The UCLA Histo-Genetic Risk Classification (U-HGRC) to predict outcomes of localized clear cell renal cell carcinoma.

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 627-627
Author(s):  
Cedric Michel Lebacle ◽  
Aydin Pooli ◽  
Nagesh Rao ◽  
Erika Louise Wood ◽  
Nils Kroeger ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
High Risk ◽  
Genetic Risk ◽  
Clear Cell ◽  
Risk Group ◽  
High Risk Group ◽  
Cell Renal Cell Carcinoma ◽  
Risk Of Recurrence ◽  
Random Samples

627 Background: Thirty percent of patients with localized clear cell renal cell carcinoma (ccRCC) will ultimately develop recurrence (local or metastatic) after nephrectomy. Current risk stratification systems still misclassify patients. We have developed a novel classification integrating cytogenetic findings to better stratify the risk of recurrence and overall survival (OS) after surgery for localized ccRCC. Methods: A total of 646 patients from UCLA with ccRCC and tumor cytogenetic analysis, were included in this study. After a selection of histologic parameters using logistic regression and cytogenetic parameters using principal component analysis a CHAID decision tree and Kaplan Meier analysis were used to build the UCLA Histo-Genetic Risk Classification (U-HGRC). Survival analyses of the model were validated on two random samples of 323 patients. Recurrence was defined as any local recurrence or development of new metastasis after surgery. Results: The T-stage, tumor size, presence of sarcomatoid features, gain of chromosome 5q, loss 10q, or loss X/Y were used to stratify the risk of recurrence of ccRCC into three U-HGRC groups of low (1), intermediate (2) or high-risk (3). After a mean follow-up of 55 months, risk of recurrence (HR = 2.44, p = .001 for U-HGRC 2; HR = 9.90, p < .0001 for U-HGRC 3), disease-free survival (DFS) (Log-rank p < .0001), risk of death (HR = 1.72, p = .033 for U-HGRC 2; HR = 4.74, p < .0001 for U-HGRC 3) and OS (Log-rank p < .0001) were significantly different between groups. These findings were validated on two random samples. For high-risk group, median DFS and OS were 2.7 and 6.3 years, respectively. The 5-year risks of recurrence for U-HGRC group 1, 2 and 3 were 9%, 25% and 62%, respectively. The AUC of the model was significantly improved comparing to the current UISS system (0.72 for U-HGRC vs 0.65 for UISS, p = .008) with an accuracy of 82.8% for the U-HGRC high-risk group. Conclusions: The U-HGRC, which integrates genomic alterations with clinical and pathologic features, allowed a better stratification of recurrence risk and overall survival that could help to select appropriate patients for surveillance and adjuvant therapy protocols.

Lactic Acid Metabolism And Transporter Related Three Genes Predict The Prognosis of Patients With Clear Cell Renal Cell Carcinoma

2021 ◽  
Author(s):  
Tuanjie Guo ◽  
Jian Zhang ◽  
Tao Wang ◽  
Zhihao Yuan ◽  
Heting Tang ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Lactic Acid ◽  
High Risk ◽  
Prognostic Model ◽  
Acid Metabolism ◽  
Clear Cell ◽  
Risk Group ◽  
High Risk Group ◽  
Cell Renal Cell Carcinoma ◽  
Lactic Acid Metabolism

Abstract Background: Lactic acid was previously considered a waste product of glycolysis, and has now become a key metabolite for cancer development, maintenance and metastasis. So far, numerous studies have confirmed that tumor lactic acid levels are associated with increased metastasis, tumor recurrence and poor prognosis. However, the prognostic value of lactic acid metabolism and transporter related genes in patients with clear cell renal cell carcinoma has not been explored.Results: We selected lactic acid metabolism and transporter related twenty-one genes for LASSO cox regression analysis in the E-MTAB-1980 cohort, and finally screened three genes (PNKD, SLC16A8, SLC5A8) to construct a clinical prognostic model for patients with clear cell renal cell carcinoma. Based on the prognostic model we constructed, the over survival (hazard ratio = 4.117, 95% CI: 1.810 - 9.362, p < 0.0001) of patients in the high-risk group and the low-risk group in the training set E-MTAB-1980 cohort had significant differences, and similar results (hazard ratio = 1.909, 95% CI: 1.414 - 2.579 p < 0.0001) were also observed in the validation set TGCA cohort. Subsequently, survival prediction was carried out based on the survival prognosis model we constructed. In the E-MTAB-1980 cohort, the area under ROC curve (AUC) of 1-, 3- and 5- years was 0.71, 0.72, and 0.77, respectively. The AUC of 1-, 3- and 5- years in TCGA cohort was 0.65, 0.65, and 0.63, respectively. Using CIBERSORT algorithm to analyze the differences in immune cell infiltration in different risk groups, we found that dendritic cells and CD4+ memory cells in the high-risk group were significantly lower than those in the low-risk group, while Treg cells were higher than in the low-risk group. Finally, through gene enrichment analysis, we found that the signal pathway that is strongly related to the prognostic model is the cell cycle. Conclusions: We constructed a prognostic model using lactic acid metabolism and transporter related genes, which can accurately predict the prognosis of patients. The poor prognosis of the high-risk group may be related to the regulation of cell cycle by lactic acid metabolism.

