Turning publicly available gene expression data into discoveries using gene set context analysis

Pro-apoptotic gene BAX is a pan-cancer predictive biomarker for prognosis and immunotherapy efficacy

BACKGROUND

Apoptosis Regulator BCL2 Associated X (BAX) is a pro-apoptotic gene. Apoptosis is one of the important components of immune response and immune regulation. However, there is no systematic pan-cancer analysis of BAX.

METHODS

Original data of this study were downloaded from TCGA databases and GTEX databases. We conducted the gene expression analysis and survival analysis of BAX in 33 types of cancer via Gene Expression Profiling Interactive Analysis (GEPIA) database. Real-time PCR and immunohistochemistry (IHC) were further performed to examine the BAX expression in cancer cells and tissues. Moreover, the relationship between BAX and immune infiltration and gene alteration was studied by the Tumor Immune Estimation Resource (TIMER) and cBioPortal tools. Protein-protein interaction analysis was performed in the STRING database. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to evaluate the enrichment analysis.

RESULTS

BAX was highly expressed in most cancers and was associated with poor prognosis in nine cancer types. In addition, BAX showed significant clinical relevance, and the mRNA expression of BAX was also strongly associated with drug sensitivity of many drugs. Furthermore, BAX may participate in proliferation and metastasis of many cancers and was associated with methylation. Importantly, BAX expression was positively correlated with most immune infiltrating cells.

CONCLUSION

Our findings suggested that BAX can function as an oncogene and may be used as a potential predictive biomarker for prognosis and immunotherapy efficacy of human cancer, which could provide a new approach for cancer therapy.

VDR is a potential prognostic biomarker and positively correlated with immune infiltration: a comprehensive pan-cancer analysis with experimental verification

The vitamin D receptor (VDR) is a transcription factor that mediates a variety of biological functions of 1,25-dihydroxyvitamin D3. Although there is growing evidence of cytological and animal studies supporting the suppressive role of VDR in cancers, the conclusion is still controversial in human cancers and no systematic pan-cancer analysis of VDR is available. We explored the relationships between VDR expression and prognosis, immune infiltration, tumor microenvironment, or gene set enrichment analysis (GSEA) in 33 types of human cancers based on multiple public databases and R software. Meanwhile, the expression and role of VDR were experimentally validated in papillary thyroid cancer (PTC). VDR expression decreased in 8 types and increased in 12 types of cancer compared with normal tissues. Increased expression of VDR was associated with either good or poor prognosis in 13 cancer types. VDR expression was positively correlated with the infiltration of cancer-associated fibroblasts, macrophages, or neutrophils in 20, 12, and 10 cancer types respectively and this correlation was experimentally validated in PTC. Increased VDR expression was associated with increased percentage of stromal or immune components in tumor microenvironment (TME) in 24 cancer types. VDR positively and negatively correlated genes were enriched in immune cell function and energy metabolism pathways, respectively, in the top 9 highly lethal tumors. Additionally, VDR expression was increased in PTC and inhibited cell proliferation and migration. In conclusion, VDR is a potential prognostic biomarker and positively correlated with immune infiltration as well as stromal or immune components in TME in multiple human cancers.

Multi-omics and immunogenomics analysis revealed PFKFB3 as a targetable hallmark and mediates sunitinib resistance in papillary renal cell carcinoma: in silico study with laboratory verification

Glycolysis-related metabolic reprogramming is a central hallmark of human cancers, especially in renal cell carcinoma. However, the regulatory function of glycolytic signature in papillary RCC has not been well elucidated. In the present study, the glycolysis-immune predictive signature was constructed and validated using WGCNA, glycolysis-immune clustering analysis. PPI network of DEGs was constructed and visualized. Functional enrichments and patients' overall survival were analyzed. QRT-PCR experiments were performed to detect hub genes' expression and distribution, siRNA technology was used to silence targeted genes; cell proliferation and migration assays were applied to evaluate the biological function. Glucose concentration, lactate secretion, and ATP production were measured. Glycolysis-Immune Related Prognostic Index (GIRPI) was constructed and combined analyzed with single-cell RNA-seq. High-GIRPI signature predicted significantly poorer outcomes and relevant clinical features of pRCC patients. Moreover, GIRPI also participated in several pathways, which affected tumor immune microenvironment and provided potential therapeutic strategy. As a key glycolysis regulator, PFKFB3 could promote renal cancer cell proliferation and migration in vitro. Blocking of PFKFB3 by selective inhibitor PFK-015 or glycolytic inhibitor 2-DG significantly restrained renal cancer cells' neoplastic potential. PFK-015 and sunitinib could synergistically inhibit pRCC cells proliferation. Glycolysis-Immune Risk Signature is closely associated with pRCC prognosis, progression, immune infiltration, and therapeutic response. PFKFB3 may serve as a pivotal glycolysis regulator and mediates Sunitinib resistance in pRCC patients.

