GSCA: an integrated platform for gene set cancer analysis at genomic, pharmacogenomic and immunogenomic levels

UFMylation in tumorigenesis: Mechanistic insights and therapeutic opportunities

Post-translational modification (PTM) is an essential mechanism that regulates protein function within cells, influencing aspects such as protein activity, stability, subcellular localization, and interactions with other molecules through the addition or removal of chemical groups on amino acid residues. One notable type of PTM is UFMylation, a recently discovered modification process that involves the covalent attachment of UFM1 to lysine residues on target proteins. This process is facilitated by a specific enzyme system that includes the UFM1-activating enzyme, the UFM1-conjugating enzyme, and the UFM1-specific ligase. UFMylation is crucial for various cellular functions, such as responding to endoplasmic reticulum stress and DNA-damage response, and it is linked to the development and progression of several human diseases, including cancers, highlighting its importance in biological processes. Despite this significance, the range of substrates, regulatory mechanisms, and biological processes associated with UFMylation are not well understood, with only a few substrates having been characterized. Here, we focus on the molecular mechanisms of UFMylation, its implications in tumorigenesis, and its interactions with tumor suppressive and oncogenic signaling pathways. Furthermore, we employed bioinformatics approaches to analyze UFMylation's role in cancer, focusing on expression profiles, mutations, prognosis, drug sensitivity, and immune infiltration to explore its therapeutic potential in immunotherapy.

Pan-cancer characterization of C-C motif chemokine ligand 5 (CCL5) identifies its role as biomarker and therapeutic target

OBJECTIVES

C-C Motif Chemokine Ligand 5 (CCL5) is known for its role in immune regulation and has been implicated in cancer progression. However, its expression and prognostic significance in pan-cancer require comprehensive evaluation. This study was initiated to decipher the pan-cancer role of CCL5 genes.

METHODS

In silico analyses involving various online databases and molecular experiments involving CCL5 knockdown experiments in KIRC cell lines evaluated its role in cell proliferation, colony formation, and migration.

RESULTS

CCL5 expression was significantly up-regulated in several cancers. High CCL5 expression correlated with poorer overall survival in kidney renal cell carcinoma (KIRC) and esophageal cancer (ESCA) patients. Promoter hypomethylation correlated with elevated CCL5 expression and poorer prognosis. CCL5 mutations were rare; indicating its role in cancer is driven by overexpression rather than genetic alterations. Positive correlations with immune inhibitory and MHC genes suggested CCL5's role in fostering an immunosuppressive tumor microenvironment. High CCL5 expression correlated with increased immune cell infiltration, particularly CD8 T cells and macrophages. CCL5 expression did not significantly influence drug sensitivity. CCL5 knockdown in resulted in reduced proliferation, colony formation, and migration, underscoring its critical role in cancer cell dynamics.

CONCLUSION

Our study highlights the significance of CCL5 in cancer progression and prognosis, particularly in KIRC and ESCA. CCL5's role in modulating the tumor immune microenvironment and its potential as a therapeutic target warrant further investigation.

Identification of hub genes, non-coding RNAs and pathways in Renal cell carcinoma (RCC): A comprehensive in silico study

Backgrounds

Renal cell carcinoma (RCC) is the most common type of kidney cancer in adults. RCC begins in the renal tubule epithelial cells, essential for blood filtration and urine production.

Methods

In this study, we aim to uncover the molecular mechanisms underlying kidney renal clear cell carcinoma (KIRC) by analyzing various non-coding RNAs (ncRNAs) and protein-coding genes involved in the disease. Using high-throughput sequencing datasets from the Gene Expression Omnibus (GEO), we identified differentially expressed mRNAs (DEMs), miRNAs (DEMIs), and circRNAs (DECs) in KIRC samples compared to normal kidney tissues. Our approach combined differential expression analysis, functional enrichment through Gene Ontology (GO) and KEGG pathway mapping, and a Protein-Protein Interaction (PPI) network to identify crucial hub genes in KIRC progression.

Results

Key findings include the identification of hub genes such as EGFR, FN1, IL6, and ITGAM, which were closely associated with immune responses, cell signaling, and metabolic dysregulation in KIRC. Further analysis indicated that these genes could be potential biomarkers for prognosis and therapeutic targets. We constructed a competitive endogenous RNA (ceRNA) network involving lncRNAs, circRNAs, and miRNAs, suggesting complex regulatory interactions that drive KIRC pathogenesis.Additionally, the study examined drug sensitivity associated with the expression of hub genes, revealing the potential for personalized treatments. Immune cell infiltration patterns showed significant correlations with hub gene expression, highlighting the importance of immune modulation in KIRC.

Conclusion

This research provides a foundation for developing targeted therapies and diagnostic biomarkers for KIRC while underscoring the need for experimental validation to confirm these bioinformatics insights.

A novel 5-differentially expressed gene (DEG) signature predicting the prognosis in patients with metastatic liver malignancies and the prognostic and therapeutic potential of SPP1

BACKGROUND

This study aimed to identify differentially expressed genes (DEGs) that are associated with hepatocarcinogenesis and metastasis in hepatocellular carcinoma (HCC) and to explore their value in predicting overall survival (OS). The methods used included bioinformatics analysis of gene expression datasets and in vitro experiments using HCC cell lines.

METHODS

Gene expression profiles from metastatic and non-metastatic liver cancer specimens were analyzed using the limma R package. Functional enrichment was performed using Metascape. A prognostic 5-gene signature was constructed using the LASSO algorithm based on TCGA-LIHC data. Kaplan-Meier survival analysis assessed the association of these genes with clinical outcomes (DFI, DSS, OS, and PFS). In vitro, Huh7 and Hep3B cells were transfected with shRNA for SPP1 knockdown. Cell viability was measured with CCK-8 assays, and migration was assessed with Transwell and wound-healing assays. Protein expression was evaluated via western blotting.

RESULTS

The analysis of gene expression profiles led to the identification of 11 DEGs associated with immune response, phagocytosis, and cell migration. From these DEGs, the LASSO algorithm identified a 5-DEG signature (MASP1, MASP2, MUC1, TREM1, and SPP1) that was predictive of OS in liver cancer patients. Among the five genes, SPP1 was the most upregulated in cancer samples and was significantly associated with poorer outcomes, including DFI, DSS, OS, and PFS. In vitro experiments confirmed that SPP1 knockdown in Huh7 and Hep3B cells significantly inhibited cancer cell viability and migration. Western blot analysis showed alterations in key proteins, with a reduction in vimentin and Ki-67 and an increase in E-cadherin following SPP1 knockdown.

CONCLUSION

This study highlights the pivotal effect of SPP1 on HCC development and underscores its potential as a biomarker for the OS of liver cancer patients. The identified DEGs may serve as predictive markers for OS and potential therapeutic targets for HCC treatment.

Comprehensive Bioinformatics Analyses and Experimental Validation of the Cell Cycle Related Protein SAPCD2 as a New Biomarker and Potential Therapeutic Target in Pancreatic Cancer

Purpose

Pancreatic adenocarcinoma (PAAD) is a highly aggressive cancer with a poor prognosis, reliable markers are urgently needed for early detection and prognosis evaluation. SAPCD2, a cell cycle related gene, has been implicated in tumorigenesis and proposed as a potential therapeutic target in cancer. However, no comprehensive study has explored its expression and regulation, discussed its role in tumor prognosis and immune modulation, along with therapy response in pan-cancer until now.

Methods

SAPCD2 expression was analyzed using data from The Cancer Genome Atlas database (TCGA) and Human Protein Atlas (HPA) database. Genetic and epigenetic alterations of SAPCD2 and the immune microenvironment were explored via NCBI, TIMER2 and cBioPortal platforms. Western blot analysis and immunohistochemistry (IHC) were performed to check SAPCD2 protein expression in PAAD cells and tissues. Cell counting kit 8 (CCK8), flow cytometry, and transwell experiments were used to evaluate the role of SAPCD2 in PAAD cell lines.

Results

Our study found that SAPCD2 is notably upregulated in various cancers, especially early-stage digestive cancers, and is linked to poor survival in most cancers like PAAD and LIHC. Gene amplification and promoter DNA hypomethylation appear to drive this upregulation. Additionally, SAPCD2 expression correlates with tumor mutation burden, microsatellite instability, and immune scores across several cancers. In PAAD, elevated SAPCD2 levels correlated with reduced immune activity, whereas in stomach cancer (STAD), its prognostic impact appeared immune-independent. In PDAC cell lines, SAPCD2 knockdown reduced proliferation and invasion, and caused reduction of G0/G1 phase. PAAD cells with high SAPCD2 expression showed increased sensitivity to DNA-PK, p38α MAPK, and Bcl-2 inhibitors.

Conclusion

SAPCD2 serves as both a prognostic marker and a potential therapeutic target in PAAD, where its low expression may enhance responsiveness to specific drugs. These findings underscore SAPCD2's dual role in cancer progression and therapy.

KRT14 is a promising prognostic biomarker of breast cancer related to immune infiltration

BACKGROUND

Breast cancer (BC) is the leading cancer among women globally, which has the highest incidence and mortality rate in over a hundred countries. This study was intended to discover a new prognostic biomarker, facilitating personalized treatment approaches.

METHODS

RNA sequencing data from The Cancer Genome Atlas database and Gene Expression Omnibus database were utilized to download to evaluate expression levels and prognostic significance of Keratin 14 (KRT14). Methylation of KRT14 was also assessed. The CIBERSORT and single-sample gene set enrichment analysis algorithms were applied to explore the connection between KRT14 and the tumor microenvironment. Primary drugs' sensitivity and potential small molecule therapeutic compounds were analyzed through the "pRRophetic" R package and the Connectivity Map. The prognostic value of KRT14 was additionally corroborated through a comparison of protein levels in peritumoral and cancerous tissues via immunohistochemistry. Moreover, an immune-related prognostic model based on KRT14 was designed to enhance the prediction accuracy for the prognosis of BC patients.

RESULTS

The study found that KRT14 expression was generally downregulated in BC, correlating strongly with poor prognosis. Compared to normal tissues, the methylation level of KRT14 was higher in BC tissues. Lower expression of KRT14 was linked to decreased anti-tumoral immune cells infiltration and increased immunosuppressive cells infiltration. Sensitivity to various key therapeutic drugs was lower in groups with diminished KRT14 expression. In addition, several potential anti-BC small molecule compounds were identified. The model designed in this study significantly enhanced the predictive capability for BC patients compared to predictions based solely on KRT14 expression levels.

