MethSurv: a web tool to perform multivariable survival analysis using DNA methylation data

Anaphase promoting complex subunit 10 is a potential diagnostic and prognostic biomarker in oral squamous cell carcinoma

OBJECTIVE

To explore the role of anaphase promoting complex subunit 10 (ANAPC10) in both the diagnosis and prognosis of oral squamous cell carcinoma (OSCC).

DESIGN

ANAPC10 expressions in OSCC tissues and adjacent normal tissues were analysed using TCGA and GEO databases. Its clinical prognostic significance was evaluated using the GEPIA tool. Signalling pathways associated with ANAPC10 were identified through GO, KEGG, and GSEA. Promoter methylation levels of ANAPC10 were assessed using the UALCAN tool. The correlation between ANAPC10 expression and tumour-infiltrating immune cells was analysed using the TIMER database. ANAPC10's role in OSCC cells was validated via CCK-8 assays, wound healing assays, cell migration assays, apoptosis assays, and cell cycle analysis.

RESULTS

ANAPC10 expression was significantly elevated in OSCC tissues. Increased ANAPC10 expression was associated with advanced T stages, pathological stages, histologic grades, and poorer therapeutic outcomes. Notably, high ANAPC10 expression was strongly correlated with reduced overall survival, disease-specific survival, and progression-free interval in OSCC patients. Functional enrichment analyses revealed that ANAPC10 is involved in RNA splicing, immune regulation, and cell cycle progression. Experimental validation further demonstrated that ANAPC10 levels are influenced by promoter methylation status, and ANAPC10 regulates oral cancer cell proliferation, migration, apoptosis, and cell cycle progression.

CONCLUSION

ANAPC10 is a critical gene in OSCC prognosis, with roles in cell cycle regulation and RNA splicing. It may serve as a diagnostic biomarker and therapeutic target.

MYB Proto-Oncogene Like 2 identified as a biomarker for uterine corpus endometrial carcinoma: evidence from bioinformatics and clinical validation

Background

Endometrial carcinoma (EC) is the sixth most prevalent malignancy among women globally, posing a significant clinical challenge due to limited therapeutic options for advanced or recurrent cases. The identification of novel prognostic biomarkers and therapeutic targets is crucial for improving patient outcomes. This study aimed to investigate the multifaceted roles of MYB Proto-Oncogene Like 2 (MYBL2) in uterine corpus endometrial carcinoma (UCEC).

Methods

We employed multiple bioinformatics algorithms (GEPIA, TCGA, TIMER2.0) to analyze MYBL2 expression across different cancer types and in UCEC specifically. Expression patterns were validated using quantitative real-time PCR (qPCR) on clinical samples. Epigenetic analyses focused on promoter methylation status, and immune infiltration patterns were assessed using MethSurv, CIBERSORT and TIMER2.0. Drug sensitivity profiling was performed using the CPADS web platform.

Results

MYBL2 was found to be significantly upregulated in UCEC tumors compared to normal tissues. Elevated MYBL2 expression correlated with advanced histologic grade and clinical stage, indicating its potential as a biomarker for disease progression. Epigenetic analysis revealed promoter hypomethylation in tumors, suggesting a regulatory mechanism driving MYBL2 overexpression. MYBL2 demonstrated dynamic interactions with the tumor immune microenvironment, including associations with immune cell infiltration patterns and co-expression with immune checkpoint molecules and chemokines. Drug sensitivity profiling highlighted differential therapeutic responses linked to MYBL2 expression levels.

Conclusion

This study establishes MYBL2 as a critical regulator of UCEC progression, bridging epigenetic dysregulation, immune modulation, and clinical outcomes. The findings provide a foundation for exploring MYBL2-targeted strategies in precision immunotherapy and personalized therapeutic interventions.

NDRG1/2 as a prognostic predictive biomarker of cervical cancer and its correlation with immune infiltration

BACKGROUND

Cervical cancer (CC) is a leading cause of cancer-related death in women. The N-myc down-stream regulatory gene (NDRG) family has an unclear prognostic role in CC.

METHODS

We analyzed NDRG mRNA and protein levels in CC using public databases. And NDRG1 expression was verified through immunohistochemistry in clinical samples. Additionally, we utilized other bioinformatics tools to analyze the correlations between NDRG and survival, as well as immune infiltration.

RESULTS

NDRG1 was elevated, and NDRG2 was reduced in CC tissues. High NDRG1 and low NDRG2/3 correlated with poorer survival and were associated with reduced immune cell infiltration, particularly CD8+ T cells. Genetic alterations in NDRG1/2/3 were primarily amplifications, while DNA hypomethylation of NDRG1 in CC tissues, particularly at specific CpG sites, was associated with prognosis. PPI and enrichment analyses implicated NDRGs in metabolic processes, HIF-1 signaling, and immune regulation, underscoring their roles in CC progression and prognosis.

CONCLUSIONS

NDRG1/2 present potential as new prognostic biomarkers, shedding light on therapeutic targets for CC.

The critical role of COL1A1 revealed by integrated bioinformatics analysis of differentially-expressed genes in colorectal cancer and inflammatory bowel disease

PURPOSE

There is an urgent need to identify biomarkers of tumorigenesis for colitis-associated cancer (CAC) as early cancer detection remains crucial for patients with inflammatory bowel disease (IBD). This in silico study examines the relationship between IBD and CAC, with particular regard to differentially-expressed genes (DEGs).

METHODS

Integrated bioinformatics tools and public databases were employed. Data from GEO (GSE102133, GSE48958, GSE9348, GSE83687, GSE138202) were processed using GEOexplorer. DEGs were then functionally annotated with DAVID, SRplot, and integrated analysis via Metascape. Validation used Oncopression and Human Protein Atlas. Survival analysis employed GEPIA2. miRNA interactions were studied via miRTargetLink 2.0. Immune infiltration was analyzed with TIMER 2.0. COL1A1 expression and mutations were examined using cBioPortal, Kaplan-Meier plotter, and DNA methylation was analyzed using MethSurv. Correlation of COL1A1 gene promoter methylation with tissue type and clinical data was performed using the UALCAN database. The ROC analysis of COL1A1 was conducted in the R environment.

RESULTS

Our analysis identified three potential hub genes (ICAM1, LAMC1, and COL1A1), which are overexpressed in IBD and cancer tissues compared to normal tissue, and hence may play a role in CAC. Furthermore, patients with lower COL1A1 expression had longer disease-free survival (p = 0.01) than those with higher expression. Therefore, this gene was chosen for further analysis and identified as the most crucial.

CONCLUSION

COL1A1 reveals significant immunohistochemistry, mutations, and methylation data. Further studies involving machine learning and clinical data are required to validate the results.

APOA1 promotes tumor proliferation and migration and may be a potential pan-cancer biomarker and immunotherapy target

INTRODUCTION

Aberrant expression of APOA1 has been reported in various cancers. However, a comprehensive investigation into its role in cancer is currently lacking.

METHODS

Online websites and databases such as TIMER2.0, GEPIA2, UALCAN and GSCA were used to investigate the relationship between APOA1 expression and prognostic value, immune infiltration, gene mutations, and drug sensitivity. In addition, in vitro CCK-8 and transwell migration and invasion assays were performed to determine the biological functions of APOA1 in gastric cancer (GC) cells.

RESULTS

The pan-cancer analysis showed that APOA1 is differentially expressed in different cancer types and significantly correlated with tumor stages. A survival analysis revealed that APOA1 predicted a poor prognosis in ACC, KIRC, STAD, and a good prognosis in BRCA, OV, and UCEC. We also found that the most common genetic alteration type of APOA1 was deep deletion, and the DNA methylation level of APOA1 decreased in various cancers. Furthermore, APOA1 expression negatively correlated with immune cells infiltration in cancers, including CD4+ T, CD8+ T, and myeloid dendritic cells. For STAD, GO/KEGG enrichment analysis revealed the possible involvement of APOA1 in cholesterol metabolism and PPAR signaling pathway. Finally, we further performed in vitro experiments to verify that overexpression of APOA1 could promote the proliferation, migration and invasion of GC cells.

CONCLUSION

The results of this study indicate that APOA1 is a potential tumor prognostic biomarker and immunotherapy target. In addition, APOA1 plays an essential role in the proliferation, migration, and invasion of GC cells by vitro experiments.

FAM72 family members serves as prognostic biomarker in liver hepatocellular carcinoma

BACKGROUND

Liver hepatocellular carcinoma (LIHC) is a common cancer with poor prognosis. The FAM72 gene family enhances neuronal self-renewal, potentially increasing tumor formation, but its functional and predictive relevance in LIHC remains unclear. We sought to investigate the function of the FAM72 gene family in LIHC in the present study.

METHODS

We acquired TCGA-LIHC expression and phenotypic data as well as extensive clinicopathologic information from the UCSC Xena Database (https://xenabrowser.net/datapages/) database. We analyzed the association between FAM72 gene family expression in LIHC and patient prognosis and immune infiltration; Genomic and functional enrichment analysis for FAM72 genes was analyzed. Finally, Western blot method, quantitative real-time polymerase chain reaction and CCK8 detection and cell invasion experiments were used to verify the effect of FAM72A expression on LIHC.

RESULTS

The expression of FAM72 gene family is different between LIHC and normal liver tissues. The expression of FAM72 gene family increased with increasing grading of LIHC tissues. The expression of FAM72 gene family was significantly reduced in LIHC stage IV. LIHC tissues expressed significantly more FAM72 genes than did normal tissues at the T stage (p < 0.001,). which has a good value in the diagnosis of LIHC (AUC greater than 0.85), and was strongly linked with the tumor stage in LIHC. Based on Cox analysis of univariate data, the FAM72 gene family was associated with poor overall survival (OS) in patients with LIHC. Analysis of multifactorial Cox data revealed an independent relationship between FAM72 expression and OS. Increased FAM72 gene expression is associated with poor survival rates and immune cell infiltration. Methylation levels were associated with the prognosis of patients with LIHC. Ultimately, our findings revealed that FAM72A is abundantly expressed in LIHC cells, facilitating proliferation and metastasis.

CONCLUSION

These findings indicate that the FAM72 gene family is a potential molecular marker for poor prognosis in LIHC, providing additional insights into the development of therapeutic approaches and prognostic markers.

In silico pan-cancer analysis of VRAC subunits and their prognostic roles in human cancers

The study focuses on the VRAC channel and its significant roles in cancer development. It addresses a research gap by conducting a pan-cancer analysis with multi-omics bioinformatics tools, integrating data from the Human Protein Atlas (HPA) and Genotype-Tissue Expression (GTEx) datasets to examine mRNA expression patterns of its Leucine Rich Repeat Containing 8 (LRRC8) subunits in various tissues and cancers. The study links variations in LRRC8s expression with patient outcomes and includes analyses of DNA and RNA methylation. The study reveals significant correlations between LRRC8s expression and immune cell infiltration, as well as a positive association with cancer-associated fibroblasts and key immune regulators such as major histocompatibility complex (MHCs) and chemokines. Furthermore, the research suggests that LRRC8s are involved in cancer-signalling pathways, which may offer new therapeutic targets. Additionally, a drug sensitivity analysis shows that LRRC8 subunits affect drug responses differently, supporting the use of personalized therapeutic strategies. In conclusion, the study emphasizes the significance of VRAC subunits in cancer biology and suggests their potential as biomarkers and targets in cancer immunotherapy and personalized medicine.

