In order to explore the potential patient population who could benefit from anti PD-1/PD-L1 mono or combination therapies, this study aimed to profile a panel of immunotherapy related biomarkers  and targeted therapy biomarkers  in NSCLC.in situ hybridization.Tumor samples from 297 NSCLC patients, including 156 adenocarcinomas (AD) and 129 squamous cell carcinomas (SCC), were analyzed using immunohistochemistry, immunofluorescence, sequencing and fluorescence 43.1% of NSCLC patients had PD-L1 positive staining on ≥ 5% tumor cells (TC). Furthermore, dual color immunofluorescence revealed that the majority of PD-L1/CD8 dual positive tumor infiltrating lymphocytes (TIL) had infiltrated into the tumor core. Finally, combined analysis of all eight biomarkers showed that tumor PD-L1 positivity overlapped with known alterations in NSCLC oncogenic tumor drivers in 26% of SCC and 76% of AD samples.Our illustration of the eight biomarkers’ overlap provides an intuitive overview of NSCLC for personalized therapeutic strategies using anti-PD-1/PD-L1 immune therapies, either as single agents, or in combination with targeted therapies. For the first time, we also report that PD-L1 and CD8 dual positive TILs are predominantly located within the tumor core. Lung cancer is the most common cause of cancer related mortality, estimated to be responsible for 1.59 million deaths, representing 19.4% of all cancer deaths worldwide in 2012 (GLOBOCAN2012). Non-small cell lung cancer (NSCLC), accounting for about 85% of all lung cancer, compromises different histological subtypes which include adenocarcinoma (AD), squamous cell carcinoma (SCC), large cell carcinoma and other types. Despite advances in improving early diagnosis, combining surgery with chemotherapy and/or radiotherapy, and understanding molecular genetics to apply personalized therapies, NSCLC still has a poor prognosis with 5-year relative survival rates remaining around 15% [Cancer immunotherapy was crowned as ‘Breakthrough of the Year 2013’ in celebrating its remarkable efficacy in many cancer patients . BlockadPD-L1 is the major ligand of PD-1 and shows normal broad expression in dendritic cells, macrophages, mast cells, T cells, B cells, endothelial and epithelial cells . Within Following demonstration of monotherapy efficacy, a number of NSCLC clinical trials are now exploring anti-PD-1/PD-L1 antibodies in combination with chemotherapy , 15 or wEGFR, KRAS, ALK, ROS1 and MET) in NSCLC.Thus, in order to assess the population of patients who could potentially benefit from single agent or combination therapies using immune checkpoint inhibitors, we profiled a panel of IMT-C related biomarkers  and oncogenic biomarkers with relevant targeted therapeutic drugs (p = 0.0304) or marginally significantly higher when using ≥ 25%  as a cut off.PD-L1 expression on tumor cells was successfully evaluated on 297 Chinese NSCLC patient samples including 156 AD, 129 SCC and 12 other types. The patients’ clinical information are summarized in Table th edition of the AJCC staging system based on tumor size and extension (T), lymph node involvement (N) and the presence of distant metastasis (M) [p < 0.0001), older (p = 0.0321), smoker (p < 0.0001), high histologic grade (p = 0.0012) or SCC (p = 0.0412) patients, but did not show any difference when comparing surgically resectable (stage I-IIIa) with non-resectable (stage IIIb-IV) patients , smoker (p = 0.0008), higher histologic grade (p = 0.0002) and surgically non-resectable (p = 0.0004) patients. The higher grades of regional lymph node metastatic (p = 0.0064) and distant metastatic (p = 0.0058) patient tumors contributed to the significance of higher PD-L1 expression in later stage patients.The correlation between tumor cell PD-L1 expression and patients’ clinical parameters was analyzed within the whole cohort. Patients’ histologic grade and clinical stages were defined according to the 7asis (M) . PD-L1 e p = 0.031, smokerEGFR, KRAS, MET, ALK and ROS1 gene abnormalities in the same cohort, dependent on tumor sample availability (Table EGFR mutations were detected in 75 out of 297 cases (25.3%) including 10 SCC and 63 AD. There were two EGFR resistance mutations observed in the AD group, one was T790M/exon19 deletion dual mutation and the other was exon 20 insertion. Both patients were PD-L1 negative. KRAS mutations were found in 14 out of 240 cases (5.8%) including 2 SCC and 10 AD patients. Among 5 (out of 183) patients with more than 5 copies of the MET gene, all were AD but none were SCC. MET protein expression positivity was observed in 35 out of 291 (12.0%), occurring in 9 SCC and 23 AD patients (3 other types). ALK rearrangements were observed in 12 patient samples  including 3 SCC and 9 AD. Three ROS1 rearranged patients were identified only within the AD group. None of the five aforementioned NSCLC driver gene aberrations showed any statistical association with PD-L1 positivity.To understand the relationship between tumor cell PD-L1 positivity and other lung cancer tumor driver gene alterations, especially those with available targeted therapeutic agents, we profiled ty Table . EGFR muEGFR mutated and 3 (3%) ALK rearranged cases, including one EGFR/ALK dual positive case. Approximately one third (15/44) of these EGFR/ALK tyrosine kinase inhibitor (TKI)-eligible patients had PD-L1 expression on ≥5% of TC. Two thirds (6/9) of KRAS mutant patient samples and three quarters (3/4) of MET FISH positive samples also had PD-L1 expression on ≥5% of TC. Within the SCC group, there were 6 EGFR mutated and 2 ALK rearranged cases. 4 out of 8 EGFR/ALK TKI-eligible patients and 1 out of 2 KRAS mutant patient samples had PD-L1 expression on ≥5% of TC. When using a PD-L1 positivity cut-off of ≥5% of tumor cells, there were 76% (22 out of 29) PD-L1 positive AD patient samples which harbored one or more of the 5 LC tumor driver alterations. Since the PD-L1 positivity rate in SCC was higher and LC tumor driver abnormalities were rarer compared to AD, only 26% (10 out of 39) of PD-L1 positive SCC patient samples harbored one or more of the LC tumor driver gene abnormalities. When using PD-L1 positivity on ≥ 50% of tumor cells as a cut off, despite the decrease in positive case numbers, the percentage of overlapping cases remained similar, with 67% AD (8 out of 12) and 33% SCC (4 out of 12) cases showing overlap.Overall, there were 91 AD and 77 SCC cases with completed analysis of tumor cell PD-L1 expression and all 5 NSCLC driver genes. Within the AD group, there were 42 (46%) p < 0.0001) (Table p < 0.0001)  was observed in 52% of patient samples (95 out of 183), including 23% (42/183) cases showing PD-L1 expressed on 1-10% of IC and 29% (53/183) showing PD-L1 expressed on >10% of IC  Figure .The expression of PD-1 and CTLA-4 on tumor infiltrating IC was successfully evaluated in 190 patients. Almost all patients showed PD-1  or CTLA-4  positivity on IC. The positive staining prevalence of both biomarkers was comparable between SCC and AD Table . FurtherIn order to explore interactions between the tumor and immune system, PD-L1 and CD8 expression on tumor cells and/or immune cells was assessed using a dual immunofluorescence (IF) assay on surgically resected samples from 95 NSCLC patients. CD8 positive tumor infiltrating lymphocytes (TILs) presented in all 95 cases. Based on the tumor cell PD-L1 staining status, we classified these 95 NSCLC patient samples into two groups: PD-L1 positive  and PD-L1 negative . The positive group was represented by a higher number of SCC patients (25/45), whilst AD patients were dominant in the negative group (32/50). Furthermore, we found that CD8 positive TILs localized to different tumor areas between the two groups. 71% (32/45) of PD-L1 positive group tumors had CD8+ lymphocytes infiltrated within the tumor core, while 98% (49/50) of PD-L1 negative group tumors had CD8+ lymphocytes distributed only within the stroma Figure .Finally, PD-L1 and CD8 dual positive lymphocytes were identified in 34 patient samples. Interestingly, 27 (79%) of them had PD-L1/CD8 dual stained lymphocytes infiltrated within the tumor core Figure . FurtherGiven that evidence of significant and durable anti-tumor efficacy has been demonstrated using PD-1/PD-L1 inhibitors in several NSCLC clinical trials –9, numerDue to some tantalizing hints of correlations between clinical responses and high PD-L1 expression on TC and/or tumor infiltrating IC , 11–13, The correlation between clinical response to PD-1/PD-L1 inhibitors and increased tumor cell PD-L1 on TC or tumor infiltrating IC has been reported previously. The FDA approved both the “narrow” usage of Keytruda in PD-L1 positive NSCLC and “broad” usage of Opdivo as second line treatments, regardless of PD-L1 expression status. Whether or not to use PD-L1 expression as a prospective patient selection biomarker for anti-PD-1/PD-L1 immunotherapies remains a challenging question. In this study, the anti-PD-L1 antibody E1L3N was used for IHC analysis. This antibody generated comparable data to that of the SP263 antibody used in AstraZeneca's clinical trials . With E1L3N, we have found that the prevalence of PD-L1 positivity on both TC and IC were higher in SCC than in AD. Since all samples used for this study were from treatment naive NSCLC patients, we were not be able to provide a PD-L1 positivity cut off to correlate with clinical response to immunotherapy. In all statistical analyses, PD-L1 expression on tumor cells was treated as a continuous variable instead of using a positivity cut off. Furthermore, the IC were usually diffused in the tumor centers or stroma, which made it challenging for the pathologists to provide a precise percentage. Therefore, our IHC positivity criteria for biomarkers  on IC was defined as any positive staining on IC, regardless of percentage.In the Keynote 001 study, 10.7% of NSCLC patients (3/28) with PD-L1 staining of < 1% achieved an overall response upon Pembrolizumab treatment [et al, Type I patient tumors which were PD-L1 positive and contained TILs were most likely to respond to PD-1/PD-L1 inhibitors. Interestingly, our data show that within the PD-L1 positive group, there is a significant enrichment of SCC tumors versus AD. The majority of the PD-L1 tumor positive group patient samples contained CD8+ lymphocytes infiltrated into the tumor core, whilst the