Citations

Abstract Cellular senescence restrains the expansion of neoplastic cells through several layers of regulation, including epigenetic decoration of chromatin structure and functional modulation of bioactive components. Here we report that expression of the histone H3-specific demethylase KDM4 is upregulated in human stromal cells upon cellular senescence. In clinical oncology, upregulated KDM4 and diminished H3K9/H3K36 methylation are correlated with adverse survival of cancer patients post-chemotherapy. Global chromatin accessibility mapping via ATAC-seq and expression profiling through RNA-seq reveal extensive reorganization of chromosomes and spatiotemporal reprogramming of the transcriptomic landscape, events responsible for development of the senescence-associated secretory phenotype (SASP). Selectively targeting KDM4 dampens the SASP of senescent stromal cells and enhances the apoptotic index of cancer cells in the treatment-damaged tumor microenvironment (TME), together prolonging overall survival of experimental animals. Our study supports the dynamic change of H3K9/H3K36 methylation marks during cellular senescence, identifies an unusually permissive chromatin state, unmasks KDM4 as a key modulator of the SASP, and presents a novel therapeutic avenue to manipulate cellular senescence and curtail age-related pathologies.

AbstractALK‐positive ALCL can lead to rapid irreversible destruction of the optic pathway. Early treatment should be instituted in patients with CNS involvement or those at increased CNS risk.

AbstractImmunotherapy is a class of promising anticancer treatments that has recently gained attention due to surging numbers of FDA approvals and extensive preclinical studies demonstrating efficacy. Nevertheless, further clinical implementation has been limited by high variability in patient response to different immunotherapeutic agents. These treatments currently do not have reliable predictors of efficacy and may lead to side effects. The future development of additional immunotherapy options and the prediction of patient‐specific response to treatment require advanced screening platforms associated with accurate and rapid data interpretation. Advanced engineering approaches ranging from sequencing and gene editing, to tumor organoids engineering, bioprinted tissues, and organs‐on‐a‐chip systems facilitate the screening of cancer immunotherapies by recreating the intrinsic and extrinsic features of a tumor and its microenvironment. High‐throughput platform development and progress in artificial intelligence can also improve the efficiency and accuracy of screening methods. Here, these engineering approaches in screening cancer immunotherapies are highlighted, and a discussion of the future perspectives and challenges associated with these emerging fields to further advance the clinical use of state‐of‐the‐art cancer immunotherapies are provided.

Abstract The words cure and hope are important terms in oncology, reflecting a balance of aspirations and realism for physicians and patients. Yet, some have suggested that oncologists are reluctant to use these terms. We tested this hypothesis by performing a bibliometric analysis of the frequency of use of these words in JAMA Oncology (JAMA Oncol) and the Journal of Clinical Oncology (JCO). The text of all articles in 3 categories—primary research, editorials, and narrative essays—appearing in JCO from 2000 to 2018 and in JAMA Oncol from 2015 to 2019 was analyzed. These analyses compared, across these categories, the proportion of articles containing the words cure and hope, as well as the proportion of total sentences containing these words. There were statistically significant differences in frequency of the use of the terms cure and hope as a function of the type of article published in the JCO and JAMA Oncol (2-sided P values ranging from .005 to <.001). Results were similar for both journals, with minor exceptions. Both hope and cure were used in a greater number of articles and sentences in the narrative and editorial categories than in primary research. Moreover, hope was used more often in narrative essays than in editorials. The relative reluctance to use these terms in more scientifically oriented original reports, despite concomitant improvements in oncologic outcomes, may reflect a bias worthy of future exploration.

