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

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.

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.

IGSF1: a biomarker for predicting prognosis, immunotherapy response, and drug candidates in COVID-19 combined hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy with poor prognosis and a common cause of cancer-related death worldwide, and despite ongoing therapeutic breakthroughs, patient survival benefits are limited. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of coronavirus disease 2019 (COVID-19) and poses a major threat to humanity worldwide. As the epidemic continues to develop, more and more people are infected with SARS-CoV-2, including patients with HCC. However, the relationship between COVID-19 and HCC has not yet been fully elucidated. Our study aimed to identify the shared genetic characteristics and molecular mechanisms between COVID-19 and HCC. The data involved in this study come from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression(GTEx), and Cancer Cell Line Encyclopedia(CCLE) databases. We used differentially expressed genes to perform enrichment analysis to reveal the biological landscape of COVID-19 combined with HCC. In addition, weighted gene co-expression network analysis (WGCNA) was used to study the co-expression network related to COVID-19 and HCC. We then combined the validation datasets to screen out immunoglobulin superfamily member 1 (IGSF1) as the most important core gene. Finally, we extensively studied the functional expression of IGSF1 in tumor samples, normal tissues, and cancer cell lines. The molecular mechanisms related to COVID-19 and HCC are rarely studied. Our study identifies IGSF1 as a potential therapeutic target and immune-related biomarker for patients with COVID-19 and HCC.

Integrative Analysis of Acupuncture Targets and Immune Genes in Diabetes, Diabetic Peripheral Neuropathy, and Adjunct Therapy of Cancer

Introduction

Acupuncture may help treat diabetes mellitus (DM), diabetic peripheral neuropathy (DPN), and adjunct therapy for cancer, but the biological mechanisms and immune-related genes involved are unclear; this study aims to clarify these aspects.

Methods

Comprehensive gene expression analysis revealed differentially expressed genes (DEGs) among DM, DPN, and control samples. Key genes from WGCNA were intersected with DEGs and acupuncture targets. Inflammatory responses, immune processes, signaling pathways, immune cell infiltration, and microRNA-gene interactions were studied. Hub immune-related genes' dysregulation was analyzed for copy number variation and gene methylation. A pan-cancer nomogram model was created to predict survival based on various factors, linking hub genes to cancer properties.

Results

Our analysis found 3,217 and 2,191 DEGs in DM/control and DPN/DM comparisons, respectively, and identified 1,830 potential acupuncture targets. We pinpointed 21 key genes in DM and 43 in DPN, involved in inflammatory responses, immune processes, CAMKK2, and cAMP signaling pathways. Distinct immune cell infiltration patterns, including M0 and M2 macrophages, neutrophils, and follicular helper T cells, were noted. Further analysis revealed microRNAs and TF genes interacting with immune hub genes in both conditions. Dysregulation of eight hub immune-related genes was linked to copy number variation and gene methylation, correlating with cancer prognosis. Co-occurrence of single nucleotide variations and oncogenic mutations was observed in these genes. The pan-cancer nomogram model showed strong prognostic capabilities, and a significant association was found between the eight genes and cancer properties like angiogenesis, EMT, and cell cycle progression.

Discussion

Our findings underscore the pivotal roles of MAPK3, IL1RN, SOD2, CTSD, ESR1, SLC1A1, NPY, and CCR2 in the immune response mediated by acupuncture in the context of DM, DPN, and adjunct therapy for cancer.

Comprehensive pan-cancer analysis reveals ENC1 as a promising prognostic biomarker for tumor microenvironment and therapeutic responses

Accumulating research showed that ENC1 plays a critical role in maintaining the physiological functions. However, little is known about its role in predicting prognosis and immunotherapy response across cancers. In our results, compared to normal tissues, most cancer tissues exhibit increased ENC1 expression. We found that the most common type of genetic variation was gene mutation. In addition, a positive correlation was found between CNV and ENC1 expression. Moreover, the overexpression of ENC1 was positively correlated with poor clinical outcomes. The GSEA results showed that ENC1 is closely correlated with tumor-promoting biological functions in most cancers. ENC1 is also closely negatively associated with the infiltration levels of T cells, activated NK cells, and B cells. Most immunomodulators are positively associated with ENC1. Further, we verified that inhibition of ENC1 expression suppressed the proliferation and migration of breast cancer, pancreatic cancer and glioma cells. In conclusion, our study demonstrated that ENC1 plays a protumorigenic role in most cancers. Additionally, ENC1 is closely correlated with tumor microenvironment features and immune checkpoint inhibitors expression. Overall, ENC1 could serve as a promising potential prognostic biomarker in various tumors.

Multi-omics analysis identifies PTTG1 as a prognostic biomarker associated with immunotherapy and chemotherapy resistance

BACKGROUND

Pituitary tumor-transforming gene 1 (PTTG1) is an important gene in tumour development. However, the relevance of PTTG1 in tumour prognosis, immunotherapy response, and medication sensitivity in human pan-cancer has to be determined.

METHODS

TIMER, GEPIA, the human protein atlas, GEPIA, TISCH2, and cBioportal examined the gene expression, protein expression, prognostic value, and genetic modification landscape of PTTG1 in 33 malignancies based on the TCGA cohort. The association between PTTG1 and tumour immunity, tumour microenvironment, immunotherapy response, and anticancer drug sensitivity was investigated using GSCA, TIDE, and CellMiner CDB. Molecular docking was used to validate the possible chemotherapeutic medicines for PTTG1. Additionally, siRNA-mediated knockdown was employed to confirm the probable role of PTTG1 in paclitaxel-resistant cells.

RESULTS

PTTG1 is overexpressed and associated with poor survival in most tumors. Functional enrichment study revealed that PTTG1 is involved in the cell cycle and DNA replication. A substantial connection between PTTG1 expression and immune cell infiltration points to PTTG1's possible role in the tumour microenvironment. High PTTG1 expression is associated with tumour immunotherapy resistance. The process could be connected to PTTG1, which mediates T cell exhaustion and promotes cytotoxic T lymphocyte malfunction. Furthermore, PTTG1 was found to be substantially linked with sensitivity to several anticancer medications. Suppressing PTTG1 with siRNA reduced clone formation and migration, implying that PTTG1 may play a role in paclitaxel resistance.

CONCLUSION

PTTG1 shows potential as a cancer diagnostic, prognostic, and chemosensitivity marker. Increased PTTG1 expression is linked to resistance to cancer treatment. The mechanism could be linked to PTTG1's role in promoting cytotoxic T lymphocyte dysfunction and mediating T cell exhaustion. It is feasible to consider PTTG1, which is expressed on Treg and Tprolif cells, as a new therapeutic target for overcoming immunotherapy resistance.

Establishment and Verification of a Novel Gene Signature Connecting Hypoxia and Lactylation for Predicting Prognosis and Immunotherapy of Pancreatic Ductal Adenocarcinoma Patients by Integrating Multi-Machine Learning and Single-Cell Analysis

Pancreatic ductal adenocarcinoma (PDAC) has earned a notorious reputation as one of the most formidable and deadliest malignant tumors. Within the tumor microenvironment, cancer cells have acquired the capability to maintain incessant expansion and increased proliferation in response to hypoxia via metabolic reconfiguration, leading to elevated levels of lactate within the tumor surroundings. However, there have been limited studies specifically investigating the association between hypoxia and lactic acid metabolism-related lactylation in PDAC. In this study, multiple machine learning approaches, including LASSO regression analysis, XGBoost, and Random Forest, were employed to identify hub genes and construct a prognostic risk signature. The implementation of the CERES score and single-cell analysis was used to discern a prospective therapeutic target for the management of PDAC. CCK8 assay, colony formation assays, transwell, and wound-healing assays were used to explore both the proliferation and migration of PDAC cells affected by CENPA. In conclusion, we discovered two distinct subtypes characterized by their unique hypoxia and lactylation profiles and developed a risk score to evaluate prognosis, as well as response to immunotherapy and chemotherapy, in PDAC patients. Furthermore, we indicated that CENPA may serve as a promising therapeutic target for PDAC.

The pan-cancer landscape presented ITGA7 as a prognostic determinant, tumor suppressor, and oncogene in multiple tumor types

Integrin α7 (ITGA7) is an extracellular matrix-binding protein. Integrins are the main type of cell adhesive molecules in mammals, playing a role in many biological pathways. Although various studies have shown correlations between ITGA7 and various types of cancer, a comprehensive study at a pan-cancer level has not yet been conducted. In this study, we investigated the function of ITGA7 in distinct tumor types using the multi-omics relevant information, then two CeRNA regulatory network was drawn to identify the ITGA7 hub regulatory RNAs. The results indicated that the expression of ITGA7 varies in different tumors. Overexpression of ITGA7 was correlated with a worse OS in BLCA, LGG, and UVM, and the downregulation of ITGA7 was related to a worse OS in PAAD. In addition, BLCA, and UVM showed poor PFS in association with ITGA7 overexpression, and PAAD, SARC, and THCA indicated poor PFS in correlation with ITGA7 under expression. Further analyses of ITGA7 gene alteration data showed that ITGA7 amplifications may have an impact on Kidney Chromophobe prognosis. In 20 types of tumors, ITGA7 expression was linked to cancer-associated fibroblast infiltration. ITGA7 expression was linked to cancer-associated fibroblast infiltration. ITGA7-Related Gene Enrichment Analysis indicated that ITGA7 expression-correlated and functional binding genes were enriched in homotypic cell-cell adhesion, focal adhesion, and ECM-receptor interaction. This pan-cancer study found that abnormal expression of ITGA7 was correlated with poor prognosis and metastasis in different types of tumors. Thus, the ITGA7 gene may prove to be a promising biomarker for the prognosis and complication prevention of different cancers.

