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The cellular components of tumors and their microenvironment play pivotal roles in tumor progression, patient survival, and the response to cancer treatments. Unveiling a comprehensive cellular profile within bulk tumors via single-cell RNA sequencing (scRNA-seq) data is crucial, as it unveils intrinsic tumor cellular traits that elude identification through conventional cancer subtyping methods. Our contribution, scBeacon, is a tool that derives cell-type signatures by integrating and clustering multiple scRNA-seq datasets to extract signatures for deconvolving unrelated tumor datasets on bulk samples. Through the employment of scBeacon on the The Cancer Genome Atlas (TCGA) cohort, we find cellular and molecular attributes within specific tumor categories, many with patient outcome relevance. We developed a tumor cell-type map to visually depict the relationships among TCGA samples based on the cell-type inferences.

AbstractBreast cancer (BC) is a malignant tumor that occurs in breast tissue. This project aims to predict the prognosis of BC patients using genes related to hypoxia and endoplasmic reticulum stress (ERS). RNA-seq and clinical data for BC were downloaded from TCGA and GEO databases. Hypoxia and ERS-related genes were collected from the Genecards database. Univariate/multivariate Cox regression and Lasso regression analyses were used to screen genes and construct prognostic models. Patients were divided into high-risk (HR) and low-risk (LR) groups based on risk scores. The CIBERSORT algorithm was used to analyze differences in immune infiltration between the two groups. The mutations of the two groups were analyzed statistically. The CellMiner database was used for drug prediction and the TISCH database for single-cell sequencing analysis. We screened 8 feature genes to construct a prognostic model. Patients in the HR group had a remarkably worse prognosis. TP53 exhibited a higher mutation frequency in the HR group. CIBERSORT analysis uncovered a remarkable increase in the infiltration levels of Macrophages M0 and Tregs in cancer patients and HR patients. Drug sensitivity prediction demonstrated that the expression of IVL was greatly negatively linked with the sensitivity of COLCHICINE. PTGS2 had a remarkably negative correlation with the Vincristine sensitivity. The prognostic model based on 8 hypoxia and ERS-related genes can predict the survival, immune status, and potential drugs of BC patients, bringing a new perspective on individualized treatment. [ABSTRACT FROM AUTHOR]

Background: Gastric cancer is one of the most prevalent gastrointestinal cancers. Mortality is high, and improved treatments are needed. A better understanding of the pathophysiology of the disease and discovery of biomarkers for targeted therapies are paramount for therapeutic progress. CDX2, a transcription factor of hindgut specification, is induced in several gastric cancers, especially with intestinal differentiation, and could be helpful for defining sub-types with particular characteristics. Methods: Gastric cancers with induced CDX2 mRNA expression were identified from the gastric cohort of The Cancer Genome Atlas (TCGA) and were compared with cancers that had no CDX2 mRNA induction. Induced CDX2 mRNA expression was defined as mRNA expression z-score relative to all samples above 0, and non-induced CDX2 mRNA expression was defined as mRNA expression z-score relative to all samples below −1. Results: Patients with gastric cancers with CDX2 mRNA induction were older, had less frequently diffuse histology, and more often had mutations in TP53 and KMT2B and amplifications in MYC. CDX2 induction was correlated with HNF4α induction and was reversely correlated with SOX2. Gastric cancers with CDX2 mRNA induction showed lower PD-L1 expression than cancers with lower CDX2 expression but did not differ in CLDN18 mRNA expression. Progression-free and overall survival of the two groups was also not significantly different. Conclusion: Gastric cancers with CDX2 mRNA induction displayed specific characteristics that differentiate them from cancers with no CDX2 induction and could be of interest for optimizing current and future therapies. [ABSTRACT FROM AUTHOR]

Background: Neural precursor cell expressed developmentally downregulated 9 (NEDD9) is considered an important factor in the progression of cancer, acting as a modulator of cellular migration, adhesion, and metastatic potential. Its significance as a prognostic factor, however, remains unclear, which necessitated a comprehensive review and meta-analysis. Methods: Our study followed the PRISMA guidelines, analyzing studies from major databases including PubMed, Embase, and Cochrane. Our eligibility criteria included studies evaluating NEDD9 expression in relation to cancer prognosis and outcomes such as overall survival (OS), progression-free survival (PFS), disease-free Survival (DFS), recurrence-free survival (RFS), and cancer-specific survival (CSS). We used random-effects and fixed-effect models for meta-analysis, and we validated our findings by comparative analysis using data from external cohorts like The Cancer Genome Atlas (TCGA). Results: The analysis of 27 studies with 3915 patients demonstrated a significant relationship between NEDD9 expression and poor OS as indicated by the pooled meta-analysis outcome across all included cancers (HR: 1.81, 95% CI: 1.38-2.37). A significant effect on PFS/DFS/RFS/CSS was also found (HR: 2.14, 95% CI: 1.42-3.23). Variations in survival across different types of cancer were indicated by subgroup analysis. NEDD9 expression was correlated with various immune cells across cancer types according to immune infiltration analysis. Protein-protein interaction (PPI) analysis indicated significant interactions involving NEDD9, suggesting mechanisms which influence tumor behavior and response to treatment. Conclusion: Our results suggest that NEDD9 is a significant prognostic marker in several human cancers. As a result of its central role in cancer progression and prognosis, it presents a promising target for therapeutic interventions. Our study highlights the importance of further research into the biology of NEDD9 and its therapeutic potential. [ABSTRACT FROM AUTHOR]

Thyroid cancer (THCA) is a malignant tumor that affects the endocrine system. At present, an effective treatment for THCA remains elusive, particularly for medullary carcinoma and undifferentiated carcinoma, due to the lack of suitable medications and prognostic markers. Patient RNA-sequencing and clinical data were obtained from The Cancer Genome Atlas and Genotype-Tissue Expression databases. Protein-protein interaction analyses were performed for differentially expressed genes related to THCA. Moreover, the associations between fibronectin 1 (FN1), clinical data, immune checkpoint genes and immune cell infiltration was assessed. The potential functional role of the FN1 gene was evaluated through gene set enrichment analysis. Immunohistochemistry was used to assess FN1 expression in 103 cases of THCA, comprising 32 with papillary carcinoma, 30 with follicular carcinoma, 35 with medullary carcinoma and 6 with undifferentiated carcinoma. Finally, 11 co-expression modules were constructed and the expression of five identified hub genes (FN1, mucin-1, keratin 19, intracellular adhesion molecule 1 and neural cell adhesion molecule) were evaluated. The results demonstrated that higher FN1 gene expression levels were strongly associated with a higher pathologic stage and tumor stage, and were significantly associated with immune cell infiltration in THCA. Significant increases in FN1 protein expression levels were noted among patients diagnosed with four types of THCA, comprising papillary carcinoma, follicular carcinoma, medullary carcinoma and undifferentiated carcinoma. Patients diagnosed with medullary carcinoma and undifferentiated carcinoma, and with low FN1 expression levels, exhibited a significant survival advantage compared with those with high FN1 expression levels. In conclusion, the present study identified five hub genes involved in the onset and progression of THCA. Furthermore, FN1 could serve as a candidate biomarker and a therapeutic target for THCA and may be a key gene mediating THCA immune infiltration. [ABSTRACT FROM AUTHOR]

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Background Methods Results Conclusion Uveal melanoma (UM) can be classified by tumour size category and by The Cancer Genome Atlas (TCGA) groups (cytogenetic‐based, 4‐category prognostic classification into Groups A‐D). This study was conducted to assess impact on metastasis‐free survival (MFS) in UM by tumour size category based on correlation with TCGA classification.Retrospective analysis of 1001 cases categorised as small (0.0–3.0 mm), medium (3.1–8.0 mm) and large (≥8.1 mm), grouped by TCGA classification.Of 1001 cases, TCGA Groups (A/B/C/D) included small (n = 270, 75%/11%/13%/1%), medium (n = 503, 46%/14%/27%/13%) and large (n = 228, 23%/19%/38%/20%) UM. The 5‐and 10‐year Kaplan–Meier MFS for small UM revealed Group A (98%, 98%), Group B (100%, 100%), Group C (86%, NA) and Group D (100%, NA). For medium UM, the values dropped with Group A (95%, 93%), Group B (90%, 90%), Group C (68%, 38%), and Group D (44%, NA). For large UM, the values dropped further with Group A (94%, 86%), Group B (85%, NA), Group C (40%, 28%), and Group D (23%, NA). Additionally, a comparison (small vs. medium vs. large tumour size category) revealed TCGA low‐risk grouping (Groups A or B) in 86% vs. 60% vs. 58% cases with UM.By tumour size category, favourable cytogenetics (Groups A or B) is found in 86% of small tumours, 60% of medium tumours, and 58% of large tumours. The MFS at 10 years for favourable cytogenetics was 98% for small tumours, 92% for medium tumours, and 54% for large tumours. Tumour size category can serve as a surrogate for TCGA. [ABSTRACT FROM AUTHOR]

