Background Necroptosis is a new form of programmed cell death that is associated with cancer initiation, progression, immunity, and chemoresistance. However, the roles of necroptosis-related genes (NRGs) in colorectal cancer (CRC) have not been explored comprehensively. Methods In this study, we obtained NRGs and performed consensus molecular subtyping by “ConsensusClusterPlus” to determine necroptosis-related subtypes in CRC bulk transcriptomic data. The ssGSEA and CIBERSORT algorithms were used to evaluate the relative infiltration levels of different cell types in the tumor microenvironment (TME). Single-cell transcriptomic analysis was performed to confirm classification related to NRGs. NRG_score was developed to predict patients’ survival outcomes with low-throughput validation in a patients’ cohort from Fudan University Shanghai Cancer Center. Results We identified three distinct necroptosis-related classifications (NRCs) with discrepant clinical outcomes and biological functions. Characterization of TME revealed that there were two stable necroptosis-related phenotypes in CRC: a phenotype characterized by few TME cells infiltration but with EMT/TGF-pathways activation, and another phenotype recognized as immune-excluded. NRG_score for predicting survival outcomes was established and its predictive capability was verified. In addition, we found NRCs and NRG_score could be used for patient or drug selection when considering immunotherapy and chemotherapy. Conclusions Based on comprehensive analysis, we revealed the potential roles of NRGs in the TME, and their correlations with clinicopathological parameters and patients’ prognosis in CRC. These findings could enhance our understanding of the biological functions of necroptosis, which thus may aid in prognosis prediction, drug selection, and therapeutics development.
Ferroptosis is a non-apoptotic form of cell death recognized in recent years. Nonetheless, the potential role of ferroptosis-associated genes in immune regulation and tumor microenvironment formation remains unknown. In this study, we characterized the ferroptosis-associated patterns of colorectal cancer through integrative analyses of multiple datasets with transcriptomics, genomics, and single-cell transcriptome profiling. Three distinct ferroptosis-associated clusters (FAC1, FAC2 and FAC3) were identified from 1251 CRC bulk samples, which were associated with different clinical outcomes and biological pathways. The TME characterization revealed that the three patterns were highly consistent with known immune profiles: immune-desert (FAC1), immune-inflamed (FAC2) and immune-excluded (FAC3), respectively. Ferroptosis-associated immune and stromal-activated genes were obtained and characterized by corresponding function in CRC tumorigenesis. Further single-cell analyses identified the ferroptosis-associated immune responding tumor cells and ferroptosis-associated stromal cells infiltration pattern. Based on the Fersig score, which was extracted from the ferroptosis phenotype-related signature, patients with lower Fersig score were characterized by prolonged survival time and effective immune responses. Collectively, we uncovered the ferroptosis-associated patterns associated with TME diversity and immune response phenotype. The Fersig we constructed could be the potential therapeutic target genes to improve the efficacy of patients' immunotherapy. The Fersig scoring scheme could enhance the understanding of TME infiltration associated with ferroptosis and prediction of immunotherapy efficacy.
Lymph node metastasis (LNM) is closely related to the postoperative recurrence of colorectal cancer (CRC), and greatly affects patient survival. Conducting Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA), we found that the epithelial-mesenchymal transition (EMT) signaling pathway is the signaling pathway most relevant to the process of LNM. An EMT-related gene signature was identified from a discovery dataset obtained 489 patients using LIMMA and LASSO Cox methods. Six external independent dataset analyses including a total of 1,045 CRC patients and stratification analysis showed that EMT-related gene signature could sort out those high- and low-risk CRC patients accurately. Functional analysis and loss-of-function exploration in vitro and in vivo indicated that the EMT-related-signature-associated coding genes might play functional roles in the sophisticated regulation of CRC proliferation and metastasis. Prognostic nomograms integrating the EMT-related gene signature and clinicopathological risk factors were constructed for use as numerical prediction tools to assess clinical prognosis and clinical decision-makings. The comprehensive transcriptomic analysis in this article highlights the prognostic value of an EMT-related gene signature for postoperative disease recurrence in CRC patients and reveals a potential prognostic and therapeutic biomarker for CRC.
