Biology subjects

Gupta, G. P.

Publications and source records attributed to Gupta, G. P..

11 recordsLinked to original sources

bioRxiv2025

Hierarchical Coordination of Polymerase Theta and RAD51 Resolves Clustered Replication Fork Collapse

The essential role of polymerase theta (Pol{theta})-mediated end joining (TMEJ), an alternative double strand break repair pathway, has been primarily studied in homologous recombination (HR)-deficient contexts(1, 2). Here, we uncover an indispensable role for TMEJ in HR-proficient mammalian cells during the repair of interstrand crosslinks (ICLs). We show that Pol{theta} is recruited downstream of canonical ICL repair steps--including ICL unhooking, RAD51 loading, and RAD51 ubiquitylation--and localizes to sites of unresolved HR through interactions with ubiquitylated RAD51 filaments. Using genomic scar profiling and targeted ICL repair assays, we find that TMEJ resolves a minor subset of lesions that are not amenable to HR repair, such as clustered ICLs that can induce two-ended replication fork collapse. These findings reveal a RAD51 ubiquitylation-dependent mechanism for Pol{theta} recruitment and establish TMEJ as a hierarchically deployed DNA repair pathway that safeguards genome stability when HR is insufficient to resolve replication-associated DNA damage. Short SummaryPol{theta} is recruited via RAD51 ubiquitylation to resolve clustered ICLs that generate HR-refractory replication fork collapse.

cell biology↗

bioRxiv2024

DNA polymerase theta-mediated DNA repair is a functional dependency and therapeutic vulnerability in DNMT3A deficient leukemia cells

Myeloid malignancies carrying somatic DNMT3A mutations (DNMT3Amut) may be refractory to standard therapy. DNMT3Amut leukemia cells accumulate toxic DNA double strand breaks (DSBs) and stalled replication forks, rendering them dependent on DNA damage response (DDR). We report here that DNA polymerase theta (Pol{theta}), a key element in DSB repair by end-joining (TMEJ) and in fork restarting, is essential for survival and proliferation of DNMT3Amut leukemia cells. Pol{theta} is overexpressed in DNMT3Amut leukemia cells due to abrogation of PARP1 PARylation-dependent UBE2O E3 ligase-mediated ubiquitination and proteasomal degradation of Pol{theta}. In addition, PARP1-mediated recruitment of the SMARCAD1-MSH2/MSH3 repressive complex to DSBs was diminished in DNMT3Amut leukemia cells which facilitated loading of Pol{theta} on DNA damage and promoting TMEJ and replication fork restart. Pol{theta} inhibitors enhanced the anti-leukemic effects of standard drugs such as FLT3 kinase inhibitor quizartinib, cytarabine +/- doxorubicin, and etoposide in vitro and in mice with DNMT3Amut leukemia. Altogether, Pol{theta} is an attractive target in DNMT3Amut hematological malignancies.

cancer biology↗

bioRxiv2024

Investigating spatial dynamics in spatial omics data with StarTrail

Spatial omics technologies revolutionize our view of biological processes within tissues. However, existing methods fail to capture localized, sharp changes characteristic of critical events (e.g. tumor development). Here, we present StarTrail, a novel gradient based method that powerfully defines rapidly changing regions and detects "cliff genes", genes exhibiting drastic expression changes at highly localized or disjoint boundaries. StarTrail, the first to leverage spatial gradients for spatial omics data, also quantifies directional dynamics. Across multiple datasets, StarTrail accurately delineates boundaries (e.g., brain layers, tumor-immune boundaries), and detects cliff genes that may regulate molecular crosstalk at these biologically relevant boundaries but are missed by existing methods. For instance, StarTrail precisely pinpointed the cancer-immune interface in a HER2+ breast cancer dataset, unveiled key cliff genes including a potential prognostic biomarker IGSF3, highlighting NK-, B-cell mediated immunity, and B cell receptor signaling pathways missed by all spatial variable gene methods attempted. StarTrail, filling important gaps in current literature, enables deeper insights into tissue spatial architecture.

genetics↗

bioRxiv2024

Single RNA molecule resolution spatial imaging of immunotherapy response in triple negative breast tumors harboring tertiary lymphoid structures