Multi-omic analyses reveal PTPN6's impact on tumor immunity across various cancers

Protein Tyrosine Phosphatase Non-Receptor Type 6 (PTPN6) plays a crucial regulatory role in cellular processes and has been implicated in oncogenesis. This pan-cancer analysis aimed to elucidate PTPN6's involvement across various cancer types, with a particular emphasis on its association with tumor immunity. We analyzed PTPN6 expression data from open access databases using various statistical techniques, including survival analysis, genetic heterogeneity analysis, immune profiling, single-cell analysis, drug sensitivity analysis, and protein interaction analysis. We also conducted in vitro experiments utilizing colorectal cancer cell lines to validate PTPN6's functional role. PTPN6 exhibited distinct expression patterns across cancers, and its prognostic significance was apparent in several cancer types, particularly in glioblastoma, sarcoma, and melanoma. We observed correlations between PTPN6 and immune genes/cell infiltration in these cancers, suggesting a potential role in modulating the tumor immune microenvironment. Single-cell analysis revealed that PTPN6 is predominantly localized in macrophages, B cells, and dendritic cells within the tumor microenvironment, implying its involvement in regulating immune cell function. Enrichment analysis highlighted PTPN6's role in immune-related pathways. Drug sensitivity analysis identified specific drugs, including PAC-1, SNX-2112, BELINOSTAT, VORINOSTAT, TPCA-1, and PHA-893,888, whose efficacy may be influenced by PTPN6 expression. Knocking down PTPN6 expression inhibited the proliferation and migration of colorectal cancer cells in vitro, confirming its oncogenic role in this cancer type. This pan-cancer analysis establishes PTPN6's multifaceted influence on tumor immunity and its potential as a biomarker and therapeutic target.

Pan-Cancer Analysis Identifies BCLAF1 as a Potential Biomarker for Renal Cell Carcinoma

B-cell lymphoma-2-associated transcription factor 1 (BCLAF1) is a versatile protein involved in the regulation of gene transcription and post-transcriptional processing. Although BCLAF1 exerts a broad tumor suppressor effect or tumor promoter effect in many cancer types, the specific roles concerning its expression levels, and its impact on tumorigenesis in Renal cell carcinoma (RCC) remain unclear. Here, we utilized the Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) datasets alongside R software and online tools to unravel the specific roles of BCLAF1 in 33 cancer types, including its expression levels, tumor immune and molecular subtypes, and its correlation with prognosis, diagnosis, DNA methylation, and immune microenvironment. Additionally, we carried out cell biology experiments to independently investigate the expression of BCLAF1 in RCC and its effects on tumor progression. BCLAF1 was differentially expressed in tumor tissues compared to normal tissues across various cancer types and was also differentially expressed in different immune and molecular subtypes. In RCC, patients with high BCLAF1 expression had a better prognosis and BCLAF1 was tightly correlated with the stage, gender, and histological grade of patients. Furthermore, BCLAF1 had higher DNA methylation levels and higher immune infiltration levels in tumor tissues. Additionally, cell functional experiments confirmed the low expression of BCLAF1 in RCC and that BCLAF1 significantly inhibited the proliferation, migration, and invasion, while inducing apoptosis and cell cycle arrest in RCC cells in vitro. Our study under-scored the potential of BCLAF1 as an important actor in tumorigenesis, especially concerning RCC where it may serve as an effective prognostic marker.

Integrative Analysis of DNA Methylation and microRNA Reveals GNPDA1 and SLC25A16 Related to Biopsychosocial Factors Among Taiwanese Women with a Family History of Breast Cancer

Biopsychosocial factors, including family history, influence the development of breast cancer. Malignancies in women with a family history of breast cancer may be detectable based on DNA methylation and microRNA. Objectives: The present study extended an integrative analysis of DNA methylation and microRNA to identify genes associated with biopsychosocial factors. Methods: We identified 3060 healthy women from the Taiwan Biobank and included 32 blood plasma samples for analysis of biopsychosocial factors and epigenetic changes. GEO databases and bioinformatics approaches were used for the identification and validation of potential genes. Results: Our integrative analysis revealed GNPDA1 and SLC25A16 as potential genes. Age, a family history of cancer, and alcohol consumption were associated with GNPDA1 and SLC25A16 based on the current data set and the GEO data set. GNPDA1 and SLC25A16 exhibited significant expression in breast cancer tissues based on UALCAN analysis, where they were overexpressed and underexpressed, respectively. Through a MethSurv analysis, GNPDA1 hypomethylation and SLC25A16 hypermethylation were associated with poor prognoses in terms of overall survival in breast cancer. Moreover, through a MetaCore functional enrichment analysis, GNPDA1 and SLC25A16 were associated with the BRCA1, BRCA2, and pro-oncogenic actions of the androgen receptor in breast cancer. Further, GNPDA1 and SLC25A16 were enriched in known targets of approved cancer drugs as potential genes associated with breast cancer. Conclusions: These two genes might serve as biomarkers for the early detection of breast cancer, especially for women with a family history of breast cancer.

Highly expressed GCN1 is associated with cancer progression and poor prognosis in hepatocellular carcinoma patients

BACKGROUND

General control non-derepressible protein 1 (GCN1), a ribosome-binding protein, has been implicated in the development and progression of multiple cancers. However, the potential role of GCN1 in hepatocellular carcinoma (HCC) has not yet been investigated.

METHODS

The expression of GCN1 in HCC was analyzed using multiple databases. Bioinformatics analysis was employed to investigate the correlation of GCN1 expression with clinical significance and immune infiltration in HCC. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, gene set enrichment analysis (GSEA), and in vitro experiments were conducted to study the function and potential mechanisms of GCN1 in HCC.

RESULTS

GCN1 was significantly upregulated in HCC, which was associated with worse clinicopathological features and poorer prognosis of the patients. GCN1 expression was closely associated with immune cell infiltration in HCC. GSEA analysis showed that GCN1 was involved in several tumor-related signaling pathways, including cell cycle, DNA replication, and Wnt signaling pathway. Knockdown of GCN1 inhibited the proliferation, invasion and migration of HCC cells, and also down-regulated the expression levels of cell cycle protein cyclin B1 (CCNB1), cyclin D1 (CCND1), and Wnt signaling pathway-related proteins Wnt3A and β-catenin.

CONCLUSION

GCN1 overexpression was associated with HCC progression and poor prognosis, and GCN1 knockdown could suppress the proliferation, migration and invasion ability of HCC cells by regulating Wnt signaling pathway, suggesting the potential of GCN1 as a prognostic and therapeutic target for HCC.

Downregulated STAT3 and STAT5B are prognostic biomarkers for colorectal cancer and are associated with immune infiltration

BACKGROUND

Colorectal cancer has high incidence and mortality rates. The signal transducer and activator of transcription (STAT) family plays vital roles in the tumorigenesis and development of colorectal cancer. The expression, prognostic value, and immune function of the STAT family are becoming much more clearly.

METHODS

Our study collected data from several public data portals such as TCGA (644 samples) and GTEx database (308 samples) and clinical samples (30 samples, China). Then we systematically assessed the expression level and prognostic value of the STAT family in colorectal cancer samples. Moreover, the immune function and immune infiltration levels of prognosis-related STAT members were explored via single cell RNA-seq and spatial transcriptomics technology data. Several useful portals and tools have been utilized such as CancerSEA and TISIDB in single-cell analysis, CBio Cancer Genomics in multidimensional alterations, MethSurv in DNA methylation, and related R packages.

RESULTS

Our study found that STAT3 and STAT5B were significantly lower in colorectal cancer via multi-omics (P < 0.001). Higher STAT3 and STAT5B level were correlated with better future outcome. Nomograms were developed to predict the distal survival time (C-index = 0.724). The functions of STAT3 and STAT5B are associated with inflammation, the JAK/STAT pathway and the immune response. The major cell types of colorectal cancer were CD4Tconv, CD8T, CD8Tex, Tprolif, Treg and STAT3 and STAT5B widely expressed in these cells. STAT3 and STAT5B both correlated with CD244 and KDR for immune checkpoints.

CONCLUSION

STAT3 and STAT5B are downregulated in colorectal cancer and have great potential as prognostic biomarkers and novel immunotherapy targets.

Screening of common genomic biomarkers to explore common drugs for the treatment of pancreatic and kidney cancers with type-2 diabetes through bioinformatics analysis

Type 2 diabetes (T2D) is a crucial risk factor for both pancreatic cancer (PC) and kidney cancer (KC). However, effective common drugs for treating PC and/or KC patients who are also suffering from T2D are currently lacking, despite the probability of their co-occurrence. Taking disease-specific multiple drugs during the co-existence of multiple diseases may lead to adverse side effects or toxicity to the patients due to drug-drug interactions. This study aimed to identify T2D-, PC and KC-causing common genomic biomarkers (cGBs) highlighting their pathogenetic mechanisms to explore effective drugs as their common treatment. We analyzed transcriptomic profile datasets, applying weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis approaches to identify T2D-, PC-, and KC-causing cGBs. We then disclosed common pathogenetic mechanisms through gene ontology (GO) terms, KEGG pathways, regulatory networks, and DNA methylation of these cGBs. Initially, we identified 78 common differentially expressed genes (cDEGs) that could distinguish T2D, PC, and KC samples from controls based on their transcriptomic profiles. From these, six top-ranked cDEGs (TOP2A, BIRC5, RRM2, ALB, MUC1, and E2F7) were selected as cGBs and considered targets for exploring common drug molecules for each of three diseases. Functional enrichment analyses, including GO terms, KEGG pathways, and regulatory network analyses involving transcription factors (TFs) and microRNAs, along with DNA methylation and immune infiltration studies, revealed critical common molecular mechanisms linked to PC, KC, and T2D. Finally, we identified six top-ranked drug molecules (NVP.BHG712, Irinotecan, Olaparib, Imatinib, RG-4733, and Linsitinib) as potential common treatments for PC, KC and T2D during their co-existence, supported by the literature reviews. Thus, this bioinformatics study provides valuable insights and resources for developing a genome-guided common treatment strategy for PC and/or KC patients who are also suffering from T2D.

