scholarly journals Significance of CD8 + T cell infiltration related biomarkers and the corresponding prediction model for the prognosis of kidney renal clear cell carcinoma

Aging ◽  
2021 ◽  
Author(s):  
Yuan Tian ◽  
Yumei Wei ◽  
Hongmei Liu ◽  
Heli Shang ◽  
Yuedong Xu ◽  
...  
Keyword(s):  
T Cell ◽  
Prediction Model ◽  
Cell Carcinoma ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Cd8 T Cell ◽  
Renal Clear Cell Carcinoma ◽  
Cell Infiltration ◽  
T Cell Infiltration

Immunogenomic characterization of advanced clear cell renal cell carcinoma treated with PD-1 blockade.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 5010-5010 ◽  
Author(s):  
David A. Braun ◽  
Yue Hou ◽  
Ziad Bakouny ◽  
Miriam Ficial ◽  
Miriam Sant'Angelo ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
T Cell ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Cd8 T Cell ◽  
Cell Infiltration ◽  
Cell Renal Cell Carcinoma ◽  
Mtor Inhibition ◽  
T Cell Infiltration

5010 Background: Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Further, the common paradigm in solid tumor immunology that pre-existing CD8+ T cell infiltration, in combination with high numbers of nonsynonymous mutations (which, in the context of diverse HLA class I alleles, may be presented as neoantigens) drives response to PD-1 blockade, has not been thoroughly explored in ccRCC. Methods: We analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials (CheckMate 009, CheckMate 010, CheckMate 025) of treatment with PD-1 blockade (n = 362) or mTOR inhibition (as control arm; n = 230) by whole-exome (n = 454) and RNA-sequencing (n = 311), integrated with CD8 immunofluorescence analysis (n = 219), to uncover the immunogenomic determinants of therapeutic response and survival. Wilcoxon rank-sum test was used to compare somatic alteration burden between clinical benefit (CB) v.s no CB (NCB); Fisher’s exact test was used to compare mutations and copy number alteration by infiltration state; and hazard ratio (HR) was calculated from Cox PH model for progression-free (PFS) and overall survival (OS) endpoints. All tests were at a significance level of p < 0.05. Results: Conventional genomic markers (tumor mutation burden, p = 0.81; neoantigen load, p = 0.47 for CB vs. NCB) and degree of CD8+ T cell infiltration (p = 0.88 for PFS; p = 0.65 for OS) were not associated with clinical response or altered survival with PD-1 blockade. These advanced ccRCC tumors were highly CD8+ T cell infiltrated, with only 22% having an immune desert phenotype and 5% with an immune excluded phenotype. Our analysis revealed that CD8+ T cell infiltrated tumors are depleted of clinically favorable PBRM1 mutations (p = 0.013) and enriched for unfavorable chromosomal losses of 9p21.3 (p < 0.001) when compared to non-infiltrated tumors. When found within infiltrated tumors, del(9p21.3) was associated with worse CB rate (36% (9/25) for del(9p21.3) vs. 88% (7/8) for wildtype at that locus, p = 0.017) and worse survival (HR = 2.38, p = 0.01 for PFS; HR = 2.44, p = 0.01 for OS) with PD-1 blockade. Conclusions: These data demonstrate how the potential interplay of immunophenotypes with somatic mutations and chromosomal alterations impacts therapeutic efficacy in advanced ccRCC.

scholarly journals Identification of biomarkers related to CD8+ T cell infiltration with gene co-expression network in clear cell renal cell carcinoma

Aging ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 3694-3712 ◽  
Author(s):  
Jiaxing Lin ◽  
Meng Yu ◽  
Xiao Xu ◽  
Yutao Wang ◽  
Haotian Xing ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
T Cell ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Cd8 T Cell ◽  
Cell Infiltration ◽  
Cell Renal Cell Carcinoma ◽  
T Cell Infiltration

scholarly journals Updates on Immunotherapy and Immune Landscape in Renal Clear Cell Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 5856
Author(s):  
Myung-Chul Kim ◽  
Zeng Jin ◽  
Ryan Kolb ◽  
Nicholas Borcherding ◽  
Jonathan Alexander Chatzkel ◽  
...  
Keyword(s):  
T Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
Single Cell Analysis ◽  
Clear Cell ◽  
Cd8 T Cell ◽  
Cell Infiltration ◽  
Cellular Mechanisms ◽  
T Cell Infiltration ◽  
Immunological Mechanisms

