SNRPB2 in the pan-cancer landscape: A bioinformatics exploration and validation in hepatocellular carcinoma.

Aberrant splicing is a significant contributor to gene expression abnormalities in cancer. SNRPB2, a component of U2 small nuclear ribonucleoprotein particles (snRNPs), contributes to the assembly of the spliceosome, the molecular machinery responsible for splicing. To date, few studies have investigated the role of SNRPB2 in tumorigenesis. We examined data sourced from various public databases, such as The Cancer Genome Atlas(TCGA), the Clinical Proteomic Tumor Analysis Consortium(CPTAC), and Gene Expression Omnibus(GEO). Our investigation included gene expression, genomic and epigenomic scrutiny, gene set enrichment assessment(GSEA), and immune cell infiltration evaluation. Furthermore, we performed empirical validation to ascertain the impact of SNRPB2 suppression on the proliferation and migration of liver cancer cells. Analysis of gene expression revealed widespread upregulation of SNRPB2 across a spectrum of cancer types, with heightened levels of SNRPB2 expression in numerous tumors linked to unfavorable prognosis. Genomic and epigenomic assessments revealed connections between SNRPB2 expression and variations in SNRPB2 copy number, DNA methylation patterns, and RNA modifications. Through gene set enrichment analysis, the involvement of SNRPB2 in vital biological processes and pathways related to cancer was identified. Furthermore, scrutiny of immune cell infiltration suggested a potential relationship between SNRPB2 and the tumor microenvironment, which was reinforced by multiple single-cell sequencing profiles. Subsequent experimental validation revealed that silencing SNRPB2 effectively impeded the proliferation and migration of liver cancer cells. Taken together, these findings underscore the prospective utility of SNRPB2 as a prognostic biomarker and a promising candidate for immunotherapy in cancer. It is necessary to engage in additional exploration into its underlying mechanisms and clinical treatment potential.

Pan-cancer characterization of cellular senescence reveals its inter-tumor heterogeneity associated with the tumor microenvironment and prognosis.

Cellular senescence (CS) is characterized by the irreversible cell cycle arrest and plays a key role in aging and diseases, such as cancer. Recent years have witnessed the burgeoning exploration of the intricate relationship between CS and cancer, with CS recognized as either a suppressing or promoting factor and officially acknowledged as one of the 14 cancer hallmarks. However, a comprehensive characterization remains absent from elucidating the divergences of this relationship across different cancer types and its involvement in the multi-facets of tumor development. Here we systematically assessed the cellular senescence of over 10,000 tumor samples from 33 cancer types, starting by defining a set of cancer-associated CS signatures and deriving a quantitative metric representing the CS status, called CS score. We then investigated the CS heterogeneity and its intricate relationship with the prognosis, immune infiltration, and therapeutic responses across different cancers. As a result, cellular senescence demonstrated two distinct prognostic groups: the protective group with eleven cancers, such as LIHC, and the risky group with four cancers, including STAD. Subsequent in-depth investigations between these two groups unveiled the potential molecular and cellular mechanisms underlying the distinct effects of cellular senescence, involving the divergent activation of specific pathways and variances in immune cell infiltrations. These results were further supported by the disparate associations of CS status with the responses to immuno- and chemo-therapies observed between the two groups. Overall, our study offers a deeper understanding of inter-tumor heterogeneity of cellular senescence associated with the tumor microenvironment and cancer prognosis.

Pan-cancer Comprehensive Analysis Identified EGFR as a Potential Biomarker for Multiple Tumor Types.