GABPB1 plays a cancer-promoting role in non-small cell lung cancer

BACKGROUND

GABPB1, the gene that encodes two isoforms of the beta subunit of GABP, has been identified as an oncogene in multiple malignant tumors. However, the role and mode of action of GABPB1 in malignant tumors, especially in lung cancer, are not well understood and need further research.

METHODS

Our research focused on examining the biological function of GABPB1 in NSCLC (Non-Small Cell Lung Cancer). We analysed tumor data from public databases to assess the expression of GABPB1 in NSCLC  and its correlation with patient prognosis and investigated GABPB1 expression and methylation patterns in relation to the tumor microenvironment. In parallel, experiments were conducted using short hairpin RNA (shRNA) to suppress the GABPB1 gene in human lung cancer cells to evaluate the effects on cell proliferation, viability, and apoptosis.

RESULTS

GABPB1 was widely expressed in various tissues of the human body. Compared to that in normal tissues, the expression of this gene was different in multiple tumor tissues. GABPB1 was highly expressed in lung cancer tissues and cell lines. Its expression was associated with molecular subtype and cellular signalling pathways, and a high level of GABPB1 expression was related to a poor prognosis in lung adenocarcinoma patients. The expression and methylation of GABPB1 affect the tumor microenvironment. After suppressing the expression of GABPB1 in both A549 and H1299 cells, we found a decrease in cell growth and expression, the formation of clones and an increase in the apoptosis rate.

CONCLUSIONS

Our research verified that GABPB1 promotes the tumorigenesis of NSCLC and has an inhibitory effect on tumor immunity. The specific role of GABPB1 may vary among different pathological types of NSCLC. This molecule can serve as a prognostic indicator for lung adenocarcinoma, and its methylation may represent a potential breakthrough in treatment by altering the tumor immune microenvironment in lung squamous cell carcinoma. The role and mechanism of action of GABPB1 in NSCLC should be further explored.

Stroma-associated FSTL3 is a factor of calcium channel-derived tumor fibrosis

Hepatocellular carcinoma (HCC) is the most widespread histological form of primary liver cancer, and it faces great diagnostic and therapeutic difficulties owing to its tumor diversity. Herein, we aim to establish a unique prognostic molecular subtype (MST) and based on this to find potential therapeutic targets to develop new immunotherapeutic strategies. Using calcium channel molecules expression-based consensus clustering, we screened 371 HCC patients from The Cancer Genome Atlas to screen for possible MSTs. We distinguished core differential gene modules between varying MSTs, and Tumor Immune Dysfunction and Exclusion scores were employed for the reliable assessment of HCC patient immunotherapeutic response rate. Immunohistochemistry and Immunofluorescence staining were used for validation of predicted immunotherapy outcomes and underlying biological mechanisms, respectively. We identified two MSTs with different clinical characteristics and prognoses. Based on the significant differences between the two MSTs, we further identified Follistatin-like 3 (FSTL3) as a potential indicator of immunotherapy resistance and validated this result in our own cohort. Finally, we found that FSTL3 is predominantly expressed in HCC stromal components and that it is a factor in enhancing fibroblast-M2 macrophage signaling crosstalk, the function of which is relevant to the pathogenesis of HCC. The presence of two MSTs associated with the calcium channel phenotype in HCC patients may provide promising directions for overcoming immunotherapy resistance in HCC, and the promotion of FSTL3 expressed in stromal components for HCC hyperfibrosis may be responsible for the poor response rate to immunotherapy in Cluster 2 (C2) patients.

