Person: Dong, Fei
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Dong
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Dong, Fei
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Publication Computational Pathology to Discriminate Benign from Malignant Intraductal Proliferations of the Breast(Public Library of Science, 2014) Dong, Fei; Irshad, Humayun; Oh, Eun-Yeong; Lerwill, Melinda F.; Brachtel, Elena; Jones, Nicholas C.; Knoblauch, Nicholas W.; Montaser-Kouhsari, Laleh; Johnson, Nicole B.; Rao, Luigi K. F.; Faulkner-Jones, Beverly; Wilbur, David; Schnitt, Stuart; Beck, AndrewThe categorization of intraductal proliferative lesions of the breast based on routine light microscopic examination of histopathologic sections is in many cases challenging, even for experienced pathologists. The development of computational tools to aid pathologists in the characterization of these lesions would have great diagnostic and clinical value. As a first step to address this issue, we evaluated the ability of computational image analysis to accurately classify DCIS and UDH and to stratify nuclear grade within DCIS. Using 116 breast biopsies diagnosed as DCIS or UDH from the Massachusetts General Hospital (MGH), we developed a computational method to extract 392 features corresponding to the mean and standard deviation in nuclear size and shape, intensity, and texture across 8 color channels. We used L1-regularized logistic regression to build classification models to discriminate DCIS from UDH. The top-performing model contained 22 active features and achieved an AUC of 0.95 in cross-validation on the MGH data-set. We applied this model to an external validation set of 51 breast biopsies diagnosed as DCIS or UDH from the Beth Israel Deaconess Medical Center, and the model achieved an AUC of 0.86. The top-performing model contained active features from all color-spaces and from the three classes of features (morphology, intensity, and texture), suggesting the value of each for prediction. We built models to stratify grade within DCIS and obtained strong performance for stratifying low nuclear grade vs. high nuclear grade DCIS (AUC = 0.98 in cross-validation) with only moderate performance for discriminating low nuclear grade vs. intermediate nuclear grade and intermediate nuclear grade vs. high nuclear grade DCIS (AUC = 0.83 and 0.69, respectively). These data show that computational pathology models can robustly discriminate benign from malignant intraductal proliferative lesions of the breast and may aid pathologists in the diagnosis and classification of these lesions.Publication GNAS mutations in primary mucinous and non-mucinous lung adenocarcinomas(Springer Science and Business Media LLC, 2017-08-04) Ritterhouse, Lauren; Vivero, Marina; Mino-Kenudson, Mari; Sholl, Lynette; Iafrate, Anthony; Nardi, Valentina; Dong, FeiGNAS mutations have been described in mucinous and non-mucinous epithelial neoplasms of the appendix, pancreas, and colon, with hotspot GNAS mutations found in up to two-thirds of pancreatic intraductal papillary mucinous neoplasms. Additionally, many GNAS-mutated tumors have concurrent mutations in the Ras/Raf pathway. The clinicopathologic features of GNAS-mutated lung carcinomas, however, have not yet been characterized. Primary lung carcinomas from Brigham and Women's Hospital (n=1282) or Massachusetts General Hospital (n=1070) were genotyped on a targeted massively parallel sequencing panel of oncogenes and tumor suppressor genes including GNAS. Clinical and pathological features were reviewed, and TTF-1 immunohistochemistry was performed when material was available. Nineteen lung adenocarcinomas with hotspot GNAS mutations were identified (19/2352, 0.8%) including 14 at codon 201 and 5 at codon 227. GNAS-mutated lung adenocarcinomas occurred predominantly in female patients (16/19, 84%). Ten (10) were classified as invasive mucinous adenocarcinomas (IMA), and nine (9) were non-mucinous adenocarcinomas. All IMAs had GNAS codon 201 mutations and concurrent Ras/Raf pathway mutations (9 KRAS, 1 BRAF). No tumors with GNAS codon 227 mutations had mucinous histological features. 86% of GNAS-mutated non-mucinous adenocarcinomas (6/7) were positive for TTF-1 immunohistochemistry, while only 25% of GNAS-mutated IMAs (1/4) were positive for TTF-1. Patients with GNAS-mutated non-mucinous adenocarcinomas were more likely to have a history of smoking (9/9, 100%) compared to patients with GNAS-mutated IMAs (2/10, 20%) (P<0.001). Hotspot GNAS mutations can occur in primary lung adenocarcinomas. When associated with concurrent mutations in the Ras/Raf pathway, these neoplasms often present as IMAs. GNAS mutations are not specific to neoplasms of the gastrointestinal tract, and clinicopathologic correlation is necessary in GNAS-mutated adenocarcinomas in the lung to determine the primary site of origin.Publication Detection of ERBB2 Amplification in Uterine Serous Carcinoma by Next-Generation Sequencing: An Approach Highly Concordant With Standard Assays(Springer Science and Business Media LLC, 2020-10-19) Robinson, Carrie; Harrison, Beth; Ligon, Azra; Dong, Fei; Maffeis, Valeria; Matulonis, Ursula; Nucci, Marisa; Kolin, David L.Uterine serous carcinoma is an aggressive subtype of endometrial cancer that accounts for fewer than 10% of endometrial carcinomas but is responsible for about half of deaths. A subset of cases has HER2 overexpression secondary to ERBB2 gene amplification, and these patients may benefit from anti-HER2 therapies, such as trastuzumab. HER2 protein overexpression is currently assessed by immunohistochemistry (IHC) and ERBB2 gene amplification by fluorescence in situ hybridization (FISH). Targeted next-generation sequencing (NGS) is increasingly used to routinely identify predictive and prognostic molecular abnormalities in endometrial carcinoma. To investigate the ability of a targeted NGS panel to detect ERBB2 amplification, we identified cases of uterine serous carcinoma (n=93) and compared HER2 expression by IHC and copy number assessed by FISH with copy number status assessed by NGS. ERBB2 copy number status using a combination of IHC and FISH was interpreted using the 2018 ASCO/CAP guidelines for breast carcinoma. ERBB2 amplification by NGS was determined by the relative number of reads mapping to ERBB2 in tumor DNA compared to control non-neoplastic DNA. Cases with copy number ≥6 were considered amplified and copy number <6 were non-amplified. By IHC, 70 specimens were classified as negative (0 or 1+), 19 were classified as equivocal (2+), and 4 were classified as positive (3+). Using combined IHC/FISH, ERBB2 amplification was observed in 8 of 93 cases (9%). NGS identified the same 8 cases with copy number ≥6; all 85 others had copy number <6. In this series, NGS had 100% concordance with combined IHC/FISH in identifying ERBB2 amplification. NGS is highly accurate in detecting ERBB2 amplification in uterine serous carcinoma and provides an alternative to measurement by IHC and FISH.