Biology subjects

Chandarlapaty, S.

Publications and source records attributed to Chandarlapaty, S..

11 recordsLinked to original sources

bioRxiv2026

Microfluidic Tissue Array Platform for Personalized Drug Screening Using Tumor Explants or Biopsies

Despite major improvements in molecular characterization of breast cancer, current biomarkers still fall short in accurate treatment prediction. Interrogating tumor tissue ex-vivo in its native conformation is a direct strategy for guiding treatment of individual patients but presents a challenge. In this study, we developed a microfluidic tissue array (FTA) using small biopsy samples (< 1mm3) mimicking physiological flow for consistent exchange of nutrients and waste, retaining the tumor native stroma. Cell/patient-derived breast cancer xenograft tissues were maintained over 2 weeks in the array and their response to therapeutic agents, doxorubicin or neratinib, were interrogated. Drug response in the uFTA showed >2-fold reduction in tumor cell viability which corroborated tumor size shrinkage in mice bearing the same tumor load. EdU/Ki67 assays indicated selective retention of cells with higher proliferative capacity after drug treatment, underscoring in vivo clinical relevance . We have also developed a valved-FTA to increase throughput and variety of treatment conditions on the same chip. Together, this FTA can be staged as a powerful, low-cost benchtop theranostic tool for personalized cancer therapeutics compatible with FDAs New Approach Methods.

cancer biology↗

bioRxiv2025

A functional map of CDK-drug interactions at single amino acid resolution

Proteins that drive or support human disease phenotypes are attractive molecular targets for precision therapy, yet most are nominated by knockout studies and then targeted with drugs that inhibit core catalytic pockets. These strategies cannot resolve which residues are essential, whether non-catalytic sites offer better selectivity or potency, or identify on-target resistance mechanisms. We introduce a framework that integrates precision genome editing, mechanistically diverse therapeutics, and computational sequence-structure-function analysis to map protein essentiality and potential druggability at single amino acid resolution. Applying this framework across 9 cyclin-dependent kinases (CDKs) and 15 cancer therapeutics--including ATP-competitive inhibitors, PROTACs, and molecular glue degraders--we identify shared and CDK-specific residues critical for cell fitness and drug response, including known resistance mutations and dozens of new variants. The resulting functional maps resolve residue- and mechanism-specific differences in the resistance spectra among agents targeting the same protein. We show that this iterative strategy can also uncover higher order interactions by performing intra- and extragenic epistasis screens to identify residues that mediate on-target and within-family cell fitness and drug resistance. Finally, we find evidence of novel CDK6 mutations in breast cancer patients and concordance between experimental and clinical correlates of response to CDK4/6 inhibitors. By mapping residue-level essentiality and forecasting therapy resistance mutations, target-drug interaction maps could inform clinical treatment and guide design of more selective therapeutic molecules.

cancer biology↗

bioRxiv2024

eIF4A controls translation of estrogen receptor alpha and is a therapeutic target in advanced breast cancer

The majority of human breast cancers are dependent on hormone-stimulated estrogen receptor alpha (ER) and are sensitive to its inhibition. Treatment resistance arises in most advanced cancers due to genetic alterations that promote ligand independent activation of ER itself or ER target genes. Whereas re-targeting of the ER ligand binding domain (LBD) with newer ER antagonists can work in some cases, these drugs are largely ineffective in many genetic backgrounds including ER fusions that lose the LBD or in cancers that hyperactivate ER targets. By identifying the mechanism of ER translation, we herein present an alternative strategy to target ER and difficult to treat ER variants. We find that ER translation is cap-independent and mTOR inhibitor insensitive, but dependent on 5 UTR elements and sensitive to pharmacologic inhibition of the translation initiation factor eIF4A, an mRNA helicase. EIF4A inhibition rapidly reduces expression of ER and short-lived targets of ER such as cyclin D1 and other components of the cyclin D-CDK complex in breast cancer cells. These effects translate into suppression of growth of a variety of ligand-independent breast cancer models including those driven by ER fusion proteins that lack the ligand binding site. The efficacy of eIF4A inhibition is enhanced when it is combined with fulvestrant--an ER degrader. Concomitant inhibition of ER synthesis and induction of its degradation causes synergistic and durable inhibition of ER expression and tumor growth. The clinical importance of these findings is confirmed by results of an early clinical trial (NCT04092673) of the selective eIF4A inhibitor zotatifin in patients with estrogen receptor positive metastatic breast cancer. Multiple clinical responses have been observed on combination therapy including durable regressions. These data suggest that eIF4A inhibition could be a useful new strategy for treating advanced ER+ breast cancer.

