Primary central nervous system lymphoma: Comprehension of cell-of-origin subtypes.

Primary central nervous system diffuse large B-cell lymphoma (PCNS-DLBCL) is an uncommon extranodal lymphoma that accounts for more than 95% of all the CNS lymphomas. Unlike its systemic/nodal counterpart, which is currently subtyped into cell-of origin (COO) subtypes, its feasibility and utility are largely debatable in PCNS-DLBCL. Objectives: To classify PCNS-DLBCL into COO-subtypes based on immunohistochemical algorithms by Hans and Choi and evaluate concordance between the two. A further aim is to investigate the clinicoradiological and histomorphological parameters of the subtypes thus obtained. Materials and Methods: As many as 143 cases of primary CNS lymphoma were evaluated by immunohistochemistry for CD10, BCL6, MUM1, GCET, and FOXP1 and based on which the said 143 cases were further classified into COO subtypes using Hans and Choi algorithms. Results: Mean age was 53.8 years with marginal male preponderance and predominantly centroblastic morphology (75.5%). CD 10 was positive in 8.9% of the cases, BCL6 in 58.6%, MUM1 in 89.9%, GCET in 32.9%, and FOXP1 in 79.5%. As much as 84.9% cases were of non-germinal center B-cell (GCB) subtype and 15.1% cases were of GCB subtype as determined based on Hans algorithm. Furthermore, 90.7% cases were of activated B-cell (ABC) subtype and 9.3% cases were of GCB subtype according to Choi algorithm. A 91.8% concordance was observed between Hans and Choi algorithms. Among the 6 discordant cases, 5 cases were subtyped as GCB by Hans and ABC by Choi and 1 case as ABC by Hans and GCB by Choi. Conclusion: Most of PCNS-DLBCLs are of non-GCB/ABC COO subtype, but inconsistences abound in the utility of IHC algorithms in PCNS-DLBCL COO subtypes.

Cognitive and negative symptoms in schizophrenia with L-Carnosine adjuvant therapy - A randomized double-blind placebo-controlled study.

The antioxidant L-Carnosine is reported to improve negative and cognitive symptoms in Schizophrenia. A randomized double-blind placebo-controlled study was planned to study the effectiveness of adjuvant L-Carnosine therapy in patients with Schizophrenia. 100 eligible patients with predominant negative symptoms as measured by scale for assessment of negative symptoms (SANS total score ≥ 60) and Schizophrenia diagnosis (International Classification of Disorder-Tenth Edition, ICD-10) were recruited. They were randomly allocated to receive a fixed dose of either 400 mg L-Carnosine or identical placebo for 3 months and increased to 800 mg from 13th week till completion of study. Primary outcome measures assessed changes in SANS scores with L-Carnosine at 24 weeks compared to baseline, 4 and 12 weeks. Secondary outcome measures were done to assess the improvement in cognitive symptoms (executive function, attention, and memory) at 24 weeks using subtests of NIMHANS (National Institute for Mental Health and Neurosciences) cognitive battery. Side effects were assessed using adverse events reporting form. The attention scores (p = .023) showed significant differences in patients receiving 800 mg of L-Carnosine at the end of the study. There were no significant differences in negative symptoms in the two arms at study completion. L-Carnosine dosing of 800 mg may be a promising agent to enhance executive functions in Schizophrenia.

Culture-Independent Raman Spectroscopic Identification of Bacterial Pathogens from Clinical Samples Using Deep Transfer Learning.

