Candidate pathways and genes for nasopharyngeal carcinoma based on bioinformatics study

Purpose: To reveal the potential microRNAs (miRNAs), genes, pathways and regulatory network involved in the process of nasopharyngeal carcinoma (NPC) by using the method of bioinformatics. Methods: Gene expression profiles {"type":"entrez-geo","attrs":{"text":"GSE12452","term_id":"12452"}}GSE12452 (31 NPC and 10 normal samples) and {"type":"entrez-geo","attrs":{"text":"GSE53819","term_id":"53819"}}GSE53819 (18 NPC and 18 normal samples), as well as miRNA expression profiles {"type":"entrez-geo","attrs":{"text":"GSE32960","term_id":"32960"}}GSE32960 (312 NPC and 18 normal samples) and {"type":"entrez-geo","attrs":{"text":"GSE36682","term_id":"36682"}}GSE36682 (62 NPC and 6 normal samples) were obtained from Gene Expression Omnibus database. The differentially expressed genes (DEGs) and miRNAs (DEmiRNAs) between NPC and normal samples were identified by using t-test based on MATLAB software (FDR < 0.01), followed by pathway enrichment analysis based on DAVID software (P-value < 0.1). Then, DEmiRNA-DEG regulatory network was constructed. Results: A total of 1254 DEGs and 107 DEmiRNAs were identified, respectively. Then, 16 pathways (including cell cycle) and 32 pathways (including pathways in cancer) were enriched by DEGs and target genes of DEmiRNAs, respectively. Furthermore, DEmiRNA-DEG regulatory network was constructed, containing 12 DEmiRNAs (including has-miR-615-3P) and 180 DEGs (including MCM4 and CCNE2). Conclusion: has-miR-615-3p might take part in the pathogenetic process of NPC through regulating MCM4 which is enriched in cell cycle. The DEmiRNAs identified in the present study might serve as new biomarkers for NPC.     

Gene expression profiling analysis of lung adenocarcinoma

The present study screened potential genes related to lung adenocarcinoma, with the aim of further understanding disease pathogenesis. The {"type":"entrez-geo","attrs":{"text":"GSE2514","term_id":"2514"}}GSE2514 dataset including 20 lung adenocarcinoma and 19 adjacent normal tissue samples from 10 patients with lung adenocarcinoma aged 45-73 years was downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) between the two groups were screened using the t-test. Potential gene functions were predicted using functional and pathway enrichment analysis, and protein-protein interaction (PPI) networks obtained from the STRING database were constructed with Cytoscape. Module analysis of PPI networks was performed through MCODE in Cytoscape. In total, 535 upregulated and 465 downregulated DEGs were identified. These included ATP5D, UQCRC2, UQCR11 and genes encoding nicotinamide adenine dinucleotide (NADH), which are mainly associated with mitochondrial ATP synthesis coupled electron transport, and which were enriched in the oxidative phosphorylation pathway. Other DEGs were associated with DNA replication (PRIM1, MCM3, and RNASEH2A), cell surface receptor-linked signal transduction and the enzyme-linked receptor protein signaling pathway (MAPK1, STAT3, RAF1, and JAK1), and regulation of the cytoskeleton and phosphatidylinositol signaling system (PIP5K1B, PIP5K1C, and PIP4K2B). Our findings suggest that DEGs encoding subunits of NADH, PRIM1, MCM3, MAPK1, STAT3, RAF1, and JAK1 might be associated with the development of lung adenocarcinoma.     