Background: Methylation of N6 adenosine (m 6 A) plays important regulatory roles in diverse biological processes. The purpose of this research was to explore the potential mechanism of m 6 A modification level on the clinical outcome of stage III colorectal cancer (CRC). Methods: Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were adopted to reveal the signal pathway which was most likely affected by m 6 A methylation. The linear models for microarray data (LIMMA) method and the least absolute shrinkage and selection operator (LASSO) Cox regression model were used to identify the signature. The signature can sensitively separate the patients into high and low risk indicating the relapse-free survival (RFS) time based on time-dependent receiver operating characteristic (ROC) analysis. Then, the multi-gene signature was validated in GSE14333 and the Cancer Genome Atlas (TCGA) cohort. The number of the samples in GSE14333 and TCGA cohort are 63 and 150. Finally, two nomograms were set up and validated to predict prognosis of patients with stage III CRC. Results: The hematopoietic cell lineage (HCL) signaling pathway was disclosed through GSEA and GSVA. Seven HCL-related genes were determined in the LASSO model to construct signature, with AUC 0.663, 0.708, and 0.703 at 1-, 3-, and 5-year RFS, respectively. Independent datasets analysis and stratification analysis indicated that the HCL-related signature was reliable in distinguishing high-and low-risk stage III CRC patients. Two nomograms incorporating the signature and pathological N stage were set up, which yielded good discrimination and calibration in the predictions of prognosis for stage III CRC patients. Conclusions: A novel HCL-related signature was developed as a predictive model for survival rate of stage III CRC patients. Nomograms based on the signature were advantageous to facilitate personalized counseling and treatment in stage III CRC.
Background:The association between tumour microenvironment (TME) in colorectal cancer (CRC) and cell death patterns requires further exploration.Cuproptosis may provide new insight into analyzing CRC's TME. Methods: We used cuproptosis-related genes (CRGs) to stratify the meta-Gene-Expression Omnibus cohort by the "non-negative matrix factorization" consistency matrix algorithm. To clarify the relative abundance of different cells in TME, CIBERSORT and single-sample gene set enrichment methods were performed. Then, CRGs' transcription in different cell types and the spatial position of CRGs' enrichment were demonstrated through single-cell spatial transcriptomics (STs) analysis. Prediction of clinical outcomes and response rate of immunotherapy was also conducted by constructing CRG_score.Results: Three cuproptosis-related TME phenotypes were figured out in CRC with distinctive clinicopathological and prognostic features. Three phenotypes were identical to immune-inflamed, immune-desert and immune-excluded profiles, respectively. Interestingly, cuproptosis-related cluster 3 (CPRC3) phenotype-related gene_score was predominantly upregulated in the fibroblast region, consisting of stromal cells. This result was in line with CPRC3's immune-excluded profile. Based on the robust cuproptosis-related risk_score Wenqin Luo, Ruiqi Gu, Hongsheng Fang and Ruijia Zhang contributed equally to this work.
Background Hepatocellular carcinoma (HCC) is still the fourth leading cause of cancer-related death. Better prognosticators are warranted for HCC. Hsa-miR-18a has been considered implicated in the pathogenesis of several tumors including HCC. Methods Bioinformatic analyses were conducted to predict target genes and carry out enrichment analysis. Validated downstream genes of hsa-miR-18a were obtained from PubMed database. Differential expression analysis was conducted within the “edgeR” R package based on the TCGA datasets. Survival analysis was performed by Kaplan-Meier survival analysis. All the visualizations were implemented by R. Results Bioinformatic analysis obtained a total of 90 target genes of hsa-miR-18a and revealed that target genes were involved in pathways essential for cancer onset and development such as cell cycle and PI3K/AKT signaling pathway. A review of literatures found target genes of miR-18a indeed participating in the biological processes of HCC. CHRM2 was identified as a special gene after the intersection analysis of TCGA differentially expressed genes (DEGs) and predicted target genes. Survival analysis validated that hsa-miR-18a and CHRM2 significantly affected the prognosis of HCC patients. Conclusion There is a strong association between hsa-miR-18a with tumors including HCC via participating essential tumor-promoting pathways including cell cycle, PI3K/AKT signaling pathway, etc. Furthermore, high miR-18a expression and low CHRM2 expression could lead to a poor prognosis in HCC. In conclusion, miR-18a could serve as an expectational prognostic biomarker in HCC.
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