Bioinformatic analysis of molecular characteristics and oncogenic features of CARD14 in human cancer

Aberrant caspase recruitment domain family member 14 (CARD14) signaling has been strongly associated with inflammatory skin conditions. CARD14 acts as a scaffold protein, ultimately activating the transcription factor NF-KB. Although primarily studied in the context of inflammation, recent research has suggested its potential implications in tumorigenesis. In this study, we gathered The Cancer Genome Atlas (TCGA) tumor data to gauge the involvement of CARD14 in cancer, including genetic alterations, expression patterns, survival correlations, immune cell infiltration and functional interactions across diverse cancer types. We found heightened CARD14 expression in most tumors and there was a significant correlation between CARD14 expression and the prognosis of patients for certain tumors. For instance, patients with higher CARD14 expression had a better prognosis in sarcoma, lung, cervix and head and neck cancers. Moreover, CARD14 expression positively correlated with neutrophil infiltration in most of the cancer types analyzed. Finally, enrichment analysis showed that epithelial development and differentiation pathways were involved in the functional mechanism of CARD14. Our results show that CARD14 may have the potential to become a prognostic biomarker in several cancers, hence, further prospective studies will be required for its validation.

A tumour-associated macrophage-based signature for deciphering prognosis and immunotherapy response in prostate cancer

For the multistage progression of prostate cancer (PCa) and resistance to immunotherapy, tumour-associated macrophage is an essential contributor. Although immunotherapy is an important and promising treatment modality for cancer, most patients with PCa are not responsive towards it. In addition to exploring new therapeutic targets, it is imperative to identify highly immunotherapy-sensitive individuals. This research aimed to establish a signature risk model, which derived from the macrophage, to assess immunotherapeutic responses and predict prognosis. Data from the UCSC-XENA, GEO and TISCH databases were extracted for analysis. Based on both single-cell datasets and bulk transcriptome profiles, a macrophage-related score (MRS) consisting of the 10-gene panel was constructed using the gene set variation analysis. MRS was highly correlated with hypoxia, angiogenesis, and epithelial-mesenchymal transition, suggesting its potential as a risk indicator. Moreover, poor immunotherapy responses and worse prognostic performance were observed in the high-MRS group of various immunotherapy cohorts. Additionally, APOE, one of the constituent genes of the MRS, affected the polarisation of macrophages. In particular, the reduced level of M2 macrophage and tumour progression suppression were observed in PCa xenografts which implanted in Apolipoprotein E-knockout mice. The constructed MRS has the potential as a robust prognostic prediction tool, and can aid in the treatment selection of PCa, especially immunotherapy options.

LTBR acts as a novel immune checkpoint of tumor-associated macrophages for cancer immunotherapy

Tumor-associated macrophages (TAMs) greatly contribute to immune checkpoint inhibitor (ICI) resistance of cancer. However, its underlying mechanisms and whether TAMs can be promising targets to overcome ICI resistance remain to be unveiled. Through integrative analysis of immune multiomics data and single-cell RNA-seq data (iMOS) in lung adenocarcinoma (LUAD), lymphotoxin β receptor (LTBR) is identified as a potential immune checkpoint of TAMs, whose high expression, duplication, and low methylation are correlated with unfavorable prognosis. Immunofluorescence staining shows that the infiltration of LTBR+ TAMs is associated with LUAD stages, immunotherapy failure, and poor prognosis. Mechanistically, LTΒR maintains immunosuppressive activity and M2 phenotype of TAMs by noncanonical nuclear factor kappa B and Wnt/β-catenin signaling pathways. Macrophage-specific knockout of LTBR hinders tumor growth and prolongs survival time via blocking TAM immunosuppressive activity and M2 phenotype. Moreover, TAM-targeted delivery of LTΒR small interfering RNA improves the therapeutic effect of ICI via reversing TAM-mediated immunosuppression, such as boosting cytotoxic CD8+ T cells and inhibiting granulocytic myeloid-derived suppressor cells infiltration. Taken together, we bring forth an immune checkpoint discovery pipeline iMOS, identify LTBR as a novel immune checkpoint of TAMs, and propose a new immunotherapy strategy by targeting LTBR+ TAMs.

Construction and validation of a machine learning-based immune-related prognostic model for glioma

BACKGROUND

Glioma stands as the most prevalent primary brain tumor found within the central nervous system, characterized by high invasiveness and treatment resistance. Although immunotherapy has shown potential in various tumors, it still faces challenges in gliomas. This study seeks to develop and validate a prognostic model for glioma based on immune-related genes, to provide new tools for precision medicine.

METHODS

Glioma samples were obtained from a database that includes the ImmPort database. Additionally, we incorporated ten machine learning algorithms to assess the model's performance using evaluation metrics like the Harrell concordance index (C-index). The model genes were further studied using GSCA, TISCH2, and HPA databases to understand their role in glioma pathology at the genomic, molecular, and single-cell levels, and validate the biological function of IKBKE in vitro experiments.

RESULTS

In this study, a total of 199 genes associated with prognosis were identified using univariate Cox analysis. Subsequently, a consensus prognostic model was developed through the application of machine learning algorithms. In which the Lasso + plsRcox algorithm demonstrated the best predictive performance. The model showed a good ability to distinguish two groups in both the training and test sets. Additionally, the model genes were closely related to immunity (oligodendrocytes and macrophages), and mutation burden. The results of in vitro experiments showed that the expression level of the IKBKE gene had a significant effect on the apoptosis and migration of GL261 glioma cells. Western blot analysis showed that down-regulation of IKBKE resulted in increased expression of pro-apoptotic protein Bax and decreased expression of anti-apoptotic protein Bcl-2, which was consistent with increased apoptosis rate. On the contrary, IKBKE overexpression caused a decrease in Bax expression an increase in Bcl-2 expression, and a decrease in apoptosis rate. Tunel results further confirmed that down-regulation of IKBKE promoted apoptosis, while overexpression of IKBKE reduced apoptosis. In addition, cells with down-regulated IKBKE had reduced migration in scratch experiments, while cells with overexpression of IKBKE had increased migration.

CONCLUSION

This study successfully constructed a glioma prognosis model based on immune-related genes. These findings provide new perspectives for glioma prognosis assessment and immunotherapy.

Facilitating integrative and personalized oncology omics analysis with UCSCXenaShiny

The continuous generation of multi-omics and phenotype data is propelling advancements in precision oncology. UCSCXenaShiny was developed as an interactive tool for exploring thousands of cancer datasets available on UCSC Xena. However, its capacity for comprehensive and personalized pan-cancer data analysis is being challenged by the growing demands. Here, we introduce UCSCXenaShiny v2, a milestone update through a variety of improvements. Firstly, by integrating multidimensional data and implementing adaptable sample settings, we create a suite of robust TPC (TCGA, PCAWG, CCLE) analysis pipelines. These pipelines empower users to conduct in-depth analyses of correlation, comparison, and survival in three modes: Individual, Pan-cancer and Batch screen. Additionally, the tool includes download interfaces that enable users to access diverse data and outcomes, several features also facilitate the joint analysis of drug sensitivity and multi-omics of cancer cell lines. UCSCXenaShiny v2 is an open-source R package and a web application, freely accessible at https://github.com/openbiox/UCSCXenaShiny .

SSCI: Self-Supervised Deep Learning Improves Network Structure for Cancer Driver Gene Identification

The pathogenesis of cancer is complex, involving abnormalities in some genes in organisms. Accurately identifying cancer genes is crucial for the early detection of cancer and personalized treatment, among other applications. Recent studies have used graph deep learning methods to identify cancer driver genes based on biological networks. However, incompleteness and the noise of the networks will weaken the performance of models. To address this, we propose a cancer driver gene identification method based on self-supervision for graph convolutional networks, which can efficiently enhance the structure of the network and further improve predictive accuracy. The reliability of SSCI is verified by the area under the receiver operating characteristic curves (AUROC), the area under the precision-recall curves (AUPRC), and the F1 score, with respective values of 0.966, 0.964, and 0.913. The results show that our method can identify cancer driver genes with strong discriminative power and biological interpretability.