Identification of colorectal cancer-associated macrophage biomarkers by integrated bioinformatic analysis

The aim of this study was to explore colorectal tumor-associated macrophage (TAM) biomarkers for early diagnosis and surveillance of colorectal cancer (CRC). We used bioinformatic methods to screen array expression data of CRC-related macrophages (GEO: {"type":"entrez-geo","attrs":{"text":"GSE29214","term_id":"29214"}}GSE29214) to detect the differentially expressed genes (DEGs) between CRC-related macrophages and normal control cells. We found 431 DEGs in TAMs compared with the control group; 399 were up-regulated and 32 were down-regulated. A functional enrichment analysis showed that the DEGs were involved in positive regulation of the ERK1 and ERK2 cascade, cell activation involved in the immune response, cytokine-mediated signaling pathway, and receptor activity, all of which were significantly enriched. We constructed a protein-protein interaction (PPI) network to identify hub genes. We identified 10 hub genes: ITGB2, ITGAM, C3AR1, PTAFR, C3, CYBB, FCER1G, PLAU, STOM, and GPR84, in the PPI network. We verified the results using array expression data of peripheral blood mononuclear cells (GEO: {"type":"entrez-geo","attrs":{"text":"GSE47756","term_id":"47756"}}GSE47756). The results showed that the expression trends of CYBB, PLAU, and STOM were consistent with those found in the {"type":"entrez-geo","attrs":{"text":"GSE29214","term_id":"29214"}}GSE29214 dataset. Further verification with The Cancer Genome Atlas and Human Protein Atlas showed that the high expression of PLAU in TAMs was statistically significant (P<0.05). We concluded that PLAU may be a biomarker of CRC-associated macrophages and may have prognostic and predictive significance for clinical utility in CRC management.     

Identification of Key Genes and Pathways associated with Endometriosis by Weighted Gene Co-expression Network Analysis

Background: Endometriosis is a common gynecological disorder with high rates of infertility and pelvic pain. However, its pathogenesis and diagnostic biomarkers remain unclear. This study aimed to elucidate potential hub genes and key pathways associated with endometriosis in ectopic endometrium (EC) and eutopic endometrium (EU).Material and Method: EC and EU-associated microarray datasets were obtained from the gene expression omnibus (GEO) database. Gene set enrichment analysis was performed to obtain further biological insight into the EU and EC-associated genes. Weighted gene co-expression network analysis (WGCNA) was performed to find clinically significant modules of highly-correlated genes. The hub genes that belong to both the weighted gene co-expression network and protein-protein interaction (PPI) network were identified using a Venn diagram.Results: We obtained EC and EU-associated microarray datasets {"type":"entrez-geo","attrs":{"text":"GSE7305","term_id":"7305"}}GSE7305 and {"type":"entrez-geo","attrs":{"text":"GSE120103","term_id":"120103"}}GSE120103. Genes in the EC were mainly enriched in the immune response and immune cell trafficking, and genes in the EU were mainly enriched in stress response and steroid hormone biosynthesis. PPI networks and weighted gene co-expression networks were constructed. An EC-associated blue module and an EU-associated magenta module were identified, and their function annotations revealed that hormone receptor signaling or inflammatory microenvironments may promote EU passing through the oviducts and migrating to the ovarian surfaces, and adhesion and immune correlated genes may induce the successful ectopic implantation of the endometrium (EC). Twelve hub genes in the EC and sixteen hub genes in the EU were recognized and further validated in independent datasets.Conclusion: Our study identified, for the first time, the hub genes and enrichment pathways in the EC and EU using WGCNA, which may provide a comprehensive understanding of the pathogenesis of endometriosis and have important clinical implications for the treatment and diagnosis of endometriosis.     

A pyroptosis-related prognosis model to predict survival in colorectal cancer patients

Pyroptosis is a recently-identified pathway of host cell death that is stimulated by a range of microbial infections. Emerging evidence indicates pyroptosis plays crucial roles in tumor growth, disease progression, and migration of different cancer cells. However, the clinical significance of pyroptosis in tumor behavior prognosis, as well as the underlying mechanism in different cancers remains elusive. Here, by evaluating the expression level of pyroptosis genes in colorectal cancer (CRC) patients from the TCGA cohort and GEO cohort ({"type":"entrez-geo","attrs":{"text":"GSE39582","term_id":"39582"}}GSE39582), we identified pyroptosis-related DEGs and then built a 13-gene risk model by applying the LASSO Cox regression algorithm. Furthermore, functional analysis using GSEA and GSEV revealed that our prognostic model may function through regulating immune responses and tumor biogenesis pathways. Significant infiltration of activated immune cells (e.g. cytotoxic T cells) was observed in the low risk score group. The selected gene set was further validated in the GEO cohort. Time-dependent ROC curves confirmed that our risk score model is robust in predicting 1, 3 and 5-year overall survival in CRC patients. Overall, we have identified a pyroptosis-related gene signature that consists of 13 genes, which serves as a potent indicator of CRC prognosis. Thus, our model provides insights in how to make better clinical decision in the future.     