Several clinicopathological features of clear cell renal cell carcinomas (ccRCC) contribute to make an “atypical” cancer, including resistance to chemotherapy, sensitivity to anti-angiogenesis therapy and ICIs despite a low mutational burden, and CD8+ T cell infiltration being the predictor for poor prognosis–normally CD8+ T cell infiltration is a good prognostic factor in cancer patients. These “atypical” features have brought researchers to investigate the molecular and immunological mechanisms that lead to the increased T cell infiltrates despite relatively low molecular burdens, as well as to decipher the immune landscape that leads to better response to ICIs. In the present study, we summarize the past and ongoing pivotal clinical trials of immunotherapies for ccRCC, emphasizing the potential molecular and cellular mechanisms that lead to the success or failure of ICI therapy. Single-cell analysis of ccRCC has provided a more thorough and detailed understanding of the tumor immune microenvironment and has facilitated the discovery of molecular biomarkers from the tumor-infiltrating immune cells. We herein will focus on the discussion of some major immune cells, including T cells and tumor-associated macrophages (TAM) in ccRCC. We will further provide some perspectives of using molecular and cellular biomarkers derived from these immune cell types to potentially improve the response rate to ICIs in ccRCC patients.

scholarly journals Diagnostic Biopsy Does Not Commonly Induce Intratumoral CD8 T Cell Infiltration in Merkel Cell Carcinoma

PLoS ONE ◽  
2012 ◽  
Vol 7 (7) ◽  
pp. e41465 ◽  
Author(s):  
Shinichi Koba ◽  
Kelly G. Paulson ◽  
Kotaro Nagase ◽  
Andrew Tegeder ◽  
Renee Thibodeau ◽  
...  
Keyword(s):  
T Cell ◽  
Cell Carcinoma ◽  
Merkel Cell Carcinoma ◽  
Cd8 T Cell ◽  
Cell Infiltration ◽  
Merkel Cell ◽  
T Cell Infiltration ◽  
Diagnostic Biopsy

scholarly journals Novel prognostic prediction model constructed through machine learning on the basis of methylation-driven genes in kidney renal clear cell carcinoma

2020 ◽  
Vol 40 (7) ◽  
Author(s):  
Weihao Tang ◽  
Yiling Cao ◽  
Xiaoke Ma
Keyword(s):  
Prediction Model ◽  
Cell Carcinoma ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Epigenetic Modification ◽  
Clinical Information ◽  
Renal Clear Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Lasso Regression ◽  
Prognosis Model

Abstract Kidney renal clear cell carcinoma (KIRC) is a common tumor with poor prognosis and is closely related to many aberrant gene expressions. DNA methylation is an important epigenetic modification mechanism and a novel research target. Thus, exploring the relationship between methylation-driven genes and KIRC prognosis is important. The methylation profile, methylation-driven genes, and methylation characteristics in KIRC was revealed through the integration of KIRC methylation, RNA-seq, and clinical information data from The Cancer Genome Atlas. The Lasso regression was used to establish a prognosis model on the basis of methylation-driven genes. Then, a trans-omics prognostic nomogram was constructed and evaluated by combining clinical information and methylated prognosis model. A total of 242 methylation-driven genes were identified. The Gene Ontology terms of these methylation-driven genes mainly clustered in the activation, adhesion, and proliferation of immune cells. The methylation prognosis prediction model that was established using the Lasso regression included four genes in the methylation data, namely, FOXI2, USP44, EVI2A, and TRIP13. The areas under the receiver operating characteristic curve of 1-, 3-, and 5-year survival rates were 0.810, 0.824, and 0.799, respectively, in the training group and 0.794, 0.752, and 0.731, respectively, in the testing group. An easy trans-omics nomogram was successfully established. The C-indices of the nomogram in the training and the testing groups were 0.8015 and 0.8389, respectively. The present study revealed the overall perspective of methylation-driven genes in KIRC and can help in the evaluation of the prognosis of KIRC patients and provide new clues for further study.

scholarly journals Alternative splicing associated with cancer stemness in kidney renal clear cell carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lixing Xiao ◽  
Guoying Zou ◽  
Rui Cheng ◽  
Pingping Wang ◽  
Kexin Ma ◽  
...  
Keyword(s):  
Stem Cells ◽  
Logistic Regression ◽  
Alternative Splicing ◽  
Prediction Model ◽  
Cell Carcinoma ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
Cancer Stemness ◽  
Alternative Splicing Events

