Tumor genetic analyses of patients with metastatic renal cell carcinoma and extended benefit from mTOR inhibitor therapy

The role of metabolic reprogramming in kidney cancer

Metabolic reprogramming is a cellular process in which cells modify their metabolic patterns to meet energy requirements, promote proliferation, and enhance resistance to external stressors. This process also introduces new functionalities to the cells. The 'Warburg effect' is a well-studied example of metabolic reprogramming observed during tumorigenesis. Recent studies have shown that kidney cells undergo various forms of metabolic reprogramming following injury. Moreover, metabolic reprogramming plays a crucial role in the progression, prognosis, and treatment of kidney cancer. This review offers a comprehensive examination of renal cancer, metabolic reprogramming, and its implications in kidney cancer. It also discusses recent advancements in the diagnosis and treatment of renal cancer.

Differential expression analysis identifies a prognostically significant extracellular matrix-enriched gene signature in hyaluronan-positive clear cell renal cell carcinoma

Hyaluronan (HA) accumulation in clear cell renal cell carcinoma (ccRCC) is associated with poor prognosis; however, its biology and role in tumorigenesis are unknown. RNA sequencing of 48 HA-positive and 48 HA-negative formalin-fixed paraffin-embedded (FFPE) samples was performed to identify differentially expressed genes (DEG). The DEGs were subjected to pathway and gene enrichment analyses. The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) data and DEGs were used for the cluster analysis. In total, 129 DEGs were identified. HA-positive tumors exhibited enhanced expression of genes related to extracellular matrix (ECM) organization and ECM receptor interaction pathways. Gene set enrichment analysis showed that epithelial-mesenchymal transition-associated genes were highly enriched in the HA-positive phenotype. A protein-protein interaction network was constructed, and 17 hub genes were discovered. Heatmap analysis of TCGA-KIRC data identified two prognostic clusters corresponding to HA-positive and HA-negative phenotypes. These clusters were used to verify the expression levels and conduct survival analysis of the hub genes, 11 of which were linked to poor prognosis. These findings enhance our understanding of hyaluronan in ccRCC.

mTOR eosinophilic renal cell carcinoma: a distinctive tumor characterized by mTOR mutation, loss of chromosome 1, cathepsin-K expression, and response to target therapy

In the spectrum of oncocytic renal neoplasms, a subset of tumors with high-grade-appearing histologic features harboring pathogenic mutations in mammalian target of rapamycin (mTOR) and hitherto clinical indolent behavior has been described. Three cases (2F,1 M) with histologically documented metastases (lymph node, skull, and liver) were retrieved and extensively investigated by immunohistochemistry, FISH, and next-generation sequencing. Tumors were composed of eosinophilic cells with prominent nucleoli (G3 by ISUP/WHO) arranged in solid to nested architecture. Additionally, there were larger cells with perinuclear cytoplasmic shrinkage and sparse basophilic Nissl-like granules, superficially resembling the so-called spider cells of cardiac rhabdomyomas. The renal tumors, including the skull and liver metastases, showed immunoexpression PAX8, CK8-18, and cathepsin-K, and negativity for vimentin. NGS identified mTOR genetic alterations in the three cases, including the skull and liver metastases. One patient was then treated with Everolimus (mTOR inhibitors) with clinical response (metastatic tumor shrinkage). We present a distinct renal tumor characterized by high-grade eosinophilic cells, cathepsin-K immunohistochemical expression, and harboring mTOR gene mutations demonstrating a malignant potential and showing responsiveness to mTOR inhibitors.

Genomic Profiling and Molecular Characterization of Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) treatment has undergone three major paradigm shifts in recent years, first with the introduction of molecular targeted therapies, then with immune checkpoint inhibitors, and, more recently, with immune-based combinations. However, to date, molecular predictors of response to targeted agents have not been identified for ccRCC. The WHO 2022 classification of renal neoplasms introduced the molecularly defined RCC class, which is a first step in the direction of a better molecular profiling of RCC. We reviewed the literature data on known genomic alterations of clinical interest in ccRCC, discussing their prognostic and predictive role. In particular, we explored the role of VHL, mTOR, chromatin modulators, DNA repair genes, cyclin-dependent kinases, and tumor mutation burden. RCC is a tumor whose pivotal genomic alterations have pleiotropic effects, and the interplay of these effects determines the tumor phenotype and its clinical behavior. Therefore, it is difficult to find a single genomic predictive factor, but it is more likely to identify a signature of gene alterations that could impact prognosis and response to specific treatment. To accomplish this task, the interpolation of large amounts of clinical and genomic data is needed. Nevertheless, genomic profiling has the potential to change real-world clinical practice settings.

PI3K signaling-regulated metabolic reprogramming: From mechanism to application

Oncogenic signaling involved in tumor metabolic reprogramming. Tumorigenesis was not only determined by the mutations or deletion of oncogenes but also accompanied by the reprogramming of cellular metabolism. Metabolic alterations play a crucial regulatory role in the development and progression of tumors. Oncogenic PI3K/AKT signaling mediates the metabolic switch in cancer cells and immune cells in the tumor microenvironment. PI3K/AKT and its downstream effector branch off and connect to multiple steps of metabolism, such as glucose, lipids, and amino acids. Thus, PI3K inhibitor could effectively regulate metabolic pathway and impede the oncogenic process and some key metabolic proteins or critical enzymes also constitute biomarkers for tumor diagnosis and treatment. In the current review, we summarize the significant effect of PI3K/AKT signaling toward tumor metabolism, it enables us to obtain the better understanding for this interaction and develop more effective therapeutic strategies targeting cancer cell metabolism.

Renal Carcinoma and Angiogenesis: Therapeutic Target and Biomarkers of Response in Current Therapies

Due to the aberrant hypervascularization and the high immune infiltration of renal tumours, current therapeutic regimens of renal cell carcinoma (RCC) target angiogenic or immunosuppressive pathways or both. Tumour angiogenesis plays an essential role in tumour growth and immunosuppression. Indeed, the aberrant vasculature promotes hypoxia and can also exert immunosuppressive functions. In addition, pro-angiogenic factors, including VEGF-A, have an immunosuppressive action on immune cells. Despite the progress of treatments in RCC, there are still non responders or acquired resistance. Currently, no biomarkers are used in clinical practice to guide the choice between the different available treatments. Considering the role of angiogenesis in RCC, angiogenesis-related markers are interesting candidates. They have been studied in the response to antiangiogenic drugs (AA) and show interest in predicting the response. They have been less studied in immunotherapy alone or combined with AA. In this review, we will discuss the role of angiogenesis in tumour growth and immune escape and the place of angiogenesis-targeted biomarkers to predict response to current therapies in RCC.