Background: The incidence and mortality of cervical cancer remain high in female malignant tumors worldwide. There is still a lack of diagnostic and prognostic markers for cervical carcinoma. This study aimed to screen differentially expressed genes (DEGs) between normal and cervical cancer tissues to identify candidate genes for further research. Methods: Uterine cervical specimens were resected from our clinical patients after radical hysterectomy. Three patients' transcriptomic datasets were built by the next generation sequencing (NGS) results. DEGs were selected through the edgeR and DESeq2 packages in the R environment. Functional enrichment analysis, including GO/DisGeNET/KEGG/Reactome enrichment analysis, was performed. Normal and cervical cancer tissue data from the public databases TCGA and GTEx were collected to compare the expression levels of 10 selected DEGs in tumor and normal tissues. ROC curve and survival analysis were performed to compare the diagnostic and prognostic values of each gene. The expression levels of candidate genes were verified in 15 paired clinical specimens via quantitative real-time polymerase chain reaction. Results: There were 875 up-regulated and 1,482 down-regulated genes in cervical cancer samples compared with the paired adjacent normal cervical tissues according to the NGS analysis. The top 10 DEGs included APOD, MASP1, ACKR1, C1QTNF7, SFRP4, HSPB6, GSTM5, IGFBP6, F10 and DCN. GO, DisGeNET and Reactome analyses revealed that the DEGs were related to extracellular matrix and angiogenesis which might influence tumorigenesis. KEGG enrichment showed that PI3K-Akt signaling pathway might be involved in cervical cancer tumorigenesis and progression. The expression levels of selected genes were decreased in tumors in both the public database and our experimental clinical specimens. All the candidate genes showed excellent diagnostic value, and the AUC values exceeded 0.90. Additionally, APOD, ACKR1 and SFRP4 expression levels could help predict the prognosis of patients with cervical cancer. Conclusions: In this study, we selected the top 10 DEGs which were down-regulated in cervical cancer tissues. All of them had dramatically diagnostic value. APOD, ACKR1 and SFRP4 were associated with the survivals of cervical cancer. C1QTNF7, HSPB6, GSTM5, IGFBP6 and F10 were first reported to be candidate genes of cervical carcinoma. [ABSTRACT FROM AUTHOR]

BackgroundPrevious studies have shown that glycolysis-related genes (GRGs) are associated with the development of breast cancer (BC), and the prognostic significance of GRGs in BC has been reported. Considering the heterogeneity of BC patients, which makes prognosis difficult to predict, and the fact that glycolysis is regulated by multiple genes, it is important to establish and evaluate new glycolysis-related prediction models in BC.MethodsIn total, 170 GRGs were selected from the GeneCards database. We analyzed data from the Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) database as a training set and data from the Gene Expression Omnibus (GEO) database as a validation cohort. Based on the overall survival data and the expression levels of GRGs, Cox regression analyses were applied to develop a glycolysis-related prognostic gene (GRPGs)-based prediction model. Kaplan (KM) survival and ROC analyses were performed to assess the performance of this model. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to identify the potential biological functions of GRPGs. cBioPortal database was used to explore the tumor mutation burden (TMB). The tumor immune dysfunction and exclusion indicator (TIDE) was used to estimate the patient response to immune checkpoint blockade (ICB). The levels of tumor-infiltrating immune cells (TICs) and stromal cells were quantitatively analyzed based on gene expression profiles.ResultsWe constructed a prediction model of 10 GRPGs (ADPGK, HNRNPA1, PGAM1, PIM2, YWHAZ, PTK2, VDAC1, CS, PGK1, and GAPDHS) to predict the survival outcomes of patients with BC. Patients were divided into low- and high-risk groups based on the gene signature. The AUC values of the ROC curves were 0.700 (1-year OS), 0.714 (3-year OS), 0.681 (5-year OS). TMB and TIDE analyses showed that patients in the high-risk group might respond better to ICB. Additionally, by combining the GRPGs signature and clinical characteristics of patients, a novel nomogram was constructed. The AUC values for this combined prediction model were 0.827 (1-year OS), 0.792 (3-year OS), and 0.783 (5-year OS), indicating an outstanding predictive performance.ConclusionA new GRPGs based prediction model was built to predict the OS and immunotherapeutic response of patients with BC.

Abstract Acute myeloid leukemia (AML) is a highly heterogeneous hematological neoplasm, highlighting the need for new molecular markers to improve prognosis prediction and therapeutic strategies. While Rho guanine nucleotide exchange factor 5 (ARHGEF5) is known to be overexpressed in various cancers, its role in AML is not well understood. This study investigates the correlation between ARHGEF5 expression and AML using data from the Cancer Genome Atlas (TCGA). ARHGEF5 expression levels in AML patients and normal samples were compared using the Wilcoxon rank-sum test. The Kaplan–Meier method and Cox regression analysis (CRA) assessed the association between ARHGEF5 expression and patient survival. A prognostic nomogram was constructed using CRA, incorporating patient age and cytogenetic risk.Our findings indicate significant overexpression of ARHGEF5 in AML compared to normal samples. Elevated ARHGEF5 levels were associated with poor prognosis, particularly in patients ≤ 60 years, those with NPM1 mutations, FLT3 mutation-positive, and wild-type RAS (P

ObjectiveTo construct a prognostic risk scoring model for gastric cancer (GC) anoikis-related genes (ARGs) based on least absolute shrinkage and selection operator (LASSO) regression, and analyze the relationship between anoikis and prognosis of gastric cancer as well as the significance of the model in immunotherapy and chemotherapy of gastric cancer patients. MethodsDifferentially expressed prognostic anoikis-related genes (ARGs) in gastric cancer and adjacent tissues were screened through The Cancer Genome Atlas (TCGA) database and the Molecular Signatures Database (MSigDB); key anoikis genes were selected based on LASSO regression analysis to construct a prognostic risk scoring model, and patients were divided into high-risk and low-risk groups with the median risk score as the cutoff point. Gene expression levels in gastric cancer clinical samples and cells were detected by real-time quantitative PCR (RT-qPCR); Kaplan-Meier (KM) survival curves, univariate and multivariate Cox regression analyses were used to verify the predictive efficiency of the prognostic risk scoring model for the prognosis of gastric cancer patients; CIBERSORT and ESTIMATE algorithms were used to analyze the immune cell infiltration levels in patients with different risk groups; the correlation between risk scores and immune checkpoint expression levels in gastric cancer patients was analyzed using the R package "ggplot2" and "ggExtra", and the correlation between tumor mutation burden (TMB) and risk scores was assessed; chemotherapy drug sensitivity analysis was used to evaluate the value of the constructed prognostic risk scoring model in gastric cancer chemotherapy. ResultsSix key ARGs (VCAN, FEN1, BRIP1, CNTN1, P3H2, DUSP1) were screened out based on LASSO regression analysis, and a prognostic risk scoring model was constructed. RT-qPCR detection showed that VCAN, FEN1, and BRIP1 genes were highly expressed in gastric cancer tissues and cells (P < 0.05), while CNTN1, P3H2, and DUSP1 genes were lowly expressed (P < 0.05); Kaplan-Meier survival curve analysis found that the survival rate of patients in the high-risk group was significantly lower than that in the low-risk group (P < 0.001), and there were statistically significant differences in survival rate and TMB levels between high- and low-risk group patients (P < 0.05); univariate and multivariate analyses showed that tumor stage, age, and risk score were significantly associated with survival in gastric cancer patients (P < 0.05); immune cell infiltration analysis showed that the tumor immune matrix score was significantly higher in the high-risk group than in the low-risk group (P < 0.05), and the constructed prognostic risk scoring model can be used as an indicator of the tumor immune microenvironment (TIME) status; analysis using the R package "ggplot2" and "ggExtra" showed that the risk score of the constructed model was positively correlated with the upregulated expression of immune checkpoints TIM3, VISTA, TIGIT, BTLA, and B7-H3 (r = 0.26, 0.40, 0.16, 0.26, 0.21, P < 0.05), and TMB level was negatively correlated with risk score (R = – 0.4, P < 0.05); the constructed prognostic risk scoring model can be used to guide chemotherapy for gastric cancer patients. ConclusionThe prognostic risk scoring model constructed based on anoikis-related genes can be used to predict the prognosis of gastric cancer patients; the risk genes in the model can serve as potential targets for gastric cancer treatment, providing a reference for individualized treatment of gastric cancer.