The rapid identification of bacterial pathogens in clinical samples like blood, urine, pus, and sputum is the need of the hour. Conventional bacterial identification methods like culturing and nucleic acid-based amplification have limitations like poor sensitivity, high cost, slow turnaround time, etc. Raman spectroscopy, a label-free and noninvasive technique, has overcome these drawbacks by providing rapid biochemical signatures from a single bacterium. Raman spectroscopy combined with chemometric methods has been used effectively to identify pathogens. However, a robust approach is needed to utilize Raman features for accurate classification while dealing with complex data sets such as spectra obtained from clinical isolates, showing high sample-to-sample heterogeneity. In this study, we have used Raman spectroscopy-based identification of pathogens from clinical isolates using a deep transfer learning approach at the single-cell level resolution. We have used the data-augmentation method to increase the volume of spectra needed for deep-learning analysis. Our ResNet model could specifically extract the spectral features of eight different pathogenic bacterial species with a 99.99% classification accuracy. The robustness of our model was validated on a set of blinded data sets, a mix of cultured and noncultured bacterial isolates of various origins and types. Our proposed ResNet model efficiently identified the pathogens from the blinded data set with high accuracy, providing a robust and rapid bacterial identification platform for clinical microbiology.

Paediatric type diffuse high grade gliomas in the WHO CNS5 classification: What the pathologist needs to know?

Pediatric-type of diffuse high-grade gliomas (HGG) are classified as a distinct group in the current fifth edition of WHO classification. This group of high-grade tumors is no more called as glioblastoma (GBM), which has been reserved for adult isocitrate dehydrogenase (IDH)-wild type HGG. These tumors are uncommon as compared to embryonal tumors and low-grade gliomas (LGG). Pediatric-type of diffuse HGG biologically differs from their adult counterparts in that they are therapeutically less sensitive to alkylating chemotherapies. They comprise a heterogeneous group of molecularly defined tumors - predominantly histone gene altered, less common receptor tyrosine kinase (RTK)-mediated, and syndrome-associated. This review provides an overview of these uncommon tumors and discusses the diagnostic approach of this heterogeneous group of tumors.

Standardized evidence-based approach for assessment of oncogenic and clinical significance of NTRK fusions.

Gene fusions involving the neurotrophic receptor tyrosine kinase genes NTRK1, NTRK2, and NTRK3, are well established oncogenic drivers in a broad range of pediatric and adult tumors. These fusions are also important actionable markers, predicting often dramatic response to FDA approved kinase inhibitors. Accurate interpretation of the clinical significance of NTRK fusions is a high priority for diagnostic laboratories, but remains challenging and time consuming given the rapid pace of new data accumulation, the diversity of fusion partners and tumor types, and heterogeneous and incomplete information in variant databases and knowledgebases. The ClinGen NTRK Fusions Somatic Cancer Variant Curation Expert Panel (SC-VCEP) was formed to systematically address these challenges and create an expert-curated resource to support clinicians, researchers, patients and their families in making accurate interpretations and informed treatment decisions for NTRK fusion-driven tumors. We describe a system for NTRK fusion interpretation (including compilation of key elements and annotations) developed by the NTRK fusions SC-VCEP. We illustrate this stepwise process on examples of LMNA::NTRK1 and KANK1::NTRK2 fusions. Finally, we provide detailed analysis of current representation of NTRK fusions in public fusion databases and the CIViC knowledgebase, performed by the NTRK fusions SC-VCEP to determine existing gaps and prioritize future curation activities.

Standards for the classification of pathogenicity of somatic variants in cancer (oncogenicity): Joint recommendations of Clinical Genome Resource (ClinGen), Cancer Genomics Consortium (CGC), and Variant Interpretation for Cancer Consortium (VICC).

PURPOSE: Several professional societies have published guidelines for the clinical interpretation of somatic variants, which specifically address diagnostic, prognostic, and therapeutic implications. Although these guidelines for the clinical interpretation of variants include data types that may be used to determine the oncogenicity of a variant (eg, population frequency, functional, and in silico data or somatic frequency), they do not provide a direct, systematic, and comprehensive set of standards and rules to classify the oncogenicity of a somatic variant. This insufficient guidance leads to inconsistent classification of rare somatic variants in cancer, generates variability in their clinical interpretation, and, importantly, affects patient care. Therefore, it is essential to address this unmet need. METHODS: Clinical Genome Resource (ClinGen) Somatic Cancer Clinical Domain Working Group and ClinGen Germline/Somatic Variant Subcommittee, the Cancer Genomics Consortium, and the Variant Interpretation for Cancer Consortium used a consensus approach to develop a standard operating procedure (SOP) for the classification of oncogenicity of somatic variants. RESULTS: This comprehensive SOP has been developed to improve consistency in somatic variant classification and has been validated on 94 somatic variants in 10 common cancer-related genes. CONCLUSION: The comprehensive SOP is now available for classification of oncogenicity of somatic variants.

