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Building Climate Change into Medical Education: A Society of General Internal Medicine Position Statement

Ghosh, Arnab K; Azan, Alexander; Basu, Gaurab; Bernstein, Joanna; Gillespie, Elizabeth; Gordon, Lesley B; Krishnamurthy, Sudarshan; LeFrancois, Darlene; Marcus, Erin N; Tejani, Mehul; Townley, Theresa; Rimler, Eva; Whelan, Heather; ,
Building expertise in climate and planetary health among healthcare professionals cannot come with greater urgency as the threats from climate change become increasingly apparent. Current and future healthcare professionals-particularly internists-will increasingly need to understand the interconnectedness of natural systems and human health to better serve their patients longitudinally. Despite this, few national medical societies and accreditation bodies espouse frameworks for climate change and planetary health-related education at the undergraduate (UME), graduate (GME), and continuing (CME) medical education level. As a community of medical educators with an enduring interest in climate change and planetary health, the Society of General Internal Medicine (SGIM) recognizes the need to explicitly define structured educational opportunities and core competencies in both UME and GME as well as pathways for faculty development. In this position statement, we build from the related SGIM Climate and Health position statement, and review and synthesize existing position statements made by US-based medical societies and accreditation bodies that focus on climate change and planetary health-related medical education, identify gaps using Bloom's Hierarchy, and provide recommendations on behalf of SGIM regarding the development of climate and planetary health curricula development. Identified gaps include (1) limited systematic approach to climate and planetary health medical education at all levels; (2) minimal emphasis on learner-driven approaches; (3) limited focus on physician and learner well-being; and (4) limited role for health equity and climate justice. Recommendations include a call to relevant accreditation bodies to explicitly include climate change and planetary health as a competency, extend the structural competency framework to climate change and planetary health to build climate justice, proactively include learners in curricular development and teaching, and ensure resources and support to design and implement climate and planetary health-focused education that includes well-being and resiliency.
PMID: 38424345
ISSN: 1525-1497
CID: 5637492

Association between city-wide lockdown and COVID-19 hospitalization rates in multigenerational households in New York City

Ghosh, Arnab K; Venkatraman, Sara; Reshetnyak, Evgeniya; Rajan, Mangala; An, Anjile; Chae, John K; Unruh, Mark A; Abramson, David; DiMaggio, Charles; Hupert, Nathaniel
BACKGROUND:City-wide lockdowns and school closures have demonstrably impacted COVID-19 transmission. However, simulation studies have suggested an increased risk of COVID-19 related morbidity for older individuals inoculated by house-bound children. This study examines whether the March 2020 lockdown in New York City (NYC) was associated with higher COVID-19 hospitalization rates in neighborhoods with larger proportions of multigenerational households. METHODS:We obtained daily age-segmented COVID-19 hospitalization counts in each of 166 ZIP code tabulation areas (ZCTAs) in NYC. Using Bayesian Poisson regression models that account for spatiotemporal dependencies between ZCTAs, as well as socioeconomic risk factors, we conducted a difference-in-differences study amongst ZCTA-level hospitalization rates from February 23 to May 2, 2020. We compared ZCTAs in the lowest quartile of multigenerational housing to other quartiles before and after the lockdown. FINDINGS/RESULTS:Among individuals over 55 years, the lockdown was associated with higher COVID-19 hospitalization rates in ZCTAs with more multigenerational households. The greatest difference occurred three weeks after lockdown: Q2 vs. Q1: 54% increase (95% Bayesian credible intervals: 22-96%); Q3 vs. Q1: 48% (17-89%); Q4 vs. Q1: 66% (30-211%). After accounting for pandemic-related population shifts, a significant difference was observed only in Q4 ZCTAs: 37% (7-76%). INTERPRETATION/CONCLUSIONS:By increasing house-bound mixing across older and younger age groups, city-wide lockdown mandates imposed during the growth of COVID-19 cases may have inadvertently, but transiently, contributed to increased transmission in multigenerational households.
PMCID:8967012
PMID: 35353857
ISSN: 1932-6203
CID: 5201162