Comprehensive analysis of DNA methylation and gene expression to identify tumor suppressor genes reactivated by MLN4924 in acute myeloid leukemia

This study investigated whether the neddylation inhibitor MLN4924 induces aberrant DNA methylation patterns in acute myeloid leukemia and contributes to the reactivation of tumor suppressor genes. DNA methylation profiles of Kasumi-1 and KU812 acute myeloid leukemia cell lines before and after MLN4924 treatment were generated using the 850K Methylation BeadChip. RNA sequencing was used to obtain transcriptomic profiles of Kasumi-1 cells. Target genes were identified through a combined analysis of methylation and transcriptome data. Methylation-specific PCR and quantitative PCR validated the changes in methylation and expression. Prognostic analysis of target genes was performed using databases, and Pearson correlation was used to examine the relationship between methylation and expression levels. In Kasumi-1 and KU812 cells, 301 and 469 differentially methylated sites, respectively, were identified. A total of 4310 differential expression genes were detected in Kasumi-1. Combined analysis revealed that TRIM58 exhibited significant demethylation and upregulation after MLN4924 treatment, as confirmed by quantitative and methylation-specific PCR. Furthermore, database analysis revealed that both down-expression and promoter hypermethylation of TRIM58 were correlated with poor prognosis in acute myeloid leukemia. A negative correlation was observed between TRIM58 methylation and expression levels. This study suggests that MLN4924 alters DNA methylation patterns in acute myeloid leukemia and reactivates TRIM58, a potential tumor suppressor gene, through demethylation.

Association of DBNDD1 with prognostic and immune biomarkers in invasive breast cancer

BACKGROUND

Dysbindin domain-containing 1 (DBNDD1) is strongly connected with the occurrence and development of malignancies, but the DBNDD1 function and mechanism in invasive breast cancer (IBC) remain poorly understood. Our objective was to ascertain the possible diagnosis and prognostic importance of DBNDD1 in IBC.

METHOD

An analysis was done to ascertain the connection between the DBNDD1 expression level in IBC and clinicopathological features employing the relevant databases, and to evaluate DBNDD1 in the diagnosis and prognosis of IBC. We explored possible cellular mechanisms and biological functions as well as explored DBNDD1-related interacting proteins, analyzed DBNDD1 methylation status, and investigated its correlation with immune cell infiltration. The effect of DBNDD1 on the function of breast cancer (BC) cells was studied in vitro.

RESULT

DBNDD1 mRNA and protein levels exhibited higher expression in IBC, and were significantly correlated with a worse outcome. DBNDD1 hypomethylation status was linked to a negative prognosis. Enrichment analysis revealed that the genes exhibiting a positive correlation with DBNDD1 expression were mostly enriched in pathways linked to DNA synthesis and DNA methylation. Furthermore, the DBNDD1 expression level exhibited a substantial correlation with the immune cell infiltration in tissue. DBNDD1 overexpression emerged to enhance the BC cell's proliferation, invasion and migration as well as suppress the BC cell's apoptosis, as validated by in vitro tests.

CONCLUSION

DBNDD1 upregulation is directly linked to the tumor immune cell infiltration and the unfavorable IBC prognosis. DBNDD1 possesses the capacity to be a biomarker for diagnosing and predicting the outcome of a disease, as well as a possible target for therapeutic interventions in IBC.

Endoplasmic reticulum stress-related CLIP4 plays a procarcinogenic role in hepatocellular carcinoma: an integrated analysis

OBJECTIVE

To explore the potential of endoplasmic reticulum stress (ERS)-associated protein CLIP4 as a biomarker for hepatocellular carcinoma (HCC) and the underlying mechanism.

METHODS

TCGA public database and a tissue microarray were used to investigate the molecular characteristics of CLIP4 and its association with disease. TCGA-LIHC dataset was used for single-gene differential expression analysis, single-gene correlation analysis, functional enrichment analysis, immune infiltration analysis, and DNA methylation analysis. RNA-seq, immunohistochemistry, western blotting, and RT-qPCR were used to verify the effect of ERS on CLIP4 expression. Public databases and miRNA-seq data were used to explore the TF-miRNA-CLIP4 regulatory network. CCK-8, colony formation, EdU staining, wound-healing, Transwell, western blotting and RT-qPCR were used to detect the effects of CLIP4 on the proliferation, migration and epithelial-mesenchymal transition (EMT) of HCC cells.

RESULTS

Analysis of TCGA datasets and tissue microarrays demonstrated that elevated CLIP4 expression was associated with poor prognosis in HCC. Enrichment analysis revealed that CLIP4 is involved in the immune response, cell adhesion, and EMT. There was a positive correlation between CLIP4 expression and the infiltration of the majority of immune cells, immunomodulators, and chemokines. Furthermore, the DNA methylation pattern of CLIP4 was found to have significant prognostic value. ERS was found to significantly upregulate CLIP4 expression. In addition, the ERS-RELA-miR-222-5p-CLIP4 transcriptional network was constructed to clarify the role of CLIP4. Cell function experiments confirmed that it promotes the proliferation, migration, and EMT of HCC cells.

CONCLUSIONS

CLIP4 is a potential immune-related oncogenic molecule in HCC. ERS regulates the expression of CLIP4, and CLIP4 promotes the proliferation, migration, and EMT of HCC cells.

Assessment of Methylation in Selected ADAMTS Family Genes in Non-Small-Cell Lung Cancer

Alterations in the methylation of genetic material can influence carcinogenesis by the downregulation or overexpression of ADAMTS (a disintegrin-like and metalloprotease with thrombospondin motifs) protease genes. Through their proteolytic activity, these enzymes are also capable of promoting angiogenesis. Consequently, ADAMTS proteases can either facilitate or inhibit cancer progression. This study aimed to evaluate the methylation levels of the ADAMTS6, ADAMTS9, and ADAMTS12 genes in non-small-cell lung cancer (NSCLC) using data from bioinformatics databases. The focus was on differences between lung adenocarcinoma (LUAD) and lung squamous-cell carcinoma (LUSC) subtypes and their impact on patient overall survival (OS). ADAMTS6 gene expression is significantly reduced in LUSC, and analysis of ADAMTS9 gene expression showed a significantly reduced gene transcript level in LUAD and LUSC, while both NSCLC subtypes demonstrated ADAMTS12 upregulation. In LUSC, significantly elevated promoter methylation was found in all of the aforementioned genes, while in LUAD, higher promoter methylation was observed only for ADAMTS9 and ADAMTS12. The differential methylation region (DMR) pattern demonstrated by ADAMTS6, ADAMTS9, and ADAMTS12 is a useful tool for distinguishing normal from cancer cells. The areas under the curve (AUCs) ranged from 0.86 to 0.99 for both LUAD and LUSC subtypes. The methylation level of different CpG sites among selected ADAMTS members is related to patient survival, suggesting it may have value as a prognostic marker. The methylation degree of promoter regions in genes encoding ADAMTS family proteins could significantly influence LUSC and LUAD. Increased promoter methylation could also reduce certain gene expression, contributing to cancer progression. The expression levels and specific DMRs of ADAMTS genes may serve as prognostic markers correlating with patient OS. Assessing ADAMTS gene methylation could become a diagnostic tool for differentiating NSCLC subtypes and potentially guide therapeutic strategies. Further research is needed to fully understand the activity and mechanisms of ADAMTS family proteins.

Disulfidptosis-related gene signatures as prognostic biomarkers and predictors of immunotherapy response in HNSCC

Background

Disulfidptosis is a newly discovered form of cell death associated with tumorigenesis, particularly under oxidative stress and metabolic disorder conditions. Currently, the biological mechanisms of disulfidptosis-related genes (DRGs) in head and neck squamous cell carcinoma (HNSCC) remain unclear.

Methods

The study includes sections on methodologies, data sources, clinical data collection, subtype establishment, identification and analysis of differentially expressed genes, genetic variation, and the construction and validation of a DRG prognostic model. Various analyses are conducted, including the relationship between the risk scores model and clinicopathological features, immune status, immune checkpoints, tumor mutational burden (TMB), microsatellite instability (MSI), ESTIMATE, mRNAsi, and drug sensitivity. The study also covers single-cell analysis and DNA methylation analysis of DRGs, and the prediction of potential microRNA and long non-coding RNA target genes. Prognostic DRGs expression in HNSCC is validated through RT-qPCR and immunohistochemistry. The model's predictive capability is confirmed using external validation cohorts from GEO datasets and clinical tissue samples. The role of DSTN in HNSCC is further validated through gene knockout experiments.

Results

We identified four valuable genes (SLC3A2, NUBPL, ACTB, DSTN) and constructed a prognostic model, along with identifying two DRG-related subtypes. Analysis of the DRG risk score revealed that the low-risk group had a better prognosis compared to the high-risk group. Significant correlations were found between the DRG risk score and clinical features, immunotherapy response, drug sensitivity, and genes related to RNA epigenetic modifications. Low-risk HNSCC patients were identified as potential beneficiaries of immune checkpoint inhibitor (ICI) therapy. A regulatory axis involving DSTN, hsa-miR-181c-5p, LUCAT1, and IGFL2-AS1 was constructed for HNSCC. RT-qPCR and IHC data further validated the upregulation of prognostic DRGs in HNSCC. The prognostic model demonstrated excellent predictive performance for the prognosis of HNSCC patients. Additionally, DSTN was significantly overexpressed in tumor cells; its knockdown inhibited tumor cell proliferation, migration, and invasion.

Conclusion

The prognostic model effectively predicts HNSCC outcomes, with better prognosis in the low-risk group. DSTN upregulation promotes tumor growth, and its knockout inhibits proliferation, migration, and invasion.

Transcription factor MAZ activates the transcription of hypomethylated TYMP in ccRCC

Clear cell renal cell carcinoma (ccRCC) is a highly malignant tumor characterized by a significant propensity for recurrence and metastasis. DNA methylation has emerged as a critical epigenetic mechanism with substantial utility in cancer diagnosis. In this study, multi-omics data were utilized to investigate the target genes regulated by the transcription factor MYC-associated zinc finger protein (MAZ) in ccRCC, leading to the identification of thymidine phosphorylase (TYMP) as a gene with notably elevated expression in ccRCC. The interaction between MAZ and TYMP was confirmed through chromatin immunoprecipitation (ChIP) assays and bioinformatics analysis. It was found that the binding of MAZ to the TYMP promoter is associated with the methylation status of this promoter region. Furthermore, the methylation of the TYMP promoter appears to be correlated with both the clinicopathological stage and overall survival of ccRCC patients. Further exploration of genes within the "nucleotide metabolism" pathway, identified through Gene Ontology (GO) enrichment analysis, revealed that uridine phosphorylase 1 (UPP1) interacts with TYMP. Interestingly, UPP1 was also shown to be activated by MAZ, suggesting a coordinated regulatory mechanism. Based on these findings, we propose that the TYMP-UPP1 complex, co-regulated by MAZ, plays a pivotal role in nucleotide metabolism in ccRCC. These results suggest that TYMP may contribute to the pathophysiology of ccRCC and that promoter methylation offers potential as a prognostic indicator, providing novel insights into the molecular underpinnings of ccRCC and potential avenues for therapeutic intervention.

Epigenetic modification of Castor zinc finger 1 (CASZ1) is associated with tumor microenvironments and prognosis of clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) represents the predominant and remarkably diverse form of renal cell carcinoma. The involvement of the Castor zinc finger 1 (CASZ1) gene in adverse prognostic outcomes has been observed across different cancer types. Nevertheless, the specific altered activities and associated multi-omics characteristics of CASZ1 in ccRCC remain unelucidated.