The epidermal growth factor receptor (EGFR) has been extensively studied for its critical role in the development and progression of various malignancies. In this comprehensive pan-cancer analysis, we investigated the potential of EGFR as a biomarker across multiple tumor types; a comprehensive analysis of EGFR gene mutation and copy number variation was conducted using cBioPortal and other tools. Utilizing multi-omics datasets from The Cancer Genome Atlas (TCGA), we analyzed EGFR's expression patterns, prognostic implications, genetic mutations, and molecular interactions in different cancers. Our findings revealed frequent dysregulation of EGFR in several tumor types, including lung cancers and glioblastoma multiforme. High EGFR expression was consistently associated with poor clinical outcomes, such as reduced overall survival, disease-free survival, and progression-free survival. Genetic alteration analysis indicated a high frequency of EGFR mutations and copy number variations, particularly in glioblastoma multiforme. Additionally, our study suggests a complex relationship between EGFR expression and cancer-associated fibroblast infiltration, which may contribute to an immunosuppressive tumor microenvironment. These findings underscore the clinical relevance of EGFR as a prognostic biomarker and therapeutic target, emphasizing the need for further research and the development of targeted therapies to enhance patient outcomes in cancers with EGFR alterations. The co-expression network of EGFR with genes and proteins involved in cell cycle regulation and mitotic control provided insights into the molecular mechanisms of oncogenesis.

Pan-cancer analysis of the prognostic and immunological roles of SHP-1/ptpn6.

SHP-1, a nonreceptor protein tyrosine phosphatase encoded by ptpn6, has been regarded as a regulatory protein of hematopoietic cell biology for years. However, there is now increasing evidence to support its role in tumors. Thus, the role of ptpn6 for prognosis and immune regulation across 33 tumors was investigated, aiming to explore its functional heterogeneity and clinical significance in pan-cancer. Differential expression of ptpn6 was found between cancer and adjacent normal tissues, and its expression was significantly correlated with the prognosis of tumor patients. In most cancers, ptpn6 expression was significantly associated with immune infiltration. This was further confirmed by ptpn6-related genes/proteins enrichment analysis. Additionally, genetic alterations in ptpn6 was observed in most cancers. As for epigenetic changes, it's phosphorylation levels significantly altered in 6 tumors, while methylation levels significantly altered in 12 tumors. Notably, the methylation levels of ptpn6 were significantly decreased in 11 tumors, accompanied by its increased expression in 8 of them, suggesting that the hypomethylation may be related to its increased expression. Our results show that ptpn6 plays a specific role in tumor immunity and exerts a pleiotropic effect in a variety of tumors. It can serve as a prognostic factor for some cancers. Especially in LGG, KIRC, UCS and TGCT, the increased expression of ptpn6 is associated with poor prognosis and high immune infiltration. This aids in understanding the role of ptpn6 in tumor biology, and can provide insight into presenting a potential biomarker for poor prognosis and immune infiltration in cancers.

Lymphocyte activation gene 3 served as a potential prognostic and immunological biomarker across various cancer types: a clinical and pan-cancer analysis.

Objectives: Lymphocyte activation gene 3 (LAG3), an inhibitory receptor in T-cell activation, is a negative prognostic factor. However, its impact on tumours has yet to be comprehensively elucidated on a pan-cancer scale. Thus, we aim to reveal its role at the pan-cancer level. Methods: We performed IHC staining on a retrospective cohort of 370 patients. Then we assessed the prognostic effect of LAG3 using Kaplan-Meier survival analysis and multivariate Cox regression analysis. In pan-cancer analysis, we constructed competing endogenous RNA and protein-protein interaction networks, conducted gene set enrichment analysis and identified correlations between LAG3 gene expression and various factors, including clinical characteristics, tumour purity, mutations, tumour immunity and drug sensitivity across 33 cancer types. Results: LAG3 was expressed higher in normal kidney tissues than in tumours. A high level of LAG3 gene expression was an independent prognostic factor for OS (HR = 6.60, 95% CI = 2.43-17.90, P < 0.001) and PFS (HR = 3.44, 95% CI = 1.68-7.10, P < 0.001). In pan-cancer analysis, LAG3 exhibited robust correlations with survival and tumour stages in various cancers. Moreover, LAG3 was strongly associated with immune-related genes, proteins and signalling pathways. LAG3 gene expression was positively associated with increased infiltration of activated immune cells and decreased infiltration of several resting cells. LAG3 gene expression was associated with tumour mutation burden and microsatellite instability in multiple cancers. Conclusion: High LAG3 gene expression was an independent risk factor in kidney neoplasms. It also functioned as a biomarker for prognosis, TIME and immunotherapy efficacy in the pan-cancer dimension.

