Patients with ClearCode34-identified molecular subtypes of clear cell renal cell carcinoma represent unique populations with distinct comorbidities

Skeletal muscle and visceral adipose radiodensities are pre-surgical, non-invasive markers of aggressive kidney cancer

INTRODUCTION

Most studies on body composition in kidney cancer have been conducted among patients with metastatic disease. Given that aggressive tumours can adversely impact body composition and even non-metastatic tumours can be aggressive, we evaluated associations between pre-surgical body composition features and tumour pathological features in patients with non-metastatic clear cell renal cell cancer (ccRCC).

METHODS

The Resolve Cohort consists of 1239 patients with non-metastatic ccRCC who underwent nephrectomy at Memorial Sloan Kettering Cancer Center between 2000 and 2020. The cross-sectional areas and radiodensities of skeletal muscle, visceral adipose, and subcutaneous adipose tissues were determined from pre-surgical computed tomography (CT) scans at the third lumbar vertebrae using Automatica software. Pearson's correlation coefficients describe inter-relationships among BMI and body composition variables, while odds ratios (OR) and 95% confidence intervals (CI) estimate associations between continuous body composition features (per 1-standard deviation) and advanced stage (Stage III vs. Stages I-II) and high Fuhrman grade (Grades 3-4 vs. 1-2) from multivariable logistic regression models that considered the potential impact of biological sex, contrast enhanced CTs, and early age at onset of ccRCC.

RESULTS

The cohort was predominantly male (69%), white (89%), and had a median age of 58. The proportion of patients presenting with advanced stage and high-grade disease were 31% and 51%, respectively. In models that adjusted for demographics and all body composition variables simultaneously, decreasing skeletal muscle radiodensity (i.e., more fat infiltration) but increasing visceral adipose tissue radiodensity (i.e., more lipid depletion) were associated with advanced tumour features. Per 8.4 HU decrease in skeletal muscle radiodensity, the odds of presenting with advanced stage was 1.61 (95% CI: 1.34-1.93). Per 7.22 HU increase in visceral adipose tissue radiodensity, the odds of presenting with advanced stage was 1.45 (95% CI: 1.22-1.74). Skeletal muscle index (i.e., sarcopenia) was not associated with either tumour feature. Similar associations were observed for Fuhrman grade, a more direct marker of tumour aggressiveness. Associations did not differ by sex, contrast use, or age at onset of ccRCC.

CONCLUSIONS

Lipid infiltrated skeletal muscle, but lipid depleted visceral adipose tissue were independently associated with advanced tumour features in non-metastatic ccRCC. Findings highlight the importance of evaluating the full range of body composition features simultaneously in multivariable models. Interpreting pre-surgical CTs for body composition for patients may be a novel and non-invasive way to identify patients with aggressive renal tumours, which is clinically relevant as renal biopsies are not routinely performed.

Current Landscape of Genomic Biomarkers in Clear Cell Renal Cell Carcinoma

CONTEXT

Dramatic gains in our understanding of the molecular biology of clear cell renal cell carcinoma (ccRCC) have created a foundation for clinical translation to improve patient care.

OBJECTIVE

To review and contextualize clinically impactful data surrounding genomic biomarkers in ccRCC.

EVIDENCE ACQUISITION

A systematic literature search was conducted focusing on genomic-based biomarkers with an emphasis on studies assessing clinical outcomes.

EVIDENCE SYNTHESIS

The advancement of tumor sequencing techniques has led to a rapid increase in the knowledge of the molecular underpinnings of ccRCC and with that the discovery of multiple candidate genomic biomarkers. These include somatic gene mutations such as VHL, PBRM1, SETD2, and BAP1; copy number variations; transcriptomic multigene signatures; and specific immune cell populations. Many of these biomarkers have been assessed for their association with survival and a smaller number as potential predictors of a response to systemic therapy. In this scoping review, we discuss many of these biomarkers in detail. Further studies are needed to continue to refine and validate these molecular tools for risk stratification, with the ultimate goal of improving clinical decision-making and patient outcomes.

CONCLUSIONS

While no tissue or blood-based biomarkers for ccRCC have been incorporated into routine clinical practice to date, the field continues to expand rapidly. There remains a critical need to develop and validate these tools in order to improve the care for patients with kidney cancer.

