Biology subjects

Brown, K. R.

Publications and source records attributed to Brown, K. R..

13 recordsLinked to original sources

bioRxiv2025

A global genetic interaction map of a human cell reveals conserved principles of genetic networks

We generated a genome-scale, genetic interaction network from the analysis of more than 4 million double mutants in the haploid human cell line, HAP1. The network maps [~]90,000 genetic interactions, including thousands of extreme synthetic lethal and genetic suppression interactions. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes, pathways, biological processes, and cellular compartments. Comparative analyses showed that general principles of genetic networks are conserved from yeast to human cells. A genetic interaction network mapped in a single genetic background complements the DepMap gene co-essentiality network, recapitulating many of the same biological connections and also capturing unique functional information to reveal roles of uncharacterized genes and molecular determinants of specific cancer cell line genetic dependencies.

systems biology↗

bioRxiv2025

Quantitative analysis of genetic interactions in human cells from genome-wide CRISPR-Cas9 screens

Genetic interaction (GI) networks in model organisms have revealed how combinations of genome variants can impact phenotypes. To advance efforts toward a reference human GI network, we developed the quantitative Genetic Interaction (qGI) score, a method for precise GI measurement from genome-wide CRISPR-Cas9 screens in different query mutants constructed in a single human cell line. We found surprising prevalent systematic variation unrelated to GIs in CRISPR screen data, including both genomically linked effects and functionally coherent covariation. Leveraging [~]40 control screens in wild-type cells and half a billion differential fitness effect measurements, we developed a pipeline for CRISPR screen data processing and normalization to correct these artifacts and measure accurate, quantitative GIs. We also comprehensively characterized GI reproducibility by characterizing 4 - 5 biological replicates for [~]125,000 unique gene pairs. The qGI framework enables systematic identification of human GIs and provides broadly applicable strategies for analyzing context-specific CRISPR screen data.

bioinformatics↗

bioRxiv2025

Integrated genetic screening reveals FEN1 as a driver of stemness and temozolomide resistance in glioblastoma

Glioblastoma (GBM) is a lethal brain tumor with limited response to standard of care chemoradiotherapy. In this study, we conducted genome-wide CRISPR knockout screening in patient-derived glioblastoma stem cells (GSCs) to identify genetic dependencies of cell survival and therapy resistance. Our screening identified flap endonuclease 1 (FEN1) as a key driver of GSC survival, with enhanced dependency under temozolomide (TMZ) treatment. Genetic perturbation of FEN1 reduced GSC self-renewal and proliferation in vitro, and prolonged survival in a patient-derived xenograft model of GBM. FEN1 inhibition (FEN1i) preferentially affected highly aggressive or recurrent GBM models compared with less aggressive GBMs and healthy neural stem cells. Moreover, FEN1 inhibition synergized with TMZ only in these aggressive FEN1i-sensitive GSCs, providing cancer-selective killing and TMZ sensitization in the most untreatable of GBMs. Mechanistically, FEN1i-sensitive GSCs exhibited greater proliferation and sphere formation, while stalling their proliferation conferred resistance to FEN1 inhibition. Single-cell transcriptomics further linked FEN1 expression to stemness and the DNA damage response, elucidating broader determinants of FEN1 dependency. These findings establish FEN1 as a promising therapeutic target in GBM, offering a strategy for both selective targeting and enhancement of TMZ efficacy in aggressive cancers. Statement of SignificanceThis study identifies FEN1 as a key vulnerability of glioblastoma stem cells, revealing its role in therapy resistance and stemness, and proposes FEN1 inhibition as a strategy to enhance temozolomide efficacy.

cancer biology↗

bioRxiv2024

Robust Methods For Quantifying Neuronal Morphology And Molecular Signaling Reveal That Psychedelics Do Not Induce Neuroplasticity

Induction of neuroplasticity has become the dominant explanatory framework for the rapid and sustained therapeutic effects of classic psychedelics. Within this broad concept, examination of morphological neuronal plasticity, such as dendritic arbor growth, is widely used to assess the neuroplasticity effects of classic and novel psychedelics. At the molecular level, it has been reported that serotonergic psychedelic compounds mediate dendritogenesis via the master molecular regulator of plasticity, TrkB, either directly via BDNF/TrkB signaling potentiation or indirectly through 5-HT2A receptor. To examine these hypotheses in detail, we developed a robust multimodal screening platform for unbiased, semi-automated quantification of cellular morphology and multiplex molecular signaling in the same cortical neurons. We found that in widely used primary neuronal cultures psychedelics do not directly modulate TrkB receptor or BDNF-TrkB signaling. We also found 5HT2a receptor gene expression and functional receptor levels are low, and psychedelics do not induce morphological growth, in contrast to significant dendritogenesis elicited by BDNF. Our results challenge recently published results in the field and indicate a need for rigorous experimental methods to study morphological manifestations of neuroplasticity effects induced by clinically used and experimental therapeutics.