Deciphering EIF3D's Role in Immune Regulation and Malignant Progression: A Pan-Cancer Analysis with a Focus on Colon Adenocarcinoma.

Background: EIF3D, a key component of the eukaryotic translation initiation factor 3 (EIF3) complex, is critical in selectively translating mRNAs with atypical cap structures. Its relationship with colon adenocarcinoma (COAD) development and immune infiltration, however, remains under-explored. This study delves into EIF3D's role in COAD using bioinformatics and in vitro experimentation. Materials and Methods: We analyzed EIF3D expression levels utilizing TCGA, GTEx, CPTAC, and TISIDB databases. The TISCH database and ssGSEA method helped in assessing EIF3D's link with the tumor immune microenvironment. EIF3D expression in CRC cells was gauged via real-time PCR. Cell proliferation was assessed using CCK8 and colony formation assays, while migration capabilities were tested through Transwell assays. Flow cytometry facilitated cell cycle distribution and apoptosis analysis. ChIP-qPCR identified transcription factors regulating EIF3D, and bulk sequencing explored EIF3D's pathways in promoting COAD. Results: EIF3D upregulation is a common feature in various tumors, especially in COAD, correlating with poor prognosis in many cancer types. It showed significant associations with immune cell and cancer-associated fibroblast (CAF) infiltration across multiple tumors. Additionally, it is closely associated with molecular and immune subtypes of multiple tumors, including COAD. Single-cell analyses depicted EIF3D's distribution and proportion in CRC immune cells. In vitro findings indicated EIF3D knockdown curtailed proliferation and migration, inducing G0/G1 arrest in COAD cells. Moreover, bulk sequencing revealed EIF3D knockdown interferes with multiple cancer-related pathways, likely by curtailing cell cycle and DNA replication activities to regulate cell proliferation. Conclusion: EIF3D emerges as a potential prognostic biomarker for tumor progression and immune infiltration, particularly in COAD, potentially predicting immunotherapy efficacy. Additionally, EIF3D represents a multifaceted target implicated in COAD's malignant progression.

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.

Neutrophil chemotaxis score and chemotaxis-related genes have the potential for clinical application to prognosticate the survival of patients with tumours.

As frontline cells, the precise recruitment of neutrophils is crucial for resolving inflammation and maintaining the homeostasis of the organism. Increasing evidence suggests the pivotal role of neutrophil chemotaxis in cancer progression and metastasis. Here, we collected clinical data and peripheral blood samples from patients with tumours to examine the alterations in the neutrophil quantity and chemotactic function using the Cell Chemotaxis Analysis Platform (CCAP). Transcriptome sequencing data of pan-cancer were obtained from The Cancer Genome Atlas (TCGA). Using the least absolute shrinkage and selection operator (LASSO) Cox regression model, we selected a total of 29 genes from 155 neutrophil- and chemotaxis-related genes to construct the ChemoScore model. Meanwhile, nomogram-based comprehensive model was established for clinical application. Furthermore, immunofluorescence (IF) staining was employed to assess the relationship between the neutrophils infiltrating and the survival outcomes of tumours. In this observational study, the chemotactic function of neutrophils was notably diminished in patients. The establishment and validation of ChemoScore suggested neutrophil chemotaxis to be a risk factor in most tumours, whereby higher scores were associated with poorer survival outcomes and were correlated with various immune cells and malignant biological processes. Moreover, IF staining of tumour tissue substantiated the adverse correlation between neutrophil infiltration and the survival of patients with lung adenocarcinoma (P = 0.0002) and colon adenocarcinoma (P = 0.0472). Taken together, patients with tumours demonstrated a decrease in chemotactic function. ChemoScore potentially prognosticates the survival of patients with tumours. Neutrophil chemotaxis provides novel directions and theoretical foundations for anti-tumour treatment.

Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types.

BACKGROUND: Homologous recombination deficiency (HRD) is recognized as a pan-cancer predictive biomarker that potentially indicates who could benefit from treatment with PARP inhibitors (PARPi). Despite its clinical significance, HRD testing is highly complex. Here, we investigated in a proof-of-concept study whether Deep Learning (DL) can predict HRD status solely based on routine hematoxylin & eosin (H&E) histology images across nine different cancer types. METHODS: We developed a deep learning pipeline with attention-weighted multiple instance learning (attMIL) to predict HRD status from histology images. As part of our approach, we calculated a genomic scar HRD score by combining loss of heterozygosity (LOH), telomeric allelic imbalance (TAI), and large-scale state transitions (LST) from whole genome sequencing (WGS) data of n = 5209 patients across two independent cohorts. The model's effectiveness was evaluated using the area under the receiver operating characteristic curve (AUROC), focusing on its accuracy in predicting genomic HRD against a clinically recognized cutoff value. RESULTS: Our study demonstrated the predictability of genomic HRD status in endometrial, pancreatic, and lung cancers reaching cross-validated AUROCs of 0.79, 0.58, and 0.66, respectively. These predictions generalized well to an external cohort, with AUROCs of 0.93, 0.81, and 0.73. Moreover, a breast cancer-trained image-based HRD classifier yielded an AUROC of 0.78 in the internal validation cohort and was able to predict HRD in endometrial, prostate, and pancreatic cancer with AUROCs of 0.87, 0.84, and 0.67, indicating that a shared HRD-like phenotype occurs across these tumor entities. CONCLUSIONS: This study establishes that HRD can be directly predicted from H&E slides using attMIL, demonstrating its applicability across nine different tumor types.

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.

STARD7 could be an immunological and prognostic biomarker: from pan-cancer analysis to hepatocellular carcinoma validation.

BACKGROUND: As the emergence of technologies such as sequencing and gene mapping, significant advancements have been made in understanding the landscape of tumors. However, the effective treatment of tumors continues to pose a tremendous challenge in clinical practice, which highlights the importance of predicting tumor markers and studying drug resistance mechanisms. The prognosis and differential expression of STARD7 in human pan-cancer were investigated by bioinformatic methods and experimental verification. METHODS: The expression, diagnostic, and prognostic significance of the STARD7 gene were comprehensive analyzed using bioinformatics techniques. Furthermore, we validated our projected outcomes in liver cancer through experimental methodologies, including the use of qRT-PCR, CCK8 and transwell assays. RESULTS: The STARD7 gene exhibits differential expression in 25 tumors, with high expression observed in 22 tumors. These distinct expression patterns within different tumor types are closely associated with poor prognosis and diagnosis. Furthermore, the STARD7 gene plays a role in regulating the tumor immune microenvironment. Methylation levels of STARD7 vary among 20 types of tumors and are correlated with survival outcomes. Furthermore, the experiment results demonstrated that STARD7 is highly expressed in hepatocellular carcinoma cells. Suppression of STARD7 significantly impedes the proliferation, migration, and invasion of HepG-2 and SMMC-7721 cells. CONCLUSIONS: STARD7 has the potential to function as a crucial prognostic biomarker and exhibit correlation with tumor immunity in various types of human cancers. The implications of our findings extend to informing cancer immune-therapy and promoting the advancement of precision immune-oncology.

CISD3 is a prognostic biomarker and therapeutic target in pan-cancer.

