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Development of a CAFs-related gene signature to predict survival and drug response in bladder cancer

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Abstract

As one of important components of tumor microenvironment, CAFs (cancer-associated fibroblasts) play a vital role in the development and metastasis of bladder cancer. The present study aimed to develop a CAFs-related gene signature to predict the prognosis of patients and the response to chemotherapy and immunotherapy based on research of multidatabase. Expression data and clinical information were obtained from TCGA and GEO databases. Different bioinformatic and statistical methods were combined to construct the robust CAFs-related gene signature for prognosis. The model was explored from four aspects: single-cell source, immune infiltration, correlation with cancer-related genes and pathways, and prediction of drug response. After screening, five genes (BNC2, LAMA2, MFAP5, NID1, and OLFML1) related to CAFs were used for constructing the signature to divide patients into high- and low-risk groups. Patients in low-risk group had better prognosis and multidatabase analysis confirmed the predictive value. The five genes were mainly expressed by fibroblasts and involved in regulation of pathways related with glycolysis, hypoxia, and epithelial–mesenchymal transition (EMT). BNC2, LAMA2, and NID1 were strongly associated with drug sensitivity. Moreover, the immunological status was different between high- and low-risk groups. High-risk patients had poor response to chemotherapy or immunotherapy. The CAFs-related gene signature might help to optimize risk stratification and provide a new insight in individual treatment for bladder cancer.

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Data availability

All the data in our study can be accessed from the online databases.

Abbreviations

CAFs:

Cancer-associated fibroblasts

BLCA:

Bladder cancer

TME:

Tumor microenvironment

TCGA:

The cancer genome atlas

MIBC:

Muscle invasive bladder cancer

NMIBC:

Non-muscle invasive bladder cancer

TMB:

Tumor mutation burden

DEGs:

Differentially expressed genes

WGCNA:

Weighted gene co-expression network analysis

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 82071750, 81772713, 81472411), Taishan Scholar Program of Shandong Province (Grant No. tsqn20161077), Major Science and technology innovation project of Shandong Province (Grant No. 2019JZZY021002), Key projects of Qingdao Science and Technology Program (Grant No. 18-6-1-64-nsh), and Research and Development Program of Shandong Province (Grant No. 2018GSF118197).

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Authors and Affiliations

  1. Department of Urology, The Affiliated Hospital of Qingdao University, No.16 Jiangsu Road, Qingdao, 266000, China

    Zhao Zhang, Wei Jiao & Haitao Niu

  2. Key Laboratory, Department of Urology and Andrology, The Affiliated Hospital of Qingdao University, Qingdao, China

    Zhao Zhang, Zhijuan Liang, Dan Li, Liping Wang, Yuanbin Chen, Ye Liang, Wei Jiao & Haitao Niu

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  1. Zhao Zhang
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Contributions

ZZ and HTN contributed to conception and design. ZJL, DL, and LPW contributed to collection and assembly of data. YL and YBC contributed to data analysis and interpretation. ZZ contributed to manuscript writing. WJ and HTN contributed to the manuscript revision and finalization.

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Correspondence to Wei Jiao or Haitao Niu.

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The authors report no conflicts of interest in this work.

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Ethical approval for this study was obtained from the Ethics Committee of the affiliated hospital of Qingdao university.

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13577_2022_673_MOESM1_ESM.tif

Supplementary file1 (TIF 5739 KB) Supplementary figure 1. Immune infiltration analysis of the CAFs-related gene signature. (A-E) Correlation analysis between the expressions of individual genes and infiltration levels of B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil, and dendritic cell. (F) Comparison of the infiltration of 22 leukocyte types between high and low CRS groups.

13577_2022_673_MOESM2_ESM.tif

Supplementary file2 (TIF 1833 KB) Supplementary figure 2. (A-E) The comparison of tumor infiltration levels among tumors with different somatic copy number alterations for the model genes. (F) Waterfall plot showing the mutation information for the model genes in TCGA.

13577_2022_673_MOESM3_ESM.tif

Supplementary file3 (TIF 1009 KB) Supplementary figure 3. The gene set drug sensitivity analysis from CTRP drug data. The color from blue to red represent the correlation between mRNA expression and IC50 (50% inhibitory concentration) of small molecules/drugs.

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Zhang, Z., Liang, Z., Li, D. et al. Development of a CAFs-related gene signature to predict survival and drug response in bladder cancer. Human Cell 35, 649–664 (2022). https://doi.org/10.1007/s13577-022-00673-w

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