Clinical significance of RETN gene expression and rs3219175 G > a polymorphism in cancer

The inflammatory cytokine resistin, which is encoded by the RETN gene, plays a variety of roles in cancer. This study aimed to assess the relationship between RETN gene expression and cancer stage, survival prognosis, immune infiltration, and drug sensitivity, and whether the rs3219175 G > A polymorphism affected the expression of the RETN gene and cancer risk. The clinical significance of RETN gene expression and the rs3219175 polymorphism in cancer was analyzed by the GSCA platform, GTEx database and STATA software. The results showed that RETN gene expression was associated with the stage of thyroid carcinoma, survival prognosis and immune infiltration of certain cancers, and sensitivity to multiple drugs. The rs3219175 polymorphism could influence the expression of the RETN gene in a wide range of tissues. Furthermore, RETN gene rs3219175 polymorphism was significantly associated with cancer risk [GA vs. GG: OR = 2.27, 95%CI = 1.26-4.09; (GA + AA) vs. GG: OR = 2.23, 95%CI = 1.28-3.88; A vs. G: OR = 1.72, 95%CI = 1.15-2.58]. In conclusion, the current study suggested that resistin might serve as a prognostic marker and therapeutic target for certain cancers, and the rs3219175 polymorphism might be used as a marker for predicting cancer risk.

Comprehensive pan-cancer analysis and experiments revealed R3HDM1 as a novel predictive biomarker for prognosis and immune therapy response

Background

R3HDM1, an RNA binding protein with one R3H domain, remains uncharacterized in terms of its association with tumor progression, malignant cell regulation, and the tumor immune microenvironment. This paper aims to fill this gap by analyzing the potential of R3HDM1 in diagnosis, prognosis, chemotherapy, and immune function across various cancers.

Methods

Data was collected from the Firehost database (http://gdac.broadinstitute.org) to obtain the TCGA pan-cancer queue containing tumor and normal samples. Additional data on miRNA, TCPA, mutations, and clinical information were gathered from the UCSC Xena database (https://xenabrowser.net/datapages/). The mutation frequency and locus of R3HDM1 in the TCGA database were examined using the cBioPortal. External validation through GEO data was conducted to assess the differential expression of R3HDM1 in different cancers. Protein expression levels were evaluated using the Clinical Proteomics Tumor Analysis Alliance (CPTAC). The differential expression of R3HDM1 was verified in lung adenocarcinoma cell lines and normal lung glandular epithelial cells via RT-qPCR. Cell migration and proliferation experiments were conducted by knocking down the expression of R3HDM1 in two lung adenocarcinoma cell lines using small interfering RNA. The biological role of R3HDM1 in pan-cancer was explored using the GSEA method. Multiple immune infiltration algorithms from the TIMER2.0 database was employed to investigate the correlation between R3HDM1 expression and the tumor immune microenvironment. Validation of transcriptome immune infiltration was based on 140 single-cell datasets from the TISCH database. The study also characterized a pan-cancer survival profile and analyzed the differential expression of R3HDM1 in different molecular subtypes. The relationship between R3HDM1 and drug resistance was investigated using four chemotherapy data sources: CellMiner, GDSC, CTRP and PRISM. The impact of chemicals on the expression of R3HDM1 was explored through the CTD database.

Result

The study revealed differential expression of R3HDM1 in various tumors, indicating its potential as an early diagnostic marker. Changes in somatic copy number (SCNA) and DNA methylation were identified as factors contributing to abnormal expression levels. Additionally, the study found that R3HDM1 expression is associated with clinical features, metabolic pathways, and important pathways related to metastasis and the immune system. High expression of R3HDM1 was linked to poor prognosis across different tumors and altered drug sensitivity. Furthermore, the expression of R3HDM1 showed significant correlations with immune modulatory molecules and biomarkers of lymphocyte subpopulation infiltration. Finally, the study highlighted four chemicals that could influence the expression of R3HDM1.

Conclusion

Overall, this study proposes that R3HDM1 expression is a promising biomarker for predicting the prognosis of cancer, especially lung adenocarcinoma, and the efficacy of immunotherapy, demonstrating the rationale for further exploration in the development of anti-tumor therapies.

Pan-cancer analysis reveals copper transporters as promising potential targets

Background

Copper transport proteins (SLC31A1, ATP7A, ATP7B) regulate copper levels in the body and may be involved in tumor development. However, their comprehensive expression and function across various cancers remain unclear.

Methods

The expressions of copper transporters in 33 tumors and normal tissues were analyzed using TCGA, GTEx, CCLE, ULCAN, and HPA databases. Cox regression assessed their impact on patient survival. Gene alterations were explored using cBioPortal. Spearman correlation tests were performed to investigate the associations between copper transporters and tumor mutation burden (TMB), microsatellite instability (MSI), and infiltration of immune cells. Gene functions were analyzed using STRING and GeneMANIA databases. Drug sensitivity was assessed using GSCALite database. ATP7B expression in lung squamous cell carcinoma (LUSC) was validated by immunohistochemical staining.

Results

Copper transporters exhibited variable expression patterns across various cancer types, indicating their potential dual role as either oncogenes or tumor suppressor genes, depending on the cancer type. Significant associations were found between these transporters and tumor stage, as well as prognosis in most tumors studied. Pathway analysis identified links between copper transporters and tumor-related pathways like apoptosis and RAS/MAPK. Copy number variation (CNV) analysis revealed varying degrees of gene amplification and deletion of copper transporters in most tumors. Copper transporters exhibited strong correlations with immune features, including TMB, MSI, and immune-infiltrating cells, suggesting their potential role in guiding immunotherapy. They were also associated with sensitivity to various chemotherapeutic and immunotherapeutic drugs. Immunohistochemical tests validated the correlation between elevated ATP7B level and worse progression-free survival (PFS) in LUSC.

Conclusion

Copper transporters may serve as potential tumor markers and therapeutic targets.

Identification of the shared gene MXD3 signatures and biological mechanism in patients with hip pain and prostate cancer

Prostate cancer (PRAD) is recognized as having a significant effect on systemic illnesses. This study examined possible immune cells, metabolic pathways, and genes that may explain the interaction between PRAD and hip pain. We used information retrieved from the Cancer Genome Atlas and the Gene Expression Omnibus databases. To find common genes, we utilized differential expression analysis and weighted gene co-expression network analysis. The genes that were shared were subjected to pathway enrichment studies using Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. Additionally, hub genes were analyzed using LASSO regression, and a receiver operating characteristic curve was generated based on the screening outcomes. The genes for the nodes were chosen in a protein-protein interaction network that was built. Single-sample gene-set enrichment analysis was performed to identify the differentially expressed genes. Immunohistochemistry staining confirmed hub gene expression, and single-sample gene-set enrichment analysis assessed immune cell infiltration. We concluded by comparing MAX dimerization protein 3 (MXD3) and MAX interactor 1 (MXI1) expression in tumor tissues using Uniform Manifold Approximation and Projection and violin plots in the Tumor lmmune Single-cell Hub database. After analyzing the intersection of the differentially expressed genes and weighted gene co-expression network analysis-significant module genes, we determined that MXD3 was the best shared diagnostic biomarker for PRAD and hip pain. One potential predictor of PRAD development was the MXI1 node gene, which was found in the protein-protein interaction network. The analyses revealed that MXD3 had a relatively positive correlation with neutrophil and T-helper cell infiltration levels, whereas MXI1 had a negative correlation with mast and Tgd cell levels. Tumors had lower levels of MXI1 expression and higher levels of MXD3 expression compared to normal tissues. Endothelial cells, induced pluripotent stem cells, and smooth muscle cells were all found to express MXI1. This is the first study to investigate the close genetic link between hip pain and PRAD using bioinformatics technologies. The 2 most significant genes involved in crosstalk between PRAD and hip pain were MXD3 and MXI1. The immunological responses triggered by T cells, mast cells, and neutrophils may be crucial in the relationship between PRAD and hip pain.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Bioinformatics tools and resources for cancer and application

ABSTRACT

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

Identification of HDAC10 as a candidate oncogene in clear cell renal carcinoma that facilitates tumor proliferation and metastasis

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) remains one of the most lethal urological malignancies even though a great number of improvements in diagnosis and management have achieved over the past few decades. Accumulated evidence revealed that histone deacetylases (HDACs) play vital role in cell proliferation, differentiation and apoptosis. Nevertheless, the biological functions of histone deacetylation modification related genes in ccRCC remains poorly understood.

METHOD

Bulk transcriptomic data and clinical information of ccRCC patients were obtained from the TCGA database and collected from the Chinese PLA General Hospital. A total of 36 histone deacetylation genes were selected and studied in our research. Univariate cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression, random forest (RF) analysis, and protein-protein interaction (PPI) network analysis were applied to identify key genes affecting the prognosis of ccRCC. The 'oncoPredict' algorithm was utilized for drug-sensitive analysis. Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was used to explore the potential biological function. The ssGSEA algorithm was used for tumor immune microenvironment analysis. The expression levels of HDAC10 were validated by RT-PCR and immunohistochemistry (IHC). 5-ethynyl-2'-deoxyuridine (EdU assay), CCK-8 assay, cell transwell migration and invasion assay and colony formation assay were performed to detect the proliferation and invasion ability of ccRCC cells. A nomogram incorporating HDAC10 and clinicopathological characteristics was established to predict the prognosis of ccRCC patients.

