Characterizing recurrent and lethal small renal masses in clear cell renal cell carcinoma using recurrent somatic mutations

Differences in mutations across tumour sizes in clear-cell renal cell carcinoma

OBJECTIVE

To assess the distribution of key mutations across tumour sizes in clear-cell renal cell carcinoma (ccRCC), and secondarily to examine the prognostic impact of aggressive mutations in smaller ccRCCs.

PATIENT AND METHODS

The distribution of mutations (VHL, PBRM1, SETD2, BAP1 and CDKN2A loss) across tumour sizes was assessed in 1039 ccRCCs treated with nephrectomy in cohorts obtained from the Tracking Cancer Evolution (TRACERx), The Cancer Genome Atlas (TCGA) and the Cancer Genomics of the Kidney (CAGEKID) projects. Logistic regression was used to model the presence of each mutation against size. In our secondary analysis, we assessed a subset of ccRCCs ≤7 cm for associations of key aggressive mutations (SETD2, BAP1, and CDKN2A loss) with metastasis, invasive disease and overall survival, while controlling for size. A subset of localised tumours ≤7 cm was also used to assess associations with recurrence after nephrectomy.

RESULTS

On logistic regression, each 1-cm increase in tumour size was associated with aggressive mutations, SETD2, BAP1, and CDKN2A loss, at odds ratios (ORs) of 1.09, 1.10 and 1.19 (P < 0.001), whereas no significant association was observed between tumour size and PBRM1 (OR 1.02; P = 0.23). VHL was mildly negatively associated with a 1-cm increase in size (OR 0.95; P = 0.01). Among tumours ≤7 cm, SETD2 and CDKN2A loss were associated with metastatic disease at ORs of 3.86 and 3.84 (P < 0.05) while controlling for tumour size. CDKN2A loss was associated with worse overall survival, with a hazard ratio (HR) of 2.19 (P = 0.03). Among localised tumours ≤7 cm, SETD2 was associated with worse recurrence-free survival (HR 2.00; P = 0.03).

CONCLUSION

Large and small ccRCCs are genomically different. Aggressive mutations, namely, SETD2, BAP1, and CDKN2A loss, are rarely observed in small ccRCCs and are observed more frequently in larger tumours. However, when present in tumours ≤7 cm, SETD2 mutations and CDKN2A loss were still independently associated with invasive disease, metastasis, worse survival, and recurrence after resection, after controlling for size.

The evolving management of small renal masses

Small renal masses (SRMs) are a heterogeneous group of tumours with varying metastatic potential. The increasing use and improving quality of abdominal imaging have led to increasingly early diagnosis of incidental SRMs that are asymptomatic and organ confined. Despite improvements in imaging and the growing use of renal mass biopsy, diagnosis of malignancy before treatment remains challenging. Management of SRMs has shifted away from radical nephrectomy, with active surveillance and nephron-sparing surgery taking over as the primary modalities of treatment. The optimal treatment strategy for SRMs continues to evolve as factors affecting short-term and long-term outcomes in this patient cohort are elucidated through studies from prospective data registries. Evidence from rapidly evolving research in biomarkers, imaging modalities, and machine learning shows promise in improving understanding of the biology and management of this patient cohort.

Exploring the Characteristics of Circulating Tumor DNA in Pt1a Clear Cell Renal Cell Carcinoma: A Pilot Study

Circulating tumor DNA (ctDNA) is a promising biomarker for clear cell renal cell carcinoma (ccRCC); however, its characteristics in small renal masses of ccRCC remain unclear. In this pilot study, we explored the characteristics of ctDNA in pT1a ccRCC. Plasma samples were collected preoperatively from 53 patients with pT1a ccRCC. The ctDNA of pT1a ccRCC was profiled using next-generation sequencing and compared with that of higher-stage ccRCC. The association of ctDNA in pT1a ccRCC with clinicopathological features was investigated. The positive relationship of mutations between ctDNA and matched tissues was evaluated. In pT1a ccRCC, the ctDNA detection rate, cell-free DNA concentration, and median variant allele frequency were 20.8%, 5.8 ng/mL, and 0.38%, respectively, which were significantly lower than those in metastatic ccRCC. The ctDNA gene proportions in pT1a samples differed from those in metastatic ccRCC samples. The relationships between ctDNA and tumor size, tumor grade, and patient age were not elucidated. The positive concordance between ctDNA and matched tissues was poor for pT1a ccRCC. Strategies are needed to increase sensitivity while eliminating noise caused by clonal hematopoiesis to increase the clinical utility of ctDNA analysis in small renal masses of ccRCC.

