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Background: Deregulations of long non-coding RNAs (lncRNAs) have been implicated in cancer initiation and progression. Current methods can only capture differential expression of lncRNAs at the population level and ignore the heterogeneous expression of lncRNAs in individual patients. Methods: We propose a method (LncRIndiv) to identify differentially expressed (DE) lncRNAs in individual cancer patients by exploiting the disrupted ordering of expression levels of lncRNAs in each disease sample in comparison with stable normal ordering. LncRIndiv was applied to lncRNA expression profiles of lung adenocarcinoma (LUAD). Based on the expression profile of LUAD individual-level DE lncRNAs, we used a forward selection procedure to identify prognostic signature for stage I-II LUAD patients without adjuvant therapy. Results: In both simulated data and real pair-wise cancer and normal sample data, LncRIndiv method showed good performance. Based on the individual-level DE lncRNAs, we developed a robust prognostic signature consisting of two lncRNA (C1orf132 and TMPO-AS1) for stage I-II LUAD patients without adjuvant therapy (P = 3.06 × 10-6, log-rank test), which was confirmed in two independent datasets of GSE50081 (P = 1.82 × 10-2, log-rank test) and GSE31210 (P = 7.43 × 10-4, log-rank test) after adjusting other clinical factors such as smoking status and stages. Pathway analysis showed that TMPO-AS1 and C1orf132 could affect the prognosis of LUAD patients through regulating cell cycle and cell adhesion. Conclusions: LncRIndiv can successfully detect DE lncRNAs in individuals and be applied to identify prognostic signature for LUAD patients. [ABSTRACT FROM AUTHOR]

Background: Cancer stem cell (CSC) hypothesis postulates that tumors are maintained by a self-renewing CSC population that is also capable of differentiating into non-self-renewing cell populations that constitute the bulk of tumor. Stem cells renewal and differentiation can be directly influenced by the oxygen levels of determined tissues, probably by the reduction of oxidative DNA damage in hypoxic regions, thus leading to a friendlier microenvironment, regarding to clonal expansion and for resistance to chemotherapeutic regimens. Furthermore, there have been strong data indicating a pivotal role of hypoxic niche in cancer stem cells development. There are evidence that hypoxia could drive the maintenance of CSC, via HIF-1α expression, but it still to be determined whether hypoxia markers are expressed in breast tumors presenting CD44+CD24-/low immunophenotype. Methods: Immunohistochemical analysis of CD44+CD24-/low expression and its relationship with hypoxia markers and clinical outcome were evaluated in 253 samples of breast ductal carcinomas. Double-immunolabeling was performed using EnVision Doublestain System (Dako, Carpinteria, CA, USA). Slides were then scanned into high-resolution images using Aperio ScanScope XT and then, visualized in the software Image Scope (Aperio, Vista, CA, USA). Results: In univariate analysis, CD44+CD24-/low expression showed association with death due to breast cancer (p = 0.035). Breast tumors expressing CD44+CD24-/low immunophenotype showed relationship with HIF-1α (p = 0.039) and negativity for HER-2 (p = 0.013). Conclusion: Considering that there are strong evidences that the fraction of a tumour considered to be cancer stem cells is plastic depending upon microenvironmental signals, our findings provide further evidence that hypoxia might be related to the worse prognosis found in CD44+CD24-/low positive breast tumors. [ABSTRACT FROM AUTHOR]

Background: Lung adenocarcinoma (LUAD) accounts for the highest proportion of lung cancers; however, specific biomarkers are lacking for diagnosis, treatment, and prognostic assessment. Cell division cycle-associated 8 (CDCA8) is a cell cycle regulator with elevated expression in various cancers. However, the association between CDCA8 expression and LUAD prognosis remains unclear. Methods: The association between CDCA8 and LUAD prognosis was evaluated based on the The Cancer Genome Atlas (TCGA) dataset, and CDCA8 related functions were determined using gene enrichment and gene ontology analyses. We also analyzed the association between CDCA8 expression and immune cell infiltration. Immunohistochemistry was used to determine the differential expression of CDCA8 in tumors and controls. Finally, we evaluated the differences in the sensitivity of different levels of CDCA8 to different anticancer drugs in LUAD. Results: CDCA8 expression was significantly higher in primary LUAD tumors than in normal tissues (P < 0.001). Moreover, Kaplan–Meier survival analysis demonstrated that high CDCA8 expression predicted poor survival in patients with LUAD (P = 0.006). The receiver operating characteristic (ROC) curves indicated that CDCA8 was an effective guide for the diagnosis of LUAD. Functional annotation indicated that CDCA8 might be involved in functions such as p53 stabilization, nucleotide metabolism, RNA-mediated gene silencing, and the G2/M phase checkpoint. Immune infiltration results suggested that CDCA8 was positively correlated with Th2 cells and Tgd and negatively correlated with Eosinophils and Mast cells (P < 0.01). In addition, elevated expression of CDCA8 may increase the sensitivity of patients to certain anticancer drugs. Conclusions: CDCA8 upregulation is significantly associated with poor survival and immune infiltration in patients with LUAD. Our study suggests that CDCA8 can be used as a biomarker for LUAD prognosis and a reference for personalized medication. [ABSTRACT FROM AUTHOR]

Background: Kidney renal clear cell carcinoma (KIRC) represents a significant proportion of renal cell carcinomas and is characterized by high aggressiveness and poor prognosis despite advancements in immunotherapy. Disulfidptosis, a novel cell death pathway, has emerged as a critical mechanism in various cellular processes, including cancer. This study leverages machine learning to identify disulfidptosis-related long noncoding RNAs (DRlncRNAs) as potential prognostic biomarkers in KIRC, offering new insights into tumor pathogenesis and treatment avenues. Results: Our analysis of data from The Cancer Genome Atlas (TCGA) led to the identification of 431 DRlncRNAs correlated with disulfidptosis-related genes. Five key DRlncRNAs (SPINT1-AS1, AL161782.1, OVCH1-AS1, AC131009.3, and AC108673.3) were used to develop a prognostic model that effectively distinguished between low- and high-risk patients with significant differences in overall survival and progression-free survival. The low-risk group had a favorable prognosis associated with a protective immune microenvironment and a better response to targeted drugs. Conversely, the high-risk group displayed aggressive tumor features and poor immunotherapy outcomes. Validation through qRT‒PCR confirmed the differential expression of these DRlncRNAs in KIRC cells compared to normal kidney cells, underscoring their potential functional significance in tumor biology. Conclusions: This study established a robust link between disulfidptosis-related lncRNAs and patient prognosis in KIRC, underscoring their potential as prognostic biomarkers and therapeutic targets. The differential expression of these lncRNAs in tumor versus normal tissue further highlights their relevance in KIRC pathogenesis. The predictive model not only enhances our understanding of KIRC biology but also provides a novel stratification tool for precision medicine approaches, improving treatment personalization and outcomes in KIRC patients. [ABSTRACT FROM AUTHOR]

Objective: Tumor immune infiltration leads to poor prognosis of gastric cancer patients and seriously affects the life quality of gastric cancer patients. This study was based on bioinformatics to screen prognostic biomarkers in patients with high degree of immune invasion of gastric cancer. Meanwhile, the action of biomarker CCDC80 was explored in gastric cancer by cell and tumorigenesis experiments, to provide reference for the cure of gastric cancer patients. Methods: Data sets and clinical massage on gastric cancer were collected from TCGA database and GEO database. ConsensusClusterPlus was used to cluster gastric cancer patients based on the 28 immune cells infiltration in ssGSEA. R "Limma" package was applied to analyze differential mRNAs between Cluster 1 and Cluster 2. Differential expression genes were screened by single factor analysis. Stemness markers (SERPINF1, DCN, CCDC80, FBLN5, SPARCL1, CCL14, DPYSL3) were identified for differential expression genes. Prognostic value of CCDC80 was evaluated in gastric cancer. Differences in genomic mutation and tumor microenvironment immune infiltration were assessed between high or low CCDC80. Finally, gastric cancer cells (HGC-27 and MKN-45) were selected to evaluate the action of silencing CCDC80 on malignant characterization, macrophage polarization, and tumor formation. Results: Bioinformatics analysis showed that CCDC80, as a stemness marker, was significantly overexpressed in gastric cancer. CCDC80 was also related to the degree of gastric cancer immune invasion. CCDC80 was up-expressed in cells of gastric cancer. Silencing CCDC80 inhibited malignant characterization and subcutaneous tumor formation of gastric cancer cells. High expression of CCDC80 was positive correspondence with immune invasion. Silencing CCDC80 inhibited M2 polarization and promoted M1 polarization in tumor tissues. In addition, gastric cancer patients were likely to have mutations in CDH1, ACTRT1, GANAB, and CDH10 genes in the High-CCDC80 group. Conclusion: Silencing CCDC80, a prognostic biomarker in patients with immune invasion of gastric cancer, could effectively inhibit the malignant characterization, M2 polarization, and tumor formation of gastric cancer. [ABSTRACT FROM AUTHOR]

Background: Experimental studies indicate that neuroendocrine pathways might play a role in progression of breast cancer. We aim to test the hypothesis that somatic mutations in the genes of neuroendocrine pathways influence breast cancer prognosis, through dysregulated gene expression in tumor tissue.Methods: We conducted an extreme case-control study including 208 breast cancer patients with poor invasive disease-free survival (iDFS) and 208 patients with favorable iDFS who were individually matched on molecular subtype from the Breast Cancer Cohort at West China Hospital (WCH; N = 192) and The Cancer Genome Atlas (TCGA; N = 224). Whole exome sequencing and RNA sequencing of tumor and paired normal breast tissues were performed. Adrenergic, glucocorticoid, dopaminergic, serotonergic, and cholinergic pathways were assessed for differences in mutation burden and gene expression in relation to breast cancer iDFS using the logistic regression and global test, respectively.Results: In the pooled analysis, presence of any somatic mutation (odds ratio = 1.66, 95% CI: 1.07-2.58) of the glucocorticoid pathway was associated with poor iDFS and a two-fold increase of tumor mutation burden was associated with 17% elevated odds (95% CI: 2-35%), after adjustment for cohort membership, age, menopausal status, molecular subtype, and tumor stage. Differential expression of genes in the glucocorticoid pathway in tumor tissue (P = 0.028), but not normal tissue (P = 0.701), was associated with poor iDFS. Somatic mutation of the adrenergic and cholinergic pathways was significantly associated with iDFS in WCH, but not in TCGA.Conclusion: Glucocorticoid pathway may play a role in breast cancer prognosis through differential mutations and expression. Further characterization of its functional role may open new avenues for the development of novel therapeutic targets for breast cancer. [ABSTRACT FROM AUTHOR]