Abstract Backgroud Cancer stemness is associated with metastases in kidney renal clear cell carcinoma (KIRC) and negatively correlates with immune infiltrates. Recent stemness evaluation methods based on the absolute expression have been proposed to reveal the relationship between stemness and cancer. However, we found that existing methods do not perform well in assessing the stemness of KIRC patients, and they overlooked the impact of alternative splicing. Alternative splicing not only progresses during the differentiation of stem cells, but also changes during the acquisition of the stemness features of cancer stem cells. There is an urgent need for a new method to predict KIRC-specific stemness more accurately, so as to provide help in selecting treatment options. Methods The corresponding RNA-Seq data were obtained from the The Cancer Genome Atlas (TCGA) data portal. We also downloaded stem cell RNA sequence data from the Progenitor Cell Biology Consortium (PCBC) Synapse Portal. Independent validation sets with large sample size and common clinic pathological characteristics were obtained from the Gene Expression Omnibus (GEO) database. we constructed a KIRC-specific stemness prediction model using an algorithm called one-class logistic regression based on the expression and alternative splicing data to predict stemness indices of KIRC patients, and the model was externally validated. We identify stemness-associated alternative splicing events (SASEs) by analyzing different alternative splicing event between high- and low- stemness groups. Univariate Cox and multivariable logistic regression analysisw as carried out to detect the prognosis-related SASEs respectively. The area under curve (AUC) of receiver operating characteristic (ROC) was performed to evaluate the predictive values of our model. Results Here, we constructed a KIRC-specific stemness prediction model with an AUC of 0.968,and to provide a user-friendly interface of our model for KIRC stemness analysis, we have developed KIRC Stemness Calculator and Visualization (KSCV), hosted on the Shiny server, can most easily be accessed via web browser and the url https://jiang-lab.shinyapps.io/kscv/. When applied to 605 KIRC patients, our stemness indices had a higher correlation with the gender, smoking history and metastasis of the patients than the previous stemness indices, and revealed intratumor heterogeneity at the stemness level. We identified 77 novel SASEs by dividing patients into high- and low- stemness groups with significantly different outcome and they had significant correlations with expression of 17 experimentally validated splicing factors. Both univariate and multivariate survival analysis demonstrated that SASEs closely correlated with the overall survival of patients. Conclusions Basing on the stemness indices, we found that not only immune infiltration but also alternative splicing events showed significant different at the stemness level. More importantly, we highlight the critical role of these differential alternative splicing events in poor prognosis, and we believe in the potential for their further translation into targets for immunotherapy.

scholarly journals Identification a ceRNA (XIST/miR-10a-5p/SERPINE1) Axis as a Prognostic Biomarker in Kidney Renal Clear Cell Carcinoma.

2021 ◽  
Author(s):  
Rui-ji Liu ◽  
Zhi-Peng Xu ◽  
Shuying Li ◽  
Jun-Jie Yu ◽  
Bin Xu ◽  
...  
Keyword(s):  
T Cell ◽  
Cell Carcinoma ◽  
Immune Cell ◽  
Clear Cell ◽  
Prognostic Biomarker ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
Immune Cell Infiltration ◽  
Cerna Network

Abstract Background: Kidney cancer is one of the most common malignancies, of which the most aggressive subtype was kidney renal clear cell carcinoma (KIRC), accounting for 80% of them. A growing number of studies point to the involvement of competitive endogenous RNAs in tumor development. However, the role of ceRNA network involved in KIRC remains unclear. Thus, the aim of this study was to investigate the BAP1-associated prognostic ceRNA in KIRC. Methods: We downloaded the RNAseq data from TCGA along with the relevant clinical data. We screened the differentially expressed lncRNAs, miRNAs, mRNAs according to the expression of BAP1 and established a ceRNA network. Results: After comprehensive bioinformatics analysis, we identified the XIST-miR-10a-5p-SERPINE1 ceRNA axis. Next, we confirmed the prognostic role of miR-10a-5p/SERPINE1 in KIRC using survival analysis and Cox regression analysis. To investigate the abnormally high expression of SERPINE1, we performed methylation analysis of SERPINE1 and concluded that the methylation level of SERPINE1 in KIRC was significantly lower than that in normal tissues. Furthermore, to study the role of SERPINE1 in the immune microenvironment in KIRC, we performed immune cell infiltration analysis and found that SERPINE1 expression was positively correlated with the level of multiple immune cell infiltration (CD 4+ T cell, CD 8+ T cell, macrophages, dendritic cells, neutrophils). Conclusion: We constructed a ceRNA (XIST/has-miR-10a-5p/SERPINE1) that can be used as prognostic biomarker of KIRC. Furthermore, we found that miR-10a-5p/SERPINE1 were significantly associated with clinical features and were independent prognostic factors of KIRC.

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