Correlating Immune Cell Infiltration Patterns with Recurrent Somatic Mutations in Advanced Clear Cell Renal Cell Carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) tumors have low frequencies of genetic alterations compared with other malignancies, but very high levels of immune cell infiltration and favorable response rates to immunotherapy. Currently, the interplay between specific ccRCC somatic mutations and immune infiltration pattern is unclear.

OBJECTIVE

To analyze the associations between common ccRCC somatic mutations and immune cell infiltration patterns within the tumor immune microenvironment (TIME).

DESIGN, SETTING, AND PARTICIPANTS

The study included tumor samples (24 primary and 24 metastatic) from 48 patients with stage IV ccRCC. Targeted sequencing was performed for well-characterized recurrent somatic mutations in ccRCC, with the analysis focusing on the six most common ones: VHL, BAP1, PBRM1, SETD2, TP53, and KDM5C. For each sample, multiplex immunofluorescence (IF) was performed in lymphoid and myeloid panels, for seven regions of interest in three zones (tumor core, stroma, and tumor-stroma interface). IF-derived cellular densities were compared across patients, stratified by their somatic mutation status, using a linear mixed-model analysis. External validation was pursued using RNA-seq enrichment scoring from three large external data sources.

RESULTS AND LIMITATIONS

Tumors with SETD2 mutations demonstrated significantly decreased levels of FOXP3+ T cells in the tumor core, stroma, and tumor-stroma interface. PBRM1 mutations were associated with decreased FOXP3+ T cells in the tumor core. Primary KDM5C mutations were associated with significantly increased CD206+ macrophage tumor infiltration in the tumor core. A computational method estimating immune cell types in the TIME using bulk RNA-seq data, xCell scoring, failed to validate associations from the IF analysis in large external data sets. A major limitation of the study is the relatively small patient population studied.

CONCLUSIONS

This study provides evidence that common somatic mutations in ccRCC, such as SETD2, PBRM1, and KDM5C, are associated with distinct immune infiltration patterns within the TIME.

PATIENT SUMMARY

In this study, we analyzed tumor samples from patients with metastatic kidney cancer to determine whether common genetic mutations that arise from the cancer cells are associated with the density of immune cells found within those tumors. We found several distinct immune cell patterns that were associated with specific genetic mutations. These findings provide insight into the interaction between cancer genetics and the immune system in kidney cancer.

The Next Paradigm Shift in the Management of Clear Cell Renal Cancer: Radiogenomics—Definition, Current Advances, and Future Directions

With improved molecular characterization of clear cell renal cancer and advances in texture analysis as well as machine learning, diagnostic radiology is primed to enter personalized medicine with radiogenomics: the identification of relationships between tumor image features and underlying genomic expression. By developing surrogate image biomarkers, clinicians can augment their ability to non-invasively characterize a tumor and predict clinically relevant outcomes (i.e., overall survival; metastasis-free survival; or complete/partial response to treatment). It is thus important for clinicians to have a basic understanding of this nascent field, which can be difficult due to the technical complexity of many of the studies. We conducted a review of the existing literature for radiogenomics in clear cell kidney cancer, including original full-text articles until September 2021. We provide a basic description of radiogenomics in diagnostic radiology; summarize existing literature on relationships between image features and gene expression patterns, either computationally or by radiologists; and propose future directions to facilitate integration of this field into the clinical setting.

