Dataset Information

Prediction of High-Grade Clear Cell Renal Cell Carcinoma Based on Plasma mRNA Profiles in Patients with Localized Pathologic T1N0M0 Stage Disease.

ABSTRACT: A high nuclear grade is crucial to predicting tumor recurrence and metastasis in clear cell renal cell carcinomas (ccRCCs). We aimed to compare the mRNA profiles of tumor tissues and preoperative plasma in patients with localized T1 stage ccRCCs, and to evaluate the potential of the plasma mRNA profile for predicting high-grade ccRCCs. Data from a prospective cohort (n = 140) were collected between November 2018 and November 2019. Frozen tumor tissues and plasma were used to measure PBRM1, BAP1, SET domain-containing 2 (SETD2), KDM5C, FOXC2, CLIP4, AQP1, DDX11, BAIAP2L1, and TMEM38B mRNA levels, and correlation with the Fuhrman grade was investigated. Multivariate logistic regression analysis revealed significant association between high-grade ccRCC and SETD2 and DDX11 mRNA levels in tissues (odds ratio (b) = 0.021, 95% confidence interval (CI): 0.001-0.466, p = 0.014; b = 6.116, 95% CI: 1.729-21.631, p = 0.005, respectively) and plasma (b = 0.028, 95% CI 0.007-0.119, p < 0.001; b = 1.496, 95% CI: 1.187-1.885, p = 0.001, respectively). High-grade ccRCC prediction models revealed areas under the curve of 0.997 and 0.971 and diagnostic accuracies of 97.86% and 92.86% for the frozen tissue and plasma, respectively. SETD2 and DDX11 mRNA can serve as non-invasive plasma biomarkers for predicting high-grade ccRCCs. Studies with long follow-ups are needed to validate the prognostic value of these biomarkers in ccRCCs.

SUBMITTER: Park JS

PROVIDER: S-EPMC7281002 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Prediction of High-Grade Clear Cell Renal Cell Carcinoma Based on Plasma mRNA Profiles in Patients with Localized Pathologic T1N0M0 Stage Disease.

Park Jee Soo JS Lee Hyo Jung HJ Almujalhem Ahmad A Althubiany Hatem Hamed HH A Alqahatani Ali AA Jang Won Sik WS Kim Jongchan J Lee Seung Hwan SH Rha Koon Ho KH Ham Won Sik WS

Cancers 20200507 5

A high nuclear grade is crucial to predicting tumor recurrence and metastasis in clear cell renal cell carcinomas (ccRCCs). We aimed to compare the mRNA profiles of tumor tissues and preoperative plasma in patients with localized T1 stage ccRCCs, and to evaluate the potential of the plasma mRNA profile for predicting high-grade ccRCCs. Data from a prospective cohort (<i>n</i> = 140) were collected between November 2018 and November 2019. Frozen tumor tissues and plasma were used to measure <i>PB ...[more]

PMID: 32392781

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Project description:The tumor stage, size, grade, and necrosis (SSIGN) score was originally defined using patients treated with radical nephrectomy (RN) between 1970 and 1998 for clear cell renal cell carcinoma (ccRCC), excluding patients treated with partial nephrectomy (PN).To characterize the original SSIGN score cohort with longer follow-up and evaluate a contemporary series of patients treated with RN and PN.Retrospective single-institution review of 3600 consecutive surgically treated ccRCC patients grouped into three cohorts: original RN, contemporary (1999-2010) RN, and contemporary PN.RN or PN.The association of the SSIGN score with risk of death from RCC was assessed using a Cox proportional hazards regression model, and predictive ability was summarized with a C-index.The SSIGN scores differed significantly between the original RN, contemporary RN, and contemporary PN cohorts (p<0.001), with SSIGN ?4 in 53.5%, 62.7%, and 4.7%, respectively (p<0.001). The median durations of follow-up for these groups were 20.1, 9.2, and 7.6 yr, respectively. Each increase in the SSIGN score was predictive of death from RCC (hazard ratios [HRs]: 1.41 for original RN, 1.37 for contemporary RN, and 1.70 for contemporary PN; all p<0.001). The C-indexes for these models were 0.82, 0.84, and 0.82 for original RN, contemporary RN, and contemporary PN, respectively. After accounting for an era-specific improvement in survival among RN patients (HR: 0.53 for contemporary vs original RN; p<0.001), the SSIGN score remained predictive of death from RCC (HR: 1.40; p<0.001).The SSIGN score remains a useful prediction tool for patients undergoing RN with 20-yr follow-up. When applied to contemporary RN and PN patients, the score retained strong predictive ability. These results should assist in patient counseling and help guide surveillance for ccRCC patients treated with RN or PN.We evaluated the validity of a previously described tool to predict survival following surgery in contemporary patients with kidney cancer. We found that this tool remains valid even when extended to patients significantly different than were initially used to create the tool.

