IgG4 Immunostaining and Its Implications in Orbital Inflammatory Disease

Objective IgG4-related disease is an emerging clinical entity which frequently involves tissue within the orbit. In order to appreciate the implications of IgG4 immunostaining, we analyzed gene expression and the prevalence of IgG4- immunostaining among subjects with orbital inflammatory diseases. Methods We organized an international consortium to collect orbital biopsies from 108 subjects including 22 with no known orbital disease, 42 with nonspecific orbital inflammatory disease (NSOI), 26 with thyroid eye disease (TED), 12 with sarcoidosis, and 6 with granulomatosis with polyangiitis (GPA). Lacrimal gland and orbital adipose tissue biopsies were immunostained for IgG4 or IgG secreting plasma cells. RNA transcripts were quantified by Affymetrix arrays. Results None of the healthy controls or subjects with TED had substantial IgG4 staining. Among the 63 others, the prevalence of significant IgG4-immunostaining ranged from 11 to 39% depending on the definition for significant. IgG4 staining was detectable in the majority of tissues from subjects with GPA and less commonly in tissue from subjects with sarcoidosis or NSOI. The detection of IgG4+ cells correlated with inflammation in the lacrimal gland based on histology. IgG4 staining tissue expressed an increase in transcripts associated with inflammation, especially B cell-related genes. Functional annotation analysis confirmed this. Conclusion IgG4+ plasma cells are common in orbital tissue from patients with sarcoidosis, GPA, or NSOI. Even using the low threshold of 10 IgG4+ cells/high powered field, IgG4 staining correlates with increased inflammation in the lacrimal gland based on histology and gene expression

HER2 Testing and Clinical Decision Making in Gastroesophageal Adenocarcinoma

CONTEXT: ERBB2 (erb-b2 receptor tyrosine kinase 2 or HER2) is currently the only biomarker established for selection of a specific therapy for patients with advanced gastroesophageal adenocarcinoma (GEA). However, there are no comprehensive guidelines for the assessment of HER2 in patients with GEA. OBJECTIVES: To establish an evidence-based guideline for HER2 testing in patients with GEA, to formalize the algorithms for methods to improve the accuracy of HER2 testing while addressing which patients and tumor specimens are appropriate, and to provide guidance on clinical decision making. DESIGN: The College of American Pathologists, American Society for Clinical Pathology, and American Society of Clinical Oncology convened an expert panel to conduct a systematic review of the literature to develop an evidence-based guideline with recommendations for optimal HER2 testing in patients with GEA. RESULTS: The panel is proposing 11 recommendations with strong agreement from the open-comment participants. RECOMMENDATIONS: The panel recommends that tumor specimen(s) from all patients with advanced GEA, who are candidates for HER2-targeted therapy, should be assessed for HER2 status before the initiation of HER2-targeted therapy. Clinicians should offer combination chemotherapy and a HER2-targeted agent as initial therapy for all patients with HER2-positive advanced GEA. For pathologists, guidance is provided for morphologic selection of neoplastic tissue, testing algorithms, scoring methods, interpretation and reporting of results, and laboratory quality assurance. CONCLUSIONS: This guideline provides specific recommendations for assessment of HER2 in patients with advanced GEA while addressing pertinent technical issues and clinical implications of the results

DCE-MRI Texture Features for Early Prediction of Breast Cancer Therapy Response

This study investigates the effectiveness of hundreds of texture features extracted from voxel-based dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps for early prediction of breast cancer response to neoadjuvant chemotherapy (NAC). In total, 38 patients with breast cancer underwent DCE-MRI before (baseline) and after the first of the 6–8 NAC cycles. Quantitative pharmacokinetic (PK) parameters and semiquantitative metrics were estimated from DCE-MRI time-course data. The residual cancer burden (RCB) index value was computed based on pathological analysis of surgical specimens after NAC completion. In total, 1043 texture features were extracted from each of the 13 parametric maps of quantitative PK or semiquantitative metric, and their capabilities for early prediction of RCB were examined by correlating feature changes between the 2 MRI studies with RCB. There were 1069 pairs of feature–map combinations that showed effectiveness for response prediction with 4 correlation coefficients >0.7. The 3-dimensional gray-level cooccurrence matrix was the most effective feature extraction method for therapy response prediction, and, in general, the statistical features describing texture heterogeneity were the most effective features. Quantitative PK parameters, particularly those estimated with the shutter-speed model, were more likely to generate effective features for prediction response compared with the semiquantitative metrics. The best feature–map pair could predict pathologic complete response with 100% sensitivity and 100% specificity using our cohort. In conclusion, breast tumor heterogeneity in microvasculature as measured by texture features of voxel-based DCE-MRI parametric maps could be a useful biomarker for early prediction of NAC response

