The Molecular Characteristics and Therapeutic Implications of O-Glycan Synthesis in Pancreatic Cancer by Integrating Transcriptome and Single-Cell Data.

BACKGROUND: Glycans constitute the primary components of proteins that regulate key carcinogenic processes in cancer progression. This study investigated the significance of O-glycan synthesis in the pathogenesis, outcome, and therapy of pancreatic cancer (PC). METHODS: Transcriptomic data and clinical prognostic information of PC were acquired via TCGA and GEO databases. CSA database was used to obtain single-cell data of PC. The O-glycan biosynthesis signaling pathway and its related genes were acquired via the MSigDB platform. The nonnegative matrix factorization (NMF) clustering was utilized to construct the O-glycan biosynthesis-associated molecular subtypes in PC. The LASSO and Cox regression were utilized to build the prognostic prediction model. We utilized real-time quantitative PCR (qRT-PCR) to verify the expressed levels of model genes. Single-cell analysis was utilized to investigate the levels of target genes and O-glycan biosynthesis signaling pathway in the PC tumour microenvironment. RESULTS: We obtained 30 genes related to O-glycan biosynthesis, among which 15 were associated with the prognosis of PC. All PC samples were grouped into two distinct molecular subtypes associated with O-glycan biosynthesis: OGRGcluster C1 and OGRGcluster C2, and compared to OGRGcluster C1. PCs in OGRGcluster C2 had a more advanced clinical stage and pathological grade, worse prognosis, and more active O-glycan biosynthesis function. Immune analysis indicated that naïve B cell, CD8+ T cell, memory-activated CD4+ T cell, and monocytes displayed remarkably higher infiltration levels in OGRGcluster C1 while resting NK cell, macrophages M0, resting dendritic cell, activated dendritic cell, and neutrophils exhibited markedly higher infiltration levels in OGRGcluster C2. OGRGcluster C1 exhibited higher sensitivities to drugs, such as cisplatin, irinotecan, KRAS(G12C) inhibitor-12, oxaliplatin, paclitaxel, and sorafenib. Besides, we built the O-glycan biosynthesis-related prognostic model (including SPRR1B, COL17A1, and ECT2) with a good prediction performance. SPRR1B, COL17A1, and ECT2 were remarkably highly expressed in PC tissues and linked to a poor outcome. Single-cell analysis revealed that Oglycan biosynthesis was observed only in PC, and consistent with this, the target genes were significantly enriched in PC. CONCLUSION: We first constructed molecular subtypes and prognostic models related to O-glycan biosynthesis in PC. It is clear that O-glycan biosynthesis is related to the development, prognosis, immune microenvironment, and treatment of PC. This provides new strategies for stratification, diagnosis, and treatment of PC patients.

Identification and characterization of interferon-γ signaling-based personalized heterogeneity and therapeutic strategies in patients with pancreatic cancer.

Background: Interferon-γ (IFN-γ) is a key cytokine with diverse biological functions, including antiviral defense, antitumor activity, immune regulation, and modulation of cellular processes. Nonetheless, its role in pancreatic cancer (PC) therapy remains debated. Therefore, it is worthwhile to explore the role of Interferon-γ related genes (IFN-γGs) in the progression of PC development. Methodology: Transcriptomic data from 930 PC were sourced from TCGA, GEO, ICGC, and ArrayExpress, and 93 IFN-γGs were obtained from the MSigDB. We researched the characteristics of IFN-γGs in pan-cancer. Subsequently, the cohort of 930 PC was stratified into two distinct subgroups using the NMF algorithm. We then examined disparities in the activation of cancer-associated pathways within these subpopulations through GSVA analysis. We scrutinized immune infiltration in both subsets and probed classical molecular target drug sensitivity variations. Finally, we devised and validated a novel IFN-γ related prediction model using LASSO and Cox regression analyses. Furthermore, we conducted RT-qPCR and immunohistochemistry assays to validate the expression of seven target genes included in the prediction model. Results: We demonstrated the CNV, SNV, methylation, expression levels, and prognostic characteristics of IFN-γGs in pan-cancers. Notably, Cluster 2 demonstrated superior prognostic outcomes and heightened immune cell infiltration compared to Clusters 1. We also assessed the IC50 values of classical molecular targeted drugs to establish links between IFN-γGs expression levels and drug responsiveness. Additionally, by applying our prediction model, we segregated PC patients into high-risk and low-risk groups, identifying potential benefits of cisplatin, docetaxel, pazopanib, midostaurin, epothilone.B, thapsigargin, bryostatin.1, and AICAR for high-risk PC patients, and metformin, roscovitine, salubrinal, and cyclopamine for those in the low-risk group. The expression levels of these model genes were further verified through HPA website data and qRT-PCR assays in PC cell lines and tissues. Conclusion: This study unveils IFN-γGs related molecular subsets in pancreatic cancer for the first time, shedding light on the pivotal role of IFN-γGs in the progression of PC. Furthermore, we establish an IFN-γGs related prognostic model for predicting the survival of PC, offering a theoretical foundation for exploring the precise mechanisms of IFN-γGs in PC.