This study aims to address the substantive issue of lacking reliable prognostic biomarkers in hepatocellular carcinoma (HCC) by investigating the relationship between TP53-inducible glycolysis and apoptosis regulator (TIGAR) and HCC prognosis using The Cancer Genome Atlas database.

Acute myeloid leukemia (AML) is a highly heterogeneous hematological neoplasm, highlighting the need for new molecular markers to improve prognosis prediction and therapeutic strategies. While Rho guanine nucleotide exchange factor 5 (ARHGEF5) is known to be overexpressed in various cancers, its role in AML is not well understood. This study investigates the correlation between ARHGEF5 expression and AML using data from the Cancer Genome Atlas (TCGA). ARHGEF5 expression levels in AML patients and normal samples were compared using the Wilcoxon rank-sum test. The Kaplan–Meier method and Cox regression analysis (CRA) assessed the association between ARHGEF5 expression and patient survival. A prognostic nomogram was constructed using CRA, incorporating patient age and cytogenetic risk.Our findings indicate significant overexpression of ARHGEF5 in AML compared to normal samples. Elevated ARHGEF5 levels were associated with poor prognosis, particularly in patients ≤ 60 years, those with NPM1 mutations, FLT3 mutation-positive, and wild-type RAS (P < 0.05). CRA confirmed that high ARHGEF5 expression independently predicts poor prognosis. Additionally, 412 differentially expressed genes (DEGs) were identified between high and low ARHGEF5 expression groups, with 216 genes upregulated and 196 downregulated. Pathway enrichment analyses using GO and KEGG, along with protein–protein interaction network and single sample gene set enrichment analyses, revealed key pathways and immune cell associations linked to ARHGEF5. These findings suggest that ARHGEF5 overexpression could serve as a biomarker for unfavorable outcomes in AML, providing insights into the underlying mechanisms of AML onset and progression. [ABSTRACT FROM AUTHOR]

Uterine corpus endometrial cancer (UCEC) is a third most common malignancy in women with a poor prognosis in advanced stages. In this study, we performed an integrated comparative analysis of exome and transcriptome data from The Cancer Genome Atlas (TCGA) of Lung Adenocarcinoma (LUAD), and UCEC patients. Our multi-omics analysis shows that the UCEC patients carrying mutations in the KEAP1-NFE2L2-CUL3 genes were associated with better progression-free survival (PFS), whereas the KEAP1-NFE2L2-CUL3 mutation in LUAD showed poor outcomes. Functional annotations and correlative expression studies show that genes, particularly GCLC and GCLM related to glutathione synthesis are expressed at lower levels in the KEAP1-NFE2L2-CUL3 mutant UCEC compared to LUAD. This events result in glutathione deficiency and it may compromise to combat intracellular reactive oxygen species (ROS). However, the expression of genes involved in the glutathione recycling process was not affected. On the other hand, cellular import of cystine is high due to increased SLC7A11 expression in UCEC. Because glutathione synthesis is impaired, the unconverted cysteine accumulates in cells, leading to di-sulfite stress. Apart from NRF2, ARID1A is one of the positive regulators of SLC7A11. In support, UCEC patients with co-occurrence of KEAP1-NFE2L2-CUL3 and ARID1A mutation shows significantly decreased PFS with decline of SLC7A11 expression as compared to patients carrying only KEAP1-NFE2L2-CUL3 mutation. Thus, we hypothesize that the KEAP1-NFE2L2-CUL3 mutation in UCEC leads to uncontrollable ROS with di-sulfite stress, reflecting a favorable clinical outcome. [Display omitted] • KEAP1-NFE2L2-CUL3 (KNC) mutations leads favorable clinical outcome in uterine corpus endometrial carcinoma (UCEC). • Expression of genes involved in glutathione synthesis differs in UCEC compared to lung adenocarcinoma (LUAD). • Co-occurrence of KNC and ARID1A mutation shows declined PFS as compared to the UCEC patients carrying only KNC mutation. • KNC mutations in UCEC leads to uncontrollable ROS with di-sulfite stress, reflecting a healthier PFS in comparison with LUAD. [ABSTRACT FROM AUTHOR]

Renal cell carcinoma (RCC) is a common malig- nancy of the urinary system. Although traditional therapies, such as surgery assisted with chemotherapy have improved the quality of life and survival time of patients with RCC, patients with metastasis or recurrence benefit little from such therapies. At present, little is known about the underlying mechanisms of RCC, rendering treatment selection and implementation challenging. Therefore, investigating the cause and underlying mechanisms of RCC remain of importance to explore poten- tial new avenues for its treatment. Inter-α-trypsin inhibitor heavy chain 1 (ITIH1) is an inflammation-associated gene reported to suppress the progression of liver cancer. However, its role in RCC remains poorly understood. Therefore, the present study aimed to investigate the role and mechanism of ITIH1 in RCC. Based on data obtained from The Cancer Genome Atlas database, ITIH1 expression was demonstrated to be significantly higher in tumor tissues compared with normal tissues, which was in turn negatively associated with the survival of patients with RCC. However, in RCC cells, ITIH1 was shown to be expressed at significantly lower levels compared with those in HK-2 cells. The discrepancy between tissues and cell lines might be due to the different environment of cell growth. ITIH1 knockdown in RCC cells significantly increased cell proliferation and invasion whilst significantly decreasing the apoptosis rate, compared with those in control cells (without ITIH1 knockdown). By contrast, overexpression of ITIH1 significantly inhibited cell proliferation and inva- sion in RCC cells. In terms of western blotting results, the phosphorylation levels of NF-κB were significantly increased following ITIH1 knockdown. The protein expression level of IκB significantly decreased whereas that of IKK, Cyclin D1, proliferating cell nuclear antigen and α-smooth muscle actin were significantly increased in ITIH1-knockdown cells, compared with those in the control cells (without ITIH1 knockdown). This suggests that the NF-κB pathway may be activated after ITIH1 knockdown. Following treatment with the NF-κB pathway inhibitor JSH-23 in combination with ITIH1 knockdown, RCC cell proliferation and invasion were significantly reduced compared with those after ITIH1 knockdown alone. In summary, results from the present study suggest that ITIH1 can serve an inhibitory role in the progres- sion of RCC, which could potentially be inhibited through the NF-κB signaling pathway. [ABSTRACT FROM AUTHOR]

PIK3CA-mutant non-small-cell lung cancer (NSCLC) is associated with other genetic mutations and may influence treatment strategies and clinical outcomes. We aimed to characterize PIK3CA mutations co-occurring with several major driver mutations using data from published cohorts and our medical center. Materials and Methods: We analyzed NSCLC patients harboring PIK3CA mutations from The Cancer Genome Atlas (TCGA) and Memorial Sloan Kettering (MSK) databases and retrospectively identified NSCLC patients with PIK3CA-mutants at a single medical center from our electronic records. The Log rank test was used to determine the association between PIK3CA mutations and overall survival (OS) in NSCLC patients. Results: Common hotspot mutations in PIK3CA were found in exon 9 (c.1633G > A, E545K, and c.1624G > A, E542K) and exon 20 (c.3140A > G, H1047R) in all cohorts. Co-occurring mutations of PIK3CA with EGFR, KRAS, and TP53 have been frequently observed in patients with NSCLC, with different percentages in these datasets generated by different background. PIK3CA mutations were observed to be significantly associated with poor OS in lung adenocarcinomas patients in the MSKCC cohort (hazard ratio [HR] = 0.519, 95% confidence interval [CI] = 0.301– 0.896; P < 0.05). Conclusion: PIK3CA co-occurring mutations in other genes may represent distinct subsets of NSCLC. Further elucidation of the roles of PIK3CA hotspot mutations combined with other driver mutations, including EGFR and KRAS, is needed to guide effective treatment in patients with advanced NSCLC. [ABSTRACT FROM AUTHOR]

