Necroptosis-Related Genes Associated With Immune Activity and Prognosis of Colorectal Cancer.
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ABSTRACT:
SUBMITTER: Peng X
PROVIDER: S-EPMC9243386 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background: Colorectal cancer (CRC) is one gastrointestinal malignancy, accounting for 10% of cancer diagnoses and cancer-related deaths worldwide each year. Therefore, it is urgent to identify genes involved in CRC predicting the prognosis. Methods: CRC's data were acquired from the Gene Expression Omnibus (GEO) database (GSE39582 and GSE41258 datasets) and The Cancer Genome Atlas (TCGA) database. The differentially expressed necroptosis-related genes (DENRGs) were sorted out between tumor and normal tissues. Univariate Cox regression analysis and least absolute shrinkage and selectionator operator (LASSO) analysis were applied to selected DENRGs concerning patients' overall survival and to construct a prognostic biomarker. The effectiveness of this biomarker was assessed by the Kaplan-Meier curve and the receiver operating characteristic (ROC) analysis. The GSE39582 dataset was utilized as external validation for the prognostic signature. Moreover, using univariate and multivariate Cox regression analyses, independent prognostic factors were identified to construct a prognostic nomogram. Next, signaling pathways regulated by the signature were explored through the gene set enrichment analysis (GSEA). The single sample gene set enrichment analysis (ssGSEA) algorithm and tumor immune dysfunction and exclusion (TIDE) were used to explore immune correlation in the two groups, high-risk and low-risk ones. Finally, prognostic genes' expression was examined in the GSE41258 dataset. Results: In total, 27 DENRGs were filtered, and a necroptosis-related prognostic signature based on 6 DENRGs was constructed, which may better understand the overall survival (OS) of CRC. The Kaplan-Meier curve manifested the effectiveness of the prognostic signature, and the ROC curve showed the same result. In addition, univariate and multivariate Cox regression analyses revealed that age, pathology T, and risk score were independent prognostic factors, and a nomogram was established. Furthermore, the prognostic signature was most significantly associated with the apoptosis pathway. Meanwhile, 24 immune cells represented significant differences between two groups, like the activated B cell. Furthermore, 32 immune checkpoints, TIDE scores, PD-L1 scores, and T-cell exclusion scores were significantly different between the two groups. Finally, a 6-gene prognostic signature represented different expression levels between tumor and normal samples significantly in the GSE41258 dataset. Conclusion: Our study established a signature including 6 genes and a prognostic nomogram that could significantly assess the prognosis of patients with CRC.
| S-EPMC9421078 | biostudies-literature
Project description:Background: Necroptosis, a type of programmed cell death, has been implicated in a variety of cancer-related biological processes. However, the roles of necroptosis-related genes in thyroid cancer yet remain unknown. Methods: A necroptosis-related gene signature was constructed using the least absolute shrinkage and selection operator (LASSO) regression analysis and Cox regression analysis. The predictive value of the prognostic signature was validated in an internal cohort. Additionally, the single-sample gene set enrichment analysis (ssGSEA) was used to examine the relationships between necroptosis and immune cells, immunological functions, and immune checkpoints. Next, the modeled genes expressions were validated in 96 pairs of clinical tumor and normal tissue samples. Finally, the effects of modeled genes on PTC cells were studied by RNA interference approaches in vitro. Results: In this study, the risk signature of seven necroptosis-related genes was created to predict the prognosis of papillary thyroid cancer (PTC) patients, and all patients were divided into high- and low-risk groups. Patients in the high-risk group fared worse in terms of overall survival than those in the low-risk group. The area under the curve (AUC) of the receiving operating characteristic (ROC) curves proved the predictive capability of created signature. The risk score was found to be an independent risk factor for prognosis in multivariate Cox analysis. The low-risk group showed increased immune cell infiltration and immunological activity, implying that they might respond better to immune checkpoint inhibitor medication. Next, GEO database and qRT-PCR in 96 pairs of matched tumorous and non-tumorous tissues were used to validate the expression of the seven modeled genes in PTCs, and the results were compatible with TCGA database. Finally, overexpression of IPMK, KLF9, SPATA2 could significantly inhibit the proliferation, invasion and migration of PTC cells. Conclusion: The created necroptosis associated risk signature has the potential to have prognostic capability in PTC for patient outcome. The findings of this study could pave the way for further research into the link between necroptosis and tumor immunotherapy.