Abstract Background: Racial disparities in breast cancer outcomes persist in the US, in which black women are more likely to die from breast cancer than white women. Despite levels of mammographic screening comparable to the US, Atlanta has a disproportionate burden of late-stage breast tumors and higher mortality rates, especially among black women. To better understand this disparity, we sought to identify tumor, treatment, and patient characteristics that may contribute to the observed differences in breast cancer mortality between black and white women in the metropolitan Atlanta area. Methods: In this study, patients were identified from the Georgia Cancer Registry. We included 4943 non-Hispanic white and 3580 non-Hispanic black women with an initial diagnosis of stage I-IV primary breast cancer between January 2010 and December 2014 in Atlanta. Cox proportional hazard regression was used to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) to compare black vs. white breast cancer mortality by tumor (stage, grade, ER status, and molecular subtype), treatment (surgery type, receipt of chemotherapy, radiation, hormone therapy, and trastuzumab), and patient (insurance, marital status, SES, and location of service) characteristics. We performed a mediation analysis to evaluate the contribution of subtype, stage, and socioeconomic status (SES) as mediators on the path between race and breast cancer mortality. Results: Compared with white breast cancer patients, black women were younger with tumors that were higher stage, higher grade, and more likely to be larger, node positive and triple negative. In fully adjusted models, black women diagnosed with Luminal A subtype were 58% more likely to die of breast cancer compared to their white counterparts (HR=1.58, 95%CI 1.31-2.00). Similarly, black women with private insurance were 60% more likely to die of breast cancer (HR=1.61, 95%CI 1.25-1.98), and black women in the highest SES group were more than twice as likely to die from breast cancer (HR=2.26, 95%CI 1.26-4.06) than white women with comparable SES. The smallest disparities in breast cancer mortality by race were observed among women without insurance, in the lowest SES index, or those diagnosed with triple-negative breast cancer. The mediation analysis showed 84.8% of the effect between race and breast cancer mortality was through stage, subtype, and SES. Conclusion: Our results indicate variation in racial disparities in breast cancer mortality by tumor and patient characteristics. Consistent with previous reports, our mediation results suggest that later stage and triple-negative subtype among black women are major contributors of the observed disparity. However, our results also shed new light on the disparity, suggesting that the largest disparities are observed among women with ER+ tumors amenable to adjuvant therapies and are most pronounced among women of high SES. More research is needed to understand the drivers of disparities in these treatable tumors. Citation Format: Lindsay J. Collin, Renjian Jiang, Kevin C. Ward, Keerthi Gogineni, Preeti D. Subhedar, Mark Sherman, Mia M. Gaudet, Carmen Radecki Breitkopf, Olivia D'Angelo, Sheryl Gabram-Mendola, Jolie Siegel, Rana Aneja, Anne Gaglioti, Lauren E. McCullough. Identification of factors contributing to breast cancer mortality disparities in the metropolitan Atlanta area [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr C053.

Objectives Magnetization transfer imaging is a novel noninvasive tool for the detection of kidney fibrosis, but its association with kidney function and hemodynamics is unclear. Renovascular disease (RVD) associated with metabolic derangements elicits renal fibrosis and is often unresponsive to percutaneous transluminal angioplasty (PTRA), but tools to predict therapeutic success are unavailable. We hypothesized that magnetization transfer imaging predicts kidney recovery after PTRA in swine with unilateral RVD. Materials and Methods Stenotic kidney (STK) and contralateral kidney magnetization transfer ratios (MTRs; M t/M 0) were measured at 3.0-T magnetic resonance imaging, at offset frequencies of 600 and 1000 Hz, before and 1 month post-PTRA in 7 RVD pigs. Stenotic kidney MTR was correlated to renal perfusion, renal blood flow (RBF), and glomerular filtration rate (GFR), determined using multidetector computed tomography and with ex vivo renal fibrosis (trichrome staining). Untreated RVD (n = 6) and normal pigs (n = 7) served as controls. Results Renovascular disease induced hypertension and renal dysfunction. Blood pressure and renal perfusion were unchanged post-PTRA, but GFR and RBF increased. Baseline cortical STK-MTR predicted post-PTRA renal perfusion and RBF, and MTR changes associated inversely with changes in perfusion and normalized GFR. Stenotic kidney MTR at 600 Hz showed closer association with renal parameters, but both frequencies predicted post-PTRA cortical fibrosis. Conclusions Renal STK-MTR, particularly at 600 Hz offset, is sensitive to hemodynamic changes after PTRA in swine RVD and capable of noninvasively predicting post-PTRA kidney perfusion, RBF, and fibrosis. Therefore, STK-MTR may be a valuable tool to predict renal hemodynamic and functional recovery, as well as residual kidney fibrosis after revascularization in RVD.