Bioinformatics profiling integrating a three immune-related long non-coding RNA signature as a prognostic model for clear cell renal cell carcinoma

2020 ◽  
Author(s):  
Yuanbin Jiang ◽  
Xin Gou ◽  
Zongjie Wei ◽  
Jianyu Tan ◽  
Haitao Yu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Cell Renal Cell Carcinoma ◽  
Immune Score

Abstract Background: Renal cell carcinoma (RCC) is one of the most common aggressive malignant tumors in urogenital system, and the clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal carcinoma. Immune related long non-coding RNAs (IRlncRs) plentiful in immune cells and immune microenvironment (IME) are potential in evaluating prognosis and assessing the effects of immunotherapy. A completed and meaningful IRlncRs analysis based on abundant ccRCC gene samples from The Cancer Genome Atlas (TCGA) will provide insight in this field. Methods: Based on the TCGA dataset, we integrated the expression profiles of IRlncRs and overall survival (OS) in the 611 ccRCC patients. The immune score of each sample was calculated based on the expression level of immune-related genes and used to identify the most meaningful IRlncRs. Survival-related IRlncRs (sIRlncRs) was estimated by calculating the algorithm of difference and COX regression analysis in ccRCC patients. Based on the median immune-related risk score (IRRS) developed from the screened sIRlncRs, the high-risk and low-risk components were distinguished. Functional annotation was detected by gene set enrichment analysis (GSEA) and principal component analysis (PCA), and the immune composition and purity of the tumor was evaluated by microenvironment cell population records. The expression levels of three sIRlncRs were verified in various tissues and cell lines.Results: A total of 39 IRlncRs were collected by Pearson correlation analyses among immune score and the lncRNA expression. A total of 7 sIRlncRs were significantly associated with the clinical outcomes of ccRCC patients. Three sIRlncRs (ATP1A1-AS1, IL10RB-DT and MELTF-AS1) with the most significant prognostic values were enrolled to build the IRRS model in which the OS of in the high-risk group was shorter than that in the low-risk group. The IRRS was identified as an independent prognosis factor and correlated with the OS. The high-risk group and low-risk group illustrated different distributions in PCA and different immune status in GSEA. Besides, we found the more significant expression in certain ccRCC cell lines and tumor tissues of ccRCC patients compared with the HK-2 and adjacent tissues respectively. Additionally, the expression levels of lncR-MELTF-AS1 and IL10RB-DT were remarkably enhanced along the more advanced T-stages, but the lncR-ATP1A1-AS1 showed the inverse gradient.Conclusion: Our results demonstrate some sIRlncRs with remark clinical relevance show the latent monitoring and prognosis values for ccRCC patients and may provide new insight in immunological researches and treatment strategies of ccRCC patients.

Improving the definition of high-risk patients for tumor recurrence from clear cell renal cell carcinoma: The U-CISS classification.

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 629-629
Author(s):  
Cedric Michel Lebacle ◽  
Nils Kroeger ◽  
Aydin Pooli ◽  
Sandy Liu ◽  
Karim Chamie ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
High Risk ◽  
Tumor Recurrence ◽  
Clear Cell ◽  
Risk Group ◽  
High Risk Group ◽  
Cell Renal Cell Carcinoma ◽  
Intermediate Group ◽  
Risk Patients ◽  
Definition Of

