Identification of basement membrane-related prognostic signature for predicting prognosis, immune response and potential drug prediction in papillary renal cell carcinoma

Author:

Xi Yujia1,Song Liying2,Wang Shuang2,Zhou Haonan3,Ren Jieying4,Zhang Ran5,Fu Feifan4,Yang Qian4,Duan Guosheng2,Wang Jingqi1

Affiliation:

1. Department of Urology, The Second Hospital of Shanxi Medical University, Taiyuan, China

2. Second School of Clinical Medicine, Shanxi Medical University, Taiyuan, China

3. First School of Clinical Medicine, Shanxi Medical University, Taiyuan, China

4. School of Basic Medicine, Shanxi Medical University, Taiyuan, China

5. School of Public Health, Shanxi Medical University, Taiyuan, China

Abstract

<abstract><p>Papillary renal cell carcinoma (PRCC) is a malignant neoplasm of the kidney and is highly interesting due to its increasing incidence. Many studies have shown that the basement membrane (BM) plays an important role in the development of cancer, and structural and functional changes in the BM can be observed in most renal lesions. However, the role of BM in the malignant progression of PRCC and its impact on prognosis has not been fully studied. Therefore, this study aimed to explore the functional and prognostic value of basement membrane-associated genes (BMs) in PRCC patients. We identified differentially expressed BMs between PRCC tumor samples and normal tissue and systematically explored the relevance of BMs to immune infiltration. Moreover, we constructed a risk signature based on these differentially expressed genes (DEGs) using Lasso regression analysis and demonstrated their independence using Cox regression analysis. Finally, we predicted 9 small molecule drugs with the potential to treat PRCC and compared the differences in sensitivity to commonly used chemotherapeutic agents between high and low-risk groups to better target patients for more precise treatment planning. Taken together, our study suggested that BMs might play a crucial role in the development of PRCC, and these results might provide new insights into the treatment of PRCC.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine

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