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A comprehensive survey of genetic variants in neuroblastoma.

BACKGROUND: Neuroblastoma (NB) is the most common extracranial solid tumor in children and is characterized by marked clinical and molecular heterogeneity. Genomic alterations play a critical role in NB pathogenesis; however, population-specific mutational features remain insufficiently characterized, particularly among Chinese patients. METHODS: Whole-exome sequencing (WES) was performed on tumor, para-tumor, and matched peripheral blood samples from nine pathologically confirmed Chinese patients with NB. Somatic variant profiles were compared with four publicly available NB datasets from cBioPortal, published in 2012, 2013, 2015, and 2023. Mutational patterns, recurrently altered genes, and Gene Ontology (GO) enrichment were analyzed using R version 4.3.2 and clusterProfiler version 4.10.0. RESULTS: A total of 77 missense variants were identified in our cohort. Single-nucleotide polymorphisms (SNPs) represented the predominant variant type, and C > T substitutions were the most frequent nucleotide change. MAP1A variants, comprising two missense variants in one patient, and RBM33 variants, comprising two distinct variants in two patients, were detected in our cohort and, to the best of our knowledge, have not been previously reported in NB, although their frequencies were low. No MYCN amplification or variants in ALK, ATRX, or DAXX were detected. Comparative analysis with the cBioPortal datasets revealed no somatic variants universally shared across all cohorts. In addition, high-risk patients exhibited distinct mutational patterns, with enrichment of the Gene Ontology term "collagen-containing extracellular matrix." CONCLUSIONS: These findings highlight the molecular diversity of NB and suggest the presence of potential population-specific genetic features in Chinese patients. The low-frequency MAP1A and RBM33 variants identified in this cohort warrant further validation in larger, independent cohorts. Moreover, the enrichment of extracellular matrix-related pathways in high-risk NB supports further investigation of tumor-microenvironment interactions as potential therapeutic targets.

Extracellular matrix

Integrative Pan-Cancer Characterization of lncRNA UPK1A-AS1 and Its Role in Hypoxia-Associated Sorafenib Resistance in Hepatocellular Carcinoma.

Long noncoding RNAs (lncRNAs) are emerging as critical regulators of tumor initiation and progression through transcriptional and posttranscriptional mechanisms. UPK1A antisense RNA 1 (UPK1A-AS1), a cancer-associated lncRNA, has been reported to participate in oncogenic processes; however, its overall landscape across human malignancies and its biological role in therapy resistance remain poorly understood. Given the increasing importance of identifying functional lncRNAs with prognostic and therapeutic potential, this study presents a comprehensive multiomics characterization of UPK1A-AS1 and its experimental validation in hepatocellular carcinoma (HCC). We integrated datasets from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression Project (GTEx), the cancer immunology data engine (CIDE), and the cBioPortal for cancer genomics (cBioPortal) to systematically assess its expression pattern, genomic alterations, clinical significance, and immunological associations. Our analyses revealed that UPK1A-AS1 is significantly upregulated in multiple tumor types, with copy-number amplification as the predominant genomic alteration driving its overexpression. Elevated UPK1A-AS1 expression was correlated with advanced disease stage, poor differentiation, immune exclusion, and unfavorable prognosis, supporting its potential as a cancer type-dependent biomarker. In parallel, functional studies demonstrated that hypoxia transcriptionally induces UPK1A-AS1 in HCC, where it promotes sorafenib resistance by suppressing apoptosis. Silencing UPK1A-AS1 restored apoptotic and enhanced sorafenib efficacy both in vitro and in vivo. Collectively, our findings suggest that UPK1A-AS1 is a hypoxia-inducible oncogenic lncRNA that plays dual roles in cancer, with cancer type-dependent associations with progression and immune modulation across malignancies and mechanistically mediating hypoxia-associated drug resistance in HCC.

Humans

Distinct mutational landscapes for germline and somatic cancer variants in forty tumor suppressor genes.