METHOD

In order to explore the expression of CASZ1, evaluate its prognostic significance, and aid in the therapeutic decision-making process for patients with ccRCC, The Cancer Genome Atlas (TCGA), Gene expression omnibus (GEO), and The Human Protein Atlas (HPA) databases were utilized to gather data on clinicopathological data, prognostic information, genomic, methylomic and immunomic data. Additionally, the Genomics of Drug Sensitivity in Cancer (GDSC) database provided information on drug sensitivity.

RESULTS

CASZ1 expression was found to be significantly reduced in ccRCC and was associated with unfavorable pathological characteristics and a bleak prognosis. Diminished CASZ1 mRNA levels were notably correlated with heightened cytosine-phosphate-guanine (CpG) methylation, indicating a poorer prognosis for patients with increased methylation. Examination of RNA-seq data from TCGA indicated that the CASZ1-high expression subgroup displayed heightened immune cell infiltration and increased expression of immune checkpoint markers, potentially suggesting a more favorable response to immunotherapy. Furthermore, data from the GDSC database indicated that the CASZ1-low expression subgroup might exhibit greater sensitivity to anti-angiogenetic treatments, such as Sunitinib and Axitinib.

CONCLUSIONS

These results indicate that CASZ1 may function as a biomarker for distinguishing various tumor microenvironment phenotypes, predicting prognosis, and assisting in treatment decisions for individuals with ccRCC.

Comprehensive Pan-cancer Analysis of CMPK2 as Biomarker and Prognostic Indicator for Immunotherapy

BACKGROUND

UMP-CMP kinase 2 (CMPK2) is involved in mitochondrial DNA synthesis, which can be oxidized and released into the cytoplasm in innate immunity. It initiates the assembly of NLRP3 inflammasomes and mediates various pathological processes such as human immunodeficiency virus infection and systemic lupus erythematosus. However, the role of CMPK2 in tumor progression and tumor immunity remains unclear.

METHODS

We identified CMPK2 expression patterns in the Genotype Tissue-Expression (GTEx), The Cancer Genome Atlas (TCGA), and the Cancer Cell Line Encyclopedia (CCLE) databases. Validation was performed using immunohistochemical staining data from the Human Protein Atlas (HPA) database and qPCR experiments. Receiver operating characteristic curve analysis and Kaplan-Meier survival analysis were conducted to assess the clinical relevance of CMPK2 expression. The Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data (ESTIMATE) algorithm and the Tumor IMmune Estimation Resource (TIMER) database were used to evaluate the correlation between CMPK2 and immune infiltration in tumors. The Tumor Immune Syngeneic Mouse (TISMO) database and other public datasets were utilized to assess the impact of CMPK2 on immune therapy response. MEXPRESS and MethSurv databases were employed to investigate the effects of methylation on CMPK2 expression.

RESULTS

CMPK2 expression was elevated in 23 cancers and decreased in two cancers. Furthermore, CMPK2 expression had a high diagnostic value for 16 cancers. Elevated CMPK2 expression was associated with lower overall survival (OS), disease-specific survival (DSS), and progression- free interval (PFI) in four cancers. Immune microenvironment-related analysis revealed strong associations between CMPK2 expression and immune cell infiltration, as well as immune checkpoint expression across various tumors. Notably, in four mouse immunotherapy cohorts, CMPK2 expression in treated mouse tumors was higher post-treatment. In five clinical immunotherapy cohorts, patients with high CMPK2 expression show better responses to immunotherapy. Moreover, the methylation level of CMPK2 gene was closely correlated to its expression and tumor prognosis. Among these cancers, the clinical and immunological indications of skin cutaneous melanoma (SKCM) are particularly closely related to CMPK2 expression.

CONCLUSION

Our analysis preliminarily describes the complex function of CMPK2 in cancer progression and immune microenvironment, highlighting its potential as a diagnostic and therapeutic target for immunotherapy.

Double-negative T cells with a distinct transcriptomic profile are abundant in the peripheral blood of patients with breast cancer

BACKGROUND

Double-negative T (DNT) cells comprise a distinct subset of T lymphocytes that have been implicated in immune responses. The aim of this study was to characterize the peripheral DNT population in breast cancer (BC) patients.

METHODS

DNT cells were isolated from the peripheral blood samples of BC patients and healthy controls by flow cytometry. The sorted DNT cells were analyzed by the Smart-seq2 for single-cell full-length transcriptome profiling. The differentially expressed genes (DEGs) between the BC and control groups were screened and functionally annotated by Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses using R. The protein-protein interaction (PPI) network of the DEGs was constructed using the CytoHubba and MCODE plug-in of Cytoscape software to identify the core genes. Survival status, DNA methylation level, immune infiltration and immune checkpoint expression were analyzed using Kaplan-Meier Plotter, UALCAN, MethSeuvr, TIMER, and TISIDB respectively. The sequencing results were verified by RT-qPCR.

RESULT

The percentage of DNT cells was higher in the BC patients compared to healthy controls. We identified 289 DEGs between the DNT populations of both groups. GO and KEGG pathway analyses revealed that the DEGs were mainly related to immunoglobulin mediated immune response, complement activation, and B cell receptor signaling. The PPI networks of the common DEGs were constructed using Cytoscape, and 10 core genes were identified, including TMEM176B, C1QB, C1QC, RASD2, and IFIT3. The expression levels of these genes correlated with the prognosis and immune infiltration in BC patients, and were validated by RT-qPCR (P < 0.05).

CONCLUSIONS

DNT cells are abundant in patients with BC, and might exert anti-tumor immune responses by regulating genes such as TMEM176B and EGR1.

The amino acid transporter SLC7A11 expression in breast cancer

Breast cancer (BC), characterized by its diverse molecular profiles and clinical outcomes, presents a significant challenge in the development of effective therapeutic strategies. Metabolic reprogramming, a defining characteristic of cancer, has emerged as a promising target for novel therapies. SLC7A11, an amino acid transporter that facilitates cysteine uptake in exchange for glutamate, plays a crucial role in sustaining the altered metabolism of cancer cells. This study delves into the comprehensive analysis of SLC7A11 at the genomic, transcriptomic, and protein levels in extensive BC datasets to elucidate its potential role in different BC subtypes. SLC7A11 gene copy number and mRNA expression were evaluated using the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort (n = 1,980) and Breast Cancer Gene Expression Miner (n = 4,712). SLC7A11 protein was assessed using immunohistochemistry in a large BC cohort (n = 1,981). Additionally, The Cancer Genome Atlas (TCGA) dataset was used to explore SLC7A11 DNA methylation patterns using MethSurv (n = 782) and association of SLC7A11 mRNA expression with immune infiltrates using TIMER (n = 1,100). High SLC7A11 mRNA and SLC7A11 protein expression were significantly associated with high tumor grade (p ≤ .02), indicating a potential role in cancer progression. Interestingly, SLC7A11 copy number gain was observed in HER2+ tumors (p = .01), suggesting a subtype-specific association. In contrast, SLC7A11 mRNA expression was higher in the basal-like/triple-negative (TN; p < .001) and luminal B tumors (p = .02), highlighting its differential expression across BC subtypes. Notably, high SLC7A11 protein expression was predominantly observed in Estrogen Receptor (ER)-negative and Triple Negative (TN) BC, suggesting a role in these aggressive subtypes. Further analysis revealed that SLC7A11 was positively correlated with other amino acid transporters and enzymes associated with glutamine metabolism, implying a coordinated role in metabolic regulation. Additionally, SLC7A11 gene expression was positively associated with neutrophil and macrophage infiltration, suggesting a potential link between SLC7A11 and tumor immunity. Our findings suggest that SLC7A11 plays a significant role in BC metabolism, demonstrating differential expression across subtypes and associations with poor patient outcomes. Further functional studies are warranted to elucidate the precise mechanisms by which SLC7A11 contributes to BC progression and to explore its potential as a therapeutic target.

CYFIP2: potential pancreatic cancer biomarker and immunotherapeutic target

OBJECTIVE

It has been shown that the CYFIP2 (Cytoplasmic FMR1-interacting protein 2) gene is apoptosis p53-dependent and is associated with poor prognosis in malignant tumors such as gastric cancer and other and cervical cancer. However, the prognostic potential of CYFIP2 in pancreatic cancer remains unclear. In this work, we first explain the great potential of CYFIP2 malignant progression from a broader perspective (pan-cancer) and confirm its oncogenic value in pancreatic cancer.

METHODS

The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) database, CELL and GEO databases were utilized to explore the distribution of the CYFIP2 gene in human cancers. Data were analyzed using a variety of web-based platforms and software such as R (4.3.2), UCSC, MethSurv, Cytoscape (v3.10.2), UALAND, STRING, TISIDB, Harmonizome 3.0, TIMER 2.0, TCIA and TIDE. The R packages R packages ?limma? and ?ggplot2? were used to compare and visualize CYFIP2 mRNA expression. The R packages ?survminer? and ?survival? were used to statistically analyze the relationship between CYFIP2 expression and the survival and prognosis of tumor patients. the R package ?ss GSEA? was used to assess the correlation between CYFIP2 expression and immune infiltration. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Variation Analysis (GSVA) were used to explore the multiple biological functions and regulatory pathways in which CYFIP2 co-expressed genes co-engage in pancreatic cancer. The R package ?maftool? was used to explore somatic mutation information in pancreatic cancer, and the TIDE database and the R package ?oncoPredic? were used to explore immunotherapeutic responses and sensitive drugs. Pancreatic cancer cell lines were constructed with the specific expression of CYFIP2 mRNA, and their invasive and metastatic abilities were analysed using scratch and transwell assays.

RESULTS

Bioinformatics analysis and in vitro experiments confirmed that CYFIP2 was differentially expressed in a variety of tumors and correlated with clinical stage, and could be used as a potential marker for evaluating the prognosis and immunotherapy of a variety of tumors, including KIRC (Kidney renal clear cell carcinoma), PAAD (Pancreatic adenocarcinoma), PAAD (Pancreatic adenocarcinoma), SKCM (Skin Cutaneous Melanoma), and UCEC (Uterine Corpus Endometrial Carcinoma).Mutations in the CYFIP2 gene and methylation indices can affect the prognosis of tumor patients. In addition, we found that CYFIP2 expression values in pancreatic cancer were positively correlated with the expression of most immune cells, especially CD8?+?T Cells, and significantly negatively correlated with macrophages M0, and negatively correlated with the metastatic and invasive ability of pancreatic cancer cells, which may provide new strategies and ideas for pancreatic cancer immunotherapy.

