A river model to map convergent cancer evolution and guide therapy in RCC

Interferon signaling promotes tolerance to chromosomal instability during metastatic evolution in renal cancer

Molecular routes to metastatic dissemination are critical determinants of aggressive cancers. Through in vivo CRISPR-Cas9 genome editing, we generated somatic mosaic genetically engineered models that faithfully recapitulate metastatic renal tumors. Disruption of 9p21 locus is an evolutionary driver to systemic disease through the rapid acquisition of complex karyotypes in cancer cells. Cross-species analysis revealed that recurrent patterns of copy number variations, including 21q loss and dysregulation of the interferon pathway, are major drivers of metastatic potential. In vitro and in vivo genomic engineering, leveraging loss-of-function studies, along with a model of partial trisomy of chromosome 21q, demonstrated a dosage-dependent effect of the interferon receptor genes cluster as an adaptive mechanism to deleterious chromosomal instability in metastatic progression. This work provides critical knowledge on drivers of renal cell carcinoma progression and defines the primary role of interferon signaling in constraining the propagation of aneuploid clones in cancer evolution.

Identification of neoantigens and immunological subtypes in clear cell renal cell carcinoma for mRNA vaccine development and patient selection

Clear cell renal cell carcinoma (ccRCC) is a common urological malignancy with diverse histological types. This study aimed to detect neoantigens in ccRCC to develop mRNA vaccines and distinguish between ccRCC immunological subtypes for construction of an immune landscape to select patients suitable for vaccination. Using The Cancer Genome Atlas SpliceSeq database, The Cancer Genome Atlas, and the International Cancer Genome Consortium cohorts, we comprehensively analysed potential tumour antigens of ccRCC associated with aberrant alternative splicing, somatic mutation, nonsense-mediated mRNA decay factors, antigen-presenting cells, and overall survival. Immune subtypes (C1/C2) and nine immune gene modules of ccRCC were identified by consistency clustering and weighted correlation network analysis. The immune landscape as well as molecular and cellular characteristics of immunotypes were assessed. Rho-guanine nucleotide exchange factor 3 (ARHGEF3) was identified as a new ccRCC antigen for development of an mRNA vaccine. A higher tumour mutation burden, differential expression of immune checkpoints, and immunogenic cell death were observed in cases with the C2 immunotype. Cellular characteristics increased the complexity of the immune environment, and worse outcomes were observed in ccRCC cases with the C2 immunotype. We constructed the immune landscape for selecting patients with the C2 immunotype suitable for vaccination.

Blood Plasma Metabolome Profiling at Different Stages of Renal Cell Carcinoma

Early diagnostics significantly improves the survival of patients with renal cell carcinoma (RCC), which is the prevailing type of adult kidney cancer. However, the absence of clinically obvious symptoms and effective screening strategies at the early stages result to disease progression and survival rate reducing. The study was focused on revealing of potential low molecular biomarkers for early-stage RCC. The untargeted direct injection mass spectrometry-based metabolite profiling of blood plasma samples from 51 non-cancer volunteers (control) and 78 patients with different RCC subtypes and stages (early stages of clear cell RCC (ccRCC), papillary RCC (pRCC), chromophobe RCC (chrRCC) and advanced stages of ccRCC) was performed. Comparative analysis of the blood plasma metabolites between the control and cancer groups provided the detection of metabolites associated with different tumor stages. The designed model based on the revealed metabolites demonstrated high diagnostic power and accuracy. Overall, using the metabolomics approach the study revealed the metabolites demonstrating a high value for design of plasma-based test to improve early ccRCC diagnosis.

Artificial Intelligence in Kidney Cancer

Artificial intelligence is rapidly expanding into nearly all facets of life, particularly within the field of medicine. The diagnosis, characterization, management, and treatment of kidney cancer is ripe with areas for improvement that may be met with the promises of artificial intelligence. Here, we explore the impact of current research work in artificial intelligence for clinicians caring for patients with renal cancer, with a focus on the perspectives of radiologists, pathologists, and urologists. Promising preliminary results indicate that artificial intelligence may assist in the diagnosis and risk stratification of newly discovered renal masses and help guide the clinical treatment of patients with kidney cancer. However, much of the work in this field is still in its early stages, limited in its broader applicability, and hampered by small datasets, the varied appearance and presentation of kidney cancers, and the intrinsic limitations of the rigidly structured tasks artificial intelligence algorithms are trained to complete. Nonetheless, the continued exploration of artificial intelligence holds promise toward improving the clinical care of patients with kidney cancer.

Deciphering Intratumoral Molecular Heterogeneity in Clear Cell Renal Cell Carcinoma with a Radiogenomics Platform

PURPOSE

Intratumoral heterogeneity (ITH) challenges the molecular characterization of clear cell renal cell carcinoma (ccRCC) and is a confounding factor for therapy selection. Most approaches to evaluate ITH are limited by two-dimensional ex vivo tissue analyses. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can noninvasively assess the spatial landscape of entire tumors in their natural milieu. To assess the potential of DCE-MRI, we developed a vertically integrated radiogenomics colocalization approach for multi-region tissue acquisition and analyses. We investigated the potential of spatial imaging features to predict molecular subtypes using histopathologic and transcriptome correlatives.

EXPERIMENTAL DESIGN

We report the results of a prospective study of 49 patients with ccRCC who underwent DCE-MRI prior to nephrectomy. Surgical specimens were sectioned to match the MRI acquisition plane. RNA sequencing data from multi-region tumor sampling (80 samples) were correlated with percent enhancement on DCE-MRI in spatially colocalized regions of the tumor. Independently, we evaluated clinical applicability of our findings in 19 patients with metastatic RCC (39 metastases) treated with first-line antiangiogenic drugs or checkpoint inhibitors.

RESULTS

DCE-MRI identified tumor features associated with angiogenesis and inflammation, which differed within and across tumors, and likely contribute to the efficacy of antiangiogenic drugs and immunotherapies. Our vertically integrated analyses show that angiogenesis and inflammation frequently coexist and spatially anti-correlate in the same tumor. Furthermore, MRI contrast enhancement identifies phenotypes with better response to antiangiogenic therapy among patients with metastatic RCC.

CONCLUSIONS

These findings have important implications for decision models based on biopsy samples and highlight the potential of more comprehensive imaging-based approaches.