BRCA1-Associated Protein 1 (BAP-1) as a Prognostic and Predictive Biomarker in Clear Cell Renal Cell Carcinoma: A Systematic Review

BACKGROUND: The gene that encodes BRCA1-associated protein 1 (BAP1) has been reported to be dysregulated in several human cancers such as uveal melanoma, malignant pleural mesothelioma, hepatocellular carcinoma, thymic epithelial tumors, and clear-cell renal cell carcinoma (ccRCC). The gene is located on the human chromosome 3p21.3, encoding a deubiquitinase and acts as a classic two-hit tumor suppressor gene. BAP1 predominantly resides in the nucleus, where it interacts with several chromatin-associated factors, as well as regulates calcium signaling in the cytoplasm. As newer therapies continue to evolve for the management of RCC, it is important to understand the role of BAP1 mutation as a prognostic and predictive biomarker. OBJECTIVE: We aimed to systematically evaluate the role of BAP1 mutations in patients with RCC in terms of its impact on prognosis and its role as a predictive biomarker. METHODS: Following PRISMA guidelines, we performed a systematic literature search using PubMed and Embase through March 2021. Titles and abstracts were screened to identify articles for full-text and then a descriptive review was performed. RESULTS: A total of 490 articles were initially identified. Ultimately 71 articles that met our inclusion criteria published between 2012–2021 were included in the analysis. Data were extracted and organized to reflect the role of BAP1 alterations as a marker of prognosis as well as a marker of response to treatments, such as mTOR inhibitors, VEGF tyrosine kinase inhibitors, and immune checkpoint inhibitors. CONCLUSIONS: Alterations in BAP1 appear to be uniformly associated with poor prognosis in patients with RCC. Knowledge gaps remain with regard to the predictive relevance of BAP1 alterations, especially in the context of immunotherapy. Prospective studies are required to more precisely ascertain the predictive value of BAP1 alterations in RCC.

Disease Progression in Older Patients With Renal Tumor Assigned to an Active Surveillance Protocol

BACKGROUND

Active surveillance (AS) is a validated option for the treatment of small renal masses (SMRs), especially in older patients. This study investigates the oncologic outcomes and competitive mortality of older patients prospectively assigned to AS.

METHODS

We conducted a monocentric study on patients ≥75 years treated between 2011 and 2016 for a SMR. Treatment modalities, biopsy data, survivals (overall, specific, cancer progression) and delayed interventions were analyzed.

RESULTS

Overall, 106 patients (median age 80.5 years) were included, of which 41 were managed by AS during a follow-up of 3.4 years [0-7.1]. Seven patients (17%) had a primary biopsy with 3 confirmed renal cell carcinomas. Fourteen patients (34.1%) presented with progression (29.2% local; 4.9% metastatic), 8 (19.5%) requiring delayed interventions (75% ablative therapy and 25% radical nephrectomy). Overall survival (OS) was 68.3% and cancer specific survival was 95.1% during the study period. Competitive mortality was higher (84.6%) than cancer specific mortality (15.4%), P = .001.

CONCLUSION

The growth rate of progression including 4.9% metastatic progression underlines the value of AS compared to simple watchful surveillance in the treatment of SMRs in older patients. Of note, the higher competitive mortality confirm that AS should be preferred to active intervention at the beginning of the management.

Somatic mutations as preoperative predictors of metastases in patients with localized clear cell renal cell carcinoma - An exploratory analysis

OBJECTIVE

Recurrent genomic alterations in clear cell renal cell carcinoma (ccRCC) have been associated with treatment outcomes; however, current preoperative predictive models do not include known genetic predictors. We aimed to explore the value of common somatic mutations in the preoperative prediction of metastatic disease among patients treated for localized ccRCC.

MATERIALS AND METHODS

After obtaining institutional review board approval, data of 254 patients with localized ccRCC treated between 2005 and 2015 who underwent genetic sequencing was collected. The mutation status of VHL, PBRM1, SETD2, BAP1 and KDM5C were evaluated in the nephrectomy tumor specimen, which served as a proxy for biopsy mutation status. The Raj et al. preoperative nomogram was used to predict the 12-year metastatic free probability (MFP). The study outcome was MFP; the relationship between MFP and mutation status was evaluated with Cox-regression models adjusting for the preoperative nomogram variables (age, gender, incidental presentation, lymphadenopathy, necrosis, and size).