Background: Neuroblastoma, a prevalent extracranial solid tumor in pediatric patients, demonstrates significant clinical heterogeneity, ranging from spontaneous regression to aggressive metastatic disease. Despite advances in treatment, high-risk neuroblastoma remains associated with poor survival. SLC1A5, a key glutamine transporter, plays a dual role in promoting tumor growth and immune modulation. However, its contributions to neuroblastoma biology remain largely unexplored. Methods: This study utilized clinical neuroblastoma samples from 20 patients and 1310 cases from four public datasets to investigate SLC1A5 expression, biological function, and prognostic significance. Differential expression, Kaplan–Meier survival analysis, gene set enrichment analysis, and weighted correlation network analysis were conducted. Functional validation included qPCR, immunohistochemistry, Western blotting, and cell proliferation assays using the SLC1A5 inhibitor V-9302. A prognostic signature, SRPS, was constructed and validated using machine-learning approaches. Immune infiltration analysis was performed to evaluate the tumor immune microenvironment. Results: SLC1A5 expression was significantly elevated in high-risk neuroblastoma and correlated with advanced stages and poor prognosis. GSEA revealed mTORC1 signaling enrichment in high SLC1A5 expression groups, validated by increased p-p70S6K levels in tumor samples and neuroblastoma cells. V-9302 treatment suppressed mTORC1 signaling and inhibited cell proliferation. Hub-genes were identified to form the SRPS model, which demonstrated superior prognostic performance compared to existing models. Immune infiltration analysis revealed a more immunosuppressive tumor microenvironment associated with high SLC1A5 expression. Additionally, SLC1A5 negatively regulated ST8SIA1, a gene crucial for GD2 biosynthesis, suggesting that SLC1A5 inhibition may enhance GD2-directed immunotherapies. Conclusion: SLC1A5 plays a pivotal role in neuroblastoma by promoting tumor progression and shaping an immunosuppressive microenvironment. The SRPS model, incorporating SLC1A5-associated genes, offers robust prognostic utility. Targeting SLC1A5 through advanced drug delivery systems and combined metabolic-immunotherapeutic strategies may enhance treatment specificity and efficacy. These findings provide a foundation for novel therapeutic approaches to improve outcomes in high-risk neuroblastoma patients. [ABSTRACT FROM AUTHOR]

Background: Bromodomain-containing protein (BRD) play a pivotal role in the development and progression of malignant tumours. This study aims to identify prognostic genes linked to BRD-related genes (BRDRGs) in patients with triple-negative breast cancer (TNBC) and to construct a novel prognostic model. Methods: Data from TCGA-TNBC, GSE135565, and GSE161529 were retrieved from public databases. GSE161529 was used to identify key cell types. The BRDRGs score in TCGA-TNBC was calculated using single-sample Gene Set Enrichment Analysis (ssGSEA). Differential expression analysis was performed to identify differentially expressed genes (DEGs): DEGs1 in key cells, DEGs2 between tumours and controls and DEGs3 in high and low BRDRGs score subgroups in TCGA-TNBC. Differentially expressed BRDRGs (DE-BRDRGs) were determined by overlapping DEGs1, DEGs2 and DEGs3. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein-protein interaction (PPI) network analysis were conducted to investigate active pathways and molecular interactions. Prognostic genes were selected through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses to construct a risk model and calculate risk scores. TNBC samples from TCGA-TNBC were classified into high and low-risk groups based on the median risk score. Additionally, correlations with clinical characteristics, Gene Set Enrichment Analysis (GSEA), immune analysis, and pseudotime analysis were performed. Results: A total of 120 DE-BRDRGs were identified by overlapping 605 DEGs1 from four key cell types, 10,776 DEGs2, and 4,497 DEGs3. GO analysis revealed enriched terms such as 'apoptotic process,' 'immune response,' and 'regulation of the cell cycle,' while 56 KEGG pathways, including the 'MAPK signaling pathway,' were associated with DE-BRDRGs. A risk model comprising six prognostic genes (KRT6A, PGF, ABCA1, EDNRB, CTSD and GJA4) was constructed. A nomogram based on independent prognostic factors was also developed. Immune cell abundance was significantly higher in high-risk group. In both risk groups, TP53 exhibited the highest mutation frequency. The expression of KRT6A, ABCA1, EDNRB, and CTSD went decreased progressively in pseudotime. Conclusion: A novel prognostic model for TNBC associated with BRDRGs was developed and validated, providing fresh insights into the relationship between BRD and TNBC. [ABSTRACT FROM AUTHOR]

Background: Methyltransferase-like (METTL) family protein plays a crucial role in the progression of malignancies. However, the function of METTL17 across pan-cancers, especially in hepatocellular carcinoma (HCC) is still poorly understood. Methods: All original data were downloaded from TCGA, GTEx, HPA, UCSC databases and various data portals. First, we comprehensively analyzed RNA-seq data from the HPA database of 25 human tissues. An array of bioinformatics methods was employed to explore the potential oncogenic roles of METTL17, including analyzing its related prognosis, mutation, landscapes, tumor stemness index, immune cell infiltration, and other factors among different tumors. Additionally, gene set enrichment analysis (GSEA) was used to analyze pathways associated with METTL17 in HCC. Immunohistochemistry (IHC) was performed on clinical samples to validate the differential expression of METTL17 in HCC and normal tissues. Ultimately, we constructed a METTL17-related risk-score model of HCC and validated its prognostic classification efficiency. Survival rates were calculated using the Kaplan-Meier method. Statistical significance was defined as P < 0.05. Results: METTL17 was differentially expressed in various cancers. METTL17 maintained strong correlations with the cancer patient's prognosis, genetic alterations, tumor stemness index, and immune-infiltrated cells, etc. In addition, IHC experiments verified that METTL expression was significantly decreased in liver tissues of HCC patients compared to normal liver tissue. GESA analysis indicated METTL17 mainly involves oncogenic and immune-related pathways among HCC. MRPS5, CHCHD2, NCBP1, LRPPRC, DAP3, and BMS1 were included in a prognostic model based on METTL17's interaction networks. Kaplan–Meier survival analysis of the prognostic model showed that the overall survival (OS) of the low-risk group was significantly better than that of the high-risk group (P < 0.001). The area under the receiver operating characteristic (ROC) curve (AUC) of the 1-year, 3-year, and 5-year OS were 0.747, 0.671, and 0.631, respectively. Conclusions: METTL17 may serve as a novel prognostic marker and therapeutic target for human tumors, offering a theoretical foundation for formulating more effective and tailored clinical treatment options for cancers, particularly HCC. [ABSTRACT FROM AUTHOR]

Background: HER2-positive breast cancer (BC) is a subtype of breast cancer. Increased ERBB3 expression has been implicated as a potential cause of resistance to other HER-targeted therapies. Our study aimed to screen and validate prognostic markers associated with ERBB3 expression by bioinformatics and affecting the prognosis of HER2 staging. Methods: Analyzing differences in ERBB3-related groups. ERBB3 expression-related differentially expressed genes (DEGs) were identified and intersected with survival status-related DEGs to obtain intersected genes. Three algorithms, LASSO, RandomForest and XGBoost were combined to identify the signature genes. we construct risk models and generate ROC curves for prediction. Furthermore, we delve into the immunological traits, correlations, and expression patterns of signature genes by conducting a comprehensive analysis that encompasses immune infiltration analysis, correlation analysis, and differential expression analysis. Results: Significant variability in ERBB3 expression and prognosis in high and low ERBB3 expression groups. Twenty-five candidate DEGs were identified by intersecting ERBB3-related DEGs with survival-related DEGs. Utilizing three distinct machine learning algorithms, we identified three signature genes-PBX1, IGHM, and CXCL13-that exhibited significant diagnostic value within the diagnostic model. In addition, the risk model had better prognostic and predictive effects, and the immune infiltration analysis showed that IGHM, CXCL13 might affect the proliferation of BC cells through immune cells. Functional studies demonstrated that interference with PBX1 inhibited the proliferation, migration, and epithelial-mesenchymal transition process of HER2-positive BC cells. Conclusion: PBX1, IGHM and CXCL13 are associated with the expression level of the ERBB3 and are prognostic markers for HER2-positive in BC, which may play an important role in the development and progression of BC. [ABSTRACT FROM AUTHOR]

Background: Due to the presence of both classical estrogen receptor (ERα) and another ER subtype (ERβ) in ovarian cancer, hormonal treatment is an attractive option. However, response to tamoxifen in ovarian cancer is modest. The presence of ERβ variants further complicated the issue. We have recently shown that specifically targeting ER subtypes using selective ER modulators showed opposing functions of ER subtypes on cell growth. In the present study, the clinical significance of ERα and ERβ variants (β1, β2 and β5) and the functional effects of ERβ2 and ERβ5 in ovarian cancer was investigated.Methods: ERα, ERβ1, ERβ2 and ERβ5 expression were evaluated by immunohistochemistry in 106 ovarian cancer tissues. The association between ERs expression and clinicopathological parameters or prognosis was analyzed. Ectopic expression of ERβ2 and ERβ5 followed by functional assays were performed in ovarian cancer cell lines in order to detect their effects on cell invasion and proliferation.Results: We found significantly higher nuclear (n)ERα and nERβ5 and lower cytoplasmic (c)ERα expression in advanced cancers. Significantly lower ERβ1 expression was also detected in high grade cancers. Significant loss of nERα and cERβ2 expression were observed in clear cell histological subtypes. Higher nERβ5 and lower cERβ5 expression were associated with serous/clear cell subtypes, poor disease-free and overall survival. Positive cERα and higher cERβ1 expression were significantly associated with better disease-free and overall survival. Furthermore, we found nERβ5 as an independent prognostic factor for overall survival. Functionally, overexpression of ERβ5 enhanced ovarian cancer cell migration, invasion and proliferation via FAK/c-Src activation whereas ERβ2 induced cell migration and invasion.Conclusions: Since tamoxifen binds to both ERα and ERβ1 which appear to bear opposing oncogenic roles, the histotypes-specific expression pattern of ERs indicates that personalized treatment for women based on ERs expression using selective estrogen receptor modulators may improve response rate. This study also suggests nERβ5 as a potential prognostic marker and therapeutic target in ovarian cancer. [ABSTRACT FROM AUTHOR]