Identification and verification of potential biomarkers in sertoli cell-only syndrome via bioinformatics analysis

Sertoli cell-only syndrome (SCOS), a severe testicular spermatogenic failure, is characterized by total absence of male germ cells. To better expand the understanding of the potential molecular mechanisms of SCOS, we used microarray datasets from the Gene Expression Omnibus (GEO) and ArrayExpress databases to determine the differentially expressed genes (DEGs). In addition, functional enrichment analysis including the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) was performed. Protein-protein interaction (PPI) networks, modules, and miRNA-mRNA regulatory networks were constructed and analyzed and the validation of hub genes was performed. A total of 601 shared DEGs were identified, including 416 down-regulated and 185 up-regulated genes. The findings of the enrichment analysis indicated that the shared DEGs were mostly enriched in sexual reproduction, reproductive process, male gamete generation, immune response, and immunity-related pathways. In addition, six hub genes (CCNA2, CCNB2, TOP2A, CDC20, BUB1, and BUB1B) were selected from the PPI network by using the cytoHubba and MCODE plug-ins. The expression levels of the hub genes were significantly decreased in patients with SCOS compared to that in normal spermatogenesis controls as indicated by the microarray data, single-cell transcriptomic data, and clinical sample levels. Furthermore, the potential miRNAs were predicted via the miRNA-mRNA network construction. These hub genes and miRNAs can be used as potential biomarkers that may be related to SCOS. However, it has not been proven that the differential expression of these biomarkers is the molecular pathogenesis mechanisms of SCOS. Our findings suggest that these biomarkers can be serve as clinical tool for diagnosis targets and may have some impact on the spermatogenesis of SCOS from a testicular germ cell perspective.

An Analysis Regarding the Association Between the Nuclear Pore Complex (NPC) and Hepatocellular Carcinoma (HCC)

Background

The nuclear pore complex (NPC) is the main mediator of nuclear and cytoplasmic communication, and delaying or blocking nuclear RNA export and protein shuttling can inhibit cell proliferation and induce apoptosis. Although NPC is a research hotspot in structural biology, relevant studies in hepatocellular carcinoma are scarce, especially in terms of translation into clinical practice.

Methods

This study used a bioinformatics approach combining validation experiments to investigate the biological mechanisms that may be related with NPC. A series of experiments performed to explore the function of the Targeting protein for Xenopus kinesin-like protein 2 (TPX2) in HCC.

Results

Patients with HCC can be divided into two NPC clusters. Patients with high NPC levels (C1) had a shorter survival time than those with low NPC levels (C2) and are characterised by high levels of proliferative signals. We demonstrated that TPX2 regulates HCC growth and inhibits apoptosis in an NPC-dependent manner and contributes to the maintenance of HCC stemness. We developed the NPCScore to predict the prognosis and degree of differentiation in HCC patients.

Conclusion

NPC plays an important role in the malignant proliferation of HCC. Assessing NPC expression patterns could help enhance our understanding of tumor cell proliferation and could guide more effective chemotherapeutic strategies.

A Novel Immune-Related Gene Prognostic Index (IRGPI) in Pancreatic Adenocarcinoma (PAAD) and Its Implications in the Tumor Microenvironment

PURPOSE

Pancreatic adenocarcinoma (PAAD) is one of the most lethal malignancies, with less than 10% of patients surviving more than 5 years. Existing biomarkers for reliable survival rate prediction need to be enhanced. As a result, the objective of this study was to create a novel immune-related gene prognostic index (IRGPI) for estimating overall survival (OS) and to analyze the molecular subtypes based on this index. Materials and procedures: RNA sequencing and clinical data were retrieved from publicly available sources and analyzed using several R software packages. A unique IRGPI and optimum risk model were developed using a machine learning algorithm. The prediction capability of our model was then compared to that of previously proposed models. A correlation study was also conducted between the immunological tumor microenvironment, risk groups, and IRGPI genes. Furthermore, we classified PAAD into different molecular subtypes based on the expression of IRGPI genes and investigated their features in tumor immunology using the K-means clustering technique.