PATIENT SUMMARY

Genomic biomarkers have the potential to better predict outcome and select the most appropriate treatment for patients with kidney cancer; however, further research is needed before any of these currently developed biomarkers are adopted into clinical practice.

The Promise of Neoadjuvant and Adjuvant Therapies for Renal Cancer

Because metachronous metastatic disease will develop in 20% to 40% of patients with presumed localized renal cell carcinoma (RCC) treated surgically, research is focused on neoadjuvant and adjuvant systemic therapy, to improve disease-free and overall survival. Neoadjuvant therapies trialed include anti-vascular endothelial growth factor (VEGF) tyrosine kinase inhibitor (TKI) agents, or combination therapies (immunotherapy with TKI), and aim to improve resectability of locoregional RCC. Adjuvant therapies trialed include cytokines, anti-VEGF TKI agents, or immunotherapy. These therapeutics can facilitate the surgical extirpation of the primary kidney tumor in the neoadjuvant setting and improve disease-free survival in the adjuvant setting.

Clear cell renal cell carcinoma molecular variations in non-Hispanic White and Hispanic patients

BACKGROUND

The United States is becoming increasingly diverse, but few molecular studies have assessed the progression of clear cell renal cell carcinoma (ccRCC) in diverse patient populations. This study examined ccRCC molecular variations in non-Hispanic White (NHW) and Hispanic patients and their effect on the association of gene expression with high-grade (Grade 3 or 4) ccRCC and overall mortality.

METHODS

A total of 156 patients were included in VHL sequencing and/or TempO-Seq analysis. DESeq2 was used to identify the genes associated with high-grade ccRCC. Logistic regression analysis was performed to assess whether race and ethnicity was associated with high/moderate impact VHL somatic mutations and the ccA/ccB subtype. Cox regression analysis was performed to assess association of molecular subtype and gene expression with overall mortality.

RESULTS

NHWs had moderate or high impact mutations in the VHL gene at a higher frequency than Hispanics (40.2% vs. 27.4%), while Hispanics had a higher frequency of the ccA subtype than NHWs (61.9% vs. 45.8%). ccA was more common in patients with BMI≥35 (65.2%) than in those with BMI < 25 (45.0%). There were 11 differentially expressed genes between high- and low-grade tumors. The Haptoglobin (HP) gene was most significantly overexpressed in high- compared to low-grade ccRCC in all samples (p-adj = 1.7 × 10^-12 ). When stratified by subtype, the 11 genes were significantly differentially expressed in the ccB subtype, but none of them were significant after adjusting for multiple testing in ccA. Finally, patients with the ccB subtype had a significantly increased risk of overall mortality (HR 4.87; p = 0.01) compared to patients with ccA, and patients with high HP expression and ccB, had a significantly increased risk of mortality compared to those with low HP expression and ccA (HR 6.45, p = 0.04).

CONCLUSION

This study reports ccRCC molecular variations in Hispanic patients who were previously underrepresented.

A comparison of analytic approaches for investigating the obesity paradox in kidney cancer

PURPOSE

Body mass index (BMI) and kidney cancer mortality are inconsistently associated in the scientific literature. To understand how study design affects results, we contrasted associations between pre-diagnosis BMI and mortality under different analytic scenarios in a large, population-based prospective cohort study.

METHODS

Using data from the NIH-AARP Diet and Health Study (1995-2011), we constructed two cohorts: a "full at-risk" cohort with no kidney cancer history at baseline (n = 252,845) and an "incident cancer" subset who developed kidney cancer during follow-up (n = 1,652). Cox Proportional Hazards models estimated hazard ratios (HR) and 95% confidence intervals (CI) between pre-diagnosis BMI and mortality for different outcomes (all-cause and cancer-specific mortality), in the different cohorts (full at-risk vs. incident cancer cohort), and with different covariates (minimally vs. fully adjusted). For the incident cancer cohort, we also examined time to mortality using different timescales: from enrollment or diagnosis.