| S-EPMC9520455 | biostudies-literature
Project description:Colorectal cancer (CRC) is a heterogeneous disease and one of the most prevalent malignancies worldwide. Previous research has demonstrated that mitophagy is crucial to developing colorectal cancer. This study aims to examine the association between mitophagy-related genes and the prognosis of CRC patients. Gene expression profiles and clinical information of CRC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) regression analysis were applied to establish a prognostic signature using mitophagy related genes. Kaplan-Meier and receiver operating characteristic (ROC) curves were used to analyze patient survival and predictive accuracy. Meanwhile, we also used the Genomics of Drug Sensitivity in Cancer (GDSC) database and Tumor Immune Dysfunction and Exclusion (TIDE) algorithm to estimate the sensitivity of chemotherapy, targeted therapy and immunotherapy. ATG14 overexpression plasmid was used to regulate the ATG14 expression level in HCT116 and SW480 cell lines, and cell counting kit-8, colony formation and transwell migration assay were performed to validate the function of ATG14 in CRC cells. A total of 22 mitophagy-driven genes connected with CRC survival were identified, and then a novel prognostic signature was established based on 10 of them (AMBRA1, ATG14, MAP1LC3A, MAP1LC3B, OPTN, VDAC1, ATG5, CSNK2A2, MFN1, TOMM22). Patients were divided into high-risk and low-risk groups based on the median risk score, and the survival of patients in the high-risk group was significantly shorter in both the training cohort and two independent cohorts. ROC curve showed that the area under the curves (AUC) of 1-, 3- and 5-year survival were 0.66, 0.66 and 0.64, respectively. Multivariate Cox regression analysis confirmed the independent prognostic value of the signature. Then we constructed a Nomogram combining the risk score, age and M stage, which had a concordance index of survival prediction of 0.77 (95% CI 0.71-0.83) and more robust predictive accuracy. Results showed that CD8+ T cells, regulatory T cells and activated NK cells were significantly more enriched in the high-risk group. Furthermore, patients in the high-risk group are more sensitive to targeted therapy or chemotherapy, including bosutinib, elesclomol, lenalidomide, midostaurin, pazopanib and sunitinib, while the low-risk group is more likely to benefit from immunotherapy. Finally, in vitro study confirmed the oncogenic significance of ATG14 in both HCT116 and SW480 cells, whose overexpression increased CRC cell proliferation, colony formation, and migration. In conclusion, we developed a novel mitophagy-related gene signature that can be utilized not only as an independent predictive biomarker but also as a tool for tailoring personalizing treatment for CRC patients, and we confirmed ATG14 as a novel oncogene in CRC.
| S-EPMC9636133 | biostudies-literature
Project description:Background and aimLipid metabolic reprogramming is considered to be a new hallmark of malignant tumors. The purpose of this study was to explore the expression profiles of lipid metabolism-related genes (LMRG) in colorectal cancer (CRC).MethodsThe lipid metabolism statuses of 500 CRC patients from the Cancer Genome Atlas (TCGA) and 523 from the Gene Expression Omnibus (GEO GSE39582) database were analyzed. The risk signature was constructed by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) Cox regression.ResultsA novel four-LMRG signature (PROCA1, CCKBR, CPT2, and FDFT1) was constructed to predict clinical outcomes in CRC patients. The risk signature was shown to be an independent prognostic factor for CRC and was associated with tumour malignancy. Principal components analysis demonstrated that the risk signature could distinguish between low- and high-risk patients. There were significantly differences in abundances of tumor-infiltrating immune cells and mutational landscape between the two risk groups. Patients in the low-risk group were more likely to have higher tumor mutational burden, stem cell characteristics, and higher PD-L1 expression levels. Furthermore, a genomic-clinicopathologic nomogram was established and shown to be a more effective risk stratification tool than any clinical parameter alone.ConclusionsThis study demonstrated the prognostic value of LMRG and showed that they may be partially involved in the suppressive immune microenvironment formation.
