The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma

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.

Emerging genomic biomarkers for improving kidney, prostate, and bladder cancer health disparities outcomes

BACKGROUND

Recent advances in genomic and genetic technologies have facilitated better health outcomes for urologic cancer patients. Genomic and genetic heterogeneity may contribute to differences in tumor biology and urologic cancer burden across various populations.

OBJECTIVE

To examine how emerging genomic and genetic biomarkers, self-reported race, and ancestry-informative markers are associated with kidney, prostate, and bladder cancer outcomes.

RESULTS

Genomic and genetic alterations found in African American kidney cancer patients included distinct somatic mutations, somatic copy number alterations, chromosomal instability, germ-line risk alleles, and germ-line genetic variants. These changes correlated with improved risk prediction, prognosis, and survival; and a predicted decrease in response to targeted therapies. SNP risk alleles and ancestry-informative markers were associated with improved risk prediction in prostate cancer patients of both African and European descent. AKT activation suggest differential response to AKT-targeted therapies in African American, Asian American, and Tunisian bladder cancer patients. Both self-reported race and genetic ancestry predicted urologic cancer risk prediction.

CONCLUSION

Precision medicine approaches that integrate population-specific genomic and genetic information with other known urologic cancer-specific characteristics can improve outcomes and be leveraged to reduce cancer health disparities. Further investigations are necessary to identify novel genomic biomarkers with clinical utility.

Resistance to Systemic Agents in Renal Cell Carcinoma Predict and Overcome Genomic Strategies Adopted by Tumor

The development of new systemic agents has led us into a "golden era" of management of metastatic renal cell carcinoma (RCC). Certainly, the approval of immune-checkpoint inhibitors and the combination of these with targeted compounds has irreversibly changed clinical scenarios. A deeper knowledge of the molecular mechanisms that correlate with tumor development and progression has made this revolution possible. In this amazing era, novel challenges are awaiting us in the clinical management of metastatic RCC. Of these, the development of reliable criteria which are able to predict tumor response to treatment or primary and acquired resistance to systemic treatments still remain an unmet clinical need. Thanks to the availability of data provided by studies evaluating genomic assessments of the disease, this goal may no longer be out of reach. In this review, we summarize current knowledge about genomic alterations related to primary and secondary resistance to target therapy and immune-checkpoint inhibitors in RCC.

Targeting the Tumor Microenvironment in Renal Cell Cancer Biology and Therapy

Renal cell cancer (RCC) is a highly vascularized and immunogenic tumor type. The inhibition of vessel formation by anti-angiogenic therapies, as well as the stimulation of the immune system by immunotherapy has revolutionized the therapeutic landscape of RCC in recent years. Nevertheless, both therapies are associated with therapy resistance due to a highly dynamic, adaptive and heterogeneous tumor microenvironment (TME). The aim of this short review article is to provide an overview of the components of the RCC TME as well as to discuss their contribution to disease progression. In addition, we report on preclinical and clinical findings and how the different TME components can be modulated to impede treatment progression as well as to overcome therapy resistance to anti-angiogenic or immunomodulating therapy concepts. Furthermore, we discuss the predictive and prognostic role of the TME in RCC therapy. We also report on the concept of combinational targeting of anti-angiogenic therapies and immune checkpoint inhibitor therapy, also including the latest results of clinical studies discussed at recent oncological meetings. Finally, promising new therapeutic targets within the TME are mentioned.

Analysis of Expression Patterns of MicroRNAs That Are Closely Associated With Renal Carcinogenesis

Background: MicroRNAs (miRNA) are frequently dysregulated in clear cell renal cell carcinoma (ccRCC). Objective: This study aimed to elucidate the role of miRNA expression patterns in renal carcinogenesis and to identify the specific miRNAs that exhibit expression patterns closely associated with patient outcomes. Methods: We examined the expression patterns of selected miRNAs, including miRNA-155-5p, miRNA-122-5p, miRNA-21-5p, miRNA-185-5p, miRNA-106a-5p, miRNA-106b-3p, miRNA-34b-3p, miRNA-210-3p, miRNA-141-3p, miRNA-200c-3p, miRNA-135a-5p, miRNA-30a-5p, miRNA-218-5p, miRNA-429, miRNA-200a-3p and miRNA-200b-3p, in 96 samples of ccRCCs using the TaqMan real-time PCR method. In addition, cluster analysis was performed to stratify expression patterns of multiple miRNAs. Results: In the present study, three distinct subgroups could be clearly stratified in ccRCCs. Subgroup 1 was characterized by upregulation of miRNA-155-5p, miRNA-122-5p, miRNA-21-5p, miRNA-185-5p, miRNA-106a-5p, miRNA-106b-3p, miRNA-34b-3p and miRNA-210-3p. Subgroup 2 was closely associated with downregulation of miRNA-141-3p, miRNA200c-3p, miRNA-30a-5p, miRNA-218-5p, miRNA-429, miRNA-200a-3p and miRNA-200b-3p. Moreover, significant lower expression of miRNA-135a-5p was a distinctive feature of subgroup 3, which was correlated with metachronous metastasis. Among the individual markers in subgroup 3, miRNA-135a-5p was retained in multivariate analysis. The cutoff value of miRNA-135a-5p expression to identify the association of an altered level of miRNA-135a-5p with metachronous metastasis in ccRCCs was determined and showed excellent specificity. Conclusion: We suggest that the expression pattern of the chosen miRNAs is useful to identify renal carcinogenesis and to help identify the association of such expression patterns with metachronous metastasis in ccRCCs. In addition, miRNA-135a-5p was an excellent marker for prediction of metachronous metastasis.

