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Serum Adiponectin Level May be an Independent Predictor of Clear Cell Renal Cell Carcinoma.

ABSTRACT: OBJECTIVES:To examine whether serum adiponectin or leptin level has the ability to differentiate clear cell renal cell carcinoma (ccRCC) from other subtypes of renal cell carcinoma (RCC) in a Chinese population. PATIENTS AND METHODS:We recruited 198 consecutive patients who were treated with radical or partial nephrectomy in our department from September 2011 to June 2013. Their histological types were all malignant, including clear cell, papillary, chromophobe and unclassified RCC. We also enrolled 86 people with no cancer or cancer-related diseases as normal controls. We measured patients' preoperative blood samples for plasma adiponectin and leptin concentrations using an enzyme-linked immunosorbent assay method. Statistical methods were used to analyze ccRCC and other subtypes as they relate to serum adiponectin/leptin level and other factors such as body mass index or visceral fat area. RESULTS:In our database, normal controls had significantly higher circulating adiponectin (p < 0.001) and leptin levels (p < 0.001) than patients with RCC. Among the 198 RCC patients, 156 patients had ccRCC while 42 patients had other histological types. Serum adiponectin levels were lower in ccRCC patients than in non-clear-cell RCC patients (p = 0.004). However, the plasma leptin level was not differently distributed between ccRCC and non-ccRCC patients (p = 0.940). In multivariate analysis, we found that serum adiponectin level may be an independent predictor for discriminating ccRCC patients from others (p = 0.004). Furthermore, in the ccRCC subgroup, we observed that men with ccRCC had lower leptin (p < 0.001) and adiponectin (p = 0.002) levels, and diabetic patients had lower plasma adiponectin levels (p = 0.001). CONCLUSIONS:Lower plasma adiponectin concentration was related to an increased incidence of ccRCC and may act as an independent predictor for ccRCC. Our study may help define the process from obesity to adipose tissue, to cytokines and finally to ccRCC.

SUBMITTER: Wang H

PROVIDER: S-EPMC4934042 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Serum Adiponectin Level May be an Independent Predictor of Clear Cell Renal Cell Carcinoma.

Wang Hongkai H Wu Junlong J Gu Weijie W Wang Beihe B Wan Fangning F Dai Bo B Zhang Hailiang H Shi Guohai G Shen Yijun Y Zhu Yiping Y Zhu Yao Y Ye Dingwei D

Journal of Cancer 20160627 10

<h4>Objectives</h4>To examine whether serum adiponectin or leptin level has the ability to differentiate clear cell renal cell carcinoma (ccRCC) from other subtypes of renal cell carcinoma (RCC) in a Chinese population.<h4>Patients and methods</h4>We recruited 198 consecutive patients who were treated with radical or partial nephrectomy in our department from September 2011 to June 2013. Their histological types were all malignant, including clear cell, papillary, chromophobe and unclassified RC ...[more]

PMID: 27390609

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Project description:BackgroundGene 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.ObjectiveTo 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.Design, setting, and participantsA 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.Outcome measurements and statistical analysisKaplan-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.Results and limitationsThe 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.ConclusionsThe ClearCode34-based model provides prognostic stratification that improves upon established algorithms to assess risk for recurrence and death for nonmetastatic ccRCC patients.Patient summaryWe 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:(1). Background: Immunohistochemical (IHC) evaluation of programmed death-1 (PD-1) and its ligand (PD-L1) is being used to evaluate advanced malignancies with potential response to immune checkpoint inhibitors. We evaluated both plasma and tissue expression of PD-1 and PD-L1 in the same cohort of patients, including non-metastatic and metastatic clear cell renal cell carcinoma (CCRCC). Concomitant plasma and tissue expression of PD-1 and PD-L1 was evaluated with emphasis on diagnostic and prognostic implications. (2) Methods: we analyzed PD-1 and PD-L1 IHC expression in tumor tissues and soluble forms (sPD-1 and sPD-L1) in plasma from 89 patients with CCRCC, of which 23 were metastatic and 16 received systemic therapy. The primary endpoint was evaluation of overall survival using Kaplan-Meier analysis and the Cox regression model. Plasma samples from healthy volunteers were also evaluated. (3) Results: Interestingly, sPD-1 and sPD-L1 levels were lower in cancer patients than in controls. sPD-1 and sPD-L1 levels and their counterpart tissue expression both at the tumor center and infiltrating front were not associated. Higher expression of both PD-1 and PD-L1 were associated with tumor grade, necrosis and tumor size. PD-1 was associated to tumor stage (pT) and PD-L1 to metastases. sPD-1 and sPD-L1 were not associated with clinico-pathological parameters, although both were higher in patients with synchronous metastases compared to metachronous ones and sPD-L1 was also higher for metastatic patients compared to non-metastatic patients. sPD-1 was also associated with the International Metastatic Renal Cell Cancer Database Consortium (IMDC) prognostic groups in metastatic CCRCC and also to the Morphology, Attenuation, Size and Structure (MASS) response criteria in metastatic patients treated with systemic therapy, mainly tyrosine-kinase inhibitors. Regarding prognosis, PD-L1 immunostaining at the tumor center with and without the tumor front was associated with worse survival, and so was sPD-L1 at a cut-off >793 ng/mL. Combination of positivity at both the tissue and plasma level increased the level of significance to predict prognosis. (4) Conclusions: Our findings corroborate the role of PD-L1 IHC to evaluate prognosis in CCRCC and present novel data on the usefulness of plasma sPD-L1 as a promising biomarker of survival in this neoplasia.

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Serum Adiponectin Level May be an Independent Predictor of Clear Cell Renal Cell Carcinoma.

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Serum Adiponectin Level May be an Independent Predictor of Clear Cell Renal Cell Carcinoma.

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