629 Background: Thirty percent of patients with localized clear cell renal cell carcinoma (ccRCC) will ultimately develop recurrence (local or metastatic) after nephrectomy. Current risk stratification systems still misclassify patients. A better stratification is needed to select high-risk patients who may benefit from adjuvant therapy. We sought to improve the existing UISS by the addition of genetic information in a new UCLA cytogenetic integrated staging system (U-CISS). Methods: A total of 240 patients from UCLA with localized ccRCC and cytogenetic analysis on tumor specimen were included in the study. In a continuation of our previous research, cytogenetic (combined loss 3p-14q) and a pathological high-risk feature, microvascular invasion (MVI) were implemented in the UISS. Association with recurrence free survival (RFS) was analyzed in a uni- and multivariable fashion; prognostic accuracy was tested with the c-index. All tumors that had either MVI, combined loss 3p/14q or both in the UISS low-risk group were placed into the U-CISS intermediate group. Tumors with one or both risk factors in the UISS intermediate group were placed into the new U-CISS high-risk group. Results: Fifty patients developed tumor recurrence. On multivariate analysis, combined loss 3p-14q, and MVI were independent prognostic factors. The U-CISS placed significantly better prognosticated RFS in the high-risk group (7/50 (14%) with UISS vs. 23/50 (46%) with U-CISS) and thus, was more accurate in prognosticating RFS. The c-index for recurrence prognostication was improved in the U-CISS (0.70 vs. 0.65 for the UISS). Furthermore, the U-CISS was a better prognostication tool when the intermediate and high-risk group were combined (prognostication of 74% with U-CISS vs. 68% UISS). Conclusions: The use of U-CISS, which integrates genomic alterations with clinical and pathologic features, allowed a re-allocation of patients to create a better stratification of recurrence risk. This new definition of high-risk of recurrence could significantly improve selection of patients who are in greatest need of closer surveillance and/or adjuvant treatment. C.L. and N.K. contributed equally to first authorship.

scholarly journals Bioinformatics profiling intergrating a three immune-related long non-coding RNA signature as a prognostic model for clear cell renal cell carcinoma

2020 ◽  
Author(s):  
Xiang Zhou ◽  
Xin Gou ◽  
Zongjie Wei ◽  
Jianyu Tan ◽  
Haitao Yu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Cell Renal Cell Carcinoma ◽  
Immune Score

Abstract Background: Immune related long non-coding RNAs (IRlncRs) plentiful in immune cells and immune microenvironment (IME) are potential in evaluating prognosis and assessing the effects of immunotherapy. A complete and meaningful IRlncRs analysis based on abundant clear cell renal cell carcinoma (ccRCC) gene samples from The Cancer Genome Atlas (TCGA) will provide insight in this field. Methods: Based on the TCGA dataset, we integrated the expression profiles of IRlncRs and overall survival (OS) in the 611 ccRCC patients. The immune score of each sample was calculated based on the expression level of immune-related genes and used to identify the most meaningful IRlncRs. Survival-related IRlncRs (sIRlncRs) was estimated by calculating the algorithm of difference and COX regression analysis in ccRCC patients. Based on the median immune-related risk score (IRRS) developed from the screened sIRlncRs, the high-risk and low-risk components were distinguished. Functional annotation was detected by gene set enrichment analysis (GSEA) and principal component analysis (PCA), and the immune composition and purity of the tumor was evaluated by microenvironment cell population records. The expression levels of three sIRlncRs were verified in various tissues and cell lines. Results: A total of 39 IRlncRs were collected by Pearson correlation analyses among immune score and the lncRNA expression. A total of 7 sIRlncRs were significantly associated with the clinical outcomes of ccRCC patients. Three sIRlncRs (ATP1A1-AS1, IL10RB-DT and MELTF-AS1) with the most significant prognostic values were enrolled to build the IRRS model in which the OS of in the high-risk group was shorter than that in the low-risk group. The IRRS was identified as an independent prognosis factor and correlated with the OS. The high-risk group and low-risk group illustrated different distributions in PCA and different immune status in GSEA. Besides, we found the more significant expression in certain ccRCC cell lines and tumor tissues of ccRCC patients compared with the HK-2 and adjacent tissues respectively. Additionally, the expression levels of lncR-MELTF-AS1 and IL10RB-DT were remarkably enhanced along the more advanced T-stages, but the lncR-ATP1A1-AS1 showed the inverse gradient. Conclusion: Our results demonstrated some sIRlncRs with remark clinical relevance shown the latent monitoring and prognosis value of ccRCC patients and may provide new insight for immunological research and treatment strategies in ccRCC patients.

