OBJECTIVES:We describe the processes used in SCOPE, a community-based participatory research (CBPR) initiative, to achieve multisectoral engagement and collective action to prevent childhood obesity.
Childhood obesity is complex and requires a ‘systems approach’ that collectively engages across multiple community settings. Sustainable Childhood Obesity Prevention through Community Engagement (SCOPE) has implemented Live 5-2-1-0—a multi-sector, multi-component childhood obesity prevention initiative informed by systems thinking and participatory research via an innovative knowledge translation (KT) model (RE-FRAME). This paper describes the protocol for implementing and evaluating RE-FRAME in two ‘existing’ (>2 years of implementation) and two ‘new’ Live 5-2-1-0 communities to understand how to facilitate and sustain systems/community-level change. In this mixed-methods study, RE-FRAME was implemented via online resources, webinars, a backbone organization (SCOPE) coordinating the initiative, and a linking system supporting KT. Qualitative and quantitative data were collected using surveys and stakeholder interviews, analyzed using thematic analysis and descriptive statistics, respectively. Existing communities described the consistency of Live 5-2-1-0 and extensive local partnerships/champions as catalysts for synergistic community-wide action; new communities felt that the simplicity of the message combined with the transfer of experiential learning would inform their own strategies and policies/programs to broadly disseminate Live 5-2-1-0. RE-FRAME effectively guided the refinement of the initiative and provided a framework upon which evaluation results described how to implement a community-based systems approach to childhood obesity prevention.
Background: Glioblastoma (GBM) is a highly malignant brain neoplasm with poor survival. Despite its aggressive nature, metastatic spread of GBM is identified only rarely. While the molecular alterations associated with GBM and its subtypes are well-described, there remains a gap in understanding which alterations may predispose towards metastasis. In this report, we present a case of GBM with multi-organ metastases and discuss its genomic alterations. Case presentation: A 74-year-old woman was diagnosed with left occipital glioblastoma (IDH-wildtype, MGMTunmethylated), for which she underwent resection, standard chemoradiation, and then stereotactic radiosurgery (SRS) for local recurrence. One month after SRS, work-up for a pathologic hip fracture revealed a left breast mass, lytic lesions involving pelvic bones, and multiple pulmonary and hepatic lesions. Biopsies of the breast and bone lesions both demonstrated metastatic IDH-wildtype GBM. For worsening neurologic symptoms, the patient underwent debulking of a large right temporal lobe recurrence and expired shortly thereafter. Autopsy confirmed metastatic GBM in multiple systemic sites, including bilateral lungs, heart, liver, thyroid, left breast, small bowel, omentum, peritoneal surfaces, visceral surfaces, left pelvic bone, and hilar lymph nodes. Targeted sequencing was performed on tissue samples obtained pre-and postmortem, as well as on cell cultures and an orthotopic mouse xenograft derived from premortem surgical specimens. A BRCA1 mutation (p.I571T) was the only variant found in common among the primary, recurrence, and metastatic specimens, suggesting its likely status as an early driver mutation. Multiple subclonal ARID1A mutations, which promote genomic instability through impairment of DNA mismatch repair, were identified only in the recurrence. Mutational spectrum analysis demonstrated a high percentage of C:G to T:A transitions in the post-treatment samples but not in the primary tumor. Conclusion: This case report examines a rare case of widely metastatic IDH-wildtype GBM with a clonal somatic mutation in BRCA1. Post-treatment recurrent tumor in the brain and in multiple systemic organs exhibited evidence of acquired DNA mismatch repair deficiency, which may be explained by functional loss of ARID1A. We identify a potential role for immune checkpoint and PARP inhibitors in the treatment of metastatic GBM.
Background: Human papillomaviruses (HPVs) have been linked to a variety of human cancers. As the landscape of HPV-related neoplasia continues to expand, uncommon and rare HPV genotypes have also started to emerge. Host-virus interplay is recognized as a key driver in HPV carcinogenesis, with host immune status, virus genetic variants and coinfection highly influencing the dynamics of malignant transformation. Immunosuppression and tissue tropism are also known to influence HPV pathogenesis. Methods: Herein, we present a case of a patient who, in the setting of HIV positivity, developed anal squamous cell carcinoma associated with HPV69 and later developed squamous cell carcinoma in the lungs, clinically presumed to be metastatic disease, associated with HPV73. Consensus PCR screening for HPV was performed by real-time PCR amplification of the L1 gene region, amplification of the E6 regions with High-Resolution Melting Curve Analysis followed by Sanger sequencing confirmation and phylogenetic analysis. Results: Sanger sequencing of the consensus PCR amplification product determined that the anal tissue sample was positive for HPV 69, and the lung tissue sample was positive for HPV 73. Conclusions: This case underscores the importance of recognizing the emerging role of these rare “possibly carcinogenic” HPV types in human carcinogenesis.
BackgroundDistinguishing well-differentiated hepatocellular carcinoma (WD-HCC), hepatocellular adenoma (HA) and non-neoplastic liver tissue (NNLT) solely on morphology is often challenging. The purpose of this study was to evaluate the use of computational image analysis to distinguish WD-HCC, HA and NNLT.MethodsSeventy-seven cases comprising of WD-HCC (n = 26), HA (n = 23) and NNLT (n = 28) were retrieved and reviewed. A total of 485 hematoxylin and eosin (H&E) photomicrographs (× 400, 0.09 µm2) of WD-HCC (n = 183), HA (n = 173), NNLT (n = 129) and nine whole-slide scans (three of each diagnosis) were obtained, color deconvoluted and digitally transformed. Quantitative data including nuclear density, nuclear sphericity, nuclear perimeter, and nuclear eccentricity from each image were acquired. The data were analyzed by one-way analysis of variance (ANOVA) with Tukey post hoc test, followed by unsupervised and supervised (Chi-square automatic interaction detection (CHAID)) cluster analysis.ResultsUnsupervised cluster analysis identified three well defined clusters of WD-HCC, HA and NNLT. Employing the four most discriminating nuclear features, supervised analysis was performed on a training set of 383 images, and validated on the remaining 102 test images. The analysis identified WD-HCC (sensitivity 100%, specificity 98%), HA (sensitivity 71%, specificity 85%) and NNLT (sensitivity 70%, specificity 86%). An analysis of whole-slide images identified WD-HCC with sensitivity and specificity of 100%.ConclusionsWe have successfully demonstrated that computational image analysis of nuclear features can differentiate WD-HCC from non-malignant liver with high accuracy, and can be used to assist in the histopathological diagnosis of hepatocellular carcinoma.
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