RESULT

Two machine learning algorithms and PPI analysis identified four histone deacetylation genes that have a significant association with the prognosis of ccRCC, with HDAC10 being the key gene among them. HDAC10 is highly expressed in ccRCC and its high expression is associated with poor prognosis for ccRCC patients. Pathway enrichment and the experiments of EdU staining, CCK-8 assay, cell transwell migration and invasion assay and colony formation assay demonstrated that HDAC10 mediated the proliferation and metastasis of ccRCC cells and involved in reshaping the tumor microenvironment (TME) of ccRCC. A clinically reliable prognostic predictive model was established by incorporating HDAC10 and other clinicopathological characteristics ( https://nomogramhdac10.shinyapps.io/HDAC10_Nomogram/ ).

CONCLUSION

Our study found the increased expression of HDAC10 was closely associated with poor prognosis of ccRCC patients. HDAC10 showed a pro-tumorigenic effect on ccRCC and promote the proliferation and metastasis of ccRCC, which may provide new light on targeted therapy for ccRCC.

mtPCDI: a machine learning-based prognostic model for prostate cancer recurrence

Background

This research seeks to formulate a prognostic model for forecasting prostate cancer recurrence by examining the interaction between mitochondrial function and programmed cell death (PCD).

Methods

The research involved analyzing four gene expression datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) using univariate Cox regression. These analyses identified genes linked with mitochondrial function and PCD that correlate with recurrence prognosis. Various machine learning algorithms were then employed to construct an optimal predictive model.

Results

A key outcome was the creation of a mitochondrial-related programmed cell death index (mtPCDI), which effectively predicts the prognosis of prostate cancer patients. It was observed that individuals with lower mtPCDI exhibited higher immune activity, correlating with better recurrence outcomes.

Conclusion

The study demonstrates that mtPCDI can be used for personalized risk assessment and therapeutic decision-making, highlighting its clinical significance and providing insights into the biological processes affecting prostate cancer recurrence.

Integrating Machine Learning and Mendelian Randomization Determined a Functional Neurotrophin-Related Gene Signature in Patients with Lower-Grade Glioma

Recent researches reported that neurotrophins can promote glioma growth/invasion but the relevant model for predicting patients' survival in Lower-Grade Gliomas (LGGs) lacked. In this study, we adopted univariate Cox analysis, LASSO regression, and multivariate Cox analysis to determine a signature including five neurotrophin-related genes (NTGs), CLIC1, SULF2, TGIF1, TTF2, and WEE1. Two-sample Mendelian Randomization (MR) further explored whether these prognostic-related genes were genetic variants that increase the risk of glioma. A total of 1306 patients have been included in this study, and the results obtained from the training set can be verified by four independent validation sets. The low-risk subgroup had longer overall survival in five datasets, and its AUC values all reached above 0.7. The risk groups divided by the NTGs signature exhibited a distinct difference in targeted therapies from the copy-number variation, somatic mutation, LGG's surrounding microenvironment, and drug response. MR corroborated that TGIF1 was a potential causal target for increasing the risk of glioma. Our study identified a five-NTGs signature that presented an excellent survival prediction and potential biological function, providing new insight for the selection of LGGs therapy.

DCS, a novel classifier system based on disulfidptosis reveals tumor microenvironment heterogeneity and guides frontline therapy for clear cell renal carcinoma

Background

Emerging evidence suggests that cell deaths are involved in tumorigenesis and progression, which may be treated as a novel direction of cancers. Recently, a novel type of programmed cell death, disulfidptosis, was discovered. However, the detailed biological and clinical impact of disulfidptosis and related regulators remains largely unknown.

Methods

In this work, we first enrolled pancancer datasets and performed multi-omics analysis, including gene expression, DNA methylation, copy number variation and single nucleic variation profiles. Then we deciphered the biological implication of disulfidptosis in clear cell renal cell carcinoma (ccRCC) by machine learning. Finally, a novel agent targeting at disulfidptosis in ccRCC was identified and verified.

Results

We found that disulfidptosis regulators were dysregulated among cancers, which could be explained by aberrant DNA methylation and genomic mutation events. Disulfidptosis scores were depressed among cancers and negatively correlated with epithelial mesenchymal transition. Disulfidptosis regulators could satisfactorily stratify risk subgroups in ccRCC, and a novel subtype, DCS3, owning with disulfidptosis depression, insensitivity to immune therapy and aberrant genome instability were identified and verified. Moreover, treating DCS3 with NU1025 could significantly inhibit ccRCC malignancy.

Conclusion

This work provided a better understanding of disulfidptosis in cancers and new insights into individual management based on disulfidptosis.

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.

Multiomics and machine learning-based analysis of pancancer pseudouridine modifications

Pseudouridine widely affects the stability and function of RNA. However, our knowledge of pseudouridine properties in tumors is incomplete. We systematically analyzed pseudouridine synthases (PUSs) expression, genomic aberrations, and prognostic features in 10907 samples from 33 tumors. We found that the pseudouridine-associated pathway was abnormal in tumors and affected patient prognosis. Dysregulation of the PUSs expression pattern may arise from copy number variation (CNV) mutations and aberrant DNA methylation. Functional enrichment analyses determined that the PUSs expression was closely associated with the MYC, E2F, and MTORC1 signaling pathways. In addition, PUSs are involved in the remodeling of the tumor microenvironment (TME) in solid tumors, such as kidney and lung cancers. Particularly in lung cancer, increased expression of PUSs is accompanied by increased immune checkpoint expression and Treg infiltration. The best signature model based on more than 112 machine learning combinations had good prognostic ability in ACC, DLBC, GBM, KICH, MESO, THYM, TGCT, and PRAD tumors, and is expected to guide immunotherapy for 19 tumor types. The model was also effective in identifying patients with tumors amenable to etoposide, camptothecin, cisplatin, or bexarotene treatment. In conclusion, our work highlights the dysregulated features of PUSs and their role in the TME and patient prognosis, providing an initial molecular basis for future exploration of pseudouridine. Studies targeting pseudouridine are expected to lead to the development of potential diagnostic strategies and the evaluation and improvement of antitumor therapies.

Clinical significance of LIN28A gene polymorphisms and expression in pan-cancer: a meta-analysis and bioinformatic analysis

Several studies have reported the relationship between LIN28A gene polymorphisms (rs3811463 T > C and rs34787247 G > A) and cancer susceptibility, but the results are inconsistent and need further clarification. The current study aimed to evaluate their relationship and also to explore the relationship between LIN28A gene expression and immune infiltration, tumor stage, survival prognosis, and drug sensitivity in pan-cancer. The meta-analysis and data mining were completed by STATA software and the GSCA platform, respectively. The meta-analysis showed that the rs3811463 polymorphism was not associated with cancer susceptibility, while the rs34787247 polymorphism was associated with cancer susceptibility in the Chinese population [AA vs. GG: Odd Ratio (OR)=1.98, 95% Confidence Interval (CI)=1.35-2.89, PZ<0.001; GA vs. GG: OR = 1.17, 95%CI= 1.01-1.36, PZ=0.04; (AA + GA) vs. GG: OR = 1.24, 95%CI = 1.07-1.43, PZ=0.004; AA vs. (GA + GG): OR = 1.90, 95%CI = 1.30- 2.78, PZ=0.001; A vs. G: OR = 1.27, 95%CI = 1.12-1.44, PZ<0.001]. LIN28A gene expression was associated not only with immune infiltration, pathological stage, and survival prognosis of certain cancers, but also with sensitivity to multiple anticancer drugs, such as cisplatin, pazopanib, olaparib, and selumetinib. In conclusion, the current study suggested that the rs34787247 G > A polymorphism might be used as a cancer risk marker in the Chinese population, and LIN28A might serve as a prognostic marker and therapeutic target for certain cancers.

Comprehensive pan-cancer analysis of ACSS3 as a biomarker for prognosis and immunotherapy response

Background

ACSS3 (acyl-CoA synthetase short-chain family member 3) is found in numerous tissues and is linked to tumor cell type development and metastasis.

Methods

We conducted a comprehensive pan-cancer analysis of ACSS3. The TCGA (Cancer Genome Atlas), CPTAC (Clinical Proteomic Tumor Analysis Consortium), and HPA databases were used to ascertain the connection between ACSS3 and various types of tumors. Genes in the TCGA database would be identified using cBioPortal queries, and their transcriptome expression would then be verified using GEO data. ACSS3 expression and cellular localization in various tumor tissues of most cancer types were analyzed using single-cell sequencing data from the TISCH database. According to HPA and CPTAC databases, we analyzed and evaluated protein expression levels. Predictive analysis based on precise survival data of ACSS3 expression levels for 26 cancer types predicted using the TCGA database. Furthermore, we investigated the relationship between ACSS3 and immune microenvironments in different tumor tissues using the TIMER and TISCH databases. CellMiner, GDSC, and CTRP data would clarify the relationship between ACSS3 and drug resistance and explore the chemicals that affect ACSS3 expression. The final part of our study explored and validated the role ACSS3 played in glioma proliferation, migration, and invasion.