scholarly journals A Mitochondrial Dysfunction and Oxidative Stress Pathway-Based Prognostic Signature for Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-32
Author(s):  
Yue Wu ◽  
Xi Zhang ◽  
Xian Wei ◽  
Huan Feng ◽  
Bintao Hu ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Renal Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Risk Group ◽  
Prognostic Significance ◽  
Individual Risk ◽  
Cell Renal Cell Carcinoma

Mitochondria not only are the main source of ATP synthesis but also regulate cellular redox balance and calcium homeostasis. Its dysfunction can lead to a variety of diseases and promote cancer and metastasis. In this study, we aimed to explore the molecular characteristics and prognostic significance of mitochondrial genes (MTGs) related to oxidative stress in clear cell renal cell carcinoma (ccRCC). A total of 75 differentially expressed MTGs were analyzed from The Cancer Genome Atlas (TCGA) database, including 46 upregulated and 29 downregulated MTGs. Further analysis screened 6 prognostic-related MTGs (ACAD11, ACADSB, BID, PYCR1, SLC25A27, and STAR) and was used to develop a signature. Kaplan-Meier survival and receiver operating characteristic (ROC) curve analyses showed that the signature could accurately distinguish patients with poor prognosis and had good individual risk stratification and prognostic potential. Stratified analysis based on different clinical variables indicated that the signature could be used to evaluate tumor progression in ccRCC. Moreover, we found that there were significant differences in immune cell infiltration between the low- and high-risk groups based on the signature and that ccRCC patients in the low-risk group responded better to immunotherapy than those in the high-risk group (46.59% vs 35.34%, P = 0.008 ). We also found that the expression levels of these prognostic MTGs were significantly associated with drug sensitivity in multiple ccRCC cell lines. Our study for the first time elucidates the biological function and prognostic significance of mitochondrial molecules associated with oxidative stress and provides a new protocol for evaluating treatment strategies targeting mitochondria in ccRCC patients.

Novel stratification of the recurrence risk following surgical extirpation of clear cell renal cell carcinoma using tissue biomarkers in the mammalian target of rapamycin pathway.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 4581-4581
Author(s):  
Laura-Maria Krabbe ◽  
Oussama M Darwish ◽  
Ganesh Raj ◽  
Ramy F. Youssef ◽  
Payal Kapur ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
High Risk ◽  
Renal Cell ◽  
Clear Cell ◽  
Mammalian Target Of Rapamycin ◽  
Mtor Pathway ◽  
Cell Renal Cell Carcinoma ◽  
Risk Of Recurrence ◽  
Marker Score ◽  
Predicted Risk

4581 Background: Aberrant activation of the mammalian target of rapamycin (mTOR) pathway promotes invasiveness and metastatic potential in a variety of malignancies. The aim of the present study was to evaluate the association of altered expression of mTOR pathway components with recurrence outcome in non-metastatic clear cell renal cell carcinoma (ccRCC) patients. Methods: Immunohistochemistry for phos-S6, phos-mTOR, mTOR, phos-AKT, HIF-1α, RAPTOR, PTEN, PI3K, and phos-4EBP1 was performed on tissue microarrays of patients treated for non-metastatic kidney cancer between 1997-2010. Patients were defined as having a low (<) or high risk (≥) of nomogram predicted recurrence (2001 MSKCC RCC post-op) using an 8% cutoff. The relationship between individual marker expression, as well as combined marker score (low, intermediate and high defined as ≤ 3, 4-5, >5 altered biomarkers; respectively) with the actual and predicted relapse rates was assessed. Results: The study included 419 non- metastatic ccRCC patients (pT1-T2 79.5%, pT3-T4 20.5%, Fuhrman nuclear grade 1-2 in 69%, 3-4 in 31%). 219 and 200 patients had low (<8%) and high (≥8%) nomogram-predicted 5-year risk of recurrence respectively. With a median follow-up of 2.2 years, recurrences were detected in 5 (2.3%) of the predicted low risk and 30 (15%) of the predicted high risk patients. mTOR pathway biomarker profiles were not predictive for patients at low predicted risk of recurrences. For patients at high predicted risk of recurrence, low, intermediate and high combined marker scores were found in 84 (42%), 79 (39.5%), and 37 (18.5%), respectively. The actual rates of recurrence were noted for 8.3% of low, 13.9% of intermediate and 32.4% of high combined marker score in a statistically significant distribution (p=0.027). Conclusions: The cumulative number of aberrantly expressed mTOR biomarkers correlates with a higher rate of recurrence. The combined marker score may help further stratify patients with high nomogram predicted risk of recurrence. Our data supports prospective evaluation of these biomarkers to augment current clinico-pathologic predictors of outcomes in ccRCC.