KNTC1 functions as a potential biomarker and oncogene regulating proliferation, migration and apoptosis in gastric cancer

BACKGROUND

As one of the most prevalent cancers, gastric cancer (GC) exhibits a remarkably high morbidity and mortality rate. To date, effective diagnostic and prognostic markers and therapeutic targets for GC are still lacking. Kinetochore associated 1 (KNTC1) is one of the proteins involved in chromosome segregation. However, the diagnostic and prognostic value of KNTC1 and its biological function in GC remain unknown.

METHODS

In this study, Gene Expression Omnibus (GEO) datasets were utilized to identify differentially expressed genes (DEGs). Prognostic and diagnostic value were assessed by Kaplan-Meier plotter and receiver operating characteristic (ROC) curve. The expression of KNTC1 was verified by q-PCR, immunohistochemistry (IHC) and Western blotting. Subsequently, KNTC1 knockdown was employed to investigate its effect on GC cells. Gene set enrichment analysis (GSEA) revealed a pathway regulated by KNTC1, which was further verified by Western blotting.

RESULTS

Four highly expressed genes (ESPL1, RAD54L, KNTC1, TACC3) were identified as biomarkers for GC diagnosis and prognosis. Notably, the value of KNTC1 as a biomarker for GC was newly revealed. Single-cell and immune analyses revealed that KNTC1 contributed to the suppression of the GC immune microenvironment. In clinical samples, we demonstrated high expression of KNTC1 in GC tissues. KNTC1 knockdown suppressed proliferation and migration while promoting apoptosis of GC cells. Additionally, KNTC1 may affect GC cells by regulating the PI3K/Akt/mTOR pathway.

CONCLUSIONS

KNTC1 acts as a potential diagnostic and prognostic marker for GC. It may promote proliferation and migration while inhibiting apoptosis of GC cells via the PI3K/Akt/mTOR pathway.

Systematic pan-cancer analysis identifies ZBTB11 as a potential pan-cancer biomarker and immunotherapy target in multiple tumor types

BACKGROUND

ZBTB11 is a putative transcription factor with an N-terminal BTB domain and tandem C-terminal zinc finger motifs. Recent studies have suggested a potential role for ZBTB11 in tumorigenesis. However, the biological significance of ZBTB11 in different cancer types remains uncertain.

METHODS

The expression levels, prognostic values, genetic mutations, and DNA promoter methylation of ZBTB11 across tumor types were explored via various online websites and databases, including TIMER2.0, GEPIA2, cBioPortal, UALCAN, GSCA, CancerSEA, and others. Additionally, a competing lncRNA-miRNA network of ZBTB11 was constructed, and its interaction with chemicals and genes was investigated.

RESULTS

Our findings revealed that ZBTB11 was aberrantly expressed in a multitude of tumor types and exhibited variability across various tumor stages. A survival analysis revealed that ZBTB11 predicted a poor prognosis in BRCA, KIRP, LIHC, PCPG, PRAD, SARC, UCEC, and a good prognosis in CHOL, ESCA, GBM, KIRC, and READ. We also found that the most frequent genetic alterations type of ZBTB11 was mutation, and the DNA methylation level of ZBTB11 decreased in various cancers. Furthermore, ZBTB11 expression correlated with immune cells infiltration and genetic markers of immunodulators in cancers. Moreover, the results of single-cell sequencing demonstrated that ZBTB11 could regulate several tumor biological behaviors, including apoptosis, DNA damage, and angiogenesis. A lncRNA-miRNA network regulating ZBTB11 expression in tumor development and progression was constructed. It is of particular significance that ZBTB11 demonstrated a correlation with the CTRP and GDSC drug sensitivity, and that it served as a mediator between chemicals and cancers.

CONCLUSION

These findings demonstrate that ZBTB11 is associated with multiple tumor types and disease prognosis. ZBTB11 may represent a potential key biomarker and therapeutic target in cancers.

Investigation of the correlation between AGRN expression and perineural invasion in colon cancer

Background and Purpose

Colon cancer is one of the most common gastrointestinal malignancies. According to the traditional view, the primary modes of transmission include direct dissemination, hematogenous metastasis, and lymph node metastasis. In recent years, the role of perineural invasion (PNI) in the spread and metastasis of tumors has received immense attention. However, there are still relatively few reports on the potential mechanisms and biomarkers of PNI occurrence and development in colon cancer.

Method

We identified genes linked to the onset and progression of PNI in colon cancer using bioinformatics tools and extensive databases. Gene function enrichment analysis was used to explore the potential roles of these genes in tumor proliferation, invasion, and PNI. A collection of postoperative pathological specimens from colon cancer patients who underwent surgery, related clinicopathological data, and immunohistochemistry were used to validate AGRN expression in PNI tissues.

Results

Bioinformatics analysis revealed that AGRN is overexpressed in colon cancer tissues and correlates with poor patient prognosis. The findings from gene association and enrichment studies indicate that AGRN and its associated genes may play a role in PNI development and progression in colon cancer by simultaneously enhancing tumor cell invasion and neural cell growth. Immunohistochemical analysis of clinical samples confirmed that AGRN expression is elevated in colon cancer tissues with PNI.

Conclusion

We found that AGRN is significantly overexpressed in colon cancer tissues exhibiting PNI and is linked to poor patient survival. AGRN and its related genes may contribute to PNI by promoting tumor cell invasion and neural cell growth. Hence, AGRN may play a crucial role in the initiation and progression of PNI in colon cancer.

Methods in DNA methylation array dataset analysis: A review

Understanding the intricate relationships between gene expression levels and epigenetic modifications in a genome is crucial to comprehending the pathogenic mechanisms of many diseases. With the advancement of DNA Methylome Profiling techniques, the emphasis on identifying Differentially Methylated Regions (DMRs/DMGs) has become crucial for biomarker discovery, offering new insights into the etiology of illnesses. This review surveys the current state of computational tools/algorithms for the analysis of microarray-based DNA methylation profiling datasets, focusing on key concepts underlying the diagnostic/prognostic CpG site extraction. It addresses methodological frameworks, algorithms, and pipelines employed by various authors, serving as a roadmap to address challenges and understand changing trends in the methodologies for analyzing array-based DNA methylation profiling datasets derived from diseased genomes. Additionally, it highlights the importance of integrating gene expression and methylation datasets for accurate biomarker identification, explores prognostic prediction models, and discusses molecular subtyping for disease classification. The review also emphasizes the contributions of machine learning, neural networks, and data mining to enhance diagnostic workflow development, thereby improving accuracy, precision, and robustness.

Low expression of GRM4 is associated with poor prognosis and tumor immune infiltration in glioma

INTRODUCTION

The metabotropic glutamate receptor 4 (mGlu4, GRM4) exhibits significant expression within the central nervous system (CNS) and has been implicated to be correlated with a poor prognosis.

OBJECTIVE

This study was aimed to elucidate the relationship between the expression profile of GRM4 and the prognosis of glioma patients.

METHODS

RNA-sequencing datasets from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and China Glioma Genome Atlas (CGGA) repositories were used to evaluate the potential relationship. The value of clinical prognostic about GRM4 was assessed using clinical survival data from CGGA and TCGA. The GEPIA database was used to select genes like GRM4. PPI network was constructed by the database of (STRING), GO and KEGG analyses were performed. TargetScan, TarBase, miRDB, and starBase were used to explore miRNAs that could regulate GRM4 expression. EWAS Data Hub, MethSurv, and MEXPRESS were used for the analysis and relationship between DNA methylation and GRM4 expression and prognosis in glioma. TIMER2.0 and CAMOIP databases were used to assess the association between immune cell infiltration and GRM4. Human GBM cell lines were used to validate the function of GRM4.

RESULTS

Our study shows that GRM4 is under expressed among gliomas and accompanied by poorer OS. Multivariate analysis showed that low mRNA expression of GRM4 was an independent factor of prognostic for shorter OS in all glioma patients. MiR-1262 affects the malignant phenotype of gliomas through GRM4. Methylation of DNA plays an important role in the instruction of GRM4 expression, the methylation level of GRM4 in glioma tissue is higher in comparison to normal tissue, and the higher methylation level was accompanied with the worse prognosis. Further analysis showed that GRM4 mRNA expression in GBM linked negatively with common lymphoid progenitor, Macrophage M1, Macrophage, and T cell CD4+ Th2, but not with the tumor purity. Overexpression of GRM4 prevents the migration of human GBM cell lines in vitro.

CONCLUSION

GRM4 may have a substantial impact on the infiltration of immune cells and serve as a valuable prognostic biomarker in gliomas.

HSPA4 Expression is Correlated with Melanoma Cell Proliferation, Prognosis, and Immune Regulation

Purpose

Heat shock protein A4 (HSPA4) is associated with a variety of human diseases. However, its function in cutaneous malignant melanoma (CMM) remains uncertain.

Patients and Methods

The gene and protein expression level of HSPA4 in CMM was investigated with public databases. Cell Counting Kit-8 (CCK8) assay was performed to assess the effect of HSPA4 on the proliferation of melanoma cells. Then, the diagnostic and prognostic value of HSPA4 in CMM were analyzed. Gene variations and methylation levels, and the correlation between HSPA4 expression and immune cell infiltration were evaluated, followed by the construction of HSPA4 related protein-protein interaction networks and functional enrichment analysis.

Results

The mRNA and protein expression level of HSPA4 was significantly higher in CMM. Knocking down HSPA4 in A-375 cell line could inhibit tumor cell growth. The receiver operating characteristic (ROC) curve analysis confirmed the diagnostic value of HSPA4. Survival analysis showed that high expression of HSPA4 was associated with poor prognosis. HSPA4 gene alterations were observed in 3% of CMM patients. Five CpG sites are associated with the prognosis of CMM. HSPA4 is negatively correlated with most immune cells in CMM. The protein interaction network shows that HSPA4 is closely related to proteins such as DnaJ heat shock protein family (Hsp40) member B1 (DNAJB1) and DnaJ heat shock protein family (Hsp40) member B6 (DNAJB6), and the expression of DNAJB1 is positively correlated with HSPA4. Functional enrichment analysis indicated that HSPA4 may be associated with immune suppression and immune escape within the tumor microenvironment of CMM.

Conclusion

HSPA4 may participate in the regulation of tumor development and microenvironment, which may be a potential diagnostic and prognostic marker of CMM.

Identification of ETV5 as a prognostic marker related to epigenetic modification in pan-cancer and facilitates tumor progression in hepatocellular carcinoma

ETS variant transcription factor 5 (ETV5), a master transcription factor during development, exerts vital function on the occurrence and progression of various cancers. In order to systematically analyze and explore ETV5 potential specific regulatory mechanisms in pan-cancer, RNA sequencing data and clinicopathological features of patients with various tumors were obtained through the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, and an integrated data mining analysis was carried out, including the association of ETV5 expression with patient prognosis, drug sensitivity and epigenetic modification. The results revealed that abnormally highly expressed ETV5 resulted in unfavorable prognosis and differential drug sensitivity in multiple malignancies, and its expression was associated with epigenetic modification modulators including EZH2. ETV5 related genes were enriched in tumorigenesis biological processes and signaling pathways. In hepatocellular carcinoma, ETV5 expression was correlated with patients' tumor pathological stage and resulted in adverse outcome of patients. Our further experiments evidences indicated that ETV5 facilitated cell proliferation and reduced sensitivity to GSK126 via regulating EZH2. Collectively, this study comprehensively elucidates the carcinogenic effects and molecular mechanisms of ETV5 in tumorigenesis and development, and provides theoretical basis and guidance for tumor diagnosis, targeted therapy for ETV5 and clinical epigenetic drug research.