cancer biology↗

bioRxiv2024

APOBEC3 mutagenesis drives therapy resistance in breast cancer

Acquired genetic alterations commonly drive resistance to endocrine and targeted therapies in metastatic breast cancer1-7, however the underlying processes engendering these diverse alterations are largely uncharacterized. To identify the mutational processes operant in breast cancer and their impact on clinical outcomes, we utilized a well-annotated cohort of 3,880 patient samples with paired tumor-normal sequencing data. The mutational signatures associated with apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) enzymes were highly prevalent and enriched in post-treatment compared to treatment-naive hormone receptor-positive (HR+) cancers. APOBEC3 mutational signatures were independently associated with shorter progression-free survival on antiestrogen plus CDK4/6 inhibitor combination therapy in patients with HR+ metastatic breast cancer. Whole genome sequencing (WGS) of breast cancer models and selected paired primary-metastatic samples demonstrated that active APOBEC3 mutagenesis promoted resistance to both endocrine and targeted therapies through characteristic alterations such as RB1 loss-of-function mutations. Evidence of APOBEC3 activity in pre-treatment samples illustrated a pervasive role for this mutational process in breast cancer evolution. The study reveals APOBEC3 mutagenesis to be a frequent mediator of therapy resistance in breast cancer and highlights its potential as a biomarker and target for overcoming resistance.

cancer biology↗

bioRxiv2024

Multimodal histopathologic models stratify hormone receptor-positive early breast cancer

For patients with hormone receptor-positive, early breast cancer without HER2 amplification, multigene expression assays including Oncotype DX (R) recurrence score (RS) have been clinically validated to identify patients who stand to derive added benefit from adjuvant cytotoxic chemotherapy. However, cost and turnaround time have limited its global adoption despite recommendation by practice guidelines. We investigated if routinely available hematoxylin and eosin (H&E)-stained pathology slides could act as a surrogate triaging data substrate by predicting RS using machine learning methods. We trained and validated a multimodal transformer model, Orpheus, using 6,203 patients across three independent cohorts, taking both H&E images and their corresponding synoptic text reports as input. We showed accurate inference of recurrence score from whole-slide images (r = 0.63 (95% C.I. 0.58 - 0.68); n = 1,029), the raw text of their corresponding reports (r = 0.58 (95% C.I. 0.51 - 0.64); n = 972), and their combination (r = 0.68 (95% C.I. 0.64 - 0.73); n = 964) as measured by Pearsons correlation. To predict high-risk disease (RS>25), our model achieved an area under the receiver operating characteristic curve (AUROC) of 0.89 (95% C.I. 0.83 - 0.94), and area under the precision recall curve (AUPRC) of 0.64 (95% C.I. 0.60 - 0.82), compared to 0.49 (95% C.I. 0.36 - 0.64) for an existing nomogram based on clinical and pathologic features. Moreover, our model generalizes well to external international cohorts, effectively identifying recurrence risk (r = 0.61, p < 10-4, n = 452; r = 0.60, p < 10-4, n = 575) and high-risk status (AUROC = 0.80, p < 10-4, AUPRC = 0.68, p < 10-4, n = 452; AUROC = 0.83, p < 10-4, AUPRC = 0.73, p < 10-4, n = 575) from whole-slide images. Probing the biologic underpinnings of the model decisions uncovered tumor cell size heterogeneity, immune cell infiltration, a proliferative transcription program, and stromal fraction as correlates of higher-risk predictions. We conclude that at an operating point of 94.4% precision and 33.3% recall, this model could help increase global adoption and shorten lag between resection and adjuvant therapy.