Results

ACSS3 is differentially expressed in various tumors and exhibits early diagnostic value. ACSS3 expression is associated with clinical features, and high ACSS expression anticipates a worse prognosis in multiple tumors and may impact drug sensitivity. The changes in the immunosuppressive microenvironment of gliomas are closely related to the upregulation of ACSS3.

Conclusions

ACSS3 is a novel biomarker for forecasting different human cancer prognoses, as it can influence the biological process by modulating the immune microenvironment. ACSS3 is a critical prognostic factor for glioma and is related to its proliferation, migration, and invasion.

A comprehensive pan-cancer analysis revealing the role of ITPRIPL1 as a prognostic and immunological biomarker

Inositol 1,4,5-Trisphosphate Receptor-Interacting Protein-Like 1 (ITPRIPL1), a single-pass type I membrane protein located in the membrane, functions as an inhibitory ligand of CD3ε. Recent studies have shown that its expression suppresses T cells activation and promote tumor immune evasion. Despite increasing evidence suggesting that ITPRIPL1 plays a significant role in tumor growth, no systematic pan-cancer analysis of ITPRIPL1 has been conducted to date. This study utilized datasets curated from The Cancer Genome Atlas, Genotype Tissue-Expression, and Human Protein Atlas to investigate the relationship between ITPRIPL1 expression and clinical outcomes, immune infiltration, and drug sensitivity across 33 cancer types. We employed multiple methods to assess its prognostic value in pan-cancer, such as univariate Cox regression, survival analysis, and ROC curve analysis and explored the relationship between ITPRIPL1 and tumor mutation burden (TMB), tumor microsatellite instability (MSI), CNV, DNA methylation, immune-related genes, immune cell infiltration, and drug sensitivity to reveal its immunological role. The mRNA expression levels of the ITPRIPL1 gene vary significantly across multiple types of cancer and significantly reduced in breast cancer. Conversely, high ITPRIPL1 expression was associated with a better prognosis in BRCA. Furthermore, the expression of ITPRIPL1 highly correlates with the presence of tumor-infiltrating immune cells and immune checkpoint genes across various types of cancers. Additionally, ITPRIPL1 expression was associated with TMB in 6 cancer types and with MSI in 13 cancer types. High expression of ITPRIPL1 serves as a protective factor in certain cancer types, correlating with longer overall survival in BRCA. Our study further confirms that ITPRIPL1 participates in regulating immune infiltration and affecting the prognosis of patients in pan-cancer. These findings underscore the promising potential of ITPRIPL1 as a therapeutic target for human cancer.

Frequent gene mutations and the correlations with clinicopathological features in clear cell renal cell carcinoma: preliminary study based on Chinese population and TCGA database

BACKGROUND

Large-scale sequencing plays important roles in revealing the genomic map of ccRCC and predicting prognosis and therapeutic response to targeted drugs. However, the relevant clinical data is still sparse in Chinese population.

METHODS

Fresh tumor specimens were collected from 66 Chinese ccRCC patients, then the genomic RNAs were subjected to whole transcriptome sequencing (WTS). We comprehensively analyzed the frequently mutated genes from our hospital's cohort as well as TCGA-KIRC cohort.

RESULTS

VHL gene is the most frequently mutated gene in ccRCC. In our cohort, BAP1 and PTEN are significantly associated with a higher tumor grade and DNM2 is significantly associated with a lower tumor grade. The mutant type (MT) groups of BAP1 or PTEN, BAP1 or SETD2, BAP1 or TP53, BAP1 or MTOR, BAP1 or FAT1 and BAP1 or AR had a significantly correlation with higher tumor grade in our cohort. Moreover, we identified HMCN1 was a hub mutant gene which was closely related to worse prognosis and may enhance anti-tumor immune responses.

CONCLUSIONS

In this preliminary research, we comprehensively analyzed the frequently mutated genes in the Chinese population and TCGA database, which may bring new insights to the diagnosis and medical treatment of ccRCC.

Dachsous cadherin related 1 (DCHS1) is a novel biomarker for immune infiltration and epithelial-mesenchymal transition in endometrial cancer via pan-cancer analysis

BACKGROUND

Dachsous cadherin related 1 (DCHS1) is one of calcium-dependent adhesion membrane proteins and is mainly involved in the development of mammalian tissues. There is a lack of more detailed research on the biological function of DCHS1 in pan-cancer.

MATERIALS AND METHODS

We evaluated the expression, the prognostic value, the diagnostic value and genomic alterations of DCHS1 by using the databases, including TCGA, UALCAN, HPA, GEPIA2.0 and GSCA. We employed the databases of UCSC, TIMER2.0, TISIDB, GSCA to analyze the association between DCHS1 expression and the immune microenvironment, stemness, TMB, MSI and anticancer drug sensitivity. BioGRID, STRING and GEPIA2.0 were used to perform protein interaction and functional enrichment analysis. Real-time quantitative PCR, CCK8, Transwell assay and Western blot were performed to determine the function of DCHS1 in UCEC.

RESULTS

DCHS1 is differentially expressed in many cancers and its expression is significantly associated with tumor prognosis and diagnosis. DCHS1 expression was significantly correlated with the infiltration of cancer-associated fibroblasts (CAFs), Endothelial cell (ECs), and Hematopoietic stem cell in most cancers. In addition, DCHS1 was significantly associated with sensitivity to many antitumor drugs. Functional enrichment analysis revealed that DCHS1-related proteins were involved in Focal adhesion, Endometrial cancer and Wnt signaling pathway. GSEA results showed that DCHS1 was related to epithelial-mesenchymal transition (EMT) in many cancers. In vitro experiments in UCEC showed that DCHS1 regulated cell proliferation, migration and EMT.

CONCLUSIONS

Our findings indicated that DCHS1 might be a novel prognostic and diagnostic biomarker and immunotherapy target, and plays an important role in the proliferation, migration and EMT in UCEC.

Pan-cancer analysis and single-cell analysis reveals FAM110B as a potential target for survival and immunotherapy

Background: FAM110B belongs to the family that has a 110 sequence similarity (FAM110) and is located in the centrosome and mitotic spindle. FAM110B has been linked to tumor cell growth in earlier research. Uncertainty exists regarding FAM110B's function within the tumor microenvironment is unclear as well as pan-cancer. Methods: In order to assess the variation in FAM110B expression within normal and pan-cancer tissues, we combined the TCGA and GTEx databases. The cBioPortal database and the GSCALite platform were used to examine the variation in genome and methylation alteration of FAM110B. Cox regression, Kaplan-Meier, and SangerBox were employed to examine the clinical features and prognosis of FAM110B and pan-cancer. The purpose of the correlational research was to investigate the associations within immunerelated genes, tumor mutation burden, microsatellite instability, immune-related genes, and immunological checkpoints and FAM110B expression. ESTIMATE, EPIC, QUANTISEQ, and MCPCOUNTER methods were used to calculate the interaction among FAM110B expression as well as the tumor immune microenvironment. The immunoinfiltration and function of FAM110B were analyzed by single-cell databases (TISCH and CancerSEA). Finally, we evaluated the sensitivity of FAM110B to small-molecule medications through GDSC and CTRP databases. Results: The transcription and protein expression of FAM110B varies significantly throughout cancer types, and this has predictive value for the prognosis of some tumors; including brain lower grade glioma (LGG), stomach adenocarcinoma (STAD), pancreatic adenocarcinoma (PAAD), etc. In the tumor microenvironment, the expression level of FAM110B was associated with immune cell infiltration, immune checkpoint immune regulatory genes, tumor mutational burden, and microsatellite fragility to a certain extent. Conclusion: This work investigates the possibility of utility of FAM110B as a marker to forecast pan-cancer immunotherapy response, providing a theoretical basis for cancer therapy.

Identifying and validating the roles of the cuproptosis-related gene DKC1 in cancer with a focus on esophageal carcinoma

BACKGROUND

Esophageal cancer is a common malignancy of the digestive tract. Despite remarkable advancements in its treatment, the overall prognosis for patients remains poor. Cuproptosis is a form of programmed cell death that affects the malignant progression of tumors. This study aimed to examine the impact of the cuproptosis-associated gene DKC1 on the malignant progression of esophageal cancer.

METHODS

Clinical and RNA sequencing data of patients with esophageal cancer were extracted from The Cancer Genome Atlas (TCGA). Univariate Cox regression analysis was used to identify the differentially expressed genes related to cuproptosis that are associated with prognosis. We then validated the difference in the expression of DKC1 between tumor and normal tissues via three-dimensional multiomics difference analysis. Subsequently, we investigated the association between DKC1 expression and the tumor microenvironment by employing the TIMER2.0 algorithm, which was further validated in 96 single-cell datasets obtained from the TISCH database. Additionally, the functional role of DKC1 in pancarcinoma was assessed through GSEA. Furthermore, a comprehensive pancancer survival map was constructed, and the expression of DKC1 was verified in various molecular subtypes. By utilizing the CellMiner, GDSC, and CTRP databases, we successfully established a connection between DKC1 and drug sensitivity. Finally, the involvement of DKC1 in the progression of esophageal cancer was investigated through in vivo and in vitro experiments.