P12.06 Computational Omics Biology Model (CBM) Identifies PD-L1 Immunotherapy Response Criteria Based on Genomic Signature of NSCLC [Meeting Abstract]

Castro, M; Ganti, A K; Grover, H; Kumar, A; Mohapatra, S; Basu, K; Sahu, D; Tyagi, A; Nair, P; Prasad, S; Kumari, P; Mundkur, N; Patel, S; Sauban, M; Behura, L; Kulkarni, S; Patil, M; Narvekar, Y; Ghosh, A; Ullal, Y; Amara, A R; Kapoor, S; Velcheti, V
Introduction: PD-L1 is an immune checkpoint protein that mediates immune evasion. In Non-Small Cell Lung Cancer (NSCLC), its expression is used to predict the outcome of treatment targeting PD-1/L1. However, clinical benefits do not occur uniformly, and new approaches are needed to assist in selecting patients for immunotherapy.
Method(s): 26 patients with known clinical response to pembrolizumab were selected from publicly available data (PMID:25765070) (Table 1). Mutation and copy number aberrations from individual cases served as input into the Cellworks Omics Biology Model (CBM) to generate a patient-specific protein network map from PubMed and other online resources. Disease-biomarkers unique to each patient were identified within protein network maps. Digital drug biosimulations were conducted by measuring the effect of pembrolizumab on a cell growth score comprised of a composite of cell proliferation, viability, apoptosis, metastasis, and other cancer hallmarks. Drug biosimulations were conducted to identify and evaluate therapeutic efficacy.
Result(s): Among 26 patients treated with pembrolizumab, 14 were clinical responders, defined as stable disease or partial response lasting longer than 6 months, and 12 non-responders. Notably, 9/12 non-responders were PD-L1 positive (Table 1). Cellworks biosimulation predicted response with 84.6% accuracy, 75% specificity, and 92.86% sensitivity. Positive predictive value was 81.25% and negative predictive value was 90%. CBM identified that response was influenced by pathways that impacted the tumor microenvironment (TME). Deletions of adenosine pathway genes were observed in responders, whereas CNVs for these genes were enriched in non-responders (Table 1). Loss of ENPP1, and INSIG1 and SENP2 CNV aberrations, all of which regulate the STING pathway, could play a significant role in governing immune checkpoint blockade (ICB) response. Although STK11 loss appears to be a biomarker for poor ICB response, it was equally enriched in responders (n=7) and non-responders (n=7) in this dataset. Notably, responders had STK11 mutations and chromosome 6 loss, whereas non-responders had STK11 loss with chromosome 6 wild type or gain. Finally, frameshift mutations (FSM) enhance neoepitope formation and were higher in responders (average FSM = 48) vs non-responders (average FSM = 19). [Formula presented]
Conclusion(s): Alterations of the adenosine and STING pathways play key roles in determining benefit from PD-1/L1 targeting and highlight therapeutic possibilities for improving outcome in specific patient subgroups based on PD-L1 expression. The Cellworks CBM captures a holistic picture of the TME using tumor omics and improves response prediction beyond PD-L1 testing. Keywords: Multi-omics Therapy Biosimulation, Personalized Cancer Therapy, Immunotherapy Biosimulation
Copyright
EMBASE:2015170020
ISSN: 1556-1380
CID: 5178882

FP16.05 Computational Omics Biology Model (CBM) Identifies Novel Biomarkers to Inform Combination Platinum Compound Therapy in NSCLC [Meeting Abstract]