Novel stratification of the recurrence risk following surgical extirpation of clear cell renal cell carcinoma using tissue biomarkers in the mammalian target of rapamycin pathway.

2013 ◽  
Vol 31 (6_suppl) ◽  
pp. 372-372
Author(s):  
Oussama M. Darwish ◽  
Ganesh Raj ◽  
Ramy F. Youssef ◽  
Payal Kapur ◽  
Aditya Bagrodia ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
High Risk ◽  
Renal Cell ◽  
Clear Cell ◽  
Mammalian Target Of Rapamycin ◽  
Mtor Pathway ◽  
Cell Renal Cell Carcinoma ◽  
Risk Of Recurrence ◽  
Marker Score ◽  
Predicted Risk

372 Background: Aberrant activation of the mammalian target of rapamycin (mTOR) pathway promotes invasiveness and metastatic potential in a variety of malignancies. The aim of the present study was to evaluate the association of altered expression of mTOR pathway components with recurrence outcome in non-metastatic clear cell renal cell carcinoma (ccRCC) patients. Methods: Immunohistochemistry for phos-S6, phos-mTOR, mTOR, phos-AKT, HIF-1α, RAPTOR, PTEN, PI3K, and phos-4EBP1 was performed on tissue microarrays of patients treated for non-metastatic kidney cancer between 1997-2010. Patients were defined as having a low (<) or high risk (≥) of nomogram predicted recurrence (2001 MSKCC RCC post-op) using an 8% cutoff. The relationship between individual marker expression, as well as combined marker score (low, intermediate and high defined as ≤ 3, 4-5, >5 altered biomarkers; respectively) with the actual and predicted relapse rates was assessed. Results: The study included 419 non-metastatic ccRCC patients (pT1-T2 79.5%, pT3-T4 20.5%, Fuhrman nuclear grade 1-2 in 69%, 3-4 in 31%). 219 and 200 patients had low (<8%) and high (≥8%) nomogram-predicted 5-year risk of recurrence respectively. With a median follow-up of 2.2 years, recurrences were detected in 5 (2.3%) of the predicted low risk and 30 (15%) of the predicted high risk patients. mTOR pathway biomarker profiles were not predictive for patients at low predicted risk of recurrences. For patients at high predicted risk of recurrence, low, intermediate and high combined marker scores were found in 84 (42%), 79 (39.5%), and 37 (18.5%), respectively. The actual rates of recurrence were noted for 8.3% of low, 13.9% of intermediate and 32.4% of high combined marker score in a statistically significant distribution (p=0.027). Conclusions: The cumulative number of aberrantly expressed mTOR biomarkers correlates with a higher rate of recurrence. The combined marker score may help further stratify patients with high nomogram predicted risk of recurrence. Our data supports prospective evaluation of these biomarkers to augment current clinico-pathologic predictors of outcomes in ccRCC.

scholarly journals Identification of Autophagy-Related Long Non-Coding RNA Prognostic Signature for Clear Cell Renal Cell Carcinoma

2020 ◽  
Author(s):  
Yankang Cui ◽  
Shaobo Zhang ◽  
Chenkui Miao ◽  
Chao Liang ◽  
Xiaochao Chen ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Cell Carcinoma ◽  
Prognostic Value ◽  
Clear Cell ◽  
Risk Group ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Independent Predictive Factor ◽  
Cell Renal Cell Carcinoma

Abstract Background: Studies over the past decade have shown that long non-coding RNAs (lncRNAs) play an essential role in the tumorigenesis and progression of kidney renal clear cell carcinoma (KIRC). Meanwhile, autophagy has been demonstrated to regulate KIRC pathogenesis and targeting therapy resistance. However, the prognostic value of autophagy-related lncRNAs in KIRC patients has not been reported before.Methods: In this study, we obtained transcriptome data of 611 KIRC cases from the TCGA database and 258 autophagy-related mRNAs from the HADb database to identify autophagy-related lncRNAs by co-expression network. A prognostic model was then established basing on these autophagy-related lncRNAs, dividing patients into high-risk and low-risk groups. Survival analysis, clinical variables dependent receiver operating characteristic (ROC) analyses, univariate/multivariate Cox analyses, and clinical correlation analysis were performed based on risk signature with R language. Gene set enrichment analysis (GSEA) was then performed to investigate the potential mechanism of the risk signature promoting KIRC progression with GSEA software. Results: A total of 17 lncRNAs were screened out and all these lncRNAs were found significantly related to KIRC patients' overall survival in subsequent survival analyses. Besides, the overall survival time in the high-risk group was much poorer than in the low-risk group. The ROC analysis revealed that the prognostic value of risk signature was better than age, gender, grade, and N stage. Univariate/multivariate analyses suggested that the risk signature was an independent predictive factor for KIRC patients. Immune-related pathways were dramatically enriched in high-risk patients according to GSEA. Conclusions: In summary, our identified 17 autophagy-related lncRNAs had prognostic value for KIRC patients which may function in Immunomodulation.