RESULTS

The study cohort included 188 males (74%) and 66 females (26%) with a median age of 58 years. VHL mutations were present in 152/254 patients (60%), PBRM1 in 91/254 (36%), SETD2 in 32/254 (13%), BAP1 in 19/254 (8%), and KDM5C in 19/254 (8%). Median follow-up for survivors was 8.1 years. Estimated 12-year MFP was 70% (95% CI: 63%-75%). On univariable analysis SETD2 (HR: 3.30), BAP1 (HR: 2.44) and PBRM1 (HR: 1.78) were significantly associated with a higher risk of metastases. After adjusting for known preoperative predictors in the existing nomogram, SETD2 mutations remained associated with a higher rate of metastases after nephrectomy (HR: 2.09, 95% CI: 1.19-3.67, P = 0.011).

CONCLUSION

In the current exploratory analysis, SETD2 mutations were significant predictors of MFP among patients treated for localized ccRCC. Our findings support future studies evaluating genetic alterations in preoperative renal biopsy samples as potential predictors of treatment outcome.

Association between visceral adiposity and DDX11 as a predictor of aggressiveness of small clear-cell renal-cell carcinoma: a prospective clinical trial

Background

Visceral fat produces several hormones and cytokines associated with carcinogenesis and tumor progression. Herein, we investigated the association between visceral adiposity and target-gene mRNA expression in patients with localized small clear-cell renal-cell carcinoma (ccRCC).

Methods

We included 200 patients with localized clinical T1a stage ccRCC who had undergone nephrectomy from November 2018 to November 2020 in a prospective clinical trial (NCT03694912). Visceral, subcutaneous, and total adipose tissue in these patients was measured via preoperative computerized tomography of the mid-third lumbar vertebra region. We then examined the association between adiposity and the mRNA levels of PBRM1, BAP1, SETD2, KDM5C, FOXC2, CLIP4, AQP1, DDX11, BAIAP2L1, and TMEM38B in matched frozen tumor tissues and plasma samples.

Results

Upon the stratification of patients into quartiles according to their relative visceral adiposity, high visceral adiposity was found to be significantly associated with low ISUP grade (P = 0.004). Multivariate logistic regression analysis revealed a significant association between frozen tissue DDX11 expression and high visceral adiposity (OR 0.676, 95% CI 0.587–0.779, P < 0.001). Moreover, frozen tissue DDX11 expression was significantly associated with high ISUP grade (OR 1.556, 95% CI 1.223–1.981, P < 0.001). The frozen tissue mRNA expression of DDX11 was identified as a biomarker for visceral adiposity and cancer aggressiveness.

Conclusions

The results obtained herein will aid in inferring the aggressiveness of small ccRCCs, represented by ISUP nuclear grade, in clinical practice. Our findings indicated that DDX11 and visceral fat play active roles in small ccRCC. These roles should be examined in future studies for the possible use of DDX11 and visceral fat as prognostic biomarkers in the treatment of patients with ccRCC.

Trial registration

ClinicalTrials.gov, NCT03694912, Registered 3 October 2018.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40170-021-00251-y.

Small Renal Mass Surveillance: Histology-specific Growth Rates in a Biopsy-characterized Cohort

BACKGROUND

Most reports of active surveillance (AS) of small renal masses (SRMs) lack biopsy confirmation, and therefore include benign tumors and different subtypes of renal cell carcinoma (RCC).

OBJECTIVE

We compared the growth rates and progression of different histologic subtypes of RCC SRMs (SRM^RCC) in the largest cohort of patients with biopsy-characterized SRMs on AS.

DESIGN, SETTING, AND PARTICIPANTS

Data from patients in a multicenter Canadian trial and a Princess Margaret cohort were combined to include 136 biopsy-proven SRM^RCC lesions managed by AS, with treatment deferred until progression or patient/surgeon decision.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Growth curves were estimated from serial tumor size measures. Tumor progression was defined by sustained size ≥4 cm or volume doubling within 1 yr.

RESULTS AND LIMITATIONS

Median follow-up for patients who remained on AS was 5.8 yr (interquartile range 3.4-7.5 yr). Clear cell RCC SRMs (SRM^ccRCC) grew faster than papillary type 1 SRMs (0.25 and 0.02 cm/yr on average, respectively, p =  0.0003). Overall, 60 SRM^RCC lesions progressed: 49 (82%) by rapid growth (volume doubling), seven (12%) increasing to ≥4 cm, and four (6.7%) by both criteria. Six patients developed metastases, and all were of clear cell RCC histology. Limitations include the use of different imaging modalities and a lack of central imaging review.