Recent studies indicate that CISD3 is crucial in mitochondrial function and tumorigenesis. Using various databases, we systematically analyzed its expression, prognostic value, and immune activity. Our findings show CISD3 is mainly expressed in tumor cells across cancers, with higher mRNA but lower protein levels, degraded post-translationally via the lysosomal pathway. In certain cancers, CISD3 expression is positively correlated with tumor-infiltrating immune cells. Prognostic analysis suggests dual roles as both protective and risk factors, notably an independent prognostic predictor in renal cell carcinoma (RCC). CISD3 copy number variations are linked to homologous recombination defects and tumor-specific neoantigens, negatively correlated with methylation levels. Pathway analysis reveals CISD3 involvement in oncogenic processes, such as proliferation inhibition and epithelial-mesenchymal transition. Protein interactions underline its role in mitochondrial metabolism and redox balance. Experiments confirm low CISD3 expression in cancers, with overexpression reducing proliferation, migration, invasion, and tumor growth in mice. Mechanistic studies indicate CISD3 overexpression disrupts mitochondrial function, increases ROS levels, decreases GSH/GSSG ratios and mitochondrial membrane potential, inhibiting antioxidant activity and promoting cell damage and ferroptosis, thus impeding cancer progression. This study highlights CISD3's potential as a prognostic biomarker and therapeutic target.

Single cell atlas reveals multilayered metabolic heterogeneity across tumour types.

BACKGROUND: Metabolic reprogramming plays a pivotal role in cancer progression, contributing to substantial intratumour heterogeneity and influencing tumour behaviour. However, a systematic characterization of metabolic heterogeneity across multiple cancer types at the single-cell level remains limited. METHODS: We integrated 296 tumour and normal samples spanning six common cancer types to construct a single-cell compendium of metabolic gene expression profiles and identify cell type-specific metabolic properties and reprogramming patterns. A computational approach based on non-negative matrix factorization (NMF) was utilised to identify metabolic meta-programs (MMPs) showing intratumour heterogeneity. In-vitro cell experiments were conducted to confirm the associations between MMPs and chemotherapy resistance, as well as the function of key metabolic regulators. Survival analyses were performed to assess clinical relevance of cellular metabolic properties. FINDINGS: Our analysis revealed shared glycolysis upregulation and divergent regulation of citric acid cycle across different cell types. In malignant cells, we identified a colorectal cancer-specific MMP associated with resistance to the cuproptosis inducer elesclomol, validated through in-vitro cell experiments. Furthermore, our findings enabled the stratification of patients into distinct prognostic subtypes based on metabolic properties of specific cell types, such as myeloid cells. INTERPRETATION: This study presents a nuanced understanding of multilayered metabolic heterogeneity, offering valuable insights into potential personalized therapies targeting tumour metabolism. FUNDING: National Key Research and Development Program of China (2021YFA1300601). National Natural Science Foundation of China (key grants 82030081 and 81874235). The Shenzhen High-level Hospital Construction Fund and Shenzhen Basic Research Key Project (JCYJ20220818102811024). The Lam Chung Nin Foundation for Systems Biomedicine.

EBNA1BP2 identified as potential prognostic biomarker for multiple tumor types in pan-cancer analysis.

BACKGROUND: Epstein-Barr virus (EBV) infection has been closely linked to the development of various types of cancer. EB nuclear antigen 1 binding protein 2 (EBNA1BP2) is a crucial molecule for stable isolation of EBV in latent infection. However, the role of EBNA1BP2 in multiple tumor types is remains unclear. In this study, we comprehensively analyzed the functional characteristics of EBNA1BP2 and investigate its potential as a prognostic biomarker in pan-cancer. METHODS: We utilized data from TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus) databases and employed various bioinformatics analysis tools, including TIMER2.0, HPA, GEPIA2.0, PrognoScan, cBioPortal, CancerSEA, and BioGRID to explore the expression pattern, prognostic value, immune infiltration, and methylation level of EBNA1BP2 in pan-cancer. Additionally, we conducted enrichment analysis of genes associated with EBNA1BP2 to identify potential biological functions and pathways. RESULTS: Our analysis revealed that EBNA1BP2 expression was significantly higher in tumor tissues compared to tumor-adjacent tissues. We observed that lower expression of EBNA1BP2 in adrenocortical carcinoma (ACC), brain lower grade glioma (LGG), sarcoma (SARC), and uterine carcinosarcoma (UCS) was significantly associated with improved overall survival (OS) and disease-free survival (DFS). Furthermore, the promoter methylation level of EBNA1BP2 was downregulated in the majority of cancer types. At the single-cell level, EBNA1BP2 was found to be positively correlated with cell cycle and DNA repair processes, while negatively correlated with hypoxia. Additionally, EBNA1BP2 was associated with the infiltration of immune cells such as B cells, cancer-associated fibroblast cells, and CD8+ T cells. Gene enrichment analysis indicated that EBNA1BP2 was mainly involved in nucleoplasm and RNA binding pathways. CONCLUSION: Our findings suggest that EBNA1BP2 may serve as a potential prognostic biomarker for survival in pan-cancer. Further experimental studies are needed to validate these findings and explore the underlying mechanisms by which EBNA1BP2 contributes to tumorigenesis.