CONCLUSION

Overall, KRT14 was closely correlated with the prognosis in BC, making it a reliable biomarker.

Pan-cancer analysis uncovered the prognostic and therapeutic value of disulfidptosis

Disulfidptosis, a newly discovered cell death mode distinct from other programmed cell death in lung and kidney cancer cells, is defined as extensive disulfide bonds to actin cytoskeleton proteins, leading to actin contraction and cytoskeletal disruption cell death. New cell death pattern discoveries often drive advances in tumor research. Therefore, the present study attempted to decipher the manifestation and importance of disulfidptosis in pan-cancer. Combining Clinical specimen immunofluorescence staining, single-cell analyses, and spatial transcriptome analyses, we demonstrated the manifestation of disulfidptosis in pan-cancer. Multi-omics analysis has revealed that genomic variants and DNA methylation in DRGs can affect the prognosis of patients with pan-cancer. The nomogram based on the DRGs Score model could accurately predict the prognosis of patients with pan-cancer. PF-562271, EHT-1864, and IPA-3 are potential therapeutic agents targeting disulfidptosis. Collectively, this study deciphered for the first time the importance of disulfidptosis for pan-cancer and developed the DRGs Score model that can assist clinicians in accurately predicting the prognosis and guiding individualized treatment of pan-cancer patients.

The comprehensive potential of AQP1 as a tumor biomarker: evidence from kidney neoplasm cohorts, cell experiments and pan-cancer analysis

Aquaporin1 (AQP1) facilitates water transport. Its ability to be a biomarker at the pan-cancer level remains uninvestigated. We performed immunohistochemical staining on tissues from 370 individuals with kidney neoplasms to measure AQP1 expression. We utilized Kaplan-Meier survival analysis, Chi-square tests, and multivariate Cox regression analyses to assess the prognostic relevance of AQP1 expression. In the pan-cancer context, we explored AQP1's competing endogenous RNAs network, protein-protein interactions, genomic changes, gene set enrichment analysis (GSEA), the correlation of AQP1 expression with survival outcomes, drug sensitivity, drug molecular docking, tumor purity and immunity. AQP1 shRNA expressing 786-O cells were established. Cell proliferation was assessed by Cell Counting Kit-8 and colony formation. Transwell migration, invasion, and cell scratch assays were conducted. In our study, AQP1 expression was an independent protective factor for OS and PFS in renal cancer patients. AQP1 expression significantly correlated with survival outcomes in renal cancers, LGG, SARC, HNSC and UVM. PI-103 sensitivity was related to AQP1 expression and had potential binding cite with AQP1 protein. Knockdown of AQP1 reduced cell proliferation, migration and invasion. Our study uncovered AQP1 as a biomarker for favorable survival outcomes in renal cancers. Furthermore, the bioinformatic analysis promoted its implication in pan-cancer scope.

DNA methyltransferase 3A: A prognostic biomarker and potential target for immunotherapy in gastric cancer

DNA methyltransferase 3A (DNMT3A) has been associated with the occurrence or progression of various tumors, including gastric cancer. However, the role of DNMT3A in the efficacy of immune-cell infiltration in the tumor microenvironment and immunotherapy in gastric cancer remains less explored. DNMT3A expression level was analyzed using TIMER 2.0, Sangerbox 3.0, and The Cancer Genome Atlas database and further verified by immunohistochemical staining and RT-qPCR. The UALCAN, chi-square test, and Kaplan-Meier plotter databases were performed to assess the correlation of DNMT3A with clinicopathological characteristics and prognosis. The GeneMANIA database, STRING database, and R package were used to construct a DNMT3A co-expression gene network. Gene set enrichment analysis was used to identify the signaling pathways related to DNMT3A expression. The correlations between DNMT3A and cancer immune infiltrates were investigated using TIMER 2.0, Sangerbox 3.0, Kaplan-Meier Plotter, R package, and TISIDB databases. The TISIDB database and R package were used to construct the correlation between DNMT3A and immunomodulators and Immune cell Proportion Score. The association of DNMT3A expression with tumor mutational burden (TMB), microsatellite instability, and tumor dryness was evaluated using the TMB function of the R package, TIMER 2.0. Finally, the biological function of DNMT3A in gastric cancer cells was further assessed by CCK-8, cloning formation, and transwell assay. DNMT3A expression was remarkably upregulated in gastric cancer. The high expression of DNMT3A was associated with poor clinical features and poor survival in patients with gastric cancer. Moreover, gene set enrichment analyses showed that DNMT3A and its related genes were involved in various pathways that promoted cancer occurrence and progression by influencing the tumor microenvironment. Finally, DNMT3A was significantly related to tumor-infiltrating immune cells, immunomodulators, TMB, microsatellite instability, and immune checkpoints in gastric cancer. Moreover, knockdown of DNMT3A reduced the proliferation and migration of gastric cancer cells. Our findings highlight the potential of DNMT3A as a prognosis biomarker and an immunotherapeutic target for gastric cancer.

Multi-Omics Characterization of Genome-Wide Abnormal DNA Methylation Reveals FGF5 as a Diagnosis of Nasopharyngeal Carcinoma Recurrence After Radiotherapy

BACKGROUND

Aberrant expression and mutations in the fibroblast growth factor (FGF) family play crucial roles in cell differentiation, growth, and migration, contributing to tumor progression across various cancers. Nasopharyngeal carcinoma (NPC), a malignancy prevalent in East Asia, is primarily treated with radiotherapy; however, radioresistance remains a major challenge, leading to recurrence and poor outcomes. While FGFs are known to activate signaling pathways such as MAPK, PI3K/AKT, and JAK/STAT to promote cancer progression, the specific role of individual FGFs in NPC radioresistance remains unclear. Emerging evidence highlights FGF5 as a key player in NPC progression, metastasis, and radioresistance, underscoring its potential as a therapeutic target to overcome treatment resistance and improve clinical outcomes.

METHODS

We analyzed single nucleotide variation (SNV) data, gene expression, and DNA methylation patterns using cancer datasets, including TCGA and GTEx, to investigate FGF5 expression. Differentially expressed genes (DEGs) were identified and interpreted using functional enrichment analysis, while survival analysis and gene set enrichment analysis (GSEA) were conducted to identify clinical correlations. DNA methylation patterns were specifically assessed using the HumanMethylation850 BeadChips on tissue samples from nine recurrent and nine non-recurrent NPC patients. Functional assays, including cell viability, migration, invasion, and clonogenic survival assays, were performed to evaluate the effects of FGF5 on NPC cell behavior in vitro and in vivo.

RESULTS

FGF5 showed elevated SNV frequencies across multiple cancers, particularly in HNSC and NPC. DNA methylation analysis revealed an inverse relationship between FGF5 expression and methylation levels in recurrent NPC tumors. Functional assays demonstrated that FGF5 enhances migration, invasion, and radioresistance in NPC cells. High FGF5 expression was associated with reduced distant metastasis-free survival (DMFS) and increased radioresistance, highlighting its role in metastatic progression and recurrence.

CONCLUSIONS

FGF5 plays a significant role in the progression and recurrence of nasopharyngeal carcinoma. Its elevated expression correlates with increased migration, invasion, and radioresistance as well as reduced distant metastasis-free survival. These findings suggest that FGF5 contributes to the metastatic and recurrence potential of NPC, making it a potential target for therapeutic intervention in treating these cancers.

ITGA4 as a potential prognostic and immunotherapeutic biomarker in human cancer and its clinical significance in gastric cancer: an integrated analysis and validation

Background

Integrin Subunit Alpha 4 (ITGA4), a member of the integrin protein family, is involved in the progression of malignant tumors. However, its role across different cancer types is not well understood.

Methods

Utilizing multi-omics data, we comprehensively evaluated ITGA4's expression, clinical relevance, diagnostic and prognostic value, functions, mutations, and methylation status, along with its impact on immunity, mismatch repair (MMR), heterogeneity, stemness, immunotherapy responsiveness, and drug resistance in pan-cancer, with partial validation in gastric cancer (GC) using transcriptomic analysis, single-cell data, western blot (WB), wound-healing assay, flow cytometry and immunohistochemistry (IHC). We further investigated its correlation with clinicopathology and serological markers on tissues from 80 GC patients.

Results

ITGA4 expression was generally low in normal tissues but varied significantly across tumor types, with higher levels in advanced stages and grades. It demonstrated diagnostic value in 20 cancer types and effectively predicted 1-, 3-, and 5-year survival rates as part of a prognostic model. ITGA4 played roles in cell adhesion, migration, immune regulation, and pathways like PI3K-Akt and TSC-mTOR. It showed alterations in 22 cancer types, with methylation at 9 sites inhibiting its expression. ITGA4 positively correlated with immune cell infiltration, immune regulatory genes, chemokines, and might reduce microsatellite instability (MSI) and tumor mutation burden (TMB) by promoting MMR gene expression. It could also predict immunotherapy efficacy and chemotherapy sensitivity. In GC, high ITGA4 expression was related to poor prognosis, promoted tumor proliferation and migration, and enhanced immune cell infiltration. ITGA4 expression was higher in GC cells and tissues than normal ones. Its downregulation inhibited GC cell migration and promoted apoptosis. Moreover, ITGA4 was correlated with N stage, pathological stage, neural and vascular invasion, serum levels of Ki-67, immune cells, CRP and CA125.

Conclusion

ITGA4 is a potential biomarker and therapeutic target to enhance cancer treatment and improve patient outcomes.

