Real-world outcomes associated with poly(ADP-ribose) polymerase inhibitor monotherapy maintenance in patients with primary advanced ovarian cancer

OBJECTIVE: This study used real-world population data to assess the trends of first-line (1L) poly(ADP-ribose) polymerase inhibitor (PARPi) maintenance treatment uptake and outcomes in patients with primary advanced ovarian cancer (AOC). METHODS: Patients diagnosed with AOC between January 1, 2017, and June 30, 2021, who completed 1L chemotherapy were selected from a real-world database. Descriptive analyses were performed to evaluate patient demographics, clinicopathological characteristics, and 1L treatment patterns. Time to next treatment or death was used as a proxy for real-world progression-free survival (rwPFS). Kaplan-Meier methods and Cox models were used for statistical analyses. RESULTS: Of 705 patients who completed 1L chemotherapy, 166 received PARPi monotherapy and 539 underwent active surveillance (AS). Median follow-up was 10.9 months for PARPi monotherapy and 20.6 months for AS. PARPi monotherapy use increased from 6% in 2017 to 53% in 2021. Overall, patients receiving PARPi monotherapy had longer rwPFS than those who underwent AS (not reached vs 9.53 mo) respectively. rwPFS was also longer in patients who received PARPi monotherapy compared with AS in patients with BRCA- mutated disease (not reached vs 11.4 mo), BRCA- wild-type disease (13.5 vs 9.1 mo), homologous recombination-deficient tumors (not reached vs 10.2 mo), and homologous recombination-proficient or unknown status tumors (13.5 vs 9.3 mo). CONCLUSIONS: Our real-world analysis suggested that 47% of patients with primary AOC did not receive PARPi maintenance in the year 2021. PARPi use was associated with significantly improved outcomes compared with AS

A Multi-Scale Correlative Approach for Crowd-Sourced Multi-Variate Spatiotemporal Data

With the increase in community-contributed data availability, citizens and analysts are interested in identifying patterns, trends and correlation within these datasets. Various levels of aggregation are often applied to interpret such large data schemes. Identifying the proper scales of aggregation is a non-trivial task in this exploratory data analysis process. In this paper, we present an integrated visual analytics environment that facilitates the exploration of multivariate categorical spatiotemporal data at multiple spatial scales of aggregation, focusing on citizen-contributed data. We propose a compact visual correlation representation by embedding various statistical measures across different spatial regions to enable users to explore correlations between multiple data categories across different spatial scales. The system provides several scale-sensitive spatial partitioning strategies to examine the sensitivity of correlations at varying spatial extents. To demonstrate the capabilities of our system, we provide several usage scenarios from various domains including citizen-contributed social media (soundscape ecology) data

Effectiveness guidance document (EGD) for Chinese medicine trials: a consensus document

Background: There is a need for more Comparative Effectiveness Research (CER) on Chinese medicine (CM) to inform clinical and policy decision-making. This document aims to provide consensus advice for the design of CER trials on CM for researchers. It broadly aims to ensure more adequate design and optimal use of resources in generating evidence for CM to inform stakeholder decision-making. Methods: The Effectiveness Guidance Document (EGD) development was based on multiple consensus procedures (survey, written Delphi rounds, interactive consensus workshop, international expert review). To balance aspects of internal and external validity, multiple stakeholders, including patients, clinicians, researchers and payers were involved in creating this document. Results: Recommendations were developed for “using available data” and “future clinical studies”. The recommendations for future trials focus on randomized trials and cover the following areas: designing CER studies, treatments, expertise and setting, outcomes, study design and statistical analyses, economic evaluation, and publication. Conclusion: The present EGD provides the first systematic methodological guidance for future CER trials on CM and can be applied to single or multi-component treatments. While CONSORT statements provide guidelines for reporting studies, EGDs provide recommendations for the design of future studies and can contribute to a more strategic use of limited research resources, as well as greater consistency in trial design

Genome-Wide and Differential Proteomic Analysis of Hepatitis B Virus and Aflatoxin B1 Related Hepatocellular Carcinoma in Guangxi, China