PD-L1 negative group patient samples displayed CD8+ lymphocytes largely within the stroma. Furthermore, PD-L1 and CD8 dual positive lymphocytes were largely observed to have infiltrated within the centers of tumors with high PD-L1 expression. Based on our data and known mechanisms, these observations suggest that tumor core colocalization of PD-L1 positive tumor cells and PD-L1/CD8 dual positive lymphocytes may represent the optimal scenario for maximal tumor cell killing when treating with PD-1/PD-L1 inhibitors.To explore the incidence of CD8+ lymphocytes and their colocation within NSCLC tumors, dual color IF for PD-L1 and CD8 was used to analyze 95 NSCLC patient samples in our study. Our PD-L1 positive and negative groups matched perfectly with the type I and type IV tumors respectively proposed by Teng . AccordiEven within PD-L1 positive NSCLC patient subgroups, the best objective response rate using single agent anti-PD-1/PD-L1 therapies has been around 45%. In order to enhance and extend the therapeutic benefit of immunotherapy to a broader population, a variety of combination strategies have been proposed or tested clinically. In this study, we explored the overlap between PD-L1 tumor cell expression and genetic alterations in commonly known oncogenic driver genes associated with LC. Our data reveal that the degree of overlap is much higher in AD than in SCC (76% vs 26%) and that furthermore, almost all patients with significant overlap expressed PD-1 or CTLA-4 on IC. The overlap between PD-L1 TC positive and PD-1 or CTLA-4 positive on IC were both very high, at 88.0% and 96.5%, respectively. Fully understanding the relationships between PD-L1 expression and other immune checkpoints, as well as response biomarkers for existing targeted therapies, will be crucial in guiding the development of rational combination approaches.Our biomarker data also showed interesting differences between SCC and AD. Overall, a higher proportion of SCC samples were PD-L1 positive, regardless of the patients’ clinical characteristics. These patient tumors also had higher CD8+ lymphocyte counts, especially within the tumor core and showed less PD-L1/oncogenic driver overlap than AD. In contrast, AD had a lower proportion of PD-L1 positive patients. The PD-L1 positive population was enriched in older, smoker and more advanced stage patients and two thirds of the PD-L1 positive AD tumor samples showed overlap with LC genetic drivers. Accordingly, these different disease characteristics suggest that SCC and AD patients may potentially require different therapeutic strategies to derive maximal benefit. For instance, SCC patients may ultimately be more responsive to immunotherapy while AD patients may potentially benefit more from combination approaches utilizing IMT-C with TKIs.In conclusion, this is the first comprehensive study of a large NSCLC cohort, not only to explore the expression of PD-L1 on tumor and infiltrating immune cells, but also to analyze the relationship between PD-L1 expression and other important NSCLC genetic drivers. Also, for the first time, we report that PD-L1 and CD8 dual positive TILs are predominantly located within the tumor cores. Taken together, these results suggest that there may be potential in using therapeutic strategies combining anti PD-1/PD-L1 immune therapies as either single agents or in combination with targeted therapies.NSCLC tumor specimens from 297 patients were collected and included 214 cases from the Shanghai Chest Hospital  collected between 2009 and 2012, and 83 cases from the ‘IGNITE’ clinical trial (D7913C00074). Prior written informed consent was obtained from all patients and the study protocol was approved by the ethics committees at Shanghai Chest hospital. These samples comprised 235 surgical samples and 62 biopsies. Formalin fixed and paraffin embedded (FFPE) sections were stained with hematoxylin and eosin (H&E) and reviewed by pathologist to confirm the NSCLC diagnosis for all cases.To achieve a more objective statistical comparison between AD and SCC, 156 AD and 129 SCC were collected. For the same reason, 91 surgically non-resectable (stage IIIb-IV) cases were enrolled in order to more accurately compare with the 206 surgically resectable (stage I-IIIa) cases. Patients’ median age was 65 years and 169 patients were ‘ever smokers’ who had current or previous smoking histories  for 30 minutes. For PD-1, sections were treated with peroxidase blocking solution  for 5 minutes. Sections were then incubated with primary antibody at room temperature for 60 minutes. After washing twice with TBS-T, sections were incubated with the EnVision+ -HRP labeled secondary antibody  for 30 minutes. After a further two washes in TBS-T, slides were finally visualized using DAB substrate-chromagen .PD-L1 and PD-1 IHC staining were performed using a rabbit anti-human PD-L1 (E1L3N) monoclonal antibody  or anti-PD-1 antibody . The IHC procedure is described briefly as follows. Deparaffinized and rehydrated FFPE sections were immersed in high pH target retrieval solution in a pressure cooker  at 97°C for either 35 minutes (PD-L1 staining) or 15 minutes (PD-1 staining). Peroxidase blocking was then performed as follows. For PD-L1, sections were treated with 2.5% HMET and CTLA-4 IHC staining was performed using a rabbit monoclonal anti-total cMET (SP44) antibody  and a goat anti-CTLA-4 monoclonal antibody  using a Ventana automatic immunostainer . MET staining followed the standard Ventana protocol, whilst the CTLA-4 staining procedure was as follows: antigen retrieval at 95°C for 64 minutes, primary antibody incubation at 37°C for 28 minutes and secondary antibody incubation at 37°C for 16 minutes.For IHC result interpretation, PD-L1 expression was evaluated both on tumor cells (TC) and tumor infiltrating immune cells (IC), while PD-1, CTLA-4 and OX40 expression was only evaluated on IC. PD-L1 positivity on TC was defined by positive TC percentage regardless of staining intensity using 5%, 25% or 50% as cut off, while the positivity on IC was defined by any positive staining on IC using 1% or 10% as cut off. PD-1, CTLA-4 and OX40 positivity were defined the same as PD-L1 without cut off setting. The existence of IC was defined as the presence of immune cells located within the stroma or tumor core [DNA was isolated from frozen tissues using the Puregene DNA extraction kit  according to the manufacturer's instructions. Extracted DNA was quantified using a Nanodrop 2000 Spectrophotometer . For EGFR mutation detection, the concentration of each DNA sample was normalized to 0.4 ng/μL. For KRAS mutation detection, the concentration of each DNA sample was normalized to 0.66 ng/μL.EGFR Gene 29 Mutations Fluorescence Polymerase Chain Reaction (PCR) Diagnostic Kit and Human KRAS Gene 7 Mutations Fluorescence Polymerase Chain Reaction (PCR) Diagnostic Kits  were used for the EGFR and KRAS mutation detections in this study. All experiments were performed according to the manufacturer's instructions.Human MET gene copy number change or ALK & ROS1 gene rearrangements. The MET probe was generated by directly labeling BAC (CTD-2270N20) with SpectrumRed-dUTP , and the CEP7- Spectrum Green probe  for the centromeric regions of chromosome 7 used as internal controls. The ALK break-apart FISH probe kit  was used according to the manufacturer's instructions. The break-apart probe sets of ROS1 N- and C-termini were generated by directly labeling BAC DNA  with SpectrumGreen-dUTP  and SpectrumRed-dUTP  respectively. The NSCLC cell lines H2228 [ALK and ROS1 break-apart FISH test respectively. FISH assays were performed as previously described [Dual-color FISH was performed to assess es H2228  and HCC7es H2228  were useMET gene copy number was conducted by scoring 50 tumor nuclei; tumors with MET average gene copy number ≥5 were defined as positive. For ALK or ROS1 break-apart analysis, the whole slide was screened and tumors meeting the following criteria were defined as ALK or ROS1 rearrangement positive. 1) Broken apart: more than one set of broken apart of N-terminal and C-terminal signals exist in ≥15% tumor cells; 2) N-terminal deletion: more C-terminal signals in addition to broken apart signals in ≥15% tumor cells tumors [FISH signals were observed using an Olympus BX61 fluorescence microscope equipped with the appropriate filters. Enumeration of s tumors .PD-L1 and CD8 dual-color immunofluorescence was performed on FFPE tissue sections using rabbit anti-human PD-L1 (E1L3N) monoclonal antibody  and monoclonal mouse anti-human CD8 antibody . Briefly, the dual-color IF procedure was performed as follows: FFPE sections were deparaffinized and rehydrated. The antigen retrieval was then performed in a pressure cooker  using high pH target retrieval solution at 97°C for 35 minutes . Slides were then covered with a mixture of two primary antibodies and incubated at room temperature for 60 minutes, followed by two washes in TBS-T and incubation with a mixture of goat anti-rabbit Alexa Fluor 488  and donkey anti-mouse Alexa Fluor 555 secondary antibody  for 30 minutes. Following two additional washes in TBS-T, slides were mounted with DAPI . Placenta and MDA-MB-231 were used as PD-L1 positive control, whilst tonsil was used as CD8 positive control.IF signals were observed by the same equipment as FISH. Green fluorescence staining on cell membranes represented PD-L1 positive expression, while CD8 positive expression was recognized by red fluorescent dye staining on cell membranes. Cells lacking fluorescence signals were defined as PD-L1 and/or CD8 negative.p-value of less than 0.05 was considered statistically significant. The analyses were performed using R (version 3.1.0).PD-L1 expression on tumor cells was treated as a continuous variable. The association between clinical characteristics and PD-L1 expression on tumor cells was evaluated in the whole cohort and in AD and SCC patients separately. PD-L1 expression among subgroups defined by binary clinical characteristics were compared using the Wilcoxon rank sum test. PD-L1 expression among subgroups defined by categorical clinical characteristics were compared using the Kruskal-Wallis rank sum test. If a significant difference was observed, the Wilcoxon rank sum test was used to perform pair-wise comparisons between each pair of the subgroups. PD-L1 expression among subgroups defined by ordinal clinical characteristics were compared using the Kruskal-Wallis rank sum test and the Spearman's rank correlation rho. The difference in prevalence of PD-L1 among subgroups was analyzed using the Fisher's Exact Test. No correction for multiple comparisons was performed. A two-sided