Messenger RNA (mRNA)-based vaccines present a promising avenue for cancer immunotherapy; however, their application in cervical cancer remains unexplored. This study investigated the interplay between the regulated cell death pathways of cuproptosis and ferroptosis to advance the development of mRNA vaccines for cervical cancer. We identified key cuproptosis-related and ferroptosis-related genes (CFRGs) from public mRNA profiles and determined their prognostic significance, mutation frequencies, and effect on the immune landscape. Our analysis revealed two distinct subtypes of cervical cancer associated with CFRGs, with differences in prognosis and immune characteristics. Using LASSO, XGBoost, and SVM–RFE methods, we established a 4-gene prognostic signature (TSC22D3, SQLE, ZNF419, and TFRC) to stratify patients based on their risk and determine its correlation with immune microenvironment, mutation profiles, and treatment responses. RT-qPCR validation confirmed the differential expression of these genes in clinical samples. Our findings identify TSC22D3, SQLE, ZNF419, and TFRC as candidate targets for mRNA vaccine development and offer a potential prognostic tool for personalized cervical cancer treatment. [ABSTRACT FROM AUTHOR]

Background: Angiogenesis is associated with tumour growth, infiltration, and metastasis. This study aimed to detect the mechanisms of angiogenesis-related genes (ARGs) in multiple myeloma (MM) and to construct a new prognostic model. Methods: MM research foundation (MMRF)-CoMMpass cohort, GSE47552, GSE57317, and ARGs were sourced from public databases. Differentially expressed genes (DEGs) in the tumour and control cohorts in GSE47552 were determined through differential expression analysis and were enriched with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Weighted gene coexpression network analysis (WGCNA) was applied to derive modules linked to the ARG scores and obtain module genes in GSE47552. Differentially expressed ARGs (DE-ARGs) were selected for subsequent analyses by overlapping DEGs and module genes. Furthermore, prognostic genes were selected using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. Depending on the prognostic genes, a risk model was constructed, and risk scores were determined. Moreover, MM samples from MMRF-CoMMpass were sorted into high- and low-risk teams on account of the median risk score. Additionally, correlations among clinical characteristics, gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), immune analysis, immunotherapy predictions and the mRNA‒miRNA‒lncRNA network were carried out. Results: A total of 898 DEGs, 211 module genes, 24 DE-ARGs and three prognostic genes (AKAP12, C11orf80 and EMP1) were selected for this study. Enrichment analysis revealed that the DEGs were related to 86 GO terms, such as 'cytoplasmic translation', and 41 KEGG pathways, such as 'small cell lung cancer'. A prognostic gene-based risk model was created in MMRF-CoMMpass and confirmed with the GSE57317 dataset. Moreover, a nomogram was established on the basis of independent prognostic factors that have proven to be good predictors. In addition, the immune cell infiltration results suggested that memory B cells were enriched in the high-risk group and that immature B cells were enriched in the low-risk group. Finally, the mRNA‒miRNA‒lncRNA network demonstrated that hsa-miR-508-5p was tightly associated with EMP1 and AKAP12. RT‒qPCR was used to validate the expression of the genes associated with prognosis. Conclusion: A new prognostic model of MM associated with ARGs was created and validated, providing a new perspective for exploring the connection between ARGs and MM. [ABSTRACT FROM AUTHOR]

Background: Identification of patients with oral dysplasia at high risk of cancer development and oral squamous cell carcinoma (OSCC) at increased risk of disease recurrence will enable rigorous personalized treatment. Regulated intramembranous proteolysis of Epithelial cell adhesion molecule (EpCAM) resulting in release of its intracellular domain Ep-ICD into cytoplasm and nucleus triggers oncogenic signaling. We analyzed the expression of Ep-ICD in oral dysplasia and cancer and determined its clinical significance in disease progression and prognosis.Methods: In a retrospective study, immunohistochemical analysis of nuclear and cytoplasmic Ep-ICD and EpEx (extracellular domain of EpCAM), was carried out in 115 OSCC, 97 oral dysplasia and 105 normal oral tissues, correlated with clinicopathological parameters and disease outcome over 60 months for oral dysplasia and OSCC patients. Disease-free survival (DFS) was determined by Kaplan-Meier method and multivariate Cox regression analysis.Results: In comparison with normal oral tissues, significant increase in nuclear Ep-ICD and membrane EpEx was observed in dysplasia, and OSCC (p = 0.013 and < 0.001 respectively). Oral dysplasia patients with increased overall Ep-ICD developed cancer in short time period (mean = 47 months; p = 0.044). OSCC patients with increased nuclear Ep-ICD and membrane EpEx had significantly reduced mean DFS of 33.7 months (p = 0.018).Conclusions: Our study provided clinical evidence for Ep-ICD as a predictor of cancer development in patients with oral dysplasia and recurrence in OSCC patients, suggesting its potential utility in enhanced management of those patients detected to have increased risk of progression to cancer and recurrence in OSCC patients. [ABSTRACT FROM AUTHOR]

Background: We assessed the expression of methylation-related proteins 5-meC, DNMT1, and ISL-1 in breast cancer and evaluated their relationship to clinicopathological factors.Methods: Immunohistochemical staining for ER, PR, HER-2, Ki-67, 5-meC, DNMT1, and ISL-1 were performed on 348 breast cancer samples in tissue microarray. Samples were subgrouped into luminal A, luminal B, HER-2, or triple-negative breast cancer (TNBC) according to immunohistochemical staining for ER, PR, HER-2, and Ki-67. The tumor stroma was histologically subtyped into desmoplastic, sclerotic, normal-like, or inflammatory type.Results: Tumor expression of DNMT1 differed by molecular subtype: it was higher in TNBC and lower in luminal A (p < 0.001) samples. DNMT1 expression was also related to higher histologic grade, ER negativity, PR negativity, and higher Ki-67 LI (p < 0.001). In western blot, protein expressions of DNMT1 and ISL-1 were higher in TNBC and relatively lower in the remaining subtypes. High tumor expression of DNMT1 was associated with shorter OS in univariate analysis (p = 0.041). DNMT1 and 5-meC were differentially expressed by stromal phenotype: 5-meC was higher in normal-like type and lower in sclerotic type (p = 0.049); DNMT1 was higher in inflammatory and lower in sclerotic type (p < 0.001).Conclusions: Tumor expression of DNMT1 in breast cancer differed by molecular subtype and stromal histological type. DNMT1 was highly expressed in TNBC and in breast cancer with inflammatory stromal type. [ABSTRACT FROM AUTHOR]

Background: Phosducin-like 3 (PDCL3) is a member of the photoreceptor family, characterized by a thioredoxin-like structural domain and evolutionary conservation. It plays roles in angiogenesis and apoptosis. Despite its significance, research on the biological role of PDCL3 in liver hepatocellular carcinoma (LIHC) remains limited. This study aims to explore the prognostic value and potential mechanisms of PDCL3 in cancer, particularly in LIHC, through bioinformatics analysis. Methods: RNA-seq data and corresponding clinical information for pan-cancer and LIHC were extracted from the TCGA database to analyze PDCL3 expression and survival prognosis. Differential expression of PDCL3 was analyzed using the HPA database. GO and KEGG enrichment analysis were performed for PDCL3-associated genes. The relationship between PDCL3 expression and various immune cell types was examined using the TIMER website. Clinical samples were collected, and immunohistochemistry and immunofluorescence experiments were conducted to validate the differential expression of PDCL3 in LIHC and normal tissues. In vitro assays, including CCK-8, wound healing, Transwell, and colony formation experiments, were employed to determine the biological functions of PDCL3 in LIHC cells. Results: Analysis from TIMER, GEPIA, UALCAN, and HPA databases revealed differential expression of PDCL3 in various tumors. Prognostic analysis from GEPIA and TCGA databases indicated that high PDCL3 expression was associated with poorer clinical staging and prognosis in LIHC. Enrichment analysis of PDCL3-associated genes revealed its involvement in various immune responses. TCGA and TIMER databases showed that high PDCL3 expression in LIHC decreased tumor immune activity by reducing macrophage infiltration. PDCL3 exhibited positive correlations with multiple immune checkpoint genes. Immunohistochemistry (IHC) and immunofluorescence (IF) experiments confirmed elevated PDCL3 expression in LIHC tissues compared to adjacent normal tissues. In vitro experiments demonstrated that PDCL3 promoted LIHC cell proliferation, migration, invasion, and colony-forming ability. Conclusion: PDCL3 is highly expressed in various cancer types. Our study suggests that elevated PDCL3 expression in hepatocellular carcinoma is associated with poorer prognosis and may serve as a potential diagnostic biomarker for LIHC. PDCL3 may regulate the biological functions of LIHC by modulating immune infiltration. However, the precise regulatory mechanisms of PDCL3 in cancer warrant further investigation. [ABSTRACT FROM AUTHOR]

Cuproptosis and disulfidptosis, recently discovered mechanisms of cell death, have demonstrated that differential expression of key genes and long non-coding RNAs (lncRNAs) profoundly influences tumor development and affects their drug sensitivity. Clear cell renal cell carcinoma (ccRCC), the most common subtype of kidney cancer, presently lacks research utilizing cuproptosis and disulfidptosis-related lncRNAs (CDRLRs) as prognostic markers. In this study, we analyzed RNA-seq data, clinical information, and mutation data from The Cancer Genome Atlas (TCGA) on ccRCC and cross-referenced it with known cuproptosis and disulfidptosis-related genes (CDRGs). Using the LASSO machine learning algorithm, we identified four CDRLRs—ACVR2B-AS1, AC095055.1, AL161782.1, and MANEA-DT—that are strongly associated with prognosis and used them to construct a prognostic risk model. To verify the model's reliability and validate these four CDRLRs as significant prognostic factors, we performed dataset grouping validation, followed by RT-qPCR and external database validation for differential expression and prognosis of CDRLRs in ccRCC. Gene function and pathway analysis were conducted using Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) for high- and low-risk groups. Additionally, we have analyzed the tumor mutation burden (TMB) and the immune microenvironment (TME), employing the oncoPredict and Immunophenoscore (IPS) algorithms to assess the sensitivity of diverse risk categories to targeted therapeutics and immunosuppressants. Our predominant objective is to refine prognostic predictions for patients with ccRCC and inform treatment decisions by conducting an exhaustive study on cuproptosis and disulfidptosis. [ABSTRACT FROM AUTHOR]

