publications

2023

Mol Cancer

CXCR2 expression during melanoma tumorigenesis controls transcriptional programs that facilitate tumor growth

J Yang, K. Bergdorf, C. Yan, and 14 more authors

Molecular Cancer Jun 2023

@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
}

Cancers

Involvement of Epithelial–Mesenchymal Transition Genes in Small Cell Lung Cancer Phenotypic Plasticity

Sarah M. Groves, Nicholas Panchy, Darren R Tyson, and 3 more authors

Cancers Jan 2023

Bib HTML

@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 Physiol

Quantifying cancer cell plasticity with gene regulatory networks and single-cell dynamics

Sarah M. Groves, and Vito Quaranta

Frontiers in Network Physiology Sep 2023

Bib HTML

@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 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

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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 Onc
Beyond Programmed Death-Ligand 1: B7-H6 Emerges as a Potential Immunotherapy Target in SCLC

Portia L. Thomas, Sarah M. Groves, Yun-Kai Zhang, and 16 more authors

Journal of Thoracic Oncology Jul 2021

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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 Cell
Patterns of transcription factor programs and immune pathway activation define four major subtypes of SCLC with distinct therapeutic vulnerabilities

Carl M. Gay, C. Allison Stewart, Elizabeth M. Park, and 27 more authors

Cancer Cell Jan 2021

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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 & Dev
ASCL1 represses a SOX9+ neural crest stem-like state in small cell lung cancer

Rachelle R. Olsen, Abbie S. Ireland, David W. Kastner, and 12 more authors

Genes & Development May 2021

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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 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 }

2016

Phys Rev C
Consistency of electron scattering data with a small proton radius

Keith Griffioen, Carl Carlson, and Sarah Maddox

Physical Review C Jun 2016

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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 }