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Malignant peripheral nerve sheath tumors (MPNSTs) are soft tissue sarcomas that frequently harbor genetic alterations in polycomb repressor complex 2 (PRC2) components—SUZ12 and EED. Here, we show that PRC2 loss confers a dedifferentiated early neural-crest phenotype which is exclusive to PRC2-mutant MPNSTs and not a feature of neurofibromas. Neural crest phenotype in PRC2 mutant MPNSTs was validated via cross-species comparative analysis using spontaneous and transgenic MPNST models. Systematic chromatin state profiling of the MPNST cells showed extensive epigenomic reprogramming or chromatin states associated with PRC2 loss and identified gains of active enhancer states/super-enhancers on early neural crest regulators in PRC2-mutant conditions around genomic loci that harbored repressed/poised states in PRC2-WT MPNST cells. Consistently, inverse correlation between H3K27me3 loss and H3K27Ac gain was noted in MPNSTs. Epigenetic editing experiments established functional roles for enhancer gains on DLX5—a key regulator of neural crest phenotype. Consistently, blockade of enhancer activity by bromodomain inhibitors specifically suppressed this neural crest phenotype and tumor burden in PRC2-mutant PDXs. Together, these findings reveal accumulation of dedifferentiated neural crest like state in PRC2-mutant MPNSTs that can be targeted by enhancer blockade.

In the development of a multiplex immunofluorescence (IF) platform and the optimization and validation of new multiplex IF panels using a tyramide signal amplification system, several technical requirements are important for high-quality staining, analysis, and results. The aim of this review is to discuss the basic requirements for performing multiplex IF tyramide signal amplification (TSA) in formalin-fixed, paraffin-embedded cancer tissues to support translational oncology research. Our laboratory has stained approximately 4000 formalin-fixed, paraffin-embedded tumor samples using the multiplex IF TSA system for immune profiling of several labeled biomarkers in a single slide to elucidate cancer biology at a protein level and identify therapeutic targets and biomarkers. By analyzing several proteins in thousands of cells on a single slide, this technique provides a systems-level view of various processes in various tumor tissues. Although this technology shows high flexibility in cancer studies, it presents several challenges when applied to study different histology cancers. Our experience shows that adequate antibody validation, staining optimization, analysis strategies, and data generation are important steps for generating quality results. Tissue management, fixation procedures, storage, and cutting can also affect the results of the assay and must be standardized. Overall, this method is reliable for supporting translational research given a precise, step-by-step approach.

Few standard treatment options are available for patients with metastatic sarcomas. We did this trial to evaluate the efficacy, safety, and changes in the tumour microenvironment for durvalumab, an anti-PD-L1 drug, and tremelimumab, an anti-CTLA-4 drug, across multiple sarcoma subtypes. In this single-centre phase 2 trial, done at The University of Texas MD Anderson Cancer Center (Houston, TX USA), patients aged 18 years or older with advanced or metastatic sarcoma with an Eastern Cooperative Oncology Group performance status of 0 or 1 who had received at least one previous line of systemic therapy were enrolled in disease subtype-specific groups (liposarcoma, leiomyosarcoma, angiosarcoma, undifferentiated pleomorphic sarcoma, synovial sarcoma, osteosarcoma, alveolar soft-part sarcoma, chordoma, and other sarcomas). Patients received 1500 mg intravenous durvalumab and 75 mg intravenous tremelimumab for four cycles, followed by durvalumab alone every 4 weeks for up to 12 months. The primary endpoint was progression-free survival at 12 weeks in the intention-to-treat population (all patients who received at least one dose of treatment). Safety was also analysed in the intention-to-treat population. This trial is registered with ClinicalTrials.gov, NCT02815995, and is completed. Between Aug 17, 2016, and April 9, 2018, 62 patients were enrolled, of whom 57 (92%) received treatment and were included in the intention-to-treat population. With a median follow-up of 37·2 months (IQR 1·8–10·1), progression-free survival at 12 weeks was 49% (95% CI 36–61). 21 grade 3–4 treatment-related adverse events were reported, the most common of which were increased lipase (four [7%] of 57 patients), colitis (three [5%] patients), and pneumonitis (three [5%] patients). Nine (16%) patients had a treatment related serious adverse event. One patient had grade 5 pneumonitis and colitis. The combination of durvalumab and tremelimumab is an active treatment regimen for advanced or metastatic sarcoma and merits evaluation in specific subsets in future trials. AstraZeneca.