The changes in the levels of intestinal biochemicals provided a distinctive biochemical signature unique to each antibiotic-supplemented group. These biochemical signatures were characterized by increases in the levels of metabolites of amino acids , fatty acids , nucleosides , and vitamins (e.g. nicotinamide). These results provide the framework for future studies to identify natural chemical compounds to improve poultry growth performance without the use of in-feed antibiotics.Although dietary antibiotic growth promoters have long been used to increase growth performance in commercial food animal production, the biochemical details associated with these effects remain poorly defined. A metabolomics approach was used to characterize and identify the biochemical compounds present in the intestine of broiler chickens fed a standard, unsupplemented diet or a diet supplemented with the antibiotic growth promoters, virginiamycin or bacitracin methylene disalicylate. Compared with unsupplemented controls, the levels of 218 biochemicals were altered  in chickens given the virginiamycin-supplemented diet, while 119 were altered  with the bacitracin-supplemented diet. When compared between antibiotic-supplemented groups, 79 chemicals were altered  in virginiamycin-  This improvement in poultry growth performance has been achieved, in large part, through advances in animal genetics, health, and nutrition, including the use of in-feed antibiotic growth promoters such as virginiamycin and bacitracin methylene disalicylate. Dietary antibiotics have been used in the food animal industry for more than 60 years, not only to control infectious diseases, but also to increase feed efficiency and improve growth performance3. In chickens, subtherapeutic, in-feed antibiotics can increase body weight gain up to 8% and decrease the feed conversion ratio (feed intake/body weight gain) up to 5%, both compared with an antibiotic-free diet4. However, use of antibiotic growth promoters in food animal production has led to the development of antibiotic resistance among the commensal gut microflora, thus increasing the zoonotic risk such as potential to be transferred to humans8.The average commercial broiler consumes 3.2 kg of feed over 35 days to achieve 1.8 kg of body weight, compared with more than 20 kg of feed over 112 days to attain the same weight in the 1920’s13. Alternatively, antibiotics were suggested to improve growth performance through an anti-inflammatory effect directed toward the intestinal epithelium14. With the advent of novel molecular biology and bioinformatics techniques, it is now clear that changes in the host intestinal inflammatory response18, as well as the structure and diversity of the gut microbial community28, occur when antibiotics are introduced into animal diets. Based on these studies, dietary antibiotic supplementation was hypothesized to promote an optimal and balanced microbiota with reduced capacity to evoke an inflammatory response and increased efficiency of energy harvest from nutrients30.The mechanisms through which dietary antibiotics exert their growth promoting effects remain to be established. Antibiotics were originally thought to improve animal growth through reductions in the number and diversity of the normal bacterial flora present in the gut, which in turn, increased the bioavailability of nutrients available to the host and/or reduced the production of microbial metabolites deleterious to animal growth31. Subsequently, Cox et al.32 reported that exposure of mice to antibiotics early in life induced long-term metabolic effects by accelerating the development of a normal, age-related microbiota. However, definitive linkage of particular gut bacterial populations to intestinal metabolic changes remains to be established33. The current study was undertaken to characterize the combined host- and microbiome-derived metabolic alterations in the chicken gut following dietary antibiotic supplementation to identify potential chemical metabolites that might be used in lieu of dietary antibiotics to improve poultry growth performance.In a mouse model of antibiotic growth promotion, administration of dietary antibiotics altered the composition and metabolic capability of the gut microbiota by selecting for bacterial species capable of metabolizing complex carbohydrates to short-chain fatty acids, thus extracting a higher proportion of available calories for energy expenditureDietary supplementation with 20 g/ton of the broad spectrum antibiotic, virginiamycin, increased chicken body weight gain by 10.1% between days 0 and 21 of age compared with chickens fed an unsupplemented diet (p < 0.05). Similarly, chickens fed a diet containing 50 g/ton of the narrow spectrum antibiotic, bacitracin methylene disalicylate, had 7.9% greater body weight gain compared with birds given an unsupplemented diet (p < 0.05).vs. control groups, the levels of 156 chemicals were increased and 62 were decreased; in the bacitracin vs. control groups, 96 chemicals were increased and 23 were decreased; in the bacitracin vs. virginiamycin groups, 43 chemicals were increased and 36 were decreased; and in the control vs. both antibiotics groups, 132 chemicals were increased and 46 were decreased.A total of 706 biochemicals were identified in the intestinal contents of chickens fed an unsupplemented, control diet, or a diet supplemented with virginiamycin or bacitracin methylene disalicylate. In the virginiamycin vs. control, bacitracin vs. control, and virginiamycin vs. bacitracin groups. RFA of the virginiamycin vs. control groups gave a predictive accuracy of 85.7%, while that of bacitracin vs. control groups was 78.5%. Among 7 samples tested from each dietary group, 6 samples from both the virginiamycin and bacitracin groups were predicted to belong to their respective group, while the remaining sample was predicted to belong to the control group. Of 7 control group samples, one was predicted to belong to the virginiamycin group and two were predicted to belong to the bacitracin group. By contrast, RFA of the virginiamycin vs. bacitracin groups gave a predictive accuracy of 65.0%, suggesting that when compared with each other, dietary supplementation with either antibiotic produced a less characteristic biochemical signature compared with the antibiotic vs. control comparisons. Among the biochemicals classified as the most biochemically important for distinguishing between the 3 dietary groups, metabolites of amino acids (33.0%), fatty acids (30.0%), and nucleosides (23.3%) accounted for the majority of biochemicals in the virginiamycin vs. control groups  (2.96-fold increase), eicosapentaenoate (2.55-fold increase), 16-hydroxypalmitate and stearate (both 2.42-fold increases), arachidate (2.39-fold increase), 10-nonadecenoate (2.30-fold increase), palmitate (2.24-fold increase), and 3-hydroxylaurate (1.51-fold increase).Fatty acids and their metabolites also contributed to the biochemical signatures separating chickens given the antibiotic-supplemented diets, particularly the bacitracin-supplemented group, from unsupplemented controls Fig. . Many lovs. unsupplemented controls included inosine , N-methyl adenosine , 5-methyl uridine , xanthosine , cytidine , uridine , and pseudouridine  , N-carbamoylaspartate (2.26-fold increase), and dihydroorate (2.03-fold increase). The levels of nicotinamide were increased in the virginiamycin vs. control (10.8-fold increase) and bacitracin vs. control (5.45-fold increase) groups, whereas its metabolites quinolinate (6.06-fold increase) and nicotinate (1.62-fold increase) were elevated only in virginiamycin vs. control groups  Fig. . Other nups Fig. . NicotinStreptomyces virginiae as a mixture of two macrocyclic lactone peptolides, virginiamycin M and virginiamycin S, both of which bind to the bacterial 50 S ribosomal subunit to synergistically inhibit protein synthesis4. Virginiamycin M is a polyunsaturated cyclic peptolide while virginiamycin S is a cyclic hexadepsipeptide34. Dietary supplementation of chickens with virginiamycin decreased intestinal colonization by Clostridium perfringens35, and decreased the severity and mortality due to necrotic enteritis caused by C. perfringens36, both compared with unsupplemented controls. Bacitracin is a mixture of more than 10 related cyclic peptides produced by Bacillus subtilis and B. licheniformis that disrupt bacterial cell wall synthesis by inhibiting dephosphorylation of lipid pyrophosphate4. Dietary supplementation of chickens with bacitracin reduced gut colonization by C. perfringens and Enterococcus faecalis37, but increased the number of Salmonella enterica, compared with unsupplemented controls38. Compared with chickens fed an unsupplemented diet, intestinal microbiome analyses of chickens fed virginiamycin- and/or bacitracin-supplemented diets have generally revealed a decreased in microbial diversity, with an increase in Enterococcus and Lactobacillus spp., although a decreased frequency of L. salivarius has been noted28. Other investigators have reported an altered bacterial composition, but no change in gut microbiome richness or diversity, associated with virginiamycin- or bacitracin-supplemented diets, compared with antibiotic-free diets39.Virginiamycin and bacitracin methylene disalicylate are common growth enhancers used in the poultry industry. Virginiamycin is a streptogramin antibiotic produced by 41. Increased activity of the kynurenine pathway is internally consistent with decreased levels of indolelactate and serotonin following antibiotic supplementation. Serotonin (5-hydroxytryptamine) receptors are found throughout the intestinal ileum and associated smooth muscle42. In the small intestine, serotonin enhances the rate at which intestinal contents move through the digestive system. Increased body weight gain in antibiotic-supplemented diets might be related, in part, through decreased serotonin levels leading to increased residence time and absorption of intestinal nutrients. Consistent with the increased levels of