Alexander B. Sibley

Gene Expression Markers of Efficacy and Resistance to Cetuximab Treatment in Metastatic Colorectal Cancer: Results from CALGB 80203 (Alliance).

Purpose: Formalin-fixed, paraffin-embedded tumor samples from CALGB 80203 were analyzed for expression of EGFR axis–related genes to identify prognostic or predictive biomarkers for cetuximab treatment. Patients and Methods: Patients (238 total) with first-line metastatic colorectal cancer (mCRC) were randomized to FOLFOX or FOLFIRI chemotherapy ± cetuximab. qRT-PCR analyses were conducted on tissues from 103 patients at baseline to measure gene expression levels of HER-related genes, including amphiregulin (AREG), betacellulin (BTC), NT5E (CD73), DUSP4, EGF, EGFR, epigen (EPGN), epiregulin (EREG), HBEGF, ERBB2 (HER2), ERBB3 (HER3), ERBB4 (HER4), PHLDA1, and TGFA. The interactions between expression levels and treatment with respect to progression-free survival (PFS) and overall survival (OS) were modeled using multiplicative Cox proportional hazards models. Results: High tumor mRNA levels of HER2 [hazard ratio (HR), 0.64; P = 0.002] and EREG (HR, 0.89; P = 0.016) were prognostic markers associated with longer PFS across all patients. HER3 and CD73 expression levels were identified as potential predictive markers of benefit from cetuximab. In KRAS wild-type (WT) tumors, low HER3 expression was associated with longer OS from cetuximab treatment, whereas high HER3 expression was associated with shorter OS from cetuximab treatment (chemo + cetuximab: HR, 1.15; chemo-only: HR, 0.48; Pinteraction = 0.029). High CD73 expression was associated with longer PFS from cetuximab treatment in patients with KRAS-WT (chemo + cetuximab: HR, 0.91; chemo-only: HR, 1.57; Pinteraction = 0.026) and KRAS-mutant (Mut) tumors (chemo + cetuximab: HR, 0.80; chemo-only: HR, 1.29; P = 0.025). Conclusions: Gene expression of HER3 and CD73 was identified as a potential predictive marker for cetuximab. These data implicate HER axis signaling and immune modulation as potential mechanisms of cetuximab action and sensitivity. Clin Cancer Res; 21(5); 1078–86. ©2014 AACR.

Pharmacogenetic Discovery in CALGB (Alliance) 90401 and Mechanistic Validation of a VAC14 Polymorphism that Increases Risk of Docetaxel-Induced Neuropathy.

Purpose: Discovery of SNPs that predict a patients risk of docetaxel-induced neuropathy would enable treatment individualization to maximize efficacy and avoid unnecessary toxicity. The objectives of this analysis were to discover SNPs associated with docetaxel-induced neuropathy and mechanistically validate these associations in preclinical models of drug-induced neuropathy. Experimental Design: A genome-wide association study was conducted in metastatic castrate-resistant prostate cancer patients treated with docetaxel, prednisone and randomized to bevacizumab or placebo on CALGB 90401. SNPs were genotyped on the Illumina HumanHap610-Quad platform followed by rigorous quality control. The inference was conducted on the cumulative dose at occurrence of grade 3+ sensory neuropathy using a cause-specific hazard model that accounted for early treatment discontinuation. Genes with SNPs significantly associated with neuropathy were knocked down in cellular and mouse models of drug-induced neuropathy. Results: A total of 498,081 SNPs were analyzed in 623 Caucasian patients, 50 (8%) of whom experienced grade 3+ neuropathy. The 1,000 SNPs most associated with neuropathy clustered in relevant pathways including neuropathic pain and axonal guidance. An SNP in VAC14 (rs875858) surpassed genome-wide significance (P = 2.12 × 10−8, adjusted P = 5.88 × 10−7). siRNA knockdown of VAC14 in stem cell–derived peripheral neuronal cells increased docetaxel sensitivity as measured by decreased neurite processes (P = 0.0015) and branches (P < 0.0001). Prior to docetaxel treatment, VAC14 heterozygous mice had greater nociceptive sensitivity than wild-type litter mate controls (P = 0.001). Conclusions: VAC14 should be prioritized for further validation of its potential role as a predictor of docetaxel-induced neuropathy and biomarker for treatment individualization. Clin Cancer Res; 22(19); 4890–900. ©2016 AACR.