LATS2 and FAT4 as key candidate genes of hippo pathway associated with the risk and progression of breast cancer: an in-silico approach

BACKGROUND

The 2020 cancer report states that breast cancer remains a significant cause of death for females, despite the use of various strategies for early detection and treatment. However, there are still gaps in the fight against this disease. Researchers are exploring the hippo pathway, one of eight significant pathways involved in cancer progression, for potential biomarkers to use in personalized therapeutics.

METHODS

The current study used bioinformatic tools such as DEGs analysis, Methsurv, Km Plotter to generate data that can predict molecular biomarkers associated with hippo pathway in breast cancer development and treatment. The protein-protein interaction pathway was generated using the STRING database to find associations of hippo pathway genes with other dysregulated genes in breast cancer datasets. A disease enrichment study was also done to explore the potential of the hippo pathway in various aspects.

RESULTS

LATS2 and FAT4 genes of the hippo pathway have shown an interesting association with overall survival, hypermethylation, genetic alterations, and decreased expression levels in the breast cancer cohort. Our findings suggest that both of these genes are associated with breast cancer progression and diagnosis and can be utilized as predictive biomarkers by oncologists for personalized therapy in patients.

The impacts of dipeptidyl- peptidase 4 (DPP-4) inhibitors on common female malignancies: A systematic review

The inhibition of dipeptidyl- peptidase 4 (DPP-4) is an essential therapy for controlling hyperglycemia in patients with type 2 diabetes (T2DM). However, the role of DPP-4 in cancer is not yet clear, with some studies suggesting that it may either promote or suppress tumors. This makes it crucial to have personalized treatment for diabetic women with cancer to effectively manage their diabetes whilst and preventing cancer mortality. To address this issue, we conducted an integrative in-silico analysis and systematic review of the literature to comprehensively examine the relationship between DPP-4 expression and the effects of its inhibitors on prevalent female malignancies. We specifically chose studies that examined the effects of DPP-4 expression and DPP-4 inhibition (DPP-4i) on prevalent cancers in women, such as breast cancer (BC), ovarian cancer (OV), cervical cancer (CC), and endometrial cancer (EC). These studies comprised those conducted both in vivo and in vitro. The review of the literature indicated that DPP-4i may worsen aggressive traits such as metastasis, Epithelial-to-mesenchymal transition (EMT), and chemotherapy resistance in BC cells. However, cohort studies on diabetic and BC patients did not confirm these findings. In vitro studies indicate that on OV, DPP-4 upregulation has been shown to prevent metastasis, while CCappears to be influenced by DPP-4 expression in terms of cell migration. sitagliptin, a pharmaceutical inhibitor of DPP-4, had a significant impact on reducing adhesion in CC cells in vitro. Overexpression of DPP-4 increased cell migration and proliferation in CC and EC cells, and hence the application of sitagliptin is expected to prevent this effect. On the other hand, the result of in-silico data confirmed that a significant correlation exists between DPP-4 expression and immune cell infiltration in breast, ovarian, cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) as well as downregulated in these cancers compared to their normal tissue samples. Furthermore, a significant (p < 0.05) effect on OS of BC and CESC patients has been reported due to the elevation of DPP-4 methylation on a specific CPG Island. These findings could aid in creating specialized treatments for diabetic women with specific malignancies, but caution should be exercised when considering the patient's medical history and cancer type.

Discovery of key molecular signatures for diagnosis and therapies of glioblastoma by combining supervised and unsupervised learning approaches

Glioblastoma (GBM) is the most malignant brain cancer and one of the leading causes of cancer-related death globally. So, identifying potential molecular signatures and associated drug molecules are crucial for diagnosis and therapies of GBM. This study suggested GBM-causing ten key genes (ASPM, CCNB2, CDK1, AURKA, TOP2A, CHEK1, CDCA8, SMC4, MCM10, and RAD51AP1) from nine transcriptomics datasets by combining supervised and unsupervised learning results. Differential expression patterns of key genes (KGs) between GBM and control samples were verified by different independent databases. Gene regulatory network (GRN) detected some important transcriptional and post-transcriptional regulators for KGs. The KGs-set enrichment analysis unveiled some crucial GBM-causing molecular functions, biological processes, cellular components, and pathways. The DNA methylation analysis detected some hypo-methylated CpG sites that might stimulate the GBM development. From the immune infiltration analysis, we found that almost all KGs are associated with different immune cell infiltration levels. Finally, we recommended KGs-guided four repurposable drug molecules (Fluoxetine, Vatalanib, TGX221 and RO3306) against GBM through molecular docking, drug likeness, ADMET analyses and molecular dynamics simulation studies. Thus, the discoveries of this study could serve as valuable resources for wet-lab experiments in order to take a proper treatment plan against GBM.

Multi-omics analysis of the biological function of the VEGF family in colon adenocarcinoma

The vascular endothelial growth factor (VEGF) family plays a crucial role in cancer progression, but the prognostic significance and biological functions of VEGF family members in colon adenocarcinoma (COAD) remain unclear. Using data from The Cancer Genome Atlas, Gene Expression Omnibus, Gene Set Cancer Analysis, cBioPortal, GeneMANIA, String, MethSurv and starBase database, we identified vascular endothelial growth factor B (VEGFB) as a key gene associated with COAD prognosis, with its abnormal expression linked to methylation dysregulation. In vitro experiments confirmed VEGFB expression was significantly higher in colon cancer tissues compared to normal tissues, as shown by Real-time quantitative PCR and immunohistochemistry. Cell Counting Kit-8 and colony formation assay showed that decreased VEGFB expression in SW480 cells resulted in decreased cell viability and proliferation ability. Scratch assay showed that VEGFB downregulation impaired SW480 cell migration. In addition, our research suggests that VEGFB not only promotes angiogenesis but is also involved in the tumor microenvironment and immune regulation. The SHNG17-miR-375-VEGFB regulatory axis provides a potential therapeutic target for COAD, highlighting VEGFB's role in immune activation during anti-angiogenic therapy and potential reversal of drug resistance.

Pan-cancer analysis of ADAR1 with its prognostic relevance in low-grade glioma

ADAR1, known as the primary enzyme for adenosine-to-inosine RNA editing, has recently been implicated in cancer development through both RNA editing-dependent and -independent pathways. These discoveries suggest that ADAR1's functions may extend beyond our current understanding. A pan-cancer analysis offers a unique opportunity to identify both common and distinct mechanisms across various cancers, thereby advancing personalized medicine. Low-grade glioma (LGG), characterized by a diverse group of tumor cells, presents a challenge in risk stratification, leading to significant variations in treatment approaches. Recently discovered molecular alterations in LGG have helped to refine the stratification of of these tumors and offered novel targets for predicting likely outcomes. This study aims to provide a detailed analysis of ADAR mRNA across multiple cancers, emphasizing its prognostic significance in LGG. We observed inconsistent mRNA and consistent protein expression patterns of ADAR1/ADAR in pan-cancer analyses that across tumor types. ADAR mRNA expression did not always correlate with ADAR1 protein expression. Nevertheless, the transcript levels correlated significantly with genetic alterations, tumor mutation burden, microsatellite instability, overall survival, recurrence-free survival, immune marker presence, immune infiltration, and the survival of patients undergoing immunotherapy in select cancers. Furthermore, ADAR and its top 50 associated genes were primarily involved in mRNA-related events, as identified through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Utilizing the Cox proportional hazards model, we developed a 3-gene signature (ADAR, HNRNPK, and SMG7), which effectively stratified patients into high- and low-risk groups, with high-risk patients exhibiting poorer overall survival, higher tumor grades, and a greater number of non-codeletions. Overall, this signature was inversely related to immune infiltration across cancers. Transcription factor SPI1 and miR-206, potential upstream regulators of the signature genes, were closely linked to patient survival in LGG. The promoter regions of these genes were hypermethylated, further associating them with patient outcomes. Additionally, these genes displayed consistent drug susceptibility patterns. In conclusion, our findings reveal multiple aspects of ADAR1's role in cancer and underscore its prognostic value in LGG, offering insights into potential therapeutic targets and strategies.

Single-Cell RNA Sequencing Reveals Monocyte-Derived Interstitial Macrophages with a Pro-Fibrotic Phenotype in Bleomycin-Induced Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease with limited effective therapies. Interstitial macrophages (IMs), especially those derived from monocytes, play an unknown role in IPF pathogenesis. By using single-cell RNA sequencing (scRNA-seq), bleomycin (BLM)-induced pulmonary fibrosis mouse lungs were analyzed to characterize the cellular landscape and heterogeneity of macrophages in this model. scRNA-seq was used to identify distinct interstitial macrophage subpopulations in fibrotic lungs, with monocyte-derived macrophages exhibiting a pro-fibrotic gene expression profile enriched in wound healing, extracellular matrix (ECM) remodeling, and pro-fibrotic cytokine production functions. A pseudotime analysis revealed that IMs originated from monocytes and differentiated along a specific trajectory. A cell-cell communication analysis demonstrated strong interactions between monocyte-derived interstitial macrophages (Mo-IMs) and fibroblasts through the transforming growth factor beta (TGFβ), secreted phosphoprotein 1 (SPP1), and platelet-derived growth factor (PDGF) signaling pathways. Flow cytometry validated the presence and expansion of Mo-IMs subpopulations in BLM-treated mice. This study reveals the cellular heterogeneity and developmental trajectory of lung macrophages in early BLM-induced pulmonary fibrosis, highlighting the crucial role of Mo-IMs with a pro-fibrotic phenotype in IPF pathogenesis via interactions with fibroblasts. Targeting these specific macrophage subpopulations and associated signaling pathways may provide novel therapeutic strategies for IPF.

ABCG2 Gene Expression in Non-Small Cell Lung Cancer

Background/Objectives: ATP-binding cassette subfamily G member 2 [ABCG2/breast cancer resistance protein (BCRP)] contributes to mechanisms of multidrug resistance (MDR) and is a marker of side population (SP) cells in human cancers. The primary objective of this study was to investigate the impact of ABCG2 gene expression on the non-small cell lung cancer (NSCLC) development, course of cancer disease, and patient prognosis using publicly available data. Obtained results were supplemented with assessment of ABCG2 expression in blood of NSCLC patients. Methods: The dataset of lung cancer was analyzed utilizing the TIMER 2.0, UALCAN, TNMplot, MEXPRESS, cBioPortal, MethSurv, KM Plotter, STRING, and ShinyGO 0.80 databases. Blood samples from 50 patients were assessed using the real-time PCR method. Results: The ABCG2 gene was expressed at a low level in NSCLC, and did not correlate with clinical aggressiveness of lung cancer. Higher ABCG2 expression improved overall survival, but only in LUAD. In addition, CpG sites located on the CpG island affecting the NSCLC patient's prognosis were indicated. In the case of our own laboratory results, the study did not reveal any changes in the ABCG2 expression levels in blood collected from patients at different time points during the diagnostic-therapeutic procedure. In the in silico analysis, most ABCG2 protein interactors were associated with the development of drug resistance. Conclusions: ABCG2 appears to have a particularly significant impact on the survival of patients with lung cancer and on the effect of immunotherapy related to immune cell infiltration. Presented findings may support personalized medicine strategies based on bioinformatics findings.