Purpose: This research probes into genes related to the risk of concurrent kidney injury in septic patients to provide reliable targets for early identification of sepsis-associated kidney injury and prognosis research. Methods: Peripheral blood samples were isolated from 10 healthy individuals and 22 septic patients for RNA sequencing and differential analyses. Meanwhile, the top 1000 kidney-associated genes were chosen from the GTEx website. Subsequently, DEGs in sepsis were intersected with kidney-specific genes, followed by GO and KEGG analyses on these intersection genes. The predictive ability of hub genes for prognosis was evaluated using survival analysis. A meta-analysis was carried out to determine the differential expression profiles of hub genes between the sepsis surviving and dead groups. ROC curves were plotted to screen hub genes and clarify their diagnostic value. Cell line localization of hub genes was further clarified through single-cell RNA sequencing. Results: There were 40 targets in the intersection between 1328 DEGs in sepsis and 1000 kidney-associated genes. These intersection genes were mainly engaged in functions and signaling pathways.Survival curves linked the higher levels of CD74 and IL32 to raised survival rates of patients, indicating positive correlations of CD74 and IL32 with patient prognosis. Meta-analysis revealed that CD74 and IL32 were highly expressed in the sepsis surviving group but poorly expressed in the sepsis dead group, showing statistically significant differences between these two groups. In the ROC analysis of hub genes, AUC values of CD74 (0.983) and IL32 (0.980) suggested their high diagnostic value. Lastly, CD74 was principally expressed in macrophages, while IL32 was mainly presented in T cells. Conclusion: CD74 and IL32, as biomarkers for early diagnosis and prognostic evaluation of sepsis complicated with kidney injury, are highly expressed in macrophages and T cells, respectively, providing new diagnostic and prognostic targets for sepsis complicated with acute kidney injury. [ABSTRACT FROM AUTHOR]

Ovarian cancer (OC) remains the primary cause of mortality among gynecological malignancies, and the identification of reliable molecular biomarkers to prognosticate OC outcomes is yet to be achieved. The gene palmitoyl protein thioesterase 2 (PPT2), which has been sparsely studied in OC, was closely associated with metabolism. This study aimed to determine the association between PPT2 expression, prognosis, immune infiltration, and potential molecular mechanisms in OC. We obtained the RNA-seq and clinical data from The Cancer Genome Atlas (TCGA), The Genotype-Tissue Expression (GTEx) and Gene Expression Omnibus (GEO) databases, then Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, nomogram, and calibration were conducted to assess and verify the role of PPT2. Gene set enrichment analysis (GSEA) was used to figure out the closely correlated pathways with PPT2. Overexpression experiment was performed to explore the function of PPT2. Our findings showed that PPT2 mRNA expression was apparent down-regulation in OC tissue compared to normal ovarian tissues in TCGA, GTEx datasets, and GEO datasets. This differential expression was also confirmed in our in-house datasets at both the mRNA and protein levels. Decreased PPT2 expression correlated with lower survival rates in TCGA, several GEO datasets, and our in-house datasets. Multivariate analysis revealed that PPT2 was an independent factor in predicting better outcomes for OC patients in TCGA and GEO. A negative correlation was revealed between immune infiltration and PPT2 expression through Single-sample GSEA (ssGSEA). Additionally, PPT2 was negatively correlated with an up-regulated immune score, stromal score, and estimate score, suggesting that patients with low PPT2 expression might benefit more from immunotherapy. Numerous chemical agents showed lower IC50 in patients with high PPT2 expression. In single-cell RNA sequencing (scRNA-seq) analysis of several OC datasets, we found PPT2 was mainly expressed in endothelial cells. Furthermore, we found that PPT2 inhibited OC cell proliferation in vitro. Our results demonstrated that PPT2 was considered a favorable prognostic biomarker for OC and may be vital in predicting response to immunotherapy and chemotherapy. Further research was needed to fully understand the relationship between PPT2 and immunotherapy efficacy in OC patients. [ABSTRACT FROM AUTHOR]

Background: Ficolins (FCNs) are a family of proteins, comprising FCN1, FCN2 and FCN3, and integral to the immune system which have been implicated in the onset and progression of tumors. Despite their recognized roles, a comprehensive analysis of FCNs in lung cancer remains elusive. Methods: We employed a variety of bioinformatics tools, including UCSC, SangerBox, Ualcan, cBioPortal, String, Metascape, GeneMANIA, TIDE, CTD, and CAMP databases to investigate the differential expression, diagnostic and prognostic significance, genetic alterations, functional enrichment, immune infiltration, and potential immunotherapeutic implications of FCN1, FCN2, and FCN3 in lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD). Additionally, RT-qPCR and immunohistochemistry were utilized to validate the expressions of FCNs at the mRNA and protein levels in LUSC and LUAD. Results: Our comprehensive bioinformatic analysis, supported by RT-qPCR and immunohistochemistry, revealed that the expressions of FCN1, FCN2 and FCN3 were consistently downregulated in both LUSC and LUAD tumor tissues. FCNs demonstrated significant diagnostic potential for LUSC and LUAD, with the area under the receiver operating characteristic curve (AUC) for FCN1 and FCN3 exceeding 0.90. Furthermore, FCN2 and FCN3 showed a strong negative correlation with overall survival (OS) in LUSC, whereas FCN1 and FCN2 were positively correlated with OS in LUAD, suggesting their prognostic value in lung cancer. Gene enrichment analysis indicated that FCNs were predominantly associated with the complement system and complement activation pathways. Immune infiltration analysis further revealed a significant positive correlation between FCNs and the presence of neutrophils and resting mast cells. Our analysis of immunotherapy outcomes revealed a significant disparity in the immunophenoscore (IPS) among lung cancer patients treated with immune checkpoint inhibitors (ICIs), distinguishing those with high FCN expression from those with low FCN expression. Additionally, we identified small molecule compounds related to FCNs and drugs pertinent to LUSC and LUAD. Conclusion: FCNs held promise as diagnostic and prognostic biomarkers for LUSC and LUAD. This study also elucidated the relationship of FCNs with the tumor microenvironment, offering novel insights into the immunotherapeutic landscape for LUSC and LUAD. [ABSTRACT FROM AUTHOR]

Background: Prostate cancer is one of the most common cancers in men with a significant proportion of patients developing biochemical recurrence (BCR) after treatment. Programmed cell death (PCD) mechanisms are known to play critical roles in tumor progression and can potentially serve as prognostic and therapeutic biomarkers in PCa. This study aimed to develop a prognostic signature for BCR in PCa using PCD-related genes. Materials and methods: We conducted an analysis of 19 different modes of PCD to develop a comprehensive model. Bulk transcriptomic, single-cell transcriptomic, genomic, and clinical data were collected from multiple cohorts, including TCGA-PRAD, GSE58812, METABRIC, GSE21653, and GSE193337. We analyzed the expression and mutations of the 19 PCD modes and constructed, evaluated, and validated the model. Results: Ten PCD modes were found to be associated with BCR in PCa, with specific PCD patterns exhibited by various cell components within the tumor microenvironment. Through Lasso Cox regression analysis, we established a Programmed Cell Death Index (PCDI) utilizing an 11-gene signature. High PCDI values were validated in five independent datasets and were found to be associated with an increased risk of BCR in PCa patients. Notably, older age and advanced T and N staging were associated with higher PCDI values. By combining PCDI with T staging, we constructed a nomogram with enhanced predictive performance. Additionally, high PCDI values were significantly correlated with decreased drug sensitivity, including drugs such as Docetaxel and Methotrexate. Patients with lower PCDI values demonstrated higher immunophenoscores (IPS), suggesting a potentially higher response rate to immune therapy. Furthermore, PCDI was associated with immune checkpoint genes and key components of the tumor microenvironment, including macrophages, T cells, and NK cells. Finally, clinical specimens validated the differential expression of PCDI-related PCDRGs at both the gene and protein levels. Conclusion: In conclusion, we developed a novel PCD-based prognostic feature that successfully predicted BCR in PCa patients and provided insights into drug sensitivity and potential response to immune therapy. These findings have significant clinical implications for the treatment of PCa. [ABSTRACT FROM AUTHOR]

Background: Treatment of gliomas, the most prevalent primary malignant neoplasm of the central nervous system, is challenging. Arachidonate 5-lipoxygenase activating protein (ALOX5AP) is crucial for converting arachidonic acid into leukotrienes and is associated with poor prognosis in multiple cancers. Nevertheless, its relationship with the prognosis and the immune microenvironment of gliomas remains incompletely understood. Methods: The differential expression of ALOX5AP was evaluated based on public Databases. Kaplan–Meier, multivariate Cox proportional hazards regression analysis, time-dependent receiver operating characteristic, and nomogram were used to estimate the prognostic value of ALOX5AP. The relationship between ALOX5AP and immune infiltration was calculated using ESTIMATE and CIBERSORT algorithms. Relationships between ALOX5AP and human leukocyte antigen molecules, immune checkpoints, tumor mutation burden, TIDE score, and immunophenoscore were calculated to evaluate glioma immunotherapy response. Single gene GSEA and co-expression network-based GO and KEGG enrichment analysis were performed to explore the potential function of ALOX5AP. ALOX5AP expression was verified using multiplex immunofluorescence staining and its prognostic effects were confirmed using a glioma tissue microarray. Result: ALOX5AP was highly expressed in gliomas, and the expression level was related to World Health Organization (WHO) grade, age, sex, IDH mutation status, 1p19q co-deletion status, MGMTp methylation status, and poor prognosis. Single-cell RNA sequencing showed that ALOX5AP was expressed in macrophages, monocytes, and T cells but not in tumor cells. ALOX5AP expression positively correlated with M2 macrophage infiltration and poor immunotherapy response. Immunofluorescence staining demonstrated that ALOX5AP was upregulated in WHO higher-grade gliomas, localizing to M2 macrophages. Glioma tissue microarray confirmed the adverse effect of ALOX5AP in the prognosis of glioma. Conclusion: ALOX5AP is highly expressed in M2 macrophages and may act as a potential biomarker for predicting prognosis and immunotherapy response in patients with glioma. [ABSTRACT FROM AUTHOR]