Identification of key gene contributing to vitiligo by immune infiltration

Background: A deeper understanding of new prognostic and diagnostic biomarkers for vitiligo, an autoimmune disease, is needed. The purpose of this study is to identify the underlying long noncoding RNAs (lncRNAs) and immune infiltration related to the cause of vitiligo. Methods: The microarray data ({"type":"entrez-geo","attrs":{"text":"GSE75819","term_id":"75819"}}GSE75819) were available to be downloaded from NCBI-GEO. Eight hub genes were identified from the Protein-protein interaction (PPI) network by the dissection of differentially expressed genes (DEG), Kyoto Gene and Genomic Encyclopedia (KEGG) expansion pathway, and Gene Ontology (GO). Further analysis based on the immune infiltration as well as the correlation between DEGs and immune cells was performed. Our conclusions were verified by using the GSE534 eventually. Results: According to our analysis, we obtained a total of 666 DEGs and 8 hub genes that include ECT2, CCT8, VRK1, UQCRH, EBNA1BP2, CRY2, IFIH1, and BCCIP, which may play an important role in vitiligo. Moreover, the immune infiltration profiles varied significantly between normal and vitiligo tissues. Compared with normal tissues, vitiligo tissues contained a greater proportion of mast cells (P<0.05). The analysis revealed that T cells regulatory (Tregs) have a negative correlation with the VRK1 expression (R=-0:77, P<0.001), whereas the mast cells resting have a positive correlation with the VRK1 expression (R=0:72, P<0.001) in vitiligo. Conclusion: The gene expression profile of vitiligo was realized by a bioinformatics method. The expressions of 8 hub genes and 22 immune cells were found, as the same as CRY2 and VRK1 have a special correlation with immune cells, which may be a significant cause of the pathogenesis of vitiligo. This provides a new idea for the diagnosis and treatment of vitiligo.     

Interaction of key pathways in sorafenib-treated hepatocellular carcinoma based on a PCR-array

This study aimed to identify the key pathways and to explore the mechanism of sorafenib in inhibiting hepatocellular carcinoma (HCC). The gene expression profile of {"type":"entrez-geo","attrs":{"text":"GSE33621","term_id":"33621"}}GSE33621, including 6 sorafenib treated group and 6 control samples, was downloaded from the GEO (Gene Expression Omnibus) database. The differentially expressed genes (DEGs) in HCC samples were screened using the ΔΔCt method with the homogenized internal GAPDH. Also, the functions and pathways of DEGs were analyzed using the DAVID. Moreover, the significant pathways of DEGs that involved in HCC were analyzed based on the Latent pathway identification analysis (LPIA). A total of 44 down-regulated DEGs were selected in HCC samples. Also, there were 84 biological pathways that these 44 DEGs involved in. Also, LPIA showed that Osteoclast differentiation and hsa04664-Fc epsilon RI signaling pathway was the most significant interaction pathways. Moreover, Apoptosis, Toll-like receptor signaling pathway, Chagas disease, and T cell receptor signaling pathway were the significant pathways that interacted with hsa04664. In addition, DEGs such as AKT1 (v-akt murine thymoma viral oncogene homolog 1), TNF (tumor necrosis factor), SYK (spleen tyrosine kinase), and PIK3R1 (phosphoinositide-3-kinase, regulatory subunit 1 (alpha)) were the common genes that involved in the significant pathways. Several pathway interaction pairs that caused by several downregulated genes such as SYK, PI3K, AKT1, and TNF, were identified play curial role in sorafenib treated HCC. Sorafenib played important inhibition roles in HCC by affecting a complicate pathway interaction network.     