RESULTS

A 12-gene IRGPI (FYN, MET, LRSAM1, PSPN, ERAP2, S100A1, IL20RB, MAP3K14, SEMA6C, PRKCG, CXCL11, and GH1) was established, and verified along with a risk model. OS prediction by our model outperformed previous gene signatures. According to the findings of our correlation studies, different risk groups and IRGPI genes were found to be tightly related to tumor microenvironments, and PAAD could be further subdivided into immunologically distinct molecular subtypes based on the expression of IRGPI genes.

CONCLUSION

The current study constructed and verified a unique IRGPI. Furthermore, our findings revealed a connection between the IRGPI and the immunological microenvironment of tumors. PAAD was differentiated into several molecular subtypes that might react differently to immunotherapy. These findings could provide new insights for precision and translational medicine for more innovative immunotherapy strategies.

RAB39B as a Chemosensitivity-Related Biomarker for Diffuse Large B-Cell Lymphoma

Background: Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive lymphoma with an increased tendency to relapse or refractoriness. RAB39B, a member of the Ras-oncogene superfamily, is associated with a variety of tumors. Nevertheless, the role of RAB39B in DLBCL is still unknown. This study aimed to identify the role of RAB39B in DLBCL using integrated bioinformatics analysis.

Methods: RAB39B expression data were examined using TIMER, UCSC, and GEO databases. The LinkedOmics database was used to study the genes and signaling pathways related to RAB39B expression. A Protein–protein interaction network was performed in STRING. TIMER was used to analyze the correlation between RAB39B and infiltrating immune cells. The correlation between RAB39B and m6A-related genes in DLBCL was analyzed using TCGA data. The RAB39B ceRNA network was constructed based on starBase and miRNet2.0 databases. Drug sensitivity information was obtained from the GSCA database.

Results: RAB39B was highly expressed in multiple tumors including DLBCL. The protein–protein interaction network showed enrichment of autophagy and RAS family proteins. Functional enrichment analysis of RAB39B co-expression genes revealed that RAB39B was closely related to DNA replication, protein synthesis, cytokine–cytokine receptor interaction, JAK-STAT signaling pathway, NF-kappa B signaling pathway, and autophagy. Immune infiltrate analysis showed that the amount of RAB39B was negatively correlated with iDC, Tem, and CD8 T-cell infiltration. CD4⁺ T cell and DC were negatively correlated with CNV of RAB39B. DLBCL cohort analysis found that RAB39B expression was related to 14 m6A modifier genes, including YTHDC1, YTHDC2, YTHDF1, YTHDF2, YTHDF3, RBMX, ZC3H13, METTL14, METTL3, RBM15, RBM15B, VIRMA, FTO, and ALKBH5. We constructed 14 possible ceRNA networks of RAB39B in DLBCL. The RAB39B expression was associated with decreased sensitivity of chemotherapy drugs such as dexamethasone, doxorubicin, etoposide, vincristine, and cytarabine and poor overall survival in DLBCL. In vitro experiments showed that RAB39B was associated with proliferation, apoptosis, and drug sensitivity of DLBCL cells.

Conclusion: RAB39B is abnormally elevated and related to drug resistance and poor OS in DLBCL, which may be due to its involvement in immune infiltration, m6A modification, and regulation by multiple non-coding RNAs. RAB39B may be used as an effective biomarker for the diagnosis and treatment of DLBCL.

Immune ULBP1 is Elevated in Colon Adenocarcinoma and Predicts Prognosis

Background: Colon adenocarcinoma (COAD) is still the main cause of cancer deaths worldwide. Although immunotherapy has made progress in recent years, there is still a need to improve diagnosis, prognosis, and treatment tools. UL-16 binding protein 1 (ULBP1) is a ligand that activates the receptor natural killer cell group 2 receptor D (NKG2D) and plays an important immunomodulatory role. We aimed to investigate the clinical significance of ULBP1 in COAD.

