RESUMEN
Hepatocellular carcinoma (HCC) is a fatal disease with poor clinical outcomes. T cells play a vital role in the crosstalk between the tumour microenvironment and HCC. Single-cell RNA sequencing data were downloaded from the GSE149614 dataset. The T-cell-related prognostic signature (TRPS) was developed with the integrative procedure including 10 machine learning algorithms. The TRPS was established using 7 T-cell-related markers in the Cancer Genome Atlas cohort with 1-, 2- and 3-year area under curve values of 0.820, 0.725 and 0.678, respectively. TRPS acted as an independent risk factor for HCC patients. HCC patients with a high TRPS-based risk score had a higher Tumour Immune Dysfunction and Exclusion score, lower PD1 and CTLA4 immunophenoscore and lower level of immunoactivated cells, including CD8+ T cells and NK cells. The response rate was significantly higher in patients with low-risk scores in immunotherapy cohorts, including IMigor210 and GSE91061. The TRPS-based nomogram had a relatively good predictive value in evaluating the mortality risk at 1, 3 and 5 years in HCC. Overall, this study develops a TRPS by integrated bioinformatics analysis. This TRPS acted as an independent risk factor for the OS rate of HCC patients. It can screen for HCC patients who might benefit from immunotherapy, chemotherapy and targeted therapy.
Asunto(s)
Carcinoma Hepatocelular , Neoplasias Hepáticas , Humanos , Carcinoma Hepatocelular/diagnóstico , Carcinoma Hepatocelular/genética , Linfocitos T CD8-positivos , Neoplasias Hepáticas/diagnóstico , Neoplasias Hepáticas/genética , Algoritmos , Biología Computacional , Microambiente TumoralRESUMEN
Liver hepatocellular carcinoma (LIHC) is characterized by high morbidity, rapid progression and early metastasis. Although many efforts have been made to improve the prognosis of LIHC, the situation is still dismal. Inability to initiate anoikis process is closely associated with cancer proliferation and metastasis, affecting patients' prognosis. In this study, a corresponding gene signature was constructed to comprehensively assess the prognostic value of anoikis-related genes (ARGs) in LIHC. Using TCGA-LIHC dataset, the mRNA levels of the differentially expressed ARGs in LIHC and normal tissues were compared by Student t test. And prognostic ARGs were identified through Cox regression analysis. Prognostic signature was established and then externally verified by ICGC-LIRI-JP dataset and GES14520 dataset via LASSO Cox regression model. Potential functions and mechanisms of ARGs in LIHC were evaluated by functional enrichment analyses. And the immune infiltration status in prognostic signature was analyzed by ESTIMATE algorithm and ssGSEA algorithm. Furthermore, ARGs expression in LIHC tissues was validated via qRT-PCR and IHC staining from the HPA website. A total of 97 differentially expressed ARGs were detected in LIHC tissues. Functional enrichment analysis revealed these genes were mainly involved in MAP kinase activity, apoptotic signaling pathway, anoikis and PI3K-Akt signaling pathway. Afterward, the prognostic signature consisting of BSG, ETV4, EZH2, NQO1, PLK1, PBK, and SPP1 had a moderate to high predictive accuracy and served as an independent prognostic indicator for LIHC. The prognostic signature was also applicable to patients with distinct clinical parameters in subgroup survival analysis. And it could reflect the specific immune microenvironment in LIHC, which indicated high-risk group tended to profit from ICI treatment. Moreover, qRT-PCR and IHC staining showed increasing expression of BSG, ETV4, EZH2, NQO1, PLK1, PBK and SPP1in LIHC tissues, which were consistent to the results from TCGA database. The current study developed a novel prognostic signature comprising of 7 ARGs, which could stratify the risk and effectively predict the prognosis of LIHC patients. Furthermore, it also offered a potential indicator for immunotherapy of LIHC.
Asunto(s)
Carcinoma Hepatocelular , Neoplasias Hepáticas , Humanos , Carcinoma Hepatocelular/genética , Anoicis/genética , Pronóstico , Multiómica , Fosfatidilinositol 3-Quinasas , Neoplasias Hepáticas/genética , Microambiente TumoralRESUMEN
Stomach adenocarcinoma (STAD) is a highly aggressive and extremely heterogeneous gastric cancer characterized by high morbidity and mortality. Cuproptosis, a copper (Cu)-triggered modality of mitochondrial cell death, could regulate tumor proliferation and metastasis. Least absolute shrinkage and selection operator cox regression analysis was constructed to develop a prognostic cuproptosis-related signature. A lncRNA-miRNA-mRNA regulatory axis was performed to explore cuproptosis-related mechanism for STAD. The expression of FDX1, LIPT1, DLD, DLAT, PDHA1, PDHB, MTF1, GLS, and CDKN2A was upregulated in STAD versus normal tissue. We also summarized single nucleotide variants and copy number variation landscape of cuproptosis-related gene in STAD. Further analysis demonstrated that STAD patients with high expression of CDKN2A, DLD, GLS, and MTF1 and low expression of DLAT, FDX1, PDHA1 and PDHB had a poor overall survival (OS) and post progression survival (PPS) rate. By performing least absolute shrinkage and selection operator cox regression analysis, we constructed a cuproptosis-related prognostic signature for STAD. Further analysis demonstrated a significant correlation between FDX1 expression and immune cell infiltration, tumor mutational burden (TMB) score, microsatellite instability (MSI) score and drug sensitivity. Univariate and multivariate analysis indicated FDX1 expression and clinical stage as independent factors affecting the prognosis of STAD patients. We also identified a lncRNA MALAT1/miR-328-3p/FDX1 regulatory axis for STAD. Multi-omics approaches were performed to develop a cuproptosis-related signature with 2 genes (FDX1 and MTF1) for STAD. We also identified a lncRNA MALAT1/miR-328-3p/FDX1 regulatory axis for STAD.