a controllable kinetic and to achieve a time- and/or site-dependent drug release based on the shape-shifting property of the device itself ,111.4D-printed structures for drug delivery systems should be biocompatible to avoid toxicity or irritation at the delivery site. In this case, 4D-printed drug delivery systems utilize biocompatible hydrogels or smart polymers that can change their properties in response to environmental factors. These materials are well-suited for controlled drug release applications. For example, a chitosan-pectin hydrogel was utilized by Long and colleagues to print a biodegradable wound dressing for the local anaesthetic medication lidocaine . The appIn smart drug delivery system fabrication, temperature-responsive materials are carefully chosen based on their ability to undergo a phase transition, typically a sol-gel transition, within a specific temperature range. Common materials include thermosensitive polymers like PNIPAAm and its derivatives . The druStaphylococcus aureus and Enterococcus faecalis [Moreover, 4D-printed hydrogels with antimicrobial properties have been receiving attention in the last decade, especially for wound closure. 4D hydrogels were functionalized with the cell-adhesive motif Arginine-Glycine-Asparagine (RGD) to enhance cell spreading , and at faecalis . In factfaecalis . Regenerfaecalis ,120.Other examples were represented by 4D-printed drug-eluting stents that could release medications gradually to prevent restenosis in blood vessels .Last, but not least, 4D printing enables the fabrication of patient-specific drug delivery systems . Each paUtilize 4D-printed materials to create drug delivery systems that can release chemotherapy agents with precise control by using the right quantity of the drug at the right time. One example is the prosthesis of paclitaxel and doxorubicin microspheres to prevent tumor recurrence and metastasis after breast-conserving surgery designed and prepared by Hao et al. in 2021 .Other examples were studied to implement real-time monitoring of treatment outcomes and patient responses to adjust drug delivery parameters as needed .For sure, to allow the use of 4D printing in clinical practice in an effectively integrated manner, we must create multidisciplinary care teams involving oncologists, pharmacists, nurses, and 4D printing specialists to facilitate patient-specific treatment planning and implementation.Finally, by designing drug delivery systems that release medication over extended periods, patients may require fewer doses, improving compliance and reducing the risk of medication errors. The potential for personalized drug delivery through 4D printing brings undoubtedly with it a host of ethical and regulatory challenges. Addressing these challenges is crucial to ensuring the safe and responsible use of this technology. First of all, personalized drug delivery may require the collection and storage of sensitive patient data, such as medical history and genetic information. For this reason, patients must understand and consent to the use of their data and the personalized drug delivery approach. On the other hand, one must implement strict data protection measures, secure storage and encryption, and ensure compliance with data privacy laws  or the Healthcare Insurance Portability and Accountability Act (HIPAA)).In conclusion, although several open challenges still must be faced , 4D (bio)printing is a breakthrough technology that, thanks to the constant progress in materials science, additive manufacturing, and biology, represents an enabling tool to address unsolved clinical needs in tissue engineering and medical device manufacturing. This review highlighted the importance and potentiality of 4D (bio)printing to tailor and customize the functionalities of a device by combining active materials with appropriate 3D architectures and advanced AM technologies.