neuroscience↗

bioRxiv2022

Multi-level cellular and functional annotation of single-cell transcriptomes

Single-cell RNA-sequencing (scRNA-seq) offers unprecedented insight into heterogenous biology, allowing for the interrogation of cellular populations and gene expression programs at single-cell resolution. Here, we introduce scPipeline, a single-cell analytic toolbox that offers modular workflows for multi-level cellular annotation and user-friendly analysis reports. Novel methods that are introduced to facilitate scRNA-seq annotation include: (i) co-dependency index (CDI)-based differential expression; (ii) cluster resolution optimization using a marker-specificity criterion; (iii) marker-based cell-type annotation with Miko scoring; and (iv) gene program discovery using scale-free shared nearest neighbor network (SSN) analysis. Our unsupervised and supervised procedures were validated using a diverse collection of scRNA-seq datasets and we provide illustrative examples of cellular and transcriptomic annotation of developmental and immunological scRNA-seq atlases. Overall, scPipeline provides a flexible computational framework for in-depth scRNA-seq analysis.

bioinformatics↗

bioRxiv2022

Characterization of the minimal residual disease state reveals distinct evolutionary trajectories of human glioblastoma

Recurrence of solid tumors renders patients vulnerable to a distinctly advanced, highly treatment-refractory disease state that has an increased mutational burden and novel oncogenic drivers not detected at initial diagnosis. Improving outcomes for recurrent cancers requires a better understanding of cancer cell populations that expand from the post-therapy, minimal residual disease (MRD) state. We profiled barcoded tumor stem cell populations through therapy at tumor initiation/engraftment, MRD and recurrence in our therapy-adapted, patient-derived xenograft models of glioblastoma (GBM). Tumors showed distinct patterns of recurrence in which clonal populations exhibited either an a priori, pre-existing fitness advantage, or a priori equipotency fitness acquired through therapy. Characterization of the MRD state by single-cell and bulk RNA sequencing revealed a tumor-intrinsic immunomodulatory signature with strong prognostic significance at the transcriptomic level and in proteomic analysis of cerebrospinal fluid (CSF) collected from GBM patients at all stages of disease. Our results provide insight into the innate and therapy-driven dynamics of human GBM, and the prognostic value of interrogating the MRD state in solid cancers.

cancer biology↗

bioRxiv2021

Systematic genome-scale identification of host factors for SARS-CoV-2 infection across models yields a core single gene dependency; ACE2

SARS-CoV-2, depends on host cell components for replication, therefore the identification of virus-host dependencies offers an effective way to elucidate mechanisms involved in viral infection. Such host factors may be necessary for infection and replication of SARS-CoV-2 and, if druggable, presents an attractive strategy for anti-viral therapy. We performed genome wide CRISPR knockout screens in Vero E6 cells and 4 human cell lines including Calu-3, Caco-2, Hek293 and Huh7 to identify genetic regulators of SARS-CoV-2 infection. Our findings identified only ACE2, the cognate SARS-CoV-2 entry receptor, as a common host dependency factor across all cell lines, while all other host genes identified were cell line specific including known factors TMPRSS2 and CTSL. Several of the discovered host-dependency factors converged on pathways involved in cell signalling, lipid metabolism, immune pathways and chromatin modulation. Notably, chromatin modulator genes KMT2C and KDM6A in Calu-3 cells had the strongest impact in preventing SARS-CoV-2 infection when perturbed. Overall, the network of host factors that have been identified will be broadly applicable to understanding the impact of SARS-CoV-2 on human cells and facilitate the development of host-directed therapies. IN BRIEFSARS-CoV-2, depends on host cell components for infection and replication. Genome-wide CRISPR screens were performed in multiple human cell lines to elucidate common host dependencies required for SARS-CoV-2 infection. Only ACE2, the cognate SARS-CoV-2 entry receptor, was common amongst cell lines, while all other host genes identified were cell line specific, several of which converged on pathways involved in cell signalling, lipid metabolism, immune pathways, and chromatin modulation. Overall, a network of host factors was identified that will be broadly applicable to understanding the impact of SARS-CoV-2 on human cells and facilitate productive targeting of host genes and pathways. HIGHLIGHTS- Genome-wide CRISPR screens for SARS-CoV-2 in multiple human cell lines - Identification of wide-ranging cell-type dependent genetic dependencies for SARS-CoV-2 infection - ACE2 is the only common host factor identified across different cell types

systems biology↗

bioRxiv2021

Hitting more birds with one stone: CD70 as an actionable immunotherapeutic target in recurrent glioblastoma