The pan-cancer analysis of LRG1 and its potential role in kidney renal clear cell carcinoma

Leucine-rich α-2 glycoprotein 1 (LRG1) is a secreted glycoprotein implicated in various diseases, yet its role across multiple cancers remains insufficiently explored. Consequently, we conducted a comprehensive bioinformatics analysis, exploring LRG1 expression patterns, prognostic implications, and potential therapeutic associations in a pan-cancer context. Additionally, we collected gene expression and clinical data from patients with kidney renal clear cell carcinoma (KIRC) from TCGA, conducting gene set enrichment analysis (GSEA) and Cox proportional hazards regression analysis to explore the potential regulatory role of LRG1 in KIRC. Our study revealed that LRG1 expression is upregulated in 18 cancer types, with elevated levels correlating with poor prognostic outcomes in several cancers, notably KIRC. Epigenetic analysis showed hypomethylation in the LRG1 promoter region, potentially contributing to the overexpression of LRG1. Moreover, LRG1 expression was linked to immunotherapeutic responses and altered drug sensitivities, particularly influencing the efficacy of tyrosine kinase inhibitors. In KIRC, high LRG1 expression was associated with the activation of key pathways, including angiogenesis, epithelial-mesenchymal transition (EMT), and hypoxia signalling. We identified key gene pairs interacting with LRG1 in KIRC, including CARD14 and CYP8B1, with CARD14 overexpression correlating with poorer clinical outcomes and CYP8B1 indicating a favourable prognosis. In conclusion, LRG1 emerges as a potential biomarker for prognosis and immunotherapy responsiveness in both pan-cancer and KIRC contexts. This study provides a theoretical foundation for further research on the therapeutic potential of target regulating LRG1 in cancer treatment.

SLC12A9 is an immunological and prognostic biomarker for glioma

BACKGROUND

Glioma is one of the most common malignant brain tumors. It has a high rate of progression and a poor prognosis, and effective biomarkers still need to be identified. The solute carrier family 12 (SLC12) family has been reported to be involved in various physiological and pathological processes, but their functional roles in glioma remain unclear.

METHODS

Using public datasets, we studied the mutation and expression level of SLC12 family genes in glioma and identified the significantly differentially expressed member solute carrier family 12 member 9 (SLC12A9). We further predicted the prognostic role of SLC12A9 in glioma by using the Kaplan-Meier method and Cox regression analysis. Then, we performed biological functional enrichment analysis. We focused on the relationships between SLC12A9 expression and immune infiltration in glioma. Meanwhile, we conducted in vitro experiments to evaluate the effect of SLC12A9 expression on glioma cells.

RESULTS

Among the members of the SLC12 family, SLC12A9 had the highest mutation rate in glioma, with gene amplification as the major mutation type, and its expression was significantly upregulated in glioma. Higher SLC12A9 expression was significantly associated with older age, higher grade, wild-type isocitrate dehydrogenase (IDH), and a worse prognosis. The functional enrichment analysis indicated that SLC12A9 is mainly related to ion channel annotation. Gene set enrichment analysis (GSEA) revealed that SLC12A9 was mainly related to the DNA replication pathway. Furthermore, we found that SLC12A9 correlated with tumor-infiltrating immune cells and immune checkpoints. Thus, SLC12A9 may be involved in regulating the immune response of glioma. Finally, our in vitro experiments revealed that silencing SLC12A9 dramatically inhibited glioma cell growth and migration.

CONCLUSIONS

We showed that SLC12A9 may be a new predictive biomarker for glioma diagnosis, prognosis, and immunotherapy response, offering helpful guidelines to advance glioma treatment.

LCAT in Cancer Biology: Embracing Epigenetic Regulation, Immune Interactions, and Therapeutic Implications

Lecithin cholesterol acyltransferase (LCAT) is a crucial enzyme in high-density lipoprotein (HDL) metabolism that is often dysregulated in cancers, affecting tumor growth and therapy response. We extensively studied LCAT expression in various malignancies, linking it to clinical outcomes and genetic/epigenetic alterations. We analyzed LCAT expression in multiple cancers and used the Cox regression model to correlate it with patient survival metrics, including overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI). We also examined the copy number variations (CNVs), single-nucleotide variations (SNVs), DNA methylation, and N6-methyladenosine (m6A) modifications of LCAT and their connections to tumor immune responses and drug sensitivity. LCAT expression varies among cancers and correlates with patient outcomes. Low expression is linked to poor prognosis in low-grade glioma (LGG) and liver hepatocellular carcinoma (LIHC), while high expression is associated with better outcomes in adrenocortical carcinoma (ACC) and colon adenocarcinoma (COAD). In kidney renal papillary cell carcinoma (KIRP) and uterine corpus endometrial carcinoma (UCEC), LCAT CNV and methylation levels are prognostic markers. LCAT interacts with m6A modifiers and immune molecules, suggesting a role in immune evasion and as a biomarker for immunotherapy response. LCAT expression correlates with chemotherapeutic drug IC50 values, indicating potential for predicting treatment response. In ACC and COAD, LCAT may promote tumor growth, while in LGG and LIHC, it may inhibit progression. LCAT expression and activity regulation could be a new cancer therapy target. As a key molecule linking lipid metabolism, immune modulation, and tumor progression, the potential of LCAT in cancer therapy is significant. Our findings provide new insights into the role of LCAT in cancer biology and support the development of personalized treatment strategies.

CDCA genes as prognostic and therapeutic targets in Colon adenocarcinoma

OBJECTIVES

The study investigates the role of Cell Division Cycle Associated (CDCA) genes in colorectal cancer (COAD) by analyzing their differential expression, epigenetic alterations, prognostic significance, and functional associations.

METHODOLOGY

This study employed a detailed in silico and in vitro experiments-based methodology.

RESULTS

RT-qPCR assays reveal significantly elevated mRNA levels of CDCA2, CDCA3, CDCA4, CDCA5, CDCA7, and CDCA8 genes in COAD cell lines compared to controls. Bisulfite sequencing indicates reduced promoter methylation of CDCA gene promoters in COAD cell lines, suggesting an epigenetic regulatory mechanism. Analysis of large TCGA datasets confirms increased CDCA gene expression in COAD tissues. Survival analysis using cSurvival database demonstrates negative correlations between CDCA gene expression and patient overall survival. Additionally, Lasso regression-based models of CDCA genes predict survival outcomes in COAD patients. Investigating immune modulation, CDCA gene expression inversely correlates with immune cell infiltration and immune modulators. miRNA-mRNA network analysis identifies regulatory miRNAs targeting CDCA genes, validated by RT-qPCR showing up-regulation of has-mir-10a-5p and has-mir-20a-5p in COAD cell lines and tissues. Drug sensitivity analysis suggests resistance to specific drugs in COAD patients with elevated CDCA gene expression. Furthermore, CDCA gene expression correlates with crucial functional states in COAD, including "angiogenesis, apoptosis, differentiation, hypoxia, inflammation, and metastasis." Additional in vitro experiments revealed that CDCA2 and CDCA3 knockdown in SW480 and SW629 cells significantly reduced cell proliferation and colony formation while enhancing cell migration.

CONCLUSION

Overall, the study elucidates the multifaceted role of CDCA genes in COAD progression, providing insights into potential diagnostic, prognostic, and therapeutic implications.

Comprehensive Analysis of Granzymes and Perforin Family Genes in Multiple Cancers

Background/Objectives: Cancer remains a significant global health concern, with immunotherapies emerging as promising treatments. This study explored the role of perforin-1 (PRF1) and granzymes A, B and K (GZMA, GZMB and GZMK) in cancer biology, focusing on their impact on tumor cell death and immune response modulation. Methods: Through a comprehensive genomic analysis across various cancer types, we explored the differential expression, mutation profiles and methylation patterns of these genes, providing insights into their potential as therapeutic targets. Furthermore, we investigated their association with immune cell infiltration and pathway activation within the tumor microenvironment in each tumor type. Results: Our findings revealed distinct expression patterns and prognostic implications for PRF1, GZMA, GZMB and GZMK across different cancers, highlighting their multifaceted roles in tumor immunity. We found increased immune infiltration across all tumor types and significant correlations between the genes of interest and cytotoxic T cells, as well as the most significant survival outcomes in breast cancer. We also show that granzymes and perforin-1 are significantly associated with indicators of immunosuppression and T cell dysfunction within patient cohorts. In skin melanoma, glioblastoma, kidney and bladder cancers, we found significant correlations between the genes of interest and patient survival after receiving immune-checkpoint inhibition therapy. Additionally, we identified potential associations between the mRNA expression levels of these genes and drug sensitivity. Conclusions: Overall, this study enhances our understanding of the molecular mechanisms underlying tumor immunity and provides valuable insights into the potential therapeutic implications of PRF1, GZMA, GZMB and GZMK in cancer treatment.

Exploring MAP3K genes in gastric cancer: biomarkers, tumor microenvironment dynamics, and chemotherapy resistance

BACKGROUND

Gastric cancer (GC) presents a significant global health burden, necessitating a deeper understanding of its molecular underpinnings for improved diagnostics and therapeutics.

METHODS

In this study, we investigated the expression profiles and clinical implications of MAP3K genes in GC using in silico and in vitro experiments.

RESULTS

Utilizing RT-qPCR analysis, we observed significant up-regulation of MAP3K1, MAP3K4, MAP3K5, MAP3K6, MAP3K7, MAP3K8, MAP3K9, and MAP3K10 in GC cell lines, while MAP3K2, MAP3K3, MAP3K11, MAP3K12, MAP3K13, MAP3K14, and MAP3K15 exhibited down-regulation. Prognostic evaluation revealed that elevated expression of MAP3K1, MAP3K4, MAP3K7, MAP3K8, MAP3K9, and MAP3K10 was associated with shorter overall survival (OS), emphasizing their clinical significance. Furthermore, the diagnostic potential was demonstrated through robust Receiver operating characteristics (ROC) curve analysis, indicating the strong discriminatory power of these genes in distinguishing GC patients. Proteomic analysis further confirmed the higher expression of MAP3K1, MAP3K4, MAP3K7, MAP3K8, MAP3K9, and MAP3K10 genes in GC. Methylation profiling further supported the idea that promoter hypomethylation of MAP3K1, MAP3K4, MAP3K7, MAP3K8, MAP3K9, and MAP3K10 genes was associated with their up-regulation. Single-cell functional analysis elucidated the involvement of MAP3K genes in shaping the tumor microenvironment. miRNA-mRNA network analysis revealed intricate regulatory mechanisms, with hsa-mir-200b-3p emerging as a key regulator. Finally, the MAP3K1 knockdown has shown significant impacts on the cellular behavior of the BGC823 cells.

CONCLUSION

This comprehensive assessment provides valuable insights into the role of MAP3K genes in GC, offering avenues for further research and therapeutic exploration.

Expression pattern and prognostic significance of aldehyde dehydrogenase 2 in lung adenocarcinoma as a potential predictor of immunotherapy efficacy

Background

The incidence of alcohol-associated cancers is higher within Asian populations having an increased prevalence of an inactivating mutation in aldehyde dehydrogenase 2 (ALDH2), a mitochondrial enzyme required for the clearance of acetaldehyde, a cytotoxic metabolite of ethanol. The role of alcohol consumption in promoting lung cancer is controversial, and little attention has been paid to the association between alcohol drinking and pulmonary ALDH2 expression.