Methods: We obtained the relevant data from The Cancer Genome Atlas (TCGA). A total of 438 patients with COAD were included in this study, with a mean age of 67.1 ± 13.03 years old, of which 234 (53.42%) were male. The diagnostic value of COAD tumor tissues and adjacent tissues was analyzed by ROC curve. Univariate and multivariate survival analysis investigated the prognostic value of ULBP1 gene, and Gene Set Enrichment Analysis (GSEA) curve was performed to analyze the biological process and enriched enrichment pathway of ULBP1 in COAD. Combination survival analysis investigated the combined prognostic effect of prognostic genes.

Results:ULBP1 gene had a high diagnostic value in COAD [AUC (TCGA) = 0.959; AUC (Guangxi) = 0.898]. Up-regulated ULBP1 gene of patients with COAD predicted a worse prognosis compared to those patients with down-regulated ULBP1 gene (Adjusted HR = 1.544, 95% CI = 1.020–2.337, p = 0.040). The GSEA showed that ULBP1 was involved in the apoptotic pathway and biological process of T cell mediated cytotoxicity, regulation of natural killer cell activation, and T cell mediated immunity of COAD. The combination survival analysis showed that the combination of high expression of ULBP1, AARS1, and DDIT3 would increase the 2.2-fold death risk of COAD when compared with those of low expression genes.

Conclusion: The immune-related ULBP1 gene had diagnostic and prognostic value in COAD. The combination of ULBP1, AARS1, and DDIT3 genes could improve the prognostic prediction performance in COAD.

The Expectations and Challenges of Wildlife Disease Research in the Era of Genomics: Forecasting with a Horizon Scan-like Exercise

The outbreak and transmission of disease-causing pathogens are contributing to the unprecedented rate of biodiversity decline. Recent advances in genomics have coalesced into powerful tools to monitor, detect, and reconstruct the role of pathogens impacting wildlife populations. Wildlife researchers are thus uniquely positioned to merge ecological and evolutionary studies with genomic technologies to exploit unprecedented "Big Data" tools in disease research; however, many researchers lack the training and expertise required to use these computationally intensive methodologies. To address this disparity, the inaugural "Genomics of Disease in Wildlife" workshop assembled early to mid-career professionals with expertise across scientific disciplines (e.g., genomics, wildlife biology, veterinary sciences, and conservation management) for training in the application of genomic tools to wildlife disease research. A horizon scanning-like exercise, an activity to identify forthcoming trends and challenges, performed by the workshop participants identified and discussed 5 themes considered to be the most pressing to the application of genomics in wildlife disease research: 1) "Improving communication," 2) "Methodological and analytical advancements," 3) "Translation into practice," 4) "Integrating landscape ecology and genomics," and 5) "Emerging new questions." Wide-ranging solutions from the horizon scan were international in scope, itemized both deficiencies and strengths in wildlife genomic initiatives, promoted the use of genomic technologies to unite wildlife and human disease research, and advocated best practices for optimal use of genomic tools in wildlife disease projects. The results offer a glimpse of the potential revolution in human and wildlife disease research possible through multi-disciplinary collaborations at local, regional, and global scales.

[Detection and interpretation of somatic variants in molecular pathology]

BACKGROUND

Due to the increasing amount of data and sources of information, data evaluation is a crucial step in parallel sequencing.

OBJECTIVES

Illustration of pitfalls in evaluating the variant list of parallel sequencing and recommendations regarding software tools and databases.

METHODS

Description of filtering steps used, demonstration of criteria and recommendations for annotation by examples from everyday work, comparative analysis of databases with somatic variants, description of the installation of an individualized database.

RESULTS

Variant filtering is a multistep process using information from different databases. The plausibility of variant calling should be verified using the Integrative Genomics Viewer and variants should be described according to the Human Genome Variation Society (HGVS) recommendations. Different databases, which all show advantages and disadvantages, are available for variant interpretation. An individualized database can be built up with the open-source tool cBioPortal.

CONCLUSIONS

Different tools and databases might be used for the analysis of parallel sequencing data. The application depends on, amongst other things, the local situation and has to be extensively validated.

Gene Expression Correlated with Severe Asthma Characteristics Reveals Heterogeneous Mechanisms of Severe Disease

RATIONALE

Severe asthma (SA) is a heterogeneous disease with multiple molecular mechanisms. Gene expression studies of bronchial epithelial cells in individuals with asthma have provided biological insight and underscored possible mechanistic differences between individuals.