AbstractHepatocellular carcinoma (HCC), as a malignancy derived from liver tissue, is typically associated with poor prognosis. Increasing evidence suggests a connection between pyrimidine metabolism and HCC progression. The purpose of this study was to establish a model applied to the prediction of HCC patients’ overall survival. Transcriptomic data of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) website. Pyrimidine metabolism-related genes (PMRGs) were collected from the Gene Set Enrichment Analysis (GSEA) website. Differential gene expression analysis was carried out on the HCC data, followed by an intersection of the differentially expressed genes (DEGs) and PMRGs. Subsequently, a prognostic model incorporating nine genes was established using univariate/multivariate Cox regression and Least absolute shrinkage and selection operator (LASSO) regression. Survival analysis demonstrated that the high-risk group defined by this model had considerably shorter overall survival than the low-risk group in both TCGA and Gene Expression Omnibus (GEO) datasets. Receiver operating characteristic (ROC) analysis indicated the good predictive capability of the model. CIBERSORT and single sample gene set enrichment analysis (ssGSEA) algorithms revealed significantly higher levels of Macrophages M0 and lower levels of natural killer (NK)_cells in the high-risk group compared to the low-risk group. The immunophenoscore (IPS) and the tumor immune dysfunction and exclusion (TIDE) score demonstrated that the model could significantly differentiate patients who would be more suitable for immunotherapy. Moreover, the CellMiner database was utilized to predict anti-tumor drugs significantly associated with the model genes. Collectively, the potential prognostic significance of pyrimidine metabolism in HCC was revealed in this study. The prognostic model aids in evaluating the survival time and immune status of HCC patients. [ABSTRACT FROM AUTHOR]

Immunotherapy combined with chemotherapy significantly improves progression-free survival (PFS) compared to first-line chemotherapy alone in advanced endometrial cancer (EC), with a much larger effect size in microsatellite instability-high (MSI-H) cases. New biomarkers might help to select patients who may have benefit among those with a microsatellite-stable (MSS) tumor. In a pre-planned translational analysis of the MITO END-3 trial, we assessed the significance of genomic abnormalities in patients randomized to standard carboplatin/paclitaxel without or with avelumab. Out of 125 randomized patients, 109 had samples eligible for next-generation sequencing analysis, and 102 had MSI tested. According to The Cancer Genome Atlas (TCGA), there were 29 cases with MSI-H, 26 with MSS TP53 wild type (wt), 47 with MSS TP53 mutated (mut), and 1 case with POLE mutation. Four mutated genes were present in >30% of cases: TP53 , PIK3CA , ARID1A , and PTEN. Eleven patients (10%) had a BRCA1 / 2 mutation (five in MSI-H and six in MSS). High tumor mutational burden (≥10 muts/Mb) was observed in all MSI-H patients, in 4 out of 47 MSS/ TP53 mut, and no case in the MSS/ TP53 wt category. The effect of avelumab on PFS significantly varied according to TCGA categories, being favorable in MSI-H and worst in MSS/ TP53 mut (P interaction = 0.003); a similar non-significant trend was seen in survival analysis. ARID1A and PTEN also showed a statistically significant interaction with treatment effect, which was better in the presence of the mutation (ARID1A P interaction = 0.01; PTEN P interaction = 0.002). The MITO END-3 trial results suggest that TP53 mutation is associated with a poor effect of avelumab, while mutations of PTEN and ARID1A are related to a positive effect of the drug in patients with advanced EC. [ABSTRACT FROM AUTHOR]

Background Hypoxia is an important clinical feature of glioblastoma (GBM), which regulates a variety of tumor processes and is inseparable from radiotherapy. Accumulating evidence suggests that long noncoding RNAs (lncRNAs) are strongly associated with survival outcomes in GBM patients and modulate hypoxia-induced tumor processes. Therefore, the aim of this study was to establish a hypoxia-associated lncRNAs (HALs) prognostic model to predict survival outcomes in GBM patients. Methods LncRNAs in GBM samples were extracted from The Cancer Genome Atlas database. Hypoxia-related genes were downloaded from the Molecular Signature Database. Co-expression analysis of differentially expressed lncRNAs and hypoxia-related genes in GBM samples was performed to determine HALs. Six optimal lncRNAs were selected for building HALs models by univariate Cox regression analysis. Results The prediction model has a good predictive effect on the prognosis of GBM patients. Meanwhile, LINC00957 among the six lncRNAs was selected and subjected to pan-cancer landscape analysis. Conclusion Taken together, our findings suggest that the HALs assessment model can be used to predict the prognosis of GBM patients. In addition, LINC00957 included in the model may be a useful target to study the mechanism of cancer development and design individualized treatment strategies. [ABSTRACT FROM AUTHOR]

Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor, making it one of the most life‐threatening human cancers. Nevertheless, research on the mechanism of action between alternative splicing (AS) and splicing factor (SF) or biomarkers in GBM is limited. AS is a crucial post‐transcriptional regulatory mechanism. More than 95% of human genes undergo AS events. AS can diversify the expression patterns of genes, thereby increasing the diversity of proteins and playing a significant role in the occurrence and development of tumors. In this study, we downloaded 599 clinical data and 169 transcriptome analysis data from The Cancer Genome Atlas (TCGA) database. Besides, we collected AS data about GBM from TCGA‐SpliceSeq. The overall survival (OS) related AS events in GBM were determined through least absolute shrinkage and selection operator (Lasso) and Cox analysis. Subsequently, the association of these 1825 OS‐related AS events with patient survival was validated using the Kaplan–Meier survival analysis, receiver operating characteristic curve, risk curve analysis, and independent prognostic analysis. Finally, we depicted the AS–SF regulatory network, illustrating the interactions between splicing factors and various AS events in GBM. Additionally, we identified three splicing factors (RNU4‐1, SEC31B, and CLK1) associated with patient survival. In conclusion, based on AS occurrences, we developed a predictive risk model and constructed an interaction network between GBM‐related AS events and SFs, aiming to shed light on the underlying mechanisms of GBM pathogenesis and progression. [ABSTRACT FROM AUTHOR]

Inferring cell type proportions from bulk transcriptome data is crucial in immunology and oncology. Here, we introduce guided LDA deconvolution (GLDADec), a bulk deconvolution method that guides topics using cell type-specific marker gene names to estimate topic distributions for each sample. Through benchmarking using blood-derived datasets, we demonstrate its high estimation performance and robustness. Moreover, we apply GLDADec to heterogeneous tissue bulk data and perform comprehensive cell type analysis in a data-driven manner. We show that GLDADec outperforms existing methods in estimation performance and evaluate its biological interpretability by examining enrichment of biological processes for topics. Finally, we apply GLDADec to The Cancer Genome Atlas tumor samples, enabling subtype stratification and survival analysis based on estimated cell type proportions, thus proving its practical utility in clinical settings. This approach, utilizing marker gene names as partial prior information, can be applied to various scenarios for bulk data deconvolution. GLDADec is available as an open-source Python package at https://github.com/mizuno-group/GLDADec. [ABSTRACT FROM AUTHOR]