Methods

We performed a comprehensive bioinformatic analysis of multi-omics data available in public databases to elucidate the role of ALDH2 in lung adenocarcinoma (LUAD).

Results

Transcriptional and proteomic data indicate a substantial pulmonary expression of ALDH2, which is functional for the metabolism of alcohol diffused from the bronchial circulation. ALDH2 expression is higher in healthy lung tissue than in LUAD and inhibits cell cycle, apoptosis, and epithelial-mesenchymal transition pathways. Moreover, low ALDH2 mRNA levels predict poor prognosis and low overall survival in LUAD patients. Interestingly, ALDH2 expression correlates with immune infiltration in LUAD.

Conclusions

A better understanding of the role of ALDH2 in lung tumor progression and immune infiltration might support its potential use as a prognostic marker and therapeutic target for improving immunotherapeutic response.

The regulatory role of KIAA1429 in epithelial-mesenchymal transition in cervical cancer via mediating m6A modification of BTG2

Cervical cancer (CC) represents one of the important cancers affecting global female population worldwide. We sought to elucidate the roles and mechanisms of KIAA1429 in the malignant properties of CC cells and the epithelial-mesenchymal transition (EMT) process. KIAA1429 was predicted to be abnormally expressed in CC and correlate with shortened survival of CC patients by GEPIA2 and GSCA databases. High expression of KIAA1429 in human CC cell lines (SiHa, HT-3) was validated by RT-qPCR and Western blot assays. A series of small interfering (si)RNAs including si-KIAA1429-1, si-KIAA1429-2, si-YTHDF2, si-BTG2, and si-negative control (NC) were utilized to interfere the expression levels of KIAA1429, YTHDF2, and BTG2, respectively. Consequently, KIAA1429 silencing attenuated the proliferation, migratory, and invasive functions of CC cells and repressed EMT while promoting CC cell apoptosis. Mechanistically, KIAA1429 could affect N6-methyladenosine (m6A) modification to attenuate the stability of BTG2 mRNA and down-regulate its expression. Additionally, loss of BTG2 partly counteracted the effects of si-KIAA1429 on repressing the malignant activities of CC cells. The aforementioned results collectively demonstrated that KIAA1429-mediated m6A modification of BTG2 and contributed to malignant progression of CC in vitro.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10616-024-00694-3.

Pan-Cancer Analysis of the Prognostic and Immunotherapeutic Value of PDGFB

Introduction

Cancer is a widespread epidemic that affects millions of individuals across the world. Identifying novel cancer targets is crucial to developing more effective cancer treatments. Platelet-derived growth factor-B (PDGFB) plays a critical role in various tumor processes, including angiogenesis and lymphatic metastasis. However, there is a lack of research on the role of PDGFB in these processes.

Methods

To address this issue, we conducted a comprehensive analysis utilizing multiple online databases to investigate the expression, prognostic, tumor stemness, and immunological effect of PDGFB. In addition, clinical samples were validated using immunohistochemistry.

Results

Our findings revealed that PDGFB was highly expressed in a diverse range of cancer types, and its expression and genetic modifications were significantly associated with clinical outcomes in certain tumors. In general, high expression of PDGFB in tumors is associated with poor prognosis. Surprisingly, PDGFB was found to be highly expressed in renal clear cell carcinoma but was associated with good prognosis. In contrast, PDGFB was low expressed in lung carcinoma, but its expression was found to improve patient survival. These findings demonstrate the complex role of PDGFB in different cancer types. The study also demonstrated that PDGFB was linked to RNA and DNA stemness in 15 and 36 tumor types, respectively, and had a positive association with tumor lymphocyte infiltration. Notably, PDGFB was found to be associated with immune modulators. PDGFB, which is involved in various immune responses, influences the malignant characteristics of various cancer types and controls immune cell infiltration. We confirmed that PDGFB positively correlated with CD8 and PDL1 expression in lower grade glioma.

Conclusion

This study concludes that PDGFB may serve as a potential prognostic marker and a potential targetable pathway in cancer immunotherapy. Overall, the study sheds new light on the role of PDGFB in cancer and highlights its potential clinical significance.

Programmable DNA‐Peptide Conjugated Hydrogel via Click Chemistry for Sequential Modulation of Peripheral Nerve Regeneration

During peripheral nerve regeneration, current deoxyribonucleic acid (DNA)‐based therapeutic platforms face the challenge of precisely regulating Schwann cells (SCs) fate to sustain their repair phenotype due to their inability to stably and precisely integrate multiple bioactive components. Herein, the strain‐promoted azide–alkyne cycloaddition reaction is utilized to integrate the neurotrophic factor mimetic peptide RGI and the laminin‐derived peptide IKVAV into DNA monomers. Through DNA sequence self‐assembly, a programmable DNA‐peptide conjugated hydrogel is constructed for loading bone marrow mesenchymal stem cell‐derived exosomes. This programmable hydrogel can rapidly, stably, and precisely integrate various bioactive components into the hydrogel network, thereby enabling sequential modulation of peripheral nerve repair. In vitro, studies show that this hydrogel, through sequential modulation mechanisms, can activate the neuregulin‐1 (Nrg1)/ErbB pathway to induce the reprogramming of SCs and promote the recruitment and proliferation of repair SCs. The induced repair SCs promote neuronal axon outgrowth and enhance tube formation in endothelial cells. In vivo, this programmable hydrogel can gelate in situ through intraneural injection in a rat sciatic nerve crush injury model, promoting nerve regeneration and functional recovery. In summary, this work provides an effective and practical strategy for peripheral nerve regeneration.

Key wound healing genes as diagnostic biomarkers and therapeutic targets in uterine corpus endometrial carcinoma: an integrated in silico and in vitro study

BACKGROUND

Uterine Corpus Endometrial Carcinoma (UCEC) is a prevalent gynecologic malignancy with complex molecular underpinnings. This study identifies key woundhealing genes involved in UCEC and elucidates their roles through a comprehensive analysis.

METHODS

In silico and in vitro experiments.

RESULTS

Seventy wound healing-associated genes were extracted from the Gene Ontology (GO) database, and a protein-protein interaction (PPI) network was constructed using the STRING database. CytoHubba analysis in Cytoscape identified six pivotal hub genes: CD44, FGF2, FGF10, KDM6A, FN1, and MMP2. These genes exhibited significantly lower expression in UCEC cell lines compared to normal controls, as confirmed by RT-qPCR. Receiver Operating Characteristic (ROC) analysis demonstrated their potential as diagnostic biomarkers, with Area Under the Curve (AUC) values ranging from 0.94 to 1.00. Validation using TCGA datasets revealed consistent downregulation of these genes in UCEC samples, corroborated by immunohistochemical staining. Promoter methylation analysis showed significantly higher methylation levels in UCEC, correlating with decreased mRNA expression and poor survival outcomes. Genetic alteration analysis indicated frequent mutations in FN1 and KDM6A, although these did not significantly affect survival. Functional analysis using the CancerSEA database highlighted the involvement of these genes in critical cancer-related processes, including angiogenesis, apoptosis, and metastasis. Immune correlation studies revealed significant associations with immune inhibitor genes and distinct expression patterns across immune subtypes. Overexpression studies in UCEC cell lines demonstrated that CD44 and MMP2 reduce proliferative ability while enhancing migration and wound healing.

CONCLUSION

Collectively, these findings underscore the crucial roles of CD44, FGF2, FGF10, KDM6A, FN1, and MMP2 in UCEC pathogenesis, highlighting their potential as biomarkers and therapeutic targets in this malignancy.

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.

Comprehensive investigation of matrix metalloproteinases in skin cutaneous melanoma: diagnostic, prognostic, and therapeutic insights

The dysregulation of matrix metalloproteinases (MMPs) in skin cutaneous melanoma (SKCM) represents a critical aspect of tumorigenesis. In this study, we investigated the diagnostic, prognostic, and therapeutic aspects of the MMPs in SKCM. Thirteen SKCM cell lines and seven normal skin cell lines were cultured under standard conditions for experimental analyses. RNA and DNA were extracted, followed by RT-qPCR to assess MMP expression and promoter methylation analysis to determine methylation levels. Functional assays, including cell proliferation, colony formation, and wound healing, were conducted post-MMP7 knockdown using siRNA in A375 cells. Databases like GEPIA2, HPA, MEXPRESS, and miRNet were employed for expression, survival, methylation, and miRNA-mRNA network analyses. We investigated the expression and promoter methylation landscape of MMPs in SKCM cell lines, revealing significant (p-value < 0.05) up-regulation of MMP1, MMP7, MMP9, MMP10, MMP11, MMP12, MMP13, MMP14, and MMP25, alongside down-regulation of MMP2, MMP3, and MMP21. Furthermore, our analysis demonstrated a significant (p-value < 0.05) inverse correlation between MMP expression levels and promoter methylation status, suggesting a potential regulatory role of DNA methylation in MMP dysregulation. Notably, MMP7, MMP11, and MMP14 exhibited significant (p-value < 0.05) associations with the overall survival of SKCM patients, emphasizing their prognostic significance. Additionally, Receiver operating characteristic (ROC) curve analysis highlighted the significant (p-value < 0.05) diagnostic potential of MMP7, MMP11, and MMP14 in distinguishing SKCM from normal individuals. Subsequent validation across multiple cohorts confirmed significant (p-value < 0.05) elevated MMP expression levels in SKCM tissues, particularly in advanced disease stages, further emphasizing their role in tumor progression. Furthermore, we elucidated potential regulatory pathways involving miR-22-3p, which targets MMP7, MMP11, and MMP14 genes in SKCM. Our findings also revealed associations between MMP expression and immune modulation, drug sensitivity, and functional states of SKCM cells. Lastly, MMP7 knockdown in A375 cells significantly significant (p-value < 0.05) impacted several characteristics, including cell proliferation, colony formation, and wound healing. Our findings highlight the diagnostic, prognostic, and therapeutic potential of MMP7, MMP11, and MMP14 in SKCM. These MMPs could serve as biomarkers for early detection and targets for therapy. Future efforts should focus on preclinical and clinical validation to translate these insights into personalized diagnostic and therapeutic strategies.