Imaging-based spatial transcriptomics (ST) is evolving as a pivotal technology in studying tumor biology and associated microenvironments. However, the strengths of the commercially available ST platforms in studying spatial biology have not been systematically evaluated using rigorously controlled experiments. We use serial 5 μm sections of formalin-fixed, paraffin-embedded surgically resected lung adenocarcinoma and pleural mesothelioma samples in tissue microarrays to compare the performance of the ST platforms (CosMx, MERFISH, and Xenium (uni/multi-modal)) in reference to bulk RNA sequencing, multiplex immunofluorescence, GeoMx, and hematoxylin and eosin staining data. In addition to an objective assessment of automatic cell segmentation and phenotyping, we perform a manual phenotyping evaluation to assess pathologically meaningful comparisons between ST platforms. Here, we show the intricate differences between the ST platforms, reveal the importance of parameters such as probe design in determining the data quality, and suggest reliable workflows for accurate spatial profiling and molecular discovery. Spatial cell distribution within a tissue microenvironment is a rapidly advancing field. Here, authors assess three commercially available single-cell resolution spatial transcriptomics approaches (CosMx, MERFISH, and Xenium) to inform which technology outperforms for immune profiling of solid tumors using patient samples.

Triple-negative inflammatory breast cancer (TN-IBC) is the most aggressive type of breast cancer, yet its defining genomic, molecular, and immunological features remain largely unknown. In this study, we performed the largest and most comprehensive genomic and transcriptomic analyses of prospectively collected TN-IBC patient samples from a phase II clinical trial ( ClinicalTrials.gov, NCT02876107, registered on August 22, 2016 ) and compared them to similarly analyzed stage III TN-non-IBC patient samples ( ClinicalTrials.gov, NCT02276443, registered on October 21, 2014 ). We found that TN-IBC tumors have distinctive genomic, molecular, and immunological characteristics, including a lower tumor mutation load than TN-non-IBC, and an association of immunosuppressive tumor-infiltrating immune components with an unfavorable response to neoadjuvant chemotherapy. To our knowledge, this is the only study in which TN-IBC and TN-non-IBC samples were collected prospectively. Our analysis improves the understanding of the molecular landscape of the most aggressive subtype of breast cancer. Further studies are needed to discover novel prognostic biomarkers and druggable targets for TN-IBC.

Biometrics is progressively becoming vital due to vulnerabilities of traditional security systems leading to frequent security breaches. Biometrics is an automated device that studies human beings’ physiological and behavioral features for their unique classification. Iris-based authentication offers stronger, unique, and contactless identification of the user. Iris liveness detection (ILD) confronts challenges such as spoofing attacks with contact lenses, replayed video, and print attacks, etc. Many researchers focus on ILD to guard the biometric system from attack. Hence, it is vital to study the prevailing research explicitly associated with the ILD to address how developing technologies can offer resolutions to lessen the evolving threats. An exhaustive survey of papers on the biometric ILD was performed by searching the most applicable digital libraries. Papers were filtered based on the predefined inclusion and exclusion criteria. Thematic analysis was performed for scrutinizing the data extracted from the selected papers. The exhaustive review now outlines the different feature extraction techniques, classifiers, datasets and presents their critical evaluation. Importantly, the study also discusses the projects, research works for detecting the iris spoofing attacks. The work then realizes in the discovery of the research gaps and challenges in the field of ILD. Many works were restricted to handcrafted methods of feature extraction, which are confronted with bigger feature sizes. The study discloses that dep learning based automated ILD techniques shows higher potential than machine learning techniques. Acquiring an ILD dataset that addresses all the common Iris spoofing attacks is also a need of the time. The survey, thus, opens practical challenges in the field of ILD from data collection to liveness detection and encourage future research.

Background: Various biochemical and histological methods are available for human age determination which are invasive and may require extraction of teeth. The present study aims to assess the accuracy of age estimation from tooth-coronal index (TCI) of known age and sex individuals and to present a noninvasive method for age estimation. Materials and Methods: This retrospective study comprised 88 patients, which included 54 males and 34 females. An orthopantomogram of these individuals were taken, and premolars and molars in the same were evaluated. The height of the crown (coronal height [CH]) and the height of the coronal pulp cavity (coronal pulp cavity height [CPCH]) was digitally measured on the computer screen. The TCI given by Ikeda et al. in 1985 (TCI = [CPCH × 100]/CH.) was computed on each tooth and regressed on real age of the sample. The mean, median, range, and standard deviation of the computed index were calculated. The correlation between the actual age and the estimated age was calculated using t-test. P < 0.05 was considered significant. Results: Results revealed that there is a significant correlation between the TCI with age. Increase in TCI observed with age; however, it showed no significant sex difference. Conclusion: TCI is a precise, noninvasive and easily used reliable biomarker for age estimation and is applicable to both living and dead individuals.