Introduction: Various pieces of evidence suggest an elevation in the levels of EGFR and HER2 in different cancers leading to the proliferation, invasion, and metastasis of cancer cells. In this study, we conducted a comprehensive investigation into the expression alterations of these two receptors in various cancers using in silico data. In addition, we investigated the therapeutic potential of lapatinib as an inhibitor of these receptors in various cancer types. Methods: RNAseq data for prevalent cancers were downloaded from The Cancer Genome Atlas (TCGA). After initial preprocessing, expression changes of HER2, EGFR, and candidate genes—identified based on their association with EGFR and HER2 signaling pathways—were examined. Human protein atlas data were utilized to assess the protein expression of HER2 and EGFR. GSE129254 was employed to identify molecular pathways and candidate genes associated with lapatinib. The protein-protein interaction network was used to identify lapatinib-influenced hub genes. Clinical data for common cancers were used to investigate the correlation between the expression of candidate genes and patients' mortality rates by Cox regression test. Results: The findings clearly indicated a significant increase in the expression levels of HER2 and EGFR in cancers such as kidney, lung, breast, bladder, pancreas, head and neck, stomach, and endometrial, both at the mRNA and protein levels (p-value

Background The incidence and mortality of cervical cancer remain high in female malignant tumors worldwide. There is still a lack of diagnostic and prognostic markers for cervical carcinoma. This study aimed to screen differentially expressed genes (DEGs) between normal and cervical cancer tissues to identify candidate genes for further research. Methods Uterine cervical specimens were resected from our clinical patients after radical hysterectomy. Three patients’ transcriptomic datasets were built by the next generation sequencing (NGS) results. DEGs were selected through the edgeR and DESeq2 packages in the R environment. Functional enrichment analysis, including GO/DisGeNET/KEGG/Reactome enrichment analysis, was performed. Normal and cervical cancer tissue data from the public databases TCGA and GTEx were collected to compare the expression levels of 10 selected DEGs in tumor and normal tissues. ROC curve and survival analysis were performed to compare the diagnostic and prognostic values of each gene. The expression levels of candidate genes were verified in 15 paired clinical specimens via quantitative real-time polymerase chain reaction. Results There were 875 up-regulated and 1,482 down-regulated genes in cervical cancer samples compared with the paired adjacent normal cervical tissues according to the NGS analysis. The top 10 DEGs included APOD, MASP1, ACKR1, C1QTNF7, SFRP4, HSPB6, GSTM5, IGFBP6, F10 and DCN. GO, DisGeNET and Reactome analyses revealed that the DEGs were related to extracellular matrix and angiogenesis which might influence tumorigenesis. KEGG enrichment showed that PI3K-Akt signaling pathway might be involved in cervical cancer tumorigenesis and progression. The expression levels of selected genes were decreased in tumors in both the public database and our experimental clinical specimens. All the candidate genes showed excellent diagnostic value, and the AUC values exceeded 0.90. Additionally, APOD, ACKR1 and SFRP4 expression levels could help predict the prognosis of patients with cervical cancer. Conclusions In this study, we selected the top 10 DEGs which were down-regulated in cervical cancer tissues. All of them had dramatically diagnostic value. APOD, ACKR1 and SFRP4 were associated with the survivals of cervical cancer. C1QTNF7, HSPB6, GSTM5, IGFBP6 and F10 were first reported to be candidate genes of cervical carcinoma.

HPV-associated oropharynx carcinoma (HPVOPC) tumors have a relatively low mutational burden. Elucidating the relative contributions of other tumor alterations, such as DNA methylation alterations, alternative splicing events (ASE), and copy number variation (CNV), could provide a deeper understanding of carcinogenesis drivers in this disease. We applied network propagation analysis to multiple classes of tumor alterations in a discovery cohort of 46 primary HPVOPC tumors and 25 cancer-unaffected controls and validated our findings with TCGA data. We identified significant overlap between differential gene expression networks and all alteration classes, and this association was highest for methylation and lowest for CNV. Significant overlap was seen for gene clusters of G protein-coupled receptor (GPCR) pathways. HPV16-human protein interaction analysis identified an enriched cluster defined by an immune-mediated GPCR signal, including CXCR3 cytokines CXCL9, CXCL10, and CXCL11. CXCR3 was found to be expressed in primary HPVOPC, and scRNA-seq analysis demonstrated CXCR3 ligands to be highly expressed in M2 macrophages. In vivo models demonstrated decreased tumor growth with antagonism of the CXCR3 receptor in immunodeficient but not immunocompetent mice, suggesting that the CXCR3 axis can drive tumor proliferation in an autocrine fashion, but the effect is tempered by an intact immune system. In conclusion, methylation, ASE, and SNV alterations are highly associated with network gene expression changes in HPVOPC, suggesting that ASE and methylation alterations have an important role in driving the oncogenic phenotype. Network analysis identifies GPCR networks, specifically the CXCR3 chemokine axis, as modulators of tumor-immune interactions that may have proliferative effects on primary tumors as well as a role for immunosurveillance; however, CXCR3 inhibition should be used with caution, as these agents may both inhibit and stimulate tumor growth considering the competing effects of this cytokine axis. Further investigation is needed to explore opportunities for targeted therapy in this setting.

Abstract Disulfidptosis represents a novel cell death mechanism triggered by disulfide stress, with potential implications for advancements in cancer treatments. Although emerging evidence highlights the critical regulatory roles of long non-coding RNAs (lncRNAs) in the pathobiology of lung adenocarcinoma (LUAD), research into lncRNAs specifically associated with disulfidptosis in LUAD, termed disulfidptosis-related lncRNAs (DRLs), remains insufficiently explored. Using The Cancer Genome Atlas (TCGA)-LUAD dataset, we implemented ten machine learning techniques, resulting in 101 distinct model configurations. To assess the predictive accuracy of our model, we employed both the concordance index (C-index) and receiver operating characteristic (ROC) curve analyses. For a deeper understanding of the underlying biological pathways, we referred to the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) for functional enrichment analysis. Moreover, we explored differences in the tumor microenvironment between high-risk and low-risk patient cohorts. Additionally, we thoroughly assessed the prognostic value of the DRLs signatures in predicting treatment outcomes. The Kaplan–Meier (KM) survival analysis demonstrated a significant difference in overall survival (OS) between the high-risk and low-risk cohorts (p

Gastric cancer if the 5th most common oncological disease in the world and one of the leading causes of death associated with this pathology. In clinical practice, the Lauren classification is widely used for gastric cancer characterization, but it does not provide accurate information on tumor progression and does not allow to select the optimal therapeutic approach. More modern tumor typologies, for example proposed by the The Cancer Genome Atlas (TCGA) and the Asian Cancer Research Group (ACRG), are based on profiling of molecular changes in the tumor genome. Currently, several new classifications exist dividing gastric cancer into groups depending on response to different treatment, for example, checkpoint inhibitors or therapy based on activity of pathological pathways associated with immunity, DNA repair, oncogenic and stromal signatures. The proposed typologies improve diagnosis and treatment of this pathology. The review describes currently available classifications of gastric tumors and considers their practical potential.

Most of the currently used cancer immunotherapies inhibit the programmed cell death protein 1 (PD1)–programmed cell death 1 ligand 1 (PDL1) axis of T‐cells. However, dendritic cells (DCs) controlled by natural killer (NK) cells via the FMS‐related tyrosine kinase 3 (FLT3) axis are necessary for activation of T‐cells. The aim of the study was to evaluate FLT3 as a prognostic factor and determine its role in immune infiltration (with emphasis on NK cells and DCs). Using The Cancer Genome Atlas (TCGA) database, we performed bioinformatic analysis of the gene expression datasets of 501 lung squamous cell carcinoma (LUSC) and 515 lung adenocarcinoma (LUAD) patient who had corresponding clinical data [analysis was performed in R (version 4.2.0)]. Disease‐free survival (DFS) differed between the FLT3‐low and FLT3‐high expression groups, respectively, in LUSC (61.0 vs 71.3 months P = 0.075) and LUAD (32.7 vs 47.5 months P = 0.045). A tumor microenvironment (TME) with high immune infiltration and rich in T‐cell exhaustion markers was observed in the FLT3‐high group. We showed overexpression of NK cell and DC gene signatures in the FLT3‐high expression group as well as overexpression of key effector genes of the cyclic GMP‐AMP synthase (cGAS)–stimulator of interferon genes protein (STING) pathway, which is crucial in response to radiotherapy. High expression of FLT3 in the TME was associated with immune cell infiltration (especially of NK cells and DCs), increased expression of T‐cell exhaustion markers and expression of effector genes of the cGAS‐STING pathway, which may consequently increase susceptibility to immunotherapy and radiotherapy. High FLT3 expression correlated with prolonged DFS in the LUSC and LUAD cohorts.