RESULTS

In the full at-risk study population, higher pre-diagnosis BMI was associated with greater cancer-specific mortality in fully adjusted multivariable models, particularly for obese participants [HR, (95% CI): 1.76, (1.38-2.25)]. This association was less pronounced in the incident cancer cohort [1.50, (1.09-2.07)]. BMI was not strongly associated with all-cause mortality in either cohort in fully adjusted models [full cohort: 1.03, (1.01, 1.06); incident cancer cohort: 1.20, (0.97, 1.48)].

CONCLUSIONS

Populations characterized by high adult BMI will likely experience greater population burdens of mortality from kidney cancer, partially because of higher rates of kidney cancer diagnosis. Questions regarding overall mortality burden and post-diagnosis cancer survivorship are distinct and require different study designs.

The Role of Long Noncoding RNA (lncRNAs) Biomarkers in Renal Cell Carcinoma

Renal cell carcinoma is one of the common cancers whose incidence and mortality are continuously growing worldwide. Initially, this type of tumour is usually asymptomatic. Due to the lack of reliable diagnostic markers, one-third of ccRCC patients already have distant metastases at the time of diagnosis. This underlines the importance of establishing biomarkers that would enable the prediction of the disease's course and the risk of metastasis. LncRNA, which modulates genes at the epigenetic, transcriptional, and post-transcriptional levels, appears promising. The actions of lncRNA involve sponging and sequestering target miRNAs, thus affecting numerous biological processes. Studies have confirmed the involvement of RNAs in various diseases, including RCC. In this review, we focused on MALAT1 (a marker of serious pathological changes and a factor in the promotion of tumorigenesis), RCAT1 (tumour promoter in RCC), DUXAP9 (a plausible marker of localized ccRCC), TCL6 (exerting tumour-suppressive effects in renal cancer), LINC00342 (acting as an oncogene), AGAP2 Antisense1 (plausible predictor of RCC progression), DLEU2 (factor promoting tumours growth via the regulation of epithelial-mesenchymal transition), NNT-AS1 (sponge of miR-22 contributing to tumour progression), LINC00460 (favouring ccRCC development and progression) and Lnc-LSG1 (a factor that may stimulate ccRCC metastasis).

The cuproptosis-associated 13 gene signature as a robust predictor for outcome and response to immune- and targeted-therapies in clear cell renal cell carcinoma

Cuproptosis, the newly identified form of regulatory cell death (RCD), results from mitochondrial proteotoxic stress mediated by copper and FDX1. Little is known about significances of cuproptosis in oncogenesis. Here we determined clinical implications of cuproptosis in clear cell renal cell carcinoma (ccRCC). Based on the correlation and survival analyses of cuproptosis-correlated genes in TCGA ccRCC cohort, we constructed a cuproptosis-associated 13 gene signature (CuAGS-13) score system. In both TCGA training and two validation cohorts, when patients were categorized into high- and low-risk groups according to a median score as the cutoff, the CuAGS-13 high-risk group was significantly associated with shorter overall survival (OS) and/or progression-free survival (PFS) independently (P<0.001 for all). The CuAGS-13 score assessment could also predict recurrence and recurrence-free survival of patients at stage I - III with a high accuracy, which outperformed the ccAccB/ClearCode34 model, a well-established molecular predictor for ccRCC prognosis. Moreover, patients treated with immune checkpoint inhibitors (ICIs) acquired complete/partial remissions up to 3-time higher coupled with significantly longer PFS in the CuAGS-13 low- than high-risk groups in both training and validation cohorts of ccRCCs (7.2 - 14.1 vs. 2.1 - 3.0 months, P<0.001). The combination of ICI with anti-angiogenic agent Bevacizumab doubled remission rates in CuAGS-13 high-risk patients while did not improve the efficacy in the low-risk group. Further analyses showed a positive correlation between CuAGS-13 and TIDE scores. We also observed that the CuAGS-13 score assessment accurately predicted patient response to Sunitinib, and higher remission rates in the low-risk group led to longer PFS (Low- vs. high-risk, 13.9 vs. 5.8 months, P = 5.0e-12). Taken together, the CuAGS-13 score assessment serves as a robust predictor for survival, recurrence, and response to ICIs, ICI plus anti-angiogenic drugs and Sunitinib in ccRCC patients, which significantly improves patient stratifications for precision medicine of ccRCC.

