Publications
publications by date in reversed chronological order.
2026
- bioRxivTranscriptional networks underlying tumour plasticity in small-cell lung cancerDebadrita Bhattacharya, Sarah M. Groves, Cameron Walker, and 9 more authorsbioRxiv Sep 2026
Across human malignancies, the ability of cancer cells to switch states (plasticity) drives progression, metastasis, and therapy resistance. Here we investigated the transcriptional and epigenetic basis of plasticity in small-cell lung cancer (SCLC), an aggressive, treatment-refractory cancer. SCLC tumours display plasticity along a neuroendocrine (NE) to nonNE axis; however, the trajectories of lineage transition and the gene regulatory network underlying it, remain poorly defined. Using single-cell multi-omics, we resolved distinct transcriptional SCLC cell states, including a previously unrecognised Intermediate state comprised of low-identity immunogenic SCLC cells that serve as an obligatory route in NE to nonNE lineage transition. Using single-cell gene expression and chromatin accessibility data, we next developed a Boolean Bayes model for transcription factor networks (BoBa-T) to predict regulators of SCLC cell states. We validated RORB as a novel gatekeeper of the NE state that represses the nonNE identity in SCLC. RORB inactivation drives NE cells into the Intermediate state, upregulates immunogenic programs, and inhibits tumour growth in immunocompetent hosts. Our work identifies a plastic, immunogenic waypoint for SCLC lineage switching and reveals strategies to target it therapeutically.
@article{10.64898/2026.09.26.754526, year = {2026}, title = {{Transcriptional networks underlying tumour plasticity in small-cell lung cancer}}, author = {Bhattacharya, Debadrita and Groves, Sarah M. and Walker, Cameron and Duronio, Gina N. and Hsieh, Marcus and Chtourou, Yamina and Hartmann, Griffin G. and Hsu, Wen-Hao and Liu, Candace C. and Angelo, Michael and Quaranta, Vito and Sage, Julien}, journal = {bioRxiv}, doi = {10.64898/2026.09.26.754526}, url = {https://www.biorxiv.org/content/10.64898/2026.09.26.754526v1}, keywords = {}, month = sep } - PLOS Comp BioCell-specific Cahn-Hilliard models predict condensed fates of the chromosomal passenger complexSarah M. Groves, Min-Jhe Lu, Astrid Catalina Alvarez-Yela, and 4 more authorsPLOS Computational Biology Aug 2026
Biomolecular condensates create dynamic subcellular compartments that alter systems-level properties of the networks surrounding them. Standard reaction-diffusion models of systems biology cannot define where these compartments emerge nor track how they evolve. One alternative physicochemical model of soluble and condensed states in space and time is the Cahn-Hilliard equation, which specifies a diffuse interface between the two phases. Customized numerical approaches required to solve this equation are absent from computing environments often used for systems biology, however, and the equation’s interfacial energy coefficient lacks empirical constraints. Here, using two complementary numerical strategies, we built stable, self-consistent Cahn-Hilliard solvers in three common systems-biology programming languages. The algorithms simulated the complete time evolution of condensed droplets as they dissolved or persisted, relating critical equilibrium droplet size to the Cahn-Hilliard interfacial energy coefficient. We applied this universal relationship to the chromosomal passenger complex, a multi-protein assembly that reportedly condenses on mitotic chromosomes. The fully constrained Cahn-Hilliard simulations predicted spatiotemporal dewetting and coarsening behaviors that matched experiments in cell types with different interfacial energy coefficients. Together, these results suggest how initially variegated recruitment yields robust localization of the chromosomal passenger complex to the inner centromere by the end of prometaphase. More generally, the Cahn-Hilliard equation tests whether condensate dynamics behave as a simple phase-separated liquid, and its numerical solutions advance generalized modeling of biomolecular systems.