Longfei Fan,1 Zhongqiang Qin,1 Di Wu,1 Yunchuan Yang,2 Yigang Zhang,2 Bo Xie,1 Jingyu Qian,1 Jianzhu Wei,1 Zhaoying Wang,1 Peipei Yang,1 Zhen Qian,1 Mu Yuan,1 Ziyi Zhu,1 Yulin Tan,1 Yi Tan2 1Department of Interventional Radiology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, 233000, People’s Republic of China; 2Department of Hepatobiliary Surgery, The First Affiliated Hospital of Bengbu Medical University, Bengbu, 233000, People’s Republic of ChinaCorrespondence: Yi Tan, Email doctortanyi2007@126.comPurpose: To study the relationship between LARS1 expression and immune infiltration and prognosis in hepatocellular carcinoma (HCC).Patients and Methods: The clinical characteristics together with LARS1 expression levels were obtained from the TCGA database. Immunohistochemistry confirmed LARS1 expression levels in paraneoplastic and tumor tissues. To investigate LARS1-related downstream molecules, a network of protein-protein interactions (PPIs) and the Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) were built. Furthermore, gene set enrichment analysis (GSEA) was used to analyze the pathways associated with LARS1 expression, whereas Single-sample GSEA (ssGSEA) was applied to perform an association study between immune infiltration and LARS1 gene expression. The TISCH Database and the TISIDB database were used to compare the difference of LARS1 expression in hepatocellular carcinoma and immunomodulators.Results: In comparison to that in normal tissues, the LARS1 expression level was elevated in tumor tissues. LARS1 expression exhibited substantial correlation with AFP, Histologic grade, pathologic stage, Residual tumor, and Vascular invasion in HCC. Higher LARS1 expression in HCC was linked to lower progression-free survival (PFS), disease-specific survival (DSS), and overall survival (OS). According to the GO/KEGG study, the important biological process (neutral lipid metabolic process), cellular component (triglyceride-rich plasma lipoprotein), molecular functions (lipase inhibitor activity), and KEGG pathway (cholesterol metabolism) could be a probable function mechanism in promoting HCC. Various pathways as per GSEA revealed that they were enriched in samples with elevated LARS1 expression. The expression level of LARS1 in malignant tumor cells after immunotherapy was significantly higher than that before immunotherapy. LARS1 was also remarkably linked to the infiltration level and the immunomodulators.Conclusion: LARS1 can be used as a biomarker of HCC, which is associated to immune infiltration of HCC.Keywords: hepatocellular carcinoma, leucyl-tRNA synthetase 1, bioinformatics analysis, biomarker, the cancer genome atlas

Intercellular adhesion molecule-1 (ICAM-1) is related to the occurrence and development of a variety of tumors. However, the role of ICAM-1 in the regulation of growth, metastasis, and clinical prognosis of the specific molecular subtypes of breast cancer, triple-negative breast cancer (TNBC), remains to be elucidated. This study explored the role of ICAM-1 in breast cancer and its triple-negative subtypes by systematic bioinformatics methods. The results showed that the expression of ICAM-1 in breast cancer tissues was significantly higher than that in normal tissues, especially in TNBC subtypes. In breast cancer, ICAM-1 mainly activates pathways related to apoptosis and epithelial–mesenchymal transition, while its overexpression in TNBC is associated with inflammatory response, apoptosis, and other processes. TNBC patients displaying higher ICAM-1 expression demonstrate enhanced responses to immunotherapy. High ICAM-1 expression is sensitive to drugs targeting tumor cell proliferation, apoptosis, and angiogenesis. In conclusion, breast cancer is characterized by significantly high expression of ICAM-1, with TNBC subtypes expressing ICAM-1 at much higher levels than other subtypes. The diagnosis, prognosis, development, distant metastases, and immunotherapy of TNBC are correlated with high expression of ICAM-1. This research provides available data for the further study of the diagnosis and treatment of TNBC.

Objective: The objective of this study was to assess whether Spen paralogue and orthologue C-terminal domaincontaining 1 (SPOCD1) gene expression could serve as a valuable prognostic and diagnostic biomarker in commoncancers, drawing from insights in recent literature. We sought to verify this concept by utilizing data sourced from TheCancer Genome Atlas (TCGA) alongside clinical samples.Materials and Methods: In this bioinformatics and experimental study, SPOCD1 RNA-seq data from 12 commoncancers were collected from TCGA Pan-Cancer Atlas using the R package "TCGA BIOLINKS" and normalized foranalysis. Various analytical tools, including receiver operating characteristic (ROC) curves, Kaplan-Meier and Coxregressionanalyses, and pathway enrichment analysis via the molecular signatures database (MSigDB), were applied.Drug resistance/sensitivity correlations with SPOCD1 expression were explored using the Gene Expression Omnibus(GEO) database. Clinical colorectal cancer (CRC) samples, including both colon and rectal malignant samples, werealso evaluated.Results: The results showed elevated SPOCD1 expression in most cancers (9/12), with notable prognostic valuein COAD, HNSC, KICH, and LIHC, and a correlation with poor prognosis in COAD for disease-free survival. ROCcurve analysis suggested SPOCD1 as a diagnostic biomarker in the majority of cases (7/12), although this patternwas inconsistent in clinical CRC samples. Pathway enrichment analysis revealed a strong correlation betweenSPOCD1 expression and critical molecular pathways. Unlike former results, we found that SPOCD1 upregulatedwhen interacting with PD-0325901. However, treating with Panobinostat led to downregulation. Both are as anticancerreagents.Conclusion: This study confirms the potential of SPOCD1 as a diagnostic and prognostic biomarker in prevalentcancers. However, extensive clinical data, particularly for CRC, are required to validate its reliability. DifferentCOAD subtypes may exhibit varying correlations with SPOCD1 expression levels, underscoring the need for furtherinvestigation to fully understand its diagnostic and prognostic value.

Patients with breast cancer show altered expression of genes within the pectoralis major skeletal muscle cells of the breast. Through analyses of The Cancer Genome Atlas (TCGA)-breast cancer (BRCA), we identified three previously uncharacterized putative novel tumor suppressor genes expressed in normal muscle cells, whose expression was downregulated in breast tumors. We found that NEDD4 binding protein 2-like 1 (N4BP2L1), pleckstrin homology domaincontaining family A member 4 (PLEKHA4), and brain-enriched guanylate kinaseassociated protein (BEGAIN) that are normally highly expressed in breast myoepithelial cells and smooth muscle cells were significantly downregulated in breast tumor tissues of a cohort of 50 patients with this cancer. Our data revealed that the low expression of PLEKHA4 in patients with menopause below 50 years correlated with a higher risk of breast cancer. Moreover, we identified N4BP2L1 and BEGAIN as potential biomarkers of HER2-positive breast cancer. Furthermore, low BEGAIN expression in breast cancer patients with blood fat, heart problems, and diabetes correlated with a higher risk of this cancer. In addition, protein and RNA expression analysis of TCGA-BRCA revealed N4BP2L1 as a promising diagnostic protein biomarker in breast cancer. In addition, the in silico data of scRNA-seq showed high expression of these genes in several cell types of normal breast tissue, including breast myoepithelial cells and smooth muscle cells. Thus, our results suggest their possible tumor-suppressive function in breast cancer and muscle development. [ABSTRACT FROM AUTHOR]