Germline and somatic cancer variants in tumor suppressor genes (TSGs) share loss-of-function mechanisms, but studies of a few genes (DICER1 and CEBPA) have demonstrated differences in variant consequence and location. To systematically assess whether TSGs display distinct mutational patterns, we leveraged large public genetic databases and compared 32,941 high-quality pathogenic/likely pathogenic (P/LP) germline variants in ClinVar, with 12,907 oncogenic/likely oncogenic (O/LO) somatic tumor variants from cBioPortal across 40 TSGs. Only 3,863 (9.2%) variants were shared. Eighteen TSGs showed significantly different distributions of variant occurrences by molecular consequence, replicated with non-overlapping somatic data from the COSMIC database (chi-squared tests, false discovery rate = 5%). DICER1, TP53, and SMAD4 displayed excess somatic missense events, while nine TSGs (e.g., RB1 and APC) contained excess somatic stop-gain events throughout the coding sequence. Analysis by tumor type revealed excess stop-gain events in tissues exposed to environmental mutagens with corresponding mutation signatures. For several TSGs (WT1), germline variants predispose to tumors (Wilms' tumor) distinct from the majority source of somatic data (myeloid leukemia). Germline and somatic events are also distributed unevenly across cDNA locations, with 103 regions of preferential clustering in 39 TSGs (78 somatic and 25 germline). Twenty somatic clusters contained recurring frameshifts in homopolymer runs, many in tumors with microsatellite instability. Germline clusters contain more germline-exclusive variants, some driving non-cancer phenotypes reflecting genetic pleiotropy. Altogether, germline and somatic variants of TSGs represent unique sets with substantially different patterns shaped by selection pressures from gene-specific and somatic mutational mechanisms. Characterizing these distinctions enables more accurate clinical interpretation of TSG variants.

Humans

Comprehensive In Silico Analysis Identifies MSTO1 and LIG1 as Candidate Biomarkers With Diagnostic and Prognostic Relevance in Hepatocellular Carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and remains a major cause of cancer-related mortality worldwide. Its poor clinical outcomes are largely attributed to late-stage diagnosis and the limited accuracy of currently available diagnostic and prognostic biomarkers. Therefore, identifying novel molecular markers with improved sensitivity, specificity, and therapeutic relevance is essential for enhancing early detection and guiding personalized treatment strategies. AIMS: To identify and prioritize novel candidate HCC biomarkers with diagnostic and prognostic value and potential therapeutic vulnerability using integrated multi-omics, survival, functional dependency, and tumor microenvironment analyses. METHODS AND RESULTS: We examined the mRNA and protein expression levels of 8 DEGs in HCC tissues in the TCGA and CPTAC datasets using UALCAN, which showed that MSTO1 and LIG1 were overexpressed consistently in HCC relative to normal liver tissues. Moreover, elevated expression levels of these genes were significantly associated with higher tumor grade and advanced stage. Kaplan-Meier plotter survival data confirmed that increased expression of MSTO1 and LIG1 was associated with poorer overall survival. The DepMap CRISPR knockout data confirmed a functional dependency of both genes in HCC cell lines. CBioPortal analyses provided characterization of genomic alterations and enabled enrichment analysis of co-expressed genes, and the TCGA-UALCAN pan-cancer analyses supported the assessment of tissue specificity across tumor types. TIMER3 analyses linked candidate gene expression with immune cell infiltration patterns. Diagnostic performance by ROC analysis showed excellent discrimination for MSTO1 (AUC = 0.987) and good discrimination for LIG1 (AUC = 0.897). Multivariate Cox regression with Benjamini-Hochberg FDR correction across the eight genes supported MSTO1 as a candidate independent prognostic factor after adjustment for tumor stage, grade, etiology, age, and sex (HR = 1.29, p = 0.035), whilst LIG1 showed no independent prognostic value. Promoter methylation of MSTO1 and ADH4, assessed via UALCAN, showed that both genes were significantly differentially methylated in the promoter region of primary HCC tissues compared with normal liver tissues. Our study also confirmed the biological and clinical relevance of established HCC biomarkers: TERT, IRAK1, and ADH4. CONCLUSION: MSTO1 and LIG1 emerged as candidate diagnostic biomarkers in HCC. Additionally, MSTO1 showed a candidate prognostic association with overall survival that remained significant after adjusting for tumor stage, grade, and etiology, as well as patients' age, but not after further adjustment for AFP status. Functional data also highlighted MSTO1 as a candidate therapeutic dependency. On the other hand, LIG1 showed no independent prognostic association in either multivariate model. Their differential expression and functional essentiality in HCC cell lines highlighted their value for further experimental and independent-cohort validation before potential integration into biomarker development pipelines aimed at improving early detection and targeted therapy in HCC.

Humans

Oncogenic EME1 promotes tumor progression and immune modulation in human cancers with therapeutic targeting potential.