Background: Epithelial ovarian carcinoma (EOC) is a prevalent gynaecological malignancy. The prognosis of patients with EOC is related to acetylation modifications and immune responses in the tumour microenvironment (TME). However, the relationships between acetylation-related genes, patient prognosis, and the tumour immune microenvironment (TIME) are not yet understood. Our research aims to investigate the link between acetylation and the tumour microenvironment, with the goal of identifying new biomarkers for estimating survival of patients with EOC. Methods: Using data downloaded from the tumour genome atlas (TCGA), genotypic tissue expression (GTEx), and gene expression master table (GEO), we comprehensively evaluated acetylation-related genes in 375 ovarian cancer specimens and identified molecular subtypes using unsupervised clustering. The prognosis, TIME, stem cell index and functional concentration analysis were compared among the three groups. A risk model based on differential expression of acetylation-related genes was established through minimum absolute contraction and selection operator (LASSO) regression analysis, and the predictive validity of this feature was validated using GEO data sets. A nomogram is used to predict a patient's likelihood of survival. In addition, different EOC risk groups were evaluated for timing, tumour immune dysfunction and exclusion (TIDE) score, stemness index, somatic mutation, and drug sensitivity. Results: We used the mRNA levels of the differentially expressed genes related to acetylation to classify them into three distinct clusters. Patients with increased immune cell infiltration and lower stemness scores in cluster 2 (C2) exhibited poorer prognosis. Immunity and tumourigenesis-related pathways were highly abundant in cluster 3 (C3). We developed a prognostic model for ten differentially expressed acetylation-related genes. Kaplan–Meier analysis demonstrated significantly worse overall survival (OS) in high-risk patients. Furthermore, the TIME, tumour immune dysfunction and exclusion (TIDE) score, stemness index, tumour mutation burden (TMB), immunotherapy response, and drug sensitivity all showed significant correlations with the risk scores. Conclusions: Our study demonstrated a complex regulatory mechanism of acetylation in EOC. The assessment of acetylation patterns could provide new therapeutic strategies for EOC immunotherapy to improve the prognosis of patients. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) is a serious global health burden because of its high morbidity and mortality rates. Hypoxia and massive lactate production are hallmarks of the CRC microenvironment. However, the effects of hypoxia and lactate metabolism on CRC have not been fully elucidated. This study aimed to develop a novel molecular subtyping based on hypoxia-related genes (HRGs) and lactate metabolism-related genes (LMRGs) and construct a signature to predict the prognosis of patients with CRC and treatment efficacy. Methods: Bulk and single-cell RNA-sequencing and clinical data of CRC were downloaded from the TCGA and GEO databases. HRGs and LMRGs were obtained from the Molecular Signatures Database. The R software package DESeq2 was used to perform differential expression analysis. Molecular subtyping was performed using unsupervised clustering. A predictive signature was developed using univariate Cox regression, random forest model, LASSO, and multivariate Cox regression analyses. Finally, the sensitivity of tumor cells to chemotherapeutic agents before and after hypoxia was verified using in vitro experiments. Results: We classified 575 patients with CRC into three molecular subtypes and were able to distinguish their prognoses clearly. The C1 subtype, which exhibits high levels of hypoxia, has a low proportion of CD8 + T cells and a high proportion of macrophages. The expression of immune checkpoint genes is generally elevated in C1 patients with severe immune dysfunction. Subsequently, we constructed a predictive model, the HLM score, which effectively predicts the prognosis of patients with CRC and the efficacy of immunotherapy. The HLM score was validated in GSE39582, GSE106584, GSE17536, and IMvigor210 datasets. Patients with high HLM scores exhibit high infiltration of CD8 + exhausted T cells (Tex), especially terminal Tex, and oxidative phosphorylation (OXPHOS)−Tex in the immune microenvironment. Finally, in vitro experiments confirmed that CRC cell lines were less sensitive to 5-fluorouracil, oxaliplatin, and irinotecan under hypoxic conditions. Conclusion: We constructed novel hypoxia- and lactate metabolism-related molecular subtypes and revealed their immunological and genetic characteristics. We also developed an HLM scoring system that could be used to predict the prognosis and efficacy of immunotherapy in patients with CRC. [ABSTRACT FROM AUTHOR]

Background: Hepatocellular carcinoma (HCC) is a primary liver malignancy that is now relatively common worldwide. TMEM79 has been reported to play diagnostic and prognostic markers in a variety of cancers and was found to be closely associated with immune infiltration. SMG5 is associated with immune cell infiltration in HCC. Multiple nonsense-mediated mRNA processes require the involvement of SMG5. TMEM79 and SMG5 complexes may be prognostic markers for prostate cancer. However, the relationship between TMEM79 expression in HCC and prognosis, its role and mechanism of action, and its relationship with SMG5 have not been studied. This article focuses on not only the prognostic role of TMEM79 and its biological significance, including immuno-infiltration, tumor mutations and drug sensitivity, but also the interaction with SMG5 in HCC. Methods: Differential expression analysis and the multiCox proportional hazards regression analyses of TMEM79 and SMG5 were performed by multiple databases. Then, use IHC to verify our results. Subsequently, we used R software to analyze the clinical phenotype of both: analysis of clinicopathological features, enrichment analysis, analysis of immune infiltration, analysis of immune checkpoints, analysis of drug sensitivity, and immunotherapy. Results: Both the database studies and the results of our research group showed that TMEM79 and SMG5 were differentially expressed in HCC and normal tissues. Validation of immunohistochemistry showed that differential expression of TMEM79 and SMG5, which influenced the prognosis of patients with HCC, could be an independent prognostic factor. Results of the TCGA database study showed that TMEM79 and SMG5 were correlated with immune infiltration, immune checkpoints, drug sensitivity, and immunotherapy. We typed TMEM79-related molecules in HCC according to R software. Two types of TMEM79 correlated with clinical features, survival of patients with HCC, and immune infiltration. Conclusion: TMEM79 are highly expressed in HCC and play an important role in the prognosis of patients with HCC. TMEM79 and SMG5 are positively correlated and may both associated with immune infiltration, and closely linked to immune checkpoints, drug sensitivity, and immunotherapy in HCC. [ABSTRACT FROM AUTHOR]

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest tumors worldwide, with extremely aggressive and complicated biology. Krüppel-like factors (KLFs) encode a series of transcriptional regulatory proteins and play crucial roles in a variety of processes, including tumor cell differentiation and proliferation. However, the potential biological functions and possible pathways of KLFs in the progression of PDAC remain elusive. Methods: We systematically evaluated the transcriptional variations and expression patterns of KLFs in pancreatic cancer from the UCSC Xena. Based on difference analysis, the non-negative matrix factorization (NMF) algorithm was utilized to identify the immune characteristics and clinical significance of two different subtypes. The multivariate Cox regression was used to construct the risk model and then explore the differences in tumor immune microenvironment (TIME) and drug sensitivity between high and low groups. Through single-cell RNA sequencing (scRNA-seq) analysis, we screened KLF6 and further investigated its biological functions in pancreatic cancer and pan-cancer. Results: The KLFs exhibited differential expression and mutations in the transcriptomic profile of PDAC. According to the expression of KLFs, patients were classified into two distinct subtypes, each exhibiting significant differences in prognosis and TIME. Moreover, the KLF signature was developed using univariate Cox and Lasso regression, which proved to be a reliable and effective prognostic model. Furthermore, the KLF_Score was closely associated with immune infiltration, response to immunotherapy, and drug sensitivity and we screened small molecule compounds targeting prognostic genes separately. Through scRNA-seq analysis, KLF6 was selected to further demonstrate its role in the malignance of PC in vitro. Finally, pan-cancer analysis emphasized the biological significance of KLF6 in multiple types of tumors and its clinical utility in assessing cancer prognosis. Conclusion: This study elucidated the pivotal role of KLF family genes in the malignant development of PC through comprehensive analysis and revealed that KLF6 would be a novel diagnostic biomolecule marker and potential therapeutic target for PDAC. [ABSTRACT FROM AUTHOR]

Background: Accumulating evidences indicate that the specific alternative splicing (AS) events are linked to the occurrence and prognosis of gastric cancer (GC). Nevertheless, the impact of AS is still unclear and needed to further elucidation. Methods: The expression profile of GC and normal samples were downloaded from TCGA. AS events were achieved from SpliceSeq database. Cox regression together with LASSO analysis were employed to identify survival-associated AS events (SASEs) and calculate risk scores. PPI and pathway enrichment analysis were implemented to determine the function and pathways of these genes. Kaplan-Meier (K-M) analysis and Receiver Operating Characteristic Curves were used to evaluate the clinical significance of genes of SASEs. Q-PCR were applied to validate the hub genes on the survival prognosis in 47 GC samples. Drug sensitivity and immune cell infiltration analysis were conducted. Results: In total, 48 140 AS events in 10 610 genes from 361 GC and 31 normal samples were analyzed. Through univariate Cox regression, 855 SASEs in 763 genes were screened out. Further, these SASEs were analyzed by PPI and 17 hub genes were identified. Meanwhile, using Lasso and multivariate Cox regression analysis, 135 SASEs in 132 genes related to 7 AS forms were further screened and a GC prognostic model was constructed. K-M curves indicates that high-risk group has poorer prognosis. And the nomogram analysis on the basis of the multivariate Cox analysis was disclosed the interrelationships between 7 AS forms and clinical parameters in the model. Five key genes were then screened out by PPI analysis and Differential Expression Gene analysis based on TCGA and Combined-dataset, namely STAT3, RAD51B, SOCS2, POLE2 and TSR1. The expression levels of AS in STAT3, RAD51B, SOCS2, POLE2 and TSR1 were all significantly correlated with survival by qPCR verification. Nineteen drugs were sensitized to high-risk patients and eight immune cells showed significantly different infiltration between the STAD and normal groups. Conclusions: In this research, the prognostic model constructed by SASEs can be applied to predict the prognosis of GC patients and the selected key genes are expected to become new biomarkers and therapeutical targets for GC treatment. [ABSTRACT FROM AUTHOR]