Project description:Gene expression signatures have proven to be useful tools in many cancers to identify distinct subtypes of disease based on molecular features that drive pathogenesis, and to aid in predicting clinical outcomes. However, there are no current signatures for kidney cancer that are applicable in a clinical setting.To generate a signature biomarker for the clear cell renal cell carcinoma (ccRCC) good risk (ccA) and poor risk (ccB) subtype classification that could be readily applied to clinical samples to develop an integrated model for biologically defined risk stratification.A set of 72 ccRCC sample standards was used to develop a 34-gene classifier (ClearCode34) for assigning ccRCC tumors to subtypes. The classifier was applied to RNA-sequencing data from 380 nonmetastatic ccRCC samples from the Cancer Genome Atlas (TCGA), and to 157 formalin-fixed clinical samples collected at the University of North Carolina.Kaplan-Meier analyses were performed on the individual cohorts to calculate recurrence-free survival (RFS), cancer-specific survival (CSS), and overall survival (OS). Training and test sets were randomly selected from the combined cohorts to assemble a risk prediction model for disease recurrence.The subtypes were significantly associated with RFS (p<0.01), CSS (p<0.01), and OS (p<0.01). Hazard ratios for subtype classification were similar to those of stage and grade in association with recurrence risk, and remained significant in multivariate analyses. An integrated molecular/clinical model for RFS to assign patients to risk groups was able to accurately predict CSS above established, clinical risk-prediction algorithms.The ClearCode34-based model provides prognostic stratification that improves upon established algorithms to assess risk for recurrence and death for nonmetastatic ccRCC patients.We developed a 34-gene subtype predictor to classify clear cell renal cell carcinoma tumors according to ccA or ccB subtypes and built a subtype-inclusive model to analyze patient survival outcomes.

Project description:BACKGROUND:Historically, VHL was the only frequently mutated gene in clear cell renal cell carcinoma (ccRCC), with conflicting clinical relevance. Recent sequencing efforts have identified several novel frequent mutations of histone modifying and chromatin remodeling genes in ccRCC including PBRM1, SETD2, BAP1, and KDM5C. PBRM1, SETD2, and BAP1 are located in close proximity to VHL within a commonly lost (approximately 90%) 3p locus. To date, the clinical and pathologic significance of mutations in these novel candidate tumor suppressors is unknown. OBJECTIVE:To determine the frequency of and render the first clinical and pathologic outcome associated with mutations of these novel candidate tumor suppressors in ccRCC. DESIGN, SETTING, AND PARTICIPANTS:Targeted sequencing was performed in 185 ccRCCs and matched normal tissues from a single institution. Pathologic features, baseline patient characteristics, and follow-up data were recorded. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS:The linkage between mutations and clinical and pathologic outcomes was interrogated with the Fisher exact test (for stage and Fuhrman nuclear grade) and the permutation log-rank test (for cancer-specific survival [CSS]). RESULTS AND LIMITATIONS:PBRM1, BAP1, SETD2, and KDM5C are mutated at 29%, 6%, 8%, and 8%, respectively. Tumors with mutations in PBRM1 or any of BAP1, SETD2, or KDM5C (19%) are more likely to present with stage III disease or higher (p = 0.01 and p = 0.001, respectively). Small tumors (<4 cm) with PBRM1 mutations are more likely to exhibit stage III pathologic features (odds ratio: 6.4; p = 0.001). BAP1 mutations tend to occur in Fuhrman grade III-IV tumors (p = 0.052) and are associated with worse CSS (p = 0.01). Clinical outcome data are limited by the number of events. CONCLUSIONS:Most mutations of chromatin modulators discovered in ccRCC are loss of function, associated with advanced stage, grade, and possibly worse CSS. Further studies validating the clinical impact of these novel mutations and future development of therapeutics remedying these tumor suppressors are warranted.

Dataset Information

Prediction of High-Grade Clear Cell Renal Cell Carcinoma Based on Plasma mRNA Profiles in Patients with Localized Pathologic T1N0M0 Stage Disease.

Publications

Prediction of High-Grade Clear Cell Renal Cell Carcinoma Based on Plasma mRNA Profiles in Patients with Localized Pathologic T1N0M0 Stage Disease.

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