A multidimensional pan-cancer analysis of NDUFA4L2 and verification of the oncogenic value in colon cancer

NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 4-like 2 (NDUFA4L2) protein is located in the mitochondria and can regulate cell proliferation. Some studies have shown that the high NDUFA4L2 expression is linked with poor prognosis and cancer progression in various patients with cancers. However, the correlation between NDUFA4L2 and pan-cancer is unknown. In this study, we used the databases and investigated the expression and variation of NDUFA4L2 in many cancers in detail to determine its diagnostic and prognostic values. We also validated the oncogenic capability of NDUFA4L2 in colon cancer by experiments or tissue microarray. In most cancers, NDUFA4L2 expression levels are upregulated, and a high level of NDUFA4L2 expression is associated with poor OS. In addition, the results showed that 10 proteins and 30 genes were correlated to NDUFA4L2. An additional analysis demonstrated that these genes and proteins exhibited either negative or positive correlations with specific pathways. Moreover, we discovered that NDUFA4L2 expression was related to tumor stemness, MSI, TMB, immune cell infiltration and ROS production. Our results show that NDUFA4L2 affects the development and mitochondrial function of colon cancer cell lines. Finally, we identified that NDUFA4L2 was sensitive to 10 anticancer drugs. Our study suggest that NDUFA4L2 could serve as a prognostic and therapeutic biomarker for most cancer, including colon cancer.

Pan-cancer analysis of Arp2/3 complex subunits: focusing on ARPC1A's role and validating the ARPC1A/c-Myc axis in non-small cell lung cancer

Background

The Arp2/3 complex is a key regulator of tumor metastasis, and targeting its subunits offers potential for anti-metastatic therapy. However, the expression profiles, prognostic relevance, and diagnostic value of its subunits across cancers remain poorly understood. This study aims to investigate the clinical relevance of Arp2/3 complex subunits, particularly ARPC1A, in pan-cancer, and to further analyze the potential biological mechanisms of ARPC1A, as well as its association with immune infiltration and chemotherapy drug sensitivity.

Methods

To explore the differential expression of Arp2/3 complex subunits and their clinical relevance across cancers, we analyzed data from TCGA and GTEx databases. The relationship between ARPC1A and immune infiltration, as well as its interactions with functional proteins, was examined using the TCPA and TIMER2.0 databases. Gene Set Enrichment Analysis (GSEA) was performed to identify ARPC1A-associated signaling pathways. Chemotherapy drug sensitivity correlated with ARPC1A expression was assessed using CellMiner, GDSC, and CTRP databases. The effect of ARPC1A on c-Myc expression was validated by quantitative PCR (qPCR) and Western blot. Finally, the biological role of ARPC1A in non-small cell lung cancer (NSCLC) cells was further validated using CCK-8, EdU incorporation, colony formation, and Transwell assays.

Results

The Arp2/3 complex subunits, particularly ARPC1A, are frequently overexpressed in a majority of cancers, correlating with poor prognostic outcomes and demonstrating significant diagnostic utility. Copy number variations may play a role in the dysregulation of Arp2/3 complex subunit expression. The small molecule X4.5.dianilinophthalimide has shown promise as a targeted therapeutic agent in a pan-cancer context. Functional predictions indicate that ARPC1A is implicated in oxidative phosphorylation pathways and cell proliferation-related signaling pathways, including those mediated by MYC, with ASNS potentially acting as an upstream regulator. Furthermore, ARPC1A has been implicated in the resistance to chemotherapy drugs, including gefitinib. In vitro experiments corroborate that ARPC1A may enhance malignant phenotypes in non-small cell lung cancer (NSCLC) cells through the regulation of c-Myc expression.

Conclusion

Our study offers novel insights into targeting Arp2/3 complex subunits as an anti-cancer strategy and underscores the potential of ARPC1A as a novel biomarker for tumor diagnosis, prognosis, and the prediction of immune therapy responses.

Functional Analysis and Experimental Validation of the Prognostic and Immune Effects of the Oncogenic Protein CDC45 in Breast Cancer

Purpose

Cell division cycle protein 45 (CDC45) plays a crucial role in DNA replication. This study investigates its role in breast cancer (BC) and its impact on tumor progression.

Methods

We utilized the GEO database to screen differentially expressed genes (DEGs) and conducted enrichment analysis on these genes. We established a Nomogram model based on CDC45 and other clinical indicators. Additionally, we performed protein-protein interaction (PPI) network construction, drug sensitivity analysis, and immune correlation analysis of CDC45. The function of CDC45 was further verified through cell and animal experiments.

Results

CDC45 is highly expressed in most tumors, including BC. The expression level of CDC45 was significantly associated with age, sex, race, cancer stage, and molecular subtypes (all p < 0.05). CDC45 was incorporated into a Nomogram model, which showed moderate accuracy in predicting patient prognosis. We also analyzed the co-expression genes of CDC45, including TOPBP1, GINS2, MCM5, GINS1, GINS4, POLE2, MCM2, MCM6, MCM4, and MCM7. Furthermore, CDC45 expression was closely linked to immune infiltration levels, immune checkpoint inhibitors, and the therapeutic response to small molecule drugs. Finally, both in vitro and in vivo experiments confirmed the cancer-promoting effect of CDC45 in BC.

Conclusion

The expression level of CDC45 is linked to the prognosis, immune infiltration, and drug sensitivity of BC. In vitro and in vivo experiments have confirmed that CDC45 acts as a cancer-promoting protein in breast cancer.

Bioinformatics analysis of mitochondrial metabolism-related genes demonstrates their importance in renal cell carcinoma

PURPOSE

Clear cell renal cell carcinoma (ccRCC) is resistant to radiotherapy and chemotherapy. Thus, it is necessary to find new diagnostic markers and therapeutic targets to increase the overall outcomes of ccRCC. Recent studies have shown that therapeutic methods that interfere with the energy transfer system can also positively affect the treatment process.

METHODS

The present study is focused on finding markers associated with mitochondrial metabolic pathways that affect the outcome of ccRCC. For this purpose, we investigated various aspects of the relationship between mitochondrial metabolism and ccRCC based on analysis of gene network connections and differentially expressed genes, through assessment of protein-protein interaction, mutations, and promoter methylation on the related genes. We also investigated gene interaction with miRNAs and immune infiltration analysis.

RESULTS

Through these steps, we provided a list of possible diagnostic markers and therapeutic targets for ccRCC.

CONCLUSION

The current study further proved the importance of mitochondrial metabolic pathways in the pathogenesis of ccRCC and provided a list of possible diagnostic markers and therapeutic targets from these pathways that can be used in ccRCC.

Expression of vesiculation-related genes is associated with a tumor-promoting microenvironment: a pan-cancer analysis

BACKGROUND

Small extracellular vesicles (sEV) released by tumor cells (tumor-derived sEV; TEX) mediate intercellular communication between tumor and non-malignant cells and were shown to impact disease progression. This study investigates the relationship between the expression levels of the vesiculation-related genes linked to sEV production and the tumor microenvironment (TME).

METHODS

Two independent gene sets were analyzed, both previously linked to sEV production in various non-malignant or malignant cells. Expression profiles were compared among 28 tumor types listed in the Cancer Genome Atlas (TCGA). Gene expression and survival analysis (GEPIA2), immunogenomic analysis (TISIDB), and genomic analysis (GSCA) were performed.

RESULTS

Vesiculation-related genes were overexpressed in tissues of most tumor types compared to healthy tissues, and high expression levels were associated with worse overall survival in cervical squamous cell carcinoma, kidney chromophobe, lower grade glioma, hepatocellular carcinoma, lung squamous cell carcinoma, and pancreatic adenocarcinoma but with improved overall survival in kidney renal clear cell carcinoma. Expression of these signatures correlated with an increased abundance of infiltrating CD4( +) T cells and dendritic cells, a decreased abundance of B cells and eosinophils, and activation of tumor cell apoptosis and epithelial-mesenchymal transition pathways in all tumor types. 17-AAG was identified as a potential drug candidate to target tumors with elevated expression of vesiculation-related genes.

CONCLUSIONS

Vesiculation-related genes were associated with distinct immunological and genomic landscapes further emphasizing the important role of TEX in cancer progression.

Integrating bioinformatics and machine learning to identify AhR-related gene signatures for prognosis and tumor microenvironment modulation in melanoma

Background

The Aryl Hydrocarbon Receptor (AhR) pathway significantly influences immune cell regulation, impacting the effectiveness of immunotherapy and patient outcomes in melanoma. However, the specific downstream targets and mechanisms by which AhR influences melanoma remain insufficiently understood.

Methods

Melanoma samples from The Cancer Genome Atlas (TCGA) and normal skin tissues from the Genotype-Tissue Expression (GTEx) database were analyzed to identify differentially expressed genes, which were intersected with a curated list of AhR-related pathway genes. Prognostic models were subsequently developed, and feature genes were identified. Advanced methodologies, including Gene Set Enrichment Analysis (GSEA) and immune cell infiltration analysis, were employed to explore the biological significance of these genes. The stability of the machine learning models and the relationship between gene expression and immune infiltrating cells were validated using three independent melanoma datasets. A mouse melanoma model was used to validate the dynamic changes of the feature genes during tumor progression. The relationship between the selected genes and drug sensitivity, as well as non-coding RNA interactions, was thoroughly investigated.

Results

Our analysis identified a robust prognostic model, with four AhR-related genes (MAP2K1, PRKACB, KLF5, and PIK3R2) emerging as key contributors to melanoma progression. GSEA revealed that these genes are involved in primary immunodeficiency. Immune cell infiltration analysis demonstrated enrichment of CD4+ naïve and memory T cells, macrophages (M0 and M2), and CD8+ T cells in melanoma, all of which were associated with the expression of the four feature genes. Importantly, the diagnostic power of the prognostic model and the relevance of the feature genes were validated in three additional independent melanoma datasets. In the mouse melanoma model, Map2k1 and Prkacb mRNA levels exhibited a progressive increase with tumor progression, supporting their role in melanoma advancement.

Conclusions

This study presents a comprehensive analysis of AhR-related genes in melanoma, highlighting MAP2K1, PRKACB, KLF5, and PIK3R2 as key prognostic markers and potential therapeutic targets. The integration of bioinformatics and machine learning provides a robust framework for enhancing prognostic evaluation in melanoma patients and offers new avenues for the development of treatments, particularly for those resistant to current immunotherapies.