@article{10.1371/journal.pcbi.1014568, year = {2026}, title = {{Cell-specific Cahn-Hilliard models predict condensed fates of the chromosomal passenger complex}}, author = {Groves, Sarah M. and Lu, Min-Jhe and Alvarez-Yela, Astrid Catalina and Gerardo-Ramírez, Monserrat and Stukenberg, P. Todd and Lowengrub, John S. and Janes, Kevin A.}, journal = {PLOS Computational Biology}, doi = {10.1371/journal.pcbi.1014568}, url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014568}, pages = {e1014568}, number = {8}, volume = {22}, keywords = {}, month = aug } - J Thor OncYAP1 defines an emergent, plastic population of relapsed small cell lung cancerC. Allison Stewart, Kavya Ramkumar, Runsheng Wang, and 21 more authorsJournal of Thoracic Oncology Apr 2026
Small cell lung cancer (SCLC) is an aggressive neuroendocrine malignancy characterized by rapid onset of chemoresistance and poor clinical outcomes. Transcriptional heterogeneity among treatment-naïve SCLC tumors underlies four transcriptional subtypes, each with distinct clinical vulnerabilities. Though previously hypothesized to delineate a distinct subtype, expression of YAP1 is largely absent from treatment-naïve, pure SCLC. To characterize relapsed SCLC, circulating tumor DNA, circulating tumor cells, and core needle biopsies from SCLC patients and preclinical models following resistance to standard-of-care therapies were analyzed. In contrast to treatment-naïve SCLC, these analyses reveal an emergent YAP1-positive cell population that coincides with treatment resistance. These YAP1-positive cells exhibit characteristics of drug tolerant persister cells, including senescence, stemness, and plasticity, as YAP1 positive cells largely abandon features characteristic of SCLC to adopt those of large-cell neuroendocrine carcinoma (LCNEC). As a result of this SCLC-like to LCNEC-like evolution, YAP1-positive cells lack several clinically relevant SCLC surface targets (i.e., DLL3, SEZ6), but are enriched for others (i.e., B7-H3, TROP2). We propose a model where YAP1 expressing cells emerge with SCLC treatment resistance and characterize a tenacious subpopulation capable of diverging from the treatment naïve lineage and adopting features to evade therapeutic response.
@article{10.1016/j.jtho.2026.103730, year = {2026}, title = {{YAP1 defines an emergent, plastic population of relapsed small cell lung cancer}}, author = {Stewart, C. Allison and Ramkumar, Kavya and Wang, Runsheng and Xi, Yuanxin and Halliday, Alexa and Diao, Lixia and Wang, Qi and Serrano, Alejandra and Groves, Sarah M. and Heeke, Simon and Tanimoto, Azusa and Kaiser, Laura and Lewis, Whitney and Bose, Mukulika and Da Rocha, Pedro and Karacosta, Loukia and Quaranta, Vito and Wang, Jing and George, Julie and Solis Soto, Luisa Maren and Zhang, Bingnan and Heymach, John V. and Byers, Lauren A. and Gay, Carl M.}, journal = {Journal of Thoracic Oncology}, doi = {10.1016/j.jtho.2026.103730}, pmcid = {PMC13120736}, url = {https://www.sciencedirect.com/science/article/pii/S1556086426001838}, pages = {103730}, number = {8}, volume = {21}, keywords = {}, month = apr }
2025
- bioRxivCahn-Hilliard dynamical models for condensed biomolecular systemsSarah M. Groves, Min-Jhe Lu, Astrid Catalina Alvarez-Yela, and 4 more authorsbioRxiv Jul 2025
Biomolecular condensates create dynamic subcellular compartments that alter systems-level properties of the networks surrounding them. One model combining soluble and condensed states is the Cahn-Hilliard equation, which specifies a diffuse interface between the two phases. Customized approaches required to solve this equation are largely inaccessible. Using two complementary numerical strategies, we built stable, self-consistent Cahn-Hilliard solvers in Python, MATLAB, and Julia. The algorithms simulated the complete time evolution of condensed droplets as they dissolved or persisted, relating critical droplet size to a coefficient for the diffuse interface in the Cahn-Hilliard equation. We applied this universal relationship to the chromosomal passenger complex, a multi-protein assembly that reportedly condenses on mitotic chromosomes. The fully constrained Cahn-Hilliard simulations yielded dewetting and coarsening behaviors that closely mirrored experiments in different cell types. The Cahn-Hilliard equation tests whether condensate dynamics behave as a phase-separated liquid, and its numerical solutions advance generalized modeling of biomolecular systems.