Somatic Copy Number Alterations and Associated Genes in Clear-Cell Renal-Cell Carcinoma in Brazilian Patients

Somatic copy number aberrations (CNAs) have been associated with clear-cell renal carcinoma (ccRCC) pathogenesis and are a potential source of new diagnostic, prognostic and therapeutic biomarkers. Recurrent CNAs include loss of chromosome arms 3p, 14q, 9p, and gains of 5q and 8q. Some of these regional CNAs are suspected of altering gene expression and could influence clinical outcomes. Despite many studies of CNAs in RCC, there are currently no descriptions of genomic copy number alterations in a Brazilian ccRCC cohort. This study was designed to evaluate the chromosomal profile of CNAs in Brazilian ccRCC tumors and explore clinical associations. A total of 92 ccRCC Brazilian patients that underwent nephrectomy at Barretos Cancer Hospital were analyzed for CNAs by array comparative genomic hybridization. Most patients in the cohort had early-stage localized disease. The most significant alterations were loss of 3p (87.3%), 14q (35.8%), 6q (29.3%), 9p (28.6%) and 10q (25.0%), and gains of 5q (59.7%), 7p (29.3%) and 16q (20.6%). Bioinformatics analysis revealed 19 genes mapping to CNA significant regions, including SETD2, BAP1, FLT4, PTEN, FGFR4 and NSD1. Moreover, gain of 5q34-q35.3 (FLT4 and NSD1) and loss of 6q23.2-q23.3 (MYB) and 9p21.3 (MLLT3) had gene expression levels that correlated with TCGA data and was also associated with advanced disease features, such as larger tumors, Fuhrman 3, metastasis at diagnosis and death. The loss of region 14q22.1 which encompasses the NIN gene was associated with poor overall survival. Overall, this study provides the first CNA landscape of Brazilian patients and pinpoints genomic regions and specific genes worthy of more detailed investigations. Our results highlight important genes that are associated with copy number changes involving large chromosomal regions that are potentially related to ccRCC tumorigenesis and disease biology for future clinical investigations.

Expression of BAG1 is associated with prognosis in kidney renal clear cell carcinoma based on bioinformatics

Background

BCL2 associated Athano-Gene 1 (BAG1) has been described to be involved in the development and progression of cancer. But the role of BAG1 in kidney renal clear cell carcinoma (KIRC) has remained largely unknown.

Methods

We performed bioinformatic analysis of data from TCGA and GEO dataset. The role of BAG1 in KIRC was explored by Logistic and Cox regression model. The molecular mechanisms of BAG1 was revealed by GSEA.

Results

The current study found that the KIRC tumor samples have a low level of BAG1 mRNA expression compared to the matched normal tissues based on TCGA data and GEO databases. Low expression of BAG1 in KIRC was significantly associated with Sex, clinical pathological stage, tumor-node-metastasis (TNM) stage, hemoglobin levels, cancer status and history of neoadjuvant treatment. Kaplan-Meier survival analysis indicated that KIRC patients with BAG1 high expression have a longer survival time than those with BAG1 low expression (p < 0.000). Cox regression analysis showed that BAG1 remained independently associated with overall survival, with a hazard ratio (HR) of 1.75(CI:1.05–2.90; p = 0.029). GSEA indicated that the signaling pathways including fatty acid metabolism and oxidative phosphorylation were differentially enriched in high BAG1 expression phenotype.

Conclusions

These findings suggested that BAG1 expression may act as a potential favorable prognostic marker and challenging therapeutic target.

Cancer evolution: A means by which tumors evade treatment

Although various methods have been tried to study and treat cancer, the cancer remains a major challenge for human medicine today. One important reason for this is the presence of cancer evolution. Cancer evolution is a process in which tumor cells adapt to the external environment, which can suppress the human immune system's ability to recognize and attack tumors, and also reduce the reproducibility of cancer research. Among them, heterogeneity of the tumor provides intrinsic motivation for this process. Recently, with the development of related technologies such as liquid biopsy, more and more knowledge about cancer evolution has been gained and interest in this topic has also increased. Therefore, starting from the causes of tumorigenesis, this paper introduces several tumorigenesis processes and pathways, as well as treatment options for different targets.

Tivozanib, a highly potent and selective inhibitor of VEGF receptor tyrosine kinases, for the treatment of metastatic renal cell carcinoma

The VHL mutation-HIF upregulation-VEGF transcription sequence is the principal pathway in the development of renal cell carcinoma. Tyrosine kinase inhibitors target the VEGF receptors to inhibit further growth of renal cell carcinoma tumors. Tivozanib, originally named AV-951 and KRN-951, is a novel, orally bioavailable VEGF tyrosine kinase inhibitor that is selective for VEGF receptors 1, 2 and 3. Further, only picomolar concentrations of tivozanib are required to target these VEGF receptors and prevent phosphorylation; this potency prevents the debilitating side effects that occur with treatments whose mechanisms of action involve broad-spectrum tyrosine kinase inhibition. This review summarizes the growing body of evidence supporting tivozanib's efficacy and safety in the treatment of advanced renal cell carcinoma.

LncRNA GA-Binding Protein Transcription Factor Subunit Beta-1 Antisense RNA 1 Inhibits Renal Carcinoma Growth Through an MiR-1246/Phosphoenolpyruvate Carboxykinase 1 Pathway

Objective

To clarify the role and mechanism of GABPB1-AS1 in renal cell carcinoma.

Methods

We collected 48 pairs of tumor and adjacent normal tissues from patients with clear cell renal cell carcinoma (ccRCC). Both 786-o and caki-1 ccRCC cell lines were transfected with GA-binding protein transcription factor subunit beta-1 antisense RNA 1 (GABPB1-AS1), miR-1246, or small interfering RNA phosphoenolpyruvate carboxykinase 1 (siPCK1) vectors. RNA expression was examined by quantitative reverse transcription-PCR and protein expression by Western blot. Cell proliferation was measured by Cell Counting Kit-8 assays. Cell migration and invasion were measured by transwell assays. Targeting relationships between genes were tested by luciferase reporter gene assays.

Results

Lower GABPB1-AS1 expression was found in ccRCC cells and tissues. GABPB1-AS1 expression was inversely associated with tumor size, TNM stage, and Furhman stage. High GABPB1-AS1 expression was associated with a better prognosis. GABPB1-AS1 overexpression significantly inhibited proliferation, migration, and invasion by 786-o and caki-1 cells. GABPB1-AS1 overexpression reduced tumor weights in xenograft experiments. Luciferase reporter assays showed that miR-1246 overexpression significantly inhibited the luciferase activity of 786-o and caki-1 cells transfected with wild-type (WT)-GABPB1-AS1 or WT-PCK1. Knockdown of PCK1 weakened the inhibition of proliferation, migration, and invasion induced by GABPB1-AS1 overexpression in 786-o and caki-1 cells.

Conclusion

GABPB1-AS1 inhibits ccRCC growth and plays a tumor suppressor role through an miR-1246/PCK1 axis.