Renal Cell Cancer and Obesity

Cancers are a frequent cause of morbidity and mortality. There are many risk factors for tumours, including advanced age, personal or family history of cancer, some types of viral infections, exposure to radiation and some chemicals, smoking and alcohol consumption, as well as obesity. Increasing evidence suggest the role of obesity in the initiation and progression of various cancers, including renal cell carcinoma. Since tumours require energy for their uncontrollable growth, it appears plausible that their initiation and development is associated with the dysregulation of cells metabolism. Thus, any state characterised by an intake of excessive energy and nutrients may favour the development of various cancers. There are many factors that promote the development of renal cell carcinoma, including hypoxia, inflammation, insulin resistance, excessive adipose tissue and adipokines and others. There are also many obesity-related alterations in genes expression, including DNA methylation, single nucleotide polymorphisms, histone modification and miRNAs that can promote renal carcinogenesis. This review focuses on the impact of obesity on the risk of renal cancers development, their aggressiveness and patients’ survival.

AGAP2-AS1 as a prognostic biomarker in low-risk clear cell renal cell carcinoma patients with progressing disease

Background

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer and one of the most common cancers. While survival for localized ccRCC is good, the survival of metastatic disease is not, and thirty percent of patients with ccRCC develop metastases during follow-up. Although current scoring methods accurately identify patients at low progression risk, a small subgroup of those patients still experience metastasis. We therefore aimed to identify ccRCC progression biomarkers in “low-risk” patients who were potentially eligible for adjuvant treatments or more intensive follow-up.

Methods

We assembled a cohort of ccRCC patients (n  = 443) and identified all “low-risk” patients who later developed progressing tumors (n  = 8). Subsequently, we performed genome-wide expression profiling from formalin-fixed samples obtained at initial surgery from these “low-risk” patients and 16 matched patients not progressing to recurrence with metastasis. The patients were matched for Leibovich sore, creatinine, age, sex, tumor size and tumor stage. Key results were confirmed with qPCR and external data from The Cancer Genome Atlas.

Results

Principal component analysis indicated that systematic transcriptomic differences were already detectable at the time of initial surgery. One thousand one hundred sixty-seven genes, mainly associated with cancer and immune-related pathways, were differentially expressed between progressors and nonprogressors. A search for a classifier revealed that overexpression of AGAP2-AS1, an antisense long noncoding RNA, correctly classified 23 of 24 samples, years (4.5 years average) in advance of the discovery of metastasis and without requiring larger gene panels. Subsequently, we confirmed AGAP2-AS1 gene overexpression by qPCR in the same samples (p  < 0.05). Additionally, in external data from The Cancer Genome Atlas, overexpression of AGAP2-AS1 is correlated with overall unfavorable survival outcome in ccRCC, irrespective of other prognostic predictors (p  = 2.44E−7).

Conclusion

AGAP2-AS1 may represent a novel biomarker identifying high-risk ccRCC patients currently classified as “low risk” at the time of surgery.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02395-9.

Differences in risk factors for molecular subtypes of clear cell renal cell carcinoma

The ccA and ccB molecular subtypes of clear cell renal cell carcinoma (ccRCC) have well-characterized prognostic relevance. However, it is not known whether they possess distinct etiologies. We investigated the relationships between these subtypes and RCC risk factors within a case-control study conducted in Eastern Europe. We analyzed risk factor data for ccA (n = 144) and ccB (n = 106) cases and 1476 controls through case-only and case-control comparisons to assess risk factor differences across subtypes using logistic and polytomous regression models. We also performed a meta-analysis summarizing case-only results from our study and three patient cohorts. Patients with ccB tumors had poorer survival than those with ccA tumors and were more likely to be male (case-only odds ratio [OR] 2.68, 95% confidence interval [CI] 1.43-5.03). In case-control analyses, body mass index was significantly associated with ccA tumors (OR 2.45, 95% CI 1.18-5.10 for ≥35 vs <25 kg/m2 ) but not with ccB tumors (1.52, 0.56-4.12), while trichloroethylene was associated with ccB but not ccA (OR 3.09, 95% CI 1.11-8.65 and 1.25, 0.36-4.39 respectively for ≥1.58 ppm-years vs unexposed). A polygenic risk score of genetic variants identified from genome-wide association studies was associated with both ccA and, in particular, ccB (OR 1.82, 1.11-2.99 and 2.87, 95% CI 1.64-5.01 respectively for 90th vs 10th percentile). In a meta-analysis of case-only results including three patient cohorts, we still observed the ccB excess for male sex and the ccA excess for obesity. In conclusion, our findings suggest the existence of etiologic heterogeneity across ccRCC molecular subtypes for several risk factors.