Differences in key genes in human alveolar macrophages between phenotypically normal smokers and nonsmokers: diagnostic and prognostic value in lung cancer

Objective: To explore the effect of smoking on gene expression in human alveolar macrophages and the value of identified key genes in the early diagnosis and prognosis of lung cancers. Methods: We downloaded three data sets ({"type":"entrez-geo","attrs":{"text":"GSE8823","term_id":"8823"}}GSE8823, {"type":"entrez-geo","attrs":{"text":"GSE2125","term_id":"2125"}}GSE2125, and {"type":"entrez-geo","attrs":{"text":"GSE3212","term_id":"3212"}}GSE3212) from the Gene Expression Omnibus (GEO) database, including 31 non-smoking and 33 smoking human alveolar macrophage samples. We identified common differentially expressed genes (DEGs), from which we obtained module genes and hub genes by using STRING and Cytoscape. Then we analyzed the protein-protein interaction (PPI) network of DEGs, hub genes, and module genes and used David online analysis tool to carry out functional enrichment analysis of DEGs and module genes. Results: A total of 85 differentially expressed genes was obtained, including 42 up-regulated genes and 43 down-regulated genes. The Human Protein Atlas and Survival analysis showed that GBP1, ITGAM, CSF1, SPP1, COL1A1, LAMB1 and THBS1 may be closely associated with the carcinogenesis and prognosis of lung cancer. Conclusion: DEGs, module, and hub genes identified in the present study help explain the effects of smoking on human alveolar macrophages and provide candidate targets for diagnosis and treatment of smoking-related lung cancer.     

Analysis of microarray-identified genes and microRNAs associated with drug resistance in ovarian cancer

The aim of this study was to identify potential microRNAs and genes associated with drug resistance in ovarian cancer through web-available microarrays. The drug resistant-related microRNA microarray dataset GS54665 and mRNA dataset {"type":"entrez-geo","attrs":{"text":"GSE33482","term_id":"33482"}}GSE33482, {"type":"entrez-geo","attrs":{"text":"GSE28646","term_id":"28646"}}GSE28646, and {"type":"entrez-geo","attrs":{"text":"GSE15372","term_id":"15372"}}GSE15372 were downloaded from the Gene Expression Omnibus database. Dysregulated microRNAs/genes were screened with GEO2R and were further identified in SKOV3 (SKOV3/DDP) and A2780 (A2780/DDP) cells by real-time quantitative PCR (qRT-PCR), and then their associations with drug resistance was analyzed by comprehensive bioinformatic analyses. Nine microRNAs (microRNA-199a-5p, microRNA-199a-3p, microRNA-199b-3p, microRNA-215, microRNA-335, microRNA-18b, microRNA-363, microRNA-645 and microRNA-141) and 38 genes were identified to be differentially expressed in drug-resistant ovarian cancer cells, with seven genes (NHSL1, EPHA3, USP51, ZSCAN4, EPHA7, SNCA and PI15) exhibited exactly the same expression trends in all three microarrays. Biological process annotation and pathway enrichment analysis of the 9 microRNAs and 38 genes identified several drug resistant-related signaling pathways, and the microRNA-mRNA interaction revealed the existence of a targeted regulatory relationship between the 9 microRNAs and most of the 38 genes. The expression of 9 microRNAs and the 7 genes by qRT-PCR in SKOV3/DDP and A2780/DDP cells indicating a consistent expression profile with the microarrays. Among those, the expression of EPHA7 and PI15 were negatively correlated with that of microRNA-141, and they were also identified as potential targets of this microRNA via microRNA-mRNA interaction. We thus concluded that microRNA-141, EPHA7, and PI15 might jointly participate in the regulation of drug resistance in ovarian cancer and serve as potential targets in targeted therapies.     