Exploiting the circuit breaker cancer evolution model in human clear cell renal cell carcinoma

The incessant interactions between susceptible humans and their respective macro/microenvironments registered throughout their lifetime result in the ultimate manifestation of individual cancers. With the average lifespan exceeding 50 years of age in humans since the beginning of 20th century, aging - the "time" factor - has played an ever-increasing role alongside host and environmental factors in cancer incidences. Cancer is a genetic/epigenetic disease due to gain-of-function mutations in cancer-causing genes (oncogene; OG) and/or loss-of-function mutations in tumor-suppressing genes (tumor suppressor genes; TSG). In addition to their integral relationship with cancer, a timely deployment of specific OG and/or TSG is in fact needed for higher organisms like human to cope with respective physiological and pathological conditions. Over the past decade, extensive human kidney cancer genomics have been performed and novel mouse models recapitulating human kidney cancer pathobiology have been generated. With new genomic, genetic, mechanistic, clinical and therapeutic insights accumulated from studying clear cell renal cell carcinoma (ccRCC)-the most common type of kidney cancer, we conceived a cancer evolution model built upon the OG-TSG signaling pair analogous to the electrical circuit breaker (CB) that permits necessary signaling output and at the same time prevent detrimental signaling overdrive. Hence, this viewpoint aims at providing a step-by-step mechanistic explanation/illustration concerning how inherent OG-TSG CBs intricately operate in concert for the organism's wellbeing; and how somatic mutations, the essential component for genetic adaptability, inadvertently triggers a sequential outage of specific sets of CBs that normally function to maintain and protect and individual tissue homeostasis.

The Efficacy of Lenvatinib Plus Everolimus in Patients with Metastatic Renal Cell Carcinoma Exhibiting Primary Resistance to Front-Line Targeted Therapy or Immunotherapy

BACKGROUND

Patients with primary refractory metastatic renal cell carcinoma (mRCC) have a dismal prognosis and poor response to subsequent treatments. While there are several approved second-line therapies, it remains critical to choose the most effective treatment regimen.

PATIENTS AND METHODS

We identified 7 patients with clear cell mRCC who had primary resistance to vascular endothelial growth factor (VEGF)-targeted tyrosine kinase inhibitors (TKIs) or immune checkpoint inhibitor (ICI) combination therapy. The patients were treated with lenvatinib (a multitargeted TKI) plus everolimus (a mammalian target of rapamycin inhibitor). Among these 7 patients, 2 had prior TKI therapy, 3 had prior ICI therapy, and 2 had prior TKI and ICI therapy. We collected the patients' clinical characteristics, molecular profiles, treatment durations, and toxicity outcomes.

RESULTS

The median time to progression on prior therapies was 1.5 months. Lenvatinib plus everolimus was used either as a second-line (n = 4) or third-line (n = 3) therapy. As best responses, 3 patients had partial responses and 3 achieved stable disease. Patients were followed for ≥17 months; progression-free survival ranged from 3 to 15 months, and overall survival ranged from 4 to 17 months.

CONCLUSION

These 7 cases provide real-world data for the use of lenvatinib plus everolimus in patients with mRCC with primary resistance to first-line VEGF-targeted TKIs or ICI combination therapy.

Glutathione transferase genotypes may serve as determinants of risk and prognosis in renal cell carcinoma

Renal cell carcinoma (RCC) represents a group of histologically similar neoplasms with significant intratumor and intertumor genetic heterogeneity. Recognized risk factors for RCC development include smoking, hypertension, obesity, as well as von Hippel-Lindau (VHL) disease. Inactivation of VHL, deregulated nuclear factor (erythroid-derived 2)-like 2 (Nrf2) pathway, and altered redox homeostasis, together with changes in glutathione transferase (GST) profile, are considered as important contributing factors in RCC development and progression. Although the available results of both gene-gene and gene-environment analysis are quite heterogeneous, they clearly indicate that certain GST genotypes may play a role as risk modifiers, either individually or in combination with other Phase I or Phase II gene polymorphisms, as well as in subjects exposed to relevant substrates. Seemingly, GST genotyping could identify individuals with impaired detoxification in renal parenchyma that are at higher risk of developing RCC. In addition to well established roles of GSTs in conjugation and biotransformation of xenobiotics, GSTs have emerged as significant regulators of pathways determining cell proliferation and survival. Indeed, there are evidence in favor of GST significance, not only in terms of risk for RCC development, but also with respect to progression and prognosis. So far, GSTM1-active genotype was confirmed to be an independent predictor of higher risk of overall mortality. Therefore, it is reasonable to assume that certain GST variants may assist in individual RCC risk assessment, as well as postoperative prognosis. Even more, GST profiling might contribute to development of personalized targeted therapy in RCC patients.

Mouse- and patient-derived CAM xenografts for studying metastatic renal cell carcinoma

Renal cell carcinoma is the seventh most common cancer in the United States, and its metastatic form has a very poor prognosis due to a lack of effective treatment and thorough understanding on metastatic mechanism. This chapter will demonstrate a novel concept that intratumoral heterogeneity is essential for metastasis in renal cell carcinoma. We will first introduce the in vitro system and the mouse model that led to the finding of the cooperative mechanism for metastasis. Then, the results from the CAM model illustrate the cooperative interactions that lead to metastasis also occur in this model. We believe that the CAM model, as a unique and sustainable system, can open up new opportunities to study the metastatic disease.

Immunotherapy in renal cell carcinoma from poverty to the spoiled of choice

Management of metastatic renal cell carcinoma has been enriched by the advent of new therapeutic compounds. The approval of new combination strategies between targeted agents and immune-checkpoint inhibitors as well as the administration of combinations between immune-checkpoint inhibitors has clearly demonstrated significant improvement toward patients' prognosis and other clinical outcomes. Due to the availability of different treatments, the choice between them may be a difficult issue in our clinical practice. We have summarized current knowledge about available treatments focusing on criteria, which may help clinicians to make decisions.

Toward a genome-based treatment landscape for renal cell carcinoma

Knowledge about molecular mechanisms driving development and progression of renal cell carcinoma has been elucidated by different studies. In few years we discovered a large difference between genomic landscapes of clear cell and non-clear cell carcinoma. Moreover, tumor heterogeneity and different acquisition of gene mutations during tumor progression are issues of particular interest. In this review we focalized our attention on principal genomic alterations identified among RCC subtypes. Acquired gene mutations may be an adaptive response to several external pressure including metabolic, treatment, genomic and immune-related external pressure. Thus we correlated and discussed principal genomic alterations adopted by tumor to escape from each external pressures. The aim of the present work is to summarize current knowledge about genomic alterations in RCC with special interest of treatment strategies tailored on the basis of disease mutations assessment.

Modeling breast cancer progression to bone: how driver mutation order and metabolism matter

BACKGROUND

Not all the mutations are equally important for the development of metastasis. What about their order? The survival of cancer cells from the primary tumour site to the secondary seeding sites depends on the occurrence of very few driver mutations promoting oncogenic cell behaviours. Usually these driver mutations are among the most effective clinically actionable target markers. The quantitative evaluation of the effects of a mutation across primary and secondary sites is an important challenging problem that can lead to better predictability of cancer progression trajectory.