Velcheti, V; Ganti, A K; Kumar, A; Patil, V; Grover, H; Watson, D; Sauban, M; S, R; Agrawal, A; Kumari, P; Pampana, A; Mundkur, N; Patel, S; Kumar, C; Palaniyeppa, N; Husain, Z; Azam, H; G, P; Mitra, U; Ullal, Y; Ghosh, A; Prakash, A; Basu, K; Lala, D; Kapoor, S; Castro, M
Introduction: Cytotoxic drugs are hampered by limited efficacy. Hence, a personalized treatment approach matching chemotherapy with appropriate patients remains an unmet need. Genomic heterogeneity creates an opportunity to discern key genomic aberrations and pathways that confer resistance and response to standard treatment options. We conducted a study using the Cellworks Computational Omics Biology Model (CBM) to identify novel genomic biomarkers associated with response among Non-Small Cell Lung Cancer (NSCLC) patients receiving platinum-based treatments.
Method(s): 104 NSCLC patients who received platinum-based chemotherapy were selected from TCGA: platinum-etoposide (N=18), platinum-gemcitabine (N=20), platinum-vinorelbine (N=31), platinum-paclitaxel (N=21), and platinum-docetaxel (N=14). Mutation and CNV from each case served as input for the CBM to generate a patient-specific protein network-map based on PubMed and other resources. Biomarkers unique to each patient were identified within protein network-maps. Drug impact on the disease network was biosimulated to determine efficacy score by measuring the effect of chemotherapy on the cell growth score, a composite of cell proliferation, viability, apoptosis, metastasis, DNA damage and other cancer hallmarks. Effectively, the mechanism of action of each drug was mapped to each patient's genome and biological consequences determined response.
Result(s): Among the 104 patients, 74 were responders (R) and 30 non-responders (NR), determined using compete and partial response based on RECIST criteria (Figure 1). The CBM predicted clinical response with 73% sensitivity and 77% specificity. Cellworks CBM identified novel biomarkers responsible for platinum-based combination therapy response as mentioned below. +Etoposide: 13q-del, RB1-del, MBD1-del, LIG4-del, ERCC5-del, ATP7B-del +Gemcitabine: AKT3-amp, MAPKAP2-amp, TAP1-del +Vinorelbine: TET2-del/LOF, TRIB3-amp, SLX4-del +Paclitaxel: KLF4-del, SNCG-del, RAC1-amp/GOF +Docetaxel: BCL2L1-amp, HMGA1-amp, NSD1-del, SLC22A7-amp, FSIP1-del These genes contributed to drug efficacy by impacting various pathways, including DNA repair, oxidative-stress, methylation machinery, spindle formation, and mitotic-catastrophe. The aberration frequency of these genes was high among the responders within each subgroup and was very low in non-responders. Additionally, a model of clinical outcome versus the linear and quadratic function of efficacy score, drug combination and the interaction of both showed that efficacy score provides predictive information above and beyond the choice of drug combination alone (likelihood ratio chi-sq = 35.56, df=13, p-value = 0.0007). [Formula presented]
Conclusion(s): This pilot study highlights how the Cellworks CBM biosimulation platform can help identify patients for therapy response prediction. By using novel biomarkers, a CBM-informed decision tree can be employed to identify the optimal drug combination for platinum-based therapy. We suggest that this approach be validated prospectively in a larger patient cohort. Keywords: Cancer Therapy Biosimulation, Multi-omics Therapy Biosimulation, Personalized Cancer Therapy
Copyright
EMBASE:2015170096
ISSN: 1556-1380
CID: 5179542

Association between overcrowded households, multigenerational households, and COVID-19: a cohort study