Identification of collaboration patterns of dysfunctional pathways in breast cancer

Breast cancer (BC) is the most common malignancy among women. We aimed to illuminate the molecular dysfunctional mechanisms of BC progression. The mRNA expression profile of BC {"type":"entrez-geo","attrs":{"text":"GSE15852","term_id":"15852"}}GSE15852 was downloaded from Gene Expression Omnibus database, including 43 normal samples and 43 cancer samples. Differentially expressed genes (DEGs) in BC were screened using the t-test by Benjamin and Hochberg method. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of the selected DEGs were enriched using Hypergeomeric distribution model. In addition, functional similarity network among the enriched pathways was constructed to further analyze the collaboration of these pathways. We found 848 down-regulated DEGs were associated with 16 significant dysfunctional pathways, including PPAR signaling fatty acid metabolism, and 1584 up-regulated DEGs were related to 6 significant dysfunctional pathways, like cell cycle, protein export, and antigen processing and presentation in BC samples. Crosstalk network analysis of pathways indicated that pyruvate metabolism, propanoate metabolism, and glycolysis gluconeogenesis were the pathways with closest connections with other pathways in BC. In addition, other antigen processing and presentation, including 19 DEGs; PPAR signaling pathway, including 18 DEGs; and pyruvate metabolism pathway, including 13 DEGs were further analyzed. Our results suggested that dysfunctional of significant pathways can greatly affect the progression of BC. Several significant disorder pathways were enriched in our comprehensive study. They may provide guidelines to explore the dysfunctional mechanism of BC progression.     

Roles of the miR-139-5p/CCT5 axis in hepatocellular carcinoma: a bioinformatic analysis

Background: MiRNAs are pivotal regulators involved in proliferation, apoptosis, invasion, metastasis, epithelial-mesenchymal transition (EMT), angiogenesis, drug resistance and autophagy in hepatocellular carcinoma (HCC). The aim of this study was to investigate the influence of miR-139-5p and its target genes on the outcomes of HCC.Methods: Survival analysis of miR-139-5p in HCC was conducted in Kaplan-Meier plotter. Target genes of miR-139-5p were identified in TargetScan, miRTarBase and starBase. Gene Expression Omnibus (GEO) series were used for the validation of miR-139-5p target genes. Cox proportional regression model was also established.Results: In Kaplan-Meier plotter, 163 HCC patients were included. MiR-139-5p downregulation was significantly associated with unfavorable overall survival (OS) and disease-free survival (DFS) in HCC patients (all P < 0.001). MiR-139-5p was significantly downregulated in HCC tumors and human hepatoma cell lines (all P < 0.05). As a target gene of miR-139-5p, CCT5 was overexpressed in HCC tumor tissues and peripheral blood mononuclear cells (all P < 0.05). A negative correlation between CCT5 and miR-139-5p was found in TCGA dataset. CCT5 overexpression was significantly associated with worse OS in HCC patients (P < 0.001), which was validated in the {"type":"entrez-geo","attrs":{"text":"GSE14520","term_id":"14520"}}GSE14520 dataset (P = 0.017). CCT5 mRNA was significantly overexpressed in HCC patients with alpha-fetoprotein (AFP) > 300 ng/ml, BCLC staging B-C, TNM staging III and main tumor size > 5 cm (all P < 0.05). According to the Cox regression model of CCT5-interacting genes, HCC patients with high risk had poor OS compared to those with low risk in the TCGA dataset (P < 0.001), with the 1-year, 3-year, and 5-year ROC curves of an area under the curve (AUC) equal to 0.704, 0.662, and 0.631, respectively.Conclusions: MiR-139-5p suppresses HCC tumor aggression and conversely correlated with CCT5. The miR-139-5p/CCT5 axis might perform crucial functions in the development of HCC.     