| S-EPMC8571885 | biostudies-literature
Project description:BackgroundGlioma is a highly aggressive brain cancer with a poor prognosis. Necroptosis is a form of programmed cell death occurring during tumor development and in immune microenvironments. The prognostic value of necroptosis in glioma is unclear. This study aimed to develop a prognostic glioma model based on necroptosis.MethodsA necroptosis-related risk model was constructed by Cox regression analysis based on The Cancer Genome Atlas (TCGA) training set, validated in two Chinese Glioma Genome Atlas (CGGA) validation sets. We explored the differences in immune infiltration and immune checkpoint genes between low and high risk groups and constructed a nomogram. Moreover, we compiled a third validation cohort including 43 glioma patients. The expression of necroptosis-related genes was verified in matched tissues using immunochemical staining in the third cohort, and we analyzed their relationship to clinicopathological features.ResultsThree necroptosis-related differentially expressed genes (EZH2, LEF1, and CASP1) were selected to construct the prognostic model. Glioma patients with a high risk score in the TCGA and CGGA cohorts had significantly shorter overall survival. The necroptosis-related risk model and nomogram exhibited good predictive performance in the TCGA training set and the CGGA validation sets. Furthermore, patients in the high risk group had higher immune infiltration status and higher expression of immune checkpoint genes, which was positively correlated with poorer outcomes. In the third validation cohort, the expression levels of the three proteins encoded by EZH2, LEF1, and CASP1 in glioma tissues were significantly higher than those from paracancerous tissues. They were also closely associated with disease severity and prognosis.ConclusionsOur necroptosis-related risk model can be used to predict the prognosis of glioma patients and improve prognostic accuracy, which may provide potential therapeutic targets and a theoretical basis for treatment.
| S-EPMC9640834 | biostudies-literature
Project description:BackgroundNecroptosis is a recently discovered form of cell death that plays an important role in the occurrence and development of colon adenocarcinoma (COAD). Our study aimed to construct a risk score model to predict the prognosis of patients with COAD based on necroptosis-related genes.MethodsThe gene expression data of COAD and normal colon samples were obtained from the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was used to calculate the risk score based on prognostic necroptosis-related differentially expressed genes (DEGs). Based on the risk score, patients were classified into high- and low-risk groups. Then, nomogram models were built based on the risk score and clinicopathological features. Otherwise, the model was verified in the Gene Expression Omnibus (GEO) database. Additionally, the tumor microenvironment (TME) and the level of immune infiltration were evaluated by "ESTIMATE" and single-sample gene set enrichment analysis (ssGSEA). Functional enrichment analysis was carried out to explore the potential mechanism of necroptosis in COAD. Finally, the effect of necroptosis on colon cancer cells was explored through CCK8 and transwell assays. The expression of necroptosis-related genes in colon tissues and cells treated with necroptotic inducers (TNFα) and inhibitors (NEC-1) was evaluated by quantitative real-time polymerase chain reaction (qRT-PCR).ResultsThe risk score was an independent prognostic risk factor in COAD. The predictive value of the nomogram based on the risk score and clinicopathological features was superior to TNM staging. The effectiveness of the model was well validated in GSE152430. Immune and stromal scores were significantly elevated in the high-risk group. Moreover, necroptosis may influence the prognosis of COAD via influencing the cancer immune response. In in-vitro experiments, the inhibition of necroptosis can promote proliferation and invasion ability. Finally, the differential expression of necroptosis-related genes in 16 paired colon tissues and colon cancer cells was found.ConclusionA novel necroptosis-related gene signature for forecasting the prognosis of COAD has been constructed, which possesses favorable predictive ability and offers ideas for the necroptosis-associated development of COAD.
| S-EPMC9731216 | biostudies-literature
Project description:Colon adenocarcinoma is the most common type of colorectal cancer. The prognosis of advanced colorectal cancer patients who received treatment is still very poor. Therefore, identifying new biomarkers for prognosis prediction has important significance for improving treatment strategies. However, the power of biomarker analyses was limited by the used sample size of individual database. In this study, we combined Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases to expand the number of healthy tissue samples. We screened differentially expressed genes between the GTEx healthy samples and TCGA tumor samples. Subsequently, we applied least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis to identify nine prognosis-related immune genes: ANGPTL4, IDO1, NOX1, CXCL3, LTB4R, IL1RL2, CD72, NOS2, and NUDT6. We computed the risk scores of samples based on the expression levels of these genes and divided patients into high- and low-risk groups according to this risk score. Survival analysis results showed a significant difference in survival rate between the two risk groups. The high-risk group had a significantly lower overall survival rate and poorer prognosis. We found the receiver operating characteristic based on the risk score was showed to accurately predict patients' prognosis. These prognosis-related immune genes may be potential biomarkers for colorectal cancer diagnosis and treatment. Our open-source code is freely available from GitHub at https://github.com/gutmicrobes/Prognosis-model.git.