Cancer immunotherapy trials have had variable success, prompting a search for biomarkers of response. Tertiary lymphoid structures (TLS) have emerged as prognostic for multiple tumor types. These ectopic immunological bodies resemble secondary lymphoid organs with segregated B and T cell zones, but they are heterogeneous in their organization and cellular composition. These features have consequences in terms of prognostication and disease clearance, so there is interest in what drives TLS heterogeneity and corresponding immunological responses. We applied single RNA molecule resolution imaging to study biopsies from triple negative breast tumors harboring TLS where the biopsies were taken longitudinally, prior to therapy, after pembrolizumab and after pembrolizumab with radiation therapy. We developed a computational framework to identify TLS and tumor beds and to align spatial trajectories between the immune and malignant structures for systematic analyses. We identified two tumor types based on immune infiltration profiles in the tumor bed. Immune "infiltrated" tumors were eliminated after pembrolizumab, while "non-infiltrated" tumors saw gains in effector T cells and myeloid cells after pembrolizumab and were cleared after pembrolizumab with RT. TLS from infiltrated tumors had better separation of B and T cell zones and had higher expression of immunoreactivity gene pathways in most cell types. Further, malignant cell MHC expression was higher in the tumor beds of infiltrated tumors, providing one plausible mechanism for the groupings. In non-infiltrated tumors, classical dendritic cells enter the tumor bed from TLS proximal zones after pembrolizumab and bring transcription of the CXCL9 chemokine, which can recruit T cells and promote T cell effector phenotypes and was higher in infiltrated tumors at baseline.

genomics↗

bioRxiv2022

Cell composition inference and identification of layer-specific spatial transcriptional profiles with POLARIS

Spatial transcriptomics (ST) technology, providing spatially resolved transcriptional profiles, facilitates advanced understanding of key biological processes related to health and disease. Sequencing-based ST technologies provide whole-transcriptome profiles, but are limited by the non-single cell level resolution. Lack of knowledge in the number of cells or cell type composition at each spot can lead to invalid downstream analysis, which is a critical issue recognized in ST data analysis. Methods developed, however, tend to under-utilize histological images, which conceptually provide important and complementary information including anatomical structure and distribution of cells. To fill in the gaps, we present POLARIS, a versatile ST analysis method that can perform cell type deconvolution, identify anatomical or functional layer-wise differentially expressed (LDE) genes and enable cell composition inference from histology images. Applied to four tissues, POLARIS demonstrates high deconvolution accuracy, accurately predicts cell composition solely from images, and identifies LDE genes that are biologically relevant and meaningful.

genetics↗

bioRxiv2022

Mre11 liberates cGAS from nucleosome sequestration during tumorigenesis

Oncogene-induced replication stress generates endogenous DNA damage that activates cGAS/STING-mediated innate immune signaling and tumor suppression1-3. However, the mechanism for cGAS activation by endogenous DNA damage remains enigmatic, particularly given the constitutive inhibition of cGAS by high-affinity histone acidic patch (AP) binding4-10. Here we report an in vivo CRISPR screen that identified the DNA double strand break sensor Mre11 as a suppressor of mammary tumorigenesis induced by Myc overexpression and p53 deficiency. Mre11 antagonizes Myc-induced proliferation through cGAS/STING activation. Direct binding of the Mre11-Rad50-Nbn (MRN) complex to nucleosomes displaces cGAS from AP sequestration, which is required for DNA damage-induced cGAS mobilization and activation by cytosolic DNA. Mre11 is thereby essential for cGAS activation in response to oncogenic stress, cytosolic DNA transfection, and ionizing radiation. Furthermore, we show Mre11-dependent cGAS activation suppresses Myc-induced proliferation through ZBP1/RIPK3/MLKL-mediated necroptosis. In human triple-negative breast cancer, ZBP1 downregulation correlates with increased genome instability, decreased immune infiltration, and poor patient prognosis. These findings establish Mre11 as a critical link between DNA damage and cGAS activation that regulates tumorigenesis through ZBP1-dependent necroptosis. One-sentence summaryMre11 is required for cGAS activation during oncogenic stress and promotes ZBP1-dependent necroptosis.

cell biology↗

bioRxiv2022

A comprehensive comparison on cell type composition inference for spatial transcriptomics data