scholarly journals Prognostic and therapeutic implications of extracellular matrix associated gene signature in renal clear cell carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pankaj Ahluwalia ◽  
Meenakshi Ahluwalia ◽  
Ashis K. Mondal ◽  
Nikhil Sahajpal ◽  
Vamsi Kota ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Cell Carcinoma ◽  
Clear Cell ◽  
Risk Group ◽  
Clear Cell Carcinoma ◽  
Gene Signature ◽  
Renal Clear Cell Carcinoma ◽  
High Risk Group ◽  
Elevated Expression

AbstractComplex interactions in tumor microenvironment between ECM (extra-cellular matrix) and cancer cell plays a central role in the generation of tumor supportive microenvironment. In this study, the expression of ECM-related genes was explored for prognostic and immunological implication in clear cell renal clear cell carcinoma (ccRCC). Out of 964 ECM genes, higher expression (z-score > 2) of 35 genes showed significant association with overall survival (OS), progression-free survival (PFS) and disease-specific survival (DSS). On comparison to normal tissue, 12 genes (NUDT1, SIGLEC1, LRP1, LOXL2, SERPINE1, PLOD3, ZP3, RARRES2, TGM2, COL3A1, ANXA4, and POSTN) showed elevated expression in kidney tumor (n = 523) compared to normal (n = 100). Further, Cox proportional hazard model was utilized to develop 12 genes ECM signature that showed significant association with overall survival in TCGA dataset (HR = 2.45; 95% CI [1.78–3.38]; p < 0.01). This gene signature was further validated in 3 independent datasets from GEO database. Kaplan–Meier log-rank test significantly associated patients with elevated expression of this gene signature with a higher risk of mortality. Further, differential gene expression analysis using DESeq2 and principal component analysis (PCA) identified genes with the highest fold change forming distinct clusters between ECM-rich high-risk and ECM-poor low-risk patients. Geneset enrichment analysis (GSEA) identified significant perturbations in homeostatic kidney functions in the high-risk group. Further, higher infiltration of immunosuppressive T-reg and M2 macrophages was observed in high-risk group patients. The present study has identified a prognostic signature with associated tumor-promoting immune niche with clinical utility in ccRCC. Further exploration of ECM dynamics and validation of this gene signature can assist in design and application of novel therapeutic approaches.

scholarly journals Development and Validation of a Prognostic Gene Signature in Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Chuanchuan Zhan ◽  
Zichu Wang ◽  
Chao Xu ◽  
Xiao Huang ◽  
Junzhou Su ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
High Risk ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC), one of the most common urologic cancer types, has a relatively good prognosis. However, clinical diagnoses are mostly done during the medium or late stages, when mortality and recurrence rates are quite high. Therefore, it is important to perform real-time information tracking and dynamic prognosis analysis for these patients. We downloaded the RNA-seq data and corresponding clinical information of ccRCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A total of 3,238 differentially expressed genes were identified between normal and ccRCC tissues. Through a series of Weighted Gene Co-expression Network, overall survival, immunohistochemical and the least absolute shrinkage selection operator (LASSO) analyses, seven prognosis-associated genes (AURKB, FOXM1, PTTG1, TOP2A, TACC3, CCNA2, and MELK) were screened. Their risk score signature was then constructed. Survival analysis showed that high-risk scores exhibited significantly worse overall survival outcomes than low-risk patients. Accuracy of this prognostic signature was confirmed by the receiver operating characteristic curve and was further validated using another cohort. Gene set enrichment analysis showed that some cancer-associated phenotypes were significantly prevalent in the high-risk group. Overall, these findings prove that this risk model can potentially improve individualized diagnostic and therapeutic strategies.

Sign in / Sign up

Export Citation Format

Share Document