Early Prediction and Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy Using Quantitative DCE-MRI

The purpose is to compare quantitative dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) metrics with imaging tumor size for early prediction of breast cancer response to neoadjuvant chemotherapy (NACT) and evaluation of residual cancer burden (RCB). Twenty-eight patients with 29 primary breast tumors underwent DCE-MRI exams before, after one cycle of, at midpoint of, and after NACT. MRI tumor size in the longest diameter (LD) was measured according to the RECIST (Response Evaluation Criteria In Solid Tumors) guidelines. Pharmacokinetic analyses of DCE-MRI data were performed with the standard Tofts and Shutter-Speed models (TM and SSM). After one NACT cycle the percent changes of DCE-MRI parameters Ktrans (contrast agent plasma/interstitium transfer rate constant), ve (extravascular and extracellular volume fraction), kep (intravasation rate constant), and SSM-unique τi (mean intracellular water lifetime) are good to excellent early predictors of pathologic complete response (pCR) vs. non-pCR, with univariate logistic regression C statistics value in the range of 0.804 to 0.967. ve values after one cycle and at NACT midpoint are also good predictors of response, with C ranging 0.845 to 0.897. However, RECIST LD changes are poor predictors with C = 0.609 and 0.673, respectively. Post-NACT Ktrans, τi, and RECIST LD show statistically significant (P < .05) correlations with RCB. The performances of TM and SSM analyses for early prediction of response and RCB evaluation are comparable. In conclusion, quantitative DCE-MRI parameters are superior to imaging tumor size for early prediction of therapy response. Both TM and SSM analyses are effective for therapy response evaluation. However, the τi parameter derived only with SSM analysis allows the unique opportunity to potentially quantify therapy-induced changes in tumor energetic metabolism

Prostate cancer with a pseudocapsule at MR imaging: a marker of high grade and stage disease?

Clinicopathological correlates of prostate cancer associated with a pseudocapsule at T2-weighted magnetic resonance (MR) imaging are presented in a retrospective series of 15 patients. Of 15 tumors, 14 involved the peripheral zone. Extracapsular extension was seen in 14 cases. Tumor Gleason score was 8 or above in 12 of 15 cases, and ductal type adenocarcinoma was identified in 4 cases. Step section histopathological correlation (n=5) demonstrated that the pseudocapsule corresponded with dense compressive or reactive peritumoral fibrosis. A pseudocapsule around prostate cancer at T2-weighted MR imaging is a rare finding that appears to be associated with high grade and stage disease

Novel mutations in neuroendocrine carcinoma of the breast: possible therapeutic targets

Abstract: Primary neuroendocrine carcinoma of the breast is a rare variant, accounting for only 2% to 5% of diagnosed breast cancers, and may have relatively aggressive behavior. Mutational profiling of invasive ductal breast cancers has yielded potential targets for directed cancer therapy, yet most studies have not included neuroendocrine carcinomas. In a tissue microarray screen, we found a 2.4% prevalence (9/372) of neuroendocrine breast carcinoma, including several with lobular morphology. We then screened primary or metastatic neuroendocrine breast carcinomas (excluding papillary and mucinous) for mutations in common cancer genes using polymerase chain reaction-mass spectroscopy (643 hotspot mutations across 53 genes), or semiconductor-based next-generation sequencing analysis (37 genes). Mutations were identified in 5 of 15 tumors, including 3 with PIK3CA exon 9 E542K mutations, 2 of which also harbored point mutations in FGFR family members (FGFR1 P126S, FGFR4 V550M). Single mutations were found in each of KDR (A1065T) and HRAS (G12A). PIK3CA mutations are common in other types of breast carcinoma. However, FGFR and RAS family mutations are exceedingly rare in the breast cancer literature. Likewise, activating mutations in the receptor tyrosine kinase KDR (VEGFR2) have been reported in angiosarcomas and non-small cell lung cancers; the KDR A1065T mutation is reported to be sensitive to VEGFR kinase inhibitors, and fibroblast growth factor receptor inhibitors are in trials. Our findings demonstrate the utility of broad-based genotyping in the study of rare tumors such as neuroendocrine breast cancer