Background The treatment of lung adenocarcinoma is difficult due to the limited therapeutic options. Cancerassociated fibroblasts play an important role in the development of cancers. This study aimed to identify a promising molecular target associated with cancer-associated fibroblasts for the treatment of lung adenocarcinoma. Methods The Cancer Genome Atlas lung adenocarcinoma dataset was used to screen hub genes associated with cancer-associated fibroblasts via the EPIC algorithm and Weighted Gene Co-expression Network Analysis. Multiple databases were used together with our data to verify the differential expression and survival of COL11A1. Functional enrichment analysis and the single-cell TISCH database were used to elucidate the mechanisms underlying COL11A1 expression. The correlation between COL11A1 and immune checkpoint genes in human cancers was also evaluated. Results Using the EPIC algorithm and Weighted Gene Co-expression Network Analysis, 13 hub genes associated with cancer-associated fibroblasts in lung adenocarcinoma were screened. Using the GEPIA database, Kaplan-Meier Plotter database, GSE72094, GSE75037, GSE32863, and our immunohistochemistry experiment data, we confirmed that COL11A1 overexpresses in lung adenocarcinoma and that high expression of COL11A1 is associated with a poor prognosis. COL11A1 has a genetic alteration frequency of 22% in patients with lung adenocarcinoma. COL11A1 is involved in the extracellular matrix activities of lung adenocarcinoma. Using the TISCH database, we found that COL11A1 is mainly expressed by cancer-associated fibroblasts in the tumor microenvironment rather than by lung adenocarcinoma cells. Finally, we found that COL11A1 is positively correlated with HAVCR2(TIM3), CD274 (PD-L1), CTLA4, and LAG3 in lung adenocarcinoma. Conclusion COL11A1 may be expressed and secreted by cancer-associated fibroblasts, and a high expression of COL11A1 may result in T cell exhaustion in the tumor microenvironment of lung adenocarcinoma. COL11A1 may serve as an attractive biomarker to provide new insights into cancer therapeutics. [ABSTRACT FROM AUTHOR]

Background: N1-methyladenosine (m1A), among the most common internal modifications on RNAs, has a crucial role to play in cancer development. The purpose of this study were systematically investigate the modification characteristics of m1A in hepatocellular carcinoma (HCC) to unveil its potential as an anticancer target and to develop a model related to m1A modification characteristics with biological functions. This model could predict the prognosis for patients with HCC. Methods: An integrated analysis of the TCGA-LIHC database was performed to explore the gene signatures and clinical relevance of 10 m1A regulators. Furthermore, the biological pathways regulated by m1A modification patterns were investigated. The risk model was established using the genes that showed differential expression (DEGs) between various m1A modification patterns and autophagy clusters. These in vitro experiments were subsequently designed to validate the role of m1A in HCC cell growth and autophagy. Immunohistochemistry was employed to assess m1A levels and the expression of DEGs from the risk model in HCC tissues and paracancer tissues using tissue microarray. Results: The risk model, constructed from five DEGs (CDK5R2, TRIM36, DCAF8L, CYP26B, and PAGE1), exhibited significant prognostic value in predicting survival rates among individuals with HCC. Moreover, HCC tissues showed decreased levels of m1A compared to paracancer tissues. Furthermore, the low m1A level group indicated a poorer clinical outcome for patients with HCC. Additionally, m1A modification may positively influence autophagy regulation, thereby inhibiting HCC cells proliferation under nutrient deficiency conditions. Conclusions: The risk model, comprising m1A regulators correlated with autophagy and constructed from five DEGs, could be instrumental in predicting HCC prognosis. The reduced level of m1A may represent a potential target for anti-HCC strategies. [ABSTRACT FROM AUTHOR]

Purpose: Establishment of sister chromatid cohesion N-acetyltransferase 2 (ESCO2) is involved in the mitotic S-phase adhesins acetylation and is responsible for bridging two sister chromatids. However, present ESCO2 cancer research is limited to a few cancers. No systematic pan-cancer analysis has been conducted to investigate its role in diagnosis, prognosis, and effector function. Methods: We thoroughly examined the ESCO2 carcinogenesis in pan-cancer by combining public databases such as The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project (GTEx), UALCAN and Tumor Immune Single-cell Hub (TISCH). The analysis includes differential expression analysis, survival analysis, cellular effector function, gene mutation, single cell analysis, and tumor immune cell infiltration. Furthermore, we confirmed ESCO2's impacts on clear cell renal cell carcinoma (ccRCC) cells' proliferative and invasive capacities in vitro. Results: In our study, 30 of 33 cancer types exhibited considerably greater levels of ESCO2 expression in tumor tissue using TCGA and GTEx databases, whereas acute myeloid leukemia (LAML) exhibited significantly lower levels. Kaplan-Meier survival analyses in adrenocortical carcinoma (ACC), kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), brain lower grade glioma (LGG), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), mesothelioma (MESO), and pancreatic adenocarcinoma (PAAD) demonstrated that tumor patients with high ESCO2 expression have short survival periods. However, in thymoma (THYM), colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ), ESCO2 was a favorable prognostic factor. Moreover, ESCO2 expression positively correlates with tumor stage and tumor size in several cancers, including LIHC, KIRC, KIRP and LUAD. Function analysis revealed that ESCO2 participates in mitosis, cell cycle, DNA damage repair, and other processes. CDK1 was identified as a downstream gene regulated by ESCO2. Furthermore, ESCO2 might also be implicated in immune cell infiltration. Finally, ESCO2'S knockdown significantly inhibited the A498 and T24 cells' proliferation, invasion, and migration. Conclusions: In conclusion, ESCO2 is a possible pan-cancer biomarker and oncogene that can reliably predict the prognosis of cancer patients. ESCO2 was also implicated in the cell cycle and proliferation regulation. In a nutshell, ESCO2 is a therapeutically viable and dependable target. [ABSTRACT FROM AUTHOR]

Background: The prevalence of lung adenocarcinoma (LUAD) has increased, thus novel biomarkers for its early diagnosis is becoming more important than ever. tRNA-derived small RNA (tsRNA) is a new class of non-coding RNA which has important regulatory roles in cancer biology. This study was designed to identify novel predictive and prognostic tsRNA biomarkers. Methods: tsRNAs were identified and performed differential expression analysis from 10 plasma samples (6 LUAD and 4 normal, SRP266333) and 96 tissue samples (48 LUAD and 48 normal, SRP133217). Then a tsRNA-mRNA regulatory network was constructed to find hub tsRNAs. Functional enrichment analysis was performed to infer the potential pathways associated with tsRNAs. Afterwards, a Support Vector Machine (SVM) algorithm was used to explore the potential biomarkers for diagnosing LUAD. Lastly, the function of tRF-21-RK9P4P9L0 was explored in A549 and H1299 cell lines. Results: A significant difference of read distribution was observed between normal people and LUAD patients whether in plasma or tissue. A tsRNA-mRNA regulatory network consisting of 155 DEtsRNAs (differential expression tsRNAs) and 406 DEmRNAs (differential expression mRNAs) was established. Three tsRNAs (tRF-16-L85J3KE, tRF-21-RK9P4P9L0 and tRF-16-PSQP4PE) were identified as hub genes with degree > 100. We found Co-DEmRNAs (intersection of DEtsRNAs target mRNAs and differentially expressed mRNAs in LUAD) were engaged in a number of cancer pathways. The AUC of the three hub tsRNAs' expression for diagnosing LUAD reached 0.92. Furthermore, the qPCR validation of the three hub tsRNAs in 37 paired normal and LUAD tissues was consistent with the RNA-Seq results. In addition, tRF-21-RK9P4P9L0 was negatively associated with LUAD prognosis. Inhibition of tRF-21-RK9P4P9L0 expression reduced the proliferation, migration and invasion ability of A549 and H1299 cell lines. Conclusion: These findings will help us further understand the molecular mechanisms of LUAD and contribute to novel diagnostic biomarkers and therapeutic target discovery. [ABSTRACT FROM AUTHOR]

ABCF1, a member of the ATP-binding cassette (ABC) transporter family, is involved in the malignant progression of tumors. However, the role of ABCF1 in bladder cancer is poorly understood. In our study, we explored the differential expression of ABCF1 in bladder cancer and normal bladder tissues based on bioinformatic analysis and immunohistochemical results. GSEA was performed to ascertain the potential related signaling pathways of ABCF1. The relationship between ABCF1 expression and bladder cancer progression was analyzed using the GSE13507 dataset. In addition, the differential expression of ABCF1 in the cell lines was verified by quantitative real-time polymerase chain reaction (qRT‒PCR) and Western blotting. ABCF1 was upregulated in bladder cancer, and the high expression of ABCF1 was closely related to sex (P = 0.00056), grade (P = 0.00049), T stage (P = 0.00007), and N stage (P = 0.0076). High expression of ABCF1 was correlated with poor overall survival in bladder cancer patients (P < 0.001). In addition, univariate and multivariate Cox regression analyses showed that high ABCF1 expression was an independent factor for poor prognosis in bladder cancer patients. Therefore, ABCF1 expression is closely related to the progression of bladder cancer and can be used as a potential indicator of poor prognosis and a therapeutic target for bladder cancer. [ABSTRACT FROM AUTHOR]

Background: Pancreatic cancer is characterized by a complex tumor microenvironment that hinders effective immunotherapy. Identifying key factors that regulate the immunosuppressive landscape is crucial for improving treatment strategies. Methods: We constructed a prognostic and risk assessment model for pancreatic cancer using 101 machine learning algorithms, identifying OSBPL3 as a key gene associated with disease progression and prognosis. We integrated multi-dataset analyses, single-cell transcriptomic data, and functional experiments to explore the role of OSBPL3 in pancreatic cancer. Results: Our risk prediction model, developed using machine learning algorithms, demonstrated high predictive accuracy across multiple datasets. Notably, the "rf" algorithm model showed an AUC of 1 in the training set and AUCs of 0.887 and 0.977 in two validation datasets. Ridge regression analysis identified OSBPL3 as a core prognostic feature gene. High OSBPL3 expression in pancreatic cancer samples was associated with immunosuppressive characteristics, including reduced CD8 + T cell infiltration and increased immunosuppressive cell populations such as Treg cells and M2 macrophages. Transcriptomic sequencing following OSBPL3 knockdown revealed enrichment of immune-related pathways, suggesting OSBPL3's influence on the immune microenvironment. Single-cell analyses further confirmed OSBPL3's role in shaping the immunosuppressive landscape by modulating Treg cells and M2 macrophages. Additionally, OSBPL3 expression was linked to resistance to immunotherapy, with high OSBPL3 expression associated with lower Immunophenoscore (IPS) scores, indicating poor responsiveness to immunotherapy. Conclusions: Our study reveals OSBPL3 as a critical regulator of the immunosuppressive microenvironment in pancreatic cancer and a potential therapeutic target. Targeting OSBPL3 may enhance the efficacy of immunotherapy and improve patient outcomes. Further research is warranted to explore OSBPL3 as a biomarker for predicting immunotherapy response and as a potential therapeutic target in combination with anti-PD1 therapy. [ABSTRACT FROM AUTHOR]