Identifying endoplasmic reticulum stress-related molecular subtypes and prognostic model for predicting the immune landscape and therapy response in pancreatic cancer.

Endoplasmic reticulum stress (ERS) is caused by the accumulation of intracellular misfolded or unfolded proteins and is associated with cancer development. In this study, pan-cancer analysis revealed complex genetic variations, including copy number variation, methylation, and somatic mutations for ERS-related genes (ERGs) in 33 kinds of cancer. Consensus clustering divided pancreatic cancer (PC) patients from TCGA and GEO databases into two ERS-related subtypes: ERGcluster A and B. Compared with ERGcluster A, ERGcluster B had a more active ERS state and worse prognosis. Subsequently, the ERS-related prognostic model was established to quantify the ERS score for a single sample. The patient with a low ERS score had remarkably longer survival times. ssGSEA and CIBERSORT algorithms revealed that activated B cells and CD8+ T cells had higher infiltration in the low ERS score group, but higher infiltration of activated CD4+ T cells, activated dendritic cells, macrophages, and neutrophils in the high ERS score group. Drug sensitivity analysis indicated the low ERS score group had a better response to gemcitabine, paclitaxel, 5-fluorouracil, oxaliplatin, and irinotecan. RT-qPCR validated that MET, MUC16, and KRT7 in the model had higher expression levels in pancreatic tumour tissues. Single-cell analysis further revealed that MET, MUC16, and KRT7 were mainly expressed in cancer cells in PC tumour microenvironment. In all, we first constructed the ERS-related molecular subtypes and prognostic model in PC. Our research highlighted the vital role of ERS in PC and contributed to further research on molecular mechanisms and novel therapeutic strategies for PC in the future.

A network pharmacology-based investigation of emodin against pancreatic adenocarcinoma.

Pancreatic adenocarcinoma (PAAD) is one of the most common malignancies worldwide with an increasing incidence and poor outcome due to the lack of effective diagnostic and treatment methods. Emerging evidence implicates that emodin displays extensive spectrum anticancer properties. Differential expression genes in PAAD patients were analyzed by Gene Expression Profiling Interactive Analysis (GEPIA) website, and the targets of emodin were obtained via Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. Subsequently, enrichment analyses were performed using R software. A protein-protein interaction (PPI) network was constructed by STRING database and Cytoscape software was used to identify the hub genes. Prognostic value and immune infiltration landscapes were explored through Kaplan-Meier plotter (KM plotter) website and the Single-Sample Gene Set Enrichment Analysis package of R. Finally, molecular docking was used to computationally verify the interaction of ligand and receptor proteins. A total of 9191 genes were significantly differentially expressed in PAAD patients and 34 potential targets of emodin were obtained. Intersections of the 2 groups were considered as potential targets of emodin against PAAD. Functional enrichment analyses illustrated that these potential targets were linked to numerous pathological processes. Hub genes identified through PPI networks were correlated with poor prognosis and infiltration level of different immune cells in PAAD patients. Perhaps emodin interacted with the key molecules and regulate the activity of them. We revealed the inherent mechanism of emodin against PAAD with the aid of network pharmacology, which provided reliable evidence and a novel guideline for clinical treatment.

Comprehensive characterization of extracellular matrix-related genes in PAAD identified a novel prognostic panel related to clinical outcomes and immune microenvironment: A silico analysis with in vivo and vitro validation.

