Hector Li-Chang

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.

Synchronous Endometrial and Ovarian Carcinomas: Evidence of Clonality

Many women with ovarian endometrioid carcinoma present with concurrent endometrial carcinoma. Organ-confined and low-grade synchronous endometrial and ovarian tumors (SEOs) clinically behave as independent primary tumors rather than a single advanced-stage carcinoma. We used 18 SEOs to investigate the ancestral relationship between the endometrial and ovarian components. Based on both targeted and exome sequencing, 17 of 18 patient cases of simultaneous cancer of the endometrium and ovary from our series showed evidence of a clonal relationship, ie, primary tumor and metastasis. Eleven patient cases fulfilled clinicopathological criteria that would lead to classification as independent endometrial and ovarian primary carcinomas, including being of FIGO stage T1a/1A, with organ-restricted growth and without surface involvement; 10 of 11 of these cases showed evidence of clonality. Our observations suggest that the disseminating cells amongst SEOs are restricted to physically accessible and microenvironment-compatible sites yet remain indolent, without the capacity for further dissemination.

Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes

We studied the whole-genome point mutation and structural variation patterns of 133 tumors (59 high-grade serous (HGSC), 35 clear cell (CCOC), 29 endometrioid (ENOC), and 10 adult granulosa cell (GCT)) as a substrate for class discovery in ovarian cancer. Ab initio clustering of integrated point mutation and structural variation signatures identified seven subgroups both between and within histotypes. Prevalence of foldback inversions identified a prognostically significant HGSC group associated with inferior survival. This finding was recapitulated in two independent cohorts (n = 576 cases), transcending BRCA1 and BRCA2 mutation and gene expression features of HGSC. CCOC cancers grouped according to APOBEC deamination (26%) and age-related mutational signatures (40%). ENOCs were divided by cases with microsatellite instability (28%), with a distinct mismatch-repair mutation signature. Taken together, our work establishes the potency of the somatic genome, reflective of diverse DNA repair deficiencies, to stratify ovarian cancers into distinct biological strata within the major histotypes.

Personalized oncogenomics: clinical experience with malignant peritoneal mesothelioma using whole genome sequencing.

Peritoneal mesothelioma is a rare and sometimes lethal malignancy that presents a clinical challenge for both diagnosis and management. Recent studies have led to a better understanding of the molecular biology of peritoneal mesothelioma. Translation of the emerging data into better treatments and outcome is needed. From two patients with peritoneal mesothelioma, we derived whole genome sequences, RNA expression profiles, and targeted deep sequencing data. Molecular data were made available for translation into a clinical treatment plan. Treatment responses and outcomes were later examined in the context of molecular findings. Molecular studies presented here provide the first reported whole genome sequences of peritoneal mesothelioma. Mutations in known mesothelioma-related genes NF2, CDKN2A, LATS2, amongst others, were identified. Activation of MET-related signaling pathways was demonstrated in both cases. A hypermutated phenotype was observed in one case (434 vs. 18 single nucleotide variants) and was associated with a favourable outcome despite sarcomatoid histology and multifocal disease. This study represents the first report of whole genome analyses of peritoneal mesothelioma, a key step in the understanding and treatment of this disease.

HER2/neu Testing in Gastric Cancer by Immunohistochemistry: Assessment of Interlaboratory Variation

CONTEXT Immunohistochemical (IHC) testing for HER2/neu is becoming the standard of care for guiding adjuvant treatment of gastric carcinoma with trastuzumab. OBJECTIVE To assess interlaboratory variation in IHC staining and interpretation across multiple laboratories. DESIGN A tissue microarray consisting of 45 cores from 28 gastric cancers was distributed to 37 laboratories for HER2/neu assessment. The IHC results were compared against expert scores at an academic institution and correlated with in situ hybridization results from the originating specimen. Interlaboratory agreement was calculated using Cohen κ statistic. RESULTS The survey demonstrated several variations in IHC methods, including the primary antibodies in use. There was excellent agreement among laboratories in HER2/neu(+) (IHC 3(+)) cases (κ = 0.80 ± 0.01) and very good agreement among laboratories in HER2/neu(-) (IHC 0 or 1(+)) cases (κ = 0.58 ± 0.01). Less agreement was observed among laboratories when scoring equivocal (IHC 2(+)) cases (κ = 0.22 ± 0.01). Sensitivity and specificity of HER2/neu IHC were 99% and 100%, respectively, when measured against expert review and consensus score as a reference standard. CONCLUSIONS There is substantial interlaboratory agreement in the interpretation of HER2/neu IHC despite variability in protocols. Although HER2/neu IHC is a highly sensitive and specific test, primary antibody selection may significantly affect IHC results. Furthermore, gastric tumors require a unique scoring system and expertise in interpretation. Intratumoral heterogeneity has a significant effect on HER2/neu scoring by IHC. Ongoing quality assurance exercises among laboratories will help ensure optimized HER2/neu testing.

Tumor budding is an independent adverse prognostic factor in pancreatic ductal adenocarcinoma.