BACKGROUND: EME1, a critical DNA repair endonuclease, has emerged as a potential oncogene implicated in genome instability and cancer progression. However, its pan-cancer roles, prognostic significance, immune interactions, and therapeutic targeting remain underexplored. METHODS: We conducted a comprehensive pan-cancer analysis integrating multi-omics data from public databases, including TIMER2.0, GEPIA2, TISIDB, and cBioPortal, to evaluate EME1 expression, genetic alterations, and their association with clinical outcomes, immune infiltration, and molecular pathways. Virtual screening of 3180 FDA-approved drugs and molecular dynamics (MD) simulations were employed to identify and validate potential EME1 inhibitors. RESULTS: EME1 was significantly overexpressed in various human cancers and positively associated with advanced tumor grade and stage. High EME1 expression and mutations were linked to poor overall and disease-free survival. Immunogenomic profiling revealed strong positive correlations between EME1 and myeloid-derived suppressor cells (MDSCs), alongside a negative association with endothelial cell function, suggesting immunosuppressive roles. Machine learning models based on EME1-associated genes demonstrated high predictive accuracy for liver hepatocellular carcinoma (AUC > 0.90). Virtual screening identified eight promising drug candidates, including Everolimus and Dioscin, with strong binding affinities. MD simulations confirmed the stability of these interactions, particularly for Dioscin. CONCLUSION: This study reveals the multifaceted oncogenic roles of EME1 in tumor progression, immune evasion, and prognosis. It proposes EME1 as a promising biomarker and therapeutic target across multiple cancer types. The identified drug candidates warrant further in vitro and in vivo validation for potential repurposing in EME1-targeted cancer therapy.

EME1

Genetic and clinical insights into the coexistence of multiple myeloma and diffuse large B cell lymphoma from a case report and systematic review with bioinformatics analysis.

BACKGROUND: Multiple myeloma (MM) and diffuse large B-cell lymphoma (DLBCL) are B-cell malignancies that rarely coexist in a single patient, presenting significant diagnostic and therapeutic challenges. While MM primarily involves clonal plasma cells, DLBCL is an aggressive lymphoid neoplasm. Investigating shared genetic mutations and understanding their clinical relevance in both cancers could provide novel insights into their pathogenesis and underlying molecular mechanisms, thereby informing future translational research. MATERIALS AND METHODS: A case report was conducted on a 52-year-old male who presented with abdominal pain and anemia. Imaging revealed lymphadenopathy, and biopsy confirmed high-grade DLBCL with concurrent bone marrow involvement suggestive of MM. Laboratory tests identified monoclonal IgM gammopathy, and the patient was treated with R-CHOP (Rituximab, Cyclophosphamide, Doxorubicin, Vincristine, and Prednisone) chemotherapy for DLBCL followed by autologous stem cell transplantation (ASCT) for MM relapse. A systematic review of the literature was performed using PubMed, Scopus, and Web of Science databases to identify cases of patients diagnosed with both MM and DLBCL. Data on patient demographics, clinical features, treatment regimens, and outcomes were extracted. Additionally, bioinformatics analysis was conducted using publicly available genomic data from cBioPortal and IntOGen to identify driver gene mutations in MM and DLBCL. Functional and pathway enrichment analysis was performed with KEGG and Gene Ontology (GO) databases. RESULTS: The case report highlighted a complex clinical course where the patient initially responded well to R-CHOP chemotherapy for DLBCL, achieving remission, but later relapsed with MM, treated with ASCT and lenalidomide. The systematic review revealed 14 eligible studies in which MM and DLBCL often occur in older patients, either simultaneously or sequentially, with variable treatment responses, including complete remission, partial remission, or relapse. The bioinformatics analysis identified several shared function and cancer-related pathways between two cancers including interleukin and cytokine-mediated signaling pathways, regulation of cell cycle, neurotrophin signaling pathway, FOXO signaling pathway, Epstein Barr virus infection, and viral carcinogenesis. CONCLUSION: This study provides valuable insights into the dual occurrence of MM and DLBCL, emphasizing the importance of tailored treatment approaches. The driver mutations identified highlight overlapping oncogenic pathways rather than implying a shared clonal origin, and may inform future studies exploring their biological and clinical implications. Further research into these shared molecular mechanisms could lead to more effective treatments for patients with coexisting MM and DLBCL.

Bioinformatics analysis

Age-stratified mutation patterns in early-onset colorectal cancer reveal distinct molecular features and therapeutic implications.