A 25-year perspective on evaluation and understanding of biomarkers in urologic cancers

The past 25 years have witnessed an explosion of investigative attempts to identify clinically useful biomarkers which can have meaningful impacts for patients with urologic cancers. However, in spite of the enormous amount of research aiming to identify markers with the hope of impacting patient care, only a handful have proven to have true clinical utility. Improvements in targeted imaging, pan-omics evaluation, and genetic sequencing at the tissue and single-cell levels have yielded many potential targets for continued biomarker investigation. This article, as one in this series for the 25th Anniversary Issue of Urologic Oncology: Seminars and Original Investigations, serves to give a perspective on our progress and failures over the past quarter-century in our highest volume urologic cancers: prostate, bladder, and kidney cancers.

Genomic profiling in renal cell carcinoma

The treatment landscape of metastatic renal cell carcinoma (RCC) has been revolutionized over the past two decades, bringing forth an era in which more than a dozen therapeutic agents are now available to treat patients. As a consequence, personalized care has become a critical part of developing effective treatment guidelines and improving patient outcomes. One of the most important emerging aspects of precision medicine in cancer is matching patients and treatments based on the genomic characteristics of an individual and their tumour. Despite the lack of a single genomic predictor of treatment response or prognostication feature in RCC, emerging research suggests that the identification of such markers remains promising. Mutations in VHL and alterations in its downstream pathways are the mainstay of RCC development and progression. However, the predictive value of VHL mutations has been questioned. Further research has examined mutations in genes involved in chromosome remodelling (for example, PBRM1, BAP1 and SETD2), DNA methylation and DNA damage repair, all of which have been associated with clinical outcomes. Here, we provide a comprehensive overview of genomic evidence in the context of RCC and its potential predictive and prognostic value.

Transcriptomic signatures related to the obesity paradox in patients with clear cell renal cell carcinoma: a cohort study

BACKGROUND

Obesity is associated with an increased risk of developing clear cell renal cell carcinoma (RCC) but, paradoxically, obesity is also associated with improved oncological outcomes in this cancer. Because the biological mechanisms underlying this paradoxical association are poorly understood, we aimed to identify transcriptomic differences in primary tumour and peritumoral adipose tissue between obese patients and those at a normal weight.

METHODS

In this cohort study, we assessed data from five independent clinical cohorts of patients with clear cell RCC aged 18 years and older. Overweight patients were excluded from each cohort for our analysis. We assessed patients from the COMPARZ phase 3 clinical trial, a cohort from the Cancer Genome Atlas (TCGA), and a Memorial Sloan Kettering (MSK) observational immunotherapy cohort for their inclusion into our study. We assessed overall survival in obese patients (those with a body-mass index [BMI] ≥30 kg/m²) and in patients with a normal weight (BMI 18·5-24·9 kg/m², as per WHO's BMI categories), defined as the time from treatment initiation (in the COMPARZ and MSK immunotherapy cohorts) or surgery (in the TCGA cohort) to the date of any-cause death or of censoring on the day of the last follow-up. We also evaluated and validated transcriptomic differences in the primary tumours of obese patients compared with those of a normal weight. We compared gene-expression differences in peritumoral adipose tissue and tumour tissue in an additional, prospectively collected cohort of patients with non-metastatic clear cell RCC (the MSK peritumoral adipose tissue cohort). We analysed differences in gene expression between obese patients and those at a normal weight in the COMPARZ, TCGA, and peritumoral adipose tissue cohorts. We also assessed the tumour immune microenvironment in a prospective cohort of patients who had nephrectomy for localised RCC at MSK.