The extracellular matrix (ECM) is a vital component of the tumor microenvironment, which interplays with stromal and tumor cells to stimulate the capacity of cancer cells to proliferate, migrate, invade, and undergo angiogenesis. Nevertheless, the crucial functions of ECM-related genes (ECMGs) in pancreatic adenocarcinoma (PAAD) have not been systematically evaluated. Hence, a comprehensive evaluation of the ECMGs is required in pan-cancer, especially in PAAD. First, a pan-cancer overview of ECMGs was explored through the integration of expression profiles, prognostic values, mutation information, methylation levels, and pathway-regulation relationships. Seven ECMGs (i.e. LAMB3, LAMA3, ITGB6, ITGB4, ITGA2, LAMC2, and COL11A1) were identified to be hub genes of PAAD, which were obviously up-regulated in PAAD and considerably linked to tumor stage as well as prognosis. Subsequently, patients with PAAD were divided into 3 clusters premised on ECMG expression and ECM scores. Cluster 2 was the subtype with the best prognosis accompanied by the lowest ECM scores, further verifying ECM's significant contribution to the pathophysiological processes of PAAD. Significant differences were observed for oncogene and tumor suppressor gene expression, immune microenvironment, and chemotherapy sensitivity across three ECM subtypes. After applying a variety of bioinformatics methods, a novel and robust ECM-associated mRNA-lncRNA-based prognostic panel (ECM-APP) was developed and validated for accurately predicting clinical outcomes of patients with PAAD. Patients with PAAD were randomly categorized into the train, internal validation, and external validation cohorts; meanwhile, each patient was allocated into high-risk (unfavorable prognosis) and low-risk (favorable prognosis) populations premised on the expression traits of ECM-related mRNAs and lncRNAs. The discrepancy in the tumor mutation burden and immune microenvironment might be responsible for the difference in prognoses across the high-risk and low-risk populations. Overall, our findings identified and validated seven ECMGs remarkably linked to the onset and progression of PAAD. ECM-based molecular classification and prognostic panel aid in the prognostic assessment and personalized intervention of patients with PAAD.

Altered polymerase theta expression promotes chromosomal instability in salivary adenoid cystic carcinoma.

Genomic instability (GIN) plays a key role in cancer progression. The disorders of polymerase theta (POLQ) were reported to contribute to GIN and progression in many cancers. Here, we found that POLQ over-expression was related to salivary adenoid cystic carcinoma (SACC) progression and poor prognosis. Then, we investigated the role and mechanism of POLQ in the GIN in SACC. GIN was assessed by chromosome staining with DAPI and Giemsa, as well as qRT-PCR of the mitosis-related gene expression. Meanwhile, PCR-SSCP was used to evaluate microsatellite instability. Modulation of POLQ expression increased chromosomal instability and enhanced the sensitivity to etoposide without impacting microsatellite stability. Mechanistically, POLQ regulated genome stability by promoting the expression of the error-prone alt-NHEJ-related protein PARP1, and down-regulating c-NHEJ- and HR-related proteins KU70 and RAD51. In vitro CCK, Transwell assays and in vivo murine xenograft models indicated that the PARP inhibitor olaparib suppressed SACC growth in the case of etoposide-induced DNA damage. Bioinformatic analysis identified CEBPB as a potential POLQ-regulating transcription factor. In summary, our research provides new insights into the mechanisms of SACC chromosomal instability and identifies new potential targets for SACC treatment.

Prognostic and immune-related value of STK17B in skin cutaneous melanoma.