@article{10.1101/2025.07.13.664571, year = {2025}, title = {{Cahn-Hilliard dynamical models for condensed biomolecular systems}}, author = {Groves, Sarah M. and Lu, Min-Jhe and Alvarez-Yela, Astrid Catalina and Gerardo-Ramírez, Monserrat and Stukenberg, P. Todd and Lowengrub, John S. and Janes, Kevin A.}, journal = {bioRxiv}, doi = {10.1101/2025.07.13.664571}, url = {https://www.biorxiv.org/content/10.1101/2025.07.13.664571v1}, keywords = {}, month = jul }
2024
- Mol Sys BiolProteome-wide copy-number estimation from transcriptomicsA.J. Sweatt, C.D. Griffiths, S.M. Groves, and 4 more authorsMolecular Systems Biology Nov 2024
Protein copy numbers constrain systems-level properties of regulatory networks, but absolute proteomic data remain scarce compared to transcriptomics obtained by RNA sequencing. We addressed this persistent gap by relating mRNA to protein statistically using best-available data from quantitative proteomics-transcriptomics for 4366 genes in 369 cell lines. The approach starts with a central estimate of protein copy number and hierarchically appends mRNA-protein and mRNA-mRNA dependencies to define an optimal gene-specific model that links mRNAs to protein. For dozens of independent cell lines and primary prostate samples, these protein inferences from mRNA outmatch stringent null models, a count-based protein-abundance repository, and empirical protein-to-mRNA ratios. The optimal mRNA-to-protein relationships capture biological processes along with hundreds of known protein-protein interaction complexes, suggesting mechanistic relationships are embedded. We use the method to estimate viral-receptor abundances of CD55-CXADR from human heart transcriptomes and build 1489 systems-biology models of coxsackievirus B3 infection susceptibility. When applied to 796 RNA sequencing profiles of breast cancer from The Cancer Genome Atlas, inferred copy-number estimates collectively reclassify 26% of Luminal A and 29% of Luminal B tumors. Protein-based reassignments strongly involve a pharmacologic target for luminal breast cancer (CDK4) and an alpha-catenin that is often undetectable at the mRNA level (CTTNA2). Thus, by adopting a gene-centered perspective of mRNA-protein covariation across different biological contexts, we achieve accuracies comparable to the technical reproducibility limits of contemporary proteomics. The collection of gene-specific models is assembled as a web tool for users seeking mRNA-guided predictions of absolute protein abundance (http://janeslab.shinyapps.io/Pinferna).