RESULTS

We introduce a quantitative model in the framework of Cellular Automata to investigate the effects of metabolic mutations and mutation order on cancer stemness and tumour cell migration from breast, blood to bone metastasised sites. Our approach models three types of mutations: driver, the order of which is relevant for the dynamics, metabolic which support cancer growth and are estimated from existing databases, and non-driver mutations. We integrate the model with bioinformatics analysis on a cancer mutation database that shows metabolism-modifying alterations constitute an important class of key cancer mutations.

CONCLUSIONS

Our work provides a quantitative basis of how the order of driver mutations and the number of mutations altering metabolic processis matter for different cancer clones through their progression in breast, blood and bone compartments. This work is innovative because of multi compartment analysis and could impact proliferation of therapy-resistant clonal populations and patient survival. Mathematical modelling of the order of mutations is presented in terms of operators in an accessible way to the broad community of researchers in cancer models so to inspire further developments of this useful (and underused in biomedical models) methodology. We believe our results and the theoretical framework could also suggest experiments to measure the overall personalised cancer mutational signature.

Vimentin Overexpressions Induced by Cell Hypoxia Promote Vasculogenic Mimicry by Renal Cell Carcinoma Cells

Vasculogenic mimicry (VM), the novel approach for tumor cells to obtain blood supply, was reported to be involved in antiangiogenic resistance and poor prognosis in renal cell carcinoma (RCC). However, the molecular mechanisms underlying VM formed by RCC cells are still not clearly depicted. In the present study, we found that OS-RC-2 acquired the VM forming ability accompanied with the increased expressions of Vimentin and AXL and decreased expression of E-Cadherin by CoCl₂ treatment. Downregulation of Vimentin by siRNA severely impaired the capability of OS-RC-2 and 786-O to form VM structures induced by cell hypoxia in vitro. Moreover, knockdown of Vimentin inhibited cell migration and invasion, which could be prompted by hypoxia induction in RCC cells. In our clear cell RCC tissues, we found that VM was positively correlated with Vimentin overexpression and both predicted poor prognosis. In conclusion, Vimentin plays an important role in hypoxia induced VM formation of RCC cells and targeted Vimentin might be beneficial for RCC therapy.

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.

BAP1 in solid tumors

One of the most attractive cancer-related genes under investigation is BAP1. Reasons of this growing interest are related to the wide spectrum of pathways directly or indirectly modulated by this gene and shared by several solid tumors. Programmed cell-death, cell metabolisms, immune cells development, ferroptosis and defects in DNA damage response are only some of the multitude of processes depending on BAP1. Loss of this gene seems to occur in different times of tumor history. Moreover, times of BAP1 loss strongly diverge among primary tumors suggesting the presence of several and different triggering factors. Regardless of when it happens, BAP1 loss usually results in prognosis worsening and in the acquisition of more aggressive clinical features by cancer cells.

Hyperpolarized MRI Visualizes Warburg Effects and Predicts Treatment Response to mTOR Inhibitors in Patient-Derived ccRCC Xenograft Models

The ever-changing tumor microenvironment constantly challenges individual cancer cells to balance supply and demand, presenting tumor vulnerabilities and therapeutic opportunities. Everolimus and temsirolimus are inhibitors of mTOR (mTORi) approved for treating metastatic renal cell carcinoma (mRCC). However, treatment outcome varies greatly among patients. Accordingly, administration of mTORi in mRCC is diminishing, which could potentially result in missing timely delivery of effective treatment for select patients. Here, we implemented a clinically applicable, integrated platform encompassing a single dose of [1-¹³C] pyruvate to visualize the in vivo effect of mTORi on the conversion of pyruvate to lactate using hyperpolarized MRI. A striking difference that predicts treatment benefit was demonstrated using two preclinical models derived from patients with clear cell RCC (ccRCC) who exhibited primary resistance to VEGFRi and quickly succumbed to their diseases within 6 months after the diagnosis of metastasis without receiving mTORi. Our findings suggest that hyperpolarized MRI could be further developed to personalize kidney cancer treatment. SIGNIFICANCE: These findings demonstrate hyperpolarized ^[1-13C]pyruvate MRI as a tool for accurately assessing the clinical success of mTOR inhibition in patients with ccRCC.

Treating metastatic prostate cancer with microRNA-145

Prostate cancer (PCa) is an incurable disease at the metastatic stage. Although there are different options for treatment, the results are limited. MicroRNAs (miRNAs) are a group of small, noncoding, regulatory RNAs with important roles in regulating gene expression. miR-145 is reported to be a key tumor suppressor miRNA (tsmiR) that controls important oncogenes, such as MYC and RAS. In this study, in vitro studies were performed to show the control of MYC and RAS by miR-145. Flow cytometry was used to analyze cell proliferation and apoptosis. The efficacy of miR-145 in treating metastatic PCa was tested in nude mice using a model of bone metastasis promoted by intraventricular injection of PC-3MLuc-C6 cells. Tumor growth was evaluated by an in vivo bioluminescence system. After the full establishment of metastases on day 21, six animals were treated with three intravenous doses of miR-145 (on days 21, 24 and 27), and six were injected with scramble miRNA as controls. Compared to the controls, tumor growth was significantly reduced in animals receiving miR-145, most importantly on day 7 after the third and last dose of miRNA. After discontinuing the treatment, tumor growth resumed, becoming similar to the group of non-treated animals. A decrease in MYC and RAS expression was observed in all cell lines after treatment with miR-145, although statistical significance was achieved only in experiments with LNCaP and PC3 cell lines, with a decrease in 56% (p = 0.012) and 31% (p = 0.013) of RAS expression, respectively. Our results suggest that miR-145 is a potential molecule to be tested for treatment of metastatic, castration-resistant PCa.

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.

The glucose and lipid metabolism reprogramming is grade-dependent in clear cell renal cell carcinoma primary cultures and is targetable to modulate cell viability and proliferation

Clear cell renal cell carcinoma (ccRCC) has a poor prognosis despite novel biological targeted therapies. Tumor aggressiveness and poor survival may correlate with tumor grade at diagnosis and with complex metabolic alterations, also involving glucose and lipid metabolism. However, currently no grade-specific metabolic therapy addresses these alterations. Here we used primary cell cultures from ccRCC of low- and high-grade to investigate the effect on energy state and reduced pyridine nucleotide level, and on viability and proliferation, of specific inhibition of glycolysis with 2-deoxy-D-glucose (2DG), or fatty acid oxidation with Etomoxir. Our primary cultures retained the tissue grade-dependent modulation of lipid and glycogen storage and aerobic glycolysis (Warburg effect). 2DG affected lactate production, energy state and reduced pyridine nucleotide level in high-grade ccRCC cultures, but the energy state only in low-grade. Rather, Etomoxir affected energy state in high-grade and reduced pyridine nucleotide level in low-grade cultures. Energy state and reduced pyridine nucleotide level were evaluated by ATP and reduced 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium (MTT) dye quantification, respectively. 2DG treatment impaired cell proliferation and viability of low-grade ccRCC and normal cortex cultures, whereas Etomoxir showed a cytostatic and cytotoxic effect only in high-grade ccRCC cultures. Our data indicate that in ccRCC the Warburg effect is a grade-dependent feature, and fatty acid oxidation can be activated for different grade-dependent metabolic needs. A possible grade-dependent metabolic therapeutic approach in ccRCC is also highlighted.