Skin cutaneous melanoma (SKCM) is a common cancer of which mortality is increasing continuously. Our study conducted a series of analyses on the clinical significance of Serine/threonine kinase 17B (STK17B) in SKCM to provide a new biomarker for diagnosis and treatment. The RNA-sequence data were obtained from The Cancer Genome Atlas and Genotype-Tissue Expression databases. The data of 468 SKCM patients were divided into STK17B high- and low-expression groups and analyzed by Bioconductor package to identify the differential expressed genes. The R package of "clusterProfiler" was used for Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene-Set Enrichment Analysis analyses. A protein-protein interaction network and immune infiltration landscape were respectively constructed via STRING database and ssGSEA. STK17B had lower expression in SKCM than normal tissues. Besides, STK17B expression was significantly related to some clinicopathological characteristics in SKCM patients including T stage, Breslow depth, radiation therapy, melanoma Clark level, and pathologic stage. The Kaplan-Meier curve analyses revealed that the low expression of STK17B was correlated with poor overall survival and disease-specific survival. We constructed nomograms to predict the 1-, 3-, and 5-year survival of SKCM patients. The function enrichment analyses showed STK17B-related differential expressed genes were enriched in cellular differentiation and immune-related progress. STK17B expression level were positively correlated with infiltrating level of immune cells. In this study, we found that STK17B, which played an important role in immune infiltration, could be a new biomarker for diagnosis and prognosis in SKCM patients.

Identification of hub genes associated with COVID-19 and idiopathic pulmonary fibrosis by integrated bioinformatics analysis.

INTRODUCTION: The coronavirus disease 2019 (COVID-19), emerged in late 2019, was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The risk factors for idiopathic pulmonary fibrosis (IPF) and COVID-19 are reported to be common. This study aimed to determine the potential role of differentially expressed genes (DEGs) common in IPF and COVID-19. MATERIALS AND METHODS: Based on GEO database, we obtained DEGs from one SARS-CoV-2 dataset and five IPF datasets. A series of enrichment analysis were performed to identify the function of upregulated and downregulated DEGs, respectively. Two plugins in Cytoscape, Cytohubba and MCODE, were utilized to identify hub genes after a protein-protein interaction (PPI) network. Finally, candidate drugs were predicted to target the upregulated DEGs. RESULTS: A total of 188 DEGs were found between COVID-19 and IPF, out of which 117 were upregulated and 71 were downregulated. The upregulated DEGs were involved in cytokine function, while downregulated DEGs were associated with extracellular matrix disassembly. Twenty-two hub genes were upregulated in COVID-19 and IPF, for which 155 candidate drugs were predicted (adj.P.value < 0.01). CONCLUSION: Identifying the hub genes aberrantly regulated in both COVID-19 and IPF may enable development of molecules, encoded by those genes, as therapeutic targets for preventing IPF progression and SARS-CoV-2 infections.

GDI2 is a novel diagnostic and prognostic biomarker in hepatocellular carcinoma.

BACKGROUND: GDP Dissociation inhibitor 2 (GDI2) gene has been correlated with some important biological processes in a variety of cancers, whereas the role of GDI2 in hepatocellular carcinoma (HCC) is ill-defined. We aimed to demonstrate the relationship between GDI2 and HCC based on The Cancer Genome Atlas (TCGA) data mining. METHODS: The expression of GDI2 was compared between cancer and normal tissues of 371 HCC patients collected from TCGA-LIHC, and verified in HCC cell lines. Gene set enrichment analysis (GSEA) was applied to annotate biological function of GDI2. Furthermore, Wilcoxon rank sum test, Logistics regression, as well as Cox regression and Kaplan-Meier survival analysis, were employed to evaluate the association of GDI2 expression with clinicopathological characteristics, and survival status of HCC patients, respectively. RESULTS: It showed that the expression of GDI2 was much higher in tumor tissues than in normal tissues (P < 0.001) of HCC patients. And the elevated expression of GDI2 was correlated with more aggressive HCC tumor status, including severe primary tumor extent, advanced pathological stage, serious histologic grade, and mutated TP53 status (P < 0.05). Moreover, high GDI2 expression was strongly associated with a poor survival rate (P < 0.001). Both enrichment and immune infiltration analyses implied that GDI2-associated signaling mainly involve lipid metabolism and extracellular matrix (ECM) constructing pathways related to tumor microenvironment (TME) (P < 0.05). CONCLUSIONS: The elevated expression of GDI2 predicts poor prognosis in HCC patients, indicating that GDI2 could be applied as a predictive biomarker for diagnosis and prognosis of HCC.

INTS8 is a therapeutic target for intrahepatic cholangiocarcinoma via the integration of bioinformatics analysis and experimental validation.

