Aline Talhouk

Hereditary Diffuse Gastric Cancer Syndrome: CDH1 Mutations and Beyond

IMPORTANCE E-cadherin (CDH1) is a cancer predisposition gene mutated in families meeting clinically defined hereditary diffuse gastric cancer (HDGC). Reliable estimates of cancer risk and spectrum in germline mutation carriers are essential for management. For families without CDH1 mutations, genetic-based risk stratification has not been possible, resulting in limited clinical options. OBJECTIVES To derive accurate estimates of gastric and breast cancer risks in CDH1 mutation carriers and determine if germline mutations in other genes are associated with HDGC. DESIGN, SETTING, AND PARTICIPANTS Testing for CDH1 germline mutations was performed on 183 index cases meeting clinical criteria for HDGC. Penetrance was derived from 75 mutation-positive families from within this and other cohorts, comprising 3858 probands (353 with gastric cancer and 89 with breast cancer). Germline DNA from 144 HDGC probands lacking CDH1 mutations was screened using multiplexed targeted sequencing for 55 cancer-associated genes. MAIN OUTCOMES AND MEASURES Accurate estimates of gastric and breast cancer risks in CDH1 mutation carriers and the relative contribution of other cancer predisposition genes in familial gastric cancers. RESULTS Thirty-one distinct pathogenic CDH1 mutations (14 novel) were identified in 34 of 183 index cases (19%). By the age of 80 years, the cumulative incidence of gastric cancer was 70% (95% CI, 59%-80%) for males and 56% (95% CI, 44%-69%) for females, and the risk of breast cancer for females was 42% (95% CI, 23%-68%). In CDH1 mutation-negative index cases, candidate mutations were identified in 16 of 144 probands (11%), including mutations within genes of high and moderate penetrance: CTNNA1, BRCA2, STK11, SDHB, PRSS1, ATM, MSR1, and PALB2. CONCLUSIONS AND RELEVANCE This is the largest reported series of CDH1 mutation carriers, providing more precise estimates of age-associated risks of gastric and breast cancer that will improve counseling of unaffected carriers. In HDGC families lacking CDH1 mutations, testing of CTNNA1 and other tumor suppressor genes should be considered. Clinically defined HDGC families can harbor mutations in genes (ie, BRCA2) with different clinical ramifications from CDH1. Therefore, we propose that HDGC syndrome may be best defined by mutations in CDH1 and closely related genes, rather than through clinical criteria that capture families with heterogeneous susceptibility profiles.

A clinically applicable molecular-based classification for endometrial cancers.

Background:Classification of endometrial carcinomas (ECs) by morphologic features is inconsistent, and yields limited prognostic and predictive information. A new system for classification based on the molecular categories identified in The Cancer Genome Atlas is proposed.Methods:Genomic data from the Cancer Genome Atlas (TCGA) support classification of endometrial carcinomas into four prognostically significant subgroups; we used the TCGA data set to develop surrogate assays that could replicate the TCGA classification, but without the need for the labor-intensive and cost-prohibitive genomic methodology. Combinations of the most relevant assays were carried forward and tested on a new independent cohort of 152 endometrial carcinoma cases, and molecular vs clinical risk group stratification was compared.Results:Replication of TCGA survival curves was achieved with statistical significance using multiple different molecular classification models (16 total tested). Internal validation supported carrying forward a classifier based on the following components: mismatch repair protein immunohistochemistry, POLE mutational analysis and p53 immunohistochemistry as a surrogate for ‘copy-number’ status. The proposed molecular classifier was associated with clinical outcomes, as was stage, grade, lymph-vascular space invasion, nodal involvement and adjuvant treatment. In multivariable analysis both molecular classification and clinical risk groups were associated with outcomes, but differed greatly in composition of cases within each category, with half of POLE and mismatch repair loss subgroups residing within the clinically defined ‘high-risk’ group. Combining the molecular classifier with clinicopathologic features or risk groups provided the highest C-index for discrimination of outcome survival curves.Conclusions:Molecular classification of ECs can be achieved using clinically applicable methods on formalin-fixed paraffin-embedded samples, and provides independent prognostic information beyond established risk factors. This pragmatic molecular classification tool has potential to be used routinely in guiding treatment for individuals with endometrial carcinoma and in stratifying cases in future clinical trials.

Confirmation of ProMisE: A simple, genomics-based clinical classifier for endometrial cancer.

Classification of endometrial carcinomas (ECs) by morphologic features is irreproducible and imperfectly reflects tumor biology. The authors developed the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE), a molecular classification system based on The Cancer Genome Atlas genomic subgroups, and sought to confirm both feasibility and prognostic ability in a new, large cohort of ECs.

