A Multi-Omics Prognostic Model Capturing Tumor Stemness and the Immune Microenvironment in Clear Cell Renal Cell Carcinoma
<b>Background:</b> 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 impo...
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2024-09-01
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| author | Beibei Xiong Wenqiang Liu Ying Liu Tong Chen Anqi Lin Jiaao Song Le Qu Peng Luo Aimin Jiang Linhui Wang |
| author_facet | Beibei Xiong Wenqiang Liu Ying Liu Tong Chen Anqi Lin Jiaao Song Le Qu Peng Luo Aimin Jiang Linhui Wang |
| author_sort | Beibei Xiong |
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| description | <b>Background:</b> 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. <b>Methods:</b> 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. <b>Results:</b> 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. <b>Conclusions:</b> 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. |
| format | Article |
| id | doaj-art-73decdcf6f864e35a77186ab84ca2f41 |
| institution | OA Journals |
| issn | 2227-9059 |
| language | English |
| publishDate | 2024-09-01 |
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| series | Biomedicines |
| spelling | doaj-art-73decdcf6f864e35a77186ab84ca2f412025-08-20T02:10:57ZengMDPI AGBiomedicines2227-90592024-09-011210217110.3390/biomedicines12102171A Multi-Omics Prognostic Model Capturing Tumor Stemness and the Immune Microenvironment in Clear Cell Renal Cell CarcinomaBeibei Xiong0Wenqiang Liu1Ying Liu2Tong Chen3Anqi Lin4Jiaao Song5Le Qu6Peng Luo7Aimin Jiang8Linhui Wang9Department of Oncology, The First People’s Hospital of Shuangliu District, Chengdu 610200, ChinaDepartment of Urology, Changhai Hospital, Navel Medical University (Second Military Medical University), Shanghai 200433, ChinaDepartment of Urology, Changhai Hospital, Navel Medical University (Second Military Medical University), Shanghai 200433, ChinaDepartment of Urology, Changhai Hospital, Navel Medical University (Second Military Medical University), Shanghai 200433, ChinaDepartment of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, ChinaDepartment of Urology, Changhai Hospital, Navel Medical University (Second Military Medical University), Shanghai 200433, ChinaDepartment of Urology, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing 210002, ChinaDepartment of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, ChinaDepartment of Urology, Changhai Hospital, Navel Medical University (Second Military Medical University), Shanghai 200433, ChinaDepartment of Urology, Changhai Hospital, Navel Medical University (Second Military Medical University), Shanghai 200433, China<b>Background:</b> 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. <b>Methods:</b> 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. <b>Results:</b> 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. <b>Conclusions:</b> 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.https://www.mdpi.com/2227-9059/12/10/2171cancer stem-like cellsprognostic modelimmune microenvironmentsrenal cell carcinoma |
| spellingShingle | Beibei Xiong Wenqiang Liu Ying Liu Tong Chen Anqi Lin Jiaao Song Le Qu Peng Luo Aimin Jiang Linhui Wang A Multi-Omics Prognostic Model Capturing Tumor Stemness and the Immune Microenvironment in Clear Cell Renal Cell Carcinoma Biomedicines cancer stem-like cells prognostic model immune microenvironments renal cell carcinoma |
| title | A Multi-Omics Prognostic Model Capturing Tumor Stemness and the Immune Microenvironment in Clear Cell Renal Cell Carcinoma |
| title_full | A Multi-Omics Prognostic Model Capturing Tumor Stemness and the Immune Microenvironment in Clear Cell Renal Cell Carcinoma |
| title_fullStr | A Multi-Omics Prognostic Model Capturing Tumor Stemness and the Immune Microenvironment in Clear Cell Renal Cell Carcinoma |
| title_full_unstemmed | A Multi-Omics Prognostic Model Capturing Tumor Stemness and the Immune Microenvironment in Clear Cell Renal Cell Carcinoma |
| title_short | A Multi-Omics Prognostic Model Capturing Tumor Stemness and the Immune Microenvironment in Clear Cell Renal Cell Carcinoma |
| title_sort | multi omics prognostic model capturing tumor stemness and the immune microenvironment in clear cell renal cell carcinoma |
| topic | cancer stem-like cells prognostic model immune microenvironments renal cell carcinoma |
| url | https://www.mdpi.com/2227-9059/12/10/2171 |
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