CONCLUSIONS

Tumor growth varies between histologic subtypes of SRM^RCC and among SRM^ccRCC, which likely reflects individual host and tumor biology. Without validated biomarkers that predict this variation, initial follow-up of histologically characterized SRMs can inform personalized treatment for patients on AS.

PATIENT SUMMARY

Many small kidney cancers are suitable for surveillance and can be monitored over time for change. We demonstrate that different types of kidney cancers grow at different rates and are at different risks of progression. These results may guide better personalized treatment.

MicroRNA profile in stage I clear cell renal cell carcinoma predicts progression to metastatic disease

OBJECTIVE

This study sought to identify microRNA (miRNA) profiles of small, pathologically confirmed stage 1 clear cell renal cell carcinoma (ccRCC) tumors that are associated with progression to metachronous metastatic disease.

MATERIALS AND METHODS

Fifty-five pathologic stage 1 ccRCC tumors ≤5cm, from 2 institutions, were examined in a miRNA screening, followed by a validation study. For the screening phase 752 miRNA were evaluated on each sample to identify those with differential expression between tumors that subsequently did (n = 10) or did not (n = 10) progress to metastatic disease. For the validation, 35 additional samples (20 nonprogressors and 15 with distant progression) were utilized to investigate 20 miRNA to determine if a miRNA panel could differentiate aggressive tumors: associations of miRNA expression with cancer specific survival was also investigated.

RESULTS

In the screening analysis, 35 miRNA were differentially expressed (P < 0.05, FDR < 0.1) between the groups. In the validation, 11 miRNA were confirmed to have differential expression. The miRNA -10a-5p, -23b-3p, and -26a-5p differentiated nonprogressive and distant progressive disease with a sensitivity of 73.3% and a specificity of 85% (AUC=0.893). In addition, levels of miR-30a-3p and -145-5p were identified as independent prognostic factors of cancer specific survival.

CONCLUSIONS

This investigation identified miRNA biomarkers that may differentiate between non-progressive ccRCC tumors and those that progress to metastatic disease in this group of stage I tumors. The miRNA profiles determined in this study have the potential to identify patients with small renal masses who are likely to have progressive ccRCC. Such information may be valuable to incorporate into predictive models.

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

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.

Integrative Radiogenomics Approach for Risk Assessment of Post-Operative Metastasis in Pathological T1 Renal Cell Carcinoma: A Pilot Retrospective Cohort Study

Despite the increasing incidence of pathological stage T1 renal cell carcinoma (pT1 RCC), postoperative distant metastases develop in many surgically treated patients, causing death in certain cases. Therefore, this study aimed to create a radiomics model using imaging features from multiphase computed tomography (CT) to more accurately predict the postoperative metastasis of pT1 RCC and further investigate the possible link between radiomics parameters and gene expression profiles generated by whole transcriptome sequencing (WTS). Four radiomic features, including the minimum value of a histogram feature from inner regions of interest (ROIs) (INNER_Min_hist), the histogram of the energy feature from outer ROIs (OUTER_Energy_Hist), the maximum probability of gray-level co-occurrence matrix (GLCM) feature from inner ROIs (INNER_MaxProb_GLCM), and the ratio of voxels under 80 Hounsfield units (Hus) in the nephrographic phase of postcontrast CT (Under80HURatio), were detected to predict the postsurgical metastasis of patients with pathological stage T1 RCC, and the clinical outcomes of patients could be successfully stratified based on their radiomic risk scores. Furthermore, we identified heterogenous-trait-associated gene signatures correlated with these four radiomic features, which captured clinically relevant molecular pathways, tumor immune microenvironment, and potential treatment strategies. Our results of accurate surrogates using radiogenomics could lead to additional benefit from adjuvant therapy or postsurgical metastases in pT1 RCC.