Intrahepatic cholangiocarcinoma (CHOL) remains a rare malignancy, ranking as the leading lethal primary liver cancer worldwide. However, the biological functions of integrator complex subunit 8 (INTS8) in CHOL remain unknown. Thus, this research aimed to explore the potential role of INTS8 as a novel diagnostic or therapeutic target in CHOL. Differentially expressed genes (DEGs) in two Gene Expression Omnibus (GEO) datasets were obtained by the "RRA" package in R software. The "maftools" package was used to visualize the CHOL mutation data from The Cancer Genome Atlas (TCGA) database. The expression of INTS8 was detected by performing quantitative reverse transcription-PCR (qRT-PCR) and immunohistochemistry in cell lines and human samples. The association between subtypes of tumour-infiltrating immune cells (TIICs) and INTS8 expression in CHOL was determined by using CIBERSORT tools. We evaluated the correlations between INTS8 expression and mismatch repair (MMR) genes and DNA methyltransferases (DNMTs) in pan-cancer analysis. Finally, the pan-cancer prognostic signature of INTS8 was identified by univariate analysis. We obtained the mutation landscapes of an RRA gene set in CHOL. The expression of INTS8 was upregulated in CHOL cell lines and human CHOL samples. Furthermore, INTS8 expression was closely associated with a distinct landscape of TIICs, MMR genes, and DNMTs in CHOL. In addition, the high INTS8 expression group presented significantly poor outcomes, including overall survival (OS), disease-specific survival (DSS) and disease-free interval (DFI) (p < 0.05) in pan-cancer. INTS8 contributes to the tumorigenesis and progression of CHOL. Our study highlights the significant role of INTS8 in CHOL and pan-cancers, providing a valuable molecular target for cancer research.

CARD11 is a prognostic biomarker and correlated with immune infiltrates in uveal melanoma.

Uveal melanoma (UVM), the most common primary intraocular malignancy, has a high mortality because of a high propensity to metastasize. Our study analyzed prognostic value and immune-related characteristics of CARD11 in UVM, hoping to provide a potential management and research direction. The RNA-sequence data of 80 UVM patients were downloaded from The Cancer Genome Atlas database and divided them into high- and low-expression groups. We analyzed the differentially expressed genes, enrichment analyses and the infiltration of immune cells using the R package and Gene-Set Enrichment Analysis. A clinical prediction nomogram and protein-protein interaction network were constructed and the first 8 genes were considered as the hub-genes. Finally, we constructed a competing endogenous RNA (ceRNA) network by Cytoscape and analyzed the statistical data via the R software. Here we found that CARD11 expression had notable correlation with UVM clinicopathological features, which was also an independent predictor for overall survival (OS). Intriguingly, CARD11 had a positively correlation to autophagy, cellular senescence and apoptosis. Infiltration of monocytes was significantly higher in low CARD11 expression group, and infiltration of T cells regulatory was lower in the same group. Functional enrichment analyses revealed that CARD11 was positively related to T cell activation pathways and cell adhesion molecules. The expressions of hub-genes were all increased in the high CARD11 expression group and the ceRNA network showed the interaction among mRNA, miRNA and lncRNA. These findings show that high CARD11 expression in UVM is associated with poor OS, indicating that CARD11 may serve as a potential biomarker for the diagnosis and prognosis of the UVM.

An immune-related lncRNA signature for the prognosis of pancreatic adenocarcinoma.

Recent evidence suggests that aberrant expression of long non-coding RNA (lncRNA) can drive the initiation and progression of malignancies. However, little is known about the prognostic potential of lncRNA. We aimed at constructing a lncRNA-based signature to improve the prognosis prediction of pancreatic adenocarcinoma (PAAD). The PAAD samples with clinical information were obtained from The Cancer Genome Atlas and International Cancer Genome Consortium. We established an eight-IRlncRNA signature in a training cohort. The prognostic value of eight-IRlncRNA signature was validated in two distinct cohorts when compared to other four prognostic models. We continued to analyze its independence in subgroups by univariate and multivariate Cox regression. We constructed a nomogram for clinicopathologic features and 1-, 3-, and 5-year overall survival performance. Moreover, Gene set enrichment analysis and Gene Set Variation Analysis distinguished the typical functions between high- and low-risk groups. In addition, we further observed the different correlations of immune cell between eight IRlncRNAs. Eight-IRlncRNA signature appears to be a good performer to predict the survival capability of PAAD patients, and the nomogram will enable PAAD patients to be more accurately managed in clinical practice.