ENO1 as a Biomarker of Breast Cancer Progression and Metastasis: A Bioinformatic Approach Using Available Databases

Background

Metabolic reprogramming is one of the hallmarks of cancer, and in breast cancer (BC), several metabolic enzymes are overexpressed and overactivated. One of these, Enolase 1 (ENO1), catalyses glycolysis and is involved in the regulation of multiple signalling pathways.

Objectives

This study aimed to evaluate in silico the prognostic and predictive effects of ENO1 expression in BC.

Design

This is a bioinformatic in silico analysis.

Methods

Using available online platforms (Kaplan-Meier [KM] plotter, receiver operating characteristic curve [ROC] plotter, cBioPortal, Genotype-2-Outcome [G-2-O], MethSurv, and Tumour-Immune System Interaction Database [TISIDB]), we performed a bioinformatic in silico analysis to establish the prognostic and predictive effects related to ENO1 expression in BC. A network analysis was performed using the Oncomine platform, and signalling, epigenetic, and immune regulation pathways were explored.

Results

ENO1 was overexpressed in all the analysed Oncomine, epigenetic, and immune pathways in triple-negative, but not in hormone receptor-positive BCs. In human epidermal growth factor receptor 2 (HER2)-positive BCs, ENO1 expression showed a mixed profile. Analysis on disease progression and histological types showed ENO1 overexpression in ductal in situ and invasive carcinoma, in high-grade tumours followed by advanced or metastasis and was linked to worse survival. High ENO1 expression was also associated with relapse-free, distant metastasis-free and overall survival, irrespectively of treatment and was mainly related to basal subtype.

Conclusion

ENO1 overexpression recruits a range of signalling pathways during disease progression conferring a worse prognosis and can be potentially used as a biomarker of disease progression and therapeutic target, particularly in triple-negative and in ductal invasive carcinoma.

ST3GAL4 promotes tumorigenesis in breast cancer by enhancing aerobic glycolysis

Sialyltransferases are enzymes that play a crucial role in regulating cancer progression by modifying glycoproteins through sialylation. In particular, the ST3 beta-galactoside alpha-2,3-sialyltransferase 4 (ST3GAL4) enzyme is known to be upregulated in breast cancer, but its specific biological functions have not been fully understood. This study aimed to investigate the impact and mechanisms of ST3GAL4 on aerobic glycolysis in breast cancer. We examined ST3GAL4 expression in tumor tissue samples and breast cancer cell lines and also manipulated ST3GAL4 expression in breast cancer cells using lentivirus transduction. The study evaluated cellular processes such as cell viability, cell cycle progression, and aerobic glycolysis by measuring parameters like extracellular acidification rate, glucose uptake, lactate production, and lactate dehydrogenase A (LDHA) expression. We found that ST3GAL4 expression was consistently increased in tumor tissues and breast cancer cell lines. High ST3GAL4 expression was associated with a poor prognosis for patients with breast cancer. Inhibiting ST3GAL4 expression decreased cell viability, disrupted cell cycle progression, and reduced aerobic glycolysis and LDHA expression. Furthermore, suppressing ST3GAL4 expression in animal models reduced tumor growth and cell proliferation. Conversely, overexpressing ST3GAL4 promoted cell viability and cell cycle progression, but these effects were reversed when an inhibitor of aerobic glycolysis was used. The study provided evidence in cells and animal models that ST3GAL4 promotes tumorigenesis in breast cancer by enhancing aerobic glycolysis. These findings suggest that targeting ST3GAL4 may be a potential strategy for the treatment of breast cancer.

PER3 promoter hypermethylation correlates to the progression of pan-cancer

BACKGROUND

Malignant cells exhibit reduced period circadian regulator 3 (PER3) expression. However, the underlying mechanisms of variations in PER3 expression in cancers and the specific function of PER3 in tumor progression remain poorly understood.

RESULTS

We explored multiple public databases, conducted bioinformatics analyses, and performed in vitro and in vivo experiments for validation. We found PER3 expression was decreased in most types of cancers, and PER3 downregulation was associated with a poor prognosis in 8 types of cancer. PER3 promoter methylation levels were increased in 11 types of cancer. Promoter hypermethylation (CpG islands [CGIs] cg12258811 and cg14204433) correlated with decreased PER3 expression in six cancers (breast invasive carcinoma, colon adenocarcinoma, head and neck squamous cell carcinoma, kidney renal papillary cell carcinoma [KIRP], lung adenocarcinoma [LUAD], and uterine corpus endometrial carcinoma). CGI cg12258811 hypermethylation was associated with reduced survival time and advanced cancer stages. Moreover, the bisulfite pyrosequencing assay confirmed CGI cg12258811 hypermethylation and its negative correlation with PER3 expression. In vitro and in vivo experiments demonstrated that PER3 inhibited KIRP and LUAD progression. Decitabine enhanced PER3 expression and inhibited KIRP cell functions by reducing promoter (cg12258811) methylation level.

CONCLUSIONS

Our findings advanced the mechanistic understanding of variations in PER3 expression in cancers and confirmed the tumor-associated function of PER3 hypermethylation and downregulation.

Comprehensive analysis of MAPK genes in the prognosis, immune characteristics, and drug treatment of renal clear cell carcinoma using bioinformatic analysis and Mendelian randomization

Mitogen-activated protein kinase (MAPK) signalling is vitally important in tumour development and progression. This study is the first to comprehensively analyse the role of MAPK-family genes in the progression, prognosis, immune-cell infiltration, methylation, and potential therapeutic value drug candidates in ccRCC. We identified a novel prognostic panel of six MAPK-signature genes (MAP3K12, MAP3K1, MAP3K5, MAPK1, MAPK8, MAPK9), and introduced a robust MAPK-signature risk model for predicting ccRCC prognosis. Model construction, evaluation, and external validation using datasets from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database demonstrated its stability, as well as high sensitivity and specificity. Enrichment analysis suggested the participation of immune-mediated mechanism in MAPK dysregulation in ccRCC. Immune-infiltration analysis confirmed the relationship and revealed that the MAPK-signature risk model might stratify immunotherapy response in ccRCC, which was verified in drug sensitivity analysis and validated in external ccRCC immunotherapy dataset (GSE67501). Potential therapeutic drug predictions for key MAPKs using DSigDB, Network Analyst, CTD, and DGIdb were subsequently verified by molecular docking with AutoDock Vina and PyMol. Mendelian randomization further demonstrated the possibilities of the MAPK-signature genes as targets for therapeutic drugs in ccRCC. Methylation analysis using UALCAN and MethSurv revealed the participation of epigenetic modifications in dysregulation and survival difference of MAPK pathway in ccRCC. Among the key MAPKs, MAP3K12 exhibited the highest significance, indicating its independent prognostic value as single gene in ccRCC. Knockout and overexpression validation experiments in vitro and in vivo found that MAP3K12 acted as a promoter of tumour progression in RCC, suggesting a pivotal role for MAP3K12 in the proliferation, migration, and invasion of RCC cells. Our findings proposed the potential of MAPK-signature genes as biomarkers for prognosis and therapy response, as well as targets for therapeutic drugs in ccRCC.

Screening of differential gene expression patterns through survival analysis for diagnosis, prognosis and therapies of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of kidney cancer. Although there is increasing evidence linking ccRCC to genetic alterations, the exact molecular mechanism behind this relationship is not yet completely known to the researchers. Though drug therapies are the best choice after the metastasis, unfortunately, the majority of the patients progressively develop resistance against the therapeutic drugs after receiving it for almost 2 years. In this case, multi-targeted different variants of therapeutic drugs are essential for effective treatment against ccRCC. To understand molecular mechanisms of ccRCC development and progression, and explore multi-targeted different variants of therapeutic drugs, it is essential to identify ccRCC-causing key genes (KGs). In order to obtain ccRCC-causing KGs, at first, we detected 133 common differentially expressed genes (cDEGs) between ccRCC and control samples based on nine (9) microarray gene-expression datasets with NCBI accession IDs GSE16441, GSE53757, GSE66270, GSE66272, GSE16449, GSE76351, GSE66271, GSE71963, and GSE36895. Then, we filtered these cDEGs through survival analysis with the independent TCGA and GTEx database and obtained 54 scDEGs having significant prognostic power. Next, we used protein-protein interaction (PPI) network analysis with the reduced set of 54 scDEGs to identify ccRCC-causing top-ranked eight KGs (PLG, ENO2, ALDOB, UMOD, ALDH6A1, SLC12A3, SLC12A1, SERPINA5). The pan-cancer analysis with KGs based on TCGA database showed the significant association with different subtypes of kidney cancers including ccRCC. The gene regulatory network (GRN) analysis revealed some crucial transcriptional and post-transcriptional regulators of KGs. The scDEGs-set enrichment analysis significantly identified some crucial ccRCC-causing molecular functions, biological processes, cellular components, and pathways that are linked to the KGs. The results of DNA methylation study indicated the hypomethylation and hyper-methylation of KGs, which may lead the development of ccRCC. The immune infiltrating cell types (CD8+ T and CD4+ T cell, B cell, neutrophil, dendritic cell and macrophage) analysis with KGs indicated their significant association in ccRCC, where KGs are positively correlated with CD4+ T cells, but negatively correlated with the majority of other immune cells, which is supported by the literature review also. Then we detected 10 repurposable drug molecules (Irinotecan, Imatinib, Telaglenastat, Olaparib, RG-4733, Sorafenib, Sitravatinib, Cabozantinib, Abemaciclib, and Dovitinib.) by molecular docking with KGs-mediated receptor proteins. Their ADME/T analysis and cross-validation with the independent receptors, also supported their potent against ccRCC. Therefore, these outputs might be useful inputs/resources to the wet-lab researchers and clinicians for considering an effective treatment strategy against ccRCC.

Host genetics and microbiota data analysis in colorectal cancer research

Colorectal cancer (CRC) is a heterogeneous disease with a complex aetiology influenced by a myriad of genetic and environmental factors. Despite advances in CRC research, it is a major burden of disease, with the second highest incidence and third leading cause of cancer deaths worldwide. To individualise diagnosis, prognosis, and treatment of CRC, developing new strategies combining precision medicine and bioinformatic procedures is promising. Precision medicine is based on omics technologies and aims to individualise the management of CRC based on patient host genetic characteristics and microbiota. Bioinformatics is central to the application of personalised medicine because it enables the analysis of large datasets generated by these technologies. At the level of host genetics, bioinformatics allows the identification of mutations, genes, molecular pathways, biomarkers and drugs relevant to colorectal carcinogenesis. At the microbiota level, bioinformatics is fundamental to analysing microbial communities' composition and functionality and developing biomarkers and personalised microbiota-based therapies. This paper explores the host and microbiota genetic data analysis in CRC research.