Cabozantinib in advanced non-clear-cell renal cell carcinoma: a multicentre, retrospective, cohort study

BACKGROUND

Cabozantinib is approved for patients with metastatic renal cell carcinoma on the basis of studies done in clear-cell histology. The activity of cabozantinib in patients with non-clear-cell renal cell carcinoma is poorly characterised. We sought to analyse the antitumour activity and toxicity of cabozantinib in advanced non-clear-cell renal cell carcinoma.

METHODS

We did a multicentre, international, retrospective cohort study of patients with metastatic non-clear-cell renal cell carcinoma treated with oral cabozantinib during any treatment line at 22 centres: 21 in the USA and one in Belgium. Eligibility required patients with histologically confirmed non-clear-cell renal cell carcinoma who received cabozantinib for metastatic disease during any treatment line roughly between 2015 and 2018. Mixed tumours with a clear-cell histology component were excluded. No other restrictive inclusion criteria were applied. Data were obtained from retrospective chart review by investigators at each institution. Demographic, surgical, pathological, and systemic therapy data were captured with uniform database templates to ensure consistent data collection. The main objectives were to estimate the proportion of patients who achieved an objective response, time to treatment failure, and overall survival after treatment.

FINDINGS

Of 112 identified patients with non-clear-cell renal cell carcinoma treated at the participating centres, 66 (59%) had papillary histology, 17 (15%) had Xp11.2 translocation histology, 15 (13%) had unclassified histology, ten (9%) had chromophobe histology, and four (4%) had collecting duct histology. The proportion of patients who achieved an objective response across all histologies was 30 (27%, 95% CI 19-36) of 112 patients. At a median follow-up of 11 months (IQR 6-18), median time to treatment failure was 6·7 months (95% CI 5·5-8·6), median progression-free survival was 7·0 months (5·7-9·0), and median overall survival was 12·0 months (9·2-17·0). The most common adverse events of any grade were fatigue (58 [52%]), and diarrhoea (38 [34%]). The most common grade 3 events were skin toxicity (rash and palmar-plantar erythrodysesthesia; five [4%]) and hypertension (four [4%]). No treatment-related deaths were observed. Across 54 patients with available next-generation sequencing data, the most frequently altered somatic genes were CDKN2A (12 [22%]) and MET (11 [20%]) with responses seen irrespective of mutational status.

INTERPRETATION

While we await results from prospective studies, this real-world study provides evidence supporting the antitumour activity and safety of cabozantinib across non-clear-cell renal cell carcinomas. Continued support of international collaborations and prospective ongoing studies targeting non-clear-cell renal cell carcinoma subtypes and specific molecular alterations are warranted to improve outcomes across these rare diseases with few evidence-based treatment options.

FUNDING

None.

Diagnostic and prognostic value of CEP55 in clear cell renal cell carcinoma as determined by bioinformatics analysis

Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignant adult kidney tumor. Tumor recurrence and metastasis is the primary cause of cancer-associated mortality in patients with ccRCC. Therefore, identification of efficient diagnostic and prognostic molecular markers may improve survival times. The GSE46699, GSE36895, GSE53000 and GSE53757 gene datasets were downloaded from the Gene Expression Omnibus database and contained 196 ccRCC samples and 164 adjacent normal kidney samples. Bioinformatics analysis was used to integrate the four microarray datasets to identify and analyze differentially expressed genes. Functional analysis revealed that there were 12 genes associated with cancer, based on the tumor-associated gene database. Erb-B2 receptor tyrosine kinase 4, centrosomal protein 55 (CEP55) and vascular endothelial growth factor A are oncogenes, all of which were associated with tumor stage, whereas only CEP55 was significantly associated with survival time as determined by Gene Expression Profiling Interactive Analysis. The mRNA expression levels of CEP55 in ccRCC samples were significantly higher than those observed in adjacent normal kidney tissues based on The Cancer Genome Atlas data and reverse transcription-polymerase chain reaction results. The receiver operating characteristic curve analysis revealed that CEP55 may be considered a diagnostic biomarker for ccRCC with an area under the curve of >0.85 in the training and validation sets. High CEP55 expression was strongly associated with sex, histological grade, stage, T classification, N classification and M classification. Univariate and multivariate Cox proportional hazards analyses demonstrated that CEP55 expression was an independent risk factor for poor prognosis. In addition, gene set enrichment analysis indicated that high CEP55 expression was associated with immunization, cell adhesion, inflammation, the Janus kinase/signal transducer and activator of transcription signaling pathway and cell proliferation. In conclusion, CEP55 was increased in ccRCC samples, and may be considered a potential diagnostic and prognostic biomarker for ccRCC.

