scholarly journals Establishment of a prognosis Prediction Model Based on Pyroptosis-Related Signatures Associated With the Immune Microenvironment and Molecular Heterogeneity in Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Aimin Jiang ◽  
Jialin Meng ◽  
Yewei Bao ◽  
Anbang Wang ◽  
Wenliang Gong ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Prediction Model ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Molecular Heterogeneity ◽  
Cell Renal Cell Carcinoma ◽  
Prognosis Prediction ◽  
Model Based ◽  
Prognosis Prediction Model

BackgroundPyroptosis is essential for tumorigenesis and progression of neoplasm. However, the heterogeneity of pyroptosis and its relationship with the tumor microenvironment (TME) in clear cell renal cell carcinoma (ccRCC) remain unclear. The purpose of the present study was to identify pyroptosis-related subtypes and construct a prognosis prediction model based on pyroptosis signatures.MethodsFirst, heterogenous pyroptosis subgroups were explored based on 33 pyroptosis-related genes and ccRCC samples from TCGA, and the model established by LASSO regression was verified by the ICGC database. Then, the clinical significance, functional status, immune infiltration, cell–cell communication, genomic alteration, and drug sensitivity of different subgroups were further analyzed. Finally, the LASSO-Cox algorithm was applied to narrow down the candidate genes to develop a robust and concise prognostic model.ResultsTwo heterogenous pyroptosis subgroups were identified: pyroptosis-low immunity-low C1 subtype and pyroptosis-high immunity-high C2 subtype. Compared with C1, C2 was associated with a higher clinical stage or grade and a worse prognosis. More immune cell infiltration was observed in C2 than that in C1, while the response rate in the C2 subgroup was lower than that in the C1 subgroup. Pyroptosis-related genes were mainly expressed in myeloid cells, and T cells and epithelial cells might influence other cell clusters via the pyroptosis-related pathway. In addition, C1 was characterized by MTOR and ATM mutation, while the characteristics of C2 were alterations in SPEN and ROS1 mutation. Finally, a robust and promising pyroptosis-related prediction model for ccRCC was constructed and validated.ConclusionTwo heterogeneous pyroptosis subtypes were identified and compared in multiple omics levels, and five pyroptosis-related signatures were applied to establish a prognosis prediction model. Our findings may help better understand the role of pyroptosis in ccRCC progression and provide a new perspective in the management of ccRCC patients.

scholarly journals Establishment of a prognosis prediction model based on pyroptosis-related signatures associated with the immune microenvironment and molecular heterogeneity in clear cell renal carcinoma

2021 ◽  
Author(s):  
Aimin Jiang ◽  
Jialin Meng ◽  
Yewei Bao ◽  
Anbang Wang ◽  
Wenliang Gong ◽  
...  
Keyword(s):  
Prediction Model ◽  
Immune Cell ◽  
Clear Cell ◽  
Clinical Stage ◽  
Genomic Alteration ◽  
Molecular Heterogeneity ◽  
Cell Renal Cell Carcinoma ◽  
Prognosis Prediction ◽  
Model Based ◽  
Prognosis Prediction Model

Background: Pytoptosis is essential for tumorigenesis and progression of clear cell renal cell carcinoma (ccRCC). However, the heterogeneity of pyroposis and its relationship with the tumor microenvironment (TME) remain unclear. The aim of the present study was to identify proptosis-related subtypes and construct a prognosis prediction model based on pyroptosis signatures. Methods: First, heterogenous pyroptosis subgroups were explored based on 33 pyroptosis-related genes and ccRCC samples from TCGA, and the model establsihed by LASSO regression was verified by ICGC database. Then, the clinical significance, functional status, immune infiltration, cell-cell communication, genomic alteration and drug sensitivity of different subgroups were further analyzed. Finally, the LASSO-Cox algorithm was applied to narrow down the candidate genes to develop a robust and concise prognostic model. Results: Two heterogenous pyroptosis subgroups were identified: pyroptosis-low immunity-low C1 subtype, and pyroptosis-high immunity-high C2 subtype. Compared with C1, C2 was associated with a higher clinical stage or grade and a worse prognosis. More immune cell infiltration was observed in C2 than that in C1, while the response rate in C2 subgroup was lower than that in C1 subgroup. Pyroptosis related genes were mainly expressed in myeloid cells, and T cells and epithelial cells might influence other cell clusters via Pyroptosis related pathway. In addition, C1 was characterized by MTOR and ATM mutation, while C2 was characterized by more significant alterations in SPEN and ROS1 mutation. Finally, we constructed and validated a robust and promising signature based on the pyroptosis-related risk score for assessing the prognosis in ccRCC. Conclusion: We identified two heterogeneous pyroptosis subtypes and 5 reliable risk signatures to establish a prognosis prediction model. Our findings may help better understand the role of pyroptosis in ccRCC progression and provide a new perspective in the management of ccRCC patients.

scholarly journals Systematic Pan-Cancer Analysis of KIF23 and a Prediction Model Based on KIF23 in Clear Cell Renal Cell Carcinoma (ccRCC)