Disulfidptosis represents a novel cell death mechanism triggered by disulfide stress, with potential implications for advancements in cancer treatments. Although emerging evidence highlights the critical regulatory roles of long non-coding RNAs (lncRNAs) in the pathobiology of lung adenocarcinoma (LUAD), research into lncRNAs specifically associated with disulfidptosis in LUAD, termed disulfidptosis-related lncRNAs (DRLs), remains insufficiently explored. Using The Cancer Genome Atlas (TCGA)-LUAD dataset, we implemented ten machine learning techniques, resulting in 101 distinct model configurations. To assess the predictive accuracy of our model, we employed both the concordance index (C-index) and receiver operating characteristic (ROC) curve analyses. For a deeper understanding of the underlying biological pathways, we referred to the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) for functional enrichment analysis. Moreover, we explored differences in the tumor microenvironment between high-risk and low-risk patient cohorts. Additionally, we thoroughly assessed the prognostic value of the DRLs signatures in predicting treatment outcomes. The Kaplan–Meier (KM) survival analysis demonstrated a significant difference in overall survival (OS) between the high-risk and low-risk cohorts (p < 0.001). The prognostic model showed robust performance, with an area under the ROC curve exceeding 0.75 at one year and maintaining a value above 0.72 in the two and three-year follow-ups. Further research identified variations in tumor mutational burden (TMB) and differential responses to immunotherapies and chemotherapies. Our validation, using three GEO datasets (GSE31210, GSE30219, and GSE50081), revealed that the C-index exceeded 0.67 for GSE31210 and GSE30219. Significant differences in disease-free survival (DFS) and OS were observed across all validation cohorts among different risk groups. The prognostic model offers potential as a molecular biomarker for LUAD prognosis. [ABSTRACT FROM AUTHOR]

APC and TP53 are the two most regularly mutated genes in colon adenocarcinoma (COAD), especially in progressive malignancies and antitumoral immune response. The current bioinformatics analysis investigates the APC and TP53 gene expression profile in colon adenocarcinoma as a prognostic characteristic for survival, particularly concentrating on the correlated immune microenvironment. Clinical and genetic data of colon cancer and normal tissue samples were obtained from The Cancer Genome Atlas (TCGA)-COAD and Genotype-Tissue Expression (GTEx) online databases, respectively. The genetic differential expressions were analyzed in both groups via the one-way ANOVA test. Kaplan–Meier survival curves were applied to estimate the overall survival (OS). P < 0.05 was fixed as statistically significant. On Tumor Immune Estimation Resource and Gene Expression Profiling Interactive Analysis databases, the linkage between immune cell recruitment and APC and TP53 status was assessed through Spearman's correlation analysis. APC and TP53 were found mutated in 66.74% and 85.71% of the 454 and 7 TCGA-COAD patients in colon and rectosigmoid junction primary sites, respectively with a higher log2-transcriptome per million reads compared to the GTEx group (318 samples in sigmoid and 368 samples in transverse). Survival curves revealed a worse significant OS for the high-APC and TP53 profile colon. Spearman's analysis of immune cells demonstrated a strong positive correlation between the APC status and infiltration of T cell CD4+, T cell CD8+, NK cell, and macrophages and also a positive correlation between status and infiltration of T cell CD4+, T cell CD8+. APC and TP53 gene mutations prevail in colon cancer and are extremely associated with poor prognosis and shortest survival. The infiltrating T cell CD4+, T cell CD8+, NK cell, and macrophages populate the colon microenvironment and regulate the mechanisms of tumor advancement, immune evasion, and sensitivity to standard chemotherapy. More comprehensive research is needed to demonstrate these results and turn them into new therapeutic outlooks. [ABSTRACT FROM AUTHOR]

This study examines the prognostic role and immunological relevance of EMP1 (epithelial membrane protein-1) in a pan-cancer analysis, with a focus on ovarian cancer. Utilizing data from TCGA, CCLE, and GTEx databases, we assessed EMP1 mRNA expression and its correlation with tumor progression, prognosis, and immune microenvironment across various cancers. Our results indicate that EMP1 expression is significantly associated with poor prognosis in multiple cancer types, including ovarian, bladder, testicular, pancreatic, breast, brain, and uveal melanoma. Immune-related analyses reveal a positive correlation between EMP1 and immune cell infiltration, particularly neutrophils, macrophages, and dendritic cells, as well as high expression of immune checkpoint such as CD274, HAVCR2, IL10, PDCD1LG2, and TGFB1 in most tumors. In vivo experiments confirm that EMP1 promotes ovarian cancer cell proliferation, metastasis, and invasion. In conclusion, EMP1 emerges as a potential prognostic biomarker and therapeutic target in various cancers, particularly ovarian cancer, due to its influence on tumor progression and immune cell dynamics. Further research is warranted to elucidate the precise mechanisms of EMP1 in cancer biology and to translate these findings into clinical applications. [ABSTRACT FROM AUTHOR]

Although new cell-based research suggests a link between PPFIA4 and colon adenocarcinoma cancer, there is currently no pan-cancer study available. Using The Cancer Genome Atlas datasets, we firstly investigated the possible oncogenic function of PPFIA4 in 33 tumors. We discovered that PPFIA4 is substantially expressed in most malignancies and is associated with tumor patient prognosis. Furthermore, missense mutation and amplification of the PPFIA4 gene were the most common types of genetic change. In contrast to lung squamous cell carcinoma, tumor purity in prostate adenocarcinoma was strongly negatively connected with PPFIA4 expression and considerably positively correlated with the amount of infiltration of cluster of differentiation 8+ T cells, dendritic cells, macrophages, cluster of differentiation 4+ T cells, B cells and neutrophils in the tumor microenvironment. PPFIA4 expression in bladder cancer and lung squamous cell carcinoma is a strong correlation with the expression levels of tumor microenvironment, M1 and M2 macrophages, which are seen in the majority of monocyte marker groups. Furthermore, the functional mechanisms of PPFIA4 were influenced by chemical synaptic transmission as well as the development of the nervous system. In summary, our work provided essential insights into PPFIA4 dysregulation in pan-cancer and prompted potential molecular mechanisms in the progression of cancer, which highlight its potential therapeutic target for patients. [ABSTRACT FROM AUTHOR]

Most of the currently used cancer immunotherapies inhibit the programmed cell death protein 1 (PD1)–programmed cell death 1 ligand 1 (PDL1) axis of T‐cells. However, dendritic cells (DCs) controlled by natural killer (NK) cells via the FMS‐related tyrosine kinase 3 (FLT3) axis are necessary for activation of T‐cells. The aim of the study was to evaluate FLT3 as a prognostic factor and determine its role in immune infiltration (with emphasis on NK cells and DCs). Using The Cancer Genome Atlas (TCGA) database, we performed bioinformatic analysis of the gene expression datasets of 501 lung squamous cell carcinoma (LUSC) and 515 lung adenocarcinoma (LUAD) patient who had corresponding clinical data [analysis was performed in R (version 4.2.0)]. Disease‐free survival (DFS) differed between the FLT3‐low and FLT3‐high expression groups, respectively, in LUSC (61.0 vs 71.3 months P = 0.075) and LUAD (32.7 vs 47.5 months P = 0.045). A tumor microenvironment (TME) with high immune infiltration and rich in T‐cell exhaustion markers was observed in the FLT3‐high group. We showed overexpression of NK cell and DC gene signatures in the FLT3‐high expression group as well as overexpression of key effector genes of the cyclic GMP‐AMP synthase (cGAS)–stimulator of interferon genes protein (STING) pathway, which is crucial in response to radiotherapy. High expression of FLT3 in the TME was associated with immune cell infiltration (especially of NK cells and DCs), increased expression of T‐cell exhaustion markers and expression of effector genes of the cGAS‐STING pathway, which may consequently increase susceptibility to immunotherapy and radiotherapy. High FLT3 expression correlated with prolonged DFS in the LUSC and LUAD cohorts. [ABSTRACT FROM AUTHOR]

