Sarah M. Groves

selected publications

1. Cell Sys

   Archetype tasks link intratumoral heterogeneity to plasticity and cancer hallmarks in small cell lung cancer

   Sarah M. Groves, Geena V. Ildefonso, Caitlin O. McAtee, and 23 more authors

   Cell Systems Aug 2022

   Abs Bib HTML

   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
   }

2. PLOS Comp Bio

   Systems-level network modeling of Small Cell Lung Cancer subtypes identifies master regulators and destabilizers

   David J. Wooten, Sarah M. Groves, Darren R. Tyson, and 6 more authors

   PLOS Computational Biology Oct 2019

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   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
   }