Tumor Xenografts of Human Clear Cell Renal Cell Carcinoma But Not Corresponding Cell Lines Recapitulate Clinical Response to Sunitinib: Feasibility of Using Biopsy Samples

BACKGROUND

Parallel development of preclinical models that recapitulate treatment response observed in patients is central to the advancement of personalized medicine.

OBJECTIVE

To evaluate the use of biopsy specimens to develop patient-derived xenografts and the use of corresponding cell lines from renal cell carcinoma (RCC) tumors for the assessment of histopathology, genomics, and treatment response.

DESIGN, SETTING, AND PARTICIPANTS

A total of 74 tumor specimens from 66 patients with RCC were implanted into immunocompromised NOD-SCID IL2Rg-/- mice. Four cell lines generated from patients' specimens with clear cell pathology were used for comparative studies.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Preclinical models were established and assessed. Engraftment rates were analyzed using chi-square testing. Analysis of variance (two-way analysis of variance) was conducted to assess tumor growth.

RESULTS AND LIMITATIONS

Overall, 33 RCC mouse xenograft models were generated with an overall engraftment rate of 45% (33 of 74). Tumor biopsies engrafted comparably with surgically resected tumors (58% vs 41%; p=0.3). Xenograft tumors and their original tumors showed high fidelity in regard to histology, mutation status, copy number change, and targeted therapy response. Engraftment rates from metastatic tumors were higher but not more significant than primary tumors (54% vs 34%; p=0.091). Our engraftment rate using metastases or biopsies was comparable with recent reports using resected primary tumors. In stark contrast to corresponding cell lines, all tested xenografts recapitulated patients' clinical response to sunitinib.

CONCLUSIONS

Patient-derived xenograft models can be effectively established from tumor biopsies. Preclinical xenograft models but not matched cell lines reflected clinical responses to sunitinib.

PATIENT SUMMARY

Matched patient-derived clear cell renal cell carcinoma xenografts and cell lines from responsive and refractory patients treated with sunitinib were established and evaluated for pharmacologic response to anti-vascular endothelial growth factor treatment. Both models accurately reflected the genetic characteristics of original tumors, but only xenografts recapitulated drug responses observed in patients. These models could serve as a powerful platform for precision medicine.

The SWI/SNF Protein PBRM1 Restrains VHL-Loss-Driven Clear Cell Renal Cell Carcinoma

PBRM1 is the second most commonly mutated gene after VHL in clear cell renal cell carcinoma (ccRCC). However, the biological consequences of PBRM1 mutations for kidney tumorigenesis are unknown. Here, we find that kidney-specific deletion of Vhl and Pbrm1, but not either gene alone, results in bilateral, multifocal, transplantable clear cell kidney cancers. PBRM1 loss amplified the transcriptional outputs of HIF1 and STAT3 incurred by Vhl deficiency. Analysis of mouse and human ccRCC revealed convergence on mTOR activation, representing the third driver event after genetic inactivation of VHL and PBRM1. Our study reports a physiological preclinical ccRCC mouse model that recapitulates somatic mutations in human ccRCC and provides mechanistic and therapeutic insights into PBRM1 mutated subtypes of human ccRCC.

Comparative Genomic Profiling of Matched Primary and Metastatic Tumors in Renal Cell Carcinoma

BACKGROUND

Next-generation sequencing (NGS) studies of matched pairs of primary and metastatic tumors in renal cell carcinoma (RCC) have been limited to small cohorts.

OBJECTIVE

To evaluate the discordance in somatic mutations between matched primary and metastatic RCC tumors.

DESIGN, SETTING, AND PARTICIPANTS

Primary tumor (P), metastasis (M), and germline DNA from 60 patients with RCC was subjected to NGS with a targeted exon capture-based assay of 341 cancer-associated genes. Somatic mutations were called using a validated pipeline.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Mutations were classified as shared (S) or private (Pr) in relation to each other within individual P-M pairs. The concordance score was calculated as (S-Pr)/(S+Pr). To calculate enrichment of Pr/S mutations for a particular gene, we calculated a two-sided p value from a binomial model for each gene with at least ten somatic mutation events, and also implemented a separate permutation test procedure. We adjusted p values for multiple hypothesis testing using the Benjamini-Hochberg procedure. The mutation discordance was calculated using Mann-Whitney U tests according to gene mutations or metastatic sites.

RESULTS AND LIMITATIONS

Twenty-one pairs (35%) showed Pr mutations in both P and M samples. Of the remaining 39 pairs (65%), 14 (23%) had Pr mutations specific to P samples, 12 (20%) had Pr mutations to M samples, and 13 (22%) had identical somatic mutations. No individual gene mutation was preferentially enriched in either P or M samples. P-M pairs with SETD2 mutations demonstrated higher discordance than pairs with wild-type SETD2. We observed that patients who received therapy before sampling of the P or M tissue had higher concordance of mutations for P-M pairs than patients who did not (Mann-Whitney p=0.088).

CONCLUSIONS

Our data show mutation discordance within matched P-M RCC tumor pairs. As most contemporary precision medicine trials do not differentiate mutations detected in P and M tumors, the prognostic and predictive value of mutations in P versus M tumors warrants further investigation.

PATIENT SUMMARY

In this study we evaluated the concordance of mutations between matched primary and metastatic tumors for 60 kidney cancer patients using a panel of 341 cancer genes. Forty-seven patients carried nonidentical cancer gene mutations within their matched primary-metastatic pair. The mutation profile of the primary tumor alone could compromise precision in selecting effective targeted therapies and result in suboptimal clinical outcomes.

Mechanisms and clinical implications of tumor heterogeneity and convergence on recurrent phenotypes

Tumor heterogeneity has been identified at various -omic levels. The tumor genome, transcriptome, proteome, and phenome can vary widely across cells in patient tumors and are influenced by tumor cell interactions with heterogeneous physical conditions and cellular components of the tumor microenvironment. Here, we explore the concept that while variation exists at multiple -omic levels, changes at each of these levels converge on the same pathways and lead to convergent phenotypes in tumors that can provide common drug targets. These phenotypes include cellular growth and proliferation, sustained oncogenic signaling, and immune avoidance, among others. Tumor heterogeneity complicates treatment of patient cancers as it leads to varied response to therapies. Identification of convergent cellular phenotypes arising in patient cancers and targeted therapies that reverse them has the potential to transform the way clinicians treat these cancers and to improve patient outcome.