Dysregulation of KIF14 regulates the cell cycle and predicts poor prognosis in cervical cancer: a study based on integrated approaches

Cervical cancer (CC) is the most common malignant tumor in females. Although persistent high-risk human papillomavirus (HPV) infection is a leading factor that causes CC, few women with HPV infection develop CC. Therefore, many mechanisms remain to be explored, such as aberrant expression of oncogenes and tumor suppressor genes. To identify promising prognostic factors and interpret the relevant mechanisms of CC, the RNA sequencing profile of CC was downloaded from the Cancer Genome Atlas and the Gene Expression Omnibus databases. The {"type":"entrez-geo","attrs":{"text":"GSE63514","term_id":"63514"}}GSE63514 dataset was analyzed, and differentially expressed genes (DEGs) were obtained by weighted coexpression network analysis and the edgeR package in R. Fifty-three shared genes were mainly enriched in nuclear chromosome segregation and DNA replication signaling pathways. Through a protein-protein interaction network and prognosis analysis, the kinesin family member 14 (KIF14) hub gene was extracted from the set of 53 shared genes, which was overexpressed and associated with poor overall survival (OS) and disease-free survival (DFS) of CC patients. Mechanistically, gene set enrichment analysis showed that KIF14 was mainly enriched in the glycolysis/gluconeogenesis signaling pathway and DNA replication signaling pathway, especially in the cell cycle signaling pathway. RT-PCR and the Human Protein Atlas database confirmed that these genes were significantly increased in CC samples. Therefore, our findings indicated the biological function of KIF14 in cervical cancer and provided new ideas for CC diagnosis and therapies.     

Construction of ceRNA network and identification of two differentially expressed circRNAs in hepatocellular carcinoma by bioinformatic analysis

Covalently closed circular RNAs (circRNAs) display dysregulated expression in several types of cancer. However, their functions remain largely unclear. In this work, datasets {"type":"entrez-geo","attrs":{"text":"GSE125469","term_id":"125469"}}GSE125469 and {"type":"entrez-geo","attrs":{"text":"GSE128274","term_id":"128274"}}GSE128274 of hepatocellular carcinoma (HCC) were selected from Gene Expression Omnibus (GEO) database. To identify differentially expressed genes (DEGs) in HCC and adjacent tissues, we used R package DESeq for analysis. Then, 15 DEcircRNAs, 65 DEmiRNAs, and 2084 DEmRNAs were identified comparing HCC and normal tissues. Next, to predict the target relationship of circRNA-miRNA and miRNA-mRNA in DEGs, we use the databases CircInteractome and starBase v2.0 for analysis. Finally, the ceRNA network of circRNA-miRNA-mRNA was established by Cytoscape software based on 2 DEcircRNAs (hsa_circ_0007813 and hsa_circ_0089372), 2 DEmiRNAs, and 98 DEmRNAs. In addition, we conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of DEGs to explore the function of DEGs in HCC. Functional enrichment analyses indicated DEmRNAs might be associated with HCC occurrence and progression. In general, our research reveals an important role of ceRNA’s molecular mechanism in HCC.     

Identification ACTA2 and KDR as key proteins for prognosis of PD‐1/PD‐L1 blockade therapy in melanoma

Programmed cell death protein 1 (PD‐1) /programmed cell death ligand 1 (PD‐L1) blockade is an important therapeutic strategy for melanoma, despite its low clinical response. It is important to identify genes and pathways that may reflect the clinical outcomes of this therapy in patients. We analyzed clinical dataset {"type":"entrez-geo","attrs":{"text":"GSE96619","term_id":"96619"}}GSE96619, which contains clinical information from five melanoma patients before and after anti‐PD‐1 therapy (five pairs of data). We identified 704 DEGs using these five pairs of data, and then the number of DEGs was narrowed down to 286 in patients who responded to treatment. Next, we performed KEGG pathway enrichment and constructed a DEG‐associated protein‐protein interaction network. Smooth muscle actin 2 (ACTA2) and tyrosine kinase growth factor receptor (KDR) were identified as the hub genes, which were significantly downregulated in the tumor tissue of the two patients who responded to treatment. To confirm our analysis, we demonstrated similar expression tendency to the clinical data for the two hub genes in a B16F10 subcutaneous xenograft model. This study demonstrates that ACTA2 and KDR are valuable responsive markers for PD‐1/PD‐L1 blockade therapy.     