MKL1 displayed ethnic stratification, with the variant being significantly more prevalent in the African cohort and resulting in reduced transcript levels as measured by qPCR. Functional validation of MKL1 by shRNA-mediated knockdown of MKL1 resulted in a more resistant phenotype. Gene expression analysis identified the developmentally associated TGFB1I1 as the most significant gene associated with sensitivity. qPCR among a panel of sensitive and resistant LCLs revealed immunoglobulin class-switching as well as differences in the expression of B cell activation markers. Flow cytometry showed heterogeneity within some cell lines relative to surface Ig isotype with a shift to more IgG+ cells among the resistant lines. Pretreatment with prednisolone could partly reverse the resistant phenotype. Results suggest that the efficacy of anti-CD20 mAb therapy may be influenced by B cell developmental status as well as polymorphism in the MKL1 gene. A clinical benefit may be achieved by pretreatment with corticosteroids such as prednisolone followed by mAb therapy.Monoclonal antibody (mAb) therapy directed against CD20 is an important tool in the treatment of B cell disorders. However, variable patient response and acquired resistance remain important clinical challenges. To identify genetic factors that may influence sensitivity to treatment, the cytotoxic activity of three CD20 mAbs: rituximab; ofatumumab; and obinutuzumab, were screened in high-throughput assays using 680 ethnically diverse lymphoblastoid cell lines (LCLs) followed by a pharmacogenomic assessment. GWAS analysis identified several novel gene candidates. The most significant SNP, rs58600101, in the gene  MS4A1 gene is a member of the membrane-spanning 4A gene family encoding the B-lymphocyte surface molecule (CD20). Its direct function is largely unknown, but it has been proposed to regulate calcium conductance and be involved in cellular activation [The lecule CD0. Its ditivation  with limtivation ,6,7,8. Itivation ,10, thustivation . This st+ B lymphocytes (LCLs), enabling genome-wide association studies (GWAS) and gene expression studies in large multi-ethnic cohorts. LCLs are thus ideally suited for studying the genetic determinants influencing sensitivity toward anti-CD20 therapies. The LCLs are prepared from peripheral blood B cells of donors immortalized by in vitro transformation with Epstein–Barr virus. Each cell line is thus a population of genetically matched cells, yet significant B cell heterogeneity may exist with respect to immunoglobulin isotypes as well as differences in activation and differentiation pathways [The lymphoblastoid cell lines (LCLs) used in this study were obtained from the 1000 Genomes Project , which ppathways .regs), or terminally differentiate into more metabolically active antibody-secreting plasma cells. Antigen engagement by the BCR is essential to B cell activation and differentiation, driving the clustering of BCR complexes along with co-receptors into microdomains organized around lipid rafts. Amplification of signaling occurs by the fusion of these microdomains. Fusion is mediated by the cytoskeleton and Src-family kinases to form larger signaling and endocytic regions on the cell surface [Gene expression analysis suggested differences in B cell developmental status differentiate sensitive from resistant cells. B cell development and maturation is a complex, multi-stage process, generating numerous B cell intermediates and subtypes reflected by a changing repertoire of cell surface markers and functionality. Circulating naïve B cells express surface-bound IgM/D. Cellular activation by antigenic binding through the IgM/BCR (B cell Receptor Complex), as well as cytokine stimulation and interaction with helper T cells, induces immunoglobulin class-switching to IgG/A/E with additional affinity maturation of the immunoglobulin through somatic hypermutation in germinal centers (GC) of secondary lymphoid tissue. GC-derived B cells then differentiate into either relatively quiescent memory B cells, regulatory B cells , associated with drug sensitivity. MKL1 is a transcriptional regulator controlling the expression of cytoskeletal genes. While a role for MKL1 in hematopoietic development is implicated by its involvement with the t translocation specific to acute megakaryoblastic leukemia, there is limited research examining an MKL1 role during B cell differentiation. B cells from a patient with an intronic deletion in MKL1 have been recently characterized and shown to have elevated levels of MKL1, which was associated with a number of phenotypic changes: increased actin content; hyperproliferation; genomic instability; decreased expression of CD11a integrin molecules; and decreased homotypic aggregation [Genome-wide association analysis identified a novel gene, regation .2 using RPMI medium 1640 and 15% fetal bovine serum .This study was performed using 680 lymphoblastoid cell lines (LCLs) from the 1000 