Clinical trial design in the era of precision medicine

Recent rapid biotechnological breakthroughs have led to the identification of complex and unique molecular features that drive malignancies. Precision medicine has exploited next-generation sequencing and matched targeted therapy/immunotherapy deployment to successfully transform the outlook for several fatal cancers. Tumor and liquid biopsy genomic profiling and transcriptomic, immunomic, and proteomic interrogation can now all be leveraged to optimize therapy. Multiple new trial designs, including basket and umbrella trials, master platform trials, and N-of-1 patient-centric studies, are beginning to supplant standard phase I, II, and III protocols, allowing for accelerated drug evaluation and approval and molecular-based individualized treatment. Furthermore, real-world data, as well as exploitation of digital apps and structured observational registries, and the utilization of machine learning and/or artificial intelligence, may further accelerate knowledge acquisition. Overall, clinical trials have evolved, shifting from tumor type-centered to gene-directed and histology-agnostic trials, with innovative adaptive designs and personalized combination treatment strategies tailored to individual biomarker profiles. Some, but not all, novel trials now demonstrate that matched therapy correlates with superior outcomes compared to non-matched therapy across tumor types and in specific cancers. To further improve the precision medicine paradigm, the strategy of matching drugs to patients based on molecular features should be implemented earlier in the disease course, and cancers should have comprehensive multi-omic (genomics, transcriptomics, proteomics, immunomic) tumor profiling. To overcome cancer complexity, moving from drug-centric to patient-centric individualized combination therapy is critical. This review focuses on the design, advantages, limitations, and challenges of a spectrum of clinical trial designs in the era of precision oncology.

Genomic signature of MTOR could be an immunogenicity marker in human colorectal cancer

Background

The mTOR signaling pathway plays an important role in cancer. As a master regulator, the status of MTOR affects pathway activity and the efficacy of mTOR inhibitor therapy. However, little research has been performed to explore MTOR in colorectal cancer (CRC).

Methods

In this study, gene expression and clinical data were analyzed using The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Signaling pathways related to MTOR in CRC were identified by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA). Somatic mutation data were downloaded from TCGA and analyzed using the maftools R package. Tumor Immune Estimation Resource (TIMER) and CIBERSORT were used to analyze correlations between MTOR and tumor-infiltrating immune cells (TIICs). Finally, we detected MTOR mutations in a CRC cohort from our database using whole-exome sequencing.

Results

We found that MTOR was overexpressed in Asian CRC patients and associated with a poor prognosis. Enrichment analysis showed that MTOR was involved in metabolism, cell adhesion, and translation pathways in CRC. High MTOR expression was correlated with high tumor mutation burden (TMB) and several TIICs. Finally, we found that the mTOR signaling pathway was activated in CRC lines characterized by microsatellite instability (MSI), and the frequency of MTOR mutations was higher in MSI-high (MSI-H) patients than in microsatellite stable (MSS) patients.

Conclusions

MTOR may represent a comprehensive indicator of prognosis and immunological status in CRC. The genomic signatures of MTOR may provide guidance for exploring the role of mTOR inhibitors in CRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09901-w.

Functionalized Lineage Tracing Can Enable the Development of Homogenization-Based Therapeutic Strategies in Cancer

The therapeutic landscape across many cancers has dramatically improved since the introduction of potent targeted agents and immunotherapy. Nonetheless, success of these approaches is too often challenged by the emergence of therapeutic resistance, fueled by intratumoral heterogeneity and the immense evolutionary capacity inherent to cancers. To date, therapeutic strategies have attempted to outpace the evolutionary tempo of cancer but frequently fail, resulting in lack of tumor response and/or relapse. This realization motivates the development of novel therapeutic approaches which constrain evolutionary capacity by reducing the degree of intratumoral heterogeneity prior to treatment. Systematic development of such approaches first requires the ability to comprehensively characterize heterogeneous populations over the course of a perturbation, such as cancer treatment. Within this context, recent advances in functionalized lineage tracing approaches now afford the opportunity to efficiently measure multimodal features of clones within a tumor at single cell resolution, enabling the linkage of these features to clonal fitness over the course of tumor progression and treatment. Collectively, these measurements provide insights into the dynamic and heterogeneous nature of tumors and can thus guide the design of homogenization strategies which aim to funnel heterogeneous cancer cells into known, targetable phenotypic states. We anticipate the development of homogenization therapeutic strategies to better allow for cancer eradication and improved clinical outcomes.

Biomarkers of everolimus efficacy in breast cancer therapy

OBJECTIVE

Everolimus is an inhibitor of serine/ threonine kinase mTOR. The drug is approved for the treatment of metastatic ER positive, HER2 negative breast cancers and benefits a subset of patients with these breast cancers in combination with hormonal therapies. Despite extensive efforts, no additional predictive biomarkers to guide therapeutic decisions for everolimus have been introduced in clinical practice.

DATA SOURCES

This paper discusses predictive biomarkers for everolimus efficacy in breast cancer. A search of the medline and web of science databases was performed using the words "everolimus" and "biomarkers". References of retrieved articles were manually scanned for additional relevant articles.

DATA SUMMARY

Everolimus benefits a subset of patients with metastatic ER positive, HER2 negative breast cancers in combination with hormonal therapies. Despite extensive efforts no additional predictive biomarkers to guide therapeutic decisions for everolimus therapy have been confirmed for use in clinical practice. However, promising biomarker leads for everolimus efficacy in breast cancer have been suggested and include expression of proteins in the mTOR pathway in ER positive, HER2 negative breast cancers. In HER2 positive cancers PIK3CA mutations, and PTEN expression loss are prognostic. Other clinical predictive biomarkers with more limited data include characteristics derived from whole genome sequencing, subsets of circulating leukocytes and changes in Standardized Uptake Values (SUV) of Positron Emission Tomography (PET) scans.

CONCLUSIONS

Putative predictive biomarkers for everolimus efficacy in breast cancer patients, both genomic and clinical, deserve further study and could lead to a better selection of responsive patients.

Spatial patterns of tumour growth impact clonal diversification in a computational model and the TRACERx Renal study

Genetic intra-tumour heterogeneity fuels clonal evolution, but our understanding of clinically relevant clonal dynamics remain limited. We investigated spatial and temporal features of clonal diversification in clear cell renal cell carcinoma through a combination of modelling and real tumour analysis. We observe that the mode of tumour growth, surface or volume, impacts the extent of subclonal diversification, enabling interpretation of clonal diversity in patient tumours. Specific patterns of proliferation and necrosis explain clonal expansion and emergence of parallel evolution and microdiversity in tumours. In silico time-course studies reveal the appearance of budding structures before detectable subclonal diversification. Intriguingly, we observe radiological evidence of budding structures in early-stage clear cell renal cell carcinoma, indicating that future clonal evolution may be predictable from imaging. Our findings offer a window into the temporal and spatial features of clinically relevant clonal evolution.

The Potential and Limitations of Precision Oncology: Lessons Learned from Whole-Exome Sequencing in an Exceptional Response to Everolimus in Advanced Renal Cell Carcinoma

Through elucidating the genetic mechanisms of drug sensitivity, precision medicine aims to improve patient selection and response to therapy. Exceptional responders are patients that exhibit exquisite and durable responses to targeted therapy, providing a rare opportunity to identify the molecular basis of drug sensitivity. We identified an exceptional responder to everolimus, an oral inhibitor of the mammalian target of rapamycin (mTOR) pathway, in a patient with advanced renal cell carcinoma. Through whole-exome sequencing on pretreatment and metastatic tumor DNA, we identified alterations in several mTOR pathway genes, with several mutations implicated in mTOR activation. Importantly, these alterations are currently not included in commercially available next-generation sequencing panels, suggesting that precision medicine is still limited in its ability to predict responses to mTOR-targeted therapies. Further research to discover and validate predictive biomarkers of response to everolimus and other targeted therapies is urgently needed. Given the rarity of patients with exceptional responses to targeted agents, cooperative efforts to understand the molecular basis for these phenotypes are essential.