Blood-based markers of efficacy and resistance to cetuximab treatment in metastatic colorectal cancer: results from CALGB 80203 (Alliance).

Circulating protein markers were assessed in patients with colorectal cancer (CRC) treated with cetuximab in CALGB 80203 to identify prognostic and predictive biomarkers. Patients with locally advanced or metastatic CRC received FOLFOX or FOLFIRI chemotherapy (chemo) or chemo in combination with cetuximab. Baseline plasma samples from 152 patients were analyzed for six candidate markers [epidermal growth factor (EGF), heparin‐binding EGF (HBEGF), epidermal growth factor receptor (EGFR), HER2, HER3, and CD73]. Analyte levels were associated with survival endpoints using univariate Cox proportional hazards models. Predictive markers were identified using a treatment‐by‐marker interaction term in the Cox model. Plasma levels of EGF, HBEGF, HER3, and CD73 were prognostic for overall survival (OS) across all patients (KRAS mutant and wild‐type). High levels of EGF predicted for lack of OS benefit from cetuximab in KRAS wild‐type (WT) patients (chemo HR = 0.98, 95% CI = 0.74–1.29; chemo+cetuximab HR = 1.54, 95% CI = 1.05–2.25; interaction P = 0.045) and benefit from cetuximab in KRAS mutant patients (chemo HR = 1.72, 95% CI = 1.02–2.92; chemo+cetuximab HR = 0.90, 95% CI = 0.67–1.21; interaction P = 0.026). Across all patients, higher HER3 levels were associated with significant OS benefit from cetuximab treatment (chemo HR = 4.82, 95% CI = 1.68–13.84; chemo+cetuximab HR = 0.95, 95% CI = 0.31–2.95; interaction P = 0.046). CD73 was also identified as predictive of OS benefit in KRAS WT patients (chemo HR = 1.28, 95% CI = 0.88–1.84; chemo+cetuximab HR = 0.60, 95% CI = 0.32–1.13; interaction P = 0.049). Although these results are preliminary, and confirmatory studies are necessary before clinical application, the data suggest that HER3 and CD73 may play important roles in the biological response to cetuximab.

Relationship of blood monocytes with chronic lymphocytic leukemia aggressiveness and outcomes: a multi-institutional study

Monocyte‐derived cells, constituents of the cancer microenvironment, support chronic lymphocytic leukemia (CLL) cell survival in vitro via direct cell‐cell interaction and secreted factors. We hypothesized that circulating absolute monocyte count (AMC) reflects the monocyte‐derived cells in the microenvironment, and that higher AMC is associated with increased CLL cell survival in vivo and thus inferior CLL patient outcomes. We assessed the extent to which AMC at diagnosis of CLL is correlated with clinical outcomes, and whether this information adds to currently used prognostic markers. We evaluated AMC, clinically used prognostic markers, and time to event data from 1,168 CLL patients followed at the Mayo Clinic, the Duke University Medical Center, and the Durham VA Medical Center. Elevated AMC was significantly associated with inferior clinical outcomes, including time to first therapy (TTT) and overall survival (OS). AMC combined with established clinical and molecular prognostic markers significantly improved risk‐stratification of CLL patients for TTT. As an elevated AMC at diagnosis is associated with accelerated disease progression, and monocyte‐derived cells in the CLL microenvironment promote CLL cell survival and proliferation, these findings suggest that monocytes and monocyte‐derived cells are rational therapeutic targets in CLL. Am. J. Hematol. 91:687–691, 2016.