BACKGROUND: Colorectal cancer (CRC) is increasingly diagnosed in younger adults, with evidence that early-onset cases (age <50 years) differ in the spectrum of prevalent gene mutations compared with older individuals. To evaluate how these age-related differences may inform testing guidelines and therapeutic development, we examined mutation rates of the most prevalent gene mutations across four age-stratified cohorts. PATIENTS AND METHODS: Clinicogenomic data were obtained from Memorial Sloan Kettering Center for Harmonized Onco-genomic Research Dataset and China Pan-Cancer cohorts available in cBioPortal. A total of 6762 samples were analyzed. Mutation frequencies for a comprehensive panel of the 100 most prevalent CRC genes were compared across four age groups: 18-29 (n = 79), 30-39 (n = 402), 40-49 (n = 1064), and &#x2265;50 (n = 5217) using chi-square analysis. False discovery rate (FDR) correction for multiple comparisons was carried out using Benjamini-Hochberg procedure. RESULTS: Statistically significant variation in mutation frequency across age groups was seen in 22 key genes. APC mutations increased with age and were seen in 49.4% of patients in the 18-29 group, 69.7% in 30-39, 73.3% in 40-49, and 75.25% of patients &#x2265;50 (P < 0.001, FDR < 0.001). The oldest cohort was more than three times more likely to have an APC mutation than the youngest [odds ratio (OR) = 3.74, 95% confidence interval (CI) 2.44-5.74, P < 0.001]. In contrast, SMAD4 mutations were twice as common in the youngest age group at 31.6% compared with those over 40, with a prevalence of 17.29% in patients 40-49, and 18.84% in patients over 50 (OR = 2.03, 95% CI 1.26-3.27, P < 0.001, FDR < 0.001). POLE mutations peaked in the 30-39 age group with a prevalence of 10.7% compared with 6.3% in patients aged 18-29, 4.9% in patients aged 40-49, and 5.9% in patients aged &#x2265;50 (P < 0.001, FDR < 0.001). Individuals in the 30-39 group were nearly twice as likely to carry a POLE mutation compared with those over 40 (OR = 1.96, 95% CI 1.41-2.74, P < 0.001). CONCLUSIONS: Differences in mutations of key genes including a lower prevalence of APC mutations and increased SMAD4 mutations in younger individuals provides further supporting evidence that early-onset CRC may represent a distinct biological subtype of CRC. Enrichment of POLE mutations in younger patients highlights the importance of expanded molecular profiling in early-onset CRC, which could help identify patients most likely to benefit from immunotherapy and advance personalized treatment strategies in CRC. Together, these findings reinforce the need to approach early-onset CRC as a distinct biological entity and ensure that appropriate molecular assays are incorporated to guide care.

APC

PSMA1, PSMA5, and PSMB2 serve as prognostic biomarkers and are correlated with tumor-infiltrating leukocytes in HCC.

Hepatocellular carcinoma (HCC) ranks as the third leading cause of cancer-related death. Proteasome (PSM) is the main intracellular proteolytic system in higher eukaryotic cells. It has been reported to be involved in the tumor's onset, metabolism, and survival, and it has been recognized as a therapeutic target for many human cancers. The 20S proteasome subunits, specifically proteasome 20S subunit alpha 1 (PSMA1), proteasome 20S subunit alpha 5 (PSMA5), and proteasome 20S subunit beta 2 (PSMB2), are overexpressed in various malignancies, including HCC. Nevertheless, the exact role of these genes in HCC prognosis remains only partially understood. Moreover, a reliable predictive biomarker for HCC is essential for supporting the implementation of personalized therapies. Therefore, this study employed a comprehensive bioinformatics approach, integrating data from cBioPortal, Human Protein Atlas (HPA), Oncomine, STRING Viruses, Kaplan-Meier plotter, and other established high-throughput databases and tools. The current study thoroughly examined the expression levels, methylation, and genomic alterations of PSM and their correlation with tumor-infiltrating leukocytes. PSMA1, PSMA5, and PSMB2 are overexpressed in various cancers, including HCC, and their expression levels are associated with tumor grade and stage. The abundance of these genes is linked to diminished DNA methylation levels and genome alterations. Moreover, there was a significant association between the expression levels of these genes and poor prognosis and immune cell infiltration. In conclusion, this study proposes PSMA1, PSMA5, and PSMB2 as biomarkers for HCC.

Humans

In silico analysis of SH3BP2 genomic alterations and expression profiles in CRC.

