Biology subjects

Mair, B.

Publications and source records attributed to Mair, B..

8 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↗

bioRxiv2024

Pharmacological SOS1 inhibitor BI-3406 demonstrates in vivo anti-tumor activity comparable to SOS1 genetic ablation in KRAS mutant tumors

Resistance to KRASmut inhibitors frequently arises, warranting further searches for anti-RAS cancer therapies. We evaluated the tolerability and efficacy of SOS1 pharmacological inhibition in comparison to genetic ablation in different KRAS-dependent tumor settings. Contrary to the rapid lethality caused by SOS1 genetic ablation in SOS2KO mice, SOS1 pharmacological inhibition by its specific inhibitor BI-3406 did not significantly affect animal weight/viability nor cause noteworthy systemic toxicity. In BI-3406-treated KRASmut MEFs, we observed significantly reduced RAS-GTP levels and RAS downstream signaling, as well as decreased tumor burden and slower disease progression resulting from tumor-intrinsic and extrinsic therapeutic drug effects. In vivo analyses of KRASG12D allografts in immunocompromised mice and KRASG12D-driven lung adenocarcinomas in immunocompetent mice showed that systemic BI-3406 treatment impaired tumor growth and downmodulated components of the tumor microenvironment comparably to the KRASG12D inhibitor MRTX1133. Markedly stronger synergistic antitumor effects were observed upon concomitant BI-3406+MRTX113 treatment, confirming SOS1 as an actionable therapy target in RAS-dependent cancers.

cancer biology↗

bioRxiv2023

SOS1 inhibition enhances the efficacy of and delays resistance to G12C inhibitors in lung adenocarcinoma

Clinical effectiveness of KRAS G12C inhibitors (G12Cis) is limited both by intrinsic and acquired resistance, necessitating the development of combination approaches. We found that targeting proximal receptor tyrosine kinase (RTK) signaling using the SOS1 inhibitor (SOS1i) BI-3406 both enhanced the potency of and delayed resistance to G12Ci treatment, but the extent of SOS1i effectiveness was modulated by both SOS2 expression and the specific mutational landscape. SOS1i enhanced the efficacy of G12Ci and limited rebound RTK/ERK signaling to overcome intrinsic/adaptive resistance, but this effect was modulated by SOS2 protein levels. Survival of drug-tolerant persister (DTP) cells within the heterogeneous tumor population and/or acquired mutations that reactivate RTK/RAS signaling can lead to outgrowth of tumor initiating cells (TICs) that drive therapeutic resistance. G12Ci drug tolerant persister cells showed a 2-3-fold enrichment of TICs, suggesting that these could be a sanctuary population of G12Ci resistant cells. SOS1i re-sensitized DTPs to G12Ci and inhibited G12C-induced TIC enrichment. Co-mutation of the tumor suppressor KEAP1 limits the clinical effectiveness of G12Cis, and KEAP1 and STK11 deletion increased TIC frequency and accelerated the development of acquired resistance to G12Ci in situ. SOS1i both delayed acquired G12Ci resistance and limited the total number of resistant colonies regardless of KEAP1 and STK11 mutational status. These data suggest that SOS1i could be an effective strategy to both enhance G12Ci efficacy and prevent G12Ci resistance regardless of co-mutations. SignificanceThe SOS1 inhibitor BI-3406 both inhibits intrinsic/adaptive resistance and targets drug tolerant persister cells to limit the development of acquired resistance to clinical KRASG12C inhibitors in lung adenocarcinoma cells.

cancer biology↗

bioRxiv2023

Genetic dependencies associated with transcription factor activities in human cancer cell lines

Transcription factors (TFs) are key components of the aberrant transcriptional programs in cancer cells. In this study, we used TF activity (TFa), inferred from the downstream regulons as a potential biomarker to identify associated genetic vulnerabilities in cancer cells. Our linear model framework, integrating TFa and genome-wide CRISPR knockout datasets identified 1,770 candidate TFa-target pairs across different cancer types and assessed their survival impact in patient data. As a proof of concept, through inhibitor screens and genetic depletion assays in cell lines, we validated the dependency of cell lines on predicted targets linked to TEAD1, the most prominent TF from our analysis. Overall, these candidate pairs represent an attractive resource for early-stage targets and drug discovery programs in oncology.