Ghosh, A K; Venkatraman, S; Soroka, O; Reshetnyak, E; Rajan, M; An, A; Chae, J K; Gonzalez, C; Prince, J; DiMaggio, C; Ibrahim, S; Safford, M M; Hupert, N
OBJECTIVES/OBJECTIVE:The role of overcrowded and multigenerational households as a risk factor for COVID-19 remains unmeasured. The objective of this study is to examine and quantify the association between overcrowded and multigenerational households and COVID-19 in New York City (NYC). STUDY DESIGN/METHODS:Cohort study. METHODS:We conducted a Bayesian ecological time series analysis at the ZIP Code Tabulation Area (ZCTA) level in NYC to assess whether ZCTAs with higher proportions of overcrowded (defined as the proportion of the estimated number of housing units with more than one occupant per room) and multigenerational households (defined as the estimated percentage of residences occupied by a grandparent and a grandchild less than 18 years of age) were independently associated with higher suspected COVID-19 case rates (from NYC Department of Health Syndromic Surveillance data for March 1 to 30, 2020). Our main measure was an adjusted incidence rate ratio (IRR) of suspected COVID-19 cases per 10,000 population. Our final model controlled for ZCTA-level sociodemographic factors (median income, poverty status, White race, essential workers), the prevalence of clinical conditions related to COVID-19 severity (obesity, hypertension, coronary heart disease, diabetes, asthma, smoking status, and chronic obstructive pulmonary disease), and spatial clustering. RESULTS: = 0.99, 95% CI: 0.99-1.00). CONCLUSIONS:Overcrowdedness and multigenerational housing are independent risk factors for suspected COVID-19. In the early phase of the surge in COVID cases, social distancing measures that increase house-bound populations may inadvertently but temporarily increase SARS-CoV-2 transmission risk and COVID-19 disease in these populations.
PMID: 34492508
ISSN: 1476-5616
CID: 5011952

Pharmacologic modulation of RNA splicing enhances anti-tumor immunity

Lu, Sydney X; De Neef, Emma; Thomas, James D; Sabio, Erich; Rousseau, Benoit; Gigoux, Mathieu; Knorr, David A; Greenbaum, Benjamin; Elhanati, Yuval; Hogg, Simon J; Chow, Andrew; Ghosh, Arnab; Xie, Abigail; Zamarin, Dmitriy; Cui, Daniel; Erickson, Caroline; Singer, Michael; Cho, Hana; Wang, Eric; Lu, Bin; Durham, Benjamin H; Shah, Harshal; Chowell, Diego; Gabel, Austin M; Shen, Yudao; Liu, Jing; Jin, Jian; Rhodes, Matthew C; Taylor, Richard E; Molina, Henrik; Wolchok, Jedd D; Merghoub, Taha; Diaz, Luis A; Abdel-Wahab, Omar; Bradley, Robert K
Although mutations in DNA are the best-studied source of neoantigens that determine response to immune checkpoint blockade, alterations in RNA splicing within cancer cells could similarly result in neoepitope production. However, the endogenous antigenicity and clinical potential of such splicing-derived epitopes have not been tested. Here, we demonstrate that pharmacologic modulation of splicing via specific drug classes generates bona fide neoantigens and elicits anti-tumor immunity, augmenting checkpoint immunotherapy. Splicing modulation inhibited tumor growth and enhanced checkpoint blockade in a manner dependent on host T cells and peptides presented on tumor MHC class I. Splicing modulation induced stereotyped splicing changes across tumor types, altering the MHC I-bound immunopeptidome to yield splicing-derived neoepitopes that trigger an anti-tumor T cell response in vivo. These data definitively identify splicing modulation as an untapped source of immunogenic peptides and provide a means to enhance response to checkpoint blockade that is readily translatable to the clinic.
PMID: 34171309
ISSN: 1097-4172
CID: 4925812