@article{10.1038/s44320-024-00064-3, year = {2024}, title = {{Proteome-wide copy-number estimation from transcriptomics}}, author = {Sweatt, A.J. and Griffiths, C.D. and Groves, S.M. and Paudel, B.B. and Wang, L. and Kashatus, D.F. and Janes, K.A.}, journal = {Molecular Systems Biology}, doi = {10.1038/s44320-024-00064-3}, url = {https://www.embopress.org/doi/full/10.1038/s44320-024-00064-3}, keywords = {}, month = nov }
2023
- Mol CancerCXCR2 expression during melanoma tumorigenesis controls transcriptional programs that facilitate tumor growthJ Yang, K. Bergdorf, C. Yan, and 14 more authorsMolecular Cancer Jun 2023
Though the CXCR2 chemokine receptor is known to play a key role in cancer growth and response to therapy, a direct link between expression of CXCR2 in tumor progenitor cells during induction of tumorigenesis has not been established. To characterize the role of CXCR2 during melanoma tumorigenesis, we generated tamoxifen-inducible tyrosinase-promoter driven BrafV600E/Pten-/-/Cxcr2-/- and NRasQ61R/INK4a-/-/Cxcr2-/- melanoma models. In addition, the effects of a CXCR1/CXCR2 antagonist, SX-682, on melanoma tumorigenesis were evaluated in BrafV600E/Pten-/- and NRasQ61R/INK4a-/- mice and in melanoma cell lines. Potential mechanisms by which Cxcr2 affects melanoma tumorigenesis in these murine models were explored using RNAseq, mMCP-counter, ChIPseq, and qRT-PCR; flow cytometry, and reverse phosphoprotein analysis (RPPA). Genetic loss of Cxcr2 or pharmacological inhibition of CXCR1/CXCR2 during melanoma tumor induction resulted in key changes in gene expression that reduced tumor incidence/growth and increased anti-tumor immunity. Interestingly, after Cxcr2 ablation, Tfcp2l1, a key tumor suppressive transcription factor, was the only gene significantly induced with a log2 fold-change greater than 2 in these three different melanoma models. Here, we provide novel mechanistic insight revealing how loss of Cxcr2 expression/activity in melanoma tumor progenitor cells results in reduced tumor burden and creation of an anti-tumor immune microenvironment. This mechanism entails an increase in expression of the tumor suppressive transcription factor, Tfcp2l1, along with alteration in the expression of genes involved in growth regulation, tumor suppression, stemness, differentiation, and immune modulation. These gene expression changes are coincident with reduction in the activation of key growth regulatory pathways, including AKT and mTOR.
@article{10.1186/s12943-023-01789-9, year = {2023}, title = {{CXCR2 expression during melanoma tumorigenesis controls transcriptional programs that facilitate tumor growth}}, author = {Yang, J and Bergdorf, K. and Yan, C. and Luo, W. and Chen, S. C. and Ayers, G.D. and Liu, Q. and Liu, X. and Boothby, M. and Weiss, V.L. and Groves, S. M. and Oleskie, A. N. and Zhang, X. and Maeda, D. Y. and Zebala, J. A. and Quaranta, V. and Richmond, A.}, journal = {Molecular Cancer}, doi = {10.1186/s12943-023-01789-9}, url = {https://link.springer.com/article/10.1186/s12943-023-01789-9}, keywords = {}, month = jun } - CancersInvolvement of Epithelial–Mesenchymal Transition Genes in Small Cell Lung Cancer Phenotypic PlasticitySarah M. Groves, Nicholas Panchy, Darren R Tyson, and 3 more authorsCancers Jan 2023
Small cell lung cancer (SCLC) is an aggressive cancer recalcitrant to treatment, arising predominantly from epithelial pulmonary neuroendocrine (NE) cells. Intratumor heterogeneity plays critical roles in SCLC disease progression, metastasis, and treatment resistance. At least five transcriptional SCLC NE and non-NE cell subtypes were recently defined by gene expression signatures. Transition from NE to non-NE cell states and cooperation between subtypes within a tumor likely contribute to SCLC progression by mechanisms of adaptation to perturbations. Therefore, gene regulatory programs distinguishing SCLC subtypes or promoting transitions are of great interest. Here, we systematically analyze the relationship between SCLC NE/non-NE transition and epithelial to mesenchymal transition (EMT)-a well-studied cellular process contributing to cancer invasiveness and resistance-using multiple transcriptome datasets from SCLC mouse tumor models, human cancer cell lines, and tumor samples. The NE SCLC-A2 subtype maps to the epithelial state. In contrast, SCLC-A and SCLC-N (NE) map to a partial mesenchymal state (M1) that is distinct from the non-NE, partial mesenchymal state (M2). The correspondence between SCLC subtypes and the EMT program paves the way for further work to understand gene regulatory mechanisms of SCLC tumor plasticity with applicability to other cancer types.