Genomes Project  after re®; Genentech, Inc., San Francisco, CA, USA) and ofatumumab  were purchased through the North Carolina Cancer Hospital pharmacy. Obinutuzumab  was kindly provided by Angela Facul .Rituximab  or in the presence of 25% human serum (as a source of complement) and with or without 10 μg/mL of each antibody. In initial screening experiments, which were part of a larger drug screening project , pooled Gene expression analyses were conducted using previously established procedures . RNA-Seqi = β0 + Li*β + ϵi, ϵi ~ NFirst stage: GijY = β0 + β1*PC1i + β2*PC2i + β3*PC3i + β4*iSex + β5*ϵi + ije, eij ∼ N, where, in the first stage: Gi is the quality-controlled RNA-Seq read count of gene g for individual i, Li is a vector of indicator variables for the lab in which the RNA-Seq was conducted for individual i, β is a vector of the regression parameters, and ϵi are the residuals = observed read count for gene g-predicted gene read count for the gene for an individual I; in the second stage: Yij is the vector of normalized responses for the one concentration for the mAb for each individual i; the Eigenvalues for the first three principal components, PC1, PC2, and PC3 are calculated using EigenStrat [i is an indicator variable denoting gender.Second stage: genStrat ; and i ii is the quality-controlled RNA-Seq read count of gene g for individual i. Li is a vector indicating the lab in which the RNA-Seq was conducted for an individual. β is a vector of the regression parameters, and ϵi are the residuals . To minimize extreme residual values from having an excessive influence on parameter estimates, residuals were log-transformed and standardized prior to use in the second stage. In the second stage, linear regression was performed using the R function lm in package stats v3.4.0 [g. Yij is the vector of normalized responses for the six concentrations of the drug for individual i; the Eigenvalues for the first three principal components, PC1, PC2, and PC3, are calculated using EigenStrat [I as an indicator variable denoting gender. Significant results from the second stage were obtained after correcting for multiple testing on a per-drug basis using: the Bonferroni correction with a significance level of p < 0.05 for the gene expression analysis; and the Benjamini–Hochberg method [p.adjust , package stats v3.4.0) [In the first stage, linear regression is performed using the limma package  to removs v3.4.0  for eachgenStrat  with I ag method  with a f v3.4.0) .p-value < 0.05) associated with ofatumumab sensitivity were used to identify signaling pathways involved in the differences between LCLs sensitive and resistant to CD20 mAbs treatment.Unsupervised and supervised enrichment analyses using gene set enrichment analysis (GSEA) and gene ontology (GO) analysis were performed using the ClusterProfiler R package . The moshttps://www.internationalgenome.org/data-portal/data-collection/phase-1, accessed on 1 May 2015) and processed as described elsewhere [p-value < 1 × 10−6. After routine quality control, 1,510,701 SNPs were used for GWAS, as described in Abdo et al. [http://pngu.mgh.harvard.edu/purcell/plink/, accessed on 20 September 2019) under a genotypic model, adjusted for sex, temperature, growth, experimental batch, and the Eigenvalues from the first three principal components using EigenStrat [Genotype data for the 1000 Genome cell lines from the Illumina HumanOnmi2.5 platform was obtained from the 1000 Genomes database  . Control cell lines were prepared using a scrambled shRNA sequence. 1 μg/mL of puromycin was used to select positive cell lines. Knockdown was confirmed by Western blotting.Stable knockdown cell lines were prepared as previously described  by lenti−6 cells using Quick-RNA Microprep Kit . Purified RNA was then reverse-transcribed into cDNA using Verso cDNA Synthesis Kit . Conventional qPCR was performed using PowerUp SYBR Green Master Mix . Reactions were conducted in quadruplicate in 10 μL volumes using 500nM of forward and reverse primers prepared by Sigma Genosys  and run on the Applied Biosystems QuantStudio 6 Flex Real-Time PCR System. Primer pairs used are provided  within one field of view for each cell line.Homotypic aggregation or cell clump size was estimated from micrographs taken 30 min following the dispersion of cells by pipetting and pulse centrifugation. Images were captured using a Nikon Eclipse Ts2R microscope with a 10x objective and NIS-Elements software. 