You are here

Cell DOI:10.1016/j.cell.2021.11.017

Microenvironment drives cell state, plasticity, and drug response in pancreatic cancer.

Publication TypeJournal Article
Year of Publication2021
AuthorsRaghavan, S, Winter, PS, Navia, AW, Williams, HL, DenAdel, A, Lowder, KE, Galvez-Reyes, J, Kalekar, RL, Mulugeta, N, Kapner, KS, Raghavan, MS, Borah, AA, Liu, N, Väyrynen, SA, Costa, ADias, Ng, RWS, Wang, J, Hill, EK, Ragon, DY, Brais, LK, Jaeger, AM, Spurr, LF, Li, YY, Cherniack, AD, Booker, MA, Cohen, EF, Tolstorukov, MY, Wakiro, I, Rotem, A, Johnson, BE, McFarland, JM, Sicinska, ET, Jacks, TE, Sullivan, RJ, Shapiro, GI, Clancy, TE, Perez, K, Rubinson, DA, Ng, K, Cleary, JM, Crawford, L, Manalis, SR, Nowak, JA, Wolpin, BM, Hahn, WC, Aguirre, AJ, Shalek, AK
JournalCell
Volume184
Issue25
Pages6119-6137.e26
Date Published2021 12 09
ISSN1097-4172
KeywordsAdult, Aged, Biomarkers, Tumor, Carcinoma, Pancreatic Ductal, Cell Line, Tumor, Female, Gene Expression Regulation, Neoplastic, Humans, Male, Middle Aged, Pancreatic Neoplasms, Single-Cell Analysis, Tumor Microenvironment
Abstract

Prognostically relevant RNA expression states exist in pancreatic ductal adenocarcinoma (PDAC), but our understanding of their drivers, stability, and relationship to therapeutic response is limited. To examine these attributes systematically, we profiled metastatic biopsies and matched organoid models at single-cell resolution. In vivo, we identify a new intermediate PDAC transcriptional cell state and uncover distinct site- and state-specific tumor microenvironments (TMEs). Benchmarking models against this reference map, we reveal strong culture-specific biases in cancer cell transcriptional state representation driven by altered TME signals. We restore expression state heterogeneity by adding back in vivo-relevant factors and show plasticity in culture models. Further, we prove that non-genetic modulation of cell state can strongly influence drug responses, uncovering state-specific vulnerabilities. This work provides a broadly applicable framework for aligning cell states across in vivo and ex vivo settings, identifying drivers of transcriptional plasticity and manipulating cell state to target associated vulnerabilities.

DOI10.1016/j.cell.2021.11.017
Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/34890551?dopt=Abstract

Alternate JournalCell
PubMed ID34890551
PubMed Central IDPMC8822455
Grant ListU01 CA224146 / CA / NCI NIH HHS / United States
K99 CA241072 / CA / NCI NIH HHS / United States
U01 CA210171 / CA / NCI NIH HHS / United States
UL1 TR002541 / TR / NCATS NIH HHS / United States
U01 CA176058 / CA / NCI NIH HHS / United States
U2C CA233195 / CA / NCI NIH HHS / United States
U01 CA250549 / CA / NCI NIH HHS / United States
P50 CA127003 / CA / NCI NIH HHS / United States
U54 CA217377 / CA / NCI NIH HHS / United States
P30 CA014051 / CA / NCI NIH HHS / United States
K08 CA218420 / CA / NCI NIH HHS / United States