Biology subjects

Sweet-Cordero, E. A.

Publications and source records attributed to Sweet-Cordero, E. A..

6 recordsLinked to original sources

bioRxiv2026

Tabular foundation model predicts alternative lengthening of telomeres (ALT) and identifies SMARCAL1 as a target in ALT-driven cancers

Alternative lengthening of telomeres (ALT) is a telomerase-independent pathway used by aggressive cancers to maintain their replicative immortality. Because ALT is absent from normal human cells, it is an appealing target for cancer therapy, but the lack of ability to determine ALT status at scale has hindered discovery. Here, we developed ALTitude, a machine learning method from a tabular foundation model that infers ALT from cell line whole genome sequencing data, without need for paired germline analysis. We deployed ALTitude across the DepMap, doubling the number of known ALT+ cancer models. Systematic integration of ALTitude with CRISPR-Cas9 screens yielded the selective dependency on SMARCAL1 in ALT+ cell lines, where we show it stabilizes the ALT phenotype. Acute depletion of SMARCAL1 leads to G2/M arrest, mitotic catastrophe, and cell death. These data provide a valuable resource for studying ALT-related genomic features and present SMARCAL1 as a therapeutic target for ALT+ malignancies.

cancer biology↗

bioRxiv2025

STING activation reshapes the tumor microenvironment leading to tumor regression in osteosarcoma

Osteosarcomas are characterized by a high degree of aneuploidy, chromothripsis and micronuclei, yet these tumors typically have an immunosuppressive, macrophage-rich, T-cell depleted tumor microenvironment. cGAS-STING dysregulation is a possible mechanism by which immune activation in response to tumor genomic instability could be repressed. We identified almost universal repression of cGAS or STING in human osteosarcomas. However, a STING-activation gene signature was predictive of survival in osteosarcoma patients suggesting potential for activation of this pathway in the osteosarcoma tumor microenvironment. Indeed, in immunocompetent osteosarcoma models, systemic STING agonism led to complete regression and induced lasting immunologic memory. Host STING activation is sufficient to promote this anti-tumor immunity even in the absence of tumor STING. These results nominate the cGAS-STING pathway as an important therapeutic target in osteosarcoma, a disease in which no new curative therapies have been developed in the last 40 years. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/684275v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@15b1e5corg.highwire.dtl.DTLVardef@12650aaorg.highwire.dtl.DTLVardef@79ef71org.highwire.dtl.DTLVardef@15704c9_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2023

Development and characterization of new patient-derived xenograft (PDX) models of osteosarcoma with distinct metastatic capacities

Models to study metastatic disease in rare cancers are needed to advance preclinical therapeutics and to gain insight into disease biology, especially for highly aggressive cancers with a propensity for metastatic spread. Osteosarcoma is a rare cancer with a complex genomic landscape in which outcomes for patients with metastatic disease are poor. As osteosarcoma genomes are highly heterogeneous, a large panel of models is needed to fully elucidate key aspects of disease biology and to recapitulate clinically-relevant phenotypes. We describe the development and characterization of osteosarcoma patient-derived xenografts (PDXs) and a panel of PDX-derived cell lines. Matched patient samples, PDXs, and PDX-derived cell lines were comprehensively evaluated using whole genome sequencing and RNA sequencing. PDXs and PDX-derived cell lines largely maintained the expression profiles of the patient from which they were derived despite the emergence of whole-genome duplication (WGD) in a subset of cell lines. These cell line models were heterogeneous in their metastatic capacity and their tissue tropism as observed in both intravenous and orthotopic models. As proof-of-concept study, we used one of these models to test the preclinical effectiveness of a CDK inhibitor on the growth of metastatic tumors in an orthotopic amputation model. Single-agent dinaciclib was effective at dramatically reducing the metastatic burden in this model. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/524562v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@17ea2a8org.highwire.dtl.DTLVardef@e8fcc7org.highwire.dtl.DTLVardef@2b9f8corg.highwire.dtl.DTLVardef@1f7b802_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2022

Sensitive multimodal profiling of native DNA by transposase-mediated single-molecule sequencing

We present SMRT-Tag: a multiplexable, PCR-free approach for constructing low-input, single-molecule Pacific Biosciences (PacBio) sequencing libraries through Tn5 transposition. As proof-of-concept, we apply SMRT-Tag to resolve human genetic and epigenetic variation in gold-standard human reference samples. SMRT-Tag requires 1-5% as much input material as existing protocols (15,000 - 50,000 human cell equivalents) and enables highly-sensitive and simultaneous detection of single nucleotide variants, small insertions / deletions, and CpG methylation comparable to the current state-of-the-art. We further combine SMRT-Tag with in situ adenine methyltransferase footprinting of nuclei (SAMOSA-Tag) to facilitate joint analysis of nucleosome repeat length, CTCF occupancy, and CpG methylation on individual chromatin fibers in osteosarcoma cells. SMRT-Tag promises to enable basic and clinical research by offering scalable, sensitive, and multimodal single-molecule genomic and epigenomic analyses in rare cell populations.

genomics↗

bioRxiv2020

Combined Proteomic and Genetic Interaction Mapping Reveals New RAS Effector Pathways and Susceptibilities

Activating mutations in RAS GTPases drive one fifth of cancers, but poor understanding of many RAS effectors and regulators, and of the roles of their different paralogs, continues to impede drug development. We developed a multi-stage discovery and screening process to understand RAS function and identify RAS-related susceptibilities in lung adenocarcinoma. Using affinity purification mass spectrometry (AP/MS), we generated a protein-protein interaction map of the RAS pathway containing thousands of interactions. From this network we constructed a CRISPR dual knockout library targeting 119 RAS-related genes that we screened for genetic interactions (GIs). We found important new effectors of RAS-driven cellular functions, RADIL and the GEF RIN1, and over 250 synthetic lethal GIs, including a potent KRAS-dependent interaction between RAP1GDS1 and RHOA. Many GIs link specific paralogs within and between gene families. These findings illustrate the power of the multiomic approach to identify synthetic lethal combinations for hitherto undruggable cancers. STATEMENT OF SIGNIFICANCEWe present a thorough survey of protein-protein and genetic interactions in the Ras pathway. These interactions suggested new discoveries that we validate here, and demonstrate important new paralog specificities and redundancies. By comparing synthetic lethal interactions across KRAS-dependent and -independent tumors, we identify new combination therapy targets against Ras-driven cancers.

cancer biology↗

bioRxiv2018

Systematic Elucidation and Validation of OncoProtein-Centric Molecular Interaction Maps

The largely incomplete and tissue-independent nature of cancer pathways represents a key limitation to the ability to elucidate mechanistic determinants of cancer phenotypes and to predict adaptive response to targeted therapy. To address these challenges, we propose replacing canonical cancer pathways with a more accurate, comprehensive, and context-specific architecture - dubbed a Protein-Centric molecular interaction Map (PC-Map) - representing modulators, effectors, and cognate binding-partners of any oncoprotein of interest. To reconstruct these complex molecular architectures de novo, we introduce a novel OncoSig algorithm. Validation of a lung adenocarcinoma specific (LUAD) KRAS-centric PC-Map recapitulated known KRAS biology and, more critically, identified a novel repertoire of proteins eliciting synthetic lethality in KRASG12D LUAD organoid cultures. Showing the generalizable nature of the algorithm, we elucidated PC-Maps for ten recurrently mutated oncoproteins, including KRAS, in distinct tumor contexts. This revealed a highly context-specific nature of cancers regulatory and signaling architectures to an unprecedented degree of resolution.

systems biology↗