Identification of therapeutic targets in chordoma through comprehensive genomic and transcriptomic analyses

Chordoma is a rare, orphan cancer arising from embryonal precursors of bone. Surgery and radiotherapy (RT) provide excellent local control, often at the price of significant morbidity because of the structures involved and the need for relatively high doses of RT; however, recurrence remains high. Although our understanding of the genetic changes that occur in chordoma is evolving rapidly, this knowledge has yet to translate into treatments. We performed comprehensive DNA (paired tumor/normal whole-exome and shallow whole-genome) and RNA (tumor whole-transcriptome) next-generation sequencing analyses of archival sacral and clivus chordoma specimens. Incorporation of transcriptomic data enabled the identification of gene overexpression and expressed DNA alterations, thus providing additional support for potential therapeutic targets. In three patients, we identified alterations that may be amenable to off-label FDA-approved treatments for other tumor types. These alterations include FGFR1 overexpression (ponatinib, pazopanib) and copy-number duplication of CDK4 (palbociclib) and ERBB3 (gefitinib). In a third patient, germline DNA demonstrated predicted pathogenic changes in CHEK2 and ATM, which may have predisposed the patient to developing chordoma at a young age and may also be associated with potential sensitivity to PARP inhibitors because of homologous recombination repair deficiency. Last, in the fourth patient, a missense mutation in IGF1R was identified, suggesting potential activity for investigational anti-IGF1R strategies. Our findings demonstrate that chordoma patients present with aberrations in overlapping pathways. These results provide support for targeting the IGF1R/FGFR/EGFR and CDK4/6 pathways as treatment strategies for chordoma patients. This study underscores the value of comprehensive genomic and transcriptomic analysis in the development of rational, individualized treatment plans for chordoma.

Integrated multi-omics characterization reveals a distinctive metabolic signature and the role of NDUFA4L2 in promoting angiogenesis, chemoresistance, and mitochondrial dysfunction in clear cell renal cell carcinoma

An altered metabolism is involved in the development of clear cell - renal cell carcinoma (ccRCC), and in this tumor many altered genes play a fundamental role in controlling cell metabolic activities. We delineated a large-scale metabolomic profile of human ccRCC, and integrated it with transcriptomic data to connect the variations in cancer metabolism with gene expression changes. Moreover, to better analyze the specific contribution of metabolic gene alterations potentially associated with tumorigenesis and tumor progression, we evaluated the transcription profile of primary renal tumor cells. Untargeted metabolomic analysis revealed a signature of an increased glucose uptake and utilization in ccRCC. In addition, metabolites related to pentose phosphate pathway were also altered in the tumor samples in association with changes in Krebs cycle intermediates and related metabolites. We identified NADH dehydrogenase (ubiquinone) 1 alpha subcomplex 4-like 2 (NDUFA4L2) as the most highly expressed gene in renal cancer cells and evaluated its role in sustaining angiogenesis, chemoresistance, and mitochondrial dysfunction. Finally, we showed that silencing of NDUFA4L2 affects cell viability, increases mitochondrial mass, and induces ROS generation in hypoxia.

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.

