Bina Desai

Dr. Bina Desai

orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 May 2020 in Nature Communications
Verified
Journal Article
Open access
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RVRobert Vander Velde
Robert Vander Velde
NYNara Yoon
Nara Yoon
VMViktoriya Marusyk
Viktoriya Marusyk
ADArda Durmaz
Arda Durmaz
ADAndrew Dhawan
Andrew Dhawan
AMAndriy Marusyk
Andriy Marusyk
Despite high initial efficacy, targeted therapies eventually fail in advanced cancers, as tumors develop resistance and relapse. In contrast to the substantial body of research on the molecular mechanisms of resistance, understanding of how resistance evolves remains limited. Using an experimental model of ALK positive NSCLC, we explored the evolution of resistance to different clinical ALK inhibitors. We found that resistance can originate from heterogeneous, weakly resistant subpopulations with variable sensitivity to different ALK inhibitors. Instead of the commonly assumed stochastic single hit (epi) mutational transition, or drug-induced reprogramming, we found evidence for a hybrid scenario involving the gradual, multifactorial adaptation to the inhibitors through acquisition of multiple cooperating genetic and epigenetic adaptive changes. Additionally, we found that during this adaptation tumor cells might present unique, temporally restricted collateral sensitivities, absent in therapy naïve or fully resistant cells, suggesting the potential for new therapeutic interventions, directed against evolving resistance.

16 August 2022 in Science Signaling
Verified
Journal Article
Closed access
LRLily L. Remsing Rix
Lily L. Remsing Rix
NSNatalia J. Sumi
Natalia J. Sumi
QHQianqian Hu
Qianqian Hu
BDBina Desai
Bina Desai
ABAnnamarie T. Bryant
Annamarie T. Bryant
URUwe Rix
Uwe Rix
Cancer-associated fibroblasts (CAFs) in the tumor microenvironment are often linked to drug resistance. Here, we found that coculture with CAFs or culture in CAF-conditioned medium unexpectedly induced drug sensitivity in certain lung cancer cell lines. Gene expression and secretome analyses of CAFs and normal lung–associated fibroblasts (NAFs) revealed differential abundance of insulin-like growth factors (IGFs) and IGF-binding proteins (IGFBPs), which promoted or inhibited, respectively, signaling by the receptor IGF1R and the kinase FAK. Similar drug sensitization was seen in gefitinib-resistant, EGFR -mutant PC9GR lung cancer cells treated with recombinant IGFBPs. Conversely, drug sensitivity was decreased by recombinant IGFs or conditioned medium from CAFs in which IGFBP5 or IGFBP6 was silenced. Phosphoproteomics and receptor tyrosine kinase (RTK) array analyses indicated that exposure of PC9GR cells to CAF-conditioned medium also inhibited compensatory IGF1R and FAK signaling induced by the EGFR inhibitor osimertinib. Combined small-molecule inhibition of IGF1R and FAK phenocopied the CAF-mediated effects in culture and increased the antitumor effect of osimertinib in mice. Cells that were osimertinib resistant and had MET amplification or showed epithelial-to-mesenchymal transition also displayed residual sensitivity to IGFBPs. Thus, CAFs promote or reduce drug resistance in a context-dependent manner, and deciphering the relationship between the differential content of CAF secretomes and the signaling dependencies of the tumor may reveal effective combination treatment strategies.

1 October 2019 in Cell Reports
Verified
Journal Article
Open access
PWPaulina M. Wojnarowicz
Paulina M. Wojnarowicz
RSRaquel Lima e Silva
Raquel Lima e Silva
MOMasayuki Ohnaka
Masayuki Ohnaka
SLSang Bae Lee
Sang Bae Lee
YCYvette Chin
Yvette Chin
RBRobert Benezra
Robert Benezra
Id helix-loop-helix (HLH) proteins (Id1-4) bind E protein bHLH transcription factors, preventing them from forming active transcription complexes that drive changes in cell states. Id proteins are primarily expressed during development to inhibit differentiation, but they become re-expressed in adult tissues in diseases of the vasculature and cancer. We show that the genetic loss of Id1/Id3 reduces ocular neovascularization in mouse models of wet age-related macular degeneration (AMD) and retinopathy of prematurity (ROP). An in silico screen identifies AGX51, a small-molecule Id antagonist. AGX51 inhibits the Id1-E47 interaction, leading to ubiquitin-mediated degradation of Ids, cell growth arrest, and reduced viability. AGX51 is well-tolerated in mice and phenocopies the genetic loss of Id expression in AMD and ROP models by inhibiting retinal neovascularization. Thus, AGX51 is a first-in-class compound that antagonizes an interaction formerly considered undruggable and that may have utility in the management of multiple diseases.

24 May 2021 in npj Breast Cancer
Verified
Journal Article
Open access
PDF file
PWPaulina M. Wojnarowicz
Paulina M. Wojnarowicz
MEMarta Garcia Escolano
Marta Garcia Escolano
YHYun-Han Huang
Yun-Han Huang
BDBina Desai
Bina Desai
YCYvette Chin
Yvette Chin
RBRobert Benezra
Robert Benezra
ID proteins are helix-loop-helix (HLH) transcriptional regulators frequently overexpressed in cancer. ID proteins inhibit basic-HLH transcription factors often blocking differentiation and sustaining proliferation. A small-molecule, AGX51, targets ID proteins for degradation and impairs ocular neovascularization in mouse models. Here we show that AGX51 treatment of cancer cell lines impairs cell growth and viability that results from an increase in reactive oxygen species (ROS) production upon ID degradation. In mouse models, AGX51 treatment suppresses breast cancer colonization in the lung, regresses the growth of paclitaxel-resistant breast tumors when combined with paclitaxel and reduces tumor burden in sporadic colorectal neoplasia. Furthermore, in cells and mice, we fail to observe acquired resistance to AGX51 likely the result of the inability to mutate the binding pocket without loss of ID function and efficient degradation of the ID proteins. Thus, AGX51 is a first-in-class compound that antagonizes ID proteins, shows strong anti-tumor effects and may be further developed for the management of multiple cancers.

9 May 2017 in Macromolecular Bioscience
Verified
Journal Article
Closed access
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TDTanmay Dichwalkar
Tanmay Dichwalkar
SPShraddha Patel
Shraddha Patel
SBSamhita Bapat
Samhita Bapat
PPPriya Pancholi
Priya Pancholi
NJNeel Jasani
Neel Jasani
VSVikas Sehdev
Vikas Sehdev

9 October 2020 in bioRxiv
Verified
Preprint
Open access
PDF file
Jeffrey WestJeffrey West
Jeffrey West
BDBina Desai
Bina Desai
MSMaximilian Strobl
Maximilian Strobl
LPLuke Pierik
Luke Pierik
RVRobert Vander Velde
Robert Vander Velde
Alexander AndersonAlexander Anderson
Alexander Anderson
Antifragility is a recently coined word used to describe the opposite of fragility. Systems or organisms can be described as antifragile if they derive a benefit from systemic variability, volatility, randomness, or disorder. Herein, we introduce a mathematical framework to quantify the fragility or antifragility of cancer cell lines in response to treatment variability. This framework enables straightforward prediction of the optimal dose treatment schedule for a range of treatment schedules with identical cumulative dose. We apply this framework to non-small-cell lung cancer cell lines with evolved resistance to ten anti-cancer drugs. We show the utility of this antifragile framework when applied to 1) treatment resistance, and 2) collateral sensitivity of sequential monotherapies.