FINDINGS

Of the 453 patients in the COMPARZ trial, 375 (83%) patients had available microarray data, pretreatment BMI measurements, and overall survival data for analyses, and we excluded 119 (26%) overweight patients, leaving a final cohort of 256 (68%) patients from this study for our analyses. From 332 patients in the TCGA cohort, we evaluated clinical and demographic data from 152 (46%) patients with advanced (ie, stages III and IV) clear cell RCC treated by nephrectomy; after exclusion of 59 (39%) overweight patients, our final cohort consisted of 93 (61%) patients. After exclusion of 74 (36%) overweight patients from the initial MSK immunotherapy study population of 203 participants, our final cohort for overall survival analysis comprised 129 (64%) participants. We found that overall survival was longer in obese patients than in those with normal weight in the TCGA cohort, after adjustment for stage or grade (adjusted HR 0·41, 95% CI 0·22-0·75), and in the COMPARZ clinical trial after adjustment for International Metastatic RCC Database (IMDC) risk score (0·68, 0·48-0·96). In the MSK immunotherapy cohort, the inverse association of BMI with mortality (HR 0·54, 95% CI 0·31-0·95) was not significant after adjustment for IMDC risk score (adjusted HR 0·72, 95% CI 0·40-1·30). Tumours of obese patients showed higher angiogenic scores on gene-set enrichment analysis-derived hallmark gene set angiogenesis signatures than did those of patients at a normal weight, but the degree of immune cell infiltration did not differ by BMI. We found increased peritumoral adipose tissue inflammation in obese patients relative to those at a normal weight, especially in peritumoral fat near the tumour.

INTERPRETATION

We found aspects of the tumour microenvironment that vary by BMI in the tumour and peritumoral adipose tissue, which might contribute to the apparent survival advantage in obese patients with clear cell RCC compared with patients at a normal weight. The complex interplay between the clear cell RCC tumour and peritumoral adipose tissue microenvironment might have clinical relevance and warrants further investigation.

FUNDING

Ruth L Kirschstein Research Service Award, American Society of Clinical Oncology Young Investigator Award, MSK's Ludwig Center, Weiss Family Kidney Research Fund, Novartis, The Sidney Kimmel Center for Prostate and Urologic Cancers, and the National Institutes of Health (National Cancer Institute) Cancer Center Support Grant.

DNA methylation-based classification and identification of renal cell carcinoma prognosis-subgroups

BACKGROUND

Renal cell carcinoma (RCC) is the most common kidney cancer and includes several molecular and histological subtypes with different clinical characteristics. The combination of DNA methylation and gene expression data can improve the classification of tumor heterogeneity, by incorporating differences at the epigenetic level and clinical features.

METHODS

In this study, we identified the prognostic methylation and constructed specific prognosis-subgroups based on the DNA methylation spectrum of RCC from the TCGA database.

RESULTS

Significant differences in DNA methylation profiles among the seven subgroups were revealed by consistent clustering using 3389 CpGs that indicated that were significant differences in prognosis. The specific DNA methylation patterns reflected differentially in the clinical index, including TNM classification, pathological grade, clinical stage, and age. In addition, 437 CpGs corresponding to 477 genes of 151 samples were identified as specific hyper/hypomethylation sites for each specific subgroup. A total of 277 and 212 genes corresponding to DNA methylation at promoter sites were enriched in transcription factor of GKLF and RREB-1, respectively. Finally, Bayesian network classifier with specific methylation sites was constructed and was used to verify the test set of prognoses into DNA methylation subgroups, which was found to be consistent with the classification results of the train set. DNA methylation-based classification can be used to identify the distinct subtypes of renal cell carcinoma.

CONCLUSIONS

This study shows that DNA methylation-based classification is highly relevant for future diagnosis and treatment of renal cell carcinoma as it identifies the prognostic value of each epigenetic subtype.

Prognostication in Kidney Cancer: Recent Advances and Future Directions

The most common type of cancer originating in the kidney is renal cell carcinoma (RCC). In both localized and advanced RCC, a number of clinical, pathologic, and molecular factors have been identified as having prognostic significance. In localized disease, risk stratification has traditionally involved the anatomic extent of disease, and several integrated scoring systems have been developed to help predict outcomes after definitive local therapy. In metastatic RCC, integrated prognostic models have also been established. These are used to stratify patients in contemporary clinical trials and to guide risk-directed treatment selection in clinical practice. Although many prognostic factors are common to both localized and advanced disease, there are some important distinctions. In both of these types of disease, the prognostic role of specific molecular and genomic alterations is an area of active investigation. In this review, we highlight the current staging systems and prognostic factors in localized and metastatic RCC. We also explore future directions in this area, including the expanding role of molecular biomarkers and their integration into the traditional prognostic models.