CTLA-4 blockade drives loss of Treg stability in glycolysis-low tumours

Zappasodi, Roberta; Serganova, Inna; Cohen, Ivan J; Maeda, Masatomo; Shindo, Masahiro; Senbabaoglu, Yasin; Watson, McLane J; Leftin, Avigdor; Maniyar, Rachana; Verma, Svena; Lubin, Matthew; Ko, Myat; Mane, Mayuresh M; Zhong, Hong; Liu, Cailian; Ghosh, Arnab; Abu-Akeel, Mohsen; Ackerstaff, Ellen; Koutcher, Jason A; Ho, Ping-Chih; Delgoffe, Greg M; Blasberg, Ronald; Wolchok, Jedd D; Merghoub, Taha
Limiting the metabolic competition in the tumor microenvironment (TME) may increase the effectiveness of immunotherapy. Because of its critical role in glucose metabolism of activated T cells, CD28 signaling has been proposed as a T-cell metabolic biosensor1. Conversely, CTLA-4 engagement has been shown to down-regulate T-cell glycolysis1. Here, we investigated the impact of CTLA-4 blockade on the metabolic fitness of intra-tumor T cells in relationship to the tumor glycolytic capacity. We found that CTLA-4 blockade promotes immune cell infiltration and metabolic fitness especially in glycolysis-low tumors. Accordingly, anti-CTLA-4 achieved better therapeutic outcomes in mice bearing glycolysis-defective tumors. Intriguingly, tumor-specific CD8+ T-cell responses correlated with phenotypic and functional destabilization of tumor-infiltrating regulatory T cells (Tregs) toward IFN-γ- and TNF-α-producing cells in glycolysis-defective tumors. By mimicking the highly and poorly glycolytic TME in vitro, we show that the effect of CTLA-4 blockade to promote Treg destabilization is dependent on Treg glycolysis and CD28 signaling. These findings indicate that decreasing tumor competition for glucose may facilitate the therapeutic activity of CTLA-4 blockade, thus supporting its combination with inhibitors of tumor glycolysis. Moreover, these results reveal a new mechanism through which anti-CTLA-4 interferes with Treg function in the presence of glucose.
PMID: 33588426
ISSN: 1476-4687
CID: 4786562

Protein PEGylation for cancer therapy: bench to bedside

Gupta, Vijayalaxmi; Bhavanasi, Sneha; Quadir, Mohiuddin; Singh, Kevin; Ghosh, Gaurav; Vasamreddy, Kritin; Ghosh, Arnab; Siahaan, Teruna J; Banerjee, Snigdha; Banerjee, Sushanta K
PEGylation is a biochemical modification process of bioactive molecules with polyethylene glycol (PEG), which lends several desirable properties to proteins/peptides, antibodies, and vesicles considered to be used for therapy or genetic modification of cells. However, PEGylation of proteins is a complex process and can be carried out using more than one strategy that depends on the nature of the protein and the desired application. Proteins of interest are covalently conjugated or non-covalently complexed with inert PEG strings. Purification of PEGylated protein is another critical step, which is mainly carried out based on electrostatic interactions or molecular sizes using chromatography. Several PEGylated drugs are being used for diseases like anemia, kidney disease, multiple sclerosis, hemophilia and cancers. With the advancement and increased specificity of the PEGylation process, the world of drug therapy, and specifically cancer therapy could benefit by utilizing this technique to create more stable and non-immunogenic therapies. In this article we describe the structure and functions of PEGylation and how this chemistry helps in drug discovery. Moreover, special emphasis has been given to CCN-family proteins that can be targeted or used as therapy to prevent or block cancer progression through PEGylation technology.
PMID: 30499020
ISSN: 1873-9601
CID: 3984112

PRION DISEASE: AN UNEXPECTED DIAGOSIS IN A PATIENT PRESENTING WITH DKA [Meeting Abstract]

Ebrahim, John L; Sowa, Alexandra; Ghosh, Arnab K; Uppal, Amit
ISI:000392201602384
ISSN: 1525-1497
CID: 2490492

A CASE OF DAPSONE-INDUCED HYPERSENSITIVITY PNEUMONITIS IN A PATIENT BEING TREATED FOR LEPROSY AT BELLEVUE HOSPITAL [Meeting Abstract]

Ghosh, Arnab K; Bond, Rachel M; Greene, Richard E
ISI:000340996201252
ISSN: 1525-1497
CID: 2490482