Identification and Validation of PIK3CA as a Marker Associated with Prognosis and Immune Infiltration in Renal Clear Cell Carcinoma

Li, Ya; Wang, Chong; Gao, Yang; Zhou, Liang

doi:10.1155/2021/3632576

Cited by 4 publications

(3 citation statements)

References 52 publications

(55 reference statements)

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“…According to reports, the common pathways activated in KIRC are PI3K/AKT/mTOR, VHL/HIF-1α, and JAK/STAT ( 42 – 44 ). KIRC is characterized by controlling hypoxic signaling pathways, leading to metabolic dysregulation, promoting neovascularization, and creating a microenvironment conducive to tumor growth ( 45 ).…”

Section: Resultsmentioning

confidence: 99%

Expression and prognosis analysis of PAQR5 in kidney cancer

Dong

et al. 2022

Front. Oncol.

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Progestin and adipoQ receptor 5 (PAQR5) affects the development of various malignancies and is specifically expressed in kidney. However, the role of PAQR5 in renal carcinoma remains unclear. We assessed the state of PAQR5 expression in kidney renal clear cell carcinoma (KIRC) by The Cancer Genome Atlas and Gene Expression Omnibus datasets. Moreover, immunohistochemistry was performed to observe the expressions of PAQR5 protein in tumor tissues. The relationships between PAQR5 expression and clinical characteristics were investigated by UALCAN. Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan–Meier plotter were used to analyze the effect of PAQR5 expression levels on overall survival and relapse-free survival (RFS). The re lationships between clinical characteristics and survival were also evaluated by univariate and multifactorial Cox regression. Gene Ontology term analysis, Kyoto Encyclopedia of Genes and Genomes analysis, and gene set enrichment analysis were performed on PAQR5 to explain the enrichment pathways and functions. Protein and protein interactions were explained by GeneMANIA and STRING. We also explored the relevance of PAQR5 to tumor immune cell infiltration and immunomodulatory molecules by TIMER and GEPIA. Finally, we explored the correlation of PAQR5 with the pathway proteins STATs, HIF-1α, and mTOR using the GSE40435 dataset. PAQR5 expression was low in KIRC and correlated significantly with clinical characteristics including cancer stage, tumor grade, and nodal metastasis status. Low PAQR5 expression was significantly associated with poorer survival. Cox regression analysis indicated that upregulation of PAQR5 was an independent factor for a good prognosis of KIRC. PAQR5 downregulation was associated mainly with STAT3 target upregulation, tumorigenesis, and poor differentiation. PAQR5 expression also correlated positively with B cells, neutrophils, macrophages, and dendritic cells and negatively with the infiltration of FOXP3+ Treg cells and the immune checkpoint molecules PD-1, CTLA4, and LAG3. Moreover, PAQR5 expression in KIRC was negatively correlated with the pathway proteins STAT1/2/3/4/5A, HIF-1α, and mTOR. PAQR5 is an excellent predictor of KIRC prognosis and may be a potential molecular therapeutic target.

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Section: Resultsmentioning

confidence: 99%

Expression and prognosis analysis of PAQR5 in kidney cancer

Dong

et al. 2022

Front. Oncol.

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“…Zhao et al found six-snoRNA signatures (SNORA70B, SNORD12B, SNORD93, SNORA59B, SNORD116-2, and SNORA2) were superior indicators to routine clinical factors (AUC = 0.732) [ 44 ]. Li et al found that patients with low PIK3CA expression had poorer overall survival, and the AUC of their ROC curve was 0.775 [ 45 ]. Li et al found that the area under the curve (AUC) values of 1-year, 3-year and 5-year survival rates of the model constructed with seven cuproptosis-related genes were 0.814, 0.762 and 0.825, respectively [ 46 ].…”

Section: Discussionmentioning

confidence: 99%

Characterization of tumor microenvironment and sensitive chemotherapy drugs based on cuproptosis-related signatures in renal cell carcinoma

Tang,

Yao,

Yao

et al. 2023

Aging

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Cuproptosis is a novel type of copper-induced cell death and is considered as a new therapeutic target for many cancers. Distant metastases occur in about 40% of patients with advanced renal cell carcinoma (RCC), with a poor 5-year prognosis of about 10%. Through a series of comprehensive analyses, four differentially expressed cuproptosis-related lncRNAs (DECRLs) were identified as candidate biomarkers for RCC. The risk model constructed by using these four DECRLs can better predict the prognosis of patients with RCC, which is determined by the receiver operating characteristic (Time dependent area under curve value at 1-year, 3-year, 5-year, and 10-year were 0.82, 0.80, 0.76, and 0.73 respectively). There were significant differences in immune status between high-risk and low-risk RCC patients. The differentially expressed gene enrichment terms between high- and low-risk patients was also dominated by immune-related terms. The risk score was also correlated with immunotherapy as measured by the tumor immune dysfunction and exclusion (TIDE) score. In addition, we also found that the sensitivity of many chemotherapy drugs varies widely between high- and low-risk patients. The sensitivity of the three chemotherapy drugs (AZD4547, Vincristine, and WEHI-539) varied among high- and low-risk patients, and was significantly negatively correlated with risk values, suggesting that they could be used as clinical treatment drugs for RCC. Our study not only obtained four potential biomarkers, but also provided guidance for immunotherapy and chemotherapy treatment of RCC, as well as new research strategies for the screening of other cancer biomarkers and sensitive drugs.

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“…Except for genes mutated across a large number of patients, some key genes in tumor initiation and progression are observed to be mutated in only a few patients [24]. For example, PIK3CA, which has been validated to be a ccRCC risk gene by previous studies [25][26][27], is mutated in no more than 5% of ccRCC patients [27]. It is difficult for purely frequency-based approaches to identify these genes with low mutation frequency but high risk.…”

Section: Introductionmentioning

confidence: 99%

Identifying potential risk genes for clear cell renal cell carcinoma with deep reinforcement learning

Lu,

Zheng,

Hao

et al. 2024

Preprint

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Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal cell carcinoma. However, our understanding of ccRCC risk genes remains limited. This gap in knowledge poses significant challenges to the effective diagnosis and treatment of ccRCC. To address this problem, we propose a deep reinforcement learning-based computational approach named RL-GenRisk to identify ccRCC risk genes. Distinct from traditional supervised models, RL-GenRisk frames the identification of ccRCC risk genes as a Markov decision process, combining the graph convolutional network and Deep Q-Network for risk gene identification. Moreover, a well-designed data-driven reward is proposed for mitigating the lim-itation of scant known risk genes. The evaluation demonstrates that RL-GenRisk outperforms existing methods in ccRCC risk gene identification. Additionally, RL-GenRisk identifies ten novel ccRCC risk genes. We successfully validated epidermal growth factor receptor (EGFR), corroborated through independent datasets and biological experimentation. This approach may also be used for other diseases in the future.

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Identification and Validation of PIK3CA as a Marker Associated with Prognosis and Immune Infiltration in Renal Clear Cell Carcinoma

Cited by 4 publications

References 52 publications

Expression and prognosis analysis of PAQR5 in kidney cancer

Expression and prognosis analysis of PAQR5 in kidney cancer

Characterization of tumor microenvironment and sensitive chemotherapy drugs based on cuproptosis-related signatures in renal cell carcinoma

Identifying potential risk genes for clear cell renal cell carcinoma with deep reinforcement learning

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