@article{10.3390/cancers15051477, year = {2023}, title = {{Involvement of Epithelial–Mesenchymal Transition Genes in Small Cell Lung Cancer Phenotypic Plasticity}}, author = {Groves, Sarah M. and Panchy, Nicholas and Tyson, Darren R and Harris, Leonard A and Quaranta, Vito and Hong, Tian}, journal = {Cancers}, doi = {10.3390/cancers15051477}, url = {https://www.mdpi.com/2072-6694/15/5/1477}, keywords = {}, month = jan } - Front Netw PhysiolQuantifying cancer cell plasticity with gene regulatory networks and single-cell dynamicsSarah M. Groves, and Vito QuarantaFrontiers in Network Physiology Sep 2023
Phenotypic plasticity of cancer cells can lead to complex cell state dynamics during tumor progression and acquired resistance. Highly plastic stem-like states may be inherently drug-resistant. Moreover, cell state dynamics in response to therapy allow a tumor to evade treatment. In both scenarios, quantifying plasticity is essential for identifying high-plasticity states or elucidating transition paths between states. Currently, methods to quantify plasticity tend to focus on 1) quantification of quasi-potential based on the underlying gene regulatory network dynamics of the system; or 2) inference of cell potency based on trajectory inference or lineage tracing in single-cell dynamics. Here, we explore both of these approaches and associated computational tools. We then discuss implications of each approach to plasticity metrics, and relevance to cancer treatment strategies.
@article{10.3389/fnetp.2023.1225736, year = {2023}, title = {{Quantifying cancer cell plasticity with gene regulatory networks and single-cell dynamics}}, author = {Groves, Sarah M. and Quaranta, Vito}, journal = {Frontiers in Network Physiology}, doi = {10.3389/fnetp.2023.1225736}, url = {https://www.frontiersin.org/journals/network-physiology/articles/10.3389/fnetp.2023.1225736/full}, keywords = {}, month = sep }
2022
- Cell SysArchetype tasks link intratumoral heterogeneity to plasticity and cancer hallmarks in small cell lung cancerSarah M. Groves, Geena V. Ildefonso, Caitlin O. McAtee, and 23 more authorsCell Systems Aug 2022
Small cell lung cancer (SCLC) tumors comprise heterogeneous mixtures of cell states, categorized into neuroendocrine (NE) and non-neuroendocrine (non-NE) transcriptional subtypes. NE to non-NE state transitions, fueled by plasticity, likely underlie adaptability to treatment and dismal survival rates. Here, we apply an archetypal analysis to model plasticity by recasting SCLC phenotypic heterogeneity through multi-task evolutionary theory. Cell line and tumor transcriptomics data fit well in a five-dimensional convex polytope whose vertices optimize tasks reminiscent of pulmonary NE cells, the SCLC normal counterparts. These tasks, supported by knowledge and experimental data, include proliferation, slithering, metabolism, secretion, and injury repair, reflecting cancer hallmarks. SCLC subtypes, either at the population or single-cell level, can be positioned in archetypal space by bulk or single-cell transcriptomics, respectively, and characterized as task specialists or multi-task generalists by the distance from archetype vertex signatures. In the archetype space, modeling single-cell plasticity as a Markovian process along an underlying state manifold indicates that task trade-offs, in response to microenvironmental perturbations or treatment, may drive cell plasticity. Stifling phenotypic transitions and plasticity may provide new targets for much-needed translational advances in SCLC. A record of this paper’s Transparent Peer Review process is included in the supplemental information.