Spatial transcriptomic (ST) technologies allow researchers to examine high-quality RNA-sequencing data along with maintained two-dimensional positional information as well as a co-registered histology image. A popular use of ST omics data is to provide insights about tissue structure and spatially unique features. However, due to the technical nature unique to most ST data, the resolution varies from a diameter of 2-10m to 50-100m instead of single-cell resolution, which brings uncertainty into cell number and cell mixture within each ST spot. Motivated by the important role for spatial arrangement of cell types within a tissue in physiology and disease pathogenesis, several ST deconvolution methods have been developed and are being used to explore gene expression variation and identification of spatial domains. The aim of this work is to review state-of-the-art methods for ST deconvolution, while comparing their strengths and weaknesses. Specifically, we use four real datasets to examine the performance of eight methods across different tissues and technological platforms. Key PointsO_LICell mixture inference is a critical step in the analysis of spatial transcriptomics (ST) data to prevent downstream analysis suffering from confounding factors at the spot level. C_LIO_LIExisting ST deconvolution methods can be classified into three groups: probabilistic-based, non-negative matrix factorization and non-negative least squares based, and other deep learning framework-based methods. C_LIO_LIWe compared eight ST deconvolution methods by using two single cell level resolution datasets and two spot level resolution ST datasets. We provided practical guidelines for the choice of method under different scenarios as well as the optimal subsets of genes to use for each method. C_LI

genetics↗

bioRxiv2020

Targeted DNA Damage Repair CRISPR/Cas9 Knockout Screen Identifies Novel Classification of Poly-ADP Ribose Polymerase Inhibitors Based on Key Base Excision Repair Proteins

DNA repair deficiencies have become an increasingly promising target for novel therapeutics within the realm of clinical oncology. Recently, several inhibitors of Poly(ADP-ribose) Polymerases (PARPs) have received approval for the treatment of cancers primarily with deleterious mutations in the homologous recombination (HR) proteins, BRCA1 and BRCA2. Despite numerous clinical trials which have been completed or are currently ongoing, the mechanism of action by which PARP inhibitors selectively kill tumor cells is poorly understood. While many believe "trapping" of PARP proteins to DNA at sites of damage is the most important determinant driving cytotoxicity by these drugs, clinically effective inhibitors exist with a diverse range of PARP-trapping qualities. These findings suggest that characterization of inhibitors as strong versus weak trappers does not properly capture the intra-class characteristics of these drugs. Here, we use a novel, targeted DNA damage response (DDR) CRISPR/Cas9 screening library to reveal heterogenous genetic dependencies on the base excision repair (BER) pathway for PARP inhibitors, which is not correlated with PARP trapping ability or catalytic inhibition of PARP. These findings demonstrate that inhibition of PARylation and induction of PARP trapping are not the only factors contributing to distinct biological activity for different PARP inhibitors, and they provide insight into the optimal choice of PARP inhibitors for use in the setting of specific DDR defects. AUTHOR SUMMARYTargeted cancer therapies rely on our general understanding of which genetic mutations are involved in both sensitivity and resistance to such anticancer agents. In this study, we describe the use of functional genetic screening to evaluate the role of various DNA repair proteins in response to inhibitors of PARP, a quintessential example of targeted therapy. While PARP inhibitors are best known for their utility in cancers with homologous recombination defects, we show that some inhibitors within this class may have additional functionality in cancers with deficient base excision repair. These findings highlight not only the importance of PARP inhibitor selection in the appropriate context, but also the mechanistic differences that exist within this class of inhibitors. It is our hope that our findings will inspire future work evaluating the use of specific PARP inhibitor selection in designing clinical trials to further expand the use of PARP inhibitors beyond tumors with homologous recombination deficiencies.

cancer biology↗

bioRxiv2020

Hyperactive end joining repair mediates resistance to DNA damaging therapy in p53-deficient cells