quinolinate following antibiotic supplementation, nicotinamide metabolism and the NAD biosynthetic pathway were also shown to be increased in chickens given the virginiamycin- or bacitracin-containing diets. Interestingly, NMN, which is produced from nicotinamide, was decreased in virginiamycin-supplemented birds, with a trend for decreased levels following bacitracin supplementation, suggesting that nicotinamide might be shuttled to nicotinate biosynthesis. Indeed, animals in the virginiamycin-supplemented group had significantly increased nicotinate levels compared with unsupplemented controls.The levels of amino acid metabolites, particularly those of lysine and tryptophan, were substantially altered by dietary supplementation with virginiamycin or bacitracin methylene disalicylate. Tryptophan is metabolized by two major pathways, either through kynurenine leading to niacin and associated cofactors, including nicotinamide adenine dinucleotide (NAD), or through a series of indole-related compounds leading to serotonin and melatonin. Dietary supplementation with either virginiamycin or bacitracin methylene disalicylate increased the levels of kynurenine, as well as its metabolites, kynurenate and quinolinate, in the chicken gut. Kynurenine and kynurenate play important roles in the regulation of inflammation and the adaptive immune response, as well as multiple neurological pathways43. Increased levels of PUFAs in the ileum of bacitracin-supplemented birds, therefore, might be the result of decreased intestinal absorption. PUFAs are important as substrates for inflammatory and anti-inflammatory fatty acids, such as the prostaglandins, leukotrienes, and thromboxanes44. Omega-3 fatty acids with a C=C double bond at the third carbon atom from the end of the carbon chain, such as eicosapentaenoate, are thought to have more anti-inflammatory properties, while omega-6 fatty acids, such as arachidonate, contribute to inflammatory reactions44. Increased levels of eicosapentaenoate following antibiotic supplementation in the current study lends support to the non-antibiotic, anti-inflammatory theory of antibiotic growth promotion14. Those growth-related metabolites are shown in Kyoto encyclopedia of genes and genomes pathway (KEGG) and human metabolome database (HMDB), further studies are required to summarizing important/abundant metabolites pathway in chickens. In summary, this study compared the metabolome profiles of the intestinal contents of chickens fed an unsupplemented diet with animals given a diet containing the antibiotic growth promoters virginiamycin or bacitracin methylene disalicylate. The results demonstrated that antibiotic supplementation had profound effects on the levels of a wide variety of chemical metabolites, particularly amino acids, fatty acids, nucleosides, and nicotinamide-related compounds. Further, these altered metabolite levels provided a biochemical signature unique to each antibiotic supplementation group when compared with unsupplemented controls. Future investigations of the chemical compounds identified in this study might provide new approaches to enhance food animal growth without the use of antibiotics.One of the most striking features of the current dataset is the increase in levels of many long chain fatty acids, particularly polyunsaturated fatty acids (PUFAs), in the intestine of bacitracin-supplemented, but not virginiamycin-supplemented, chickens. PUFAs are not commonly found in bacteria, and while chickens can synthesize PUFAs from dietary linolenate and linoleate, much of the PUFA content in chicken tissues is thought to originate from ingested sourcesad libitum. Animal husbandry followed guidelines for the care and use of animals in agricultural research45. All experimental protocols were approved by the Small Animal Care Committee of the Beltsville Agricultural Research Center.Forty-five-day-old commercial broiler chickens  were housed in electrically-heated battery starter cages . Chickens were raised in starter cages until 14 days of age and transferred to finisher cages where they were kept until the end of the experimental period. Feed and water were provided 46, or the basal diet supplemented with 20 g/ton (22 ppm) virginiamycin  or 50 g/ton (55 ppm) bacitracin methylene disalicylate   were fed from hatch with a corn- and soybean meal-based unsupplemented, basal diet (control) formulated to meet or exceed the National Research Council’s nutrient requirements for broiler chickensvs. control, bacitracin methylene disalicylate vs. control, virginiamycin vs. bacitracin methylene disalicylate) following median scaling, log transformation, and imputation of missing values, if any, with the minimum value observed for each compound. Standard statistical analyses of log-transformed data were performed using Array Studio software . For analyses that were not standard in Array Studio, the programs R  or JMP  were used. Changes in biochemical levels with p ≤ 0.05 were considered statistically significant. An estimate of the false discovery rate (FDR) was obtained by calculating the q-value to account for the false positives that normally occur in metabolomics-based studies. Random Forest Analysis (RFA) was performed by computing the Mean Decrease Accuracy (MDA) as a measure of biochemical importance to a classification.A two-tailed Student’s t-test was used to compare body weight gains and feed conversion ratios of chickens fed the unsupplemented and virginiamycin- and bacitracin methylene disalicylate-supplemented diets. ANOVA was used to identify the biochemicals whose levels were significantly altered among the three dietary groups (virginiamycin


The membrane-bound molecules programmed death 1 (PD-1) and its ligand PD-L1 (PD-1/PD-L1) belong to the immune checkpoint pathway. PD-1 pathway downregulates effector T cells in immune response, thereby causing immune suppression. Recent studies have revealed that membrane-bound PD-1 and PD-L1 also have soluble forms. These soluble forms increase the complexity and diversity of the composition and function of the PD-1/PD-L1 signaling pathway. However, the exact roles of these molecules remain unknown. The objective of this systematic review was to elucidate the biological significance of soluble PD-1/PD-L1 in human cancers and evaluate whether they are potential diagnostic, therapeutic, or prognostic biomarkers. We expect to provide new clues for future research on soluble PD-1/PD-L1 pathway in human malignant tumors. Malignant tumor cells use various methods of immune suppression to resist antitumor immunity. One of these methods is modifying the PD-1/PD-L1 pathway, which is called the “immune checkpoint” . The actPD-1 is mainly expressed on different immune cells and has two ligands, namely PD-L1 (B7-H1 or CD274) and PD-L2 (B7-DC or CD273) . AlthougT-cell immune responses are vital in adaptive antitumor immune responses through the direct killing of target tumor cells or indirect inhibition by cytokines . The PD-PD-1 gene was discovered in 1992 as an upregulated gene in a T-cell hybridoma and hematopoietic progenitor cell line [The ell line . The aa ell line .PD-1 is expressed on active T cells, B cells, natural killer T cells, and myeloid cells such as dendritic cells (DCs), and activated monocytes , 23. PD-The two ligands of PD-1 are the B7 family molecules, PD-L1  and PD-L2  . PD-L1 iThe expression profile of PD-L1 is considerably more promiscuous than that of PD-1. Cells of the hematopoietic lineage, including active T cells, B cells, NK cells, DCs, monocytes, and macrophages, can express mPD-L1. It is also expressed on activated vascular endothelial cells, cultured bone marrow–derived mast cells and mesenchymal stem cells . Further2+ mobilization as well as long-term effects such as cell growth retardation [The inhibitory signaling of the PD-1 pathway was initially analyzed in the B cell line, IIA1.6, by using a chimeric molecule consisting of a PD-1 cytoplasmic region and an IgG Fc receptor type IIB extracellular region (FcPD). In the IIA1.6 cell line, co-crosslinking of B cell receptors (BCRs) and FcPD induced the phosphorylation of tyrosine residues in both ITSM and ITIM. Only the phosphorylated tyrosine residue in ITSM recruits SHP-2 through its SH2 domain and later phosphorylates the SHP-2 molecule. Subsequently, phosphorylated SHP-2 dephosphorylates the proximal well-known signal transducers of BCR, such as Ig α/β and Syk, which cause the deactivation of downstream molecules, including PLCγ2, PI3K, and ERK. Finally, the deactivated signal transducers lead to the suppression of acute-phase responses such as Caardation . In summ+ T and CD8+ T cells [In T cells, the PD-1 pathway attenuates TCR signals through similar mechanisms. PD-1 downregulates the effector phase of T-cell immune responses by elevating the threshold of T-cell activation, inhibiting T-cell proliferation, and promoting activated T-cell apoptosis. The mechanism of PD-1 signaling is associated with dephosphorylation of molecules belonging to the TCR pathway and the transmission of suppressive signals . PD-1 li T cells , 47. Not T cells .Numerous costimulatory molecules in immunoregulation pathways assume two forms of expression, namely the membrane-bound and soluble forms. The soluble form of molecules is usually generated by proteolytic cleavage of the membrane-bound form of the costimulatory proteins, as in the case of soluble tumor necrosis factor  and sB7-Five splice variants of PD-1 mRNA transcripts have been cloned from human peripheral blood mononuclear cells: flPD-1, PD-1 Deltaex2, PD-1 Deltaex3, PD-1 Deltaex2,3, and PD-1 Deltaex2,3,4  . MoreoveTumor-related mPD-1 and mPD-L1 contribute to tumor immune escape , 65. ImmSeveral studies on the functions of sPD-1 are based on animal models. In a study on murine hepatocarcinoma, the eukaryotic expression plasmid encoded sPD-1 protein was constructed, and its significant improvement in the antitumor immunity was proven . Later, As aforementioned, the importance of the PD-1 checkpoint pathway in T-cell anergy and immunosuppression has been confirmed. In thisin vitro experiments. Blockade of tumor PD-1 pathway by hydrodynamic injection of plasmid DNA encoding sPD-1 and tumor-derived heat shock protein-70 (HSP70) peptide complexes reduced pulmonary metastasis of B16F1 melanoma cells and therefore increased