The prognostic and immune significance of Rab11A in pan-cancer and its function and mechanism underlying estrogen receptor targeting in breast cancer.

OBJECTIVE: Rab11A is an important molecule for recycling endosomes and is closely related to the proliferation, invasion, and metastasis of tumors. This study investigated the prognostic and immune significance of Rab11A and validated its potential function and mechanism in breast cancer (BRCA). METHODS: RNA sequencing data for 33 tumors were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression databases. Correlation analysis was used to evaluate the relationship between Rab11A expression and immune characteristics. Potential pathways were identified using the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analysis. Immunohistochemical analysis, colony formation assay, bromodeoxyuridine incorporation assay, immunofluorescence, and Western blot were used to explore potential function and mechanism. RESULTS: Analysis of the TCGA database showed significant upregulation of Rab11A expression in a variety of cancers. Rab11A was up-regulated in 82.4% of BRCA. High Rab11A expression is associated with poor survival in cancer patients and is a predictor of poor prognosis. CIBERSORT analysis showed that Rab11A was negatively associated with almost all immune cycle activity scores pan-cancer. The results of the TCGA-BRCA cohort were further confirmed by using pathological samples from clinical BRCA patients. The results showed that Rab11A expression was correlated with estrogen receptor (ER) and progesterone receptor expression in BRCA (p < 0.05). Knockdown and overexpression of Rab11A affected the proliferation of BRCA cells. Further mechanistic studies revealed that down-regulation of ER alpha (ERα) and up-regulation of ER beta (ERß) mediated Rab11A-induced inhibition of BRCA cell proliferation. CONCLUSION: Rab11A expression in pan-cancer is associated with poor prognosis and immune profile. In particular, in BRCA, Rab11A expression regulates cell proliferation by targeting ERα and ERß. High Rab11A expression is tightly associated with immune characteristics, tumor microenvironment, and genetic mutations. These results provide a reference for exploring the role of Rab11A in pan-cancer and provide a new perspective for revealing potential therapeutic targets in BRCA.

Exploring the role of ADAMTSL2 across multiple cancer types: A pan-cancer analysis and validated in colorectal cancer.

BACKGROUND: Recent studies have established a correlation between ADAMTSL2 (ADAMTS-like 2) and the development of various cancers. This study aims to conduct a comprehensive pan-cancer analysis in 37 cancer types and investigate its potential role in colon and rectal adenocarcinoma (COADREAD). METHOD: Pan-cancer and mutation data were sourced from The Cancer Genome Atlas (TCGA) database and analyzed using Sangerbox analysis platform. We explored the expression patterns and prognostic implications of ADAMTSL2, and investigated its relationships with tumor heterogeneity, stemness, immune checkpoint genes, immune cell infiltration, RNA modifications, and mutational profiles across different cancers. Additionally, with Ethics Committee approval, we conducted immunohistochemical (IHC) analysis on 120 COADEAD samples to evaluate ADAMTSL2 expression and its association with clinicopathological parameters. RESULTS: ADAMTSL2 expression was positively correlated with the hazard ratio of OS, DSS, DFI and PFI for ESCA and COADREAD. A negative correlation was observed between ADAMTSL2 expression and NEO levels in COAD. Gene alterations in ADAMTSL2 were observed, with a mutation frequency of 5.0% in COAD. There is a significant correlation between ADAMTSL2 expression and immune cell infiltration in a variety of cancers. The expression level of ADAMTSL2 protein was associated with T stage, N stage, M stage (p < 0.05). Kaplan‒Meier survival curves demonstrated that the high ADAMTSL2 group had a shorter OS time (p = 0.047) and progression free survival time (p = 0.026) than the low ADAMTSL2 group. CONCLUSION: In summary, we conducted a comprehensive pan-cancer analysis of ADAMTSL2 and we demonstrated that ADAMTSL2 may serve as a novel prognostic biomarker and immunotherapy target in COADREAD.