Tumor budding is a well-established adverse prognostic factor in colorectal cancer. However, the significance and diagnostic reproducibility of budding in pancreatic carcinoma requires further study. We aimed to assess the prognostic significance of tumor budding in pancreatic ductal adenocarcinoma, determine its relationship with other clinicopathologic features, and assess interobserver variability in its diagnosis. Tumor budding was assessed in 192 archival cases of pancreatic ductal adenocarcinoma using hematoxylin and eosin (H&E) sections; tumor buds were defined as single cells or nonglandular clusters composed of <5 cells. The presence of budding was determined through assessment of all tumor-containing slides, and associations with clinicopathologic features and outcomes were analyzed. Six gastrointestinal pathologists participated in an interobserver variability study of 120 images of consecutive tumor slides stained with H&E and cytokeratin. Budding was present in 168 of 192 cases and was associated with decreased overall survival (P=0.001). On multivariable analysis, tumor budding was prognostically significantly independent of stage, grade, tumor size, nodal status, lymphovascular invasion, and perineural invasion. There was substantial agreement among pathologists in assessing the presence of tumor budding using both H&E (K=0.63) and cytokeratin (K=0.63) stains. The presence of tumor budding is an independent adverse prognostic factor in pancreatic ductal carcinoma. The assessment of budding with H&E is reliable and could be used to better risk stratify patients with pancreatic ductal adenocarcinoma.

ARID1A/BAF250a as a prognostic marker for gastric carcinoma: a study of 2 cohorts

ARID1A/BAF250a has been recently implicated as a tumor suppressor in gastric cancer. We sought to clarify the clinical significance of BAF250a/ARID1A in relation to other clinical parameters and relevant biomarkers in gastric carcinoma. Cases from 2 separate cohorts of patients with gastric carcinoma from Vancouver (n = 173) and Toronto (n = 80) were selected for the construction of tissue microarrays, which were used to assess the immunohistochemical status of BAF250a (anti-ARID1A), mismatch repair proteins and p53, as well as in situ hybridization for HER2 amplification and Epstein-Barr virus infection. The Toronto cohort contained a higher proportion of early stage cases (P = .019) and a smaller proportion of cases from the proximal stomach (P < .001). Overall, immunohistochemical loss of BAF250a was observed in 22.5% of gastric adenocarcinomas from the Vancouver group and 20% from Toronto. In both cohorts, loss of BAF250a was positively associated with loss of mismatch repair protein expression (P < .0001 and P = .035, respectively). Loss of BAF250a expression was independently associated with poor overall survival in the Toronto cohort (P = .0015), whereas no significant association with survival was observed in the Vancouver cohort. BAF250a loss was not significantly associated with any additional clinical parameters in either cohort. HER2 amplification was confirmed as a negative prognostic factor in both cohorts. These findings suggest that ARID1A/BAF250a may be of prognostic significance in a subset of patients with early stage gastric cancer and that pathological assessment should increasingly use a multimarker approach.

Mismatch repair status may predict response to adjuvant chemotherapy in resectable pancreatic ductal adenocarcinoma

Deficiencies in DNA mismatch repair have been associated with inferior response to 5-FU in colorectal cancer. Pancreatic ductal adenocarcinoma is similarly treated with pyrimidine analogs, yet the predictive value of mismatch repair status for response to these agents has not been examined in this malignancy. A tissue microarray with associated clinical outcome, comprising 254 resected pancreatic ductal adenocarcinoma patients was stained for four mismatch repair proteins (MLH1, MSH2, MSH6 and PMS2). Mismatch repair deficiency and proficiency was determined by the absence or presence of uniform nuclear staining in tumor cells, respectively. Cases identified as mismatch repair deficient on the tissue microarray were confirmed by immunohistochemistry on whole slide sections. Of the 265 cases, 78 (29%) received adjuvant treatment with a pyrimidine analog and 41 (15%) showed a mismatch repair-deficient immunoprofile. Multivariable disease-specific survival in the mismatch repair-proficient cohort demonstrated that adjuvant chemotherapy, regional lymph-node status, gender, and the presence of tumor budding were significant independent prognostic variables (P≤0.04); however, none of the eight clinico-pathologic covariates examined in the mismatch repair-deficient cohort were of independent prognostic significance. Univariable assessment of disease-specific survival revealed an almost identical survival profile for both treated and untreated patients with a mismatch repair-deficient profile, while treatment in the mismatch repair-proficient cohort conferred a greater than 10-month median disease-specific survival advantage over their untreated counterparts (P=0.0018). In this cohort, adjuvant chemotherapy with a pyrimidine analog conferred no survival advantage to mismatch repair-deficient pancreatic ductal adenocarcinoma patients. Mismatch repair immunoprofiling is a feasible predictive marker in pancreatic ductal adenocarcinoma patients, and further prospective evaluation of this finding is warranted.

Automatic Diagnosis of Ovarian Carcinomas via Sparse Multiresolution Tissue Representation

It has now been convincingly demonstrated that ovarian carcinoma subtypes are not a single disease but comprise a heterogeneous group of neoplasms. Whole slide images of tissue sections are used clinically for diagnosing biologically distinct subtypes, as opposed to different grades of the same disease. This new grading scheme for ovarian carcinomas results in a low to moderate interobserver agreement among pathologists. In practice, the majority of cases are diagnosed at advanced stages and the overall prognosis is typically poor. In this work, we propose an automatic system for the diagnosis of ovarian carcinoma subtypes from large-scale histopathology images. Our novel approach uses an unsupervised feature learning framework composed of a sparse tissue representation and a discriminative feature encoding scheme. We validate our model on a challenging clinical dataset of 80 patients and demonstrate its ability to diagnose whole slide images with an average accuracy of 91% using a linear support vector machine classifier.