RESULTS

In this study, we identified a copper death-related gene, DKC1, in esophageal cancer. Furthermore, we observed varying levels of DKC1 expression across different tumor types. Additionally, we conducted an analysis to determine the correlation between DKC1 expression and clinical features, revealing its association with common cell cycle pathways and multiple metabolic pathways. Notably, high DKC1 expression was found to indicate poor prognosis in patients with various tumors and to influence drug sensitivity. Moreover, our investigation revealed significant associations between DKC1 expression and the expression of molecules involved in immune regulation and infiltration of lymphocyte subtypes. Ultimately, the increased expression of DKC1 in esophageal cancer tissues was verified using clinical tissue samples. Furthermore, DKC1-mediated promotion of esophageal cancer cell proliferation and migration was confirmed through both in vitro and in vivo experiments. Additionally, it is plausible that DKC1 may play a role in the regulation of cuproptosis.

CONCLUSION

In this study, we conducted a systematic analysis of DKC1 and its regulatory factors and experimentally validated its excellent diagnostic and prognostic abilities in various cancers. Further research indicated that DKC1 may reshape the tumor microenvironment (TME), highlighting the potential of DKC1-based cancer treatment and its usefulness in predicting the response to chemotherapy.

XRCC2 driven homologous recombination subtypes and therapeutic targeting in lung adenocarcinoma metastasis

Lung adenocarcinoma (LUAD) is a leading cause of cancer mortality, with many patients facing poor prognosis, particularly those with metastatic or drug-resistant tumors. Homologous recombination genes (HRGs) are crucial in tumor progression and therapy resistance, but their clinical significance in LUAD is not well understood. In this study, we systematically characterize key HRGs in LUAD patients, identifying two distinct HR subtypes associated with different outcomes and biological functions. We establish a 5-gene scoring system (XRCC2, RAD51, BRCA1, FANCA, and CHEK1) that reliably predicts patient outcomes and immunotherapy responses in LUAD. Bioinformatics analysis and clinical validation highlight XRCC2 as a crucial biomarker in LUAD. Functional investigations through in vivo and in vitro experiments reveal the role of XRCC2 in promoting lung cancer migration and invasion. Mechanistically, XRCC2 stabilizes vimentin (VIM) protein expression through deubiquitylation. We predict c-MYC as a potential regulator of XRCC2 and demonstrate that inhibiting c-MYC with compound 10058-F4 reduces XRCC2 and VIM expression. Preclinical studies show the synergistic inhibition of metastasis in vivo when combining 10058-F4 with doxorubicin (Dox). Our findings present a potential personalized predictive tool for LUAD prognosis, identifying XRCC2 as a critical biomarker. The c-Myc-XRCC2-VIM axis emerges as a promising therapeutic target for overcoming lung metastasis. This study provides valuable insights into LUAD, proposing a prognostic tool for further clinical validation and unveiling a potential therapeutic strategy for combating lung metastasis by targeting c-Myc-XRCC2-VIM.

Neuromedin U receptor 1 deletion leads to impaired immunotherapy response and high malignancy in colorectal cancer

Colorectal cancer (CRC) exhibits significant heterogeneity, impacting immunotherapy efficacy, particularly in immune desert subtypes. Neuromedin U receptor 1 (NMUR1) has been reported to perform a vital function in immunity and inflammation. Through comprehensive multi-omics analyses, we have systematically characterized NMUR1 across various tumors, assessing expression patterns, genetic alterations, prognostic significance, immune infiltration, and pathway associations at both the bulk sequencing and single-cell scales. Our findings demonstrate a positive correlation between NMUR1 and CD8+ T cell infiltration, with elevated NMUR1 levels in CD8+ T cells linked to improved immunotherapy outcomes in patients with CRC. Further, we have validated the NMUR1 expression signature in CRC cell lines and patient-derived tissues, revealing its interaction with key immune checkpoints, including lymphocyte activation gene 3 and cytotoxic T-lymphocyte-associated protein 4. Additionally, NMUR1 suppression enhances CRC cell proliferation and invasiveness. Our integrated analyses and experiments open new avenues for personalized immunotherapy strategies in CRC treatment.

A Multi-Omics Analysis of an Exhausted T Cells' Molecular Signature in Pan-Cancer

T cells are essential tumor suppressors in cancer immunology, but their dysfunction induced by cancer cells can result in T cell exhaustion. Exhausted T cells (Tex) significantly influence the tumor immune environment, and thus, there is a need for their thorough investigation across different types of cancer. Here, we address the role of Tex cells in pan-cancer, focusing on the expression, mutations, methylation, immune infiltration, and drug sensitivity of a molecular signature comprising of the genes HAVCR2, CXCL13, LAG3, LAYN, TIGIT, and PDCD1across multiple cancer types, using bioinformatics analysis of TCGA data. Our analysis revealed that the Tex signature genes are differentially expressed across 14 cancer types, being correlated with patient survival outcomes, with distinct survival trends. Pathway analysis indicated that the Tex genes influence key cancer-related pathways, such as apoptosis, EMT, and DNA damage pathways. Immune infiltration analysis highlighted a positive correlation between Tex gene expression and immune cell infiltration in bladder cancer, while mutations in these genes were associated with specific immune cell enrichments in UCEC and SKCM. CNVs in Tex genes were widespread across cancers. We also highlight high LAYN methylation in most tumors and a negative correlation between methylation levels and immune cell infiltration in various cancers. Drug sensitivity analysis identified numerous correlations, with CXCL13 and HAVCR2 expressions influencing sensitivity to several drugs, including Apitolisib, Belinostat, and Docetaxel. Overall, these findings highlight the importance of reviving exhausted T cells to enhance the treatment efficacy to significantly boost anti-tumor immunity and achieve better clinical outcomes.

Construction and assessment of an angiogenesis-related gene signature for prognosis of head and neck squamous cell carcinoma

OBJECTIVE

Angiogenesis-associated genes (AAGs) play a critical role in cancer patient survival. However, there are insufficient reports on the prognostic value of AAGs in head and neck squamous cell carcinoma (HNSC). Therefore, this study aimed to investigate the correlation between AAG expression levels and survival in HNSC patients, explore the predictive value of signature genes and lay the groundwork for future in-depth research.

METHODS

Relevant data for HNSC were obtained from the databases. AAGs-associated signature genes linked to prognosis were screened to construct a predictive model. Further analysis was conducted to determine the functional correlation of the signature genes.

RESULTS

The signature genes (STC1, SERPINA5, APP, OLR1, and PDGFA) were used to construct prognostic models. Patients were divided into high-risk and low-risk groups based on the calculated risk scores. Survival analysis showed that patients in the high-risk group had a significantly lower overall survival than those in the low-risk group (P < 0.05). Therefore, this prognostic model was an independent prognostic factor for predicting HNSC. In addition, patients in the low-risk group were more sensitive to multiple anti-cancer drugs. Functional correlation analysis showed a good correlation between the characteristic genes and HNSC metastasis, invasion, and angiogenesis.

CONCLUSION

This study established a new prognostic model for AAGs and may guide the selection of therapeutic agents for HNSC. These genes have important functions in the tumor microenvironment; it also provides a valuable resource for the future clinical trials investigating the relationship between HNSC and AAGs.

Immune infiltration-related genes regulate the progression of AML by invading the bone marrow microenvironment

In this study, we try to find the pathogenic role of immune-related genes in the bone marrow microenvironment of AML. Through WGCNA, seven modules were obtained, among which the turquoise module containing 1793 genes was highly correlated with the immune infiltration score. By unsupervised clustering, the turquoise module was divided into two clusters: the intersection of clinically significant genes in the TCGA and DEGs to obtain 178 genes for mutation analysis, followed by obtaining 17 genes with high mutation frequency. Subsequently, these 17 genes were subjected to LASSO regression analysis to construct a riskscore model of 8 hub genes. The TIMER database, ImmuCellAI portal website, and ssGSEA elucidate that the hub genes and risk scores are closely related to immune cell infiltration into the bone marrow microenvironment. In addition, we also validated the relative expression levels of hub genes using the TCGA database and GSE114868, and additional expression levels of hub genes in AML cell lines in vitro. Therefore, we constructed an immune infiltration-related gene model that identify 8 hub genes with good risk stratification and predictive prognosis for AML.

An immune biomarker associated with EMT serves as a predictor for prognosis and drug response in bladder cancer

BACKGROUND

Bladder cancer (BLCA), which develops from the upper endometrial of the bladder, is the sixth most prevalent cancer across the globe. WDHD1 (WD repeat and HMG-box DNA binding protein 1 gene) directly affects signaling, the cell cycle, and the development of the cell skeleton. Uncertainty surrounds WDHD1's function in BLCA immunity and prognosis, though.