Background: Asymptomatic recurrences of atrial fibrillation (AF) are common after ablation of AF. Objective: We aimed to analyze the performance of the mobile ECG device using artificial intelligence (AI) algorithm in detection of AF after ablation. Method: A randomized controlled trial of AF screening using a handheld single-lead ECG monitor (BigThumb®) or a traditional follow-up strategy was conducted in patients with non-valvular AF after catheter ablation. Consecutive patients were randomized to either BigThumb Group (BT Group) or Traditional Follow-up Group (TF Group). Monitoring data was collected and analyzed. The ECGs collected by BigThumb were compared using the automated AF detection algorithm, AI algorithm and cardiologists’ manual review. Subsequent changes in adherence on oral anticoagulation of patients were also recorded. Result: We studied 218 patients (109 in BT Group, 109 in TF Group). After a follow-up of 345.4±60.2 days, AF-free survival rate was 64.2% in BT Group and 78.9% in TF Group (P=0.0163), with more adherence on oral anticoagulation in BT Group (P=0.0052). The participants in the BT Group recorded 26133 ECGs during the follow-up, among which 3299 (12.6%) were diagnosed as AF by cardiologists’ manual review. The sensitivity and specificity of the AI algorithm were 94.4% and 98.5% respectively, which are significantly higher than the automated AF detection algorithm (90.7% and 96.2%). Conclusion: We found that follow-up after AF ablation using BigThumb leads to a more frequent detection of AF recurrence and more adherence on oral anticoagulation. Artificial intelligence algorithm improves the accuracy of ECG diagnosis.

AbstractObjectiveTo identify depression subphenotypes from Electronic Health Records (EHRs) using machine learning methods, and analyze their characteristics with respect to patient demographics, comorbidities, and medications.Materials and MethodsUsing EHRs from the INSIGHT Clinical Research Network (CRN) database, multiple machine learning (ML) algorithms were applied to analyze 11 275 patients with depression to discern depression subphenotypes with distinct characteristics.ResultsUsing the computational approaches, we derived three depression subphenotypes: Phenotype_A (n = 2791; 31.35%) included patients who were the oldest (mean (SD) age, 72.55 (14.93) years), had the most comorbidities, and took the most medications. The most common comorbidities in this cluster of patients were hyperlipidemia, hypertension, and diabetes. Phenotype_B (mean (SD) age, 68.44 (19.09) years) was the largest cluster (n = 4687; 52.65%), and included patients suffering from moderate loss of body function. Asthma, fibromyalgia, and Chronic Pain and Fatigue (CPF) were common comorbidities in this subphenotype. Phenotype_C (n = 1452; 16.31%) included patients who were younger (mean (SD) age, 63.47 (18.81) years), had the fewest comorbidities, and took fewer medications. Anxiety and tobacco use were common comorbidities in this subphenotype.ConclusionComputationally deriving depression subtypes can provide meaningful insights and improve understanding of depression as a heterogeneous disorder. Further investigation is needed to assess the utility of these derived phenotypes to inform clinical trial design and interpretation in routine patient care.

AbstractDisturbed intrauterine development increases the risk of renal disease. Various studies have reported that Notch signalling plays a significant role in kidney development and kidney diseases. A disintegrin and metalloproteinase domain 10 (ADAM10), an upstream protease of the Notch pathway, is also reportedly involved in renal fibrosis. However, how ADAM10 interacts with the Notch pathway and causes renal fibrosis is not fully understood. In this study, using a prenatal chlorpyrifos (CPF) exposure mouse model, we investigated the role of the ADAM10/Notch axis in kidney development and fibrosis. We found that prenatal CPF‐exposure mice presented overexpression of Adam10, Notch1 and Notch2, and led to premature depletion of Six2+ nephron progenitors and ectopic formation of proximal tubules (PTs) in the embryonic kidney. These abnormal phenotypic changes persisted in mature kidneys due to the continuous activation of ADAM10/Notch and showed aggravated renal fibrosis in adults. Finally, both ADAM10 and NOTCH2 expression were positively correlated with the degree of renal interstitial fibrosis in IgA nephropathy patients, and increased ADAM10 expression was negatively correlated with decreased kidney function evaluated by serum creatinine, cystatin C, and estimated glomerular filtration rate. Regression analysis also indicated that ADAM10 expression was an independent risk factor for fibrosis in IgAN. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.