Background: Abnormal dynamics of the Golgi apparatus reshape the tumor microenvironment and immune landscape, playing a crucial role in the prognosis and treatment response of cancer. This study aims to investigate the potential role of Golgi apparatus-related genes (GARGs) in the heterogeneity and prognosis of head and neck squamous cell carcinoma (HNSCC). Methods: Transcriptional data and corresponding clinical information of HNSCC were obtained from public databases for differential expression analysis, consensus clustering, survival analysis, immune infiltration analysis, immune therapy response assessment, gene set enrichment analysis, and drug sensitivity analysis. Multiple machine learning algorithms were employed to construct a prognostic model based on GARGs. A nomogram was used to integrate and visualize the multi-gene model with clinical pathological features. Results: A total of 321 GARGs that were differentially expressed were identified, out of which 69 were associated with the prognosis of HNSCC. Based on these prognostic genes, two molecular subtypes of HNSCC were identified, which showed significant differences in prognosis. Additionally, a risk signature consisting of 28 GARGs was constructed and demonstrated good performance for assessing the prognosis of HNSCC. This signature divided HNSCC into the high-risk and low-risk groups with significant differences in multiple clinicopathological characteristics, including survival outcome, grade, T stage, chemotherapy. Immune response-related pathways were significantly activated in the high-risk group with better prognosis. There were significant differences in chemotherapy drug sensitivity and immune therapy response between the high-risk and low-risk groups, with the low-risk group being more suitable for receiving immunotherapy. Riskscore, age, grade, and radiotherapy were independent prognostic factors for HNSCC and were used to construct a nomogram, which had good clinical applicability. Conclusions: We successfully identified molecular subtypes and prognostic signature of HNSCC that are derived from GARGs, which can be used for the assessment of HNSCC prognosis and treatment responses. [ABSTRACT FROM AUTHOR]

Background: HBV infection is the leading risk factor for HCC. HBV infection has been confirmed to be associated with the exhaustion status of CD8+ T cells and immunotherapeutic efficacy in HCC. In this study, we aimed to investigate the prognostic value of the CD8+ T-cell exhaustion signature and immunotherapy response in patients with HBV-related HCC. Methods: We identified different clusters of HBV-related HCC cells by single-cell RNA sequencing (scRNA-seq) and identified CD8+ T-cell exhaustion-related genes (TERGs) by pseudotime analysis. We conducted differential expression analysis and LASSO Cox regression to detect genes and construct a CD8+ T-cell exhaustion index (TEI). We next combined the TEI with other clinicopathological factors to design a prognostic nomogram for HCC patients. We also analysed the difference in the TEI between the non-responder and responder groups during anti-PD-L1 therapy. In addition, we investigated how HBV induces CD8+ T lymphocyte exhaustion through the inhibition of tyrosine metabolism in HCC using gene set enrichment analysis and RT‒qPCR. Results: A CD8+ T-cell exhaustion index (TEI) was established with 5 TERGs (EEF1E1, GAGE1, CHORDC1, IKBIP and MAGOH). An AFP level > 500 ng, vascular invasion, histologic grade (G3-G4), advanced TNM stage and poor five-year prognosis were related to a higher TEI score, while HBV infection was related to a lower TEI score. Among those receiving anti-PD-L1 therapy, responders had lower TEIs than non-responders did. The TEI also serves as an independent prognostic factor for HCC, and the nomogram incorporating the TEI, TNM stage, and vascular invasion exhibited excellent predictive value for the prognosis in HCC patients. RT‒qPCR revealed that among the tyrosine metabolism-associated genes, TAT (tyrosine aminotransferase) and HGD (homogentisate 1,2 dioxygenase) were expressed at lower levels in HBV-HCC than in non-HBV HCC. Conclusion: Generally, we established a novel TEI model by comprehensively analysing the progression of CD8+ T-cell exhaustion, which shows promise for predicting the clinical prognosis and potential immunotherapeutic efficacy in HBV-related HCC patients. [ABSTRACT FROM AUTHOR]

Background: Gastric cancer (GC) is considered the sixth highly prevailing malignant neoplasm and is ranked third in terms of cancer mortality rates. To enable an early and efficient diagnosis of GC, it is important to detect the fundamental processes involved in the oncogenesis and progression of gastric malignancy. The understanding of molecular signaling pathways can facilitate the development of more effective therapeutic strategies for GC patients. Methods: The screening of genes that exhibited differential expression in early and advanced GC was performed utilizing the Gene Expression Omnibus databases (GSE3438). Based on this, the protein and protein interaction network was constructed to screen for hub genes. The resulting list of hub genes was evaluated with bioinformatic analysis and selected genes were validated the protein expression by immunohistochemistry (IHC). Finally, a competing endogenous RNA network of GC was constructed. Results: The three genes (ITGB1, LUM, and COL5A2) overexpressed in both early and advanced GC were identified for the first time. Their upregulation has been linked with worse overall survival (OS) time in patients with GC. Only LUM was identified as an independent risk factor for OS among GC patients by means of additional analysis. IHC results demonstrated that the expression of LUM protein was increased in GC tissue, and was positively associated with the pathological T stage. LUM expression can effectively differentiate tumorous tissue from normal tissue (area under the curve = 0.743). The area under 1-, 3-, and 5-year survival relative operating characteristics were greater than 0.6. Biological function enrichment analyses suggested that the genes related to LUM expression were involved in extracellular matrix development-related pathways and enriched in several cancer-related pathways. LUM affects the infiltration degree of cells linked to the immune system in the tumor microenvironment. In GC progression, the AC117386.2/hsa-miR-378c/LUM regulatory axis was also identified. Conclusion: Collectively, a thorough bioinformatics analysis was carried out and an AC117386.2/hsa-miR-378c/LUM regulatory axis in the stomach adenocarcinoma dataset was detected. These findings should serve as a guide for future experimental investigations and warrant confirmation from larger studies. [ABSTRACT FROM AUTHOR]

Background: It has previously been proven that circadian rhythm disruption is associated with the incidence and deterioration of several tumors, which potentially leads to increased tumor susceptibility and a worse prognosis for tumor-bearing patients. However, their potential role in osteosarcoma has yet to be sufficiently investigated. Methods: Transcriptomic and clinical data of 84 osteosarcoma samples and 70 normal bone tissue samples were obtained from the TARGET and GTEx databases, circadian rhythm-related genes were obtained from Genecards, and circadian rhythm-related lncRNAs (CRLs) were obtained by Pearson correlation analysis, differential expression analysis, and protein–protein interaction (PPI) analysis. COX regression and LASSO regression were performed on the CRLs in order to construct a circadian rhythm-related prognostic prediction signature (CRPS). CRPS reliability was verified by Kaplan–Meier (KM), principal component analysis (PCA), nomogram, and receiver operating characteristic (ROC) curve. CRPS effects on the immune microenvironment of osteosarcoma were explored by enrichment analysis and immune infiltration analysis, and the effect of critical gene RP11-414H17.5 on osteosarcoma was experimentally verified. Result: CRPS consisting of three CRLs was constructed and its area under the curve (AUC) values predicted that osteosarcoma prognosis reached 0.892 in the training group and 0.843 in the test group, with a p value of < 0.05 for the KM curve and stable performance across different clinical subgroups. PCA analysis found that CRPS could significantly distinguish between different risk subgroups, and exhibited excellent performance in the prediction of the immune microenvironment. The experiment verified that RP11-414H17.5 can promote metastasis and inhibit apoptosis of osteosarcoma cells. Conclusion: The study revealed that circadian rhythm plays a crucial role in osteosarcoma progression and identified the impact of the key gene RP11-414H17.5 on osteosarcoma, which provides novel insights into osteosarcoma diagnosis and therapy. [ABSTRACT FROM AUTHOR]

Background: The role of nicotinamide N-methyltransferase (NNMT) in ovarian cancer is still elusive. Our aim is to explore the expression of NNMT in ovarian cancer and to assess its association with patient prognosis and treatment response.Methods: We first analyzed the differential expression of NNMT among fallopian tube epithelium, primary ovarian cancers, metastatic ovarian cancers, and recurrent ovarian cancers using Gene Expression Ominus (GEO) database (GSE10971, GSE30587, GSE44104 and TCGA datasets). Then, we assessed the association of NNMT expression with clinical and molecular parameters using CSIOVDB database and GSE28739 dataset. Next, we evaluate the association of NNMT expression with the prognosis of ovarian cancer patients in both GSE9891 dataset and TCGA dataset. Finally, GSE140082 dataset was used to explore the association of NNMT expression with bevacizumab response.Results: NNMT expression was significantly elevated in lymphovascular space invasion (LVSI)-positive ovarian cancers compared with that in LVSI-negative ovarian cancers (TCGA dataset, P < 0.05), Moreover, increased expression of NNMT was associated with increased tumor stage, grade, and mesenchymal molecular subtype (CSIOVDB database). Survival analysis indicated that increased expression of NNMT was associated with a reduced OS in both GSE9891 dataset (HR: 2.28, 95%CI: 1.51-3.43, Log-rank P < 0.001) and TCGA dataset (HR: 1.55, 95%CI: 1.02-2.36, Log-rank P = 0.039). Multivariate analysis further confirmed the negative impact of NNMT expression on OS in ovarian cancer patients in those two datasets. Furthermore, the NNMT-related nomogram showed that NNMT shared a larger contribution to OS, compared with debulking status. More interestingly, bevacizumab conferred significant improvements in OS for patients with low NNMT expression (HR: 0.56, 95%CI: 0.31-0.99, Log-rank P = 0.049). In contrast, patients with high NNMT expression didn't benefit from bevacizumab treatment significantly (HR: 0.85, 95%CI: 0.48-1.49, Log-rank P = 0.561). NNMT expression was positively correlated with the expression of genes, LDHA and PGAM1, involved in Warburg effect.Conclusions: In conclusion, NNMT expression is associated with the aggressive behavior of ovarian cancer, correlates with a poor prognosis, and is predictive of sensitivity to bevacizumab treatment. [ABSTRACT FROM AUTHOR]

