18 research outputs found

    Overcoming intratumoural heterogeneity for reproducible molecular risk stratification: a case study in advanced kidney cancer

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    Abstract Background Metastatic clear cell renal cell cancer (mccRCC) portends a poor prognosis and urgently requires better clinical tools for prognostication as well as for prediction of response to treatment. Considerable investment in molecular risk stratification has sought to overcome the performance ceiling encountered by methods restricted to traditional clinical parameters. However, replication of results has proven challenging, and intratumoural heterogeneity (ITH) may confound attempts at tissue-based stratification. Methods We investigated the influence of confounding ITH on the performance of a novel molecular prognostic model, enabled by pathologist-guided multiregion sampling (n = 183) of geographically separated mccRCC cohorts from the SuMR trial (development, n = 22) and the SCOTRRCC study (validation, n = 22). Tumour protein levels quantified by reverse phase protein array (RPPA) were investigated alongside clinical variables. Regularised wrapper selection identified features for Cox multivariate analysis with overall survival as the primary endpoint. Results The optimal subset of variables in the final stratification model consisted of N-cadherin, EPCAM, Age, mTOR (NEAT). Risk groups from NEAT had a markedly different prognosis in the validation cohort (log-rank p = 7.62 × 10−7; hazard ratio (HR) 37.9, 95% confidence interval 4.1–353.8) and 2-year survival rates (accuracy = 82%, Matthews correlation coefficient = 0.62). Comparisons with established clinico-pathological scores suggest favourable performance for NEAT (Net reclassification improvement 7.1% vs International Metastatic Database Consortium score, 25.4% vs Memorial Sloan Kettering Cancer Center score). Limitations include the relatively small cohorts and associated wide confidence intervals on predictive performance. Our multiregion sampling approach enabled investigation of NEAT validation when limiting the number of samples analysed per tumour, which significantly degraded performance. Indeed, sample selection could change risk group assignment for 64% of patients, and prognostication with one sample per patient performed only slightly better than random expectation (median logHR = 0.109). Low grade tissue was associated with 3.5-fold greater variation in predicted risk than high grade (p = 0.044). Conclusions This case study in mccRCC quantitatively demonstrates the critical importance of tumour sampling for the success of molecular biomarker studies research where ITH is a factor. The NEAT model shows promise for mccRCC prognostication and warrants follow-up in larger cohorts. Our work evidences actionable parameters to guide sample collection (tumour coverage, size, grade) to inform the development of reproducible molecular risk stratification methods

    Carbonic Anhydrase 9 Expression Increases with Vascular Endothelial Growth Factor-Targeted Therapy and Is Predictive of Outcome in Metastatic Clear Cell Renal Cancer

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    AbstractBackgroundThere is a lack of biomarkers to predict outcome with targeted therapy in metastatic clear cell renal cancer (mccRCC). This may be because dynamic molecular changes occur with therapy.ObjectiveTo explore if dynamic, targeted-therapy-driven molecular changes correlate with mccRCC outcome.Design, setting, and participantsMultiple frozen samples from primary tumours were taken from sunitinib-naïve (n=22) and sunitinib-treated mccRCC patients (n=23) for protein analysis. A cohort (n=86) of paired, untreated and sunitinib/pazopanib-treated mccRCC samples was used for validation. Array comparative genomic hybridisation (CGH) analysis and RNA interference (RNAi) was used to support the findings.InterventionThree cycles of sunitinib 50mg (4 wk on, 2 wk off).Outcome measurements and statistical analysisReverse phase protein arrays (training set) and immunofluorescence automated quantitative analysis (validation set) assessed protein expression.Results and limitationsDifferential expression between sunitinib-naïve and treated samples was seen in 30 of 55 proteins (p<0.05 for each). The proteins B-cell CLL/lymphoma 2 (BCL2), mutL homolog 1 (MLH1), carbonic anhydrase 9 (CA9), and mechanistic target of rapamycin (mTOR) (serine/threonine kinase) had both increased intratumoural variance and significant differential expression with therapy. The validation cohort confirmed increased CA9 expression with therapy. Multivariate analysis showed high CA9 expression after treatment was associated with longer survival (hazard ratio: 0.48; 95% confidence interval, 0.26–0.87; p=0.02). Array CGH profiles revealed sunitinib was associated with significant CA9 region loss. RNAi CA9 silencing in two cell lines inhibited the antiproliferative effects of sunitinib. Shortcomings of the study include selection of a specific protein for analysis, and the specific time points at which the treated tissue was analysed.ConclusionsCA9 levels increase with targeted therapy in mccRCC. Lower CA9 levels are associated with a poor prognosis and possible resistance, as indicated by the validation cohort.Patient summaryDrug treatment of advanced kidney cancer alters molecular markers of treatment resistance. Measuring carbonic anhydrase 9 levels may be helpful in determining which patients benefit from therapy

    Differential nuclear Ki67 expression between primary, renal vein tumour thrombus and metastatic RCC.

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    <p>Significantly increased expression of nuclear Ki67 shown in the metastases compared to the VTT and primary tumour but no difference in expression between the primary tumour and the VTT.</p

    AQUA Images of renal cell carcinoma.

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    <p>Representative TMA core showing green cytoplasmic staining with a combination of cytokeratin and pancadherin (A), blue nuclear staining with DAPI (B), red target staining (C, in this case VEGFR1) and all three compartments combined (D). Quantitative assessment and compartment localisation of target expression is measured through calculating the sum of target pixel intensity divided by the compartment area and normalized for exposure time.</p
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