pathology↗

bioRxiv2024

Homologous recombination deficiency and tumor suppressor heterozygosity mediate resistance to front-line therapy in breast cancer

The co-occurrence of germline and somatic oncogenic alterations is frequently observed in breast cancer, but their combined biologic and clinical significance has not been evaluated. To assess the role of germline-somatic interactions on outcomes in routine practice, we developed an integrated clinicogenomic pipeline to analyze the genomes of over 4,500 patients with breast cancer. We find that germline (g)BRCA2-associated tumors are enriched for RB1 loss-of-function mutations and manifest poor outcomes on standard-of-care, front-line CDK4/6 inhibitor (CDK4/6i) combinations. Amongst these tumors, gBRCA2-related homologous recombination deficiency (HRD) as well as baseline RB1 LOH status promote acquisition of RB1 loss-of- function mutations under the selective pressure of CDK4/6i, causing therapy resistance. These findings suggest an alternative therapeutic strategy using sequential targeting of HRD in gBRCA- associated breast cancers through PARP inhibitors prior to CDK4/6i therapy to intercept deleterious RB1-loss trajectories and thus suppress the emergence of CDK4/6 inhibitor resistance. More broadly, our findings demonstrate how germline-somatic driven genomic configurations shape response to systemic therapy and can be exploited therapeutically as part of biomarker-directed clinical strategies.

genomics↗

bioRxiv2023

Long-term breast cancer response to CDK4/6 inhibition defined by TP53-mediated geroconversion

Inhibition of CDK4/6 kinases has led to improved outcomes in breast cancer. Nevertheless, only a minority of patients experience long-term disease control. Using a clinically-annotated cohort of patients with metastatic HR+ breast cancer, we identified TP53 loss (28.8%) and MDM2 amplification (6.7%) to be associated with lack of long-term disease control. Human breast cancer models revealed that p53 loss did not affect CDK4/6 activity or G1-blockade, but instead promoted drug-insensitive p130 phosphorylation by CDK2. Persistence of phospho-p130 prevented DREAM complex assembly, enabling cell cycle reentry and tumor progression. Inhibitors of CDK2 could overcome p53 loss, leading to geroconversion and manifestation of senescence phenotypes. Complete inhibition of both CDK4/6 and CDK2 kinases appears to be necessary to facilitate long-term response across genomically-diverse HR+ breast cancers.

cancer biology↗

bioRxiv2021

ERα-LBD, a novel isoform of estrogen receptor alpha, promotes breast cancer proliferation and endocrine resistance

Estrogen receptor alpha (ER) drives mammary gland development and breast cancer (BC) growth through an evolutionarily conserved linkage of DNA binding and hormone activation functions. Therapeutic targeting of the hormone binding pocket is a widely utilized and successful strategy for breast cancer prevention and treatment. However, resistance to this endocrine therapy is frequently encountered and may occur through bypass or reactivation of ER-regulated transcriptional programs. We now identify the induction of a novel ER isoform, ER-LBD, that is encoded by an alternative ESR1 transcript and lacks the activation function and DNA binding domains. Despite lacking the transcriptional activity, ER-LBD is found to promote breast cancer growth and resistance to the ER antagonist fulvestrant. ER-LBD is predominantly localized to the cytoplasm and mitochondria of BC cells and leads to enhanced glycolysis, respiration and stem-like features. Intriguingly, ER-LBD expression and function does not appear to be restricted to cancers that express full length ER but also promotes growth of triple negative breast cancers and ER-LBD transcript (ESR1-LBD) is also present in BC samples from both ER(+) and ER(-) human tumors. These findings point to ER-LBD as a potential mediator of breast cancer progression and therapy resistance. SIGNIFICANCE STATEMENTEndocrine resistant and metastatic breast cancer (BC) is a clinically significant problem. Our study of fulvestrant resistant cancer cells led to the discovery of a novel ER isoform which we call ER-LBD. Encoded by a truncated transcript variant (ESR1-LBD) and lacking the N-terminal domains (activation of transcription and DNA binding), ER-LBD displays a unique role in BC tumorigenesis and progression by mechanisms that may involve metabolic and cell growth advantages, stemness and therapy resistance. Importantly, ESR1-LBD is preferentially expressed in human breast tumor tissues and may be used as prognostic marker in BC.