the OS rate in female C57BL/6 mice [in vitro coadministration of human papilloma virus-16 E7 DNA vaccine with sPD-1 DNA considerably improved E7-specific CD8+ T-cell responses, leading to valid antitumor effects against E7-expressing tumors [In addition, the use of sPD-1 combined with other agents produced promising outcomes L/6 mice . Similarg tumors . The codg tumors . Considep = 0.013) and OS (p = 0.006) [A few clinical studies have analyzed the relationship between the level of sPD-1 in blood and clinicopathological characteristics in patients with cancer for evaluating the predictive role of sPD-1 (Table = 0.006) . By cont= 0.006)  assessedIn vitro experiments, CD4+ T lymphocytes were cocultured with synovial fluid mononuclear cells. The addition of PD-1 or PD-L1 fusion proteins at a concentration range higher than 20 ng/mL led to a significantly increased level of T-cell proliferation which can express mPD-1 or mPD-L1. This finding suggested that the properties of mPD-1 and mPD-L1 are upregulated by their soluble forms.In contrast to sPD-1, a higher number of studies has been conducted on the mechanisms and functions of sPD-L1 in humans than in animal models . Moreover, in this study, the adenocarcinoma patients with higher levels of sPD-L1 had better prognosis than did low-level patients (p = 0.028). However, on the contrary, other studies have revealed that the sPD-L1 levels may indicate a poor prognosis or treatment resistance [+ and CD8+ T lymphocytes to either tumor cell-derived sPD-L1 or mature DCs-derived sPD-L1 induced apoptosis. Similarly, Zhang et al. [p < 0.001). In addition, the median OS in the low- and high-level groups were 26.8 (95% CI: 26.2∼27.4 months) and 18.7 months (95% CI: 15.9∼21.5 months), respectively. This suggested that patients with a low sPD-L1 levels may have a longer survival time. A French multicenter clinical trial revealed that patients with elevated sPD-L1 experienced a poorer prognosis (p < 0.001) than did the controls, and the sPD-L1 level returned to its normal value after complete remission of DLBCL. Therefore, sPD-L1 may be a potent predicting biomarker in DLBCL, which indicates the utility of alternative therapeutic strategies [On the basis of the predictive role of sPD-L1, Zheng et al.  designedsistance , 79, 82.sistance  discoverg et al.  reportedrategies . Severalrategies  and renarategies . HoweverIn recent years, with the growth of economies and improvement in living standards, cancer incidence and mortality have increase significantly . Cancer In addition, the treatment strategies targeting PD-1/PD-L1 with mAbs such as nivolumab, pembrolizumab, and atezolizumab and so on exhibited promising results and fundamentally changed cancer treatments . HoweverThe PD-1 pathway has generated immense academic and commercial interest in the fight against cancer . The appThis article does not contain any studies with human participants or animals performed by any of the authors.


A two-dimensional (2D) material placed on an atomically flat substrate can lead to the formation of surface nanobubbles trapping different types of substances. In this paper graphene nanobubbles of the radius of 7–34 nm with argon atoms inside are studied using molecular dynamics (MD). All modeled graphene nanobubbles except for the smallest ones exhibit an universal shape, i.e., a constant ratio of a bubble height to its footprint radius, which is in an agreement with experimental studies and their interpretation using the elastic theory of membranes. MD simulations reveal that argon does exist in a solid close-packed phase, although the internal pressure in the nanobubble is not sufficiently high for the ordinary crystallization that would occur in a bulk system. The smallest graphene bubbles with a radius of 7 nm exhibit an unusual “pancake” shape. Previously, nanobubbles with a similar pancake shape were experimentally observed in completely different systems at the interface between water and a hydrophobic surface. These structures are usually created layer by layer, and sometimes, atoms and molecules can be trapped between layers, which results in bubbles, blisters and nanodrums of nanoscale height10. The formation of these enclosures were first considered undesirable defects of the surface. However, later studies showed that they possess several interesting properties, including a giant pseudo magnetic field6 and extreme internal pressure9, and their presence can adjust phonon-electron interactions11. These structures can also be used as hydrothermal reactors12, as surface modifiers7 and for the visualization of chemical reactions13. Graphene nanobubbles and blisters on metalic substrates produced by bombarding with noble gas ions15 are actively studied and could be used for novel gas storage technologies.Graphene is a basic material used to create various heterostructures that have been actively studied and have shown potential for many electronic and optical applications9 is assumed to be present in the substance trapped inside the heterostructures. These pressures can lead to a phase transition that is strongly affected by the surface interaction between the substrate and the two-dimensional (2D) crystal. This confinement ordering has already been discovered in carbon nanotubes both experimentally16 and theoretically17. However, because of the small radius of the nanotube and, consequently, the small number of atoms and molecules inside it, it is more appropriate to treat such a phase transition as an ordering of atoms and molecules. The phase transition inside nanobubbles leads to intermediate states wherein the system consists of billions of atoms, and its thermodynamic behavior is understood and largely determined by the interaction with the interface.A high pressure of up to 1 GPa8 the consistent experimental AFM study of geometry of nanobubbles in 2D materials was performed. It was shown that the shape of the nanobubbles with the radius more than 50 nm exhibits universal scaling, i.e. the ratio of the bubble height (H) to the radius of its footprint (R) is constant in a wide range of bubble sizes and depends only on type of 2D material used . In addition to these experiments, the elastic theory of membranes was used for theoretical calculation of nanobubble shape and mechanical properties. This theory validates the experimental observations and yields the expression for the ratio of the maximum nanobubble’s height to the radius of it’s footprint (H/R) for round-type nanobubbles. In the experiments8 the substance inside the nanobubbles was unknown. Therefore there was no possibility to estimate adhesion energy magnitude between trapped substance and 2D-crystal or substrate which was used as a parameter in the elastic theory of the membranes. Instead, the adhesion energy was fitted so that theoretically predicted H/R ratio matches with experimental measurements.The pressure inside graphene nanobubbles is determined by their shape and hence could be experimentally evaluated using atomic force microscopy (AFM). In the work18 showed that to correctly apply this theory to atomically thin and micron-sized membranes, the dependence of Young’s modulus and bending rigidity on the size of the system should be accounted for. Therefore, verifying the elastic theory of membranes with the help of molecular dynamics (MD) will be useful. In atomistic modeling, all material parameters can be calculated, and the graphene nanobubble takes shape spontaneously. In general, MD simulations could play a valuable role in evaluating the assumptions of the elasticity theory of nanoscale membranes and in providing a benchmark system for validating analytic theories.Another issue associated with application of the elastic theory of membranes to modeling of graphene nanobubbles is related to the fact that all material properties, such as Young’s modulus and adhesion energies, are assumed to be constant. It is not obvious. In fact, one study8.In this paper, the MD method is used to investigate graphene nanobubbles. Here we use a graphene sheet with graphite substrate. Together with the substance trapped inside, these two parts compose the graphene nanobubble. Nanobubbles with radii in the range of 7–34 nm are studied. The first goal of this paper is to study state of the matter inside graphene nanobubbles, and in particular, to show if solid state of the matter can be observed. The second goal is to study the nanobubbles shape and to see if it fits to the predictions of the standard theory of elastic membranes19.It is shown that argon is in the solid state of the matter with a close-packed crystal structure in all the nanobubbles with various radii. The thermodynamic states of the observed crystal structures in the pressure-temperature (P-T) diagram are located considerably below the melting curve of the bulk argon. We attribute this behavior to the stabilizing role of the interface between the 2D crystal and the substrate. It is also shown that the results provided by theory of elastic membranes agree well with those obtained by atomistic modeling. We also report here the existence of so-called “pancake” nanobubbles, which have not been observed in heterostructures yet, and which contradicts the theory of elastic membranes, but have been found at the interface between highly oriented pyrolytic graphite and waterThe MD method is used to study the properties of graphene nanobubbles. The model of the graphene nanobubble is presented schematically in Fig. 20 which is known to describe well the mechanical properties of graphene and graphite21. The interaction between argon atoms is described by Lennard-Jones potential 20. The resulting parameters agree with the previously used ones (see Table Carbon-carbon parameters mentclass2pt{minim(i)8:h is the height at a particular point, and r is the radius at that point. The two graphene layers are consist of the same number of carbon atoms, hence the bonds in the upper layer are stretched. The corresponding average strain is of order The cubic box is used in the simulations. Firstly, two graphene layers are generated, they are stacked the same as in graphite: the bond length is 1.418 Å, the distance between layers is 3.35 Å. Then the upper graphene sheet is curved according to a previous experimental study(ii)23. Periodic boundary conditions are applied in the in-plane (xy) directions. Non-periodic and fixed boundary conditions are applied in z direction, so that particles do not interact across the boundary and do not move from one side of the simulation box to the other. Two types of minimization were performed, MD and conjugate gradient descent, which yielded the same final results, except for the smallest nanobubble. In that case, the final results depend on the method of minimization, and we obtain two types of nanobubbles with the same number of argon atoms, regular and pancake. During the relaxation stage, the NPT ensemble is imposed on the substrate, and the force component perpendicular to the surface is set to zero. The target pressure for NPT ensemble is set to 0 bars, the target temperature for NPT ensemble is set to 300 K, which allows the relaxation of the stresses that occur in the substrate due to the initial artificial formation of the nanobubble. The 2D crystal and argon atoms are allowed to move in the NVT ensemble. All temperatures for NVT ensemble are set to 300 K. When the stresses in the substrate are removed, the substrate atoms are fixed, the 2D crystal and argon atoms continue to be set in the NVT ensemble. The MD time step for all calculations is set to 1 fs. The number of time steps to calculate one nanobubble varies from 5 to 20 million depending on the bubble size.Calculations are performed using the software package, LAMMPSIt should be noted, although the initial shape of the nanobubble is set to the experimental one eq. (iii)24. The per-atom stress tensor is evaluated according to ref.25. After averaging the per-atom stress tensor and obtaining the total stress tensor of the argon atoms, the pressure is calculated as a minus trace of the obtained stress tensor.After the energy of the system stabilizes, we assume that equilibrium is achieved, and statistical information can be gathered. During the statistic acquisition stage, the NVT ensemble is imposed on the 2D crystal and argon atoms, the substrate atoms are fixed, and properties such as the shape of the nanobubble, structural properties of argon, and stresses in the 2D crystal are calculated. To evaluate the pressure inside the nanobubble, the volume is calculated using the Voronoi tessellationA typical calculation consists of three stages: (i) construction of initial configuration, (ii) relaxation and (iii) statistical acquisition.27. The CNA uses a decomposition of the radial distribution function and provides direct interpretation of various features of the radial distribution function in terms of atomic structure. It can be used to identify atoms in particular environment, such as FCC, HCP, BCC or icosahedral.To analyze the obtained crystal structure of solid argon inside graphene nanobubbles, we use common neighbor analysis (CNA)28.Visualization is done by software package VMDThe datasets generated during the current study are available from the corresponding author on reasonable request.After relaxation, the argon inside all considered graphene nanobubbles with various radii is found to be in the solid state see Fig. . For the30 , which agrees well with ab initio calculations and experiments.To validate equation , Young’s32. In our case, γGB = γSB because the 2D crystal and substrate consist of the same material. This adhesion energy is also calculated in this work. Three layers of graphene in contact with argon atoms are considered. The potential energy Ucomposite of this system is also calculated. Then, only argon atoms are considered at the same pressure and the same temperature of T = 300 K, and their potential energy Uargon is evaluated. Finally, the potential energy of the three layers of graphene, Ugraphene, is computed. Adhesion energies γGB and γSB are evaluated as (Ucomposite − Uargon − Ugraphene)/Sarea. For two different argon pressures, 86 MPa and 291 MPa, we calculate γGB = γSB to be 0.0049 eV/Å2 and 0.0052 eV/Å2, respectively. Because these values are very similar, for estimation, we take the average of these two values, The adhesion energy between the graphene and the substrate is calculated as the work required to separate graphene from the substrate. For the AIREBO potential, we obtain a value of The calculated values of the H/R ratio for nanobubbles 2–6 , low energy electron microscopy (LEEM) and synchrotron-based photoemission electron microscopy (XPEEM) make possible to investigate both the shape of the nanobubbles and the structure of trapped material. Experimental research of graphene nanobubbles filled with argon on Ir14 provides direct evidence of argon cluster formation at and above room temperature which supports the existence of solid argon inside graphene nanobubble. The direct comparison between results of this work and experimental study14 can not be done due to fundamental difference in types of substrate. In our cause the substrate is graphene and interaction between 2D crystal and substrate governed by Van der Waals forces. When substrate is metallic as in study14 the interaction between the 2D crystal and the substrate has a complex nature related to the redistribution of the charge density between atoms10.AFM studies33 shows that at pressure 100 MPa and temperature 260 K approximately three argon layers are constructed on the substrate. These pressure and temperature are close to the parameters in largest nanobubbles that is simulated (see Table Argon is solid at room temperature at a pressure which is significantly lower than that shown by the P-T diagram see Fig.  and than35. We assume that this suggests that these two systems are highly analogous. The emergence of the pancake shape is a manifestation of the complicated interplay between surface interactions and the inner state of trapped substances.Nanobubble 1 in Table 8, which was previously used to describe the morphology of graphene nanobubbles. The dimensionless shape and the stress distribution calculated from MD are in good agreement with the elastic theory of membranes. We also found very small nanobubbles with an exotic pancake shape that has not been reported so far in the case of heterostructured nanobubbles. However, this shape has been observed for nanobubbles at the interface between water and highly oriented pyrolytic graphite.Argon trapped in small graphene nanobubbles with a radius of less than 33 nm does exist in a solid close-packed phase with a mixture of FCC and HCP lattices. The pressure of argon in these nanobubbles is considerably lower than the pressure required for the ordinary crystallization to occur in a bulk system. Therefore, these objects present good examples of physical systems in which the phase state is highly affected by interface interactions. Compared with nanotubes, which can only accommodate a few dozen atoms inside, the heterostructured nanobubbles can accumulate millions of atoms and molecules, and therefore can be treated as true thermodynamic systems. In this work, we observed a layered structure of argon atoms inside graphene nanobubbles. The shape of the observed nanobubbles, except for the smallest one, obeyed a universal shape law, i.e., a constant ratio of height to radius, independent on the nanobubble radius. This is consistent with the elastic theory of membranesWe expect that a subsequent increase in the nanobubble radius will lead to a pressure drop inside nanobubble and will eventually lead to the solid-liquid phase transition in the confined argon system. This research clearly demonstrates the possibility that nanobubbles in heterostructures can be used to investigate the fundamentally interesting phenomenon of phase transition in confined systems.Side view of considered nanobubblesVideo 1Video 2


It is found that the cracks are formed preferentially in the zigzag directions which are consistent with that observed from tensile deformation. Specifically, the boundary condition is found to exert an obvious influence on the stress distribution and transmission during the impact process, which eventually influences the penetration energy and crack growth. For similar sample size, the circular shape graphene possesses the best impact resistance, followed by hexagonal graphene membrane. Moreover, it is found the failure shape of graphene membrane has a strong relationship with the initial kinetic energy of the projectile. The higher kinetic energy, the more number the cracks. This study provides a fundamental understanding of the deformation mechanisms of monolayer graphene under impact, which is crucial in order to facilitate their emerging future applications for impact protection, such as protective shield from orbital debris for spacecraft.The excellent mechanical properties of graphene have enabled it as appealing candidate in the field of impact protection or protective shield. By considering a monolayer graphene membrane, in this work, we assessed its deformation mechanisms under hypervelocity impact (from 2 to 6 km/s), based on a serial of  It is seen that they could only reproduce the formation of three cracks after perforation, which is different from the experimental observation . Moreover, since the energy delocalization is realized through stress wave propagation, a comprehensive understanding about how the boundary will influence the wave transmission is a necessity, which however is lacking in previous studies.Theoretically, graphene appears as good candidate for impact protection due to its high in-plane Young’s modulus and low mass density, which leads to a superior speed of sound (~22.2 km/s). Such high speed of sound could efficiently transmit the concentrated tensile stress (in the impact area), and thus rapidly delocalize the impact energyTherefore, in this work, we will first discuss the stress distribution and transmission during impact by varying the size of the projectile and also the sample shape. Afterwards, emphasis will be put on the failure shape of the graphene membrane, by examining influence from the projectile velocity, the relationship between crack length and penetration energy, as well as the stress wave.x direction (armchair edge in y direction). The projectile is located in the middle of the graphene sample, and its centre has an initial distance of ~78.5 Å with the graphene centre. To isolate the influence from thermal fluctuations, the initial system temperature was chosen as 1 K.The fracture behaviour of graphene