@article{10.1016/j.cels.2022.07.006, year = {2022}, title = {{Archetype tasks link intratumoral heterogeneity to plasticity and cancer hallmarks in small cell lung cancer}}, author = {Groves, Sarah M. and Ildefonso, Geena V. and McAtee, Caitlin O. and Ozawa, Patricia M.M. and Ireland, Abbie S. and Stauffer, Philip E. and Wasdin, Perry T. and Huang, Xiaomeng and Qiao, Yi and Lim, Jing Shan and Bader, Jackie and Liu, Qi and Simmons, Alan J. and Lau, Ken S. and Iams, Wade T. and Hardin, Doug P. and Saff, Edward B. and Holmes, William R. and Tyson, Darren R. and Lovly, Christine M. and Rathmell, Jeffrey C. and Marth, Gabor and Sage, Julien and Oliver, Trudy G. and Weaver, Alissa M. and Quaranta, Vito}, journal = {Cell Systems}, issn = {2405-4712}, doi = {10.1016/j.cels.2022.07.006}, url = {https://www.cell.com/cell-systems/fulltext/S2405-4712(22)00313-1?\_returnURL=https\%3A\%2F\%2Flinkinghub.elsevier.com\%2Fretrieve\%2Fpii\%2FS2405471222003131\%3Fshowall\%3Dtrue}, keywords = {}, month = aug }
2021
- J Thor OncBeyond Programmed Death-Ligand 1: B7-H6 Emerges as a Potential Immunotherapy Target in SCLCPortia L. Thomas, Sarah M. Groves, Yun-Kai Zhang, and 16 more authorsJournal of Thoracic Oncology Jul 2021
Introduction The programmed death-ligand 1 (PD-L1) immune checkpoint inhibitors, atezolizumab and durvalumab, have received regulatory approval for the first-line treatment of patients with extensive-stage SCLC. Nevertheless, when used in combination with platinum-based chemotherapy, these PD-L1 inhibitors only improve overall survival by 2 to 3 months. This may be due to the observation that less than 20% of SCLC tumors express PD-L1 at greater than 1%. Evaluating the composition and abundance of checkpoint molecules in SCLC may identify molecules beyond PD-L1 that are amenable to therapeutic targeting. Methods We analyzed RNA-sequencing data from SCLC cell lines (n = 108) and primary tumor specimens (n = 81) for expression of 39 functionally validated inhibitory checkpoint ligands. Furthermore, we generated tissue microarrays containing SCLC cell lines and patient with SCLC specimens to confirm expression of these molecules by immunohistochemistry. We annotated patient outcomes data, including treatment response and overall survival. Results The checkpoint protein B7-H6 (NCR3LG1) exhibited increased protein expression relative to PD-L1 in cell lines and tumors (p < 0.05). Higher B7-H6 protein expression correlated with longer progression-free survival (p = 0.0368) and increased total immune infiltrates (CD45+) in patients. Furthermore, increased B7-H6 gene expression in SCLC tumors correlated with a decreased activated natural killer cell gene signature, suggesting a complex interplay between B7-H6 expression and immune signature in SCLC. Conclusions We investigated 39 inhibitory checkpoint molecules in SCLC and found that B7-H6 is highly expressed and associated with progression-free survival. In addition, 26 of 39 immune checkpoint proteins in SCLC tumors were more abundantly expressed than PD-L1, indicating an urgent need to investigate additional checkpoint targets for therapy in addition to PD-L1.