Playing the Devil's Advocate: Should We Give a Second Chance to mTOR Inhibition in Renal Clear Cell Carcinoma? - ie Strategies to Revert Resistance to mTOR Inhibitors

In the last decade, the inhibition of the mechanistic target of Rapamycin (mTOR) in renal clear cell carcinoma (RCC) has disappointed the clinician's expectations. Many clinical trials highlighted the low efficacy and unmanageable safety profile of first-generation mTOR inhibitors (Rapalogs), thus limiting their use in the clinical practice only to those patients who already failed several therapy lines. In this review, we analyze the major resistance mechanisms that undermine the efficacy of this class of drugs. Moreover, we describe some of the possible strategies to overcome the mechanisms of resistance and their clinical experimentation, with particular focus on novel mTOR inhibitors and the combinations of mTOR inhibitors and other anti-cancer drugs.

Clonal Architecture and Evolutionary Dynamics in Acute Myeloid Leukemias

Acute myeloid leukemias (AML) results from the accumulation of genetic and epigenetic alterations, often in the context of an aging hematopoietic environment. The development of high-throughput sequencing-and more recently, of single-cell technologies-has shed light on the intratumoral diversity of leukemic cells. Taking AML as a model disease, we review the multiple sources of genetic, epigenetic, and functional heterogeneity of leukemic cells and discuss the definition of a leukemic clone extending its definition beyond genetics. After introducing the two dimensions contributing to clonal diversity, namely, richness (number of leukemic clones) and evenness (distribution of clone sizes), we discuss the mechanisms at the origin of clonal emergence (mutation rate, number of generations, and effective size of the leukemic population) and the causes of clonal dynamics. We discuss the possible role of neutral drift, but also of cell-intrinsic and -extrinsic influences on clonal fitness. After reviewing available data on the prognostic role of genetic and epigenetic diversity of leukemic cells on patients' outcome, we discuss how a better understanding of AML as an evolutionary process could lead to the design of novel therapeutic strategies in this disease.

Metabolic reprogramming in renal cancer: Events of a metabolic disease

Recent studies have established that tumors can reprogram the pathways involved in nutrient uptake and metabolism to withstand the altered biosynthetic, bioenergetics and redox requirements of cancer cells. This phenomenon is called metabolic reprogramming, which is promoted by the loss of tumor suppressor genes and activation of oncogenes. Because of alterations and perturbations in multiple metabolic pathways, renal cell carcinoma (RCC) is sometimes termed as a "metabolic disease". The majority of metabolic reprogramming in renal cancer is caused by the inactivation of von Hippel-Lindau (VHL) gene and activation of the Ras-PI3K-AKT-mTOR pathway. Hypoxia-inducible factor (HIF) and Myc are other important players in the metabolic reprogramming of RCC. All types of RCCs are associated with reprogramming of glucose and fatty acid metabolism and the tricarboxylic acid (TCA) cycle. Metabolism of glutamine, tryptophan and arginine is also reprogrammed in renal cancer to favor tumor growth and oncogenesis. Together, understanding these modifications or reprogramming of the metabolic pathways in detail offer ample opportunities for the development of new therapeutic targets and strategies, discovery of biomarkers and identification of effective tumor detection methods.

Clinical cancer genomic profiling

Technological innovation and rapid reduction in sequencing costs have enabled the genomic profiling of hundreds of cancer-associated genes as a component of routine cancer care. Tumour genomic profiling can refine cancer subtype classification, identify which patients are most likely to benefit from systemic therapies and screen for germline variants that influence heritable cancer risk. Here, we discuss ongoing efforts to enhance the clinical utility of tumour genomic profiling by integrating tumour and germline analyses, characterizing allelic context and identifying mutational signatures that influence therapy response. We also discuss the potential clinical utility of more comprehensive whole-genome and whole-transcriptome sequencing and ultra-sensitive cell-free DNA profiling platforms, which allow for minimally invasive, serial analyses of tumour-derived DNA in blood.

Prevalence and Landscape of Actionable Genomic Alterations in Renal Cell Carcinoma

PURPOSE

We report our experience with next-generation sequencing to characterize the landscape of actionable genomic alterations in renal cell carcinoma (RCC).

EXPERIMENTAL DESIGN

A query of our institutional clinical sequencing database (MSK-IMPACT) was performed that included tumor samples from 38,468 individuals across all cancer types. Somatic variations were annotated using a precision knowledge database (OncoKB) and the available clinical data stratified by level of evidence. Alterations associated with response to immune-checkpoint blockade (ICB) were analyzed separately; these included DNA mismatch repair (MMR) gene alterations, tumor mutational burden (TMB), and microsatellite instability (MSI). Data from The Cancer Genome Atlas (TCGA) consortium as well as public data from several clinical trials in metastatic RCC were used for validation purposes. Multiregional sequencing data from the TRAcking Cancer Evolution through Therapy (TRACERx) RENAL cohort were used to assess the clonality of somatic mutations.

RESULTS

Of the 753 individuals with RCC identified in the MSK-IMPACT cohort, 115 showed evidence of targetable alterations, which represented a prevalence of 15.3% [95% confidence interval (CI), 12.7%-17.8%). When stratified by levels of evidence, the alterations identified corresponded to levels 2 (11.3%), 3A (5.2%), and 3B (83.5%). A low prevalence was recapitulated in the TCGA cohort at 9.1% (95% CI, 6.9%-11.2%). Copy-number variations predominated in papillary RCC tumors, largely due to amplifications in the MET gene. Notably, higher rates of actionability were found in individuals with metastatic disease (stage IV) compared with those with localized disease (OR, 2.50; 95% CI, 1.16-6.16; Fisher's P = 0.01). On the other hand, the prevalence of alterations associated with response to ICB therapy was found to be approximately 5% in both the MSK-IMPACT and TCGA cohorts and no associations with disease stage were identified (OR, 1.35; 95% CI, 0.46-5.40; P = 0.8). Finally, multiregional sequencing revealed that the vast majority of actionable mutations occurred later during tumor evolution and were only present subclonally in RCC tumors.

CONCLUSIONS

RCC harbors a low prevalence of clinically actionable alterations compared with other tumors and the evidence supporting their clinical use is limited. These aberrations were found to be more common in advanced disease and seem to occur later during tumor evolution. Our study provides new insights on the role of targeted therapies for RCC and highlights the need for additional research to improve treatment selection using genomic profiling.