Knockdown of CENPF induces cell cycle arrest and inhibits epithelial‑mesenchymal transition progression in glioma

Gliomas are among the most common malignant tumors of the central nervous system. Despite surgical resection followed by postoperative radiotherapy and chemotherapy, their prognosis remains unfavorable. The present study aimed to assess new mechanisms and explore promising prognostic biomarkers for patients with glioma using comprehensive bioinformatics analysis and in vitro and in vivo assays. Overlapping differentially expressed genes were screened from The Cancer Genome Atlas, GSE111260 and GSE16011 samples for protein-protein interaction networks, a risk score model, gene mutation analysis and a nomogram to identify the prognostic hub genes. Subsequently, an immunoassay was performed to determine key genes. Functional and animal assays were then performed to assess the tumorigenesis of the key genes in glioma. Using bioinformatics analysis, centromere protein F (CENPF), kinesin superfamily member 20A, kinesin superfamily protein 4A and marker of proliferation Ki-67 were identified as potential prognostic biomarkers for patients with glioma. Furthermore, CENPF knockdown was demonstrated to suppress the proliferation and metastasis of glioma cells, and induce G2 arrest in the cell cycle. Moreover, CENPF knockdown was revealed to decrease Vimentin and increase E-cadherin levels in glioma cells, and significantly reduce the size and mass of tumors in vivo. Overall, the present study identified new clinical biomarkers and revealed that CENPF may promote glioma progression by regulating the epithelial-mesenchymal transition pathway. By elucidating the complexities of glioma and identifying prognostic biomarkers, the present research enables further improvement of patient outcomes and the advancement of precision medicine for this disease.

Prognostic Significance and Therapeutic Potential of SERPINE1 in Head and Neck Squamous Cell Carcinoma

BACKGROUND

This study aims to elucidate the expression pattern of SERPINE1, assess its prognostic significance, and explore potential therapeutic drugs targeting this molecule.

METHODS AND RESULTS

In this study, we delved into the variations in gene mutation, methylation patterns, and expression levels of SERPINE1 in head and neck squamous cell carcinoma (HNSCC) and normal tissues, leveraging comprehensive analyses of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. The connection between the biological function of the gene and prognosis was scrutinized through immune infiltration and enrichment analyses. Concurrently, we assessed the potential therapeutic value of SERPINE1 through drug sensitivity analysis. It was observed that, particularly in human papillomavirus (HPV) negative HNSCC, SERPINE1 exhibited elevated expression levels, correlating with poorer prognosis. The infiltration levels of eight cell types, such as eosinophils, Tgd, and macrophages, showed a positive correlation with SERPINE1 expression, whereas infiltration levels of four cell types, including cytotoxic cells, B cells, and pDCs, displayed a negative correlation. Furthermore, copy number variations of SERPINE1 were primarily characterized by homologous amplification, positively correlating with its expression, while methylation showed an inverse correlation. The outcomes of drug sensitivity analysis underscored the potential of SERPINE1 as a therapeutic target.

CONCLUSION

Elevated expression of SERPINE1 in HNSCC is intricately linked with adverse prognostic outcomes and has the potential to influence the immune microenvironment. Subsequent investigations are imperative to fully elucidate the prognostic implications of SERPINE1 as a biomarker and to unlock its therapeutic promise as a target for intervention.

Integrated analysis of cell cycle and p53 signaling pathways related genes in breast, colorectal, lung, and pancreatic cancers: implications for prognosis and drug sensitivity for therapeutic potential

Cancer, a leading cause of death worldwide, is projected to increase by 76.6% in new cases and 89.7% in mortality by 2050 (WHO 2022). Among various types, lung cancer is the most prevalent with high morbidity, while breast, colorectal, and pancreatic cancers also show high mortality rates. Cancer progression often involves disruption in cell cycle regulation and signaling pathways, with mutations in genes like TP53, EGFR, and K-RAS playing significant roles. In this study, we analyzed gene expression datasets to identify common molecular signatures across breast, colorectal, lung and pancreatic cancers. Our focus was on genes related to cell cycle regulation and p53 signaling pathway, intending to discover potential biomarkers for improved diagnosis and treatment strategies. The study analyzed GEO datasets; GSE45827, GSE9348, GSE30219, and GSE62165 for breast, colorectal, lung, and pancreatic cancers respectively. Differentially expressed genes (DEGs) were identified using GEO2R, and functional annotation and pathway analysis were performed using WebGestalt. Common cell cycle and p53 signaling genes were acquired from MSigDB using GSEA. A protein-protein interaction network was constructed using STRING and Cytoscape, identifying top hub genes. Validation of hub genes at mRNA and protein levels was done via GEPIA2 and Human Protein Atlas. Survival analysis was conducted using TCGA data by GEPIA2 and LASSO, and drug sensitivity was analyzed with the GSCA drug bank database, highlighting potential therapeutic targets. The study identified 411 common DEGs among these four cancers. Pathway and functional enrichment revealed key biological processes and pathways like p53 signaling, and cell cycle. The intersection of these DEGs with genes involved in cell cycle and p53 signaling, identified 23 common genes that were used for constructing a PPI network. The top 10 hub genes were validated both for mRNA and protein expression, revealing they are significantly overexpressed in all studied cancers. Prognostic relevance showed that MCM4, MCM6, CCNA2, CDC20, and CHEK1 are associated with survival. Additionally, drug sensitivity analysis highlighted key gene-drug interactions, suggesting potential targets for therapeutic intervention.

Pan-cancer analysis reveals the prognostic and immunomodulatory potential of super-enhancer-induced ANGPT2 and experimental validation in colorectal cancer

BACKGROUND

ANGPT2 plays important roles in cancer development. However, there is still no systematic analysis of ANGPT2 in pan-cancer.

METHODS

In this paper, we conducted a pan-cancer analysis to investigate the characteristics of ANGPT2. Furthermore, we investigated the impact of genetic and epigenetic factors on ANGPT2 expression by bioinformatics and assays.

RESULTS

By several TCGA and GEO databases, we identified elevated expression of ANGPT2 in various tumor types. Besides, high expression of ANGPT2 induced poor prognosis of patients in multiple tumors. Through enrichment analysis, we found that ANGPT2 participated in various biological processes, including angiogenesis and immunity. Various immune analyses indicated that high expression of ANGPT2 might suggest a propensity towards a hot tumor microenvironment, but its impact on immunotherapy was negative. Bioinformatics analysis and experiments confirmed that genetic and epigenetic factors explained part of the mechanism behind ANGPT2 abnormal expression. Finally, we screened candidate drugs targeting the ANGPT2 protein by molecular docking and molecular dynamics simulation.

CONCLUSION

ANGPT2 has diagnostic and prognostic values in multiple tumor types. Though with a hot tumor microenvironment, ANGPT2 high expression patients are not suitable for immunotherapy because of its proangiogenic function, contributing to selecting the exact patients for immunotherapy. Both genetic and epigenetic factors influenced ANGPT2 expression, with the influence of super-enhancer being more pronounced. This paper for the first time did the systematic analysis of ANGPT2 and showed its characteristic in pan-cancer. We summarized the biomarker role of ANGPT2 on tumor diagnosis and prognosis, as well as its target role on tumor immunotherapy.

Exploring potential key genes and pathways associatedwith hepatocellular carcinoma prognosis through bioinformatics analysis, followed by experimental validation

BACKGROUND

Liver Hepatocellular Carcinoma (LIHC) is a prevalent and aggressive liver cancer with limited therapeutic options. Identifying key genes involved in LIHC can enhance our understanding of its molecular mechanisms and aid in the development of targeted therapies. This study aims to identify differentially expressed genes (DEGs) and key hub genes in LIHC using bioinformatics approaches and experimental validation.

METHOD

We analyzed two LIHC-related datasets, GSE84598 and GSE19665, from the Gene Expression Omnibus (GEO) database to identify DEGs. Differential expression analysis was performed using the limma package in R to identify DEGs between cancerous and non-cancerous liver tissues. A Protein-Protein Interaction (PPI) network was constructed using STRING to determine key hub genes. Further validation of these hub genes was conducted through UALCAN, OncoDB, and the Human Protein Atlas (HPA) databases for mRNA and protein expression levels. Promoter methylation and mutational analyses were performed using cBioPortal. Kaplan-Meier survival analysis assessed the impact of hub gene expression on patient survival. Correlations with immune cell abundance and drug sensitivity were explored using GSCA. Finally, AURKA was knocked down in HepG2 cells, and cell proliferation, colony formation, and wound healing assays were performed.

RESULTS

Analysis identified 180 DEGs, with four key hub genes, including AURKA, BUB1B, CCNA2, and PTTG1 showing significant overexpression and hypomethylation in LIHC tissues. AURKA knockdown in HepG2 cells led to decreased cell proliferation, reduced colony formation, and impaired wound healing, confirming its role in LIHC progression. These hub genes were also hypomethylated and their elevated expression correlated with poor overall survival.

CONCLUSION

AURKA, BUB1B, CCNA2, and PTTG1 are crucial for LIHC pathogenesis and may serve as potential biomarkers or therapeutic targets. Our findings provide new insights into LIHC mechanisms and suggest promising avenues for future research and therapeutic development.

A Novel Peroxisome-Related Gene Signature Predicts Breast Cancer Prognosis and Correlates with T Cell Suppression

Background

Peroxisomes are increasingly linked to cancer development, yet the prognostic role of peroxisome-related genes (PRGs) in breast cancer remains unclear.

Objective

This study aimed to construct a prognostic model based on PRG expression in breast cancer to clarify their prognostic value and clinical implications.

Methods

Transcriptomic data from TCGA and GEO were used for training and validation cohorts. TME characteristics were analyzed with ESTIMATE, MCP-counter, and CIBERSORT algorithms. qPCR validated mRNA expression levels of risk genes, and data analysis was conducted in R.