Comparison of analgesic efficacy of shoulder block versus interscalene block for postoperative analgesia in arthroscopic shoulder surgeries: A randomised trial.

BACKGROUND AND AIMS: Arthroscopic orthopaedic surgery may lead to significant postoperative pain. Interscalene block (ISB) is associated with undesirable effects like phrenic nerve palsy. Shoulder block (ShB) is a relatively recent diaphragm sparing alternative for analgesia in these cases. METHODS: This prospective randomised trial was conducted in 70 adult patients posted for arthroscopic Bankart repair surgery. Patients were randomly assigned into two groups: interscalene block [Group ISB (n = 35): 0.5% bupivacaine 10 ml] or shoulder block [Group ShB (n = 35): 0.5% bupivacaine (suprascapular block 10 ml and axillary block 10 ml)] using ultrasound and nerve stimulator. The primary aim of our study was to compare the ISB with ShB for visual analogue score (VAS) in recovery area (zero hour). Time for block performance, VAS, time to first rescue analgesia, total analgesic requirement, patient satisfaction and complications were recorded. RESULTS: VAS was significantly higher in ShB group at 2 and 4 h (P = 0.001 and 0.000) while it was significantly higher in ISB group at 12 h (P = 0.013). The time to first analgesic request was significantly prolonged in ISB group as compared to ShB group (8.22 h vs. 4.69 h; P = 0.002) but total analgesic requirement and patient satisfaction at 24 h were similar. Complications like dyspnoea, ptosis and motor weakness were seen only with ISB group. CONCLUSION: Both ShB and ISB blocks have similar efficacy in terms of postoperative pain scores, cumulative analgesic requirements and patient satisfaction. However, considering the various undesirable effects associated with ISB, like phrenic nerve blockade, prolonged upper limb weakness and the occurrence of rebound pain, shoulder block may be preferred for arthroscopic shoulder surgeries.

Comparison of Analgesic Efficacy of Ultrasound-Guided Interscalene Block Versus Continuous Subacromial Infusion for Postoperative Analgesia Following Arthroscopic Rotator Cuff Repair Surgeries: A Randomized Trial.

BACKGROUND: Arthroscopic rotator cuff repair surgery may lead to significant postoperative pain. Interscalene block (ISB) is an effective analgesic technique in these surgeries but there is a risk of the phrenic blockade. Subacromial local anesthetic infiltration is a phrenic sparing alternative technique for postoperative analgesia. The primary aim of our study was to compare the ISB with a continuous subacromial infusion (SAC) with regard to postoperative analgesia. METHODS:  This prospective randomized, interventional parallel arm trial was conducted in 60 ASA grade I and II, adult patients (30 patients in each group) posted for arthroscopic rotator cuff repair surgery. Patients were randomly assigned to receive either ultrasound-guided ISB (Group ISB: 15 ml of 0.75% ropivacaine) or continuous SAC (Group SAC: 15 ml 0.75% ropivacaine as a subacromial injection by ultrasound guidance and infusion of 3 ml/hour of 0.5% ropivacaine through the catheter placed subacromial by the surgeon). Intraoperative hemodynamic parameters, visual analog scores (VAS), and rescue analgesic requirements for 24 hours, patient satisfaction, and complications were recorded. RESULTS: Rescue analgesic requirement was significantly higher in SAC at zero hours (P=0.000), while it was significantly higher in ISB at 12 hours (P=0.02). The VAS scores were comparable at all time points and patient satisfaction at 24 hours was similar. None of the patients had rated satisfaction related to pain relief as poor in any group. Complications like ptosis and motor weakness were seen only with ISB. CONCLUSION: Both the techniques provided effective analgesia and comparable patient satisfaction with lesser incidence of complications in the SAC group. ISB provided more effective immediate postoperative pain relief while SAC was more effective in delayed analgesia for arthroscopic rotator cuff repair surgeries. SAC can be considered a reasonably safe alternative to ISB in patients with contraindications to the latter.

