Ocal, I Tolgay

Context.— Neoadjuvant systemic therapy refers to the use of systemic agent(s) for malignancy prior to surgical treatment and has recently emerged as an option for most breast cancer patients eligible for adjuvant systemic therapy. Consequently, treated breast carcinomas have become routine specimens in pathology practices. A standard protocol has not yet been universally adopted for the evaluation and reporting of these specimens. The American Joint Committee on Cancer staging system recognizes the challenges in staging breast carcinomas after neoadjuvant treatment and provides important data points but does not currently provide detailed guidance in estimating the residual tumor burden in the breast and lymph nodes. The Residual Cancer Burden system is the only Web-based system that quantifies treatment response as a continuous variable using residual tumor burden in the breast and the lymph nodes. Objective.— To provide clarifications and guidance for evaluation and reporting of postneoadjuvant breast specimens, discuss issues with the current staging and reporting systems, and provide specific suggestions for future modifications to the American Joint Committee on Cancer system and the Residual Cancer Burden calculator. Data Sources.— English-language literature on the subject and the data from the I-SPY 2, a multicenter, adaptive randomization phase 2 neoadjuvant platform trial for early-stage, high-risk breast cancer patients. Conclusions.— This article highlights challenges in the pathologic evaluation and reporting of treated breast carcinomas and provides recommendations and clarifications for pathologists and clinicians. It also provides specific recommendations for staging and discusses future directions.

Abstract Purpose: Pheochromocytomas and paragangliomas (PPGL) are genetically heterogeneous tumors of neural crest origin, but the molecular basis of most PPGLs is unknown. Experimental Design: We performed exome or transcriptome sequencing of 43 samples from 41 patients. A validation set of 136 PPGLs was used for amplicon-specific resequencing. In addition, a subset of these tumors was subjected to microarray-based transcription, protein expression, and histone methylation analysis by Western blotting or immunohistochemistry. In vitro analysis of mutants was performed in cell lines. Results: We detected mutations in chromatin-remodeling genes, including histone-methyltransferases, histone-demethylases, and histones in 11 samples from 8 patients (20%). In particular, we characterized a new cancer syndrome involving PPGLs and giant cell tumors of bone (GCT) caused by a postzygotic G34W mutation of the histone 3.3 gene, H3F3A. Furthermore, mutations in kinase genes were detected in samples from 15 patients (37%). Among those, a novel germline kinase domain mutation of MERTK detected in a patient with PPGL and medullary thyroid carcinoma was found to activate signaling downstream of this receptor. Recurrent germline and somatic mutations were also detected in MET, including a familial case and sporadic PPGLs. Importantly, in each of these three genes, mutations were also detected in the validation group. In addition, a somatic oncogenic hotspot FGFR1 mutation was found in a sporadic tumor. Conclusions: This study implicates chromatin-remodeling and kinase variants as frequent genetic events in PPGLs, many of which have no other known germline driver mutation. MERTK, MET, and H3F3A emerge as novel PPGL susceptibility genes. Clin Cancer Res; 22(9); 2301–10. ©2015 AACR.