Yukti Choudhury

A Multigene Assay Identifying Distinct Prognostic Subtypes of Clear Cell Renal Cell Carcinoma with Differential Response to Tyrosine Kinase Inhibition

Patients with clear cell renal cell carcinoma (ccRCC) have divergent survival outcomes and therapeutic responses, which may be determined by underlying molecular diversity. We aimed to develop a practical molecular assay that can identify subtypes with differential prognosis and response to targeted therapy. Whole-genome expression analysis of formalin-fixed paraffin-embedded (FFPE) material from 55 ccRCC patients was performed and two molecular subtypes with differential clinical outcomes were identified by hierarchical clustering. An eight-gene quantitative polymerase chain reaction assay for classification into two subtypes was developed for FFPE material. The primary objective was to assess assay performance by correlating ccRCC prognostic subtypes to cancer-specific survival (CSS) and, for patients receiving targeted therapy, radiologic response. In three validation cohorts, patients could be distinguished into prognostic subtypes with differential CSS (Singapore General Hospital FFPE cohort: n = 224; p = 1.48 × 10(-8); the Cancer Genome Atlas RNA-Sequencing cohort: n = 419; p = 3.06 × 10(-7); Van Andel Research Institute microarray cohort: n=174; p=0.00743). For 48 patients receiving tyrosine kinase inhibitor (TKI) treatment, the prognostic classification was associated with radiologic response to treatment (p = 5.96 × 10(-4)) and prolonged survival on TKI treatment (p=0.019). The multigene assay can classify ccRCCs into clinical prognostic subtypes, which may be predictive of response in patients receiving TKI therapy.

Association of ABCB1 and FLT3 Polymorphisms with Toxicities and Survival in Asian Patients Receiving Sunitinib for Renal Cell Carcinoma

Sunitinib is a tyrosine kinase inhibitor used as first-line treatment for metastatic renal cell carcinoma (mRCC). Asian ethnicity has been previously associated with lower clearance and greater toxicities for sunitinib treatment, relative to Caucasian ethnicity. Research focusing on identifying corresponding biomarkers of efficacy and toxicity has been hitherto conducted in Caucasian populations, and few of the reported associations have been externally validated. Our work thus aims to investigate candidate biomarkers in Asian patients receiving sunitinib, comparing the observed genotype effects with those reported in Caucasian populations. Using data from 97 Asian mRCC patients treated with sunitinib, we correlated 7 polymorphisms in FLT3, ABCB1, VEGFR2, ABCG2 and BIM with patient toxicities, response, and survival. We observed a stronger association of FLT3 738T genotype with leucopenia in our Asian dataset than that previously reported in Caucasian mRCC patients (odds ratio [OR]=8.0; P=0.03). We observed significant associations of FLT3 738T (OR=2.7), ABCB1 1236T (OR=0.3), ABCB1 3435T (OR=0.1), ABCB1 2677T (OR=0.4), ABCG2 421A (OR=0.3) alleles and ABCB1 3435, 1236, 2677 TTT haplotype (OR=0.1) on neutropenia. Primary resistance (OR=0.1, P=0.004) and inferior survival (progression-free: hazard ratio [HR]=5.5, P=0.001; overall: HR=5.0, P=0.005) were associated with the ABCB1 3435, 1236, 2677 TTT haplotype. In conclusion, ABCB1 and FLT3 polymorphisms may be helpful in predicting sunitinib toxicities, response and survival benefit in Asian mRCC patients. We have also validated the association between FLT3 738T and sunitinib-induced leucopenia previously reported in Caucasian populations, but have not validated other reported genetic associations.

Recognizing the Continuous Nature of Expression Heterogeneity and Clinical Outcomes in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) has been previously classified into putative discrete prognostic subtypes by gene expression profiling. To investigate the robustness of these proposed subtype classifications, we evaluated 12 public datasets, together with a new dataset of 265 ccRCC gene expression profiles. Consensus clustering showed unstable subtype and principal component analysis (PCA) showed a continuous spectrum both within and between datasets. Considering the lack of discrete delineation and continuous spectrum observed, we developed a continuous quantitative prognosis score (Continuous Linear Enhanced Assessment of RCC, or CLEAR score). Prognostic performance was evaluated in independent cohorts from The Cancer Genome Atlas (TCGA) (n = 414) and EMBL-EBI (n = 53), CLEAR score demonstrated both superior prognostic estimates and inverse correlation with anti-angiogenic tyrosine-kinase inhibition in comparison to previously proposed discrete subtyping classifications. Inverse correlation with high-dose interleukin-2 outcomes was also observed for the CLEAR score. Multiple somatic mutations (VHL, PBRM1, SETD2, KDM5C, TP53, BAP1, PTEN, MTOR) were associated with the CLEAR score. Application of the CLEAR score to independent expression profiling of intratumoral ccRCC regions demonstrated that average intertumoral heterogeneity exceeded intratumoral expression heterogeneity. Wider investigation of cancer biology using continuous approaches may yield insights into tumor heterogeneity; single cell analysis may provide a key foundation for this approach.