Metabolic Pathways in Kidney Cancer: Current Therapies and Future Directions

BACKGROUND

Renal cell carcinoma (RCC) has become known as a metabolic disease, owing to the diverse array of metabolic defects and perturbations that occur as a result of the unique genetics that can drive these tumors. Recent attention to this feature of RCCs has fueled interest in targeting metabolism as a therapeutic strategy.

METHODS

We conducted a literature search to develop themes around discrete pathways or processes of cellular metabolism, provide a framework for understanding emerging therapeutic strategies, and consider future interventions.

RESULTS

Defects occur in metabolic pathways ranging from glycolysis to mitochondrial function and affect not only the tumor cell functionality, but also the local environment. We identified opportunities for therapeutic intervention associated with each pathway.

CONCLUSION

The metabolism of RCC cells presents a special environment of tumor susceptibilities, with opportunities for novel imaging applications and treatment paradigms that are being tested in monotherapy or as adjuncts to targeted or immune-based strategies.

Obesity and renal cell carcinoma risk by histologic subtype: A nested case-control study and meta-analysis

BACKGROUND

Although obesity is an established risk factor for renal cell carcinoma (RCC), it is unclear whether this relationship varies across histologic subtypes.

METHODS

We conducted a nested case-control study within the Kaiser Permanente Northern California (KPNC) health care network, and meta-analysis combining our results with those of previously published studies. Our KPNC study included 685 RCC cases [421 clear cell; 65 papillary; 24 chromophobe; 35 other; 141 not otherwise specified (NOS)] and 4266 controls. Subtype-specific odds ratios (ORs) and 95% confidence intervals (CIs) for categories of body mass index (BMI) and were computed from the case-control data using polytomous logistic regression. Findings from this and other relevant studies were combined by meta-analysis using a random effects model.

RESULTS

In the KPNC study, obesity (BMI ≥ 30 kg/m²) was associated with clear cell RCC (OR 1.5, 95% CI 1.1-2.1) and chromophobe RCC (OR 2.5, 95%CI 0.8-8.1), but not with papillary RCC (OR 1.0, 95% CI 0.5-1.9). In meta-analysis including three additional studies, a similar pattern of summary relative risks (SRR) for obesity was observed across subtypes (clear cell: SRR 1.8, 95% CI 1.5-2.2; chromophobe: SRR 2.2, 95% CI 1.3-3.7; papillary, SRR 1.2, 95% CI 0.8-1.6).

CONCLUSIONS

These findings support the hypothesis that histologic subtypes of RCC possess distinct etiologic pathways, with obesity important for the development of clear cell and, possibly, chromophobe RCC, but not papillary RCC.

Integrative radiomics expression predicts molecular subtypes of primary clear cell renal cell carcinoma

AIM

To identify combined positron-emission tomography (PET)/magnetic resonance imaging (MRI)-based radiomics as a surrogate biomarker of intratumour disease risk for molecular subtype ccA and ccB in patients with primary clear cell renal cell carcinoma (ccRCC).

MATERIALS AND METHODS

PET/MRI data were analysed retrospectively from eight patients. One hundred and sixty-eight radiomics features for each tumour sampling based on the regionally sampled tumours with 23 specimens were extracted. Sparse partial least squares discriminant analysis (SPLS-DA) was applied to feature screening on high-throughput radiomics features and project the selected features to low-dimensional intrinsic latent components as radiomics signatures. In addition, multilevel omics datasets were leveraged to explore the complementing information and elevate the discriminative ability.

RESULTS

The correct classification rate (CCR) for molecular subtype classification by SPLS-DA using only radiomics features was 86.96% with permutation test p=7×10^-4. When multi-omics datasets including mRNA, microvascular density, and clinical parameters from each specimen were combined with radiomics features to refine the model of SPLS-DA, the best CCR was 95.65% with permutation test, p<10^-4; however, even in the case of generating the classification based on transcription features, which is the reference standard, there is roughly 10% classification ambiguity. Thus, this classification level (86.96-95.65%) of the proposed method represents the discriminating level that is consistent with reality.