MATERIALS AND METHODS

Using weighed gene co-expression network analysis (WGCNA), initially, we first identified 32 risk factors in genes with differential expression for this investigation. Then, using a variety of bioinformatic techniques and experimental validation, we examined the connections between WDHD1 and BLCA expression, clinical pathological traits, WDHD1-related proteins, upper-skin-intermediate conversion (EMT), immune cell immersion, convergence factors, immune markers, and drug sensitivity.

RESULT

The findings demonstrated that we constructed a 32-gene risk-predicting model where WDHD1 was elevated as a representative gene expression in BLCA and related to a range of clinical traits. Furthermore, high WDHD1 expression was a standalone predictor associated with a worse survival rate. The most commonly recruited cells and their evolutionary patterns were highlighted to better comprehend WDHD1's function in cancer. High WDHD1 expression was associated with many aspects of immunology. Finally, the study found that individuals with high expression of WDHD1 were drug-sensitive to four different broad-spectrum anti-cancer drugs.

CONCLUSION

These results describe dynamic changes in the tumor microenvironment in BLCA and provide evidence for the hypothesis that WDHD1 is a novel biomarker of tumor development. WDHD1 may therefore be a useful target for the detection and management of BLCA.

WNT5A in Cancer: A Pan-Cancer Analysis Revealing Its Diagnostic and Prognostic Biomarker Potential

BACKGROUND AND OBJECTIVE

The wingless-related integration site family (WNT) signaling pathway is critical for tumor progression and development. It is associated with various neoplasms produced by WNT pathway deregulation; WNT5A, a member of the WNT family, has been linked to carcinogenesis, exhibiting either oncogenic or tumor-suppressive effects. The study investigates how the gene affects certain types of cancer. The study aimed to evaluate the potential prognostic significance of WNT5A genes as diagnostic biomarkers for various types of cancer.

METHODOLOGY

We investigated WNT5A gene expression in a pan-cancer analysis using various bioinformatics databases, including GEPIA (Gene Expression Profiling Interactive Analysis), TIMER2 (Tumor Immune Estimation Resource, Version 2), the University of Alabama at Birmingham Cancer Data Analysis Portal UACLAN databases, the Kaplan-Meier (K-M) plotter, cBioPortal, and Gene Set Cancer Analysis (GSCA). We aimed to gain insight into the expression of WNT5A in various tumors and its relationship with immune infiltration, overall survival, and genetic changes. Public datasets validated WNT5A expression in lung squamous cell carcinoma (LUSC) and stomach adenocarcinoma (STAD) samples.

RESULTS

WNT5A pan-cancer analysis was highly expressed in two cancer types, including STAD and LUSC. Additionally, TIMER results showed a positive association of WNT5A with immune cell infiltration in LUSC and STAD. Survival analysis indicated that LUSC cancer exhibits better overall survival, while STAD has lower overall survival levels, which means a poor prognosis in the STAD cancer type. Furthermore, mutation analysis revealed that the WNT5A gene was mutated in 1.4% of cases, with most alterations being deletions followed by amplifications.

CONCLUSIONS

The WNT5A gene's high expression in many malignancies, including LUSC and STAD, suggests it could be used as a diagnostic biomarker. This study shows a relationship between WNT5A expression and immune cell abundance in LUSC and STAD. Our pan-cancer analysis of this gene is the first of its type, and it will inform future research, comprehensive investigation, and wet lab experiments.

Mitotic catastrophe heterogeneity: implications for prognosis and immunotherapy in hepatocellular carcinoma

Background and aims

The mitotic catastrophe (MC) pathway plays an important role in hepatocellular carcinoma (HCC) progression and tumor microenvironment (TME) regulation. However, the mechanisms linking MC heterogeneity to immune evasion and treatment response remain unclear.

Methods

Based on 94 previously published highly correlated genes for MC, HCC patients' data from the Cancer Genome Atlas (TCGA) and changes in immune signatures and prognostic stratification were studied. Time and spatial-specific differences for MCGs were assessed by single-cell RNA sequencing and spatial transcriptome (ST) analysis. Multiple external databases (GEO, ICGC) were employed to construct an MC-related riskscore model.

Results

Identification of two MC-related subtypes in HCC patients from TCGA, with clear differences in immune signatures and prognostic risk stratification. Spatial mapping further associates low MC tumor regions with significant immune escape-related signaling. Nomogram combining MC riskscore and traditional indicators was validated great effect for early prediction of HCC patient outcomes.

Conclusion

MC heterogeneity enables immune escape and therapy resistance in HCC. The MC gene signature serves as a reliable prognostic indicator for liver cancer. By revealing clear immune and spatial heterogeneity of HCC, our integrated approach provides contextual therapeutic strategies for optimal clinical decision-making.

CCND1 as a Prognostic and Diagnostic Biomarker and the Impact of Its Epigenetic Alterations on Cancer Survival

BACKGROUND

Cyclin D1 (CCND1) plays a crucial role in cell cycle regulation and has been implicated in various cancers. As is well known, cancer is caused by the accumulation of detrimental variations in the genome. In this study, we shed light on the role of CCND1 in the diagnosis and progression of cancer and aimed to provide a comprehensive analysis of CCND1 across multiple cancer types, focusing on its expression, clinical correlations, DNA methylation status, prognostic implications, genetic alterations, and immune infiltration.

METHODS

Gene expression analysis of CCND1 was conducted across 33 cancer types using the TIMER, GEPIA, and UALCAN databases. Clinical parameters were investigated to assess their correlations with CCND1 expression. Methylation analysis was performed using the UALCAN and GSCA databases to investigate the relationship between CCND1 promoter methylation and gene expression and their association with survival. Immune infiltration and survival analyses were performed to explore the prognostic implications of CCND1 expression in various cancers. Statistical tests, such as the Cox proportional hazards model and the Kaplan-Meier analysis, were used to assess survival outcomes. Additionally, genetic alteration analysis was performed using the cBioPortal database to examine the prevalence and types of CCND1 alterations across different cancer types.

RESULTS

CCND1 expression was significantly elevated in 13 cancers compared to normal tissues, with distinct patterns observed across different cancer types. It is highly expressed in BLCA, CHOL, COAD, ESCA, GBM, HNSC, KIRC, PAAD, RRAD, READ, STAD, THCA, and UCEC. The investigation of clinical parameters revealed associations between CCND1 expression and factors such as age, gender, race, and cancer stage. The methylation analysis highlighted hypomethylation of CCND1 across the 13 selected cancer types. The survival analysis identified both favorable and unfavorable prognostic implications of CCND1 expression in different cancers and revealed that a high expression of CCND1 was associated with a poor prognosis in HNSC and PAAD, while a high expression of CCND1 was associated with a good prognosis in KIRC, STAD, THCA, and UCEC. In the immune infiltration analysis of various cancers, many statistically significant correlations were observed between the immune cell types and tumor purity. For example, in BLCA, neutrophils and dendritic cells showed statistically significant positive correlations and a negative correlation with macrophages. While in CHOL patients, none of the immune cell types showed a significant correlation. Similar statistical significance was observed in other cancer types, such as COAD, HNSC, GBM, KIRC, PAAD, PRAD, READ, and STAD, with different immune cell types. The genetic alteration analysis revealed that amplification was the predominant genetic alteration type in CCND1, with specific patterns observed in different cancer types.

CONCLUSION

The findings of this study provide valuable insights into the role of CCND1 in cancer diagnosis and progression, and its potential for targeted therapies. CCND1 could be used as a potential diagnostic biomarker for the COAD, ESCA, KIRC, READ, STAD, and THCA stages. Furthermore, CCND1 could be used as a potential prognostic biomarker for HNSC, KIRC, and PAAD. Also, the correlation between CCND1 methylation and expression could be used as a potential diagnostic and prognostic biomarker for ESCA, HNSC, and STAD.

Metabolic Recoding of NSUN2-Mediated m5C Modification Promotes the Progression of Colorectal Cancer via the NSUN2/YBX1/m5C-ENO1 Positive Feedback Loop

The RNA modification, 5-methylcytosine (m5C), has recently gained prominence as a pivotal post-transcriptional regulator of gene expression, intricately intertwined with various tumorigenic processes. However, the exact mechanisms governing m5C modifications during the onset and progression of colorectal cancer (CRC) remain unclear. Here, it is determined that the m5C methyltransferase NSUN2 exhibits significantly elevated expression and exerts an oncogenic function in CRC. Mechanistically, NSUN2 and YBX1 are identified as the "writer" and "reader" of ENO1, culminating in the reprogramming of the glucose metabolism and increased production of lactic acid in an m5C-dependent manner. The accumulation of lactic acid derived from CRC cells, in turn, activates the transcription of NSUN2 through histone H3K18 lactylation (H3K18la), and induces the lactylation of NSUN2 at the Lys356 residue (K356), which is crucial for capturing target RNAs. Together, these findings reveal an intriguing positive feedback loop involving the NSUN2/YBX1/m5C-ENO1 signaling axis, thereby bridging the connection between metabolic reprogramming and epigenetic remodeling, which may shed light on the therapeutic potential of combining an NSUN2 inhibitor with immunotherapy for CRC.

