Biphenotypic Sinonasal Sarcoma with a Novel PAX7::PPARGC1 Fusion: Expanding the Spectrum of Gene Fusions Beyond the PAX3 Gene.

Biphenotypic sinonasal sarcoma (BSNS) is a rare low-grade malignancy occurring in the sinonasal tract that is characterized by dual neural and myogenic differentiation. Rearrangements involving the PAX3 gene, usually with MAML3, are a hallmark of this tumor type and their identification are useful for diagnosis. Rarely, a MAML3 rearrangement without associated PAX3 rearrangement has been described. Other gene fusions have not been previously reported. Herein, we report a 22 year-old woman with a BSNS harboring a novel gene fusion involving the PAX7 gene (specifically PAX7::PPARGC1A), which is a paralogue of PAX3. The histologic features of the tumor were typical with two exceptions: a lack of entrapment of surface respiratory mucosa and no hemangiopericytoma-like vasculature. Immunophenotypically, the tumor was notably negative for smooth muscle actin, which is usually positive in BSNS. However, the classic S100 protein-positive, SOX10-negative staining pattern was present. In addition, the tumor was positive for desmin and MyoD1 but negative for myogenin, a pattern that is common among BSNS with variant fusions. Awareness of the possibility of PAX7 gene fusions in BSNS is important as it may aid in the diagnosis of PAX3 fusion negative tumors.

Metastasis of papillary thyroid cancer to the larynx and pharynx: unusual case report.

Papillary thyroid cancer favors lymphatic spread both within the thyroid gland and to the cervical lymph nodes. Hematogenous spread rarely occurs in the lung, bones and brain. We report a case where metastatic nodules from papillary thyroid cancer were seen in the right aryepiglottic fold (supraglottis) and lateral wall of hypopharynx, an extremely rare event.

Bilateral peripheral T-cell lymphoma of breast: a case report.

Primary non-Hodgkin's lymphoma (NHL) of the breast is uncommon and the bilateral involvement is extremely rare. Usually, primary breast lymphoma is of B-cell phenotype, most common subtype being the diffuse large B-cell lymphoma. Preoperative differentiation of lymphoma from carcinoma is essential and limited material can pose diagnostic problem unless the index of suspicion is high. Twenty six year old pregnant lady, presented with bilateral breast lumps with a clinical impression of carcinoma. Fine needle aspiration cytology (FNAC) followed by biopsy of the breast mass was performed and a diagnosis of NHL, peripheral T-cell type (not otherwise specified) was made. She received 8 cycles of CHOP chemotherapy and showed dramatic improvement with regression of bilateral breast masses. She had an uneventful normal delivery and both the mother and the child are doing well. Since FNAC is a primary diagnostic tool for all breast lesions, a differential of lymphoma should always be kept in mind in all poorly differentiated malignant tumours. Such cases need biopsy confirmation and immunophenotyping for further sub-typing.

Analysis of deferrals on static telepathology consultation service.

The objective of this study is to analyze the deferrals in static telepathology consultation service. A store and forward approach is used to transmit cases from two remotely located rural centers to Tata Memorial Hospital. A total of 346 tele-surgical pathology cases were accessioned for second opinion and were reported from January 2002 to August 2005. The glass slides and paraffin blocks were reviewed at a later date and the telepathology diagnosis was compared with the final diagnosis rendered on light microscopy. Of all 251 teleconsults referred from one of the referring centers, a telepathology diagnosis was rendered in 205 cases and 46 cases were deferred. The reasons for deferral were as follows: the requirement for ancillary studies (40 cases), clinical details (5 cases) and poor quality sections and images (1 case). In all these deferred cases, a probable diagnosis was rendered by the telepathologist and was compared with the final diagnosis after paraffin block evaluation. In 47% of the cases, the "probable" diagnosis on telepathology matched the final diagnosis.

Quantitative imaging for development of companion diagnostics to drugs targeting HGF/MET.

The limited clinical success of anti-HGF/MET drugs can be attributed to the lack of predictive biomarkers that adequately select patients for treatment. We demonstrate here that quantitative digital imaging of formalin fixed paraffin embedded tissues stained by immunohistochemistry can be used to measure signals from weakly staining antibodies and provides new opportunities to develop assays for detection of MET receptor activity. To establish a biomarker panel of MET activation, we employed seven antibodies measuring protein expression in the HGF/MET pathway in 20 cases and up to 80 cores from 18 human cancer types. The antibodies bind to epitopes in the extra (EC)- and intracellular (IC) domains of MET (MET4EC, SP44_METIC, D1C2_METIC), to MET-pY1234/pY1235, a marker of MET kinase activation, as well as to HGF, pSFK or pMAPK. Expression of HGF was determined in tumour cells (T_HGF) as well as in stroma surrounding cancer (St_HGF). Remarkably, MET4EC correlated more strongly with pMET (r = 0.47) than SP44_METIC (r = 0.21) or D1C2_METIC (r = 0.08) across 18 cancer types. In addition, correlation coefficients of pMET and T_HGF (r = 0.38) and pMET and pSFK (r = 0.56) were high. Prediction models of MET activation reveal cancer-type specific differences in performance of MET4EC, SP44_METIC and anti-HGF antibodies. Thus, we conclude that assays to predict the response to HGF/MET inhibitors require a cancer-type specific antibody selection and should be developed in those cancer types in which they are employed clinically.