Molecular Classification of Renal Cell Carcinoma and Its Implication in Future Clinical Practice

Renal cell carcinoma (RCC) encompasses a wide spectrum of morphologically and molecularly distinct (>10) cancer subtypes originated from the kidney epithelium. Metastatic RCC (mRCC) is lethal and refractory to conventional chemotherapeutic agents. The incorporation of targeted therapies and immune checkpoint inhibitors into the current practice of mRCC has markedly improved the median overall survival of clear cell RCC (ccRCC) patients, the most common subtype, but not rare kidney cancer (RKC or non-ccRCC, nccRCC). Varied treatment response in mRCC patients is observed, which presents clinical challenges/opportunities at the modern mRCC therapeutic landscape consisting of 12 approved drugs representing 6 different effective mechanisms. Key contributing factors include inter- and intra-RCC heterogeneity. With the advances in pan-omics technologies, we now have a better understanding of the molecular pathobiology of individual RCC subtype. Here, we attempt to classify ccRCC based on contemporary molecular features with emphasis on their respective potential significance in clinical practice.

Genomic landscape and evolution of metastatic chromophobe renal cell carcinoma

Chromophobe renal cell carcinoma (chRCC) typically shows ~7 chromosome losses (1, 2, 6, 10, 13, 17, and 21) and ~31 exonic somatic mutations, yet carries ~5%-10% metastatic incidence. Since extensive chromosomal losses can generate proteotoxic stress and compromise cellular proliferation, it is intriguing how chRCC, a tumor with extensive chromosome losses and a low number of somatic mutations, can develop lethal metastases. Genomic features distinguishing metastatic from nonmetastatic chRCC are unknown. An integrated approach, including whole-genome sequencing (WGS), targeted ultradeep cancer gene sequencing, and chromosome analyses (FACETS, OncoScan, and FISH), was performed on 79 chRCC patients including 38 metastatic (M-chRCC) cases. We demonstrate that TP53 mutations (58%), PTEN mutations (24%), and imbalanced chromosome duplication (ICD, duplication of ≥ 3 chromosomes) (25%) were enriched in M-chRCC. Reconstruction of the subclonal composition of paired primary-metastatic chRCC tumors supports the role of TP53, PTEN, and ICD in metastatic evolution. Finally, the presence of these 3 genomic features in primary tumors of both The Cancer Genome Atlas kidney chromophobe (KICH) (n = 64) and M-chRCC (n = 35) cohorts was associated with worse survival. In summary, our study provides genomic insights into the metastatic progression of chRCC and identifies TP53 mutations, PTEN mutations, and ICD as high-risk features.

Stratification of clear cell renal cell carcinoma (ccRCC) genomes by gene-directed copy number alteration (CNA) analysis

Tumorigenic processes are understood to be driven by epi-/genetic and genomic alterations from single point mutations to chromosomal alterations such as insertions and deletions of nucleotides up to gains and losses of large chromosomal fragments including products of chromosomal rearrangements e.g. fusion genes and proteins. Overall comparisons of copy number alterations (CNAs) presented in 48 clear cell renal cell carcinoma (ccRCC) genomes resulted in ratios of gene losses versus gene gains between 26 ccRCC Fuhrman malignancy grades G1 (ratio 1.25) and 20 G3 (ratio 0.58). Gene losses and gains of 15762 CNA genes were mapped to 795 chromosomal cytoband loci including 280 KEGG pathways. CNAs were classified according to their contribution to Fuhrman tumour gradings G1 and G3. Gene gains and losses turned out to be highly structured processes in ccRCC genomes enabling the subclassification and stratification of ccRCC tumours in a genome-wide manner. CNAs of ccRCC seem to start with common tumour related gene losses flanked by CNAs specifying Fuhrman grade G1 losses and CNA gains favouring grade G3 tumours. The appearance of recurrent CNA signatures implies the presence of causal mechanisms most likely implicated in the pathogenesis and disease-outcome of ccRCC tumours distinguishing lower from higher malignant tumours. The diagnostic quality of initial 201 genes (108 genes supporting G1 and 93 genes G3 phenotypes) has been successfully validated on published Swiss data (GSE19949) leading to a restricted CNA gene set of 171 CNA genes of which 85 genes favour Fuhrman grade G1 and 86 genes Fuhrman grade G3. Regarding these gene sets overall survival decreased with the number of G3 related gene losses plus G3 related gene gains. CNA gene sets presented define an entry to a gene-directed and pathway-related functional understanding of ongoing copy number alterations within and between individual ccRCC tumours leading to CNA genes of prognostic and predictive value.

Persistent Severe Hyperlactatemia and Metabolic Derangement in Lethal SDHB-Mutated Metastatic Kidney Cancer: Clinical Challenges and Examples of Extreme Warburg Effect

To describe the unique clinical features, determine the genomics, and investigate the metabolic derangement of an extremely rare form of a hereditary lethal kidney cancer syndrome.

Patients and Methods

Three patients with lethal kidney cancer (age 19, 20, and 37 years) exhibiting persistent (1 to 3 months) extremely high levels of blood lactate (> 5 mM) despite normal oxygen perfusion, highly avid tumors on [18F]fluorodeoxyglucose positron emission tomography (PET), and pleomorphic histopathologic features were identified and treated in a single institute. Integrated studies including whole-genome sequencing (WGS), targeted sequencing, immunohistochemistry, cell-based assays, and 18F-glutamine PET imaging were performed to investigate this rare kidney cancer syndrome.

Results

All three patients with kidney cancer were initially given various diagnoses as a result of diverse tumor histopathology and atypical clinical presentations. The correct diagnoses of these SDHB-mutated renal cell carcinomas were first made based on cancer genomics. Genomic studies of the blood and tumors of these patients identified three different kinds of germline loss-of-function mutations in the SDHB gene and the common loss of heterozygosity in the remaining SDHB allele thorough somatic chromosome 1p deletion. In one patient, WGS revealed that a germline mutation of SDHB coupled with loss of heterozygosity was the sole genetic event. Cancer evolution analysis of SDHB tumors based on WGS demonstrated that SDHB in kidney epithelium fulfills the Knudson two-hit criteria as a major tumor suppressor gene. SDHB -/- tumor cells displayed increase in glucose uptake and lactate production, alteration in mitochondrial architecture, and defect in oxidative respiration. 18F-Glutamine PET imaging studies demonstrated increased glutamine metabolism.

Conclusion

SDHB-deficient metastatic renal cell carcinoma is a rare, aggressive form of kidney cancer that manifests with clinical evidence of a severe Warburg effect, and genomic studies demonstrated two genetic hits at SDHB genes during kidney tumorigenesis.