Background: Perianal Paget's disease (PPD) is rare and mostly described in clinical literature as case reports or small series. Methods: We investigated the clinicopathologic and immunohistochemical features of PPD in a total of 13 cases retrieved from multiple academic institutions. Results: The median age at diagnosis was 75 (range 50–86) years. Males were predominant with a male to female ratio of 2.25:1. Four (30.8%) cases were classified as primary PPD due to lack of synchronous or metachronous underlying malignancies, while nine (69.2%) were classified as secondary PPD with concurrent invasive adenocarcinoma (n = 8) or tubular adenoma with high-grade dysplasia (n = 1). Immunohistochemically, there is no differential expression of CK7 or CK20 in Paget's cells between primary and secondary PPD; however, GCDFP-15 was only positive in primary PPD (3/3 vs. 0/6, P = 0.012), while CDX2 was only positive in secondary PPD (0/3 vs. 7/7, P = 0.008), suggesting different cell origin. All patients received local surgical resection with or without adjuvant therapy. After a median follow-up of 47 months, one patient with secondary PPD (7.7%) died of disease progression from underlying adenocarcinoma. Conclusions: PPD occurs in elderly patients with male predominance and is frequently associated with underlying malignancies. Differential expression of CDX2 and GCDFP-15 may help distinguishing primary vs. secondary PPD, which is important for management as the presence of an underlying malignancy impacts clinical course and prognosis. Surgical excision remains the major treatment strategy for PPD. Long-term follow-up is required to monitor the disease recurrence and metastasis. [ABSTRACT FROM AUTHOR]

Background: Little is known about the relationship between integrin subunit alpha V (ITGAV) and cancers, including small cell lung cancer (SCLC).Methods: Using large sample size from multiple sources, the clinical roles of ITGAV expression in SCLC were explored using differential expression analysis, receiver operating characteristic curves, Kaplan-Meier curves, etc. RESULTS: Decreased mRNA (SMD = - 1.05) and increased protein levels of ITGAV were detected in SCLC (n = 865). Transcription factors-ZEB2, IK2F1, and EGR2-may regulate ITGAV expression in SCLC, as they had ChIP-Seq (chromatin immunoprecipitation followed by sequencing) peaks upstream of the transcription start site of ITGAV. ITGAV expression made it feasible to distinguish SCLC from non-SCLC (AUC = 0.88, sensitivity = 0.78, specificity = 0.84), and represented a risk role in the prognosis of SCLC (p < 0.05). ITGAV may play a role in cancers by influencing several immunity-related signaling pathways and immune cells. Further, the extensive pan-cancer analysis verified the differential expression of ITGAV and its clinical significance in multiple cancers.Conclusion: ITGAV served as a potential marker for prognosis and identification of cancers including SCLC. [ABSTRACT FROM AUTHOR]

Background: Cyclin-dependent kinase inhibitor 2C (CDKN2C) was identified to participate in the occurrence and development of multiple cancers; however, its roles in small cell lung carcinoma (SCLC) remain unclear.Methods: Differential expression analysis of CDKN2C between SCLC and non-SCLC were performed based on 937 samples from multiple centers. The prognosis effects of CDKN2C in patients with SCLC were detected using both Kaplan-Meier curves and log-rank tests. Using receiver-operating characteristic curves, whether CDKN2C expression made it feasible to distinguish SCLC was determined. The potential mechanisms of CDKN2C in SCLC were investigated by gene ontology terms and signaling pathways (Kyoto Encyclopedia of Genes and Genomes). Based on 10,080 samples, a pan-cancer analysis was also performed to determine the roles of CDKN2C in multiple cancers.Results: For the first time, upregulated CDKN2C expression was detected in SCLC samples at both the mRNA and protein levels (p of Wilcoxon rank-sum test < 0.05; standardized mean difference = 2.86 [95% CI 2.20-3.52]). Transcription factor FOXA1 expression may positively regulate CDKN2C expression levels in SCLC. High CDKN2C expression levels were related to the poor prognosis of patients with SCLC (hazard ratio > 1, p < 0.05) and showed pronounced effects for distinguishing SCLC from non-SCLC (sensitivity, specificity, and area under the curve ≥ 0.95). CDKN2C expression may play a role in the development of SCLC by affecting the cell cycle. Furthermore, the first pan-cancer analysis revealed the differential expression of CDKN2C in 16 cancers (breast invasive carcinoma, etc.) and its independent prognostic significance in nine cancers (e.g., adrenocortical carcinoma). CDKN2C expression was related to the immune microenvironment, suggesting its potential usefulness as a prognostic marker in immunotherapy.Conclusions: This study identified upregulated CDKN2C expression and its clinical significance in SCLC and other multiple cancers, suggesting its potential usefulness as a biomarker in treating and differentiating cancers. [ABSTRACT FROM AUTHOR]

Background: ATP7B is a copper-transporting protein that contributes to the chemo-resistance of human cancer cells. It remains unclear what the molecular mechanisms behind ATP7B are in cancer, as well as its role in human pan-cancer studies. Methods: Our study evaluated the differential expression of ATP7B in cancer and paracancerous tissues based on RNA sequencing data from the GTEx and TCGA. Kaplan–Meier and Cox proportional hazards regressions were used to estimate prognostic factors associated with ATP7B.The correlations between the expression of ATP7B and immune cell infiltration, tumor mutation burden, microsatellite instability and immune checkpoint molecules were analyzed. Co-expression networks and mutations in ATP7B were analyzed using the web tools. An analysis of ATP7B expression difference on drug sensitivity on tumor cells was performed using the CTRP, GDSC and CMap database. Results: ATP7B expression differed significantly between cancerous and paracancerous tissues. The abnormal expression of ATP7B was linked to prognosis in LGG and KIRC. Infiltration of immune cells, tumor mutation burden, microsatellite instability and immunomodulators had all been linked to certain types of cancer. Cancer cells exhibited a correlation between ATP7B expression and drug sensitivity. Conclusion: ATP7B might be an immunotherapeutic and prognostic biomarker based on its involvement in cancer occurrence and development. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) is one of the three deadliest malignant tumors in the world, posing a severe hazard to human health. Nonetheless, the 5-year survival rate for advanced CRC remains unsatisfactory. Grid2 interacting protein (GRID2IP) is a Purkinje fiber postsynaptic scaffold protein implicated in a number of signal transduction pathways in the nervous system. Previous studies have shown that Grid2 is closely related to the occurrence and prognosis of gastric cancer and many other diseases. Therefore, we aim to identify the relationship between GRID2IP and the occurrence and prognosis of CRC. Methods: Transcriptome data were retrieved from The Cancer Genome Atlas (TCGA) database to analyze the differential expression of GRID2IP in a variety of malignant tumors and then validate it by quantitative real time polymerase chain reaction(Q-PCR) and Western Blot in HT29 and SW480 cells. "DESeq2" package was used to analyze the differentially expressed genes (DEGs) between the high- and low-GRID2IP subgroups. In relation to DEGs, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed. In addition, gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were employed to examine DEGs-associated signaling pathways and GRID2IP-associated immune cell infiltration levels. Besides, overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) were compared between the two subgroups using a Kaplan–Meier analysis. In addition, a prognostic model for GRID2IP and clinical characteristics was developed using the univariate Cox regression method. The "pRRophetic" package was applied to predict the drug sensitivity of different subgroups. Moreover, we also performed single-cell analysis of GRID2IP using the TISCH database. Results: GRID2IP is upregulated in CRC patients. The rise of GRID2IP inhibits the invasion of tumor-associated immune cells resulting in a lower immune score. In addition, high GRID2IP expression was associated with poor prognosis in different clinical subgroups. Analysis of single cells revealed that GRID2IP was predominantly expressed in immune cells, myofibroblasts, and cancerous cells. In terms of chemotherapy drug sensitivity, the subgroup with high GRID2IP expression was less sensitive to gemcitabine. Conclusions: Our results suggest that rising GRID2IP promotes tumor-associated immune cell infiltration and suggests adverse outcomes in CRC patients, which may be a useful biomarker for determining the prognosis of CRC and a potential target molecule for CRC therapy. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to explore metabolic abnormalities in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) for metabolism-related genes. Methods: We downloaded expression data for metabolism-related genes, performed differential expression analysis, and applied weighted gene co-expression network analysis (WGCNA) to identify metabolism-related functional modules. We obtained normalised miRNA expression data and identified master methylation regulators for metabolism-related genes. Cox regression of data on metabolism-related genes was performed to screen for genes that affect the prognosis of patients with CESC. Furthermore, we selected key genes for validation. Results: Our results identified 3620 metabolism-related genes in CESC, 2493 of which contained related mutations. The co-occurrence of CUBN, KALRN, and HERC1 was related to the prognosis of CESC. The fraction of genome altered (FGA) closely correlated with overall survival. In expression analysis, 374 genes were related to the occurrence and prognosis of CESC. We then identified four metabolic pathway modules in WGCNA. Further analysis revealed that glycolysis/gluconeogenesis was related to endothelial cells and that arachidonic acid metabolism was related to cell proliferation. These four modules were also related to the prognosis of CESC. Among CESC-related metabolic genes, two genes were found to be regulated by microRNAs (miRNAs) and methylation, whereas another two genes were coregulated by miRNAs and mutations. Conclusions: Among metabolism-related genes, 15 genes were related to the prognosis of CESC. The co-occurrence of CUBN/KALRN/HERC1 was associated with CESC prognosis. Glycolysis/gluconeogenesis was related to endothelial cells, and arachidonic acid metabolism was related to cell proliferation. [ABSTRACT FROM AUTHOR]