Gene Expression Analysis of Aggressive Clinical T1 Stage Clear Cell Renal Cell Carcinoma for Identifying Potential Diagnostic and Prognostic Biomarkers

The molecular characteristics of early-stage clear cell renal cell carcinomas (ccRCCs) measuring ≤7 cm associated with poor clinical outcomes remain poorly understood. Here, we sought to validate genes associated with ccRCC progression and identify candidate genes to predict ccRCC aggressiveness. From among 1069 nephrectomies performed on patients, RNA sequencing was performed for 12 ccRCC patients with aggressive characteristics and matched pairs of 12 ccRCC patients without aggressive characteristics. Using a prospective cohort (ClinicalTrials.gov Identifier: NCT03694912), the expression levels of nine genes (PBRM1, BAP1, SETD2, KDM5C, FOXC2, CLIP4, AQP1, DDX11, and BAIAP2L1) were measured by reverse-transcription polymerase chain reaction from frozen tissues, and their relation to Fuhrman grade was investigated in 70 patients with small ccRCC (≤4 cm). In total, 251 genes were differentially expressed and presented fold changes with p-values < 0.05; moreover, 10 genes with the greatest upregulation or downregulation in aggressive ccRCC remained significant even after adjustment. We validated previously identified genes that were associated with ccRCC progression and identified new candidate genes that reflected the aggressiveness of ccRCC. Our study provides new insight into the tumor biology of ccRCC and will help stratify patients with early-stage ccRCC by molecular subtyping.

Combining molecular and imaging metrics in cancer: radiogenomics

Background

Radiogenomics is the extension of radiomics through the combination of genetic and radiomic data. Because genetic testing remains expensive, invasive, and time-consuming, and thus unavailable for all patients, radiogenomics may play an important role in providing accurate imaging surrogates which are correlated with genetic expression, thereby serving as a substitute for genetic testing.

Main body

In this article, we define the meaning of radiogenomics and the difference between radiomics and radiogenomics. We provide an up-to-date review of the radiomics and radiogenomics literature in oncology, focusing on breast, brain, gynecological, liver, kidney, prostate and lung malignancies. We also discuss the current challenges to radiogenomics analysis.

Conclusion

Radiomics and radiogenomics are promising to increase precision in diagnosis, assessment of prognosis, and prediction of treatment response, providing valuable information for patient care throughout the course of the disease, given that this information is easily obtainable with imaging. Larger prospective studies and standardization will be needed to define relevant imaging biomarkers before they can be implemented into the clinical workflow.

Expression of PBRM1 as a prognostic predictor in metastatic renal cell carcinoma patients treated with tyrosine kinase inhibitor

OBJECTIVE

PBRM1, located on 3p21, functions as a tumor suppressor and somatic mutation of PBRM1 is frequent in clear cell renal cell carcinoma (ccRCC). This study aims to determine the influence of PBRM1 expression on the prognosis of patients with mRCC receiving tyrosine kinase inhibitor (TKI) treatment.

METHODS

We identified 116 mRCC patients who were administered sunitinib or sorafenib as first-line therapy, between January 2006 and December 2016 at our institution. PBRM1 expression was assessed by immunohistochemistry. The Kaplan-Meier method was used to estimate the progression-free survival (PFS) and overall survival (OS), log-rank test was used to compare the survival outcomes between patients with low and high PBRM1 expression levels, and the Cox proportional hazard regression model was used to estimate the prognostic value. Prognostic accuracy was determined using Harrell concordance index, and nomograms were built to evaluate the prognosis of mRCC.

RESULTS

Patients with low PBRM1 expression had significantly shorter median PFS (9 vs 26 months, P < 0.001) and OS (21 vs 44 months, P < 0.001) than those with high expression. Multivariate analysis showed that PBRM1 expression was an independent predictor of PFS (HR 1.975, P = 0.013) and OS (HR 2.282, P = 0.007). The model built by the addition of PBRM1 improved the C-index of PFS and OS to 0.72 and 0.82, respectively.

CONCLUSIONS

The expression of PBRM1 could be a significant prognostic factor for mRCC patients treated with targeted therapy, and it increases the prognostic accuracy of the established prognostic model.