Overcome tumor heterogeneity-imposed therapeutic barriers through convergent genomic biomarker discovery: A braided cancer river model of kidney cancer

Tumor heterogeneity, encompassing genetic, epigenetic, and microenvironmental variables, is extremely complex and presents challenges to cancer diagnosis and therapy. Genomic efforts on genetic intratumor heterogeneity (G-ITH) confirm branched evolution, support the trunk-branch cancer model, and present a seemingly insurmountable obstacle to conquering cancers. G-ITH is conspicuous in clear cell renal cell carcinoma (ccRCC), where its presence complicates identification and validation of biomarkers and thwarts efforts in advancing precision cancer therapeutics. However, long-term clinical benefits on targeted therapy are not uncommon in metastatic ccRCC patients, implicating that there are underlying constraints during ccRCC evolution, which in turn force a nonrandom sequence of parallel gene/pathway/function/phenotype convergence within individual tumors. Accordingly, we proposed a "braided cancer river model" depicting ccRCC evolution, which deduces cancer development based on multiregion tumor genomics of exceptional mTOR inhibitor (mTORi) responders. Furthermore, we employ an outlier case to explore the river model and highlight the importance of "Five NGS Matters: Number, Frequency, Position, Site and Time" in assessing cancer genomics for precision medicine. This mutable cancer river model may capture clinically significant phenotype-convergent events, predict vulnerability/resistance mechanisms, and guide effective therapeutic strategies. Our model originates from studying exceptional responders in ccRCC, which warrants further refinement and future validation concerning its applicability to other cancer types. The goal of this review is employing kidney cancer as an example to illustrate critical issues concerning tumor heterogeneity.

Renal cell carcinoma

Renal cell carcinoma (RCC) denotes cancer originated from the renal epithelium and accounts for >90% of cancers in the kidney. The disease encompasses >10 histological and molecular subtypes, of which clear cell RCC (ccRCC) is most common and accounts for most cancer-related deaths. Although somatic VHL mutations have been described for some time, more-recent cancer genomic studies have identified mutations in epigenetic regulatory genes and demonstrated marked intra-tumour heterogeneity, which could have prognostic, predictive and therapeutic relevance. Localized RCC can be successfully managed with surgery, whereas metastatic RCC is refractory to conventional chemotherapy. However, over the past decade, marked advances in the treatment of metastatic RCC have been made, with targeted agents including sorafenib, sunitinib, bevacizumab, pazopanib and axitinib, which inhibit vascular endothelial growth factor (VEGF) and its receptor (VEGFR), and everolimus and temsirolimus, which inhibit mechanistic target of rapamycin complex 1 (mTORC1), being approved. Since 2015, agents with additional targets aside from VEGFR have been approved, such as cabozantinib and lenvatinib; immunotherapies, such as nivolumab, have also been added to the armamentarium for metastatic RCC. Here, we provide an overview of the biology of RCC, with a focus on ccRCC, as well as updates to complement the current clinical guidelines and an outline of potential future directions for RCC research and therapy.

Genomic Biomarkers of a Randomized Trial Comparing First-line Everolimus and Sunitinib in Patients with Metastatic Renal Cell Carcinoma

BACKGROUND

Metastatic renal cell carcinoma (RCC) patients are commonly treated with vascular endothelial growth factor (VEGF) inhibitors or mammalian target of rapamycin inhibitors. Correlations between somatic mutations and first-line targeted therapy outcomes have not been reported on a randomized trial.

OBJECTIVE

To evaluate the relationship between tumor mutations and treatment outcomes in RECORD-3, a randomized trial comparing first-line everolimus (mTOR inhibitor) followed by sunitinib (VEGF inhibitor) at progression with the opposite sequence in 471 metastatic RCC patients.

DESIGN, SETTING, AND PARTICIPANTS

Targeted sequencing of 341 cancer genes at ∼540× coverage was performed on available tumor samples from 258 patients; 220 with clear cell histology (ccRCC).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Associations between somatic mutations and median first-line progression free survival (PFS1L) and overall survival were determined in metastatic ccRCC using Cox proportional hazards models and log-rank tests.

RESULTS AND LIMITATIONS

Prevalent mutations (≥ 10%) were VHL (75%), PBRM1 (46%), SETD2 (30%), BAP1 (19%), KDM5C (15%), and PTEN (12%). With first-line everolimus, PBRM1 and BAP1 mutations were associated with longer (median [95% confidence interval {CI}] 12.8 [8.1, 18.4] vs 5.5 [3.1, 8.4] mo) and shorter (median [95% CI] 4.9 [2.9, 8.1] vs 10.5 [7.3, 12.9] mo) PFS1L, respectively. With first-line sunitinib, KDM5C mutations were associated with longer PFS1L (median [95% CI] of 20.6 [12.4, 27.3] vs 8.3 [7.8, 11.0] mo). Molecular subgroups of metastatic ccRCC based on PBRM1, BAP1, and KDM5C mutations could have predictive values for patients treated with VEGF or mTOR inhibitors. Most tumor DNA was obtained from primary nephrectomy samples (94%), which could impact correlation statistics.

CONCLUSIONS

PBRM1, BAP1, and KDM5C mutations impact outcomes of targeted therapies in metastatic ccRCC patients.

PATIENT SUMMARY

Large-scale genomic kidney cancer studies reported novel mutations and heterogeneous features among individual tumors, which could contribute to varied clinical outcomes. We demonstrated correlations between somatic mutations and treatment outcomes in clear cell renal cell carcinoma, supporting the value of genomic classification in prospective studies.

Constraints in cancer evolution

Next-generation deep genome sequencing has only recently allowed us to quantitatively dissect the extent of heterogeneity within a tumour, resolving patterns of cancer evolution. Intratumour heterogeneity and natural selection contribute to resistance to anticancer therapies in the advanced setting. Recent evidence has also revealed that cancer evolution might be constrained. In this review, we discuss the origins of intratumour heterogeneity and subsequently focus on constraints imposed upon cancer evolution. The presence of (1) parallel evolution, (2) convergent evolution and (3) the biological impact of acquiring mutations in specific orders suggest that cancer evolution may be exploitable. These constraints on cancer evolution may help us identify cancer evolutionary rule books, which could eventually inform both diagnostic and therapeutic approaches to improve survival outcomes.

The difficulty in selecting patients for cytoreductive nephrectomy: An evaluation of previously described predictive models

PURPOSE

To externally evaluate a preoperative points system and a preoperative nomogram, both created to assess time to death after cytoreductive nephrectomy (CN).