TP53 mutations in cancer are associated with poor patient outcomes and resistance to DNA damaging therapies1-3. However, the mechanisms underlying treatment resistance in p53-deficient cells remain poorly characterized. Here, we show that p53-deficient cells exhibit hyperactive repair of therapy-induced DNA double strand breaks (DSBs), which is suppressed by inhibition of DNA-dependent protein kinase (DNA-PK). Single-cell analyses of DSB repair kinetics and cell cycle state transitions reveal an essential role for DNA-PK in suppressing S phase DNA damage and mitotic catastrophe in p53-deficient cells. Yet, a subset of p53-deficient cells exhibit intrinsic resistance to therapeutic DSBs due to a repair pathway that is not sensitive to DNA-PK inhibition. We show that p53 deficiency induces overexpression of DNA Polymerase Theta (Pol {theta}), which mediates an alternative end-joining repair pathway that becomes hyperactivated by DNA-PK inhibition4. Combined inhibition of DNA-PK and Pol {theta} restores therapeutic DNA damage sensitivity in p53-deficient cells. Thus, our study identifies two targetable DSB end joining pathways that can be suppressed as a strategy to overcome resistance to DNA-damaging therapies in p53-deficient cancers.

cell biology↗

bioRxiv2019

Mechanistic Basis for Microhomology Identification and Genome Scarring by Polymerase Theta

DNA Polymerase Theta mediates an end joining pathway (TMEJ) that repairs chromosome breaks. It requires resection of broken ends to generate long, 3 single stranded DNA tails, annealing of complementary sequence segments (microhomologies) in these tails, followed by microhomology-primed synthesis sufficient to resolve broken ends. The means by which microhomologies are identified is thus a critical step in this pathway, but is not understood. Here we show microhomologies are identified by a scanning mechanism initiated from the 3 terminus and favoring bi-directional progression into flanking DNA, typically to a maximum of 15 nucleotides into each flank. Polymerase theta is frequently insufficiently processive to complete repair of breaks in microhomology-poor, AT-rich regions. Aborted synthesis leads to one or more additional rounds of microhomology search, annealing, and synthesis; this promotes complete repair in part because earlier rounds of synthesis generate microhomologies de novo that are sufficiently long that synthesis is more processive. Aborted rounds of synthesis are evident in characteristic genomic scars as insertions of 3-30 bp of sequence that is identical to flanking DNA ("templated" insertions). Templated insertions are present at higher levels in breast cancer genomes from patients with germline BRCA1/2 mutations, consistent with an addiction to TMEJ in these cancers. Our work thus describes the mechanism for microhomology identification, and shows both how it mitigates limitations implicit in the microhomology requirement, and generates distinctive genomic scars associated with pathogenic genome instability.

molecular biology↗

bioRxiv2018

Evidence that the cell cycle is a series of uncoupled, memoryless phases

The cell cycle is canonically described as a series of 4 phases: G1 (gap phase 1), S (DNA synthesis), G2 (gap phase 2), and M (mitosis). Various models have been proposed to describe the durations of each phase, including a two-state model with fixed S-G2-M duration and random G1 duration1,2; a \"stretched\" model in which phase durations are proportional3; and an inheritance model in which sister cells show correlated phase durations2,4. A fundamental challenge is to understand the quantitative laws that govern cell-cycle progression and to reconcile the evidence supporting these different models. Here, we used time-lapse fluorescence microscopy to quantify the durations of G1, S, G2, and M phases for thousands of individual cells from three human cell lines. We found no evidence of correlation between any pair of phase durations. Instead, each phase followed an Erlang distribution with a characteristic rate and number of steps. These observations suggest that each cell cycle phase is memoryless with respect to previous phase durations. We challenged this model by perturbing the durations of specific phases through oncogene activation, inhibition of DNA synthesis, reduced temperature, and DNA damage. Phase durations remained uncoupled in individual cells despite large changes in durations in cell populations. To explain this behavior, we propose a mathematical model in which the independence of cell-cycle phase durations arises from a large number of molecular factors that each exerts a minor influence on the rate of cell-cycle progression. The model predicts that it is possible to force correlations between phases by making large perturbations to a single factor that contributes to more than one phase duration, which we confirmed experimentally by inhibiting cyclin-dependent kinase 2 (CDK2). We further report that phases can show coupling under certain dysfunctional states such as in a transformed cell line with defective cell cycle checkpoints. This quantitative model of cell cycle progression explains the paradoxical observation that phase durations are both inherited and independent and suggests how cell cycle progression may be altered in disease states.

systems biology↗