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A Novel TGF-β-Related Signature for Predicting Prognosis, Tumor Microenvironment, and Therapeutic Response in Colorectal Cancer

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Abstract

The transforming growth factor beta (TGF-β) signaling plays a critical role in immune evasion and tumor progression. However, its modulatory influences on prognosis, tumor microenvironment (TME), and therapeutic efficacy remain unknown in colorectal cancer (CRC). We summarized TGF-β-related genes and comprehensively estimated their expression pattern in 2142 CRC samples from 9 datasets. Two distinct cluster patterns were divided and biological characteristics of each pattern were further analyzed. Then, to quantify the TGF-β cluster pattern of individual CRC patient, we generated the TGF-β score (TGFBscore) model based on TGF-β cluster pattern-relevant differentially expressed genes (DEGs). Subsequently, we conducted correlation analysis for TGFBscore and clinical prognosis, consensus molecular subtypes (CMSs), TME characteristics, liver metastasis, drug response, and immunotherapeutic efficacy in CRC. We illustrated transcriptional and genetic alterations of TGF-β-relevant genes, which were closely linked with carcinogenic pathways. We identified two different TGF-β cluster patterns, characterized by a high and a low TGFBscore. The TGFBscore-high group was significantly linked with worse patient survival, epithelial–mesenchymal transition (EMT) activation, liver metastasis tendency, and the infiltration of immunosuppressive cells (regulatory T cells [Tregs], M2 macrophages, cancer-associated fibroblasts [CAFs], and myeloid-derived suppressor cells [MDSCs]), while the TGFBscore-low group was linked with a survival advantage, epithelial phenotype, early CRC staging, and the infiltration of immune-activated cells (B cell, CD4 T cell, natural killer T [NKT] cell, and T helper 1 [Th1] cell). In terms of predicting drug response, TGFBscore negatively correlated (sensitive to TGFBscore-high group) with drugs targeting PI3K/mTOR, JNK and p38, RTK signaling pathways, and positively correlated (sensitive to TGFBscore-low group) with drugs targeting EGFR signaling pathway. Also, TGFBscore could predict the efficacy of different anti-tumor therapies. TGFBscore-low patients might benefit more from anti-PDL1 immunotherapy, adjuvant chemotherapy (ACT), and ERBB targeted therapy, whereas TGFBscore-high patients might benefit more from antiangiogenic targeted therapy. Our study constructed a novel TGF-β scoring model that could predict prognosis, liver metastasis tendency, and TME characteristics for CRC patients. More importantly, this work emphasizes the potential clinical utility of TGFBscore in evaluating the efficacy of chemotherapy, targeted therapy, and immunotherapy, guiding individualized precision treatment in CRC.

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Data Availability

All datasets related to this study can be downloaded from the Cancer Genome Atlas database (TCGA, https://portal.gdc.cancer.gov/) and the Gene Expression Omnibus database (GEO, https://www.ncbi.nlm.nih.gov/geo/).

Abbreviations

TGF-β:

Transforming growth factor beta

TGFBscore:

TGF-β score

CRC:

Colorectal cancer

CRLM:

Colorectal cancer liver metastasis

mCRC:

Metastatic colorectal cancer

TME:

Tumor microenvironment

DEGs:

Differentially expressed genes

CMSs:

Consensus molecular subtypes

EMT:

Epithelial–mesenchymal transition

Tregs:

Regulatory T cells

CAFs:

Cancer-associated fibroblasts

MDSCs:

Myeloid-derived suppressor cells

NKT:

Natural killer T

Th1:

T helper 1

1; PDL1:

Programmed death ligand

TAMs:

Tumor-associated macrophages

TANs:

Tumor-associated neutrophils

ACT:

Adjuvant chemotherapy

CNV:

Copy number variation

SNV:

Single-nucleotide variation

TCGA:

The Cancer Genome Atlas

GEO:

Gene Expression Omnibus

COAD:

Colon adenocarcinoma

READ:

Rectum adenocarcinoma

GSVA:

Gene set variation analysis

ssGSEA:

Single sample gene set enrichment analysis

TIDE:

Tumor immune dysfunction and exclusion

PCA:

Principal component analysis

GDSC:

Genomics of Drug Sensitivity in Cancer

OS:

Overall survival

RFS:

Relapse-free survival

CR:

Complete response

PR:

Partial response

SD:

Stable disease

PD:

Progressive disease

MSI:

Microsatellite instability

dMMR:

Deficient mismatch repair

TMB:

Tumor mutation burden

IPS:

Immunophenoscore

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Funding

This work was funded by the China National Science and Technology Major Project for Prevention and Treatment of Infectious Diseases (2017ZX10203207).

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Author notes

  1. Baorui Tao, Chenhe Yi, Yue Ma and Yitong Li have contributed equally to this work.

Authors and Affiliations

  1. Department of General Surgery, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Road, Shanghai, 200040, People’s Republic of China

    Baorui Tao, Chenhe Yi, Yue Ma, Yitong Li, Bo Zhang, Yan Geng, Zhenmei Chen, Xiaochen Ma & Jinhong Chen

  2. Cancer Metastasis Institute, Fudan University, Shanghai, People’s Republic of China

    Baorui Tao, Chenhe Yi, Yue Ma, Yitong Li, Bo Zhang, Yan Geng, Zhenmei Chen, Xiaochen Ma & Jinhong Chen

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  1. Baorui Tao
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Contributions

JHC, BRT, CHY, and YM: designed this study. BRT, CHY, and YTL: were responsible for the integration and analyses of the data. BRT and YTL: wrote this manuscript. JHC, CHY, YM, BZ, YG, ZMC, and XCM: edited and revised the manuscript. All authors approved this manuscript.

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Correspondence to Jinhong Chen.

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Tao, B., Yi, C., Ma, Y. et al. A Novel TGF-β-Related Signature for Predicting Prognosis, Tumor Microenvironment, and Therapeutic Response in Colorectal Cancer. Biochem Genet (2023). https://doi.org/10.1007/s10528-023-10591-7

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