Radiogenomics in renal cell carcinoma

Radiogenomics, a field of radiology investigating the association between the imaging features of a disease and its gene expression pattern, has expanded considerably in the last few years. Recent advances in whole-genome sequencing of clear cell renal cell carcinoma (ccRCC) and the identification of mutations with prognostic significance have led to increased interest in the relationship between imaging and genomic data. ccRCC is particularly suitable for radiogenomic analysis as the relative paucity of mutated genes allows for more straightforward genomic-imaging associations. The ultimate aim of radiogenomics of ccRCC is to retrieve additional data for accurate diagnosis, prognostic stratification, and optimization of therapy. In this review article, we will present the state-of-the-art of radiogenomics of ccRCC, and after briefly reviewing updates in genomics, we will discuss imaging-genomic associations for diagnosis and staging, prognosis, and for assessment of optimal therapy in ccRCC.

Harnessing the Genomic Landscape of the Small Renal Mass to Guide Clinical Management

CONTEXT

Small renal masses (SRMs; tumors <4 cm) encompass a diagnostic and therapeutic challenge. Genomic profiling has the potential to improve risk stratification and personalize treatment selection.

OBJECTIVE

Herein, we review the evidence regarding the utility, challenges, and potential implications of genomic profiling in the management of SRMs.

EVIDENCE ACQUISITION

Pertinent publications available on PubMed database pertaining to kidney cancer, tumor size, genomics, and clinical management were reviewed.

EVIDENCE SYNTHESIS

Compared with larger tumors, SRMs range from benign to lethal, necessitating strategies for improved treatment selection. Recent advances in the molecular characterization of renal cell carcinoma have improved our understanding of the disease; however, utility of these tools for the management of SRMs is less clear. While intratumoral heterogeneity (ITH) reduces the accuracy and reliability of sequencing, relative genomic uniformity of SRMs somewhat lessens the impact of ITH. Therefore, renal mass biopsy of SRMs represents an appealing opportunity to evaluate how incorporation of molecular profiles may improve management strategies.

CONCLUSIONS

Ongoing research into the genomic landscape of SRMs has advanced our understanding of the spectrum of disease aggressiveness and may hold promise in matching disease biology to treatment intensity.

PATIENT SUMMARY

Small renal masses are a clinical challenge, as they range from benign to lethal. Genomic profiling may eventually improve treatment selection, but more research is needed.

Identification of gene expression levels in primary melanoma associated with clinically meaningful characteristics

Factors influencing melanoma survival include sex, age, clinical stage, lymph node involvement, as well as Breslow thickness, presence of tumor-infiltrating lymphocytes based on histological analysis of primary melanoma, mitotic rate, and ulceration. Identification of genes whose expression in primary tumors is associated with these key tumor/patient characteristics can shed light on molecular mechanisms of melanoma survival. Here, we show results from a gene expression analysis of formalin-fixed paraffin-embedded primary melanomas with extensive clinical annotation. The Cancer Genome Atlas data on primary melanomas were used for validation of nominally significant associations. We identified five genes that were significantly associated with the presence of tumor-infiltrating lymphocytes in the joint analysis after adjustment for multiple testing: IL1R2, PPL, PLA2G3, RASAL1, and SGK2. We also identified two genes significantly associated with melanoma metastasis to the regional lymph nodes (PIK3CG and IL2RA), and two genes significantly associated with sex (KDM5C and KDM6A). We found that LEF1 was significantly associated with Breslow thickness and CCNA2 and UBE2T with mitosis. RAD50 was the gene most significantly associated with survival, with a higher level of expression associated with worse survival.

Risk Prediction Tool for Aggressive Tumors in Clinical T1 Stage Clear Cell Renal Cell Carcinoma Using Molecular Biomarkers