under hypervelocity impact is acquired through a series of large-scale MD simulations using the open-source LAMMPS codeThe widely used adaptive intermolecular reactive empirical bond order (AIREBO) potential was employed to describe the C-C atomic interactions1921222930αβ, which is expressed as32During the simulation, the atomic stress in the graphene membrane is estimated based on the virial stress ∏i. ϖi is the effective volume of the ith atom and Ω is the volume of the whole system. mi and vi are the mass and velocity of the ith atom, respectively. Fij and rij are the force and distance between atoms i and j, respectively, and the indices α and β denote the Cartesian components. In this work, the volume of the graphene membrane is estimated by assuming the graphene as a continuum media with a thickness of h . Considering the stress states during impact, we tracked the atomic planar stress σxy in the graphene membrane based on the atomic virial stress  is chosen to initiate the impact process, which is larger than the velocities used in experiments (<1 km/s).Initially, we assess the stress distribution and also transmission during the impact process by considering a large square graphene membrane with a size of 50 × 50 nmEtot,G) and projectile  during the impact process. Here, the total energy (Etot) of the system is a sum of the kinetic energy (Eke) and potential energy (Epe). During the impact, the kinetic energy of projectile  will decrease, and in the meanwhile its potential energy  will increase due to the deformation  equals to that of the graphene membrane , which is also the penetration energy (Ep). As is seen in Etot,G almost overlaps with ΔEtot,P during the penetration process. However, they deviate from each other after penetration. Specifically, the total energy change of projectile ΔEtot,P remains as a constant after penetration, which is understandable as the simulation is under a vacuum condition. However, for graphene membrane, the energy change reaches a much larger value after penetration and then experiences a gradual increase before approaching a relatively flat profile  is equal to ΔEtot,P .ormation . Theoret profile . Such obx and y-axis of the graphene. After the projectile completely perforated (or pass through) graphene, the high stress area decreases significantly  comparing with the change of its kinetic energy . Comparing with its counterpart with all fully fixed boundaries . Considering the six preferential crack directions, a hexagonal graphene membrane is firstly assessed, which has a similar size as the above square sample with an edge length approximating 30 nm. Unlike the square graphene membrane, six clear stress fringes are formed perpendicular to the six edges, which have an average interval angle of about 60° . Such scOf interest, we also compare the atomic planar stress distribution between the fully-fixed hexagonal and square graphene membrane. Here the stress distribution is calculated at selected simulation time. From D, ~6 nm) and the thickness of graphene  is much larger than one, i.e., D/h ≫ 1, the penetration energy can be estimated from14Another important characteristic with the impact process is the failure shape of graphene after penetration. Recall ρ is the mass density, As is the strike face area , and v is the impact velocity. The first term represents the minimum inelastic energy transferred to the sample, and the second term Ed represents all other energy dissipation during impact . According to 2 square graphene membrane is considered. Projectile with a same impact velocity of 20 Å/ps but different radius ranging from 24 to 34 Å is adopted. As expected, the penetration energy increases with the projectile radius (Ep is around 4156 eV for the largest examined projectile (34 Å), which is over two times higher than the results obtained from the projectile with a radius of 25 Å (~1745 eV). When its radius is reduced to 24 Å, the projectile is bounced back with no penetration occurrence observed.Here, e radius , e.g., Ea, a’), , and , where the two directions in each pair are the inverse direction to each other  according toAs expected, with changing impact velocity, the failure shape of the graphene varies . Specifich other , and theith crack, and n is the number of cracks . x − x0)2 + (y − y0)2 = r2, with  as the projectile centre coordinate. Thus, depending on the pairs that the crack belongs to, its ideal and melt length can be easily calculated based on the coordinates of the crack tip  and the intersection  between the crack line and the melt edge according to (see where g to see Lcrack ~506 Å). It is assumed that larger projectile will induce more significant local deformation to graphene before failure, i.e., require higher penetration energy. After penetration, the stored strain energy is released and cause more bonds to break. Essentially, besides the energy loss in the impact area, majority of the penetration energy is consumed by the crack growth. Therefore, the total crack length is supposed to have a strong relationship with the penetration energy, which is seen from the simulation results in To ensure a good estimation, v2/2), in line with the previous supersonic projectile penetration studies142We then consider the failure shape of graphene under different impact velocity values, ranging from 20 to 60 Å/ps. As shown in To further reveal the velocity impacts, we compared the atomic configurations of the graphene under the velocity of 30 and 60 Å/ps. As is seen, the graphene experiences extensive elastic deformation before the onset of crack generation and propagation under 30 Å/ps. However, for the 60 Å/ps case, the impact area is melted immediately when the projectile approaches graphene, which creates a large number of dangling bonds inset of . For botIt is crucial to mention that the creation of dangling bonds  is due to the hypervelocity impact, and the time step  adopted here is accurate to reproduce this phenomenon. From the impact tests under a high impact velocity of 6 km/s, the number of breaking bonds in graphene under different time steps (ranging from 0.05 to 1 fs) agrees well with each other. As illustrated in c. As illustrated in One striking feature between c direction is ~85.6 Å, which is shorter comparing with the smaller sample (~97.5 Å). The total crack length also shows similar phenomenon. Such result could be explained from the perspective of the tensile stress wave bounced back by the fixed boundary, which is supposed to help the crack growth. Theoretically, the tensile stress wave in monolayer graphene has an ultra-high speed of 22.2 km/s (222 Å/ps). In other words, it only takes around 1.1 ps for the stress wave to reach the boundary for the square graphene membrane (size of 50 nm). Considering the simulation time before the projectile approaching the sample (~0.9 ps) under the velocity of 6 km/s, the stress wave would bounce back to the impact area at approximately 3.1 ps for the 50 nm graphene, and ~5.3 ps for the 100 nm graphene , that is, its energy decays with travelling distance. Therefore, for the lager sample, the returning stress wave also possesses much less energy, and thus exerts less impact to the crack growth. Overall, increase the graphene membrane size will weaken the influence on the crack growth from the stress wave bounced back by the boundaries.It is noted that although the larger sample shows slightly higher penetration energy (~3608 eV) than the smaller sample ~3568 eV), its crack in 68 eV, itEp* is defined as Above results have suggested that the failure shape of graphene will change with projectile radius and impact velocity. Recall the boundary influence on stress distribution and transmission during impact, here we conduct another four groups of simulations. Particularly, we revisited the square graphene with two fixed boundary, the hexagonal graphene, and the circular graphene, by applying various impact velocity ranging from 20 to 60 Å/ps. At the lowest impact velocity (20 Å/ps), no penetration is observed for the hexagonal and circular graphene membrane. As compared in Kep), i.e., it increases monotonically with the kinetic energy. Specifically, for Kep higher than ~7 keV, the graphene shows six cracks . For Kep between ~4 and 7 keV, the graphene exhibits five cracks, and the crack number decreases further if the projectile has smaller kinetic energy. These results also explain why the graphene only exhibits two or three cracks in the work by Haque et al.Before conclusion, we summarised the failure shape (the crack number) as obtained from different testings. As compared in Based on large-scale molecular dynamics simulations, we explored the fracture behaviour of monolayer graphene under hypervelocity impact. It is found that the cracks are formed preferentially in the zigzag directions which are consistent with that observed from tensile deformation. Specifically, the boundary condition is found to exert an obvious influence on the stress distribution and transmission during the impact process, which eventually influences the penetration energy and crack growth. For similar sample size, the circular shape graphene possesses the best impact resistance, followed by hexagonal graphene membrane. Moreover, it is found the failure shape of graphene membrane has a strong relationship with the initial kinetic energy of the projectile. The higher kinetic energy, the more number the cracks. For instance, for initial projectile kinetic energy higher than around 7 keV, the graphene membrane will show a hexagonal failure shape (with six cracks). In comparison, fewer cracks will appear when the kinetic energy decreases. This study provides a fundamental understanding of the deformation mechanisms of monolayer graphene under hypervelocity impact, which should shed lights on the design of graphene-based textile for bullet-proof application, or shielding structure for aerospace systems. We note that although these results are obtained from monolayer graphene under a low temperature, similar failure mechanisms are also expected under higher temperature or multi-layer graphene membrane, which still deserves further investigation.How to cite this article: Xia, K. et al. Failure mechanism of monolayer graphene under hypervelocity impact of spherical projectile. Sci. Rep. 6, 33139; doi: 10.1038/srep33139 (2016).


