Dataset Information

Identification of immune cell infiltration landscape for predicting prognosis of colorectal cancer.

ABSTRACT:

Background

The tumor microenvironment plays an essential role in the therapeutic response to immunotherapy. It is necessary to identify immune cell infiltration (ICI) subtypes for evaluating prognosis and therapeutic benefits. This study aimed to evaluate the ICI score as an effective prognostic biomarker for immune response.

Methods

The cell-type identification by estimating relative subsets of RNA transcripts and the estimation of stromal and immune cells in malignant tumors using expression methods were used to analyse ICI landscapes in 161 colorectal cancer (CRC) samples with patients' clinical and prognostic data, RNA sequencing data, and whole-exome sequencing data from the Sixth Affiliated Hospital, Sun Yat-sen University (Guangzhou, China). Statistical analysis and data processing were conducted to calculate ICI scores, and to analyse the prognosis of CRC patients with different ICI scores and other features. A similar analysis with RNA sequencing and clinical data of colon adenocarcinoma (COAD) samples from The Cancer Genome Atlas (TCGA) database was conducted to confirm the correctness of the findings.

Results

The high-ICI score group with a better prognosis (hazard ratio [HR], 2.19; 95% confidence interval [CI], 1.03-4.64; log-rank test, P = 0.036) was characterized by the increased tumor mutational burden and interleukin-17 (IL-17) signaling pathway. Significant differences in the prognosis and the expression levels of immune checkpoints and chemokine marker genes were found between the two ICI score groups. For COAD samples from TCGA, the results also showed a significant difference in patients' prognosis between the two ICI score groups (HR, 1.72; 95% CI, 1.00-2.96; log-rank test, P = 0.047).

Conclusions

Tumor heterogeneity induced differences in identifying ICI subtypes of CRC patients. The ICI score may serve as an effective biomarker for predicting prognosis, help identify new therapeutic markers for CRC, and develop novel effective immune checkpoint blockade therapies.

SUBMITTER: Wu X

PROVIDER: S-EPMC10089677 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

Identification of immune cell infiltration landscape for predicting prognosis of colorectal cancer.

Wu Xueqian X Li Jianxia J Zhang Yuanzhe Y Cheng Yi Y Wu Zehua Z Zhan Weixiang W Deng Yanhong Y

Gastroenterology report 20230411

<h4>Background</h4>The tumor microenvironment plays an essential role in the therapeutic response to immunotherapy. It is necessary to identify immune cell infiltration (ICI) subtypes for evaluating prognosis and therapeutic benefits. This study aimed to evaluate the ICI score as an effective prognostic biomarker for immune response.<h4>Methods</h4>The cell-type identification by estimating relative subsets of RNA transcripts and the estimation of stromal and immune cells in malignant tumors usi ...[more]

PMID: 37056281

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Project description:BackgroundRNA methylation is a potential target for cancer therapy, while anoikis, a form of programmed cell death, is linked to cancer metastasis. However, the prognostic and immune significance of RNA methylation- and anoikis-related genes in colorectal cancer (CRC) remains unknown.MethodsTranscriptomic and clinicopathological data for CRC were obtained from TCGA and the GEO databases. A novel signature was constructed based on RNA methylation- and anoikis-related genes using univariate and multivariate Cox regression as well as LASSO Cox regression methods. CRC patients were stratified into low- and high-risk groups based on this signature. Differences in prognosis, immune infiltration, and drug sensitivity between two groups were analyzed. Finally, immunohistochemistry, western blot, and RT-qPCR were employed to validate the expression of the key gene SERPINE1 in CRC tissues and cells, as well as the effect of FTO on its expression.ResultsWe identified 79 differentially expressed RNA methylation-associated anoikis-related genes (RMRARGs) in both cancerous and normal tissues. A signature composed of 9 key genes (BID, FASN, PLK1, CDKN3, MYC, EPHA2, SERPINE1, CD36, PDK4) was established. Kaplan-Meier analysis revealed a poorer prognosis in the high-risk group. Compared to the other three published models, this signature demonstrated superior predictive performance based on the ROC curve analysis. Functional analyses highlighted differences in drug sensitivities and signaling pathways between risk groups. Furthermore, immune analysis results showed that risk score was associated with some immune cells and immune checkpoints. Immunohistochemistry showed high SERPINE1 expression in CRC tissues, with FTO expression positively correlated with SERPINE1. Furthermore, RT-qPCR and western blot indicated FTO knockdown markedly downregulated SERPINE1 levels.ConclusionOur findings underscore the prognostic value of this signature in CRC patients and its utility in assessing immune status. Additionally, the m6A demethylase FTO regulates the expression of the anoikis-related gene SERPINE1.

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Dataset Information

Identification of immune cell infiltration landscape for predicting prognosis of colorectal cancer.

Background

Methods

Results

Conclusions

Publications

Identification of immune cell infiltration landscape for predicting prognosis of colorectal cancer.

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