8-bit grayscale images were converted to binary then particles were defined using the best-fit ellipse selection tool. The particle areas were then estimated with ImageJ software  with a size defined as 2000–∞ ; αIgG-FITC (Invitrogen); and αIgM-BV711 . Antibodies were added to samples for an additional 45 min before adding an equal volume of buffer. Samples were centrifuged, washed, and pellets resuspended in 0.5 mL of the same buffer containing either TOPRO-3 (Invitrogen) or DAPI (Thermo Scientific) as a viability dye. Surface expression analysis was performed on an Attune NxT V6 flow cytometer (Thermo Scientific). Data analysis was performed with FlowJo software . For sorting experiments, 107 cells were stained as above with αIgG except omitting sodium azide from the staining buffer and sorted on a FACSAria III  within the UNC Flow Cytometry Core Facility.1.0 × 10−5 cells/well in 25ul media. The reaction was begun by the addition of an equal volume containing 8 μM EthD1 (Molecular Probes), ±20 μg/mL of anti-CD20 mAb, and containing 50% human serum. An Infinite F200 microplate reader (Tecan US) and iControl software (Version 1.6) were used to measure the fluorescence intensity of the dye at EX535nm and EM595nm at timed intervals. The fluorescence of untreated cells was subtracted as background from treated cells. Dye uptake is then presented as a percentage relative to a positive control using cells lysed with 0.1% saponin.Cells were plated into 384 well plates at 2.5 × 10g for 10 min to pellet cells. The supernatant was then centrifuged at 1500× g for 10 min to remove cell fragments, including apoptotic bodies. Exosomal material was collected in a subsequent 15,000xg centrifugation for 30 min. In some experiments, 10% (w/v) PEG-10000 (Sigma) in 0.3M NaCl was added to the 15,000× g supernatant overnight at −20 °C then centrifuged at 15,000× g for 30′ to confirm quantitative removal of CD20 in the preceding fractions. Pelleted fractions were resuspended in lysis buffer and analyzed by western blotting.Exosomes were isolated by centrifugation of cell cultures at 250× R2 = 0.51 , ofatumumab (ofat), and obinutuzumab (obin) using a single, saturating concentration of 10 μg /mL, were compared using 680 lymphoblastoid cell lines (LCLs) under both normal cell culture conditions (ofat and obin) as well as in the presence of human serum as a source of complement  as part of a larger, drug screening project . Alamar 2 = 0.51 . All thr2 = 0.51 . LCL res = 0.441 . There wtwo mAbs . The mintwo mAbs . Likewistwo mAbs . Direct ectively .p-value < 10−6). At the genome-wide suggestive threshold of p-value < 10−6, there were eight peak associations for ofatumumab and obinutuzumab under normal culture conditions measuring direct cell kill , the most significant SNPs were associated with obinutuzumab treatment (SCAMP5 gene). An additional SNP, rs60910940 (synonymous variant in SCAMP5), was also associated with obinutuzumab treatment.Using genotype data from the 1000 Genomes database, separate GWAS was performed using the response data from the three monoclonal antibodies: rituximab; ofatumumab; and obinutuzumab. ell kill . In the ell kill . At the reatment . They weMKL1 gene with ofatumumab treatment . MKL1 was therefore chosen as a candidate gene for functional validation to examine if its expression influenced sensitivity toward anti-CD20 mAbs using shRNA knockdown constructs.Under the more physiologic condition with complement present, the most significant association is for SNP, rs58600101, an intronic SNP within the reatment . The MKLMKL1 exons 14–15, which help comprise the transcriptional activation domain (TAD) of MKL1 [MKL1 transcript variant occurs within this region through the use of an alternate splice site, resulting in a frameshift and an early stop codon. For this reason, primers were designed spanning exons 13–15 for both the reference transcript as well as for the splice variant. A third pair of primers were included in a separate region of the gene spanning exons 11–12. MKL1 gene expression of either of the reference transcripts was reduced in the SNP variants to an average of 0.37 (stdev ± 0.114) relative to wildtype expression (MKL1 in the SNP variant averaged 0.34 (stdev ± 0.19) in comparison to wildtype. Therefore, SNP rs58600101 affects transcript levels but did not appear to influence the formation of splice variants.SNP, rs58600101, is