Results

Univariate and multivariate Cox regression identified a 7-gene PRG risk signature (ACBD5, ACSL5, DAO, NOS2, PEX3, PEX10, and SLC27A2) predicting breast cancer prognosis in training (n=1069), internal validation (n=327), and external validation (merged from four GEO datasets, n=640) datasets. While basal and Her2 subtypes had higher risk scores than luminal subtypes, a significant prognostic impact of the PRG risk signature was seen only in luminal subtypes. The high-risk subgroup exhibited a higher frequency of focal synonymous copy number alterations (SCNAs), arm-level amplifications and deletions, and single nucleotide variations. These increased genomic aberrations were associated with greater immune suppression and reduced CD8+ T cell infiltration. Bulk RNA sequencing and single-cell analyses revealed distinct expression patterns of peroxisome-related genes (PRGs) in the breast cancer TME: PEX3 was primarily expressed in malignant and stromal cells, while ACSL5 showed high expression in T cells. Additionally, the PRG risk signature demonstrated efficacy comparable to that of well-known biomarkers for predicting immunotherapy responses. Drug sensitivity analysis revealed that the PRG high-risk subgroup was sensitive to inhibitors of BCL-2 family proteins (BCL-2, BCL-XL, and MCL1) and other kinases (PLK1, PLK1, BTK, CHDK1, and EGFR).

Conclusion

The PRG risk signature serves as a promising biomarker for evaluating peroxisomal activity, prognosis, and responsiveness to immunotherapy in breast cancer.

Investigating the clinical significance of OAS family genes in breast cancer: an in vitro and in silico study

BACKGROUND

Breast cancer is the most common malignancy among women worldwide, characterized by complex molecular and cellular heterogeneity. Despite advances in diagnosis and treatment, there is an urgent need to identify reliable biomarkers and therapeutic targets to improve early detection and personalized therapy. The OAS (2'-5'-oligoadenylate synthetase) family genes, known for their roles in antiviral immunity, have emerged as potential regulators in cancer biology. This study aimed to explore the diagnostic and functional relevance of OAS family genes in breast cancer.

METHODOLOGY

Breast cancer cell lines and controls were cultured under specific conditions, and DNA and RNA were extracted for downstream analyses. RT-qPCR, bisulfite sequencing, and Western blotting were employed to assess gene expression, promoter methylation, and knockdown efficiency of OAS family genes. Functional assays, including CCK-8, colony formation, and wound healing, evaluated cellular behaviors, while bioinformatics tools (UALCAN, GEPIA, HPA, OncoDB, cBioPortal, and others) validated findings and explored correlations with clinical data.

RESULTS

The OAS family genes (OAS1, OAS2, OAS3, and OASL) were found to be significantly upregulated in breast cancer cell lines and tissues compared to normal controls. This overexpression was strongly associated with reduced promoter methylation. Receiver operating characteristic (ROC) analysis demonstrated high diagnostic accuracy, with area under the curve (AUC) values exceeding 0.93 for all four genes. Increased OAS expression correlated with advanced cancer stages and poor overall survival in breast cancer patients. Functional analysis revealed their involvement in critical biological processes, including immune modulation and oncogenic pathways. Silencing OAS genes in breast cancer cells significantly inhibited cell proliferation and colony formation, while unexpectedly enhancing migratory capacity. Additionally, correlations with immune cell infiltration, molecular subtypes, and drug sensitivity highlighted their potential roles in the tumor microenvironment and therapeutic response.

CONCLUSION

The findings of this study established OAS family genes as potential biomarkers and key players in breast cancer progression, offering promise as diagnostic biomarkers and therapeutic targets to address unmet clinical needs.

Exploring the function and prognostic value of RPLP0, RPLP1 and RPLP2 expression in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer (NSCLC) and is characterized by its heterogeneity and poor prognosis. The role of ribosomal proteins RPLP0, RPLP1 and RPLP2 in multiple cancers has been implicated. However, their function in LUAD and their correlation with the poor prognosis of LUAD remains elusive. In this study, we performed a comprehensive bioinformatic analysis of the impact of these ribosomal proteins on LUAD. Our findings reveal that RPLP0, RPLP1 and RPLP2 are overexpressed in LUAD, which are likely attributed to abnormal copy number variations and decreased methylation levels of their promoters. LUAD patients with high expression of RPLP0, RPLP1 or RPLP2 have worse clinical outcomes in terms of overall survival (OS), first progression (FP) and post-progression survival (PPS), indicating poor prognosis. Moreover, the expression of RPLP0, RPLP1 and RPLP2 affects immune cell infiltration in LUAD tissues. Finally, we identified multiple existing drugs that may inhibit the expression of RPLP1 and RPLP2. Collectively, our data implicate the oncogenic role of RPLP0, RPLP1 and RPLP2 in LUAD and underscore their prognostic value in LUAD patients.

EVA1B facilitates esophageal squamous carcinoma progression and recruitment of immunosuppressive myeloid-derived suppressor cells in the tumor microenvironment

Eva-1 Homolog B (EVA1B) has been preliminarily found to be associated with prognostic outcomes and immune microenvironment in several human cancer types, but the implications of EVA1B in ESCC remain unclear. Human ESCC and paracancerous tissues were gathered in this study, and EVA1B expression was measured via immunoblotting. EC109 and KYSE-180 ESCC cells were stably infected by sh-EVA1B lentivirus, and functional experiments were subsequently implemented. Syngeneic mouse models were built, and the expansion and recruitment of myeloid-derived suppressor cells (MDSCs) were then evaluated. The results showed that EVA1B presented the notable up-regulation in clinical ESCC tissues versus controls, and was connected to more advanced stages and the abundance of MDSCs. Silencing EVA1B notably attenuated proliferation of ESCC cells and tumor growth in syngeneic mouse models. Moreover, EVA1B suppression resulted in apoptosis and cell cycle arrest, and impaired ESCC cell aggressiveness. Among ESCC patients, EVA1B was strongly correlated to EMT pathway activity. Targeted suppression of EVA1B mitigated the expression of Wnt3a, β-catenin and LRP6 in ESCC cells and tumor xenografts. Additionally, inhibition of EVA1B attenuated the expansion and recruitment of MDSCs within the immune microenvironment based upon the reduction in the percentage of CD11b+Gr-1+ immunosuppressive MDSCs as well as the expression of MDSC expansion stimulators (S100A8, S100A9, Arg-1, and VEGF). Collectively, our findings unveiled the contribution of high expression of EVA1B to ESCC progression and MDSCs expansion and recruitment, indicating that targeted suppression of EVA1B may be a potential treatment choice for ESCC patients.

Uncovering the potential of APOD as a biomarker in gastric cancer: A retrospective and multi-center study

Gastric cancer (GC) poses a significant health challenge worldwide, necessitating the identification of predictive biomarkers to improve prognosis. Dysregulated lipid metabolism is a well-recognized hallmark of tumorigenesis, prompting investigation into apolipoproteins (APOs). In this study, we focused on apolipoprotein D (APOD) following comprehensive analyses of APOs in pan-cancer. Utilizing data from the TCGA-STAD and GSE62254 cohorts, we elucidated associations between APOD expression and multiple facets of GC, including prognosis, tumor microenvironment (TME), cancer biomarkers, mutations, and immunotherapy response, and identified potential anti-GC drugs. Single-cell analyses and immunohistochemical staining confirmed APOD expression in fibroblasts within the GC microenvironment. Additionally, we independently validated the prognostic significance of APOD in the ZN-GC cohort. Our comprehensive analyses revealed that high APOD expression in GC patients was notably associated with unfavorable clinical outcomes, reduced microsatellite instability and tumor mutation burden, alterations in the TME, and diminished response to immunotherapy. These findings provide valuable insights into the potential prognostic and therapeutic implications of APOD in GC.

METTL2B m3C RNA transferase: oncogenic role in ovarian cancer progression via regulation of the mTOR/AKT pathway and its link to the tumor immune microenvironment

BACKGROUND

Aberrant expression of N3-methylcytidine methyltransferase 2B (METTL2B) has been observed in various human malignancies, including those of the prostate, liver, breasts, and bladder. However, its role in ovarian cancer (OC) remains largely unexplored. This research preliminarily investigated METTL2B expression in OC and elucidated the associated molecular mechanisms.

METHODS

We utilized three publicly available cancer-related databases (Genotype-Tissue Expression, Gene Expression Omnibus, and The Cancer Genome Atlas) to identify gene signatures in patients with OC and normal individuals with a specific focus on METTL2B. The role of METTL2B in OC was evaluated using patient survival data, and its impact on oncogenic behaviors in both cell and animal models, including growth potential, migration, invasion, and the tumor microenvironment, was examined. This assessment was conducted using bioinformatics tools such as Gene Set Cancer Analysis, GeneMANIA, and Tumor Immune Single-cell Hub 2. Additionally, the association between drug sensitivity and METTL2B expression was analyzed using CellMiner.

RESULTS

METTL2B expression was significantly elevated in OC, highlighting its potential clinical value in the diagnosis and prognosis of OC. Patients with lower METTL2B expression exhibited favorable survival. Furthermore, METTL2B knockdown significantly disrupted oncogenic behaviors in OC cell lines by suppressing the mTOR/AKT signaling pathway. Additionally, bioinformatics-based Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses suggested a close correlation between METTL2B and immune responses.

CONCLUSIONS

Our research confirmed the upregulation of METTL2B in OC, suggesting its oncogenic function. However, METTL2B expression was negatively correlated with the infiltration scores of multiple immune cells, including cytotoxic cells and T cells, indicating its complex role in the tumor immune microenvironment. These findings highlight the significant clinical value of METTL2B in the diagnosis and prognosis of OC.

Clinical relevance and function of HMGB1 gene polymorphism and expression in colorectal cancer

High HMGB1 levels contribute to the development and metastasis of tumors such as colorectal cancer (CRC). The current investigation sought to evaluate the association of a functional InDel polymorphism (rs34000982) on the HMGB1 gene with CRC susceptibility and tumor stage and the clinical relevance of HMGB1 gene expression. A total of 600 CRC patients and 600 healthy control individuals were genotyped by a polymerase chain reaction-polyacrylamide gel electrophoresis assay. The findings demonstrated that the rs34000982 Ins allele or Ins/Ins genotype was associated not only with reduced susceptibility to CRC, especially stage III-IV CRC (Ins vs. Del: OR = 0.65, 95%CI = 0.51-0.82, p < 0.001; Ins/Ins vs. Del/Del: OR = 0.29, 95%CI = 0.14- 0.60, p < 0.001), but also with tumor stage. CRC patients carrying the Ins allele or Ins/Ins genotype had a significantly lower risk of stage III-IV tumors (Ins vs. Del: OR = 0.69, 95%CI = 0.53- 0.91; Ins/Ins vs. Del/Del: OR = 0.41, 95%CI = 0.18-0.94). Functional research revealed that the rs34000982 Ins allele enabled hsa-miR-944 to interact with the 3' untranslated region of HMGB1. In addition, HMGB1 gene expression levels were associated not only with multiple immune cell infiltration, but also with multiple anti-CRC drug sensitivities. The current findings suggest that the HMGB1 rs34000982 polymorphism may serve as a marker of CRC susceptibility and progression in the Chinese population, and HMGB1 levels may serve as an anti-CRC drug sensitivity marker.