Both hepatitis B virus (HBV) and aflatoxin B1 (AFB1) exposure can cause liver damage as well as increase the probability of hepatocellular carcinoma (HCC). To investigate the underlying genetic changes that may influence development of HCC associated with HBV infection and AFB1 exposure, HCC patients were subdivided into 4 groups depending upon HBV and AFB1 exposure status: (HBV(+)/AFB1(+), HBV(+)/AFB1(-), HBV(-)/AFB1(+), HBV(-)/AFB1(-)). Genetic abnormalities and protein expression profiles were analyzed by array-based comparative genomic hybridization and isobaric tagging for quantitation. A total of 573 chromosomal aberrations (CNAs) including 184 increased and 389 decreased were detected in our study population. Twenty-five recurrently altered regions (RARs; chromosomal alterations observed in ≥10 patients) in chromosomes were identified. Loss of 4q13.3-q35.2, 13q12.1-q21.2 and gain of 7q11.2-q35 were observed with a higher frequency in the HBV(+)/AFB1(+), HBV(+)/AFB1(-) and HBV(-)/AFB1(+) groups compared to the HBV(-)/AFB(-) group. Loss of 8p12-p23.2 was associated with high TNM stage tumors (P = 0.038) and was an unfavorable prognostic factor for tumor-free survival (P=0.045). A total of 133 differentially expressed proteins were identified in iTRAQ proteomics analysis, 69 (51.8%) of which mapped within identified RARs. The most common biological processes affected by HBV and AFB1 status in HCC tumorigenesis were detoxification and drug metabolism pathways, antigen processing and anti-apoptosis pathways. Expression of AKR1B10 was increased significantly in the HBV(+)/AFB1(+) and HBV(-)/AFB1(+) groups. A significant correlation between the expression of AKR1B10 mRNA and protein levels as well as AKR1B10 copy number was observed, which suggest that AKR1B10 may play a role in AFB1-related hepatocarcinogenesis. In summary, a number of genetic and gene expression alterations were found to be associated with HBV and AFB1- related HCC. The possible synergistic effects of HBV and AFB1 in hepatocarcinogenesis warrant further investigations

Diagnosing Sarcopenia with AI-Aided Ultrasound (DINOSAUR)—A Pilot Study

Background: Sarcopenia has been recognized as a determining factor in surgical outcomes and is associated with an increased risk of postoperative complications and readmission. Diagnosis is currently based on clinical guidelines, which includes assessment of skeletal muscle mass but not quality. Ultrasound has been proposed as a useful point-of-care diagnostic tool to assess muscle quality, but no validated cut-offs for sarcopenia have been reported. Using novel automated artificial intelligence (AI) software to interpret ultrasound images may assist in mitigating the operator-dependent nature of the modality. Our study aims to evaluate the fidelity of AI-aided ultrasound as a reliable and reproducible modality to assess muscle quality and diagnose sarcopenia in surgical patients. Methods: Thirty-six adult participants from an outpatient clinic were recruited for this prospective cohort study. Sarcopenia was diagnosed according to Asian Working Group for Sarcopenia (AWGS) 2019 guidelines. Ultrasonography of the rectus femoris muscle was performed, and images were analyzed by an AI software (MuscleSound® (Version 5.69.0)) to derive muscle parameters including intramuscular adipose tissue (IMAT) as a proxy of muscle quality. A receiver operative characteristic (ROC) curve was used to assess the predictive capability of IMAT and its derivatives, with area under the curve (AUC) as a measure of overall diagnostic accuracy. To evaluate consistency between ultrasound users of different experience, intra- and inter-rater reliability of muscle ultrasound parameters was analyzed in a separate cohort using intraclass correlation coefficients (ICC) and Bland–Altman plots. Results:The median age was 69.5 years (range: 26–87), and the prevalence of sarcopenia in the cohort was 30.6%. The ROC curve plotted with IMAT index (IMAT% divided by muscle area) yielded an AUC of 0.727 (95% CI: 0.551–0.904). An optimal cut-off point of 4.827%/cm2 for IMAT index was determined with a Youden’s Index of 0.498. We also demonstrated that IMAT index has excellent intra-rater reliability (ICC = 0.938, CI: 0.905–0.961) and good inter-rater reliability (ICC = 0.776, CI: 0.627–0.866). In Bland–Altman plots, the limits of agreement were from −1.489 to 1.566 and −2.107 to 4.562, respectively. Discussion: IMAT index obtained via ultrasound has the potential to act as a point-of-care evaluation for sarcopenia screening and diagnosis, with good intra- and inter-rater reliability. The proposed IMAT index cut-off maximizes sensitivity for case finding, supporting its use as an easily implementable point-of-care test in the community for sarcopenia screening. Further research incorporating other ultrasound parameters of muscle quality may provide the basis for a more robust diagnostic tool to help predict surgical risk and outcomes.</p