Gene Expression Signature Correlates with Outcomes in Metastatic Renal Cell Carcinoma Patients Treated with Everolimus Alone or with a Vascular Disrupting Agent

Everolimus monotherapy use for metastatic renal cell carcinoma (mRCC) has diminished due to recent approvals of immune checkpoint and VEGF inhibitors. We hypothesized that gene expression associated with everolimus benefit may provide rationale to select appropriate patients. To address this hypothesis, tumors from a phase I/II trial that compared everolimus alone or with BNC105P, a vascular disrupting agent, were profiled using Nanostring as a discovery cohort. A phase III trial (CheckMate 025) was used for validation. Clinical benefit (CB) was defined as response or stable disease for ≥6 months. A propensity score covariate adjustment was used, and model discrimination performance was assessed using the area under the ROC curve (AUC). In a discovery cohort of 82 patients, 35 (43%) were treated with everolimus alone and 47 (57%) received everolimus + BNC105P. Median PFS (mPFS) was 4.9 (95% CI, 2.8-6.2) months. A four-gene signature (ASXL1, DUSP6, ERCC2, and HSPA6) correlated with CB with everolimus ± BNC105P [AUC, 86.9% (95% CI, 79.2-94.7)]. This was validated in 130 patients from CheckMate 025 treated with everolimus [AUC, 60.2% (95% CI, 49.7-70.7)]. Among 43 patients (52.4%) with low expression of an 18-gene signature, everolimus + BNC105P was associated with significantly longer mPFS compared with everolimus alone (10.4 vs. 6.9 months; HR, 0.49; 95% CI, 0.24-1.002; P = 0.047). These signatures warrant further validation to select patients who may benefit from everolimus alone or with a vascular disrupting agent.

Modeling Neoplastic Growth in Renal Cell Carcinoma and Polycystic Kidney Disease

Renal cell carcinoma (RCC) and autosomal dominant polycystic kidney disease (ADPKD) share several characteristics, including neoplastic cell growth, kidney cysts, and limited therapeutics. As well, both exhibit impaired vasculature and compensatory VEGF activation of angiogenesis. The PI3K/AKT/mTOR and Ras/Raf/ERK pathways play important roles in regulating cystic and tumor cell proliferation and growth. Both RCC and ADPKD result in hypoxia, where HIF-α signaling is activated in response to oxygen deprivation. Primary cilia and altered cell metabolism may play a role in disease progression. Non-coding RNAs may regulate RCC carcinogenesis and ADPKD through their varied effects. Drosophila exhibits remarkable conservation of the pathways involved in RCC and ADPKD. Here, we review the progress towards understanding disease mechanisms, partially overlapping cellular and molecular dysfunctions in RCC and ADPKD and reflect on the potential for the agile Drosophila genetic model to accelerate discovery science, address unresolved mechanistic aspects of these diseases, and perform rapid pharmacological screens.

Machine Learning as a Precision-Medicine Approach to Prescribing COVID-19 Pharmacotherapy with Remdesivir or Corticosteroids

Purpose: Coronavirus disease–2019 (COVID-19) continues to be a global threat and remains a significant cause of hospitalizations. Recent clinical guidelines have supported the use of corticosteroids or remdesivir in the treatment of COVID-19. However, uncertainty remains about which patients are most likely to benefit from treatment with either drug; such knowledge is crucial for avoiding preventable adverse effects, minimizing costs, and effectively allocating resources. This study presents a machine-learning system with the capacity to identify patients in whom treatment with a corticosteroid or remdesivir is associated with improved survival time.

Methods: Gradient-boosted decision-tree models used for predicting treatment benefit were trained and tested on data from electronic health records dated between December 18, 2019, and October 18, 2020, from adult patients (age ≥18 years) with COVID-19 in 10 US hospitals. Models were evaluated for performance in identifying patients with longer survival times when treated with a corticosteroid versus remdesivir. Fine and Gray proportional-hazards models were used for identifying significant findings in treated and nontreated patients, in a subset of patients who received supplemental oxygen, and in patients identified by the algorithm. Inverse probability-of-treatment weights were used to adjust for confounding. Models were trained and tested separately for each treatment.

Findings: Data from 2364 patients were included, with men comprising slightly more than 50% of the sample; 893 patients were treated with remdesivir, and 1471 were treated with a corticosteroid. After adjustment for confounding, neither corticosteroids nor remdesivir use was associated with increased survival time in the overall population or in the subpopulation that received supplemental oxygen. However, in the populations identified by the algorithms, both corticosteroids and remdesivir were significantly associated with an increase in survival time, with hazard ratios of 0.56 and 0.40, respectively (both, P = 0.04).

Implications: Machine-learning methods have the capacity to identify hospitalized patients with COVID-19 in whom treatment with a corticosteroid or remdesivir is associated with an increase in survival time. These methods may help to improve patient outcomes and allocate resources during the COVID-19 crisis.

Genetic and Non-Genetic Mechanisms Underlying Cancer Evolution

Simple Summary

Our manuscript summarizes the up-to-date data on the complex and dynamic nature of adaptation mechanisms and evolutionary processes taking place during cancer initiation, development and progression. Although for decades cancer has been viewed as a process governed by genetic mechanisms, it is becoming more and more clear that non-genetic mechanisms may play an equally important role in cancer evolution. In this review, we bring together these fundamental concepts and discuss how those tightly interconnected mechanisms lead to the establishment of highly adaptive quickly evolving cancers. Furthermore, we argue that in depth understanding of cancer progression from the evolutionary perspective may allow the prediction and direction of the evolutionary path of cancer populations towards drug sensitive phenotypes and thus facilitate the development of more effective anti-cancer approaches.

Abstract

Cancer development can be defined as a process of cellular and tissular microevolution ultimately leading to malignancy. Strikingly, though this concept has prevailed in the field for more than a century, the precise mechanisms underlying evolutionary processes occurring within tumours remain largely uncharacterized and rather cryptic. Nevertheless, although our current knowledge is fragmentary, data collected to date suggest that most tumours display features compatible with a diverse array of evolutionary paths, suggesting that most of the existing macro-evolutionary models find their avatar in cancer biology. Herein, we discuss an up-to-date view of the fundamental genetic and non-genetic mechanisms underlying tumour evolution with the aim of concurring into an integrated view of the evolutionary forces at play throughout the emergence and progression of the disease and into the acquisition of resistance to diverse therapeutic paradigms. Our ultimate goal is to delve into the intricacies of genetic and non-genetic networks underlying tumour evolution to build a framework where both core concepts are considered non-negligible and equally fundamental.

Mechanistic Target of Rapamycin Inhibitors in Renal Cell Carcinoma: Potential, Limitations, and Perspectives

Several elements highlight the importance of the mechanistic target of rapamycin (mTOR) in the biology of renal cell carcinoma (RCC). mTOR signaling pathway is indeed frequently activated in RCC, inducing cancer cell proliferation and survival. In addition, mTOR promotes tumor angiogenesis and regulates the expression of hypoxia-inducible factors that play an important role in a subset of RCC. Despite mTOR protumorigenic effects, mTOR inhibitors have failed to provide long-lasting anticancer benefits in RCC patients, highlighting the need to readdress their role in the treatment of RCC. This review aims to present the rationale and limitations of targeting mTOR in RCC. Future roles of mTOR inhibitors in the treatment of RCC are also discussed, in particular in the context of immunotherapies.

Combination treatment of copanlisib and gemcitabine in relapsed/refractory PTCL (COSMOS): an open-label phase I/II trial

BACKGROUND

Current treatment options for peripheral T-cell lymphomas (PTCLs) in the relapsed/refractory setting are limited and demonstrate modest response rates with rare achievement of complete response (CR).

PATIENTS AND METHODS

This phase I/II study (NCT03052933) investigated the safety and efficacy of copanlisib, a phosphatidylinositol 3-kinase-α/-δ inhibitor, in combination with gemcitabine in 28 patients with relapsed/refractory PTCL. Patients received escalating doses of intravenous copanlisib on days 1, 8, and 15, administered concomitantly with fixed-dose gemcitabine (1000 mg/m² on days 1 and 8) in 28-day cycles.