Some early-stage clear cell renal cell carcinomas (ccRCCs) of ≤7 cm are associated with a poor clinical outcome. In this study, we investigated molecular biomarkers associated with aggressive clinical T1 stage ccRCCs of ≤7 cm, which were used to develop a risk prediction tool toward guiding the decision of treatment. Among 1069 nephrectomies performed for ccRCC of ≤7 cm conducted between January 2008 and December 2014, 177 cases with available formalin-fixed paraffin-embedded tissue were evaluated. An aggressive tumor was defined as a tumor exhibiting synchronous metastasis, recurrence, or leading to cancer-specific death. Expression levels of six genes (FOXC2, CLIP4, PBRM1, BAP1, SETD2, and KDM5C) were measured by reverse-transcription polymerase chain reaction (qRT-PCR) and their relation to clinical outcomes was investigated. Immunohistochemistry was performed to validate the expression profiles of selected genes significantly associated with clinical outcomes in multivariate analysis. Using these genes, we developed a prediction model of aggressive ccRCC based on logistic regression and deep-learning methods. FOXC2, PBRM1, and BAP1 expression levels were significantly lower in aggressive ccRCC than non-aggressive ccRCC both in univariate and multivariate analysis. The immunohistochemistry result demonstrated the significant downregulation of FOXC2, PBRM1, and BAP1 expression in aggressive ccRCC. Adding immunohistochemical staining results to qRT-PCR, the aggressive ccRCC prediction models had the area under the curve (AUC) of 0.760 and 0.796 and accuracy of 0.759 and 0.852 using the logistic regression method and deep-learning method, respectively. Use of these biomarkers and the developed prediction model can help stratify patients with clinical T1 stage ccRCC.

Current Management of Small Renal Masses, Including Patient Selection, Renal Tumor Biopsy, Active Surveillance, and Thermal Ablation

Renal cancer represents 2% to 3% of all cancers, and its incidence is rising. The increased use of ultrasonography and cross-sectional imaging has resulted in the clinical dilemma of incidentally detected small renal masses (SRMs). SRMs represent a heterogeneous group of tumors that span the full spectrum of metastatic potential, including benign, indolent, and more aggressive tumors. Currently, no composite model or biomarker exists that accurately predicts the diagnosis of kidney cancer before treatment selection, and the use of renal mass biopsy remains controversial. The management of SRMs has changed dramatically over the last two decades as our understanding of tumor biology and competing risks of mortality in this population has improved. In this review, we critically assess published consensus guidelines and recent literature on the diagnosis and management of SRMs, with a focus on patient treatment selection and use of renal mass biopsy, active surveillance, and thermal ablation. Finally, we highlight important opportunities for leveraging recent research discoveries to identify patients with SRMs at high risk for renal cell carcinoma-related mortality and minimize overtreatment and patient morbidity.

[Limits of surgery in uro-oncology]

The limits of cancer surgery in uro-oncology are characterized by a carefully weighed risk of surgical feasibility and oncological necessity. The limits of uro-oncological cancer surgery do not represent fixed dogmas but ideally these more or less cognitive boundaries move based on new scientific findings, improved imaging modalities, optimized surgical techniques and perioperative care. The limits of cancer surgery are defined by patient-specific parameters, the biological aggressiveness of the tumor itself, the skills and expertise of the surgeon, and adequate perioperative care of the patient. Dependent on the origin of the cancers of the upper and lower urogenital tract, the specific particularities of each individual cancer in terms of prognosis need to be known, taking into consideration the newest molecular insights and modern multimodality treatment regimes. Only the consideration of the above mentioned basics will allow the best decision to be made with the patient concerning the optimal individual treatment. The current article highlights general parameters of the patient, tumor and surgeon which might define the limits of cancer surgery in uro-oncology. In addition, specific clinical scenarios are discussed with regard to surgery limits in cancer of the kidney, the prostate and the testis.

Genomic classifications of renal cell carcinoma: a critical step towards the future application of personalized kidney cancer care with pan-omics precision

Over the past 20 years, classifications of kidney cancer have undergone major revisions based on morphological refinements and molecular characterizations. The 2016 WHO classification of renal tumors recognizes more than ten different renal cell carcinoma (RCC) subtypes. Furthermore, the marked inter- and intra-tumor heterogeneity of RCC is now well appreciated. Nevertheless, contemporary multi-omics studies of RCC, encompassing genomics, transcriptomics, proteomics, and metabolomics, not only highlight apparent diversity but also showcase and underline commonality. Here, we wish to provide an integrated perspective concerning the future 'functional' classification of renal cancer by bridging gaps among morphology, biology, multi-omics, and therapeutics. This review focuses on recent progress and elaborates the potential value of contemporary pan-omics approaches with a special emphasis on cancer genomics unveiled through next-generation sequencing technology, and how an integrated multi-omics approach might impact precision-based personalized kidney cancer care in the near future. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.