Exploring the Correlation Between Hypoxia, HIF1A Variants, and Breast Cancer in Different Ethnicities, and Bangladeshi Women: Through ELISA and Integrative Multi-Omics Analysis

Background

Hypoxia, a condition where there is a lack of oxygen, is known to play a role in cancer progression.

Objective

This study investigates the correlation between HIF1A gene-altered expression and hypoxia in Bangladeshi breast cancer (BC) cases and TCGA_BC datasets.

Design

This case-control study compares BC cases to healthy controls to understand the relationship between gene changes and cancer.

Method

This study used advanced analysis methods to examine the transcriptional landscape of BC, and quantitatively assessed its correlation using integrated multi-omics analysis.

Results

In Bangladeshi BC cases, the T allele of HIF1A rs1154946 correlates notably (P-value < .001) with BC incidence. ELISA results confirmed a significant association (P-value < .005) between elevated HIF1A expression and BC-related hypoxia. Bioinformatics eQTL analysis validated the correlation between increased HIF1A expression and rs11549465 T allele (P-value < .01). Structural analyses suggested that rs11549465 (P582S) mutation may decrease protein stability (ΔΔG-value: -1.24 kcal/mole), potentially affecting HIF1A function. HIF1A enrichment analysis in BC underscores strong associations with oxygen levels, hypoxia, metabolic processes, apoptosis, and programed cell death (P-value < .001). Transcriptomic data demonstrated a robust correlation (P-value < .0001) between HIF1A expression and copy-number alterations, mutations, and abnormal methylation. Altered HIF1A expression showed strong negative correlations (P-value < .00001) with methylation and the expression of the ER (ESR1), in Whites. Survival analysis revealed marked differences in overall survival linked to high and low HIF1A expression (P-value < .00001). Furthermore, HIF1A expression significantly correlated (P-value < .000001) with hypoxia, TMB, MSI, and immune infiltration by CD8+ T cells, neutrophils, dendritic, and macrophages, providing deeper insights into the BC microenvironment.

Conclusion

Thus, the HIF1A gene could serve as a promising biomarker for breast cancer progression, control, and survival across ethnicities, emphasizing its role in disease development and regulation.

FAM109B plays a tumorigenic role in low-grade gliomas and is associated with tumor-associated macrophages (TAMs)

BACKGROUND

Family with sequence similarity 109, member B (FAM109B) is involved in endocytic transport and affects genetic variation in brain methylation. It is one of the important genes related to immune cell-associated diseases. In the tumor immune system, methylation can regulate tumor immunity and influence the maturation and functional response of immune cells. Whether FAM109B is involved in tumor progression and its correlation with the tumor immune microenvironment has not yet been disclosed.

METHODS

A comprehensive pan-cancer analysis of FAM109B expression, prognosis, immunity, and TMB was conducted. The expression, clinical features, and prognostic value of FAM109B in low-grade gliomas (LGG) were evaluated using TCGA, CGGA, and Gravendeel databases. The expression of FAM109B was validated by qRT-PCR, immunohistochemistry (IHC), and Western blotting (WB). The relationship between FAM109B and methylation, Copy Number Variation (CNV), prognosis, immune checkpoints (ICs), and common chemotherapy drug sensitivity in LGG was explored through Cox regression, Kaplan-Meier curves, and Spearman correlation analysis. FAM109B levels and their distribution were studied using the TIMER database and single-cell analysis. The potential role of FAM109B in gliomas was further investigated through in vitro and in vivo experiments.

RESULTS

FAM109B was significantly elevated in various tumor types and was associated with poor prognosis. Its expression was related to aggressive progression and poor prognosis in low-grade glioma patients, serving as an independent prognostic marker for LGG. Glioma grade was negatively correlated with FAM109B DNA promoter methylation. Immune infiltration and single-cell analysis showed significant expression of FAM109B in tumor-associated macrophages (TAMs). The expression of FAM109B was closely related to gene mutations, immune checkpoints (ICs), and chemotherapy drugs in LGG. In vitro studies showed increased FAM109B expression in LGG, closely related to cell proliferation. In vivo studies showed that mice in the sh-FAM109B group had slower tumor growth, slower weight loss, and longer survival times.

CONCLUSIONS

FAM109B, as a novel prognostic biomarker for low-grade gliomas, exhibits specific overexpression in TAMs and may be a potential therapeutic target for LGG patients.

Bioinformatics tools and resources for cancer and application

ABSTRACT

Tumor bioinformatics plays an important role in cancer research and precision medicine. The primary focus of traditional cancer research has been molecular and clinical studies of a number of fundamental pathways and genes. In recent years, driven by breakthroughs in high-throughput technologies, large-scale cancer omics data have accumulated rapidly. How to effectively utilize and share these data is particularly important. To address this crucial task, many computational tools and databases have been developed over the past few years. To help researchers quickly learn and understand the functions of these tools, in this review, we summarize publicly available bioinformatics tools and resources for pan-cancer multi-omics analysis, regulatory analysis of tumorigenesis, tumor treatment and prognosis, immune infiltration analysis, immune repertoire analysis, cancer driver gene and driver mutation analysis, and cancer single-cell analysis, which may further help researchers find more suitable tools for their research.

A novel super-enhancer-related risk model for predicting prognosis and guiding personalized treatment in hepatocellular carcinoma

BACKGROUND

Our research endeavored to develop a robust predictive signature grounded in super-enhancer-related genes (SERGs), with the dual objectives of forecasting survival outcomes and evaluating the tumor immune microenvironment (TiME) in hepatocellular carcinoma (HCC).

METHODS

HCC RNA-sequencing data were retrieved from The Cancer Genome Atlas (TCGA), and 365 patients were randomly assigned to training or testing sets in 1:1 ratio. SERGs of HCC were downloaded from Super-Enhancer Database (SEdb). On the basis of training set, a SERGs signature was identified, and its prognostic value was confirmed by internal and external validation (GSE14520) sets. We subsequently examined the model for potential functional enrichment and the degree of tumor immune infiltration. Additionally, we carried out in vitro experiments to delve into the biological functions of CBX2 gene.

RESULTS

An SE-related prognostic model including CBX2, TPX2, EFNA3, DNASE1L3 and SOCS2 was established and validated. According to this risk model, patients in the high-risk group had a significantly worse prognosis, and their immune cell infiltration was significantly different from that of low-risk group. Moreover, the high-risk group exhibited a significant enrichment of tumor-associated pathological pathways. The SERGs signature can generally be utilized to screen HCC patients who are likely to respond to immunotherapy, as there is a positive correlation between the risk score and the Tumor Immune Dysfunction and Exclusion (TIDE) score. Furthermore, the downregulation of the CBX2 gene expression was found to inhibit HCC cell viability, migration, and cell cycle progression, while simultaneously promoting apoptosis.

CONCLUSIONS

We developed a novel HCC prognostic model utilizing SERGs, indicating that patients with high-risk score not only face a poorer prognosis but also may exhibit a diminished therapeutic response to immune checkpoint inhibitors (ICIs). This model is designed to tailor personalized treatment strategies to the individual needs of each patient, thereby improving the overall clinical outcomes for HCC patients. Furthermore, CBX2 is a promising candidate for therapeutic intervention in HCC.

Stanniocalcin Protein Expression in Female Reproductive Organs: Literature Review and Public Cancer Database Analysis

Stanniocalcin (STC) 1 and 2 serve as antihyperglycemic polypeptide hormones with critical roles in regulating calcium and phosphate homeostasis. They additionally function as paracrine and/or autocrine factors involved in numerous physiological processes, including female reproduction. STC1 and STC2 contribute to the pathophysiology of several diseases, including female infertility- and pregnancy-associated conditions, and even tumorigenesis of reproductive organs. This comprehensive review highlights the dynamic expression patterns and potential dysregulation of STC1 and STC2, restricted to female fertility, and infertility- and pregnancy-associated diseases and conditions, such as endometriosis, polycystic ovary syndrome (PCOS), abnormal uterine bleeding, uterine polyps, and pregnancy complications, like impaired decidualization, preeclampsia, and preterm labor. Furthermore, the review elucidates the role of dysregulated STC in the progression of cancers of the reproductive system, including endometrial, cervical, and ovarian cancers. Additionally, the review evaluates the expression patterns and prognostic significance of STC in gynecological cancers by utilizing existing public datasets from The Cancer Genome Atlas to help decipher the multifaceted roles of these pleiotropic hormones in disease progression. Understanding the intricate mechanisms by which STC proteins influence all these reviewed conditions could lead to the development of targeted diagnostic and therapeutic strategies in the context of female reproductive health and oncology.

Bioinformatics analysis to disclose shared molecular mechanisms between type-2 diabetes and clear-cell renal-cell carcinoma, and therapeutic indications

Type 2 diabetes (T2D) and Clear-cell renal cell carcinoma (ccRCC) are both complicated diseases which incidence rates gradually increasing. Population based studies show that severity of ccRCC might be associated with T2D. However, so far, no researcher yet investigated about the molecular mechanisms of their association. This study explored T2D and ccRCC causing shared key genes (sKGs) from multiple transcriptomics profiles to investigate their common pathogenetic processes and associated drug molecules. We identified 259 shared differentially expressed genes (sDEGs) that can separate both T2D and ccRCC patients from control samples. Local correlation analysis based on the expressions of sDEGs indicated significant association between T2D and ccRCC. Then ten sDEGs (CDC42, SCARB1, GOT2, CXCL8, FN1, IL1B, JUN, TLR2, TLR4, and VIM) were selected as the sKGs through the protein-protein interaction (PPI) network analysis. These sKGs were found significantly associated with different CpG sites of DNA methylation that might be the cause of ccRCC. The sKGs-set enrichment analysis with Gene Ontology (GO) terms and KEGG pathways revealed some crucial shared molecular functions, biological process, cellular components and KEGG pathways that might be associated with development of both T2D and ccRCC. The regulatory network analysis of sKGs identified six post-transcriptional regulators (hsa-mir-93-5p, hsa-mir-203a-3p, hsa-mir-204-5p, hsa-mir-335-5p, hsa-mir-26b-5p, and hsa-mir-1-3p) and five transcriptional regulators (YY1, FOXL1, FOXC1, NR2F1 and GATA2) of sKGs. Finally, sKGs-guided top-ranked three repurposable drug molecules (Digoxin, Imatinib, and Dovitinib) were recommended as the common treatment for both T2D and ccRCC by molecular docking and ADME/T analysis. Therefore, the results of this study may be useful for diagnosis and therapies of ccRCC patients who are also suffering from T2D.