cancer biology↗

bioRxiv2021

Genomic characterization of metastatic patterns from prospective clinical sequencing of 25,000 patients

Progression to metastatic disease remains the main cause of cancer death. Yet, the underlying genomic mechanisms driving metastasis remain largely unknown. Here, we present MSK-MET, an integrated pan-cancer cohort of tumor genomic and clinical outcome data from more than 25,000 patients. We analyzed this dataset to identify associations between tumor genomic alterations and patterns of metastatic dissemination across 50 tumor types. We found that chromosomal instability is strongly correlated with metastatic burden in some tumor types, including prostate adenocarcinoma, lung adenocarcinoma and HR-positive breast ductal carcinoma, but not in others, such as colorectal adenocarcinoma, pancreatic adenocarcinoma and high-grade serous ovarian cancer. We also identified specific somatic alterations associated with increased metastatic burden and specific routes of metastatic spread. Our data offer a unique resource for the investigation of the biological basis for metastatic spread and highlight the crucial role of chromosomal instability in cancer progression.

cancer biology↗

bioRxiv2019

Personalized Cancer Therapy Prioritization Based on Driver Alteration Co-occurrence Patterns

Identification of actionable genomic vulnerabilities is the cornerstone of precision oncology. Based on a large-scale drug screening in patient derived-xenografts, we uncover connections between driver gene alterations, derive Driver Co-Occurrence (DCO) networks, and relate these to drug sensitivity. Our collection of 53 drug response predictors attained an average balanced accuracy of 58% in a cross-validation setting, which rose to a 66% for the subset of high-confidence predictions. Morevover, we experimentally validated 12 out of 14 de novo predictions in mice. Finally, we adapted our strategy to obtain drug-response models from patients progression free survival data. By revealing unexpected links between oncogenic alterations, our strategy can increase the clinical impact of genomic profiling.

cancer biology↗

bioRxiv2018

The SERM/SERD Bazedoxifene Disrupts ESR1 Helix 12 to Overcome Acquired Hormone Resistance in Breast Cancer Cells

Acquired resistance to endocrine therapy remains a significant clinical burden for breast cancer patients. Somatic mutations in the ESR1 (estrogen receptor alpha (ER) gene ligand-binding domain (LBD) represent a recognized mechanism of acquired resistance. Antiestrogens with improved efficacy versus tamoxifen might overcome the resistant phenotype in ER+ breast cancers. Bazedoxifene (BZA) is a potent antiestrogen that is clinically approved for use in hormone replacement therapies. We find BZA possesses improved inhibitory potency against the Y537S and D538G ER mutants compared to tamoxifen and has additional inhibitory activity in combination with the CDK4/6 inhibitor palbociclib. In addition, comprehensive biophysical and structural biology studies show that BZAs selective estrogen receptor degrading (SERD) properties that override the stabilizing effects of the Y537S and D538G ER mutations.\n\nSignificanceBazedoxifene (BZA) is a potent orally available antiestrogen that is clinically approved for use in hormone replacement therapy (DUAVEE). We explore the efficacy of BZA to inhibit activating somatic mutants of ER that can arise in metastatic breast cancers after prolonged exposure to aromatase inhibitors or tamoxifen therapy. Breast cancer cell line, biophysical, and structural data show that BZA disrupts helix 12 of the ER ligand binding domain to achieve improved potency against Y537S and D538G somatic mutants compared to 4-hydroxytamoxifen.

cancer biology↗