an intronic SNP located between the last pair of  of MKL1 . qPCR wapression . The splMS4A1 (CD20), was examined by both qPCR and flow cytometry in these cell lines  of the nine cell lines, suggesting MKL1 is responsible for additional mechanisms of resistance. Further characterization of the MKL1 knockdown cells  and lymphoma lines  using shRNA constructs. Knockdown was confirmed by western blotting to average 87% . Transforming Growth Factor Beta 1 Induced Transcript 1  was the most significant gene correlating with sensitivity. Two genes were identified for rituximab  that were likewise significant for ofatumumab. Eight genes were identified for obinutuzumab . Five of these genes were likewise significantly associated with ofatumumab. The three remaining genes could thus be uniquely assigned to the type II antibody, obinutuzumab, and included: RSAD1 (p < 0.02), RP11-251G23.2 (p < 0.02), and PDCD4 (p < 0.04).Associations between basal gene expression and complement-mediated cytotoxic drug response were examined for these three anti-CD20 mAbs using publicly available expression data . The genp < 0.05 . The MS4MHCII-associated genes was associated with the resistant phenotype. SCAMP5 again appeared as a significant gene during this analysis. Its interaction with the cytoskeleton at the inner plasma membrane surface and involvement in calcium-triggered vesicle fusion followed by exocytosis likewise suggest potential protective mechanisms.The gene list generated by ofatumumab was examined en masse to identify biological processes that might distinguish sensitive from resistant cells using GSEA  and GO (Gene ontology) enrichment analyses . The GO-p ≤ 0.001). Since homotypic aggregation can be indicative of a more activated B cell, frequently as a consequence of CD40 signaling [IgM relative to IgG. In contrast, resistant cell lines expressed more IgG as well as markers associated with an activated B cell phenotype, such as IRF4, TNFSRF17, CD40, and CD23 (FcεRII) [PAX5 (p ≤ 0.0003).During the screening of LCLs in viability assays, increased homotypic aggregation was often observed in resistant cell lines relative to more sensitive lines. Therefore, the size of cell aggregate was measured in seven resistant and seven sensitive cell lines. The relative aggregate size of resistant cell lines averaged 778 μm (±101 sem) compared to 161μm (±45.8 sem) for sensitive cell lines  ,40,41,42+, and generally, sensitive cells were more IgM+. Some cell lines exhibited mixed populations of both IgG+ and IgM+ cells  higher in IgG+ cells relative to the IgM+ population when assayed against rituximab (p ≤ 0.01) higher in the IgG+ population when compared to IgM+ cells.Surface expression of IgG and IgM were then analyzed in 9 LCLs by flow cytometry. As expected, based on results from qPCR data, resistant lines were predominantly IgGM+ cells . One sucfor IGHG . The twoituximab . The difGiven that there appeared to be an association between mAb resistance and expression of activated B cell markers, a panel of B cell lines was pre-treated with the immunosuppressant, prednisolone for 10 days to essentially deactivate and thus sensitize the cell lines toward CD20 mAb treatment. While not all cell lines appeared responsive to prednisolone, the majority of cells were sensitized. Cell viability was reduced an additional 63% (±0.21 stdev) on average relative to cells not pre-treated with prednisolone following exposure to ofatumumab  following high-throughput in vitro screening of LCLs as an unbiased approach to identify genes affecting sensitivity toward anti-CD20 mAb therapy without reliance on a priori knowledge for potential gene candidates.MKL1, also referred to as Myocardin-related transcription factor A (MRTFA), as a significant determinant of sensitivity. MKL1 is a transcriptional co-regulator along with serum response factor (SRF) controlling the expression of cytoskeleton-related genes, including actin [MKL1 SNP, rs58600101, is an intronic SNP located in the 3′ end of the gene between the last pair of exons 14/15. The SNP variant was associated with increased resistance toward anti-CD20 mAbs during high-throughput screening. The variant could be associated with reduced MKL1 mRNA expression. This was consistent with subsequent shRNA knockdown experiments in which reduced MKL1 expression was accompanied by a more resistant phenotype in both lymphoblastoid as well as lymphoma cell lines. This SNP