RESULTS

Dose-limiting toxicity was not observed in the dose-escalation phase and 60 mg copanlisib was selected for phase II evaluation. Twenty-five patients were enrolled in phase II of the study. Frequent grade ≥3 adverse events (AEs) included transient hyperglycemia (57%), neutropenia (45%), thrombocytopenia, (37%), and transient hypertension (19%). However, AEs were manageable, and none were fatal. The overall response rate was 72% with a CR rate of 32%. Median duration of response was 8.2 months, progression-free survival was 6.9 months, and median overall survival was not reached. Combination treatment produced a greater CR rate in patients with angioimmunoblastic T-cell lymphoma than those with PTCL-not otherwise specified (55.6% versus 15.4%, respectively, P = 0.074) and progression-free survival was significantly longer (13.0 versus 5.1 months, respectively, P = 0.024). In an exploratory gene mutation analysis of 24 tumor samples, TSC2 mutation was present in 25% of patients and occurred exclusively in responders.

CONCLUSION

The combination of copanlisib and gemcitabine is a safe and effective treatment option in relapsed/refractory PTCLs and represents an important new option for therapy in this rare group of patients.

Features of increased malignancy in eosinophilic clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common form of renal cancer. Due to inactivation of the von Hippel-Lindau tumour suppressor, the hypoxia-inducible transcription factors (HIFs) are constitutively activated in these tumours, resulting in a pseudo-hypoxic phenotype. The HIFs induce the expression of genes involved in angiogenesis and cell survival, but they also reset the cellular metabolism to protect cells from oxygen and nutrient deprivation. ccRCC tumours are highly vascularized and the cytoplasm of the cancer cells is filled with lipid droplets and glycogen, resulting in the histologically distinctive pale (clear) cytoplasm. Intratumoural heterogeneity may occur, and in some tumours, areas with granular, eosinophilic cytoplasm are found. Little is known regarding these traits and how they relate to the coexistent clear cell component, yet eosinophilic ccRCC is associated with higher grade and clinically more aggressive tumours. In this study, we have for the first time performed RNA sequencing comparing histologically verified clear cell and eosinophilic areas from ccRCC tissue, aiming to analyse the characteristics of these cell types. Findings from RNA sequencing were confirmed by immunohistochemical staining of biphasic ccRCC. We found that the eosinophilic phenotype displayed a higher proliferative drive and lower differentiation, and we confirmed a correlation to tumours of higher stage. We further identified mutations of the tumour suppressor p53 (TP53) exclusively in the eosinophilic ccRCC component, where mTORC1 activity was also elevated. Also, eosinophilic areas were less vascularized, yet harboured more abundant infiltrating immune cells. The cytoplasm of clear cell ccRCC cells was filled with lipids but had very low mitochondrial content, while the reverse was found in eosinophilic tissue. We herein suggest possible transcriptional mechanisms behind these phenomena. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Is Machine Learning a Better Way to Identify COVID-19 Patients Who Might Benefit from Hydroxychloroquine Treatment?-The IDENTIFY Trial

Therapeutic agents for the novel coronavirus disease 2019 (COVID-19) have been proposed, but evidence supporting their use is limited. A machine learning algorithm was developed in order to identify a subpopulation of COVID-19 patients for whom hydroxychloroquine was associated with improved survival; this population might be relevant for study in a clinical trial. A pragmatic trial was conducted at six United States hospitals. We enrolled COVID-19 patients that were admitted between 10 March and 4 June 2020. Treatment was not randomized. The study endpoint was mortality; discharge was a competing event. Hazard ratios were obtained on the entire population, and on the subpopulation indicated by the algorithm as suitable for treatment. A total of 290 patients were enrolled. In the subpopulation that was identified by the algorithm, hydroxychloroquine was associated with a statistically significant (p = 0.011) increase in survival (adjusted hazard ratio 0.29, 95% confidence interval (CI) 0.11–0.75). Adjusted survival among the algorithm indicated patients was 82.6% in the treated arm and 51.2% in the arm not treated. No association between treatment and mortality was observed in the general population. A 31% increase in survival at the end of the study was observed in a population of COVID-19 patients that were identified by a machine learning algorithm as having a better outcome with hydroxychloroquine treatment. Precision medicine approaches may be useful in identifying a subpopulation of COVID-19 patients more likely to be proven to benefit from hydroxychloroquine treatment in a clinical trial.

Combination drug regimens for metastatic clear cell renal cell carcinoma

Renal cell carcinomas (RCC) make up about 90% of kidney cancers, of which 80% are of the clear cell subtype. About 20% of patients are already metastatic at the time of diagnosis. Initial treatment is often cytoreductive nephrectomy, but systemic therapy is required for advanced RCC. Single agent targeted therapies are moderately toxic and only somewhat effective, leading to development of immunotherapies and combination therapies. This review identifies limitations of monotherapies for metastatic renal cell carcinoma, discusses recent advances in combination therapies, and highlights therapeutic options under development. The goal behind combining various modalities of systemic therapy is to potentiate a synergistic antitumor effect. However, combining targeted therapies may cause increased toxicity. The initial attempts to create therapeutic combinations based on inhibition of the vascular endothelial growth factor or mammalian target of rapamycin pathways were largely unsuccessful in achieving a profile of increased synergy without increased toxicity. To date, five combination therapies have been approved by the U.S. Food and Drug Administration, with the most recently approved therapies being a combination of checkpoint inhibition plus targeted therapy. Several other combination therapies are under development, including some in the phase 3 stage. The new wave of combination therapies for metastatic RCC has the potential to increase response rates and improve survival outcomes while maintaining tolerable side effect profiles.

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.

Update on Circulating Tumor Cells in Genitourinary Tumors with Focus on Prostate Cancer

Current developments in the treatment of genitourinary tumors underline the unmet clinical need for biomarkers to improve decision-making in a challenging clinical setting. The detection of circulating tumor cells (CTCs) has become one of the most exciting and important new approaches to identifying biomarkers at different stages of disease in a non-invasive way. Potential applications of CTCs include monitoring treatment efficacy and early detection of progression, selecting tailored therapies, as well as saving treatment costs. However, despite the promising implementation of CTCs in a clinical scenario, the isolation and characterization of these cells for molecular studies remain expensive with contemporary platforms, and significant technical challenges still need to be overcome. This updated, critical review focuses on the state of CTCs in patients with genitourinary tumor with focus on prostate cancer, discussing technical issues, main clinical results and hypothesizing potential future perspectives in clinical scenarios.

Significance of PI3K signalling pathway in clear cell renal cell carcinoma in relation to VHL and HIF status

Renal cell carcinoma (RCC) includes diverse tumour types characterised by various genetic abnormalities. The genetic changes, like mutations, deletions and epigenetic alterations, play a crucial role in the modification of signalling networks, tumour pathogenesis and prognosis. The most prevalent RCC type, clear cell RCC (ccRCC), is asymptomatic in the early stages and has a poorer prognosis compared with the papillary and the chromophobe types RCCs. Generally, ccRCC is refractory to chemotherapy and radiation therapy. Loss of von Hippel-Lindau (VHL) gene and upregulation of hypoxia-inducible factors (HIF), the signature of most sporadic ccRCC, promote multiple growth factors. Hence, VHL/HIF and a variety of pathways, including phosphatase and TEnsin homolog on chromosome 10/phosphatidylinositol-3-kinase (PI3K)/AKT, are closely connected and contribute to the ontogeny of ccRCC. In the recent decade, multiple targeting agents have been developed based on blocking major signalling pathways directly or indirectly involved in ccRCC tumour progression, metastasis, angiogenesis and survival. However, most of these drugs have limitations; either metastatic ccRCC develops resistance to these agents, or despite blocking receptors, tumour cells use alternate signalling pathways. This review compiles the state of knowledge about the PI3K/AKT signalling pathway confined to ccRCC and its cross-talks with VHL/HIF pathway.