@article{10.1016/j.jtho.2021.03.011, year = {2021}, title = {{Beyond Programmed Death-Ligand 1: B7-H6 Emerges as a Potential Immunotherapy Target in SCLC}}, author = {Thomas, Portia L. and Groves, Sarah M. and Zhang, Yun-Kai and Li, Jia and Gonzalez-Ericsson, Paula and Sivagnanam, Shamilene and Betts, Courtney B. and Chen, Hua-Chang and Liu, Qi and Lowe, Cindy and Chen, Heidi and Boyd, Kelli L. and Kopparapu, Prasad R. and Yan, Yingjun and Coussens, Lisa M. and Quaranta, Vito and Tyson, Darren R. and Iams, Wade and Lovly, Christine M.}, journal = {Journal of Thoracic Oncology}, issn = {1556-0864}, doi = {10.1016/j.jtho.2021.03.011}, pmid = {33839362}, pmcid = {PMC8222171}, url = {https://www.sciencedirect.com/science/article/pii/S1556086421020669}, pages = {1211--1223}, number = {7}, volume = {16}, keywords = {}, month = jul } - Cancer CellPatterns of transcription factor programs and immune pathway activation define four major subtypes of SCLC with distinct therapeutic vulnerabilitiesCarl M. Gay, C. Allison Stewart, Elizabeth M. Park, and 27 more authorsCancer Cell Jan 2021
Despite molecular and clinical heterogeneity, small cell lung cancer (SCLC) is treated as a single entity with predictably poor results. Using tumor expression data and non-negative matrix factorization, we identify four SCLC subtypes defined largely by differential expression of transcription factors ASCL1, NEUROD1, and POU2F3 or low expression of all three transcription factor signatures accompanied by an Inflamed gene signature (SCLC-A, N, P, and I, respectively). SCLC-I experiences the greatest benefit from the addition of immunotherapy to chemotherapy, while the other subtypes each have distinct vulnerabilities, including to inhibitors of PARP, Aurora kinases, or BCL-2. Cisplatin treatment of SCLC-A patient-derived xenografts induces intratumoral shifts toward SCLC-I, supporting subtype switching as a mechanism of acquired platinum resistance. We propose that matching baseline tumor subtype to therapy, as well as manipulating subtype switching on therapy, may enhance depth and duration of response for SCLC patients.
@article{10.1016/j.ccell.2020.12.014, year = {2021}, title = {{Patterns of transcription factor programs and immune pathway activation define four major subtypes of SCLC with distinct therapeutic vulnerabilities}}, journal = {Cancer Cell}, issn = {1535-6108}, doi = {10.1016/j.ccell.2020.12.014}, pmid = {33482121}, url = {https://www.cell.com/cancer-cell/fulltext/S1535-6108(20)30662-0}, keywords = {}, month = jan } - Genes & DevASCL1 represses a SOX9+ neural crest stem-like state in small cell lung cancerRachelle R. Olsen, Abbie S. Ireland, David W. Kastner, and 12 more authorsGenes & Development May 2021
ASCL1 is a neuroendocrine lineage-specific oncogenic driver of small cell lung cancer (SCLC), highly expressed in a significant fraction of tumors. However, ∼25% of human SCLC are ASCL1-low and associated with low neuroendocrine fate and high MYC expression. Using genetically engineered mouse models (GEMMs), we show that alterations in Rb1/Trp53/Myc in the mouse lung induce an ASCL1+ state of SCLC in multiple cells of origin. Genetic depletion of ASCL1 in MYC-driven SCLC dramatically inhibits tumor initiation and progression to the NEUROD1+ subtype of SCLC. Surprisingly, ASCL1 loss promotes a SOX9+ mesenchymal/neural crest stem-like state and the emergence of osteosarcoma and chondroid tumors, whose propensity is impacted by cell of origin. ASCL1 is critical for expression of key lineage-related transcription factors NKX2-1, FOXA2, and INSM1 and represses genes involved in the Hippo/Wnt/Notch developmental pathways in vivo. Importantly, ASCL1 represses a SOX9/RUNX1/RUNX2 program in vivo and SOX9 expression in human SCLC cells, suggesting a conserved function for ASCL1. Together, in a MYC-driven SCLC model, ASCL1 promotes neuroendocrine fate and represses the emergence of a SOX9+ nonendodermal stem-like fate that resembles neural crest.