An integrative view of the regulatory and transcriptional landscapes in mouse hematopoiesis.

Thousands of epigenomic data sets have been generated in the past decade, but it is difficult for researchers to effectively use all the data relevant to their projects. Systematic integrative analysis can help meet this need, and the VISION project was established for validated systematic integration of epigenomic data in hematopoiesis. Here, we systematically integrated extensive data recording epigenetic features and transcriptomes from many sources, including individual laboratories and consortia, to produce a comprehensive view of the regulatory landscape of differentiating hematopoietic cell types in mouse. By using IDEAS as our integrative and discriminative epigenome annotation system, we identified and assigned epigenetic states simultaneously along chromosomes and across cell types, precisely and comprehensively. Combining nuclease accessibility and epigenetic states produced a set of more than 200,000 candidate cis-regulatory elements (cCREs) that efficiently capture enhancers and promoters. The transitions in epigenetic states of these cCREs across cell types provided insights into mechanisms of regulation, including decreases in numbers of active cCREs during differentiation of most lineages, transitions from poised to active or inactive states, and shifts in nuclease accessibility of CTCF-bound elements. Regression modeling of epigenetic states at cCREs and gene expression produced a versatile resource to improve selection of cCREs potentially regulating target genes. These resources are available from our VISION website to aid research in genomics and hematopoiesis.National Institute of Diabetes and Digestive and Kidney Diseases (grant number R24DK106766-01A1), the National Human Genome Research Institute (grant number U54HG006998

Gradient lithography of engineered proteins to fabricate 2D and 3D cell culture microenvironments

Spatial patterning of proteins is a valuable technique for many biological applications and is the prevailing tool for defining microenvironments for cells in culture, a required procedure in developmental biology and tissue engineering research. However, it is still challenging to achieve protein patterns that closely mimic native microenvironments, such as gradient protein distributions with desirable mechanical properties. By combining projection dynamic mask lithography and protein engineering with non-canonical photosensitive amino acids, we demonstrate a simple, scalable strategy to fabricate any user-defined 2D or 3D stable gradient pattern with complex geometries from an artificial extracellular matrix (aECM) protein. We show that the elastic modulus and chemical nature of the gradient profile are biocompatible and allow useful applications in cell biological research

Deregulation of DUX4 and ERG in acute lymphoblastic leukemia

Chromosomal rearrangements deregulating hematopoietic transcription factors are common in acute lymphoblastic leukemia (ALL).1,2 Here, we show that deregulation of the homeobox transcription factor gene DUX4 and the ETS transcription factor gene ERG are hallmarks of a subtype of B-progenitor ALL that comprises up to 7% of B-ALL. DUX4 rearrangement and overexpression was present in all cases, and was accompanied by transcriptional deregulation of ERG, expression of a novel ERG isoform, ERGalt, and frequent ERG deletion. ERGalt utilizes a non-canonical first exon whose transcription was initiated by DUX4 binding. ERGalt retains the DNA-binding and transactivating domains of ERG, but inhibits wild-type ERG transcriptional activity and is transforming. These results illustrate a unique paradigm of transcription factor deregulation in leukemia, in which DUX4 deregulation results in loss-of-function of ERG, either by deletion or induction of expression of an isoform that is a dominant negative inhibitor of wild type ERG function