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A Multi-Omics Prognostic Model Capturing Tumor Stemness and the Immune Microenvironment in Clear Cell Renal Cell Carcinoma.

作者信息

Xiong Beibei, Liu Wenqiang, Liu Ying, Chen Tong, Lin Anqi, Song Jiaao, Qu Le, Luo Peng, Jiang Aimin, Wang Linhui

机构信息

Department of Oncology, The First People's Hospital of Shuangliu District, Chengdu 610200, China.

Department of Urology, Changhai Hospital, Navel Medical University (Second Military Medical University), Shanghai 200433, China.

出版信息

Biomedicines. 2024 Sep 24;12(10):2171. doi: 10.3390/biomedicines12102171.


DOI:10.3390/biomedicines12102171
PMID:39457484
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11504857/
Abstract

Cancer stem-like cells (CSCs), a distinct subset recognized for their stem cell-like abilities, are intimately linked to the resistance to radiotherapy, metastatic behaviors, and self-renewal capacities in tumors. Despite their relevance, the definitive traits and importance of CSCs in the realm of oncology are still not fully comprehended, particularly in the context of clear cell renal cell carcinoma (ccRCC). A comprehensive understanding of these CSCs' properties in relation to stemness, and their impact on the efficacy of treatment and resistance to medication, is of paramount importance. In a meticulous research effort, we have identified new molecular categories designated as CRCS1 and CRCS2 through the application of an unsupervised clustering algorithm. The analysis of these subtypes included a comprehensive examination of the tumor immune environment, patterns of metabolic activity, progression of the disease, and its response to immunotherapy. In addition, we have delved into understanding these subtypes' distinctive clinical presentations, the landscape of their genomic alterations, and the likelihood of their response to various pharmacological interventions. Proceeding from these insights, prognostic models were developed that could potentially forecast the outcomes for patients with ccRCC, as well as inform strategies for the surveillance of recurrence after treatment and the handling of drug-resistant scenarios. Compared with CRCS1, CRCS2 patients had a lower clinical stage/grading and a better prognosis. The CRCS2 subtype was in a hypoxic state and was characterized by suppression and exclusion of immune function, which was sensitive to gefitinib, erlotinib, and saracatinib. The constructed prognostic risk model performed well in both training and validation cohorts, helping to identify patients who may benefit from specific treatments or who are at risk of recurrence and drug resistance. A novel therapeutic target, SAA2, regulating neutrophil and fibroblast infiltration, and, thus promoting ccRCC progression, was identified. Our findings highlight the key role of CSCs in shaping the ccRCC tumor microenvironment, crucial for therapy research and clinical guidance. Recognizing tumor stemness helps to predict treatment efficacy, recurrence, and drug resistance, informing treatment strategies and enhancing ccRCC patient outcomes.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/21c83cb26cb0/biomedicines-12-02171-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/a6bff205d594/biomedicines-12-02171-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/53b35df53957/biomedicines-12-02171-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/eeb40e73b5e0/biomedicines-12-02171-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/0cb51b5da4bf/biomedicines-12-02171-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/391435d40b70/biomedicines-12-02171-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/d77424967ee0/biomedicines-12-02171-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/d77c10f5a474/biomedicines-12-02171-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/21c83cb26cb0/biomedicines-12-02171-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/a6bff205d594/biomedicines-12-02171-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/53b35df53957/biomedicines-12-02171-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/eeb40e73b5e0/biomedicines-12-02171-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/0cb51b5da4bf/biomedicines-12-02171-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/391435d40b70/biomedicines-12-02171-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/d77424967ee0/biomedicines-12-02171-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/d77c10f5a474/biomedicines-12-02171-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cf3/11504857/21c83cb26cb0/biomedicines-12-02171-g008.jpg

相似文献

[1]
A Multi-Omics Prognostic Model Capturing Tumor Stemness and the Immune Microenvironment in Clear Cell Renal Cell Carcinoma.

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[7]
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[8]
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[9]
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[10]
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引用本文的文献

[1]
mRNA expression, tumor heterogeneity, and response to therapy in patients with advanced renal cell carcinoma treated with immune-based combinations (ARON-1α).

Biochem Biophys Rep. 2025-8-7

[2]
Tumor-initiating and metastasis-initiating cells of clear-cell renal cell carcinoma.

J Biomed Sci. 2025-2-8

[3]
Multiomics Analysis of Exportin Family Reveals XPO1 as a Novel Target for Clear Cell Renal Cell Carcinoma.

Int J Genomics. 2025-1-21

本文引用的文献

[1]
Renal cancer: signaling pathways and advances in targeted therapies.

MedComm (2020). 2024-8-1

[2]
Multiomics characterization and verification of clear cell renal cell carcinoma molecular subtypes to guide precise chemotherapy and immunotherapy.

Imeta. 2023-11-16

[3]
Hepatocytes coordinate immune evasion in cancer via release of serum amyloid A proteins.

Nat Immunol. 2024-5

[4]
Multi-omic profiling of clear cell renal cell carcinoma identifies metabolic reprogramming associated with disease progression.

Nat Genet. 2024-3

[5]
Proteomic Profiling of Advanced Melanoma Patients to Predict Therapeutic Response to Anti-PD-1 Therapy.

Clin Cancer Res. 2024-1-5

[6]
SETD2 Deficiency Confers Sensitivity to Dual Inhibition of DNA Methylation and PARP in Kidney Cancer.

Cancer Res. 2023-11-15

[7]
Machine learning in the identification of prognostic DNA methylation biomarkers among patients with cancer: A systematic review of epigenome-wide studies.

Artif Intell Med. 2023-9

[8]
A new thinking: deciphering the aberrance and clinical implication of copper-death signatures in clear cell renal cell carcinoma.

Cell Biosci. 2022-12-29

[9]
A novel thinking: DDR axis refines the classification of ccRCC with distinctive prognosis, multi omics landscape and management strategy.

Front Public Health. 2022

[10]
Senescent stromal cells: roles in the tumor microenvironment.

Trends Cancer. 2023-1

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