Targeted Exome Sequencing of the Cancer Genome in Patients with Very High-risk Bladder Cancer

We completed targeted exome sequencing of the tumors of 50 patients with pTis-pT4b bladder cancer. Mutations were categorized by type, stratified against previously identified cancer loci in the Catalogue of Somatic Mutations in Cancer and The Cancer Genome Atlas databases, and evaluated in pathway analysis and comutation plots. We analyzed mutation associations with receipt of neoadjuvant chemotherapy, nodal involvement, metastatic disease development, and survival. Compared with The Cancer Genome Atlas, we found higher mutation rates in genes encoding products involved in epigenetic regulation and cell cycle regulation. Of the pathways examined, PI3K/mTOR and Cell Cycle/DNA Repair exhibited the greatest frequencies of mutation. RB1 and TP53, as well as NF1 and PIK3CA were frequently comutated. We identified no association between mutations in specific genes and key clinical outcomes of interest when corrected for multiple testing. Discovery phase analysis of the somatic mutations in 50 high-risk bladder cancer patients revealed novel mutations and mutational patterns, which may be useful for developing targeted therapy regimens or new biomarkers for patients at very high risk of disease metastasis and death.nnnPATIENT SUMMARYnIn this report we found known, as well as previously unreported, genetic mutations in the tumors of patients with high-risk bladder cancer. These mutations, if validated, may serve as actionable targets for new trials.

Leveraging Population Information in Family-based Rare Variant Association Analyses of Quantitative Traits

Confounding due to population substructure is always a concern in genetic association studies. Although methods have been proposed to adjust for population stratification in the context of common variation, it is unclear how well these approaches will work when interrogating rare variation. Family‐based association tests can be constructed that are robust to population stratification. For example, when considering a quantitative trait, a linear model can be used that decomposes genetic effects into between‐ and within‐family components and a test of the within‐family component is robust to population stratification. However, this within‐family test ignores between‐family information potentially leading to a loss of power. Here, we propose a family‐based two‐stage rare‐variant test for quantitative traits. We first construct a weight for each variant within a gene, or other genetic unit, based on score tests of between‐family effect parameters. These weights are then used to combine variants using score tests of within‐family effect parameters. Because the between‐family and within‐family tests are orthogonal under the null hypothesis, this two‐stage approach can increase power while still maintaining validity. Using simulation, we show that this two‐stage test can significantly improve power while correctly maintaining type I error. We further show that the two‐stage approach maintains the robustness to population stratification of the within‐family test and we illustrate this using simulations reflecting samples composed of continental and closely related subpopulations.

SparkScore: Leveraging Apache Spark for Distributed Genomic Inference

The method of the efficient score statistic is used extensively to conduct inference for high throughput genomic data due to its computational efficiency and abilityto accommodate simple and complex phenotypes. Inference based on these statistics can readily incorporate a priori knowledge from a vast collection of bioinformatics databases to further refine the analyses. The sampling distribution of the efficient score statistic is typically approximated using asymptotics. As this may be inappropriate in the context of small study size, or uncommon or rare variants, resampling methods are often used to approximate the exact sampling distribution. We propose SparkScore, a set of distributed computational algorithms implemented in Apache Spark, to leverage the embarrassingly parallel nature of genomic resampling inference on the basis of the efficient score statistics. We illustrate the application of this computational approachfor the analysis of data from genome-wide analysis studies(GWAS). This computational approach also harnesses thefault-tolerant features of Spark and can be readily extended to analysis of DNA and RNA sequencing data, including expression quantitative trait loci (eQTL) and phenotype association studies.

Facilitating the Calculation of the Efficient Score Using Symbolic Computing

ABSTRACT The score statistic continues to be a fundamental tool for statistical inference. In the analysis of data from high-throughput genomic assays, inference on the basis of the score usually enjoys greater stability, considerably higher computational efficiency, and lends itself more readily to the use of resampling methods than the asymptotically equivalent Wald or likelihood ratio tests. The score function often depends on a set of unknown nuisance parameters which have to be replaced by estimators, but can be improved by calculating the efficient score, which accounts for the variability induced by estimating these parameters. Manual derivation of the efficient score is tedious and error-prone, so we illustrate using computer algebra to facilitate this derivation. We demonstrate this process within the context of a standard example from genetic association analyses, though the techniques shown here could be applied to any derivation, and have a place in the toolbox of any modern statistician. We further show how the resulting symbolic expressions can be readily ported to compiled languages, to develop fast numerical algorithms for high-throughput genomic analysis. We conclude by considering extensions of this approach. The code featured in this report is available online as part of the supplementary material.