Machine learning approaches to analyze histological images of tissues from radical prostatectomies.

Computerized evaluation of histological preparations of prostate tissues involves identification of tissue components such as stroma (ST), benign/normal epithelium (BN) and prostate cancer (PCa). Image classification approaches have been developed to identify and classify glandular regions in digital images of prostate tissues; however their success has been limited by difficulties in cellular segmentation and tissue heterogeneity. We hypothesized that utilizing image pixels to generate intensity histograms of hematoxylin (H) and eosin (E) stains deconvoluted from H&E images numerically captures the architectural difference between glands and stroma. In addition, we postulated that joint histograms of local binary patterns and local variance (LBPxVAR) can be used as sensitive textural features to differentiate benign/normal tissue from cancer. Here we utilized a machine learning approach comprising of a support vector machine (SVM) followed by a random forest (RF) classifier to digitally stratify prostate tissue into ST, BN and PCa areas. Two pathologists manually annotated 210 images of low- and high-grade tumors from slides that were selected from 20 radical prostatectomies and digitized at high-resolution. The 210 images were split into the training (n=19) and test (n=191) sets. Local intensity histograms of H and E were used to train a SVM classifier to separate ST from epithelium (BN+PCa). The performance of SVM prediction was evaluated by measuring the accuracy of delineating epithelial areas. The Jaccard J=59.5 ± 14.6 and Rand Ri=62.0 ± 7.5 indices reported a significantly better prediction when compared to a reference method (Chen et al., Clinical Proteomics 2013, 10:18) based on the averaged values from the test set. To distinguish BN from PCa we trained a RF classifier with LBPxVAR and local intensity histograms and obtained separate performance values for BN and PCa: JBN=35.2 ± 24.9, OBN=49.6 ± 32, JPCa=49.5 ± 18.5, OPCa=72.7 ± 14.8 and Ri=60.6 ± 7.6 in the test set. Our pixel-based classification does not rely on the detection of lumens, which is prone to errors and has limitations in high-grade cancers and has the potential to aid in clinical studies in which the quantification of tumor content is necessary to prognosticate the course of the disease. The image data set with ground truth annotation is available for public use to stimulate further research in this area.

Interobserver variation is a significant limitation in the diagnosis of Burkitt lymphoma.

CONTEXT: The pathology of classic Burkitt lymphoma (BL) remains a challenge despite being a well-defined entity, in view of the significant overlap with atypical BL and B-cell lymphoma intermediate between DLBL (diffuse large B cell lymphoma) and BL. They are difficult to be segregated in resource-limited setups which lack molecular testing facilities. This is further affected by interobserver variability and experience of the reporting pathologist. AIMS: The aim of our study was to quantitate variability among a group of pathologists with an interest in lymphomas (albeit with variable levels of experience) and quantitate the benefit of joint discussions as a tool to increase accuracy and reduce interobserver variability of pathologists, in the diagnosis of BL in a resource-limited setup. MATERIALS AND METHODS: A set of 25 non-Hodgkin lymphoma cases in which a diagnosis of BL was entertained were circulated to 14 participating pathologist within the Mumbai lymphoma study group. A proforma recorded the morphologic and immunohistochemical features perceived during the initial independent diagnosis followed by a consensus meeting for discussion on morphology and additional information pertinent to the case. STATISTICAL ANALYSIS AND RESULTS: The concordance was poor for independent diagnosis among all the pathologists with kappa statistics (±SE) of 0.168 (±0.018). Expert lymphoma pathologists had the highest (albeit only fair) concordance (kappa = 0.373 ± 0.071) and general pathologists the lowest concordance (kappa = 0.138 ± 0.035). Concordance for morphological diagnosis was highest among expert lymphoma pathologists (kappa = 0.356 ± 0.127). Revision of diagnoses after consensus meeting was highest for B-cell lymphoma intermediate between DLB and BL. To conclude, interobserver variation is a significant problem in BL in the post WHO 2008 classification era. Experience with a larger number of cases and joint discussion exercises such as the one we conducted are needed as they represent a simple and effective way of improving diagnostic accuracy of pathologists working in a resource-limited setup.