AIM: Colorectal cancer (CRC) is a widespread health issue that attains high mortality. The adaptor protein SH3BP2 amplification results in metabolic changes, oxidative stress, NK cell activity, and inflammation. The NK cells are capable of destroying tumor cells without prior activation, help prevent metastasis, and have prognostic value. Targeting SH3BP2 to regulate NK cell activity in the TME could enhance CRC-based immunotherapy. MATERIALS AND METHODS: The cancer hallmark tool helps in understanding SH3BP2&#xa0;hallmark annotation. Utilizing the STRING tool and the KEGG pathway, protein functional enrichment and PPI networking were analyzed. TIMER 2.0 was used for immune cell infiltration correlation analysis, and UALCAN was used for CPTAC-based protein expression profiling. RESULTS AND CONCLUSIONS: The GEO (GSE9348) dataset showed SH3BP2 is upregulated in CRC (log2 fold change&#x2009;=&#x2009;1.18). GEO, TCGA, and cBioPortal revealed SH3BP2 alterations in CRC cases, potentially aiding immune evasion. Mutations in SH3BP2 influence cancer growth, suppressing tumors or promoting them by activating NF-&#x3ba;B and affecting immune responses through WNT/&#x3b2;-catenin, PI3K, MAPK, and JAK-STAT pathways. Overall, SH3BP2 plays a key role in cancer growth and immune regulation, making it a promising target for CRC therapy. Further experimental validation is needed to demonstrate its diagnostic and therapeutic potency.

Humans

Liquid biopsies reveal dual compartments of cancer risk from tumor and host-derived mutations.

MOTIVATION: Circulating tumor DNA (ctDNA) and clonal hematopoiesis of indeterminate potential (CHIP) are two biologically distinct sources of somatic mutations detectable in blood. While ctDNA captures tumor-intrinsic alterations, CHIP arises from age-related hematopoietic clones and is often considered background noise. Here, we conduct a large-scale, tumor-type-resolved analysis of over 9000 patients with CHIP data and 1500 patients with ctDNA data across solid tumors profiled at Memorial Sloan Kettering Cancer Center. RESULTS: Our results reveal that CHIP and ctDNA mutations exhibit non-overlapping, clinically meaningful signals. CHIP mutations, particularly in DNA damage response and epigenetic regulators (e.g. PPM1D, CHEK2, ATM, TP53, ASXL1), are associated with worse overall survival, increased metastatic potential, and site-specific dissemination. ctDNA mutations in canonical oncogenic drivers (e.g. TP53, EGFR, KRAS, STK11) reflect tumor aggressiveness and correlate with poor prognosis and metastasis across multiple cancer types. Joint modeling in lung adenocarcinoma confirms the independent prognostic contributions of both compartments. Additionally, longitudinal clonal analysis links specific CHIP mutations to the emergence of hematologic malignancies under therapeutic pressure. These findings support a dual-compartment model of liquid biopsy, in which tumor- and host-derived mutations jointly inform on cancer risk, progression, and metastatic behavior. Integrating both compartments may enhance the clinical utility of blood-based biomarkers in oncology. AVAILABILITY: All genomic and clinical data used in this study are available through cBioPortal. Summarized outputs and processed results tables are provided in Supplementary Data.

Humans

SPOP expression is associated with tumor-infiltrating lymphocytes in pancreatic cancer.

BACKGROUND: Speckle Type POZ Protein (SPOP), despite its tumor type-dependent role in tumorigenesis, primarily as a tumor suppressor gene is associated with a variety of different cancers. However, its function in pancreatic cancer remains uncertain. METHODS: SPOP expression and the association between its expression and patient prognosis and immune function were evaluated using The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), The Tumor Immune Estimation Resource 2.0 (TIMER2.0) database, cBioportal, and various bioinformatic databases. Enrichment analysis of SPOP and the association between SPOP expression with clinical stage and grade were analyzed using the R software package. Then immunohistochemistry (IHC) was used to estimate the correlation between SPOP and tumor-infiltrating lymphocytes (TILs) in patients with pancreatic cancer. RESULTS: As part of our study, we assessed that SPOP was anomalously expressed in kinds of cancers, associated with clinical stage and outcomes. Meanwhile, SPOP also played a crucial role in the tumor microenvironment (TME). The expression level of SPOP was significantly correlated to tumor-infiltrating immune cells (TICs) in pancreatic cancer. CONCLUSIONS: Our study uncovered the potential corrections in SPOP with TICs, suggesting that SPOP may act as a biomarker for immunotherapy in pancreatic cancer.

