Caldas, Carlos

Abstract Purpose: The aim of PREDICT was to confirm clinical validity and the potential for clinical utility of serial circulating tumor cell (CTC) enumeration in patients with metastatic breast cancer, focusing on its prognostic value in different breast cancer subtypes and clinical settings. Experimental Design: In total, 4,436 individual patient-level data with CTC results from both baseline and one follow-up (CellSearch; Menarini Silicon Biosystems) were analyzed to evaluate the association between CTC detection and overall survival (OS) in the full patient cohort and separately for tumor and treatment types. Results: Using the cutoff ≥1 CTC for CTC positivity, 913 (20.6%) patients had 0 CTCs at both time points (neg/neg) and 325 (7.3%) and 1,189 (26.8%) patients converted from CTC negative to CTC positive (neg/pos) or vice versa (pos/neg), whereas 2,009 (45.3%) patients had at least one CTC at both time points (pos/pos). The median OS for the neg/neg, neg/pos, pos/neg, and pos/pos group was 45.6, 26.1, 32.3, and 17.3 months, respectively (P < 0.0001, global log-rank test). CTC responders (pos/neg) showed a lower risk of death compared with CTC nonresponders (pos/pos; HR, 0.48; 95% confidence interval, 0.44–0.53). Similar results were obtained in subgroup analyses according to hormone receptor and HER2 subtype, treatment type, and with a ≥5 CTC cutoff for CTC positivity. Conclusions: Follow-up CTC assessments strongly predict OS independently from tumor subtype and treatment. New randomized trials to define the clinical utility of CTC monitoring for risk stratification and as an early response marker in metastatic breast cancer are urgently needed.

Abstract Background: Over 20 susceptibility single-nucleotide polymorphisms (SNP) have been identified for esophageal adenocarcinoma (EAC) and its precursor, Barrett esophagus (BE), explaining a small portion of heritability. Methods: Using genetic data from 4,323 BE and 4,116 EAC patients aggregated by international consortia including the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON), we conducted a comprehensive transcriptome-wide association study (TWAS) for BE/EAC, leveraging Genotype Tissue Expression (GTEx) gene-expression data from six tissue types of plausible relevance to EAC etiology: mucosa and muscularis from the esophagus, gastroesophageal (GE) junction, stomach, whole blood, and visceral adipose. Two analytical approaches were taken: standard TWAS using the predicted gene expression from local expression quantitative trait loci (eQTL), and set-based SKAT association using selected eQTLs that predict the gene expression. Results: Although the standard approach did not identify significant signals, the eQTL set–based approach identified eight novel associations, three of which were validated in independent external data (eQTL SNP sets for EXOC3, ZNF641, and HSP90AA1). Conclusions: This study identified novel genetic susceptibility loci for EAC and BE using an eQTL set–based genetic association approach. Impact: This study expanded the pool of genetic susceptibility loci for EAC and BE, suggesting the potential of the eQTL set–based genetic association approach as an alternative method for TWAS analysis.

A robust personalized ctDNA test, TARDIS, achieves high accuracy for residual disease after completion of neoadjuvant therapy.

Abstract Patient-derived tumor xenograft (PDX) mouse models have emerged as an important oncology research platform to study tumor evolution, mechanisms of drug response and resistance, and tailoring chemotherapeutic approaches for individual patients. The lack of robust standards for reporting on PDX models has hampered the ability of researchers to find relevant PDX models and associated data. Here we present the PDX models minimal information standard (PDX-MI) for reporting on the generation, quality assurance, and use of PDX models. PDX-MI defines the minimal information for describing the clinical attributes of a patient's tumor, the processes of implantation and passaging of tumors in a host mouse strain, quality assurance methods, and the use of PDX models in cancer research. Adherence to PDX-MI standards will facilitate accurate search results for oncology models and their associated data across distributed repository databases and promote reproducibility in research studies using these models. Cancer Res; 77(21); e62–66. ©2017 AACR.

Objective Oesophageal adenocarcinoma (OA) incidence has risen sharply in Western countries over recent decades. Local and systemic inflammation is considered an important contributor to OA pathogenesis. Established risk factors for OA and its precursor, Barrett's oesophagus (BE), include symptomatic reflux, obesity and smoking. The role of inherited genetic susceptibility remains an area of active investigation. Here, we explore whether germline variation related to inflammatory processes influences susceptibility to BE/OA. Design We used data from a genomewide association study of 2515 OA cases, 3295 BE cases and 3207 controls. Our analysis included 7863 single-nucleotide polymorphisms (SNPs) in 449 genes assigned to five pathways: cyclooxygenase (COX), cytokine signalling, oxidative stress, human leucocyte antigen and nuclear factor-κB. A principal components-based analytic framework was employed to evaluate pathway-level and gene-level associations with disease risk. Results We identified a significant signal for the COX pathway in relation to BE risk (p=0.0059, false discovery rate q=0.03), and in gene-level analyses found an association with microsomal glutathione-S-transferase 1 (MGST1); (p=0.0005, q=0.005). Assessment of 36 MGST1 SNPs identified 14 variants associated with elevated BE risk (q<0.05). Four of these were subsequently confirmed (p<5.5×10−5) in a meta-analysis encompassing an independent set of 1851 BE cases and 3496 controls, and are known strong expression quantitative trait loci for MGST1. Three such variants were associated with similar elevations in OA risk. Conclusions This study provides the most comprehensive evaluation of inflammation-related germline variation in relation to risk of BE/OA and suggests that variants in MGST1 influence disease susceptibility.

AbstractBreast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large‐scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65–70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose‐response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96–98%), but yielded many false positives (positive predictive value = 30–32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large‐scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker‐specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results.