PurposeGlioblastoma (GBM) patients suffer from a dismal prognosis, with standard of care therapy inevitably leading to therapy-resistant recurrent tumors. The presence of brain tumor initiating cells (BTICs) drives the extensive heterogeneity seen in GBM, prompting the need for novel therapies specifically targeting this subset of tumor-driving cells. Here we identify CD70 as a potential therapeutic target for recurrent GBM BTICs. Experimental DesignIn the current study, we identified the relevance and functional influence of CD70 on primary and recurrent GBM cells, and further define its function using established stem cell assays. We utilize CD70 knockdown studies, subsequent RNAseq pathway analysis, and in vivo xenotransplantation to validate CD70s role in GBM. Next, we developed and tested an anti-CD70 CAR-T therapy, which we validated in vitro and in vivo using our established preclinical model of human GBM. Lastly, we explored the importance of CD70 in the tumor immune microenvironment (TIME) by assessing the presence of its receptor, CD27, in immune infiltrates derived from freshly resected GBM tumor samples. ResultsCD70 expression is elevated in recurrent GBM and CD70 knockdown reduces tumorigenicity in vitro and in vivo. CD70 CAR-T therapy significantly improves prognosis in vivo. We also found CD27 to be present on the cell surface of multiple relevant GBM TIME cell populations. ConclusionCD70 plays a key role in recurrent GBM cell aggressiveness and maintenance. Immunotherapeutic targeting of CD70 significantly improves survival in animal models and the CD70/CD27 axis may be a viable poly-therapeutic avenue to co-target both GBM and its TIME.

cancer biology↗

bioRxiv2020

NOX4 links metabolic regulation in pancreatic cancer to endoplasmic reticulum redox vulnerability and dependence on PRDX4

Pancreatic ductal adenocarcinoma (PDAC) is an almost universally fatal malignancy and there is an urgent need for new therapeutic targets. PDAC cells harbor genetic alterations and display metabolic changes that render them vulnerable to perturbations in redox homeostasis. Peroxiredoxin 4 (PRDX4) supports redox homeostasis by metabolizing H2O2 in the endoplasmic reticulum (ER). Based on functional genomics, we found that PDAC cell lines are dependent on PRDX4 for their growth and survival. We validated this dependency in established and primary PDAC cells, as well as 3D models and orthotopic xenografts. Cell death induced by PRDX4 depletion was accompanied by increased levels of reactive oxygen species (ROS), DNA damage and a DNA-PKcs-governed DNA damage response. As such, PRDX4 depletion also sensitized cells and tumors to ionizing radiation. The source of ROS that created a dependency on PRDX4 was attributed to NADPH oxidase 4 (NOX4), which localizes to the ER membrane. The functional requirement for PRDX4 was correlated with cellular NADPH levels across different models of PDAC and could be rescued by depletion of NOX4 or NADPH. As such, this study has identified NOX4 as a link between metabolic deregulation and ER-specific redox vulnerability in PDAC. Since PRDX4 is not an essential gene in normal tissues, our work also suggests that PRDX4 represents a novel therapeutic target for pancreatic cancer that may be particularly potent in combination with radiotherapy.

cancer biology↗

bioRxiv2020

Major functional bias for mitochondrial complexes in genome-wide CRISPR screens

We present FLEX (Functional evaluation of experimental perturbations), a pipeline that leverages several functional annotation resources to establish reference standards for benchmarking human genome-wide CRISPR screen data and methods for analyzing them. We apply FLEX to analyze data from the diverse cell line screens generated by the DepMap project. We identify a dominant mitochondria-associated signal, which our time-resolved CRISPR screens and analysis suggests may reflect screen dynamics and protein stability effects rather than genetic dependencies.

systems biology↗

bioRxiv2020

Ontogeny and Vulnerabilities of Lapatinib Drug-Tolerant Persisters in HER2+ Breast Cancer