2021 ◽  
Vol Volume 14 ◽  
pp. 1717-1729
Author(s):  
Xiaojie Bai ◽  
Yuanfei Cao ◽  
Xin Yan ◽  
Kurerban Tuoheti ◽  
Guowei Du ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Prediction Model ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Cell Renal Cell Carcinoma ◽  
Model Based ◽  
Pan Cancer

scholarly journals An improved clear cell renal cell carcinoma stage prediction model based on gene sets

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Fangjun Li ◽  
Mu Yang ◽  
Yunhe Li ◽  
Mingqiang Zhang ◽  
Wenjuan Wang ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Prediction Model ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Cell Renal Cell Carcinoma ◽  
Model Based ◽  
Gene Sets

scholarly journals A Two-DNA Methylation Signature to Improve Prognosis Prediction of Clear Cell Renal Cell Carcinoma

2019 ◽  
Vol 60 (11) ◽  
pp. 1013 ◽  
Author(s):  
Shanping Shi ◽  
Shazhou Ye ◽  
Xiaoyue Wu ◽  
Mingjun Xu ◽  
Renjie Zhuo ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Cell Renal Cell Carcinoma ◽  
Prognosis Prediction

scholarly journals Development and Interpretation of a Genomic Instability Derived lncRNAs Based Risk Signature as a Predictor of Prognosis for Clear Cell Renal Cell Carcinoma Patients

2021 ◽  
Vol 11 ◽  
Author(s):  
Huiying Yang ◽  
Xiaoling Xiong ◽  
Hua Li
Keyword(s):  
Renal Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Genomic Instability ◽  
Renal Cell ◽  
Clear Cell ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Cell Renal Cell Carcinoma ◽  
Prognosis Prediction

BackgroundClear cell renal cell carcinoma (ccRCC) is a kind of frequently diagnosed cancer, leading to high death rate in patients. Genomic instability (GI) is regarded as playing indispensable roles in tumorigenesis and impacting the prognosis of patients. The aberrant regulation of long non-coding RNAs (lncRNAs) is a main cause of GI. We combined the somatic mutation profiles and expression profiles to identify GI derived lncRNAs (GID-lncRNAs) in ccRCC and developed a GID-lncRNAs based risk signature for prognosis prediction and medication guidance.MethodsWe decided cases with top 25% cumulative number of somatic mutations as genomically unstable (GU) group and last 25% as genomically stable (GS) group, and identified differentially expressed lncRNAs (GID-lncRNAs) between two groups. Then we developed the risk signature with all overall survival related GID-lncRNAs with least absolute shrinkage and selection operator (LASSO) Cox regression. The functions of the GID-lncRNAs were partly interpreted by enrichment analysis. We finally validated the effectiveness of the risk signature in prognosis prediction and medication guidance.ResultsWe developed a seven-lncRNAs (LINC00460, AL139351.1, AC156455.1, AL035446.1, LINC02471, AC022509.2, and LINC01606) risk signature and divided all samples into high-risk and low-risk groups. Patients in high-risk group were in more severe clinicopathologic status (higher tumor grade, pathological stage, T stage, and more metastasis) and were deemed to have less survival time and lower survival rate. The efficacy of prognosis prediction was validated by receiver operating characteristic analysis. Enrichment analysis revealed that the lncRNAs in the risk signature mainly participate in regulation of cell cycle, DNA replication, material metabolism, and other vital biological processes in the tumorigenesis of ccRCC. Moreover, the risk signature could help assess the possibility of response to precise treatments.ConclusionOur study combined the somatic mutation profiles and the expression profiles of ccRCC for the first time and developed a GID-lncRNAs based risk signature for prognosis predicting and therapeutic scheme deciding. We validated the efficacy of the risk signature and partly interpreted the roles of the seven lncRNAs composing the risk signature in ccRCC. Our study provides novel insights into the roles of genomic instability derived lncRNAs in ccRCC.

Intratumoural heterogeneity may hinder precision medicine strategies in patients with clear cell renal cell carcinoma

2018 ◽  
Vol 71 (5) ◽  
pp. 467-471 ◽  
Author(s):  
Maria Rosaria Raspollini ◽  
Ilaria Montagnani ◽  
Rodolfo Montironi ◽  
Francesca Castiglione ◽  
Guido Martignoni ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Precision Medicine ◽  
Renal Cell ◽  
Clear Cell ◽  
Molecular Heterogeneity ◽  
Precision Oncology ◽  
Cell Renal Cell Carcinoma ◽  
Renal Sinus ◽  
The Moment

Clear cell renal cell carcinoma (ccRCC) is an heterogeneous tumour at architectural, cellular and molecular level, a reason why the 2014 International Society of Urological Pathology consensus recommended wide sampling of RCC masses to include at least 1 block/cm of tumour together with perpendicular sections of the tumour/perinephric fat interface and the tumour/renal sinus interface. Intratumoural molecular heterogeneity may be a limitation at the moment of defining precision medicine strategies based on gene mutation status. This study analyses the presence of any mutation of KRAS, NRAS, BRAF, PIK3CA, ALK, ERBB2, DDR2, MAP2K1, RET and EGFR genes in 20 tissue blocks from a case of ccRCC and its metastasis. We observed the presence of the mutation at pH1047R of PIK3CA gene in five samples of the tumour, while the remaining 15 samples did not show any mutation at PIK3CA or any other investigated gene. There is a great need to develop novel RCC sampling strategies to overcome tumour heterogeneity prior to define precision oncology strategies.

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