Comprehensive pan-cancer analysis reveals CDC6 as a potential immunomodulatory agent and promising therapeutic target in pancreatic cancer.

Background: CDC6 is critical in DNA replication initiation, but its expression patterns and clinical implications in cancer are underexplored. This study uses multi-omics data from The Cancer Genome Atlas (TCGA) to comprehensively analyze CDC6 across various cancers, aiming to evaluate its potential as a prognostic biomarker and explore its role in immunotherapy. Methods: By leveraging multi-omics data from TCGA, we conducted a comprehensive analysis of CDC6 expression across a variety of cancer types. Least absolute shrinkage and selection operator (LASSO) regression was employed to assess the association of CDC6 with key molecules implicated in pancreatic cancer. Results: CDC6 expression was found to be significantly upregulated across a broad spectrum of cancers. High levels of CDC6 expression were associated with poor prognosis in several cancer types. Notable associations were observed between CDC6 expression and tumor mutational burden (TMB), microsatellite instability (MSI), as well as immune cell infiltration. Co-expression analysis revealed significant associations between CDC6 and prevalent immune checkpoint genes. A risk model incorporating CDC6-related genes, including CCNA1, CCNA2, CCND1, CCND2, CDC25B, CDC6, and CDK2, was developed for pancreatic cancer. Conclusions: CDC6 emerges as a promising prognostic biomarker and a potential target for immunotherapy across various cancers, including pancreatic cancer. It appears to modulate immune responses across cancer types, highlighting its regulatory role. Further exploration into the biological functions and clinical implications of CDC6 is warranted.

NCKAP1 as a prognostic and immunological biomarker: pan-cancer analysis and validation in renal clear cell carcinoma.

OBJECTIVES: To systematically investigate the expression, prognostic value, genetic alterations, immune infiltration, and molecular function of Nck-associated protein 1 (NCKAP1) in a pan-cancer analysis, with a specific focus on its association with kidney renal cell carcinoma (KIRC). METHODS: We analyzed the role of NCKAP1 across various tumor types using data from The Cancer Genome Atlas (TCGA). The Gene Expression Profiling Interactive Analysis version 2 (GEPIA2) database was used to assess the correlation between NCKAP1 expression levels and overall survival (OS) and disease-free survival (DFS) across different cancers, as well as its association with cancer stage. Genetic alterations of NCKAP1 were explored using CBioPortal, and their prognostic implications were assessed. NCKAP1 was further analyzed through Gene Ontology and protein interaction network analyses. Immunohistochemistry (IHC) staining from the Human Protein Atlas (HPA) database evaluated NCKAP1 levels in KIRC tissues. Functional assays, including Cell Counting Kit-8 (CCK-8), colony formation, transwell, and wound healing assays, were conducted to determine the effects of NCKAP1 overexpression on cell growth rate and their ability to invade, proliferate, migrate in a KIRC (786-O) cell line. The relationship between NCKAP1 expression and immune infiltration in KIRC was systematically examined using the Tumor Immune Estimation Resource. RESULTS: NCKAP1 expression was significantly altered in most tumor types compared to corresponding non-tumor tissues. Survival analysis indicated that low NCKAP1 expression was associated with poor OS, DFS, and advanced cancer stage (P < 0.05) specifically in KIRC. Genetic alterations in NCKAP1 were linked to clinical outcome in cancer patients, and a positive correlation was observed between NCKAP1 expression and cancer-associated fibroblast infiltration (P < 0.05). Gene Ontology analysis revealed that NCKAP1 regulates the actin cytoskeleton and interacts with proteins such as CYFIP1, ABI2, WASF2, and BRK1. IHC staining showed significantly lower NCKAP1 levels in KIRC tissues compared to normal tissues. Overexpression of NCKAP1 in KIRC cell lines reduced cell proliferation, invasion, and migration (P < 0.05). NCKAP1 was also positively correlated with macrophage, neutrophil, and CD4+ T cell infiltration (P < 0.001). CONCLUSION: NCKAP1 may serve as a prognostic and immunological marker and may be a therapeutic target for KIRC.