Screening of non-alcoholic steatohepatitis (NASH)-related datasets and identification of NASH-related genes

Non-alcoholic steatohepatitis (NASH) is a common liver disease in the western world. The mechanisms behind NASH formation are poorly understood, but there may be multiple targets considering the disease’s multifactorial nature. To explore the genes related to the pathogenesis of NASH, we downloaded clinical data and gene expression of NASH patients from the Gene Expression Omnibus database (GEO). We identified 281 genes with a common expression in two NASH-related datasets ({"type":"entrez-geo","attrs":{"text":"GSE89632","term_id":"89632"}}GSE89632 and {"type":"entrez-geo","attrs":{"text":"GSE83452","term_id":"83452"}}GSE83452), suggesting that they may be related to NASH. Further study showed that Angptl4, Foxo1, and Ttc39B might be essential for NASH progression, and these have been poorly studied. Therefore, we explored their roles in NASH. Our data show that these genes participate in the development of NASH through lipid metabolism. This suggests that the three genes can be used as therapeutic targets in NASH.     

MET overexpression and intratumor heterogeneity in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is among the ten most frequent and deadly cancers, without effective therapies for most patients. More recently, drugs targeting deregulated growth factor signaling receptors have been developed, such as HGF-MET targeted therapy. We assessed MET and HGF genetic alterations and gene and protein expression profiles in ESCC patients from the Brazilian National Cancer Institute and publicly available datasets, as well as the intratumor heterogeneity of the alterations found. Our analyses showed that HGF and MET genetic alterations, both copy number and mutations, are not common in ESCC, affecting 5 and 6% of the cases, respectively. HGF showed a variable mRNA expression profile between datasets, with no alterations ({"type":"entrez-geo","attrs":{"text":"GSE20347","term_id":"20347"}}GSE20347), downregulation ({"type":"entrez-geo","attrs":{"text":"GSE45670","term_id":"45670"}}GSE45670), and upregulation in ESCC (our dataset and {"type":"entrez-geo","attrs":{"text":"GSE75241","term_id":"75241"}}GSE75241). On the other hand, MET was found consistently upregulated in ESCC compared to non-tumor surrounding tissue, with median fold-changes of 5.96 ({"type":"entrez-geo","attrs":{"text":"GSE20347","term_id":"20347"}}GSE20347), 3.83 ({"type":"entrez-geo","attrs":{"text":"GSE45670","term_id":"45670"}}GSE45670), 6.02 ({"type":"entrez-geo","attrs":{"text":"GSE75241","term_id":"75241"}}GSE75241), and 5.0 (our dataset). Among our patients, 84% of the tumors showed at least a two-fold increase in MET expression. This observation was corroborated by protein levels, with 55% of cases exhibiting positivity in 100% of the tumor cells. Intratumor heterogeneity was evaluated in at least four tumor biopsies from five patients and two cases showed a consistent increase in MET expression (at least two-fold) in all tumor samples. Our data suggested that HGF-MET signaling pathway was likely to be overactivated in ESCC, representing a potential therapeutic target, but eligibility for this therapy should consider intratumor heterogeneity.     