exhibited ethnic stratification with the minor allele found predominantly in the African population cohort (MAF = 0.170), with only one variant found within the non-African cohort of the 680 cell lines in this study sample. This result suggests that the efficacy of anti-CD20 mAbs may be diminished in patients of African descent.GWAS identified the SNP, rs58600101, in ng actin ,46. MKL1ng actin ,48,49. Tng actin ,51,52,53ng actin . The MKLTGFB1l1, as one of the most significant determinants of sensitivity. TGFB1l1 is a member of the paxillin superfamily of focal adhesion adaptor proteins [Gene expression results indicate that differences in B cell development or activation status likely affect sensitivity with potential involvement of the TGF-beta 1 signaling pathway. TGFb1 is an important regulator of B cell development, having been shown to interfere with the expression of cell surface λ light chains during in vitro differentiation of normal human pre-B cells  and to iproteins ,59 that proteins .CBLB, as a determinant of anti-CD20 sensitivity. Knockdown experiments resulted in increased CD20 clustering on the cell surface and increased resistance toward anti-CD20 mAbs [A previous, smaller study by this group relying on linkage analysis of pedigreed cell lines identified a similar gene, D20 mAbs . Like TGD20 mAbs ,62. TherD20 mAbs  characteD20 mAbs . Togethe+, while resistant lines were enriched in class-switched IgG+ cells. Other cell lines used in this study were observed to have a more evenly mixed population of IgM+ and IgG+ cells. While this Ig isotype-mixed population of cells within a cell line may interfere with the results obtained during gene expression analysis, it allowed for the separation of a single cell line, one individual, based on the surface expression of the Ig isotype. The cell line GM12876 was thus separated by flow cytometry based on Ig surface expression. Consistent with the results above, the IgG+ subline was more resistant toward anti-CD20 mAb treatment relative to the IgM+ subline.The developmental/activation status of LCLs was examined more closely for evidence of immunoglobulin class-switching among a group of sensitive versus resistant cell lines by flow cytometry. Sensitive lines were predominantly IgM+ cells [IgG-switched cells can be associated with a more activated status. In mice, IgG memory cells have been shown to be more likely to differentiate into antibody-secreting plasma cells following re-stimulation with antigen compared to IgM memory cells ,66. Memb+ cells ,70. HoweDifferences in gene expression, as well as differences in homotypic aggregation between resistant and sensitive cells, suggest that B cell activation status affects sensitivity to anti-CD20 mAbs. Based on this hypothesis, the glucocorticoid prednisolone was used as an immunosuppressant to deactivate and thus sensitize resistant cell lines in this study. Prednisone is presently used concurrently as a component of the cancer drug combination R-CHOP , prednisone) for treatment against B cell malignancies. This combination regimen is typically used for leukemia and lymphomas. Rituximab treatment may also be used for a variety of autoimmune conditions such as rheumatoid arthritis, myasthenia gravis, multiple sclerosis, antiphospholipid syndrome, and potentially, systemic lupus erythematosus . MKL1 gene, a transcriptional activator controlling the expression of cytoskeletal genes. A polymorphism in MKL1 was associated with mAb resistance and exhibited ethnic stratification suggesting the efficacy of anti-CD20 mAb therapy may be impacted by ethnicity. In addition, results suggested that B cell developmental/activation status likewise influences sensitivity toward anti-CD20 mAb therapy, with some increase in sensitivity occurring following extended pretreatment with the immunosuppressant prednisolone. Exploring potential protective mechanisms toward complement-mediated mAb therapy suggests that while CD20 is constitutively shed from cells, it is the kinetics of membrane repair following complement fixation that distinguishes sensitive from resistant cells.The purpose of this study was to pharmacogenomically assess several hundred ethnically diverse lymphoblastoid cell lines for response to anti-CD20 mAb therapy to identify genes affecting sensitivity or having prognostic value. Results provided several insights. Multiple gene candidates were identified with a focus on the