Endometrial carcinomas with POLE exonuclease domain mutations have a favorable prognosis

Purpose: The aim of this study was to confirm the prognostic significance of POLE exonuclease domain mutations (EDM) in endometrial carcinoma patients. In addition, the effect of treatment on POLE-mutated tumors was assessed. Experimental Design: A retrospective patient cohort of 496 endometrial carcinoma patients was identified for targeted sequencing of the POLE exonuclease domain, yielding 406 evaluable tumors. Univariable and multivariable analyses were performed to determine the effect of POLE mutation status on progression-free survival (PFS), disease-specific survival (DSS), and overall survival (OS). Combining results from eight studies in a meta-analysis, we computed pooled HR for PFS, DSS, and OS. Results: POLE EDMs were identified in 39 of 406 (9.6%) endometrial carcinomas. Women with POLE-mutated endometrial carcinomas were younger, with stage I (92%) tumors, grade 3 (62%), endometrioid histology (82%), and frequent (49%) lymphovascular invasion. In univariable analysis, POLE-mutated endometrial carcinomas had significantly improved outcomes compared with patients with no EDMs for PFS, DSS, and OS. In multivariable analysis, POLE EDMs were only significantly associated with improved PFS. The effect of adjuvant treatment on POLE-mutated cases could not be determined conclusively; however, both treated and untreated patients with POLE EDMs had good outcomes. Meta-analysis revealed an association between POLE EDMs and improved PFS and DSS with pooled HRs 0.34 [95% confidence interval (CI), 0.15–0.73] and 0.35 (95% CI, 0.13–0.92), respectively. Conclusions: POLE EDMs are prognostic markers associated with excellent outcomes for endometrial carcinoma patients. Further investigation is needed to conclusively determine if treatment is necessary for this group of women. Clin Cancer Res; 22(12); 2865–73. ©2016 AACR.

Morphologic and Molecular Characteristics of Mixed Epithelial Ovarian Cancers.

Epithelial ovarian cancer (EOC) consists of 5 major histotypes: high-grade serous carcinoma (HGSC), endometrioid carcinoma (EC), clear cell carcinoma (CCC), mucinous carcinoma (MC), and low-grade serous carcinoma (LGSC). Each can have a broad spectrum of morphologic appearances, and 1 histotype can closely mimic histopathologic features more typical of another. Historically, there has been a relatively high frequency of mixed, defined by 2 or more distinct histotypes present on the basis of routine histopathologic assessment, histotype carcinoma diagnoses (3% to 11%); however, recent immunohistochemical (IHC) studies identifying histotype-specific markers and allowing more refined histotype diagnoses suggest a much lower incidence. We reviewed hematoxylin and eosin–stained slides from 871 cases of EOC and found the frequency of mixed carcinomas to be 1.7% when modern diagnostic criteria are applied. Through international collaboration, we established a cohort totaling 22 mixed EOCs, consisting of 9 EC/CCC, 4 EC/LGSC, 3 HGSC/CCC, 2 CCC/MC, and 4 other combinations. We interrogated the molecular differences between the different components of each case using IHC, gene expression, and hotspot sequencing analyses. IHC data alone suggested that 9 of the 22 cases were not mixed tumors, as they presented a uniform immuno-phenotype throughout, and these cases most probably represent morphologic mimicry and variation within tumors of a single histotype. Synthesis of molecular data further reduces the incidence of mixed carcinomas. On the basis of these results, true mixed carcinomas with both morphologic and molecular support for the presence of >1 histotype within a given tumor represent <1% of EOCs.

Neoadjuvant chemotherapy of ovarian cancer results in three patterns of tumor-infiltrating lymphocyte response with distinct implications for immunotherapy.

Purpose: Some forms of chemotherapy can enhance antitumor immunity through immunogenic cell death, resulting in increased T-cell activation and tumor infiltration. Such effects could potentially sensitize tumors to immunotherapies, including checkpoint blockade. We investigated whether platinum- and taxane-based chemotherapy for ovarian cancer induces immunologic changes consistent with this possibility. Experimental Design: Matched pre- and post-neoadjuvant chemotherapy tumor samples from 26 high-grade serous carcinoma (HGSC) patients were analyzed by immunohistochemistry (IHC) for a large panel of immune cells and associated factors. The prognostic significance of post-chemotherapy TIL patterns was assessed in an expanded cohort (n = 90). Results: Neoadjuvant chemotherapy was associated with increased densities of CD3+, CD8+, CD8+ TIA-1+, PD-1+ and CD20+ TIL. Other immune subsets and factors were unchanged, including CD79a+ CD138+ plasma cells, CD68+ macrophages, and MHC class I on tumor cells. Immunosuppressive cell types were also unchanged, including FoxP3+ PD-1+ cells (putative regulatory T cells), IDO-1+ cells, and PD-L1+ cells (both macrophages and tumor cells). Hierarchical clustering revealed three response patterns: (i) TILhigh tumors showed increases in multiple immune markers after chemotherapy; (ii) TILlow tumors underwent similar increases, achieving patterns indistinguishable from the first group; and (iii) TILnegative cases generally remained negative. Despite the dramatic increases seen in the first two patterns, post-chemotherapy TIL showed limited prognostic significance. Conclusions: Chemotherapy augments pre-existing TIL responses but fails to relieve major immune-suppressive mechanisms or confer significant prognostic benefit. Our findings provide rationale for multipronged approaches to immunotherapy tailored to the baseline features of the tumor microenvironment. Clin Cancer Res; 23(4); 925–34. ©2016 AACR.