| S-EPMC9995717 | biostudies-literature
Project description:Pancreatic cancer (PCa) is a highly lethal and aggressive disease, characterized by high mortality rates. Although necroptosis plays a vital role in tumor progression, cancer metastasis, prognosis of cancer patients, necroptosis-related gene (NRG) sets have rarely been analyzed in PCa. Therefore, definition of novel necroptosis-related prognostic markers for PCa patients is urgently needed. Here, we screened 159 NRGs and identified 132 differentially expressed NRGs in The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) cohorts. Next, we employed univariate and multivariate Cox proportional regression models to establish a prognostic-related NRG signature comprising five NRGs that could stratify patients into high-risk and low-risk groups. Results from survival analysis showed that patients in the high-risk had dramatically shorter overall survival (OS) rates compared with their low-risk counterparts. Results from univariate and multivariate Cox regression analysis further confirmed the independent prognostic value of the established necroptosis-related signature, and the area under receiver (AUC) of the operating curve (ROC) for 1-, 3-, 5-years was 0.72, 0.74, and 0.75, respectively. Finally, we validated the signature efficacy using an independent cohort from the Gene Expression Omnibus (GEO) database. The ROC curve confirmed the predictive capacity of the five-gene signature. Furthermore, we validated expression of the signature proteins using the Human Protein Atlas (HPA) database. In conclusion, we successfully constructed a novel necroptosis-related signature for prognosis of patients with pancreatic cancer.
| S-EPMC8995900 | biostudies-literature
Project description:Bladder cancer, one of the most prevalent malignant cancers, has high rate of recurrence and metastasis. Owing to genomic instability and high-level heterogeneity of bladder cancer, chemotherapy and immunotherapy drugs sensitivity and lack of prognostic markers, the prognosis of bladder cancer is unclear. Necroptosis is a programmed modality of necrotic cell death in a caspase-independent form. Despite the fact that necroptosis plays a critical role in tumor growth, cancer metastasis, and cancer patient prognosis, necroptosis-related gene sets have rarely been studied in bladder cancer. As a result, the development of new necroptosis-related prognostic indicators for bladder cancer patients is critical. Herein, we assessed the necroptosis landscape of bladder cancer patients from The Cancer Genome Atlas database and classified them into two unique necroptosis-related patterns, using the consensus clustering. Then, using five prognosis-related genes, we constructed a prognostic model (risk score), which contained 5 genes (ANXA1, DOK7, FKBP10, MAP1B and SPOCD1). And a nomogram model was also developed to offer the clinic with a more useful prognostic indicator. We found that risk score was significantly associated with clinicopathological characteristics, TIME, and tumor mutation burden in patients with bladder cancer. Moreover, risk score was a valid guide for immunotherapy, chemotherapy, and targeted drugs. In our study, DOK7 was chosen to further verify our prognosis model, and functional assays indicated that knockdown the expression of DOK7 could prompt bladder cancer proliferation and migration. Our work demonstrated the potential role of prognostic model based on necroptosis genes in the prognosis, immune landscape and response efficacy of immunotherapy of bladder cancer.
| S-EPMC9883845 | biostudies-literature
Project description:BackgroundMany properties of cancer cells are reminiscent of those in normal stem cells. Genes important to stem cell development have been significantly implicated in the etiology and clinical outcome of colorectal cancer (CRC). However, the associations of genetic variations in these genes with CRC prognosis have not yet been elucidated.MethodsWe analyzed the effects of eight potentially functional single nucleotide polymorphisms (SNPs) in six stem cell-related genes on the prognosis of a well-characterized population of 380 Chinese CRC patients diagnosed from February 2006 to January 2010.ResultsThe most significant finding was related to rs879882, a variant in the 5' region of POU5F1 gene which encodes a protein essential for embryonic stem cell self-renewal and pluripotency, and induced pluripotent stem cell reprogramming. The variant-containing genotypes of rs879882 were associated with an increased risk of recurrence (hazard ratio [HR] = 2.10, 95% confidence interval [CI] 1.17-3.76, P = 0.01). In chemotherapy-stratified analysis, the association remained borderline significant in patients receiving chemotherapy (HR = 1.97, 95% CI 0.89-4.34, P = 0.09). In addition, a nonsynonymous SNP of APC gene was also significantly associated with recurrence risk in chemotherapy-treated patients (HR = 2.63, 95% CI 1.14-6.06 P = 0.02). Further analyses showed a combined effect of the two SNPs in predicting CRC recurrence in patients receiving chemotherapy (P = 0.04) but not in those without chemotherapy (P = 0.43). Moreover, an exploratory multivariate assessment model indicated that these two variants enhanced the power to predict recurrence after chemotherapy.ConclusionWe presented one of the first epidemiologic studies showing that stem cell-related genetic variants may impact CRC clinical outcomes, especially in chemotherapy-treated patients.
| S-EPMC3721524 | biostudies-literature