Onco-Multi-OMICS Approach: A New Frontier in Cancer Research

The acquisition of cancer hallmarks requires molecular alterations at multiple levels including genome, epigenome, transcriptome, proteome, and metabolome. In the past decade, numerous attempts have been made to untangle the molecular mechanisms of carcinogenesis involving single OMICS approaches such as scanning the genome for cancer-specific mutations and identifying altered epigenetic-landscapes within cancer cells or by exploring the differential expression of mRNA and protein through transcriptomics and proteomics techniques, respectively. While these single-level OMICS approaches have contributed towards the identification of cancer-specific mutations, epigenetic alterations, and molecular subtyping of tumors based on gene/protein-expression, they lack the resolving-power to establish the casual relationship between molecular signatures and the phenotypic manifestation of cancer hallmarks. In contrast, the multi-OMICS approaches involving the interrogation of the cancer cells/tissues in multiple dimensions have the potential to uncover the intricate molecular mechanism underlying different phenotypic manifestations of cancer hallmarks such as metastasis and angiogenesis. Moreover, multi-OMICS approaches can be used to dissect the cellular response to chemo- or immunotherapy as well as discover molecular candidates with diagnostic/prognostic value. In this review, we focused on the applications of different multi-OMICS approaches in the field of cancer research and discussed how these approaches are shaping the field of personalized oncomedicine. We have highlighted pioneering studies from “The Cancer Genome Atlas (TCGA)” consortium encompassing integrated OMICS analysis of over 11,000 tumors from 33 most prevalent forms of cancer. Accumulation of huge cancer-specific multi-OMICS data in repositories like TCGA provides a unique opportunity for the systems biology approach to tackle the complexity of cancer cells through the unification of experimental data and computational/mathematical models. In future, systems biology based approach is likely to predict the phenotypic changes of cancer cells upon chemo-/immunotherapy treatment. This review is sought to encourage investigators to bring these different approaches together for interrogating cancer at molecular, cellular, and systems levels.

Loss of Nuclear BAP1 Expression Is Associated with High WHO/ISUP Grade in Clear Cell Renal Cell Carcinoma

Background

BRCA1-associated protein 1 (BAP1) mutations are frequently reported in clear cell renal cell carcinoma (ccRCC); however, very few studies have evaluated the role of these mutations in other renal cell carcinoma (RCC) subtypes. Therefore, we analyzed BAP1 protein expression using immunohistochemistry in several RCC subtypes and assessed its relationship with clinicopathological characteristics of patients.

Methods

BAP1 expression was immunohistochemically evaluated in tissue microarray blocks constructed from 371 samples of RCC collected from two medical institutions. BAP1 expression was evaluated based on the extent of nuclear staining in tumor cells, and no expression or expression in < 10% of tumor cells was defined as negative.

Results

Loss of BAP1 expression was observed in ccRCC (56/300, 18.7%), chromophobe RCC (6/26, 23.1%), and clear cell papillary RCC (1/4, 25%), while we failed to detect BAP1 expression loss in papillary RCC, acquired cystic disease-associated RCC, or collecting duct carcinoma. In ccRCC, loss of BAP1 expression was significantly associated with high World Health Organization (WHO)/International Society of Urological Pathology (ISUP) grade (p = .002); however, no significant correlation was observed between loss of BAP1 expression and survival in ccRCC. Loss of BAP1 expression showed no association with prognostic factors in chromophobe RCC.

Conclusions

Loss of BAP1 nuclear expression was observed in both ccRCC and chromophobe RCC. In addition, BAP1 expression loss was associated with poor prognostic factors such as high WHO/ISUP grade in ccRCC.

Overexpression of low density lipoprotein receptor-related protein 1 (LRP1) is associated with worsened prognosis and decreased cancer immunity in clear-cell renal cell carcinoma

AIM

Clear-cell renal cell carcinoma (ccRCC) is characterized with underlying genetic disorders and the role of low density lipoprotein receptor-related protein 1 (LRP1) in ccRCC is unknown.

METHOD

An in silico exploratory analysis using multiple public genetic datasets was used to establish association between LRP1 expression and clinicopathological parameters. Associations of interest were validated using 155 ccRCC samples using immunohistochemistry.

RESULTS

LRP1 was overexpressed in tumor compared with normal kidney tissue. Increased LRP1 expression in ccRCC was associated with advanced stage, grade and worsened overall survival and progression-free survival. Functional annotation indicated an immune-modulatory role of LRP1 in ccRCC. LRP1 expression was significantly correlated with expressions of PBRM1, SETD2, and KDM5C. Positive correlations between LRP1 and pro-angiogenic factors ERAP1, SCG2, STAB1, and RUNX1 were observed. LRP1 expression was positively correlated with PD-L2 level. Negative correlations between LRP1 and anti-angiogenic factors EMCN and IL18 were observed. LRP1 expression was not associated with microvessel density (MVD) yet was negatively correlated with tumor-infiltrating lymphocytes (TIL).

CONCLUSION

LRP1 is associated with worsened prognosis in ccRCC and is related to cancer immune modulation. LRP1-targeted therapy can be of therapeutic potential.

Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer

We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, and miRNA expression levels and reverse-phase protein arrays, of which all, except for aneuploidy, revealed clustering primarily organized by histology, tissue type, or anatomic origin. The influence of cell type was evident in DNA-methylation-based clustering, even after excluding sites with known preexisting tissue-type-specific methylation. Integrative clustering further emphasized the dominant role of cell-of-origin patterns. Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan-cancer analyses, such as pan-gastrointestinal, pan-gynecological, pan-kidney, and pan-squamous cancers, and those related by stemness features, which in turn may inform strategies for future therapeutic development.