OBJECTIVES

Identify networks of genes reflective of underlying biological processes that define SA.

METHODS

Airway epithelial cell gene expression from 155 subjects with asthma and healthy control subjects in the Severe Asthma Research Program was analyzed by weighted gene coexpression network analysis to identify gene networks and profiles associated with SA and its specific characteristics (i.e., pulmonary function tests, quality of life scores, urgent healthcare use, and steroid use), which potentially identified underlying biological processes. A linear model analysis confirmed these findings while adjusting for potential confounders.

MEASUREMENTS AND MAIN RESULTS

Weighted gene coexpression network analysis constructed 64 gene network modules, including modules corresponding to T1 and T2 inflammation, neuronal function, cilia, epithelial growth, and repair mechanisms. Although no network selectively identified SA, genes in modules linked to epithelial growth and repair and neuronal function were markedly decreased in SA. Several hub genes of the epithelial growth and repair module were found located at the 17q12-21 locus, near a well-known asthma susceptibility locus. T2 genes increased with severity in those treated with corticosteroids but were also elevated in untreated, mild-to-moderate disease compared with healthy control subjects. T1 inflammation, especially when associated with increased T2 gene expression, was elevated in a subgroup of younger patients with SA.

CONCLUSIONS

In this hypothesis-generating analysis, gene expression networks in relation to asthma severity provided potentially new insight into biological mechanisms associated with the development of SA and its phenotypes.

Gene Expression Correlated with Severe Asthma Characteristics Reveals Heterogeneous Mechanisms of Severe Disease

RATIONALE

Severe asthma (SA) is a heterogeneous disease with multiple molecular mechanisms. Gene expression studies of bronchial epithelial cells in individuals with asthma have provided biological insight and underscored possible mechanistic differences between individuals.

OBJECTIVES

Identify networks of genes reflective of underlying biological processes that define SA.

METHODS

Airway epithelial cell gene expression from 155 subjects with asthma and healthy control subjects in the Severe Asthma Research Program was analyzed by weighted gene coexpression network analysis to identify gene networks and profiles associated with SA and its specific characteristics (i.e., pulmonary function tests, quality of life scores, urgent healthcare use, and steroid use), which potentially identified underlying biological processes. A linear model analysis confirmed these findings while adjusting for potential confounders.

MEASUREMENTS AND MAIN RESULTS

Weighted gene coexpression network analysis constructed 64 gene network modules, including modules corresponding to T1 and T2 inflammation, neuronal function, cilia, epithelial growth, and repair mechanisms. Although no network selectively identified SA, genes in modules linked to epithelial growth and repair and neuronal function were markedly decreased in SA. Several hub genes of the epithelial growth and repair module were found located at the 17q12-21 locus, near a well-known asthma susceptibility locus. T2 genes increased with severity in those treated with corticosteroids but were also elevated in untreated, mild-to-moderate disease compared with healthy control subjects. T1 inflammation, especially when associated with increased T2 gene expression, was elevated in a subgroup of younger patients with SA.

CONCLUSIONS

In this hypothesis-generating analysis, gene expression networks in relation to asthma severity provided potentially new insight into biological mechanisms associated with the development of SA and its phenotypes.

The Pluripotency Factor NANOG Binds to GLI Proteins and Represses Hedgehog-mediated Transcription

The Hedgehog (HH) signaling pathway is essential for the maintenance and response of several types of stem cells. To study the transcriptional response of stem cells to HH signaling, we searched for proteins binding to GLI proteins, the transcriptional effectors of the HH pathway in mouse embryonic stem (ES) cells. We found that both GLI3 and GLI1 bind to the pluripotency factor NANOG. The ectopic expression of NANOG inhibits GLI1-mediated transcriptional responses in a dose-dependent fashion. In differentiating ES cells, the presence of NANOG reduces the transcriptional response of cells to HH. Finally, we found thatGli1andNanogare co-expressed in ES cells at high levels. We propose that NANOG acts as a negative feedback component that provides stem cell-specific regulation of the HH pathway.