Humans

CDC20B Dysregulation: Links to Tumor Prognosis and Immunity.

OBJECTIVE: This study aimed to clarify the pan-cancer expression pattern, upstream regulatory mechanisms, prognostic relevance, and immune associations of CDC20B. METHOD: Using public databases (GTEx, GEO, and TCGA), we examined CDC20B expression and its associations with prognosis and tumor immunity across multiple cancers. Immunohistochemistry (IHC) on an independent clinical cohort was performed to validate CDC20B upregulation in tumor tissues. Promoter methylation, genetic alterations, and immune infiltration were analyzed using bioinformatics tools (cBioPortal, UALCAN, TIMER2.0, ESTIMATE). Functional enrichment was assessed by GSEA and single-cell state analysis (CancerSEA). RESULTS: CDC20B was markedly upregulated in most tumor types (p < 0.001), with strong diagnostic efficiency (AUC > 0.7 in 15 cancers) and potential regulation by promoter hypomethylation. IHC confirmed its overexpression in clinical tumor tissues. However, the prognostic impact of CDC20B was cancer-type-specific: high expression correlated with poor overall survival in UCS, LGG, KIRC, and OV, but with favorable survival in BRCA, LUAD, and PAAD. CDC20B expression was associated with immune infiltration patterns, showing negative correlations with ImmuneScore in most cancers but positive correlations with CD8+ T cells in PAAD. Functional analyses indicated involvement in EMT, KRAS/NF-&#x3ba;B signaling, and DNA damage response pathways. DISCUSSION: The dual prognostic role of CDC20B suggests context-dependent functions, likely influenced by tumor microenvironment composition and underlying oncogenic programs. Promoter hypomethylation emerges as a potential epigenetic driver of overexpression. The associations with immune modulation and genomic instability suggest that CDC20B is a candidate biomarker, though causal relationships require experimental validation. CONCLUSION: CDC20B may contribute to tumor progression in a context-dependent manner, with its prognostic impact varying across cancer types. Its role in tumor immunity and oncogenic pathways warrants further investigation, particularly in stratified patient populations.

CDC20B

Pan-cancer Bioinformatics Analysis Combined with Colon Cancer Experimental Validation: A Study on TMED3 as a Diagnostic and Prognostic Biomarker.

Transmembrane Emp24 Protein Transport Domain 3 (TMED3), a member of the p24 protein family, has been implicated in tumor proliferation, invasion, and migration. This study aimed to evaluate the expression patterns, prognostic significance, immune associations, and potential biological functions of TMED3 across multiple cancer types using pan-cancer bioinformatics analysis combined with immunohistochemical (IHC) validation in colon cancer. Multiomics datasets from The Cancer Genome Atlas, Genotype-Tissue Expression, UALCAN, Human Protein Atlas, and cBioPortal databases were analyzed to investigate TMED3 expression and genetic alterations in pan-cancer. Immunohistochemistry was performed to evaluate TMED3 protein expression in colon cancer tissues. Kaplan-Meier survival analysis and Cox regression analysis were used to assess the prognostic value of TMED3. Spearman correlation analysis was conducted to evaluate the associations of TMED3 with tumor mutational burden, microsatellite instability (MSI), immune cell infiltration, and immune checkpoints. Gene Set Enrichment Analysis was performed to investigate potential biological pathways associated with TMED3 in colon cancer. TMED3 expression was elevated in most tumor types and was associated with unfavorable overall survival and disease-specific survival in adrenocortical carcinoma, colon adenocarcinoma, and uveal melanoma. The greatest frequency of TMED3 genetic alterations was identified in mesothelioma, with amplification representing the predominant alteration type. In addition, TMED3 expression showed significant correlations with tumor mutational burden and microsatellite instability in kidney renal clear cell carcinoma, stomach adenocarcinoma, and uterine corpus endometrial carcinoma. TMED3 expression was also associated with immune infiltration and immune checkpoint expression in several tumors. IHC analysis demonstrated increased TMED3 expression in colon cancer tissues compared with normal colon tissues and showed an association with T stage. Functional enrichment analysis identified pathways related to ribosome, antigen processing and presentation, oxidative phosphorylation, and pentose phosphate. These findings indicate that TMED3 may represent a promising biomarker for the diagnosis and prognostic evaluation of colon cancer as well as other tumor types.

Humans