MATERIALS AND METHODS

We identified 298 patients who underwent CN at our institution, a tertiary cancer center, between 1989 and 2015. To validate the points system, we compared reported overall survival (OS) for each criterion to observed OS in our cohort. To evaluate the nomogram, we prognosticated risk of death at 6 months after surgery for 280 patients with sufficient follow-up in our cohort and evaluated discrimination using area under the curve (AUC) and calibration. Decision curve analysis was performed to assess clinical utility of the nomogram.

RESULTS

Significant differences in OS were observed between patients with and without 5 of 7 criteria on univariate analysis: low albumin (P<0.0001), high lactate dehydrogenase (P = 0.002), liver metastasis (P = 0.004), retroperitoneal lymphadenopathy (P = 0.002), and supradiaphragmatic lymphadenopathy (P = 0.019). Discrimination from the preoperative model, predicting death within 6 months of surgery was lower in our cohort (AUC = 0.65, 95% CI: 0.52-0.79) than the original publication (AUC = 0.76). Decision curve analysis demonstrated little benefit for applicability.

CONCLUSIONS

Five previously defined risk factors are predictive of decreased OS after CN in our cohort. We found lower discrimination using the preoperative model and minimal clinical utility according to decision analysis in our study cohort. These findings suggest the need for improved models to aid patient stratification and consequent treatment choice.

A braided cancer river connects tumor heterogeneity and precision medicine

With the ever-increasing complexity of tumor heterogeneity (TH) discovered through cancer genome sequencing, it is apparent that TH has become the biggest hurdle for precision cancer therapeutics. Through studying the genomics of exceptional responders to targeted therapeutic agents in kidney cancer, we demonstrated parallel convergent gene/pathway/capability/function evolution of kidney cancer in the context of TH, which prompted us to propose a new cancer evolution model “the braided cancer river model”. Based on this model, we might be able to outsmart a given cancer type within an individual patient through simultaneously inhibiting preferred parallel pathways or sequential nodes. Thus, the goals of this perspective are to define tumor heterogeneity, discuss tumor evolution, introduce braided cancer river model, and improve precision medicine.

Mechanistically distinct cancer-associated mTOR activation clusters predict sensitivity to rapamycin

Genomic studies have linked mTORC1 pathway-activating mutations with exceptional response to treatment with allosteric inhibitors of mTORC1 called rapalogs. Rapalogs are approved for selected cancer types, including kidney and breast cancers. Here, we used sequencing data from 22 human kidney cancer cases to identify the activating mechanisms conferred by mTOR mutations observed in human cancers and advance precision therapeutics. mTOR mutations that clustered in focal adhesion kinase targeting domain (FAT) and kinase domains enhanced mTORC1 kinase activity, decreased nutrient reliance, and increased cell size. We identified 3 distinct mechanisms of hyperactivation, including reduced binding to DEP domain-containing MTOR-interacting protein (DEPTOR), resistance to regulatory associated protein of mTOR-mediated (RAPTOR-mediated) suppression, and altered kinase kinetics. Of the 28 mTOR double mutants, activating mutations could be divided into 6 complementation groups, resulting in synergistic Rag- and Ras homolog enriched in brain-independent (RHEB-independent) mTORC1 activation. mTOR mutants were resistant to DNA damage-inducible transcript 1-mediated (REDD1-mediated) inhibition, confirming that activating mutations can bypass the negative feedback pathway formed between HIF1 and mTORC1 in the absence of von Hippel-Lindau (VHL) tumor suppressor expression. Moreover, VHL-deficient cells that expressed activating mTOR mutants grew tumors that were sensitive to rapamycin treatment. These data may explain the high incidence of mTOR mutations observed in clear cell kidney cancer, where VHL loss and HIF activation is pathognomonic. Our study provides mechanistic and therapeutic insights concerning mTOR mutations in human diseases.

Therapeutic Guide for mTOuRing through the Braided Kidney Cancer Genomic River

mTORC1 inhibitors were first approved for the use in metastatic kidney cancer. However, observed treatment benefit was highly heterogeneous among patients. Through case-based cancer genomic sequencing of therapeutic outliers, we can begin to appreciate the convergent evolution of given cancer pathways/phenotypes beyond genes in kidney cancer, like a braided river. Clin Cancer Res; 22(10); 2320-2. ©2016 AACRSee related article by Kwiatkowski et al., p. 2445.

An Integrated Metabolic Atlas of Clear Cell Renal Cell Carcinoma

Dysregulated metabolism is a hallmark of cancer, manifested through alterations in metabolites. We performed metabolomic profiling on 138 matched clear cell renal cell carcinoma (ccRCC)/normal tissue pairs and found that ccRCC is characterized by broad shifts in central carbon metabolism, one-carbon metabolism, and antioxidant response. Tumor progression and metastasis were associated with metabolite increases in glutathione and cysteine/methionine metabolism pathways. We develop an analytic pipeline and visualization tool (metabolograms) to bridge the gap between TCGA transcriptomic profiling and our metabolomic data, which enables us to assemble an integrated pathway-level metabolic atlas and to demonstrate discordance between transcriptome and metabolome. Lastly, expression profiling was performed on a high-glutathione cluster, which corresponds to a poor-survival subgroup in the ccRCC TCGA cohort.

Tumor Evolutionary Principles: How Intratumor Heterogeneity Influences Cancer Treatment and Outcome

Recent studies have shown that intratumor heterogeneity contributes to drug resistance in advanced disease. Intratumor heterogeneity may foster the selection of a resistant subclone, sometimes detectable prior to treatment. Next-generation sequencing is enabling the phylogenetic reconstruction of a cancer's life history and has revealed different modes of cancer evolution. These studies have shown that cancer evolution is not always stochastic and has certain constraints. Consideration of cancer evolution may enable the better design of clinical trials and cancer therapeutics. In this review, we summarize the different modes of cancer evolution and how this might impact clinical outcomes. Furthermore, we will discuss several therapeutic strategies for managing emergent intratumor heterogeneity.

Genomic characterisation of two cancers of unknown primary cases supports a kidney cancer origin

Cancer of unknown primary (CUP) comprises of 3-5% of new cancer diagnoses in the USA. Diagnostic work up typically includes CT of the chest, abdomen and pelvis, and histopathological review of tissue specimens. These measures are neither sensitive nor specific in determining tissue of origin (ToO) of primary tumours and, therefore, are unable to guide therapy. We present two cases of CUP for which we utilised ultra-deep genomic sequencing to identify the candidate ToO and to propose treatment. Patient 1 presented with metastases involving the lung, lymph nodes and bone. Patient 2 presented with an acute pathological fracture of the T7 vertebral body and metastases involving the bone, lymph nodes and soft tissue. No primary renal mass was found. Sequencing revealed SETD2 and NF2 mutations, and heterozygous loss of the short arm of chromosome 3 (3p). Mutations in conjunction with clinicopathological features strongly support a diagnosis of renal cell carcinoma. Both patients initially responded to mTORC1 inhibition therapy.