Anti-angiogenesis and Immunotherapy: Novel Paradigms to Envision Tailored Approaches in Renal Cell-Carcinoma

Although decision making strategy based on clinico-histopathological criteria is well established, renal cell carcinoma (RCC) represents a spectrum of biological ecosystems characterized by distinct genetic and molecular alterations, diverse clinical courses and potential specific therapeutic vulnerabilities. Given the plethora of drugs available, the subtype-tailored treatment to RCC subtype holds the potential to improve patient outcome, shrinking treatment-related morbidity and cost. The emerging knowledge of the molecular taxonomy of RCC is evolving, whilst the antiangiogenic and immunotherapy landscape maintains and reinforces their potential. Although several prognostic factors of survival in patients with RCC have been described, no reliable predictive biomarkers of treatment individual sensitivity or resistance have been identified. In this review, we summarize the available evidence able to prompt more precise and individualized patient selection in well-designed clinical trials, covering the unmet need of medical choices in the era of next-generation anti-angiogenesis and immunotherapy.

Identification of circulating tumor DNA using a targeted 545-gene next generation sequencing panel in patients with gastric cancer

Gastric cancer (GC) is characterized by unique genetic aberrations. Some of these mutations may be used to predict tumor prognosis or to guide patient therapy. Cell-free circulating tumor DNA (ctDNA) has been considered a promising alternative to biopsy to identify genome aberrations. However, no standardized methods to detect ctDNA variations in patients with GC are currently available. In the present study, the targeted sequencing of 545 genes was used to identify somatic alterations in tissues and matched plasma samples of nine patients with GC. Driver gene mutations were detected in matched tissues and plasma ctDNA. The mutated reads concordance rate of ctDNA in GC tissues with matched tissues was 45%. A true positive copy number gain of human epidermal growth factor receptor 2 in plasma from patients with GC was identified. Furthermore, the ctDNA fraction in plasma cell-free DNA (cfDNA) was positively correlated with metastasis lymph node number and with lactate dehydrogenase level. In conclusion, results from the present study suggested that targeted sequencing of plasma ctDNA may be considered a potential option for the clinical monitoring of GC.

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.

Sunitinib Versus Sorafenib as Initial Targeted Therapy for mCC-RCC With Favorable/Intermediate Risk: Multicenter Randomized Trial CROSS-J-RCC

PURPOSE

The present study compared the efficacy of sunitinib and sorafenib as first-line treatment of metastatic clear cell renal cell carcinoma (mCC-RCC) with favorable or intermediate Memorial Sloan Kettering Cancer Center (MSKCC) risk.

PATIENTS AND METHODS

Treatment-naive patients with mCC-RCC were randomized to receive open-label sunitinib followed by sorafenib (SU/SO) or sorafenib followed by sunitinib (SO/SU). The primary endpoint was first-line progression-free survival (PFS). The secondary endpoints were total PFS and overall survival (OS).

RESULTS

Of the 124 patients enrolled at 39 institutions from February 2010 to July 2012, 120 were evaluated. The median first-line PFS duration was 8.7 and 7.0 months in the SU/SO and SO/SU groups, respectively (hazard ratio [HR], 0.67; 95% confidence interval [CI], 0.42-1.08). The total PFS and OS were not significantly different between the SU/SO and SO/SU groups (27.8 and 22.6 months; HR, 0.73; 95% CI, 0.428-1.246; and 38.4 and 30.9 months; HR, 0.934; 95% CI, 0.588-1.485, respectively). The subgroup analysis revealed that the total PFS with SU/SO was superior to the total PFS with SO/SU in the patients with favorable MSKCC risk and those with < 5 metastatic sites). SO/SU was superior to SU/SO for patients without previous nephrectomy.

CONCLUSIONS

No statistically significant differences were found in first-line PFS, total PFS, or OS between the 2 treatment arms (ClinicalTrials.gov identifier, NCT01481870).

MicroRNAs as potential predictors of extreme response to tyrosine kinase inhibitors in renal cell cancer

BACKGROUND

MicroRNAs play an important role as modulators of gene expression in several biological processes and are closely related to development and cell differentiation regulation. Previous works have revealed a potential predictive role for miRNAs in different tumor types. This study aims to analyze the ability of miRNAs in segregating metastatic renal cell carcinoma patients according to their responses to tyrosine kinase inhibitors (TKIs).

METHODS

Extreme responders were considered in the study and were defined as those patients that either had a long-term response (LR) (progression-free survival ˃11 months) or those that were primary refractory (PR) (progression as best response). The expression of 754 miRNAs was analyzed in tumor tissue of these 2 sets of patients.

RESULTS

In a study cohort (n = 15) 4 miRNAs were significantly associated with patient response and differentially expressed in PR vs. LR (up-regulated in PR vs. LR: miR-425-5p, down-regulated in PR vs. LR: miR-139-3p, let-7d and let-7e). Further analysis in a validation cohort (n = 36) revealed similar results.

CONCLUSION

The present data strength the potential role of miRNAs as a tool to predict treatment outcomes in patients with metastatic renal cell carcinoma treated with TKIs.

Prognostic and Predictive Value of PBRM1 in Clear Cell Renal Cell Carcinoma

Renal cell carcinoma (RCC) is the most frequent kidney solid tumor, the clear cell RCC (ccRCC) being the major histological subtype. The probability of recurrence and the clinical behavior of ccRCC will greatly depend on the different clinical and histopathological features, already incorporated to different scoring systems, and on the genomic landscape of the tumor. In this sense, ccRCC has for a long time been known to be associated to the biallelic inactivation of Von Hippel-Lindau (VHL) gene which causes aberrant hypoxia inducible factor (HIF) accumulation. Recently, next generation-sequencing technologies have provided the bases for an in-depth molecular characterization of ccRCC, identifying additional recurrently mutated genes, such as PBRM1 (≈40-50%), SETD2 (≈12%), or BAP1 (≈10%). PBRM1, the second most common mutated gene in ccRCC after VHL, is a component of the SWI/SNF chromatin remodeling complex. Different studies have investigated the biological consequences and the potential role of PBRM1 alterations in RCC prognosis and as a drug response modulator, although some results are contradictory. In the present article, we review the current evidence on PBRM1 as potential prognostic and predictive marker in both localized and metastatic RCC.