Granzyme family acts as a predict biomarker in cutaneous melanoma and indicates more benefit from anti-PD-1 immunotherapy

The incidence of cutaneous melanoma (CM) increased since the 1970s, and also along with an unfavorable prognosis. CM patients have been verified benefits from immunotherapy, and granzymes (GZMs) comprise more than 90% of the cytolytic granules secreted by cytotoxic T lymphocytes and nature killer cell. Therefore, it is essential to evaluate the prognostic value of GZMs in CM. A total of 633 CM patients was enrolled to access the prognostic value of GZMs. The integrated prognostic value of five GZMs was validated in TCGA-SKCM, {"type":"entrez-geo","attrs":{"text":"GSE65904","term_id":"65904"}}GSE65904, {"type":"entrez-geo","attrs":{"text":"GSE53118","term_id":"53118"}}GSE53118, {"type":"entrez-geo","attrs":{"text":"GSE19234","term_id":"19234"}}GSE19234 and {"type":"entrez-geo","attrs":{"text":"GSE22153","term_id":"22153"}}GSE22153 cohorts. GZMscore, age, Breslow''s depth and tumor stage are the independent risk factors for CM patients, risk score based on these factors was calculated in TCGA-SKCM and {"type":"entrez-geo","attrs":{"text":"GSE65906","term_id":"65906"}}GSE65906 cohorts, which could polarize the CM patients to high- and low-risk groups with diverse prognosis. Patients in low-risk group obtained the activated immune signaling pathways and response, especially for the activated CD8+ T cells, and could benefit more from anti-PD-1 therapy. A higher tumor mutation burden was observed in low-risk group, especially for the mutation of BRAF. The protect function of GZMK was confirmed by CM cell lines, overexpression of GZMK in A375 and G361 cells suppresses cell proliferation, migration, but not cell apoptosis. All in all, we revealed the prognostic value of GZMs in CM patients, which could also act as a predicted value for the selection of responders of anti-PD-1 immunotherapy.     

Integrated bioinformatics analysis for differentially expressed genes and signaling pathways identification in gastric cancer

Background: Gastric cancer (GC) has a high mortality rate in cancer-related deaths worldwide. Currently, the pathogenesis of gastric cancer progression remains unclear. Here, we identified several vital candidate genes related to gastric cancer development and revealed the potential pathogenic mechanisms using integrated bioinformatics analysis.Methods: Two microarray datasets from Gene Expression Omnibus (GEO) database integrated. Limma package was used to analyze differentially expressed genes (DEGs) between GC and matched normal specimens. DAVID was utilized to conduct Gene ontology (GO) and KEGG enrichment analysis. The relative expression of OLFM4, IGF2BP3, CLDN1 and MMP1were analyzed based on TCGA database provided by UALCAN. Western blot and quantitative real time PCR assay were performed to determine the protein and mRNA levels of OLFM4, IGF2BP3, CLDN1 and MMP1 in GC tissues and cell lines, respectively.Results: We downloaded the expression profiles of {"type":"entrez-geo","attrs":{"text":"GSE103236","term_id":"103236"}}GSE103236 and {"type":"entrez-geo","attrs":{"text":"GSE118897","term_id":"118897"}}GSE118897 from the Gene Expression Omnibus (GEO) database. Two integrated microarray datasets were used to obtain differentially expressed genes (DEGs), and bioinformatics methods were used for in-depth analysis. After gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments analysis, we identified 61 DEGs in common, of which the expression of 34 genes were elevated and 27 genes were decreased. GO analysis displayed that the biological functions of DEGs mainly focused on negative regulation of growth, fatty acid binding, cellular response to zinc ion and calcium-independent cell-cell adhesion. KEGG pathway analysis demonstrated that these DEGs mainly related to the Wnt and tumor signaling pathway. Interestingly, we found 4 genes were most significantly upregulated in the DEGs, which were OLFM4, IGF2BP3, CLDN1 and MMP1. Then, we confirmed the upregulation of these genes in STAD based on sample types. In the final, western blot and qRT-PCR assay were performed to determine the protein and mRNA levels of OLFM4, IGF2BP3, CLDN1 and MMP1 in GC tissues and cell lines.Conclusion: In our study, using integrated bioinformatics to screen DEGs in gastric cancer could benefit us for understanding the pathogenic mechanism underlying gastric cancer progression. Meanwhile, we also identified four significantly upregulated genes in DEGs from both two datasets, which might be used as the biomarkers for early diagnosis and prevention of gastric cancer.