Metformin Inhibits Cellular Proliferation and Bioenergetics in Colorectal Cancer Patient-Derived Xenografts

There is increasing preclinical evidence suggesting that metformin, an antidiabetic drug, has anticancer properties against various malignancies, including colorectal cancer. However, the majority of evidence, which was derived from cancer cell lines and xenografts, was likely to overestimate the benefit of metformin because these models are inadequate and require supraphysiologic levels of metformin. Here, we generated patient-derived xenograft (PDX) lines from 2 colorectal cancer patients to assess the properties of metformin and 5-fluorouracil (5-FU), the first-line drug treatment for colorectal cancer. Metformin (150 mg/kg) as a single agent inhibits the growth of both PDX tumors by at least 50% (P < 0.05) when administered orally for 24 days. In one of the PDX models, metformin given concurrently with 5-FU (25 mg/kg) leads to an 85% (P = 0.054) growth inhibition. Ex vivo culture of organoids generated from PDX demonstrates that metformin inhibits growth by executing metabolic changes to decrease oxygen consumption and activating AMPK-mediated pathways. In addition, we also performed genetic characterizations of serial PDX samples with corresponding parental tissues from patients using next-generation sequencing (NGS). Our pilot NGS study demonstrates that PDX represents a useful platform for analysis in cancer research because it demonstrates high fidelity with parental tumor. Furthermore, NGS analysis of PDX may be useful to determine genetic identifiers of drug response. This is the first preclinical study using PDX and PDX-derived organoids to investigate the efficacy of metformin in colorectal cancer. Mol Cancer Ther; 16(9); 2035–44. ©2017 AACR.

Automated Renal Cancer Grading Using Nuclear Pleomorphic Patterns

PURPOSE Nuclear pleomorphic patterns are essential for Fuhrman grading of clear cell renal cell carcinoma (ccRCC). Manual observation of renal histopathologic slides may lead to subjective and inconsistent assessment between pathologists. An automated, image-based system that classifies ccRCC slides by quantifying nuclear pleomorphic patterns in an objective and consistent interpretable fashion can aid pathologists in histopathologic assessment. METHODS In the current study, histopathologic tissue slides of 59 patients with ccRCC who underwent surgery at Singapore General Hospital were assembled retrospectively. An automated image classification pipeline detects and analyzes prominent nucleoli in ccRCC images to classify them as either low (Fuhrman grade 1 and 2) or high (Fuhrman grade 3 and 4). The pipeline uses machine learning and image pixel intensity-based feature extraction techniques for nuclear analysis. We trained classification systems that concurrently analyze different permutations of multiple prominent nucleoli image patches. RESULTS Given the parameters for feature combination and extraction, we present experimental results across various configurations for the classification of a given ccRCC histopathologic image. We also demonstrate that the image score used by the pipeline, termed fraction value, is correlated ( R = 0.59) with an existing multigene assay-based scoring system that has previously been demonstrated to be a strong indicator of prognosis in patients with ccRCC. CONCLUSION The current method provides an objective and fully automated way by which to process pathologic slides. The correlation study with a multigene assay-based scoring system also allows us to provide quantitative interpretation for already established nuclear pleomorphic patterns in ccRCC. This method can be extended to other cancers whose corresponding grading systems use nuclear pattern information.

The Issue of Tissue in Molecular Stratification

This letter reflects on the importance of external validation, in real‐world settings, for clinical application.

Modeling patient variability in pazopanib-induced hepatotoxicity with iPSC-derived hepatocyte-like cells.

578 Background: The tyrosine kinase inhibitor drug, pazopanib, is commonly prescribed as a first-line treatment option for metastatic renal cell carcinoma (mRCC). Administration of pazopanib can produce severe hepatotoxicity with elevated transaminases and bilirubin levels. The idiosyncrasy of hepatotoxicity suggests individual patient-factors as the key predisposition. Patient-derived induced pluripotent stem cells (iPSCs) bearing individual genetic and other signatures, were interrogated as a novel cell-based approach to model inter-patient drug response variability. Methods: iPSC lines were generated from five mRCC patients who exhibited positive (n = 3) or negative (n = 2) clinical hepatotoxicity to pazopanib. The iPSC lines were differentiated into functional hepatocyte-like cells (HLCs), which were then dosed with pazopanib. Differential cellular viability changes among hepatotoxicity-positive and -negative lines were assessed. To gain insight into the mechanism of idiosyncratic hepatotoxicity, a co...

Doubling Down on mTOR Inhibition: Harnessing ZEBRA for Insights.

A number of contemporary anticancer therapies have been derived from inhibition of PI3K/AKT/mTOR signaling, a pathway central to cellular survival and tumor progression that is activated in several cancers including renal cell carcinoma (RCC) [1,2]. PI3K/AKT/mTOR signaling is activated by the binding of growth factors to their respective receptors, leading to recruitment of PI3K. This triggers a downstream cascade of events including activation of AKT, which then indirectly activates mTOR through phosphorylation of a number of targets. mTOR exerts its effects through two functionally and structurally distinct multiprotein complexes, mTORC1 and mTORC2. Among several functions vital to cancer cell signaling, mTORC1 regulates the expression of genes such as cyclin D and HIF, while mTORC2 enhances AKT catalytic activity via AKT Ser473 phosphorylation. In RCC, allosteric inhibitors of mTORC1— everolimus and temsirolimus—have demonstrated clinical activity, albeit withmodest efficacy [3,4]. The inadequacy of these agents despite prominent in vitro activity suggested a need to revisit resistance mechanisms, particularly feedback activation of other oncogenic signaling pathways in response to mTOR inhibition. During mTORC1-selective inhibition, relief of constitutive negative feedback loops allows upstream overstimulation of IRS1-mediated AKT activation, reinstating the signaling pathway to overcome mTORC1 abrogation [5]. Persistent AKT activation is also permitted through mTORC2-dependent signaling (Fig. 1). To overcome at least some of these hurdles, dual catalytic inhibitors of PI3K/mTOR and[1_TD

Patient-specific hepatocyte-like cells derived from induced pluripotent stem cells model pazopanib-mediated hepatotoxicity

DIFF] mTORC1/mTORC2 are being evaluated in several early clinical studies. In this issue of European Urology, Powles et al [6] report on the results of a