Construction of an immune-related prognostic signature and lncRNA-miRNA-mRNA ceRNA network in acute myeloid leukemia

The progression of acute myeloid leukemia (AML) is influenced by the immune microenvironment in the bone marrow and dysregulated intracellular competing endogenous RNA (ceRNA) networks. Our study utilized data from UCSC Xena, The Cancer Genome Atlas Program, the Gene Expression Omnibus, and the Immunology Database and Analysis Portal. Using Cox regression analysis, we identified an immune-related prognostic signature. Genomic analysis of prognostic messenger RNA (mRNA) was conducted through Gene Set Cancer Analysis (GSCA), and a prognostic ceRNA network was constructed using the Encyclopedia of RNA Interactomes. Correlations between signature mRNAs and immune cell infiltration, checkpoints, and drug sensitivity were assessed using R software, gene expression profiling interactive analysis (GEPIA), and CellMiner, respectively. Adhering to the ceRNA hypothesis, we established a potential long noncoding RNA (lncRNA)/microRNA (miRNA)/mRNA regulatory axis. Our findings pinpointed 9 immune-related prognostic mRNAs (KIR2DL1, CSRP1, APOBEC3G, CKLF, PLXNC1, PNOC, ANGPT1, IL1R2, and IL3RA). GSCA analysis revealed the impact of copy number variations and methylation on AML. The ceRNA network comprised 14 prognostic differentially expressed lncRNAs (DE-lncRNAs), 6 prognostic DE-miRNAs, and 3 prognostic immune-related DE-mRNAs. Correlation analyses linked these mRNAs' expression to 22 immune cell types and 6 immune checkpoints, with potential sensitivity to 27 antitumor drugs. Finally, we identified a potential LINC00963/hsa-miR-431-5p/CSRP1 axis. This study offers innovative insights for AML diagnosis and treatment through a novel immune-related signature and ceRNA axis. Identified novel biomarkers, including 2 mRNAs (CKLF, PNOC), 1 miRNA (hsa-miR-323a-3p), and 10 lncRNAs (SNHG25, LINC01857, AL390728.6, AC127024.5, Z83843.1, AP002884.1, AC007038.1, AC112512, AC020659.1, AC005921.3) present promising candidates as potential targets for precision medicine, contributing to the ongoing advancements in the field.

The role of LOXL2 in tumor progression, immune response and cellular senescence: a comprehensive analysis

LOXL2, an enzyme belonging to the LOX family, facilitates the cross-linking of extracellular matrix (ECM) elements. However, the roles of the LOXL2 gene in mechanisms of oncogenesis and tumor development have not been clearly defined. In this pan-cancer study, we examined the notable disparity in LOXL2 expression at the mRNA and protein levels among various cancer types and elucidated its interconnected roles in tumor progression, mutational profile, immune response, and cellular senescence. Apart from investigating the hyperexpression of LOXL2 being related to poorer prognosis in different types of tumors, this study also unveiled noteworthy connections between LOXL2 and genetic mutations, infiltration of tumor immune cells, and genes in immune checkpoint pathways. Further analysis revealed the participation of LOXL2 in multiple pathways related to cancer extracellular matrix remodeling and cellular senescence. Moreover, our investigation uncovered that the knockdown and inhibition of LOXL2 significantly attenuated the proliferation and migration of PC-9 and HCC-LM3 cells. The knock-down and inhibition of LOXL2 enhanced cellular senescence in lung and liver cancer cells, as confirmed by SA-β-Gal staining and quantitative RT-PCR analyses. This comprehensive analysis offers valuable insights on the functions of LOXL2 in different types of cancer and its role in regulating the senescence of cancer cells.

Prognostic and therapeutic insights into colorectal carcinoma through immunogenic cell death gene profiling

While the significance of immunogenic cell death (ICD) in oncology is acknowledged, its specific impact on colorectal carcinoma remains underexplored. In this study, we delved into the role of ICD in colorectal carcinoma, a topic not yet comprehensively explored. A novel ICD quantification system was developed to forecast patient outcomes and the effectiveness of immunotherapy. Utilizing single-cell sequencing, we constructed an ICD score within the tumor immune microenvironment (TIME) and examined immunogenic cell death related genes (ICDRGs). Using data from TCGA and GEO, we discovered two separate molecular subcategories within 1,184 patients diagnosed with colon adenocarcinoma/rectum adenocarcinoma (COADREAD). The ICD score was established by principal component analysis (PCA), which classified patients into groups with low and high ICD scores. Further validation in three independent cohorts confirmed the model's accuracy in predicting immunotherapy success. Patients with higher ICD scores exhibited a "hot" immune phenotype and showed increased responsiveness to immunotherapy. Key genes in the model, such as AKAP12, CALB2, CYR61, and MEIS2, were found to enhance COADREAD cell proliferation, invasion, and PD-L1 expression. These insights offered a new avenue for anti-tumor strategies by targeting ICD, marking advances in colorectal carcinoma treatment.

Pan-cancer exploration of oncogenic and clinical impacts revealed that HOXA9 is a diagnostic indicator of tumorigenesis

Homeodomain transcription factor A9 (HOXA9) is a member of the HOX cluster family of transcription factors that are crucially involved in embryo implantation, morphogenesis, body axis development, and endothelial cell differentiation. Despite numerous reports on its aberrant expression in a few malignancies, the molecular and functional complexity of HOXA9 across cancers remains obscure. We aimed to analyze the dynamic role of HOXA9 across cancers by identifying, analyzing, and understanding its multiple modes of regulation and functional implications and identifying possible therapeutic avenues. We conducted a comprehensive analysis to determine the role of HOXA9 across cancers. This approach involved the integration of large-scale datasets from public repositories such as the Genomic Data Commons, specifically the Cancer Genome Atlas (GDC-TCGA), across 33 different cancer types. The multiple modes of HOXA9 regulation by genetic and epigenetic factors were determined using online tools, which comprised experimentally validated observations. Furthermore, downstream pathways were identified by predicting the targets of HOXA9 and by performing functional enrichment analysis. We also assessed the clinical significance of HOXA9 in terms of prognosis and stage stratification. This study evaluated the correlation between HOXA9 and tumor-infiltrating molecules and discussed its association with therapeutically approved antineoplastic drugs. HOXA9 was significantly upregulated in 9 tumors and downregulated in 2 cancers. The deregulation of HOXA9 is primarily attributed to epigenetic factors, including promoter DNA methylation and noncoding RNAs (ncRNAs). The HOXA9 transcription factor interacts with PBX/MEIS cofactors and regulates multiple genes involved in cancer-associated EMT, autophagy, the cell cycle, metabolic pathways, Wnt signaling, TGF-β signaling, the AMPK pathway, PI3K/AKT signaling, and NF-κB signaling, thereby establishing control over downstream mechanisms. Differential expression in various clinical stages across cancers was shown to have prognostic significance and to be correlated with tumor-infiltrating immune molecules. The assessment of the correlation of HOXA9 expression with approved antineoplastic drugs revealed that targeting HOXA9 could be the most reliable strategy for preventing cancer progression. HOXA9 is upregulated in the majority of malignancies and drives cancer progression by regulating multiple signaling mechanisms. Hence, HOXA9 could be a reliable diagnostic indicator and a potential therapeutic candidate for solid cancer types.

Pancancer Analysis of NSUN2 with a Focus on Prognostic and Immunological Roles in Endometrial Cancer

The significance of NSUN2 in carcinogenesis is gradually being recognized, yet a comprehensive analysis across pan-cancer remains a pivotal void in existing research. In our investigation, we capitalized on the UCSC Xena platform to evaluate NSUN2 expression levels and their prognostic implications across a range of cancer types. Furthermore, we employed the cBioPortal database to delve into the genomic variations of NSUN2 within human cancers. Our study encompassed the use of molecular docking, genomic tumor profiling, and an assessment of the gene's responsiveness to pharmacological treatments. Additionally, we utilized algorithmic techniques to measure the relationship between NSUN2 expression and key clinical biomarkers, such as microsatellite instability (MSI), tumor mutational burden (TMB), and immune cell infiltration. Our results have established a notable association between NSUN2 and endometrial cancer (UCEC), thereby confirming its clinical significance through an analysis of tumoral expression patterns, mutational spectra, methylation profiles, and drug sensitivity. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were crucial tools in elucidating the biological roles of NSUN2 in endometrial cancer. Consistently, elevated NSUN2 expression was associated with unfavorable clinical outcomes and was primarily observed in the context of genetic amplifications. Across 22 distinct tumor types, our analysis revealed a notable correlation between NSUN2 expression and various metrics related to immune cell infiltration, tumor stroma, and immune scores. Notably, higher levels of NSUN2 expression have been linked to a reduced response to certain chemotherapeutic agents, including PHA-793887. In UCEC, a positive correlation between NSUN2 methylation and gene expression hints at a potential epigenetic regulatory mechanism underlying cancer progression. Our study highlights the potential of NSUN2 as a key oncogene and its promising role as a therapeutic target as well as a prognostic biomarker for endometrial cancer. This underscores its potential importance in predicting responses to immunotherapy.