CancerHubs: a systematic data mining and elaboration approach for identifying novel cancer-related protein interaction hubs

Conventional approaches to predict protein involvement in cancer often rely on defining either aberrant mutations at the single-gene level or correlating/anti-correlating transcript levels with patient survival. These approaches are typically conducted independently and focus on one protein at a time, overlooking nucleotide substitutions outside of coding regions or mutational co-occurrences in genes within the same interaction network. Here, we present CancerHubs, a method that integrates unbiased mutational data, clinical outcome predictions and interactomics to define novel cancer-related protein hubs. Through this approach, we identified TGOLN2 as a putative novel broad cancer tumour suppressor and EFTUD2 as a putative novel multiple myeloma oncogene.

Towards simplified graph neural networks for identifying cancer driver genes in heterophilic networks

The identification of cancer driver genes is crucial for understanding the complex processes involved in cancer development, progression, and therapeutic strategies. Multi-omics data and biological networks provided by numerous databases enable the application of graph deep learning techniques that incorporate network structures into the deep learning framework. However, most existing methods do not account for the heterophily in the biological networks, which hinders the improvement of model performance. Meanwhile, feature confusion often arises in models based on graph neural networks in such graphs. To address this, we propose a Simplified Graph neural network for identifying Cancer Driver genes in heterophilic networks (SGCD), which comprises primarily two components: a graph convolutional neural network with representation separation and a bimodal feature extractor. The results demonstrate that SGCD not only performs exceptionally well but also exhibits robust discriminative capabilities compared to state-of-the-art methods across all benchmark datasets. Moreover, subsequent interpretability experiments on both the model and biological aspects provide compelling evidence supporting the reliability of SGCD. Additionally, the model can dissect gene modules, revealing clearer connections between driver genes in cancers. We are confident that SGCD holds potential in the field of precision oncology and may be applied to prognosticate biomarkers for a wide range of complex diseases.

GLN2 as a key biomarker and therapeutic target: evidence from a comprehensive pan-cancer study using molecular, functional, and bioinformatic analyses

BACKGROUND

GNL2, a nuclear protein, is involved in ribosome production and cell cycle regulation. However, its expression and function in different types of tumors are not well understood. Comprehensive studies across multiple cancer types are needed to assess the potential of GNL2 as a diagnostic, prognostic, and immunological marker.

METHODS

mRNA expression data, copy number alteration threshold data, masked copy number segmentation data, and DNA methylation 450 K data from The Cancer Genome Atlas (TCGA) pan-cancer cohort were obtained from the Firehose database. Additional data, including miRNA, The Cancer Proteome Atlas (TCPA), mutation data, and clinical information, were sourced from the University of California Santa Cruz (UCSC) Xena database. The cBioPortal database facilitates the examination of GNL2 mutation frequency, location, and 3D structure in the TCGA database. Gene Expression Omnibus (GEO) data verified the transcriptome level expression in the TCGA cohort. Protein expression levels were analyzed via the Human Protein Atlas (HPA) database and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. Gene set enrichment analysis (GSEA) was employed to investigate the biological role of GNL2 across cancers. Multiple immune infiltration algorithms from the TIMER2.0 database were utilized to examine the correlation between GNL2 expression and the tumor immune microenvironment. The transcriptome-wide immune infiltration results were validated using 72 single-cell datasets from the Tumor Immune Single-cell Hub (TISCH) database. Pan-cancer survival maps were constructed, and GNL2 expression in different molecular subtypes across cancers was examined. The relationship between GNL2 and drug resistance was investigated using data from CellMiner, GDSC, and CTRP. The Comparative Toxicogenomics Database (CTD) was used to identify chemicals affecting GNL2 expression.

RESULTS

GNL2 is located primarily in the nucleus, and its expression is regulated mainly through somatic copy number alteration (SCNA) and aberrant DNA methylation, according to TCGA data. Database analysis and immunohistochemical results from clinical samples revealed high GNL2 expression in most tumors, which was correlated with diagnostic significance. High GNL2 expression often indicates a poor prognosis with pan-cancer prognostic value. Gene set enrichment analysis (GSEA) suggested that GNL2 is involved in tumor development through cell proliferation-related pathways. GNL2 expression is correlated with the expression of immune-related genes and the infiltration levels of multiple immune cells. The relationships between GNL2 and various drugs and chemicals were examined, revealing its influence on drug sensitivity and identifying five chemicals countering GNL2-mediated pro-cancer effects.

CONCLUSION

Comprehensive bioinformatics analysis of GNL2 in pan-cancer tissues, combined with experimental validation, elucidated the pan-cancer expression pattern of GNL2, determined its diagnostic and prognostic value, and explored the biological functions of GNL2. GNL2 may be involved in the regulation of cell cycle progression and remodeling of the tumor microenvironment and is associated with poor prognosis as a risk factor in most tumors. The potential of GNL2-based cancer therapies is emphasized, assisting in predicting the response to chemotherapy.

Importance of LINC00852/miR-145-5p in breast cancer: a bioinformatics and experimental study

PURPOSE

We aimed to examine the importance of an lncRNA, namely LINC00852, in the pathogenesis of breast cancer.

MATERIALS AND METHODS

In the current study, we used several online tools to examine the importance of LINC00852 in breast cancer. Then, we examined these findings in 50 pairs of breast cancer tissues and adjacent non-cancerous ones. We also re-evaluated the data of miR-145-5p signature from our recent study.

RESULTS

While in silico tools revealed down-regulation of LINC00852 in breast cancer samples, expression assays showed significant up-regulation of this lncRNAs in breast cancer samples compared with matching control samples from Iranian patients. miR-145-5p was under-expressed in breast cancer samples compared with non-cancerous samples. LINC00852 could separate breast cancer tissues from adjacent non-malignant tissues with an AUC value of 0.7218 (P value < 0.001).

CONCLUSION

The current study potentiates LINC00852/miR-145-5p axis as a possible contributor to the pathogenesis of breast cancer.

Ribosomal proteins in hepatocellular carcinoma: mysterious but promising

Ribosomal proteins (RPs) are essential components of ribosomes, playing a role not only in ribosome biosynthesis, but also in various extra-ribosomal functions, some of which are implicated in the development of different types of tumors. As universally acknowledged, hepatocellular carcinoma (HCC) has been garnering global attention due to its complex pathogenesis and challenging treatments. In this review, we analyze the biological characteristics of RPs and emphasize their essential roles in HCC. In addition to regulating related signaling pathways such as the p53 pathway, RPs also act in proliferation and metastasis by influencing cell cycle, apoptosis, angiogenesis, and epithelial-to-mesenchymal transition in HCC. RPs are expected to unfold new possibilities for precise diagnosis and individualized treatment of HCC.

SPP1+ macrophages and FAP+ fibroblasts promote the progression of pMMR gastric cancer

Immunotherapy has become a primary and secondary treatment for gastric cancer (GC) patients with mismatch repair deficiency (dMMR), and is used in both perioperative and advanced stages. The tumor immune microenvironment (TiME) is crucial for immunotherapy efficacy, yet the impact of MMR status on TiME remains understudied. We employed single-cell RNA sequencing (scRNA-seq) to analyze 33 fresh tissue samples from 25 patients, which included 10 normal tissues, 6 dMMR tumor tissues, and 17 pMMR tumor tissues, aiming to characterize the cellular and molecular components of the TiME. The proficient mismatch repair (pMMR) group displayed a significantly higher prevalence of a specific GC cell type, termed GC2, characterized by increased hypoxia, epithelial-mesenchymal transition (EMT), and angiogenic activities compared to the dMMR group. GC2 cells overexpressed BEX3 and GPC3, and they significantly correlated with poorer survival. The pMMR group also showed increased infiltration of SPP1 + macrophages and FAP + fibroblasts, exhibiting strong hypoxic and pro-angiogenic features. Furthermore, a higher proportion of E2 endothelial cells, involved in extracellular matrix (ECM) remodeling and showing heightened VEGF pathway, HIF pathway, and angiogenesis activity, were identified in pMMR patients. Intercellular communication analyses revealed that GC2 cells, SPP1 + macrophages, FAP + fibroblasts, and E2 endothelial cells interact through VEGF, SPP1, and MIF signals, forming a TiME characterized by hypoxia, pro-angiogenesis, and ECM remodeling. This study uncovered TiME heterogeneity among GC patients with different MMR states, highlighting that the pMMR TiME is distinguished by hypoxia, pro-angiogenesis, and ECM remodeling, driven by the presence of GC2 cells, SPP1 + macrophages, FAP + fibroblasts, and E2 endothelial cells. These findings are pivotal for developing targeted immunotherapies for GC patients with pMMR.

Prognostic and therapeutic potential of gene profiles related to tertiary lymphoid structures in colorectal cancer

The role of tertiary lymphoid structures (TLS) in oncology is gaining interest, particularly in colorectal carcinoma, yet a thorough analysis remains elusive. This study pioneered a novel TLS quantification system for prognostic and therapeutic response prediction in colorectal carcinoma, alongside a comprehensive depiction of the TLS landscape. Utilizing single-cell sequencing, we established a TLS score within the Tumor Immune Microenvironment (TIME). Analysis of tertiary lymphoid structure-related genes (TLSRGs) in 1,184 patients with colon adenocarcinoma/rectum adenocarcinoma (COADREAD) from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases led to the identification of two distinct molecular subtypes. Differentially expressed genes (DEGs) further segregated these patients into gene subtypes. A TLS score was formulated using gene set variation analysis (GSVA) and its efficacy in predicting immunotherapy outcomes was validated in two independent cohorts. High-scoring patients exhibited a 'hot' immune phenotype, correlating with enhanced immunotherapy efficacy. Key genes in our model, including C5AR1, APOE, CYR1P1, and SPP1, were implicated in COADREAD cell proliferation, invasion, and PD-L1 expression. These insights offer a novel approach to colorectal carcinoma treatment, emphasizing TLS targeting as a potential anti-tumor strategy.