Purpose There is persistent controversy as to whether EGFR/KRAS mutations occur in pulmonary squamous cell carcinoma (SQCC). We hypothesized that the reported variability may reflect difficulties in the pathologic distinction of true SQCC from adenosquamous carcinoma (AD-SQC) and poorly-differentiated adenocarcinoma (ADC) due to incomplete sampling or morphologic overlap. The recent development of a robust immunohistochemical approach for distinguishing squamous vs glandular differentiation provides an opportunity to reassess EGFR/KRAS and other targetable kinase mutation frequencies in a pathologically homogeneous series of SQCC. Experimental Design Ninety-five resected SQCC, verified by immunohistochemistry as ΔNp63+/TTF-1−, were tested for activating mutations in EGFR, KRAS, BRAF, PIK3CA, NRAS, AKT1, ERBB2/HER2, and MAP2K1/MEK1. Additionally, all tissue samples from rare patients with the diagnosis of EGFR/KRAS-mutant “SQCC” encountered during5 years of routine clinical genotyping were reassessed pathologically. Results The screen of 95biomarker-verified SQCC revealed no EGFR/KRAS (0%; 95%CI 0–3.8%), 4 PIK3CA (4%; 95% CI 1–10%) and 1 AKT1 (1%; 95% CI 0–5.7%) mutations. Detailed morphologic and immunohistochemical reevaluation of EGFR/KRAS-mutant SQCC” identified during clinical genotyping (n=16) resulted in reclassification of 10 (63%)cases as AD-SQC and 5 (31%) cases as poorly-differentiated ADC morphologically mimicking SQCC (i.e. ADC with “squamoid” morphology). One (6%) case had no follow-up. Conclusions Our findings suggest that EGFR/KRAS mutations do not occur in pure pulmonary SQCC, and occasional detection of these mutations in samples diagnosed as “SQCC” is due to challenges with the diagnosis of AD-SQC and ADC, which can be largely resolved by comprehensive pathologic assessment incorporating immunohistochemical biomarkers.
Carcinomas of the endometrium and ovary with undifferentiated components are uncommon neoplasms that are likely underdiagnosed. They are important to recognize as they have been shown to be clinically aggressive. We identified 32 carcinomas with undifferentiated components as defined by Silva and co-workers, 26 endometrial and 6 of ovarian origin. The patient age ranged from 21 to 76 years (median 55); 40% of patients were r50 years of age. Most patients (58% of endometrial and 83% of ovarian carcinomas with undifferentiated components) presented at advanced stages (FIGO III-IV). Pelvic and para-aortic lymph nodes were the most frequent sites of metastases. Twenty tumors, entirely undifferentiated, consisted of sheets of dyshesive, ovoid cells with uniform, large vesicular nuclei, whereas 12 tumors contained combinations of differentiated endometrioid adenocarcinoma with undifferentiated components. Although most undifferentiated tumors had a monotonous cytologic appearance without prominent stroma, six showed focal nuclear pleomorphism and eight cases had variably sized zones of rhabdoid cells in a background of myxoid stroma. The tumors were frequently misdiagnosed; they received a wide range of diagnoses, including FIGO grade 2 or 3 endometrioid carcinoma, carcinosarcoma, high-grade sarcoma including endometrial stromal sarcoma, neuroendocrine carcinoma, lymphoma, granulosa cell tumor and epithelioid sarcoma. Up to 86% of the cases showed focal, but strong keratin and/or epithelial membrane antigen staining, with CK18 being the most frequently positive keratin stain. They were predominantly negative for neuroendocrine markers, smooth muscle markers and estrogen receptor/progesterone receptor. Mismatch repair protein expression by immunohistochemistry was evaluated in 17 cases, and 8 (47%) were abnormal (7 with loss of MLH1/PMS2 and 1 with MSH6 loss). Follow-up was available for 27 patients, although it was very short in many cases, ranging from 0.5 to 89 months (median 9 months). Eleven patients (41%) died of the disease in 0.5-20 months, four are alive with disease and twelve patients have no evidence of disease. Endometrial and ovarian carcinomas with undifferentiated components have a broad histologic differential diagnosis, but they show specific histologic features that should enable accurate diagnosis. These tumors can occur in young women, may be associated with microsatellite instability and behave in a clinically aggressive manner.
Approximately 20% of Western patients with metastatic gastric cancer are HER2 positive. Unlike breast cancer, HER2 positivity is not independently prognostic of patient outcome in metastatic gastric or GEJ.
Classification of histologic patterns in lung adenocarcinoma is critical for determining tumor grade and treatment for patients. However, this task is often challenging due to the heterogeneous nature of lung adenocarcinoma and the subjective criteria for evaluation. In this study, we propose a deep learning model that automatically classifies the histologic patterns of lung adenocarcinoma on surgical resection slides. Our model uses a convolutional neural network to identify regions of neoplastic cells, then aggregates those classifications to infer predominant and minor histologic patterns for any given whole-slide image. We evaluated our model on an independent set of 143 whole-slide images. It achieved a kappa score of 0.525 and an agreement of 66.6% with three pathologists for classifying the predominant patterns, slightly higher than the inter-pathologist kappa score of 0.485 and agreement of 62.7% on this test set. All evaluation metrics for our model and the three pathologists were within 95% confidence intervals of agreement. If confirmed in clinical practice, our model can assist pathologists in improving classification of lung adenocarcinoma patterns by automatically pre-screening and highlighting cancerous regions prior to review. Our approach can be generalized to any whole-slide image classification task, and code is made publicly available at https://github.com/BMIRDS/deepslide .
BackgroundImmune checkpoint inhibitors (ICIs) have changed the clinical management of melanoma. However, not all patients respond, and current biomarkers including PD-L1 and mutational burden show incomplete predictive performance. The clinical validity and utility of complex biomarkers have not been studied in melanoma.MethodsCutaneous metastatic melanoma patients at eight institutions were evaluated for PD-L1 expression, CD8+ T-cell infiltration pattern, mutational burden, and 394 immune transcript expression. PD-L1 IHC and mutational burden were assessed for association with overall survival (OS) in 94 patients treated prior to ICI approval by the FDA (historical-controls), and in 137 patients treated with ICIs. Unsupervised analysis revealed distinct immune-clusters with separate response rates. This comprehensive immune profiling data were then integrated to generate a continuous Response Score (RS) based upon response criteria (RECIST v.1.1). RS was developed using a single institution training cohort (n = 48) and subsequently tested in a separate eight institution validation cohort (n = 29) to mimic a real-world clinical scenario.ResultsPD-L1 positivity ≥1% correlated with response and OS in ICI-treated patients, but demonstrated limited predictive performance. High mutational burden was associated with response in ICI-treated patients, but not with OS. Comprehensive immune profiling using RS demonstrated higher sensitivity (72.2%) compared to PD-L1 IHC (34.25%) and tumor mutational burden (32.5%), but with similar specificity.ConclusionsIn this study, the response score derived from comprehensive immune profiling in a limited melanoma cohort showed improved predictive performance as compared to PD-L1 IHC and tumor mutational burden.Electronic supplementary materialThe online version of this article (10.1186/s40425-018-0344-8) contains supplementary material, which is available to authorized users.
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