Targeting mTOR and Metabolism in Cancer: Lessons and Innovations

Cancer cells support their growth and proliferation by reprogramming their metabolism in order to gain access to nutrients. Despite the heterogeneity in genetic mutations that lead to tumorigenesis, a common alteration in tumors occurs in pathways that upregulate nutrient acquisition. A central signaling pathway that controls metabolic processes is the mTOR pathway. The elucidation of the regulation and functions of mTOR can be traced to the discovery of the natural compound, rapamycin. Studies using rapamycin have unraveled the role of mTOR in the control of cell growth and metabolism. By sensing the intracellular nutrient status, mTOR orchestrates metabolic reprogramming by controlling nutrient uptake and flux through various metabolic pathways. The central role of mTOR in metabolic rewiring makes it a promising target for cancer therapy. Numerous clinical trials are ongoing to evaluate the efficacy of mTOR inhibition for cancer treatment. Rapamycin analogs have been approved to treat specific types of cancer. Since rapamycin does not fully inhibit mTOR activity, new compounds have been engineered to inhibit the catalytic activity of mTOR to more potently block its functions. Despite highly promising pre-clinical studies, early clinical trial results of these second generation mTOR inhibitors revealed increased toxicity and modest antitumor activity. The plasticity of metabolic processes and seemingly enormous capacity of malignant cells to salvage nutrients through various mechanisms make cancer therapy extremely challenging. Therefore, identifying metabolic vulnerabilities in different types of tumors would present opportunities for rational therapeutic strategies. Understanding how the different sources of nutrients are metabolized not just by the growing tumor but also by other cells from the microenvironment, in particular, immune cells, will also facilitate the design of more sophisticated and effective therapeutic regimen. In this review, we discuss the functions of mTOR in cancer metabolism that have been illuminated from pre-clinical studies. We then review key findings from clinical trials that target mTOR and the lessons we have learned from both pre-clinical and clinical studies that could provide insights on innovative therapeutic strategies, including immunotherapy to target mTOR signaling and the metabolic network in cancer.

Towards individualized therapy for metastatic renal cell carcinoma

Over the past decade, the treatment landscape for patients with metastatic renal cell carcinoma (RCC) has evolved dramatically. The therapeutic options available have expanded and now include immune-checkpoint inhibitors, novel targeted agents and combination strategies, and thus optimal patient selection and treatment sequencing are increasingly pertinent for optimizing clinical outcomes. A better understanding of the underlying biology of the tumour and its microenvironment continues to drive the inception of new diagnostic and therapeutic approaches. Furthermore, many biomarkers robustly associated with treatment and disease-specific outcomes have been identified, and their integration into clinical decision-making for patients with advanced-stage disease will soon become a reality. Herein, we review relevant aspects of the molecular biology of metastatic RCC, with an emphasis on predictive and prognostic biomarkers, and suggest tailored algorithms to individualize and guide treatment approaches for specific subgroups of patients.

Integrating multi-platform genomic datasets for kidney renal clear cell carcinoma subtyping using stacked denoising autoencoders

Clear cell renal cell carcinoma (ccRCC) is highly heterogeneous and is the most lethal cancer of all urologic cancers. We developed an unsupervised deep learning method, stacked denoising autoencoders (SdA), by integrating multi-platform genomic data for subtyping ccRCC with the goal of assisting diagnosis, personalized treatments and prognosis. We successfully found two subtypes of ccRCC using five genomics datasets for Kidney Renal Clear Cell Carcinoma (KIRC) from The Cancer Genome Atlas (TCGA). Correlation analysis between the last reconstructed input and the original input data showed that all the five types of genomic data positively contribute to the identification of the subtypes. The first subtype of patients had significantly lower survival probability, higher grade on neoplasm histology and higher stage on pathology than the other subtype of patients. Furthermore, we identified a set of genes, proteins and miRNAs that were differential expressed (DE) between the two subtypes. The function annotation of the DE genes from pathway analysis matches the clinical features. Importantly, we applied the model learned from KIRC as a pre-trained model to two independent datasets from TCGA, Lung Adenocarcinoma (LUAD) dataset and Low Grade Glioma (LGG), and the model stratified the LUAD and LGG patients into clinical associated subtypes. The successful application of our method to independent groups of patients supports that the SdA method and the model learned from KIRC are effective on subtyping cancer patients and most likely can be used on other similar tasks. We supplied the source code and the models to assist similar studies at https://github.com/tjgu/cancer_subtyping.

Mutations and Response to Rapalogs in Patients with Metastatic Renal Cell Carcinoma

We previously showed that alterations in mTOR pathway genes were correlated with response to rapalog therapy in metastatic renal cell carcinoma (mRCC), when the analysis focused on extremes of response. Herein, we expand on the prior cohort and examine genetic correlations with rapalog response in a dataset not selected for extremes of response. Tumors from 58 patients from the phase III trial of temsirolimus and 51 local patients with mRCC treated with rapalogs were studied. Somatic mutations were investigated using a targeted sequencing platform covering 27 genes. Clinical benefit (CB) was defined as patients with complete remission, partial response, or stable disease lasting at least 22 weeks. Mutational analyses focused on 5 mTOR pathway genes (TSC1, TSC2, MTOR, PTEN, PIK3CA) and 6 genes commonly mutated in RCC (BAP1, KDM5C, PBRM1 SETD2, TP53, and VHL). Among the 109 patients, 93 (85%) patients had clear cell histology, and 31 (28%) showed CB. Nine of 30 (30%) patients harboring mTOR pathway mutations in their tumor achieved CB versus 22 of 79 (28%) in the wild-type group. There was no distinct association between any individual or combination of mTOR pathway gene mutations and CB. Three of 7 patients with TSC1 mutations showed CB. In addition, none of the 6 genes commonly mutated in RCC showed a mutation pattern that correlated with CB. Overall, in this large and diverse population of patients with mRCC, there is no suggestion of a correlation between response to rapalog therapy and mutation status for mTOR pathway genes.

Monosomy of Chromosome 9 Is Associated With Higher Grade, Advanced Stage, and Adverse Outcome in Clear-cell Renal Cell Carcinoma

BACKGROUND

Clear-cell renal cell carcinoma (ccRCC) is one of the most common malignancies in humans and is usually associated with poor outcomes. Cancers are considered to be genetic diseases. Therefore, a better understanding of genetic alterations that are related to disease progression or poor prognosis can help to more precisely identify high-risk patients and treat them more effectively. The aim of this study was to examine the frequency of whole chromosome 9 loss (monosomy of chromosome 9) and its prognostic value in patients with ccRCC.

MATERIALS AND METHODS

Single nucleotide polymorphism-based chromosome microarray (CMA) analysis was performed on 103 resected specimens from patients with ccRCC who had undergone partial or radical nephrectomy between January 2002 and March 2017 at Fox Chase Cancer Center. Monosomy 9 was correlated with clinicopathologic parameters and recurrence-free survival.

RESULTS

Chromosome 9 loss was detected in 31 (30%) of 103 tumors. Tumors with chromosome 9 loss had higher histologic grade (3 and 4; P < .001) and pathologic stage (P < .001). In 59 patients with non-metastatic ccRCC, chromosome 9 loss was also associated with higher recurrence rate and shorter recurrence-free survival (RFS) (12-month RFS, 77.8%; 95% confidence interval, 36.5%-93.9% for chromosome 9 loss vs. 95.7%; 95% confidence interval, 84.0%-98.9% for no loss; P = .002).

CONCLUSIONS

Chromosome 9 loss was found in 30% of patients with ccRCC and correlated with higher grade, advanced stage, and shorter RFS in patients with Stage I to III ccRCC.