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

Introduction: Esophageal squamous cell carcinoma (ESCC) accounts for over 90% of all esophageal tumors. However, the molecular mechanism underlying ESCC development and prognosis remains unclear, and there are still no effective molecular biomarkers for diagnosing or predicting the clinical outcome of patients with ESCC. Here, we used bioinformatics analysis to identify potential biomarkers and therapeutic targets for ESCC.Methodology: Differentially expressed genes (DEGs) between ESCC and normal esophageal tissue samples were obtained by comprehensively analyzing publicly available RNA-seq datasets from the TCGA and GTEX. Gene Ontology (GO) annotation and Reactome pathway analysis identified the biological roles of the DEGs. Moreover, the Cytoscape 3.10.1 platform and subsidiary tools such as CytoHubba were used to visualize the DEGs’ protein-protein interaction (PPI) network and identify hub genes, Furthermore our results are validated by using Single-cell RNA analysis. Results: Identification of 2524 genes exhibiting altered expression enriched in pathways including keratinization, epidermal cell differentiation, G alpha(s) signaling events, and biological process of cell proliferation and division, extracellular matrix (ECM) disassembly, and muscle function. Moreover, upregulation of hallmarks E2F targets, G2M checkpoints, and TNF signaling. CytoHubba revealed 20 hub genes that had a valuable influence on the progression of ESCC in these patients. Among these, the high expression levels of four genes, CDK1 MAD2L1, PLK1, and TOP2A, were associated with critical dependence for cell survival in ESCC cell lines, as indicated by CRISPR dependency scores, gene expression data, and cell line metadata. We also identify the molecules targeting these essential hub genes, among which GSK461364 is a promising inhibitor of PLK1, BMS265246, and Valrubicin inhibitors of CDK1 and TOP2A, respectively. Moreover, we identified that elevated expression of MMP9 is associated with worse overall survival in ESCC patients, which may serve as potential prognostic biomarker or therapeutic target for ESCC. The single-cell RNA analysis showed MMP9 is highly expressed in myeloid, fibroblast, and epithelial cells, but low in T cells, endothelial cells, and B cells. This suggests MMP9’s role in tumor progression and matrix remodeling, highlighting its potential as a prognostic marker and therapeutic target.Discussion: Our study identified key hub genes in ESCC, assessing their potential as therapeutic targets and biomarkers through detailed expression and dependency analyses. Notably, MMP9 emerged as a significant prognostic marker with high expression correlating with poor survival, underscoring its potential for targeted therapy. These findings enhance our understanding of ESCC pathogenesis and highlight promising avenues for treatment.

Objective: To explore the potential therapeutic targets and mechanisms of resveratrol in the treatment of non-small cell lung cancer (NSCLC), a comprehensive study was conducted incorporating network pharmacology, molecular docking methods, and experimental validation. Methods: The targets of resveratrol were searched on Swiss Target Prediction database and Target net database. NSCLC targets were gathered from Genecards, OMIM, TTD databases. The intersection of drug targets and disease targets was obtained using Venny 2.1.0 platform. Next, Cytoscape 3.7.2 software was applied along with the String database to generate target protein interaction networks (PPI) and perform topological analysis. GO functional enrichment analysis and KEGG pathway enrichment analysis of intersecting targets were conducted using the Metascape database, resulting in gene maps of the intersecting targets. Molecular docking studies were performed for the top three ranked core targets and resveratrol using Autodock Vina software. Clinical case samples were obtained from The Cancer Genome Atlas (TCGA) database to analyze the expression of relevant targets in NSCLC patients (n=1017) and healthy controls (n=627). The effects of different concentrations (30 and 50 μmol/L) of resveratrol on the protein expression of SRC, EGFR and PI3K/AKT signaling pathway in human lung adenocarcinoma A549 cells were examined using Western Blot at the cellular level. Results: Total of 40 potential targets were screened out, followed by obtaining 8 key targets after topological analysis. These keys targets, including EGFR, SRC, and ESR1 were closely associated with NSCLC. The treatment of NSCLC with resveratrol primarily involved multiple signaling pathways, such as tumor proteoglycans, estrogen signaling and PI3K/AKT. Molecular docking results demonstrated that resveratrol had a good binding ability with the target protein. Clinical sample results revealed that the expression of EGFR, SRC, ESR1, HSP90AA1, and MMP9 was upregulated, while the expression of TNF, CDC42, and RELA was downregulated in NSCLC patients. Cellular experiments indicated that resveratrol could inhibit the protein expression of SRC, EGFR, p-PI3K, and p-AKT in human lung adenocarcinoma A549 cells in a dose-dependent manner. Conclusion: This study demonstrates that resveratrol involves multiple targets and signaling pathways in the treatment of NSCLC, and clarifies that resveratrol could exert its anti-cancer effects by inhibiting the PI3K/AKT signaling pathway.

Glioma stem cells (GSCs) contribute to the pathogenesis of glioblastoma (GBM), which is the most malignant form of glioma. The implications and underlying mechanisms of protein glycosylation in GSC phenotypes and GBM malignancy are not fully understood. The implication of protein glycosylation and the corresponding candidate genes on the stem cell properties of GSCs and poor clinical outcomes in GBM were investigated, using datasets from the Gene Expression Omnibus, The Cancer Genome Atlas, and the Chinese Glioma Genome Atlas, accompanied by biological validation in vitro. N-linked glycosylation was significantly associated with GSC properties and the prognosis of GBM in the integrated bioinformatics analyses of clinical specimens. N-linked glycosylation was associated with the glioma grade, molecular biomarkers, and molecular subtypes. The expression levels of the asparagine-linked glycosylation (ALG) enzyme family, which is essential for the early steps in the biosynthesis of N-glycans, were prominently associated with GSC properties and poor survival in patients with GBM with high stem-cell properties. Finally, the oxidative phosphorylation pathway was primarily enriched in GSCs with a high expression of the ALG enzyme family. These findings suggest the role of N-linked glycosylation in the regulation of GSC phenotypes and GBM malignancy.

IntroductionLiver cancer is the sixth most common and second most fatal type of cancer worldwide. Few treatment options are available as patients with liver cancer are often diagnosed in an advanced stage due to a lack of clinical symptoms. Effectively preventing and treating liver cancer relies heavily on early diagnosis; early diagnosis results from identifying and monitoring high-risk patients. Epigenetic risk factors, such as hepatitis B, hepatitis C, cirrhosis, nonalcoholic fatty liver disease, and alcohol/tobacco abuse, are highly prevalent in Asia and likely cause Asians to have a higher incidence and mortality rate of liver cancer. While these acquired risk factors are relatively well understood, the underlying genetic background of liver cancer in Asians has not been well established or correlated with clinical outcomes.MethodsIn this study, we accessed The Cancer Genome Atlas (TCGA) hepatocellular carcinoma clinical and mutation data through TCGAbiolinksGUI.ResultsWe found that mutations in five genes (TP53, TTN, OBSCN, MUC5B, CSMD1) were statistically linked with increased mortality in Asians compared to non-Asians, four of which (TTN, OBSCN, MUC5B, CSMD1) were also more prevalent in the Asian population. Within the Asian cohort, two gene mutations (TTN, HMCN1) were statistically linked with worse outcomes. We also found that the TP53 mutation predicts worse outcomes within the non-Asian cohort but not within the Asian cohort.Discussion/conclusionOur findings can improve cancer care in the Asian population through better disease prognostication, evaluations for potential targeted therapy, and a deeper understanding of liver cancer pathogenesis.

Abstract Background High-grade serious ovarian carcinoma (HGSOC) is a subtype of ovarian cancer with a different prognosis attributable to genetic heterogeneity. The prognosis of patients with advanced HGSOC requires prediction by genetic markers. This study systematically analyzed gene expression profile data to establish a genetic marker for predicting HGSOC prognosis. Methods The RNA-seq data set and information on clinical follow-up of HGSOC were retrieved from Gene Expression Omnibus (GEO) database, and the data were standardized by DESeq2 as a training set. On the other hand, HGSOC RNA sequence data and information on clinical follow-up were retrieved from The Cancer Genome Atlas (TCGA) as a test set. Additionally, ovarian cancer microarray data set was obtained from GEO as the external validation set. Prognostic genes were screened from the training set, and characteristic selection was performed using the least absolute shrinkage and selection operator (LASSO) with 80% re-sampling for 5000 times. Genes with a frequency of more than 2000 were selected as robust biomarkers. Finally, a gene-related prognostic model was validated in both the test and GEO validation sets. Results A total of 148 genes were found to be significantly correlated with HGSOC prognosis. The expression profile of these genes could stratify HGSOC prognosis and they were enriched to multiple tumor-related regulatory pathways such as tyrosine metabolism and AMPK signaling pathway. AKR1B10 and ANGPT4 were obtained after 5000-time re-sampling by LASSO regression. AKR1B10 was associated with the metastasis and progression of several tumors. In this study, Cox regression analysis was performed to create a 2-gene signature as an independent prognostic factor for HGSOC, which has the ability to stratify risk samples in all three data sets (p