Identification and assessment of PLK1/2/3/4 in lung adenocarcinoma and lung squamous cell carcinoma: Evidence from methylation profile.

Lung cancer is a very aggressive cancer characterized with molecular heterogeneities in different subtypes, including lung adenocarcinoma and lung squamous cell carcinoma. However, few related molecular signatures have been established for the treatment of lung cancer subtypes. Polo-like kinase (PLK) family is a crucial regulator during cell division. Aberrant genetic and epigenetic alteration of PLK members plays a controversial role among different cancers. In this study, we performed an analysis of transcriptional and protein expression to identify overexpressed PLK1/4 and under-expressed PLK2/3 in lung cancer subtypes. We then analysed biological function of PLKs and related genes. Besides, we estimated a correlation of PLKs with patient's genders and TP53 mutation in lung cancer. Higher PLK1/4 expression was significantly associated with male patient and TP53 mutant status, separately. Moreover, we carried out a methylation profile analysis including methylation level, DNA methyltransferases correlation and survival analysis of global methylation. Global methylation survival analysis showed that prognostic value of PLK1/2/4 methylation remained the same significant trend between two lung cancer subtypes, whereas prognostic value of PLK3 methylation lacked consistency. Taken together, these results provided instructive insights into a comprehensive evaluation for advanced therapeutic strategy based on epigenetic evidences.

The novel immune-related genes predict the prognosis of patients with hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the main causes of cancer deaths globally. Immunotherapy is becoming increasingly important in the cure of advanced HCC. Thus it is essential to identify biomarkers for treatment response and prognosis prediction. We searched publicly available databases and retrieved 465 samples of genes from The Cancer Genome Atlas (TCGA) database and 115 tumor samples from Gene Expression Omnibus (GEO). Meanwhile, we used the ImmPort database to determine the immune-related genes as well. Weighted gene correlation network analysis, Cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis were used to identify the key immune related genes (IRGs) which are closely related to prognosis. Gene set enrichment analysis (GSEA) was implemented to explore the difference of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway between Immune high- and low-risk score groups. Finally, we made a prognostic nomogram including Immune-Risk score and other clinicopathologic factors. A total of 318 genes from prognosis related modules were identified through weighted gene co-expression network analysis (WGCNA). 46 genes were strongly linked to prognosis after univariate Cox analysis. We constructed a seven genes prognostic signature which showed powerful prediction ability in both training cohort and testing cohort. 16 significant KEGG pathways were identified between high- and low- risk score groups using GSEA analysis. This study identified and verified seven immune-related prognostic biomarkers for the patients with HCC, which have potential value for immune modulatory and therapeutic targets.

WGCNA identification of TLR7 as a novel diagnostic biomarker, progression and prognostic indicator, and immunotherapeutic target for stomach adenocarcinoma.

Stomach adenocarcinoma (STAD) is a malignant tumor with high histological heterogeneity. However, the potential mechanism of STAD tumorigenesis remains to be elucidated. The purpose of our research was to identify candidate genes associated with the diagnosis, progression, prognosis, and immunotherapeutic targets of STAD. Based on tumor samples from the GSE28541 dataset, weighted gene co-expression network analysis revealed 16 modules related to STAD stage and grade. The salmon module emerged as the most relevant module (cor = 0.34), and functional enrichment analysis showed that the genes in the salmon were primarily related to major histocompatibility complex, immune response, and cell differentiation. Toll-like receptor 7 (TLR7) was recognized as the real hub gene in the salmon module. Compared to normal stomach tissues, the transcriptional and translational levels of TLR7 were significantly elevated in STAD. Receiver operating characteristic curves verified that TLR7 displayed remarkable sensitivity and specificity for the diagnosis of STAD. The functions of TLR7 were primarily enriched in the regulation of Toll-like receptor signaling pathway, pattern recognition receptor signaling pathway, and innate immune response. Overexpression of TLR7 tended to indicate more advanced STAD, higher degree of STAD, and poorer prognosis of STAD. In addition, TLR7 expression was positively correlated with immune cell infiltration and immune checkpoint expression. Somatic copy number alteration of TLR7 was also significantly related to immune cell infiltration. In conclusion, this study revealed the crucial role of TLR7 in STAD and provided new perspectives for the selection of biomarkers, progression and prognosis indicators, and immunotherapeutic targets for STAD.