In vitro studies showed that MTDH provides cancer stem cell (CSC) properties in metastatic PDAC cells and contributes to anoikis resistance with epithelial characteristics in PDAC cells. We also performed in vivo studies using both orthotopic transplantation and intra-portal vein injection as experimental models of liver metastasis to examine the function of MTDH at the metastatic site. MTDH knockdown dramatically reduced the incidence of liver metastases along with epithelial features in both experimental mouse models. Collectively, MTDH facilitates metastatic colonization with putative CSC and epithelial properties in PDAC cells. PDAC cells were transiently treated with TGF-β1 to investigate the roles of MTDH on epithelial plasticity. Intriguingly, MTDH expression was negatively correlated with Twist1 expression during the Mesenchymal-Epithelial transition (MET) induction in metastatic PDAC cells. These results suggest that MTDH may contribute to MET induction via downregulation of Twsit1. Lastly, immunohistochemistry indicated that MTDH overexpression is closely associated with hematogenous metastasis and predicts poor prognosis in patients with PDAC. This is the first demonstration of MTDH function in PDAC metastatic colonization. Our data suggest that MTDH targeting therapy could be applied to control PDAC metastasis.Pancreatic ductal adenocarcinoma (PDAC) has a high metastatic potential. However, the mechanism of metastatic colonization in PDAC remains poorly understood. Metadherin (MTDH) has emerged in recent years as a crucial mediator of metastasis in several cancer types, although the biological role of MTDH in PDAC has not been investigated. Here, we demonstrated the functional roles of MTDH in PDAC progression, especially focusing on the metastatic cascade.  Surgicase model . TherefoNumerous studies described that the activation of the Epithelial-Mesenchymal transition (EMT) program confers cancer stem cell (CSC) properties, and these are responsible for tumorigenesis and metastasis , 6. In cMetadherin (MTDH), also called AEG1 or LYRIC/3D3, is a single-pass transmembrane protein encoded by a gene located on chromosome 8q22 . MTDH   Figure . Similarll lines . Furtherll lines . These rin vitro, pancreatosphere formation assay was performed in both human and murine PDAC cell lines. Using MTDH specific siRNAs  in KPCY cells, lineage YFP-labeled cancer cells from pancreatic tumor-bearing KPCY mice. After confirming MTDH knockdown efficiency in these KPCY-MTDH shRNA-1 and -2 cells  is one of the most crucial steps for metastatic colonization. To elucidate the molecular mechanism by which MTDH fosters PDAC metastatic colonization, we investigated the correlation between MTDH and E-cadherin or Twist1, a classical EMT marker in mouse PDAC metastatic cells. Unexpectedly, MTDH knockdown using siRNAs did not lead to a decrease of E-cadherin expression, but notably, increased Twist1 expression in KPC1Liv, metastatic mouse PDAC cells Figure .To further explore how MTDH is correlated with E-cadherin and Twist1 during the EMT/MET process, we evaluated these expression patterns in response to transient TGF-β1 treatment in KPC1Liv cells Figure . After tTo validate the correlation between MTDH and Twist1, Twist1 expression at MET induction was examined in MTDH-knocked down KPC1Liv cells in which EMT was induced by transient TGF-β1 treatment Figure . After EP = 0.02, chi-square test) and hematogenous dissemination after surgery  Table . To avoiNext, we estimated E-cadherin and Twist1 expression in resected human PDAC tissues by IHC staining to validate the correlation between MTDH and these expressions in PDAC. Interestingly, although there is no correlation with MTDH and Twist1, MTDH were strongly correlated with E-cadherin in primary PDAC site Figure  and 4F. In this study, we demonstrated that MTDH promotes CSC property of PDAC cells and prevents disseminating cancer cells from anoikis. Furthermore, MTDH is associated with the suppression of Twist1 expression, supporting the switch of tumor phenotype from mesenchymal to epithelial cells to accelerate metastatic colonization with epithelial plasticity. The analysis of human clinical samples indicated that MTDH is significantly associated with hematogenous dissemination, resulting in poor prognosis of patients with PDAC. Our results reveal a novel mechanistic insight of MTDH, which is functionally correlated with epithelial plasticity in metastatic cascade of PDAC Figure .MTDH was initially reported as a protein mediating metastasis of mouse breast cancer . Furtheret al. proposed that EMT contributes to the acquisition of CSCs, even though turning off Twist1, key master regulation of EMT, is necessary to acquire CSCs at the metastatic site [Meanwhile, we demonstrated that MTDH is positively correlated with MET in metastatic PDAC. Notably, some groups recently revealed that EMT and CSCs properties are not always inextricably linked , and thatic site . Furtheret al. demonstrated that MTDH regulates EMT and contributes the promotion of CSC properties in invasion (EMT phase) in breast cancer progression [Liang gression . ContrarIn addition, we identified Prrx1 as an overlapping key transcription factor among pancreatic development, regeneration and PDAC progression . Prrx1a in vitro studies, anoikis assay was utilized to evaluate both resistance to apoptosis after losing contact with the extracellular matrix and subsequent colonisation. In vivo experiments, the functional roles of MTDH in PDAC metastatic site was assessed in the intra-portal vein injection model created to exclude the invasion process from the pancreas into the systemic circulation. Our results in both experimental models indicate the crucial role for MTDH in the colonisation at the distant site.We next examined the last step of the metastatic cascade (colony formation after extravasation from blood vessels) in In this study, we demonstrated that high MTDH expression is associated with unfavorable outcome and is an independent prognostic factor in patients with PDAC. Previous reports also described that high MTDH expression is closely linked to poor prognosis in breast, hepatocellular, esophageal and colorectal cancers , 28, 29.In conclusion, we demonstrated for the first time that MTDH promotes metastasis by supporting CSC properties and epithelial plasticity in PDAC. Our experimental data suggest that MTDH facilitates MET, in part, by downregulation of Twist1 in metastatic PDAC cells. This study presents some limitations. We only analyzed the role of MTDH by knockdown in order to investigate the cellular response in physiological conditions. Further MTDH gain of function experiments are required to elucidate the correlation between MTDH and Twist1 during metastatic colonization. MTDH might be a novel target for the regulation of metastasis in PDAC. Controlling epithelial plasticity by modulating MTDH during PDAC progression may provide a new strategy for the treatment of PDAC.PDAC tissues were obtained from 134 consecutive patients who underwent microscopically curative surgical resection (R0) at the Department of General Surgery, Chiba University Hospital, Japan, from June 2006 to March 2015. All patients were histologically diagnosed with primary invasive PDAC. The patients’ characteristics are described in Table LSL-KrasG12D/+;p53R172H/+;Pdx1-cre) [Pdx1-cre;LSL-KrasG12D/+;p53fl/+;R26YFP mouse (KPCY mice) and were provided by Dr. Andrew D. Rhim (The University of Texas MD Anderson Cancer Center).The human pancreatic cell lines, PANC-1, MIA PaCa-2, Capan-1, AsPC-1, CFPAC-1, and Hs766T, were obtained from the American Type Culture Collection  The PANC-1 and MIA PaCa-2 in Dulbecco’s Modified Eagle Medium  with 10% fetal bovine serum (FBS) and antibiotics (1% penicillin and streptomycin), CFPAC-1 and Capan-2 in Iscove’s Modified Dulbecco’s Medium  with 10% FBS and antibiotics, and AsPC-1 cells in RPMI-1640 medium (Thermo Fisher Scientific) with 10% FBS and antibiotics. Mouse primary pancreatic cells were cultured and maintained as described previously . Murine dx1-cre) , whereasTM+Kits , and visualized using 0.01% 3, 3-diaminobenzidine. The staining patterns were scored as follows: low expression: 0–50% of tumor cells with positive staining; high expression: more than 50% of tumor cells with positive staining. The intensity of staining of islet cells was used as an internal positive control. The score of immunohistochemical staining was evaluated independently by three investigators. Immunofluorescence staining was carried out as described previously [Immunohistochemical staining of MTDH was performed following standard protocols. Briefly, paraffin-embedded tissue blocks were cut into 4-µm thick sections. The tissue sections were incubated with anti-MTDH antibodies  overnight at 4°C, incubated in Envisioneviously . The fol5) were plated in a 60-mm dish and incubated for 24 hours. Cells were then treated with siRNA  in LipofectamineTM RNAiMAX Transfection Reagent (Invitrogen). Cells were detached and re-plated for the cell cytotoxic assay after 24 hours of siRNA treatment. Protein was harvested from cells after culturing for 72 hours. Lentiviral transduction was performed as previously described [MTDH siRNAs  and control siRNA (AllStars negative control siRNA) were purchased from QIAGEN . Cells  according to the manufacturer’s instructions. Complementary DNA (cDNA) was synthesized from mRNA using SuperScript VILO cDNA Synthesis Kit and Master Mix . Quantitative real-time reverse transcriptase-polymerase chain reaction (RT-PCR) was performed with the Sequence Detection System ABI Prism 7300 , using the SYBR Green method with following reagents: MTDH primers  and FAST SYBR Green PCR Master MIX (Life Technologies).Total protein was purified from cultured cells with Radio-Immunoprecipitation Assay (RIPA) Buffer (SIGMA-ALDRICH) and preserved at-80°C. Thirty micrograms of protein were loaded onto a 7.5-15% XV PANTERA Gel , and transferred onto a polyvinylidene difluoride (PVDF) membrane. The membranes were blocked at room temperature for 60 minutes in 5% milk in 0.1% Tris Buffed Saline with Tween-20 (TBS-T). Membranes were incubated with anti-MTDH , anti-E-cadherin , anti-Twist1 , and anti-β-actin  antibodies overnight at 4°C, washed three times for 5 minutes each with TBS-T, and incubated with secondary antibodies . The membranes were developed using ImageQuant LAS-4000UV mini Mac  after immersion in the detection reagent. Western blots were quantified by densitometry analysis and normalized to β-actin using the Image J software.Pancreatosphere formation assays were performed as described previously . In brieTwo million cells were suspended in 100 µL PBS and incubated with antibodies for 60 minutes on ice in the dark. Antibodies used were; APC anti-human CD133 , APC anti-mouse CD133 (Prominin-1) , APC anti-CD326 (EpCAM) . After washing with PBS, cells were re-suspended in 1 mL PBS and measured by a CANTO II system (Beckton-Dickinson). All Data were analyzed using FlowJo v10.1r5 software .Three-dimensional (3D) pancreatic ductal cell culture was performed as previously described , 35. In To evaluate anoikis resistance (the resistance for apoptosis after losing contact with the extracellular matrix), 2000 KPCY cells/ml  infectedin vivo metastasis assay was conducted as previously described [4 KPCY cells infected with lentiviral constructs  into the pancreas tails under anesthesia. At 14 days after cell injection, the mice were euthanized and primary pancreatic tumor and the whole liver were removed. The volume of primary tumor was measured, and serial sections were made from the liver every 1000μm. Liver metastases were counted under the microscope.The escribed . In the 5 KPCY cells infected with lentivirus into the portal vein under anesthesia. After 14 days, the mice were euthanized and the whole liver were removed. Liver metastases were counted as previously described [In intra-portal vein injection model, female nude KSN/slc mice at the age of 9 weeks were injected with 1 × 10escribed . Animal Transient TGF-β1 treatment was performed as described previously . In brieP < 0.05 was considered significant in all analyses. Each experiment was repeated at least three times in triplicate.All statistical analyses were conducted with the Statview-J5.0 software package . Accumulative rates were calculated by using the Kaplan-Meier method and the significance of difference in survival rate was analyzed by the log-rank test. Data are expressed as mean ± SD. Survival data were evaluated using univariate and multivariate Cox proportional regression analyses. Statistically significant differences were determined by Student’s t-test, Chi-square test, or Fisher’s exact test.