Modeling the Prognostic Impact of Circulating Tumor Cells Enumeration in Metastatic Breast Cancer for Clinical Trial Design Simulation

Biomarker; Liquid biopsy; Machine learningBiomarcadores; Biopsia líquida; Aprendizaje automáticoBiomarcadors; Biòpsia líquida; Aprenentatge automàticDespite the strong prognostic stratification of circulating tumor cells (CTCs) enumeration in metastatic breast cancer (MBC), current clinical trials usually do not include a baseline CTCs in their design. This study aimed to generate a classifier for CTCs prognostic simulation in existing datasets for hypothesis generation in patients with MBC. A K-nearest neighbor machine learning algorithm was trained on a pooled dataset comprising 2436 individual MBC patients from the European Pooled Analysis Consortium and the MD Anderson Cancer Center to identify patients likely to have CTCs ≥ 5/7 mL blood (StageIVaggressive vs StageIVindolent). The model had a 65.1% accuracy and its prognostic impact resulted in a hazard ratio (HR) of 1.89 (Simulatedaggressive vs SimulatedindolentP < .001), similar to patients with actual CTCs enumeration (HR 2.76; P < .001). The classifier’s performance was then tested on an independent retrospective database comprising 446 consecutive hormone receptor (HR)-positive HER2-negative MBC patients. The model further stratified clinical subgroups usually considered prognostically homogeneous such as patients with bone-only or liver metastases. Bone-only disease classified as Simulatedaggressive had a significantly worse overall survival (OS; P < .0001), while patients with liver metastases classified as Simulatedindolent had a significantly better prognosis (P < .0001). Consistent results were observed for patients who had undergone CTCs enumeration in the pooled population. The differential prognostic impact of endocrine- (ET) and chemotherapy (CT) was explored across the simulated subgroups. No significant differences were observed between ET and CT in the overall population, both in terms of progression-free survival (PFS) and OS. In contrast, a statistically significant difference, favoring CT over ET was observed among Simulatedaggressive patients (HR: 0.62; P = .030 and HR: 0.60; P = .037, respectively, for PFS and OS).The study was supported by Lynn Sage Cancer Research Foundation and the the CRO Aviano 5x1000 2014 per la Ricerca Sanitaria, Cancer Specific Intramural Grant. The funding sources had no role in the study design, data collection, data analysis, interpretation, or writing of the manuscript

Positive predictive value of ERBB2 copy number gain by tissue or circulating tumor DNA next-generation sequencing across advanced cancers

BACKGROUND: The correlation of ERBB2 copy number gain (CNG) from tissue or circulating tumor DNA (ctDNA) by next-generation sequencing (NGS) with standard HER2 tissue evaluation is not well understood. MATERIALS AND METHODS: We retrospectively identified patients with ERBB2 CNG on commercial NGS. We described their clinical-pathologic features and calculated the positive predictive value (PPV) of ERBB2 CNG by NGS for HER2-positivity by IHC and FISH testing. RESULTS: 176 patients had NGS revealing an ERBB2 CNG (112 by tumor tissue and 91 by ctDNA). The cancer subtypes with the most cases with ERBB2 CNG by NGS were breast ( CONCLUSIONS: ERBB2 CNG by NGS is detected in numerous malignancies for which HER2 testing is not standard. Detection of ERBB2 CNG by tissue NGS and ctDNA has a high PPV for true HER2-positivity by standard IHC and/or FISH testing in breast cancer

Therapeutic potential of flavonoids in cancer: ROS-mediated mechanisms

Cancer is a leading cause of morbidity and mortality around the globe. Reactive oxygen species (ROS) play contradicting roles in cancer incidence and progression. Antioxidants have attracted attention as emerging therapeutic agents. Among these are flavonoids, which are natural polyphenols with established anticancer and antioxidant capacities. Increasing evidence shows that flavonoids can inhibit carcinogenesis via suppressing ROS levels. Surprisingly, flavonoids can also trigger excessive oxidative stress, but this can also induce death of malignant cells. In this review, we explore the inherent characteristics that contribute to the antioxidant capacity of flavonoids, and we dissect the scenarios in which they play the contrasting role as pro-oxidants. Furthermore, we elaborate on the pathways that link flavonoid-mediated modulation of ROS to the prevention and treatment of cancer. Special attention is given to the ROS-mediated anticancer functions that (-)-epigallocatechin gallate (EGCG), hesperetin, naringenin, quercetin, luteolin, and apigenin evoke in various cancers. We also delve into the structure-function relations that make flavonoids potent antioxidants. This review provides a detailed perspective that can be utilized in future experiments or trials that aim at utilizing flavonoids or verifying their efficacy for developing new pharmacologic agents. We support the argument that flavonoids are attractive candidates for cancer therapy

Sustainability considerations for clinical and translational research informatics infrastructure

A robust biomedical informatics infrastructure is essential for academic health centers engaged in translational research. There are no templates for what such an infrastructure encompasses or how it is funded. An informatics workgroup within the Clinical and Translational Science Awards network conducted an analysis to identify the scope, governance, and funding of this infrastructure. After we identified the essential components of an informatics infrastructure, we surveyed informatics leaders at network institutions about the governance and sustainability of the different components. Results from 42 survey respondents showed significant variations in governance and sustainability; however, some trends also emerged. Core informatics components such as electronic data capture systems, electronic health records data repositories, and related tools had mixed models of funding including, fee-for-service, extramural grants, and institutional support. Several key components such as regulatory systems (e.g., electronic Institutional Review Board [IRB] systems, grants, and contracts), security systems, data warehouses, and clinical trials management systems were overwhelmingly supported as institutional infrastructure. The findings highlighted in this report are worth noting for academic health centers and funding agencies involved in planning current and future informatics infrastructure, which provides the foundation for a robust, data-driven clinical and translational research program

Dysregulation of angiotensin converting enzyme 2 expression and function in comorbid disease conditions possibly contributes to coronavirus infectious disease 2019 complication severity

ACE2 has emerged as a double agent in the COVID-19 ordeal, as it is both physiologically protective and virally conducive. The identification of ACE2 in as many as 72 tissues suggests that extrapulmonary invasion and damage is likely, which indeed has already been demonstrated by cardiovascular and gastrointestinal symptoms. On the other hand, identifying ACE2 dysregulation in patients with comorbidities may offer insight as to why COVID-19 symptoms are often more severe in these individuals. This may be attributed to a pre-existing proinflammatory state that is further propelled with the cytokine storm induced by SARS-CoV-2 infection or the loss of functional ACE2 expression as a result of viral internalization. Here, we aim to characterize the distribution and role of ACE2 in various organs to highlight the scope of damage that may arise upon SARSCoV- 2 invasion. Furthermore, by examining the disruption of ACE2 in several comorbid diseases, we offer insight into potential causes of increased severity of COVID-19 symptoms in certain individuals.This work was supported by the Medical Practice Plan Grants from the Faculty of Medicine at the American University of Beirut [320148] to A.F.E.-Y. and the Medical Practice Plan Grants from the Faculty of Medicine at the American University of Beirut [320133] to A.H.E. 1S.H. and Z.W. contributed equally to this work. https://doi.org/10.1124/molpharm.120.000119.Scopu