Collaborative, Multidisciplinary Evaluation of Cancer Variants Through Virtual Molecular Tumor Boards Informs Local Clinical Practices.

PURPOSE: The cancer research community is constantly evolving to better understand tumor biology, disease etiology, risk stratification, and pathways to novel treatments. Yet the clinical cancer genomics field has been hindered by redundant efforts to meaningfully collect and interpret disparate data types from multiple high-throughput modalities and integrate into clinical care processes. Bespoke data models, knowledgebases, and one-off customized resources for data analysis often lack adequate governance and quality control needed for these resources to be clinical grade. Many informatics efforts focused on genomic interpretation resources for neoplasms are underway to support data collection, deposition, curation, harmonization, integration, and analytics to support case review and treatment planning. METHODS: In this review, we evaluate and summarize the landscape of available tools, resources, and evidence used in the evaluation of somatic and germline tumor variants within the context of molecular tumor boards. RESULTS: Molecular tumor boards (MTBs) are collaborative efforts of multidisciplinary cancer experts equipped with genomic interpretation resources to aid in the delivery of accurate and timely clinical interpretations of complex genomic results for each patient, within an institution or hospital network. Virtual MTBs (VMTBs) provide an online forum for collaborative governance, provenance, and information sharing between experts outside a given hospital network with the potential to enhance MTB discussions. Knowledge sharing in VMTBs and communication with guideline-developing organizations can lead to progress evidenced by data harmonization across resources, crowd-sourced and expert-curated genomic assertions, and a more informed and explainable usage of artificial intelligence. CONCLUSION: Advances in cancer genomics interpretation aid in better patient and disease classification, more streamlined identification of relevant literature, and a more thorough review of available treatments and predicted patient outcomes.

Evidence-Based Network Approach to Recommending Targeted Cancer Therapies.

PURPOSE: In this work, we introduce CDGnet (Cancer-Drug-Gene Network), an evidence-based network approach for recommending targeted cancer therapies. CDGnet represents a user-friendly informatics tool that expands the range of targeted therapy options for patients with cancer who undergo molecular profiling by including the biologic context via pathway information. METHODS: CDGnet considers biologic pathway information specifically by looking at targets or biomarkers downstream of oncogenes and is personalized for individual patients via user-inputted molecular alterations and cancer type. It integrates a number of different sources of knowledge: patient-specific inputs (molecular alterations and cancer type), US Food and Drug Administration-approved therapies and biomarkers (curated from DailyMed), pathways for specific cancer types (from Kyoto Encyclopedia of Genes and Genomes [KEGG]), gene-drug connections (from DrugBank), and oncogene information (from KEGG). We consider 4 different evidence-based categories for therapy recommendations. Our tool is delivered via an R/Shiny Web application. For the 2 categories that use pathway information, we include an interactive Sankey visualization built on top of d3.js that also provides links to PubChem. RESULTS: We present a scenario for a patient who has estrogen receptor (ER)-positive breast cancer with FGFR1 amplification. Although many therapies exist for patients with ER-positive breast cancer, FGFR1 amplifications may confer resistance to such treatments. CDGnet provides therapy recommendations, including PIK3CA, MAPK, and RAF inhibitors, by considering targets or biomarkers downstream of FGFR1. CONCLUSION: CDGnet provides results in a number of easily accessible and usable forms, separating targeted cancer therapies into categories in an evidence-based manner that incorporates biologic pathway information.

Standard operating procedure for curation and clinical interpretation of variants in cancer.