The nine ADAMs family members serve as potential biomarkers for immune infiltration in pancreatic adenocarcinoma.

BACKGROUND: The functional significance of ADAMs family members in the immune infiltration of pancreatic adenocarcinoma (PAAD) awaits elucidation. METHODS: ADAMs family members with significant expression were identified among differentially expressed genes of PAAD based on The Cancer Genome Atlas (TCGA) database followed by a verification based on the Oncomine database. The correlation of ADAMs in PAAD was estimated with the Spearman's rho value. The pathway enrichment of ADAMs was performed by STRING and GSEALite, respectively. The protein-protein interaction and Gene Ontology analyses of ADAMs and their similar genes were exanimated in STRING and visualized by Cytoscape. Subsequently, the Box-Whisker plot was used to show a correlation between ADAMs and different tumor grade 1/2/3/4 with Student's t-test. TIMER was applied to estimate a correlation of ADAMs expressions with immune infiltrates and immune checkpoint blockade (ICB) immunotherapy-related molecules. Furthermore, the effect of copy number variation (CNV) of ADAMs genes was assessed on the immune infiltration levels. RESULT: ADAM8/9/10/12/15/19/28/TS2/TS12 were over-expressed in PAAD. Most of the nine ADAMs had a significant correlation. ADAM8/12/15/19 expression was remarkably increased in the comparison between grade 1 and grade 2/3 of PAAD. ADAM8/9/10/12/19/28/TS2/TS12 had a positive correlation with almost five immune infiltrates. ADAM12/19/TS2/TS12 dramatically related with ICB immunotherapy-related molecules. CNV of ADAMs genes potentially influenced the immune infiltration levels. CONCLUSION: Knowledge of the expression level of the ADAMs family could provide a reasonable strategy for improved immunotherapies to PAAD.

Systemic analyses of expression patterns and clinical features for GIMAPs family members in lung adenocarcinoma.

GTPase of immunity-associated proteins (GIMAPs) are frequently prescribed as important components of immune regulation complexes, which were known to play key roles in lung adenocarcinoma. However, little is known about the function of distinct GIMAPs in lung adenocarcinoma. To address this issue, this study investigated the biological function and pathway of GIMAPs in lung adenocarcinoma using multiple public databases. Absent expression of GIMAPs was found in lung adenocarcinoma at mRNA and protein levels. While a purity-corrected value uncovered that all GIMAPs were positively associated with the immune infiltration of lung adenocarcinoma. Furthermore, the expressions of GIMAPs were considered to be negatively associated with clinical cancer stages, patient's gender and pathological tumor grades in patients with lung adenocarcinoma. Besides, higher mRNA expression of GIMAPs was significantly associated with longer overall survival of patients with lung adenocarcinoma. Taken together, these results may enable GIMAPs family members as diagnostic and survival biomarker candidates or even potential therapeutic targets for patients with lung adenocarcinoma.

T Lymphocytes: A Promising Immunotherapeutic Target for Pancreatitis and Pancreatic Cancer?

Pancreatic disorders cause a broad spectrum of clinical diseases, mainly including acute and chronic pancreatitis and pancreatic cancer, and are associated with high global rates of morbidity and mortality. Unfortunately, the pathogenesis of pancreatic disease remains obscure, and there is a lack of specific treatments. T lymphocytes (T cells) play a vital role in the adaptive immune systems of multicellular organisms. During pancreatic disease development, local imbalances in T-cell subsets in inflammatory and tumor environments and the circulation have been observed. Furthermore, agents targeting T cells have been shown to reverse the natural course of pancreatic diseases. In this review, we have discussed the clinical relevance of T-cell alterations as a potential outcome predictor and the underlying mechanisms, as well as the present status of immunotherapy targeting T cells in pancreatitis and neoplasms. The breakthrough findings summarized in this review have important implications for innovative drug development and the prospective use of immunotherapy for pancreatitis and pancreatic cancer.