The Vitamin D receptor gene as a determinant of survival in pancreatic cancer patients: Genomic analysis and experimental validation

Purpose Advanced pancreatic cancer is a highly refractory disease almost always associated with survival of little more than a year. New interventions based on novel targets are needed. We aim to identify new genetic determinants of overall survival (OS) in patients after treatment with gemcitabine using genome-wide screens of germline DNA. We aim also to support these findings with in vitro functional analysis. Patients and methods Genome-wide screens of germline DNA in two independent cohorts of pancreatic cancer patients (from the Cancer and Leukemia Group B (CALGB) 80303 and the Mayo Clinic) were used to select new genes associated with OS. The vitamin D receptor gene (VDR) was selected, and the interactions of genetic variation in VDR with circulating vitamin D levels and gemcitabine treatment were evaluated. Functional effects of common VDR variants were also evaluated in experimental assays in human cell lines. Results The rs2853564 variant in VDR was associated with OS in patients from both the Mayo Clinic (HR 0.81, 95% CI 0.70–0.94, p = 0.0059) and CALGB 80303 (HR 0.74, 0.63–0.87, p = 0.0002). rs2853564 interacted with high pre-treatment levels of 25-hydroxyvitamin D (25(OH)D, a measure of endogenous vitamin D) (p = 0.0079 for interaction) and with gemcitabine treatment (p = 0.024 for interaction) to confer increased OS. rs2853564 increased transcriptional activity in luciferase assays and reduced the binding of the IRF4 transcription factor. Conclusion Our findings propose VDR as a novel determinant of survival in advanced pancreatic cancer patients. Common functional variation in this gene might interact with endogenous vitamin D and gemcitabine treatment to determine improved patient survival. These results support evidence for a modulatory role of the vitamin D pathway for the survival of advanced pancreatic cancer patients.

Abstract 3388: Genetic prediction of VEGF-A plasma levels in cancer patients

ABSTRACT Background: Angiogenesis is an essential event in tumor growth, progression and metastasis and is strongly regulated by multiple VEGF ligands and receptors. We sought to discover genetic variants that could predict levels of circulating angiogenic proteins in cancer patients prior to receiving therapy. Methods: EDTA plasma was collected at baseline (before treatment) in 216 treatment naive pancreatic cancer patients (CALGB 80303, discovery) and 149 treatment naive colorectal cancer patients (CALGB 80203, validation). Thirty-one angiogenic factors were measured by a multiplexed ELISA assay. Genetic variants associated with levels of each of the 31 proteins were selected from a genome-wide genotyping of 484,523 common variants in CALGB 80303. Using a cut off of p Results: In CALGB 80303, three genetic variants passed the p G) for VEFG-A levels was validated in CALGB 80203 (p = 1.23×10−5). Patients with the AA genotype exhibited 2.2-fold higher VEGF-A levels than AG patients, who had 1.2-fold higher levels than GG patients. rs7767396 was not associated with VEGF-A mRNA levels from the primary tumors of patients in CALGB 80203 (p>0.05). rs7767396 is a common variant (frequency of 49% in Europeans), is located about 150 Kb 3’ to the VEGFA gene, and is predicted by HaploReg to disrupt the binding motifs of two transcription factors, NF-AT1 and ZBRK1. Conclusions: A common genetic variant predicts the levels of circulating VEGF-A in cancer patients. A similar effect has been also shown in non-cancerous individuals (Debette S et al., Circ Res, 2011). Due to the central role of VEFG-A in the pathophysiology of many conditions, genetic testing could predict patients who have high versus low levels, potentially helping to guide the use of anti-angiogenesis therapies. Citation Format: Federico Innocenti, Chen Jiang, Alexander Sibley, Amy Etheridge, Yoichi Furukawa, Michiaki Kubo, Hedy L. Kindler, Alan P. Venook, Herber I. Hurwitz, Andrew B. Nixon, Kouros Owzar. Genetic prediction of VEGF-A plasma levels in cancer patients. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3388.