Manually curated variant knowledgebases and their associated knowledge models are serving an increasingly important role in distributing and interpreting variants in cancer. These knowledgebases vary in their level of public accessibility, and the complexity of the models used to capture clinical knowledge. CIViC (Clinical Interpretation of Variants in Cancer - www.civicdb.org) is a fully open, free-to-use cancer variant interpretation knowledgebase that incorporates highly detailed curation of evidence obtained from peer-reviewed publications and meeting abstracts, and currently holds over 6300 Evidence Items for over 2300 variants derived from over 400 genes. CIViC has seen increased adoption by, and also undertaken collaboration with, a wide range of users and organizations involved in research. To enhance CIViC's clinical value, regular submission to the ClinVar database and pursuit of other regulatory approvals is necessary. For this reason, a formal peer reviewed curation guideline and discussion of the underlying principles of curation is needed. We present here the CIViC knowledge model, standard operating procedures (SOP) for variant curation, and detailed examples to support community-driven curation of cancer variants.

A case for expert curation: an overview of cancer curation in the Clinical Genome Resource (ClinGen).

We describe the Clinical Genome Resource (ClinGen) cancer-related curation activities and the importance of curation to the evolving state of variant interpretation in a clinical context for both pediatric and adult cancer patients. We highlight specific examples from the CDH1 and PTEN Variant Curation Expert Panels (VCEPs) of the FDA-recognized process by which ClinGen VCEPs specify the American College of Medical Genetics and Genomics/Association of Molecular Pathology evidence code to develop variant classifications. We also review gene curations performed within the Hereditary Cancer Clinical Domain. We describe the parallel efforts for curation of somatic cancer variants from the Somatic Cancer Working Group. The ClinGen Germline/Somatic Committee is working to improve incorporation of both hereditary and somatic variant data to aid clinical interpretation. These ClinGen efforts rely on broad data sharing and detailed phenotypic and molecular information from published case studies to provide expert-curated variant interpretation to the cancer community.

Dynamic Regulation of Caveolin-1 Phosphorylation and Caveolae Formation by Mammalian Target of Rapamycin Complex 2 in Bladder Cancer Cells.

The mammalian target of rapamycin (mTOR) and associated phosphatidylinositol 3-kinase/AKT/mTOR signaling pathway is commonly up-regulated in cancer, including bladder cancer. mTOR complex 2 (mTORC2) is a major regulator of bladder cancer cell migration and invasion, but the mechanisms by which mTORC2 regulates these processes are unclear. A discovery mass spectrometry and reverse-phase protein array-based proteomics dual approach was used to identify novel mTORC2 phosphoprotein targets in actively invading cancer cells. mTORC2 targets included focal adhesion kinase, proto-oncogene tyrosine-protein kinase Src, and caveolin-1 (Cav-1), among others. Functional testing shows that mTORC2 regulates Cav-1 localization and dynamic phosphorylation of Cav-1 on Y14. Regulation of Cav-1 activity by mTORC2 also alters the abundance of caveolae, which are specialized lipid raft invaginations of the plasma membrane associated with cell signaling and membrane compartmentalization. Our results demonstrate a unique role for mTORC2-mediated regulation of caveolae formation in actively migrating cancer cells.

A virtual molecular tumor board to improve efficiency and scalability of delivering precision oncology to physicians and their patients.

OBJECTIVES: Scalable informatics solutions that provide molecularly tailored treatment recommendations to clinicians are needed to streamline precision oncology in care settings. MATERIALS AND METHODS: We developed a cloud-based virtual molecular tumor board (VMTB) platform that included a knowledgebase, scoring model, rules engine, an asynchronous virtual chat room and a reporting tool that generated a treatment plan for each of the 1725 patients based on their molecular profile, previous treatment history, structured trial eligibility criteria, clinically relevant cancer gene-variant assertions, biomarker-treatment associations, and current treatment guidelines. The VMTB systematically allows clinician users to combine expert-curated data and structured data from clinical charts along with molecular testing data to develop consensus on treatments, especially those that require off-label and clinical trial considerations. RESULTS: The VMTB was used as part of the cancer care process for a focused subset of 1725 patients referred by advocacy organizations wherein resultant personalized reports were successfully delivered to treating oncologists. Median turnaround time from data receipt to report delivery decreased from 14 days to 4 days over 4 years while the volume of cases increased nearly 2-fold each year. Using a novel scoring model for ranking therapy options, oncologists chose to implement the VMTB-derived therapies over others, except when pursuing immunotherapy options without molecular support. DISCUSSION: VMTBs will play an increasingly critical role in precision oncology as the compendium of biomarkers and associated therapy options available to a patient continues to expand. CONCLUSION: Further development of such clinical augmentation tools that systematically combine patient-derived molecular data, real-world evidence from electronic health records and expert curated knowledgebases on biomarkers with computational tools for ranking best treatments can support care pathways at point of care.