Prognostic and immunological roles of RSPO1 in pan-cancer and its correlation with LUAD proliferation and metastasis.

Aberrant RSPO1 expression is implicated in tumor progression across various cancers and correlates with anti-cancer immune cell characteristics. However, the specific role of R-spondin 1 (RSPO1) in lung adenocarcinoma (LUAD) remains unclear. In this study, we utilized data from The Cancer Genome Atlas (TCGA) to assess RSPO1 expression across 33 tumor types. Kaplan-Meier (K-M) analysis revealed the prognostic significance of RSPO1 in various cancers. Using statistical software R, we examined RSPO1's associations with immune cell infiltration, methylation, mutation, and competing endogenous RNA (ceRNA) networks. Exploration via the Tumor Immune Single Cell Hub (TISCH) database uncovered RSPO1's link to the tumor microenvironment (TME) and identified potential small molecule drug targets. We further investigated RSPO1's impact on LUAD cell proliferation, metastasis, and the Wnt pathway in vitro. Our findings highlight RSPO1's role in cancer progression and suggest its potential as both a prognostic marker and therapeutic target in LUAD, implicating the modulation of the Wnt pathway.

PCMT1 confirmed as a pan-cancer immune biomarker and a contributor to breast cancer metastasis.

Protein L-isoaspartyl (D-aspartyl) methyltransferase (PIMT, gene name PCMT1) is an enzyme that repairs proteins with altered aspartate residues by methylation, restoring their normal structure and function. This study conducted a comprehensive analysis of PCMT1 in pan-cancer. The Cancer Genome Atlas, Human Protein Atlas website, and the Genotype-Tissue Expression were utilized in analysis of PCMT1 expression. We examined the association between PCMT1 expression and various factors, including gene modifications, DNA methylation, immune cell infiltration, immunological checkpoints, drug susceptibility, tumor mutation burden (TMB), and microsatellite instability (MSI). Enrichment analyses determined the potential biological roles and pathways involving PCMT1. Our focus then shifted to the role of PCMT1 in breast invasive carcinoma (BRCA). We found that PCMT1 expression was aberrant in many tumors and significantly influenced the prognosis across several cancer types. Gene alterations in PCMT1 predominantly involved deep deletions and amplifications. A negative correlation was observed between DNA methylation and PCMT1 expression across all studied cancer types except thyroid carcinoma PCMT1 exhibited positive correlations with common lymphoid progenitor and CD4(+) T helper 2 cells, whereas it was inversely correlated with central and effector memory T cells, memory CD8(+) T cells, and CD4(+) T helper 1 cells. In many cancer types, PCMT1 expression closely correlated with immunological checkpoint inhibitors, TMB, and MSI. It was also significantly linked to pathways involved in epithelial-mesenchymal transition (EMT), highlighting its role in cancer metastasis. PCMT1 emerged as a significant predictor of breast cancer progression. In vitro experiments demonstrated that reducing PCMT1 expression decreased BRCA cell migration and invasiveness. Additionally, animal studies confirmed that inhibition of PCMT1 slowed tumor growth.