bioinformatics↗

bioRxiv2021

A cohesin traffic pattern genetically linked to gene regulation

Cohesin-mediated loop extrusion folds interphase chromosomes at the ten to hundreds kilobases scale. This process produces structural features such as loops and topologically associating domains. We identify three types of cis-elements that define the chromatin folding landscape generated by loop extrusion. First, CTCF sites form boundaries by stalling extruding cohesin, as shown before. Second, transcription termination sites form boundaries by acting as cohesin unloading sites. RNA polymerase II contributes to boundary formation at transcription termination sites. Third, transcription start sites form boundaries that are mostly independent of cohesin, but are sites where cohesin can pause. Together with cohesin loading at enhancers, and possibly other cis-elements, these loci create a dynamic pattern of cohesin traffic along the genome that guides enhancer-promoter interactions. Disturbing this traffic pattern, by removing CTCF barriers, renders cells sensitive to knock-out of genes involved in transcription initiation, such as the SAGA and TFIID complexes, and RNA processing such DEAD-Box RNA helicases. In the absence of CTCF, several of these factors fail to be efficiently recruited to active promoters. We propose that the complex pattern of cohesin movement along chromatin contributes to appropriate promoter-enhancer interactions and localization of transcription and RNA processing factors to active genes. HIGHLIGHTSO_LIAt least three types of chromatin boundaries regulate a cohesin traffic pattern. C_LIO_LIThe cohesin traffic pattern guides enhancer-promoter interactions. C_LIO_LIRemoving CTCF renders cells sensitive to deletion of RNA processing and gene regulation genes. C_LIO_LIDepleting CTCF affects localization of RNA processing and gene regulatory proteins. C_LI

genomics↗

bioRxiv2021

Interrogation of cancer gene dependencies reveals novel paralog interactions of autosome and sexchromosome encoded genes

Genetic networks are characterized by extensive buffering. During tumour evolution, disruption of these functional redundancies can create de novo vulnerabilities that are specific to cancer cells. In this regard, paralog genes are of particular interest, as the loss of one paralog gene can render tumour cells dependent on a remaining paralog. To systematically identify cancer-relevant paralog dependencies, we searched for candidate dependencies using CRISPR screens and publicly available loss-of-function datasets. Our analysis revealed >2,000 potential candidate dependencies, several of which were subsequently experimentally validated. We provide evidence that DNAJC15-DNAJC19, FAM50A-FAM50B and RPP25-RPP25L are novel cancer relevant paralog dependencies. Importantly, our analysis also revealed unexpected redundancies between sex chromosome genes. We show that chrX- and chrY- encoded paralogs, as exemplified by ZFX-ZFY, DDX3X-DDX3Y and EIF1AX-EIF1AY, are functionally linked so that tumour cell lines from male patients with Y-chromosome loss become exquisitely dependent on the chrX-encoded gene. We therefore propose genetic redundancies between chrX- and chrY- encoded paralogs as a general therapeutic strategy for human tumours that have lost the Y-chromosome.

genomics↗

bioRxiv2019

Scalable, FACS-Free Genome-Wide Phenotypic Screening

Genome-scale functional genetic screens can identify key regulators of a phenotype of interest, such as determinants of protein expression or modification. Here, we present a rapid, high-throughput approach to phenotypic CRISPR-Cas9 screening. To study factors that modulate the display of CD47 on the cell surface, we processed an entire genome-wide screen containing more than 108 cells in under one hour and maintained high levels of cell viability using a highly scalable cell sorting technology. We robustly identified modulators of CD47 function including QPCTL, an enzyme required for formation of the pyroglutamyl modification at the N-terminus of this protein.

genomics↗