iTextMine: integrated text-mining system for large-scale knowledge extraction from the literature.

Numerous efforts have been made for developing text-mining tools to extract information from biomedical text automatically. They have assisted in many biological tasks, such as database curation and hypothesis generation. Text-mining tools are usually different from each other in terms of programming language, system dependency and input/output format. There are few previous works that concern the integration of different text-mining tools and their results from large-scale text processing. In this paper, we describe the iTextMine system with an automated workflow to run multiple text-mining tools on large-scale text for knowledge extraction. We employ parallel processing with dockerized text-mining tools with a standardized JSON output format and implement a text alignment algorithm to solve the text discrepancy for result integration. iTextMine presently integrates four relation extraction tools, which have been used to process all the Medline abstracts and PMC open access full-length articles. The website allows users to browse the text evidence and view integrated results for knowledge discovery through a network view. We demonstrate the utilities of iTextMine with two use cases involving the gene PTEN and breast cancer and the gene SATB1.

Adapting crowdsourced clinical cancer curation in CIViC to the ClinGen minimum variant level data community-driven standards.

Harmonization of cancer variant representation, efficient communication, and free distribution of clinical variant-associated knowledge are central problems that arise with increased usage of clinical next-generation sequencing. The Clinical Genome Resource (ClinGen) Somatic Working Group (WG) developed a minimal variant level data (MVLD) representation of cancer variants, and has an ongoing collaboration with Clinical Interpretations of Variants in Cancer (CIViC), an open-source platform supporting crowdsourced and expert-moderated cancer variant curation. Harmonization between MVLD and CIViC variant formats was assessed by formal field-by-field analysis. Adjustments to the CIViC format were made to harmonize with MVLD and support ClinGen Somatic WG curation activities, including four new features in CIViC: (1) introduction of an assertions feature for clinical variant assessment following the Association of Molecular Pathologists (AMP) guidelines, (2) group-level curation tracking for organizations, enabling member transparency, and curation effort summaries, (3) introduction of ClinGen Allele Registry IDs to CIViC, and (4) mapping of CIViC assertions into ClinVar submission with automated submissions. A generalizable workflow utilizing MVLD and new CIViC features is outlined for use by ClinGen Somatic WG task teams for curation and submission to ClinVar, and provides a model for promoting harmonization of cancer variant representation and efficient distribution of this information.

Standardizing And Democratizing Access To Cancer Molecular Diagnostic Test Data From Patients To Drive Translational Research.

In the last 3-5 years, there has been a rapid increase in clinical use of next generation sequencing (NGS) based cancer molecular diagnostic (MolDx) testing to develop better treatment plans with targeted therapies. To truly achieve precision oncology, it is critical to catalog cancer sequence variants from MolDx testing for their clinical relevance along with treatment information and patient outcomes, and to do so in a way that supports large-scale data aggregation and new hypothesis generation. Through the NIH-funded Clinical Genome Resource (ClinGen), in collaboration with NLM's ClinVar database and >50 academic and industry based cancer research organizations, a Minimal Variant Level Data (MVLD) framework to standardize reporting and interpretation of drug associated alterations was developed. Methodological and technology development to standardize and map MolDx data to the MVLD standard are presented here. Also described is a novel community engagement effort through disease-focused taskforces to provide usecases for technology development.