Validation and Clinical Applications of a Comprehensive Next Generation Sequencing System for Molecular Characterization of Solid Cancer Tissues

Identification of somatic molecular alterations in primary and metastatic solid tumor specimens can provide critical information regarding tumor biology and its heterogeneity, and enables the detection of molecular markers for clinical personalized treatment assignment. However, the optimal methods and target genes for clinical use are still being in development. Toward this end, we validated a targeted amplification-based NGS panel (Oncomine comprehensive assay v1) on a personal genome machine sequencer for molecular profiling of solid tumors. This panel covers 143 genes, and requires low amounts of DNA (20 ng) and RNA (10 ng). We used 27 FFPE tissue specimens, 10 cell lines, and 24 commercial reference materials to evaluate the performance characteristics of this assay. We also evaluated the performance of the assay on 26 OCT-embedded fresh frozen specimens (OEFF). The assay was found to be highly specific (>99%) and sensitive (>99%), with low false-positive and false-negative rates for single-nucleotide variants, indels, copy number alterations, and gene fusions. Our results indicate that this is a reliable method to determine molecular alterations in both fixed and fresh frozen solid tumor samples, including core needle biopsies.

A Renal Cell Carcinoma with Biallelic Somatic TSC2 Mutation: Clinical Study and Literature Review

OBJECTIVE

To elucidate the effect of the biallelic somatic TSC2 mutations, identified in one adolescent patient, in renal cell carcinoma (RCC).

METHODS

Mutation analyses, immunohistochemistry and real-time polymerase chain reaction (PCR) were conducted.

RESULTS

Two novel somatic mutations of TSC2 in unilateral and solitary RCC samples from a 14-year-old female were identified. The pathological features suggest the tumor as a clear-cell renal cell carcinoma. In addition, immunohistochemistry revealed elevated levels of phosphorylated S6K1. Results from in vitro cellular experiments suggest that the mutant TSC2 proteins were quickly degraded and they failed to repress the phosphorylation of S6K1 and STAT3, which leads to constitutive activation of mTORC1 pathway and ultimately cause the development of RCC.

CONCLUSION

Detecting TSC2 mutation in patients with early RCC onset would be beneficial and mTOR inhibitor could be a therapeutic option for TSC2 mutation-induced RCC.

PTEN expression and mutations in TSC1, TSC2 and MTOR are associated with response to rapalogs in patients with renal cell carcinoma

The mammalian target of rapamycin (mTOR) pathway inhibitors are key drugs for the treatment of many tumor types, however, there are no predictive biomarkers in clinical use. Here, we performed a molecular and immunohistochemical characterization of key mTOR pathway components in a series of 105 renal cell carcinoma patients treated with rapalogs, aimed at identifying markers of treatment response. Mutational analysis in MTOR, TSC1 and TSC2 was performed through targeted next-generation sequencing (NGS), and immunohistochemistry (IHC) was performed for PTEN, pAKT, pS6K1, pS6 and p21. Among patients with NGS data, 11 of 87 (13%) had mTOR pathway mutations (8 in MTOR, 1 in TSC1 and 2 in TSC2). When comparing the molecular data to the response of the patients, we found that partial response was more frequent in cases with mTOR pathway mutations than in those without mutations (odds ratio [OR] = 0.08, 95% confidence interval [CI] = 0.008-0.79, p = 0.030 univariate; p = 0.038 multivariable). Regarding IHC, negative PTEN staining was detected in 58% of the tumors, and it was more frequent in rapalog responder patients (OR = 0.24, 95% CI = 0.065-0.86, p = 0.029 univariate; p = 0.029 multivariable). Mutations and PTEN IHC were not mutually exclusive events and its combination improved response prediction (OR = 0.16, 95% CI = 0.04-0.62, p = 0.008 univariate; p = 0.013 multivariable). The staining of other proteins did not show and association with response and no association with PFS was observed in unselected patients. In conclusion, our findings suggest that mTOR pathway mutations, negative PTEN IHC and their combination are potential markers of rapalog response.

Prospective Genotyping of Hepatocellular Carcinoma: Clinical Implications of Next-Generation Sequencing for Matching Patients to Targeted and Immune Therapies

PURPOSE

Prior molecular profiling of hepatocellular carcinoma (HCC) has identified actionable findings that may have a role in guiding therapeutic decision-making and clinical trial enrollment. We implemented prospective next-generation sequencing (NGS) in the clinic to determine whether such analyses provide predictive and/or prognostic information for HCC patients treated with contemporary systemic therapies.

EXPERIMENTAL DESIGN

Matched tumor/normal DNA from patients with HCC (N = 127) were analyzed using a hybridization capture-based NGS assay designed to target 341 or more cancer-associated genes. Demographic and treatment data were prospectively collected with the goal of correlating treatment outcomes and drug response with molecular profiles.

RESULTS

WNT/β-catenin pathway (45%) and TP53 (33%) alterations were frequent and represented mutually exclusive molecular subsets. In sorafenib-treated patients (n = 81), oncogenic PI3K-mTOR pathway alterations were associated with lower disease control rates (DCR, 8.3% vs. 40.2%), shorter median progression-free survival (PFS; 1.9 vs. 5.3 months), and shorter median overall survival (OS; 10.4 vs. 17.9 months). For patients treated with immune checkpoint inhibitors (n = 31), activating alteration WNT/β-catenin signaling were associated with lower DCR (0% vs. 53%), shorter median PFS (2.0 vs. 7.4 months), and shorter median OS (9.1 vs. 15.2 months). Twenty-four percent of patients harbored potentially actionable alterations including TSC1/2 (8.5%) inactivating/truncating mutations, FGF19 (6.3%) and MET (1.5%) amplifications, and IDH1 missense mutations (<1%). Six percent of patients treated with systemic therapy were matched to targeted therapeutics.

CONCLUSIONS

Linking NGS to routine clinical care has the potential to identify those patients with HCC likely to benefit from standard systemic therapies and can be used in an investigational context to match patients to genome-directed targeted therapies.See related commentary by Pinyol et al., p. 2021.

Emerging Molecular Technologies in Renal Cell Carcinoma: Liquid Biopsy

Liquid biopsy, based on the circulating tumor cells (CTCs) and cell-free nucleic acids has potential applications at multiple points throughout the natural course of cancer, from diagnosis to follow-up. The advantages of doing ctDNA assessment vs. tissue-based genomic profile are the minimal procedural risk, the possibility to serial testing in order to monitor disease-relapse and response to therapy over time and to reduce hospitalization costs during the entire process. However, some critical issues related to ctDNA assays should be taken into consideration. The sensitivity of ctDNA assays depends on the assessment technique and genetic platforms used, on tumor-organ, stage, tumor heterogeneity, tumor clonality. The specificity is usually very high, whereas the concordance with tumor-based biopsy is generally low. In patients with renal cell carcinoma (RCC), qualitative analyses of ctDNA have been performed with interesting results regarding selective pressure from therapy, therapeutic resistance, exceptional treatment response to everolimus and mutations associated with aggressive behavior. Quantitative analyses showed variations of ccfDNA levels at different tumor stage. Compared to CTC assay, ctDNA is more stable than cells and easier to isolate. Splice variants, information at single-cell level and functional assays along with proteomics, transcriptomics and metabolomics studies can be performed only in CTCs.