@article{10.1101/gad.348295.121, year = {2021}, title = {{ASCL1 represses a SOX9+ neural crest stem-like state in small cell lung cancer}}, author = {Olsen, Rachelle R. and Ireland, Abbie S. and Kastner, David W. and Groves, Sarah M. and Spainhower, Kyle B. and Pozo, Karine and Kelenis, Demetra P. and Whitney, Christopher P. and Guthrie, Matthew R. and Wait, Sarah J. and Soltero, Danny and Witt, Benjamin L. and Quaranta, Vito and Johnson, Jane E. and Oliver, Trudy G.}, journal = {Genes \& Development}, issn = {0890-9369}, doi = {10.1101/gad.348295.121}, pmid = {34016693}, url = {http://genesdev.cshlp.org/content/35/11-12/847}, keywords = {}, month = may }
2019
- PLOS Comp BioSystems-level network modeling of Small Cell Lung Cancer subtypes identifies master regulators and destabilizersDavid J. Wooten, Sarah M. Groves, Darren R. Tyson, and 6 more authorsPLOS Computational Biology Oct 2019
Adopting a systems approach, we devise a general workflow to define actionable subtypes in human cancers. Applied to small cell lung cancer (SCLC), the workflow identifies four subtypes based on global gene expression patterns and ontologies. Three correspond to known subtypes (SCLC-A, SCLC-N, and SCLC-Y), while the fourth is a previously undescribed ASCL1+ neuroendocrine variant (NEv2, or SCLC-A2). Tumor deconvolution with subtype gene signatures shows that all of the subtypes are detectable in varying proportions in human and mouse tumors. To understand how multiple stable subtypes can arise within a tumor, we infer a network of transcription factors and develop BooleaBayes, a minimally-constrained Boolean rule-fitting approach. In silico perturbations of the network identify master regulators and destabilizers of its attractors. Specific to NEv2, BooleaBayes predicts ELF3 and NR0B1 as master regulators of the subtype, and TCF3 as a master destabilizer. Since the four subtypes exhibit differential drug sensitivity, with NEv2 consistently least sensitive, these findings may lead to actionable therapeutic strategies that consider SCLC intratumoral heterogeneity. Our systems-level approach should generalize to other cancer types.
@article{10.1371/journal.pcbi.1007343, year = {2019}, title = {{Systems-level network modeling of Small Cell Lung Cancer subtypes identifies master regulators and destabilizers}}, author = {Wooten, David J. and Groves, Sarah M. and Tyson, Darren R. and Liu, Qi and Lim, Jing S. and Albert, Réka and Lopez, Carlos F. and Sage, Julien and Quaranta, Vito}, journal = {PLOS Computational Biology}, issn = {1553-734X}, doi = {10.1371/journal.pcbi.1007343}, pmid = {31671086}, url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007343}, pages = {e1007343}, number = {10}, volume = {15}, keywords = {}, month = oct }
2016
- Phys Rev CConsistency of electron scattering data with a small proton radiusKeith Griffioen, Carl Carlson, and Sarah MaddoxPhysical Review C Jun 2016
We determine the charge radius of the proton by analyzing the published low momentum transfer electron-proton scattering data from Mainz. We note that polynomial expansions of the form factor converge for momentum transfers squared below 4mπ2, where mπ is the pion mass. Expansions with enough terms to fit the data, but few enough not to overfit, yield proton radii smaller than the CODATA or Mainz values and in accord with the muonic atom results. We also comment on analyses using a wider range of data, and overall obtain a proton radius RE=0.840(16) fm.
@article{10.1103/physrevc.93.065207, year = {2016}, title = {{Consistency of electron scattering data with a small proton radius}}, author = {Griffioen, Keith and Carlson, Carl and Maddox, Sarah}, journal = {Physical Review C}, issn = {2469-9985}, doi = {10.1103/physrevc.93.065207}, pages = {065207}, number = {6}, volume = {93}, keywords = {}, month = jun }