Resistance to targeted therapies is an important clinical problem in HER2-positive (HER2+) breast cancer. "Drug-tolerant persisters" (DTPs), a sub-population of cancer cells that survive via reversible, non-genetic mechanisms, are implicated in resistance to tyrosine kinase inhibitors (TKIs) in other malignancies, but DTPs following HER2 TKI exposure have not been well characterized. We found that HER2 TKIs evoke DTPs with a luminal-like or a mesenchymal-like transcriptome. Lentiviral barcoding/single cell RNA-sequencing reveal that HER2+ breast cancer cells cycle stochastically through a "pre-DTP" state, characterized by a G0-like expression signature and enriched for diapause and/or senescence genes. Trajectory analysis/cell sorting show that pre-DTPs preferentially yield DTPs upon HER2 TKI exposure. Cells with similar transcriptomes are present in HER2+ breast tumors and are associated with poor TKI response. Finally, biochemical experiments indicate that luminal-like DTPs survive via estrogen receptor-dependent induction of SGK3,leading to rewiring of the PI3K/AKT/mTORC1 pathway to enable AKT-independent mTORC1 activation. STATEMENT OF SIGNIFICANCEDTPs are implicated in resistance to TKIs, other targeted therapies, and chemotherapy, but their ontogeny and vulnerabilities remain unclear. We find that HER2 TKI-DTPs emerge from stochastically arising primed cells ("pre-DTPs") that preferentially engage either of two distinct transcriptional programs upon TKI exposure. Our results provide new insights into DTP ontogeny and identify potential therapeutic vulnerabilities.

cancer biology↗

bioRxiv2019

Systematic mapping of genetic interactions for de novo fatty acid synthesis

The de novo synthesis of fatty acids has emerged as a therapeutic target for various diseases including cancer. While several translational efforts have focused on direct perturbation of de novo fatty acid synthesis, only modest responses have been associated with mono-therapies. Since cancer cells are intrinsically buffered to combat metabolic stress, cells may adapt to loss of de novo fatty acid biosynthesis. To explore cellular response to defects in fatty acid synthesis, we used pooled genome-wide CRISPR screens to systematically map genetic interactions (GIs) in human HAP1 cells carrying a loss-of-function mutation in FASN, which catalyzes the formation of long-chain fatty acids. FASN mutant cells showed a strong dependence on lipid uptake that was reflected by negative GIs with genes involved in the LDL receptor pathway, vesicle trafficking, and protein glycosylation. Further support for these functional relationships was derived from additional GI screens in query cell lines deficient for other genes involved in lipid metabolism, including LDLR, SREBF1, SREBF2, ACACA. Our GI profiles identified a potential role for a previously uncharacterized gene LUR1 (C12orf49) in exogenous lipid uptake regulation. Overall, our data highlights the genetic determinants underlying the cellular adaptation associated with loss of de novo fatty acid synthesis and demonstrate the power of systematic GI mapping for uncovering metabolic buffering mechanisms in human cells.

systems biology↗

bioRxiv2017

Evaluation and Design of Genome-wide CRISPR/Cas9 Knockout Screens

The adaptation of CRISPR/Cas9 technology to mammalian cell lines is transforming the study of human functional genomics. Pooled libraries of CRISPR guide RNAs (gRNAs), targeting human protein-coding genes and encoded in viral vectors, have been used to systematically create gene knockouts in a variety of human cancer and immortalized cell lines, in an effort to identify whether these knockouts cause cellular fitness defects. Previous work has shown that CRISPR screens are more sensitive and specific than pooled library shRNA screens in similar assays, but currently there exists significant variability across CRISPR library designs and experimental protocols. In this study, we re-analyze 17 genome-scale knockout screens in human cell lines from three research groups using three different genome-scale gRNA libraries, using the Bayesian Analysis of Gene Essentiality (BAGEL) algorithm to identify essential genes, to refine and expand our previously defined set of human core essential genes, from 360 to 684 genes. We use this expanded set of reference Core Essential Genes (CEG2), plus empirical data from six CRISPR knockout screens, to guide the design of a sequence-optimized gRNA library, the Toronto KnockOut version 3.0 (TKOv3) library. We demonstrate the high effectiveness of the library relative to reference sets of essential and nonessential genes as well as other screens using similar approaches. The optimized TKOv3 library, combined with the CEG2 reference set, provide an efficient, highly optimized platform for performing and assessing gene knockout screens in human cell lines.

systems biology↗