CONCLUSION

Featured with high accuracy, an integrated multi-omics model of PET/MRI-based radiomics could be the first non-invasive investigation for disease risk stratification and guidance of treatment in patients with primary ccRCC.

Systematic Review: ClearCode 34 - A Validated Prognostic Signature in Clear Cell Renal Cell Carcinoma (ccRCC)

The standard of care of patients with localized clear cell RCC (ccRCC) is observation after nephrectomy. However, a third of these patients have local or distant recurrence. Along with basic clinical and pathologic variables like stage, necrosis and grade, robust molecular based prognostic markers are needed that could help better predict groups of patients who will most benefit from such adjuvant treatment approaches. ccA/ccB classification was developed to classify ccRCC patients into high and low risk based on gene expression patterns. ClearCode 34 is a genetic signature that was developed from the ccA/ccB classification to predict recurrence in localized ccRCC patients. This signature has been validated in several patient cohorts and is ready for future testing in a variety of clinical scenarios. This review will evaluate the molecular signature ClearCode34, discuss its role in predicting recurrence and consider the rational application of this example of a molecular biomarker in the management of ccRCC.

Clear Cell Type A and B Molecular Subtypes in Metastatic Clear Cell Renal Cell Carcinoma: Tumor Heterogeneity and Aggressiveness

BACKGROUND

Intratumor molecular heterogeneity has been reported for primary clear cell renal cell carcinoma (ccRCC) tumors; however, heterogeneity in metastatic ccRCC tumors has not been explored.

OBJECTIVE

To evaluate intra- and intertumor molecular heterogeneity in resected metastatic ccRCC tumors.

DESIGN, SETTING, AND PARTICIPANTS

We identified 111 patients who had tissue available from their primary tumor and at least one metastasis. ClearCode34 genes were analyzed for all tumors.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Primary and metastatic tumors were classified as clear cell type A (ccA) or B (ccB) subtypes. Logistic and Cox regression were used to evaluate associations with pathologic features and survival.

RESULTS AND LIMITATIONS

Intratumor heterogeneity of ccA/ccB subtypes was observed in 22% (95% confidence interval [CI] 3-60%) of metastatic tumors. Subtype differed across longitudinal metastatic tumors from the same patient in 23% (95% CI 10-42%) of patients and across patient-matched primary and metastatic tumors in 43% (95% CI 32-55%) of patients. Association of subtype with survival was validated in primary ccRCC tumors. The ccA/ccB subtype in metastatic tumors was significantly associated with metastatic tumor location, metastatic tumor grade, and presence of tumor necrosis. A limitation of this study is that we only analyzed patients who had both a nephrectomy and metastasectomy.

CONCLUSIONS

Approximately one quarter of metastatic tumors displayed intratumor heterogeneity; a similar rate of heterogeneity was observed across longitudinal metastatic tumors. Thus, for biomarker studies it is likely adequate to analyze a single sample per metastatic tumor provided that pathologic review is incorporated into the study design. Subtypes across patient-matched primary and metastatic tumors differed 43% of the time, suggesting that the primary tumor is not a good surrogate for the metastatic tumor.

PATIENT SUMMARY

Primary and secondary/metastatic cancers of the kidney differed in nearly one half of ccRCC patients. The pattern of this relationship may affect tumor growth and the most suitable treatment.

Renal cancer subtypes: Should we be lumping or splitting for therapeutic decision making?

The treatment of advanced renal cell carcinoma has posed a challenge for decades, in part because of common themes related to intrinsic resistance to cytotoxic chemotherapy and the obscure biology of these cancer types. Forward movement in the treatment of the renal cell carcinomas thus can be approached in 2 ways: by splitting the tumor types along histologic and molecular features, in the hopes of coupling highly precision-focused therapy on a subset of patients who have disease with the most potential for benefit; or by lumping the various biologies and histologies together, to include the rarer renal cell carcinoma types with the more common types. The former strategy satisfies the desire for customized precision in treatment delivery, whereas the latter strategy allows clinicians to offer a wider therapeutic menu in a set of diseases we are continuing to learn about on a physiologic and molecular level. Cancer 2017;123:200-209. © 2016 American Cancer Society.