Molecularly Defined Adult Granulosa Cell Tumor of the Ovary: The Clinical Phenotype

The histopathologic features of adult granulosa cell tumors (AGCTs) are relatively nonspecific, resulting in misdiagnosis of other cancers as AGCT, a problem that has not been well characterized. FOXL2 mutation testing was used to stratify 336 AGCTs from three European centers into three categories: 1) FOXL2 mutant molecularly defined AGCT (MD-AGCT) (n = 256 of 336), 2) FOXL2 wild-type AGCT (n = 17 of 336), 3) misdiagnosed other tumor types (n = 63 of 336). All statistical tests were two-sided. The overall and disease-specific survival of the misdiagnosed cases was lower than in the MD-AGCTs (P < .001). The misdiagnosed cases accounted for 71.9% of disease-specific deaths within five years. In the population-based cohort, overall survival of MD-AGCT patients was not different from age-matched, population-based controls. Even though 35.2% of all the MD-AGCT patients in our study experienced a relapse, AGCT is usually an indolent disease. The historical, premolecular data underpinning our clinical understanding of AGCT was likely skewed by inclusion of misdiagnosed cases, and future management strategies should reflect the potential for surgical cure and long survival even after relapse.

New classification of endometrial cancers: the development and potential applications of genomic-based classification in research and clinical care

Endometrial carcinoma (EC) is the fourth most common cancer in women in the developed world. Classification of ECs by histomorphologic criteria has limited reproducibility and better tools are needed to distinguish these tumors and enable a subtype-specific approach to research and clinical care. Based on the Cancer Genome Atlas, two research teams have developed pragmatic molecular classifiers that identify four prognostically distinct molecular subgroups. These methods can be applied to diagnostic specimens (e.g., endometrial biopsy) with the potential to completely change the current risk stratification systems and enable earlier informed decision making. The evolution of genomic classification in ECs is shared herein, as well as potential applications and discussion of the essential research still needed in order to optimally integrate molecular classification in to current standard of care.

Efficient Bayesian Inference for Multivariate Probit Models With Sparse Inverse Correlation Matrices

We propose a Bayesian approach for inference in the multivariate probit model, taking into account the association structure between binary observations. We model the association through the correlation matrix of the latent Gaussian variables. Conditional independence is imposed by setting some off-diagonal elements of the inverse correlation matrix to zero and this sparsity structure is modeled using a decomposable graphical model. We propose an efficient Markov chain Monte Carlo algorithm relying on a parameter expansion scheme to sample from the resulting posterior distribution. This algorithm updates the correlation matrix within a simple Gibbs sampling framework and allows us to infer the correlation structure from the data, generalizing methods used for inference in decomposable Gaussian graphical models to multivariate binary observations. We demonstrate the performance of this model and of the Markov chain Monte Carlo algorithm on simulated and real datasets. This article has online supplementary materials.

Final validation of the ProMisE molecular classifier for endometrial carcinoma in a large population-based case series

Background We have previously developed and confirmed a pragmatic molecular classifier for endometrial cancers; ProMisE (Proactive Molecular Risk Classifier for Endometrial Cancer). Inspired by the Cancer Genome Atlas, ProMisE identifies four prognostically distinct molecular subtypes and can be applied to diagnostic specimens (biopsy/curettings) enabling earlier informed decision-making. We have strictly adhered to the Institute of Medicine (IOM) guidelines for the development of genomic biomarkers, and herein present the final validation step of a locked-down classifier before clinical application. Patients and methods We assessed a retrospective cohort of women from the Tübingen University Womens Hospital treated for endometrial carcinoma between 2003 and 2013. Primary outcomes of overall, disease-specific, and progression-free survival were evaluated for clinical, pathological, and molecular features. Results Complete clinical and molecular data were evaluable from 452 women. Patient age ranged from 29 to 93 (median 65) years, and 87.8% cases were endometrioid histotype. Grade distribution included 282 (62.4%) G1, 75 (16.6%) G2, and 95 (21.0%) G3 tumors. 276 (61.1%) patients had stage IA disease, with the remaining stage IB [89 (19.7%)], stage II [26 (5.8%)], and stage III/IV [61 (13.5%)]. ProMisE molecular classification yielded 127 (28.1%) MMR-D, 42 (9.3%) POLE, 55 (12.2%) p53abn, and 228 (50.4%) p53wt. ProMisE was a prognostic marker for progression-free (P = 0.001) and disease-specific (P = 0.03) survival even after adjusting for known risk factors. Concordance between diagnostic and surgical specimens was highly favorable; accuracy 0.91, κ 0.88. Discussion We have developed, confirmed, and now validated a pragmatic molecular classification tool (ProMisE) that provides consistent categorization of tumors and identifies four distinct prognostic molecular subtypes. ProMisE can be applied to diagnostic samples and thus could be used to inform surgical procedure(s) and/or need for adjuvant therapy. Based on the IOM guidelines this classifier is now ready for clinical evaluation through prospective clinical trials.