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

Cancer Cancer
Computational Methods Computational Methods
Genomics Genomics
Immunology Immunology
Medicine Medicine
R&D R&D
Technology Technology
Alex K. Shalek Alex K. Shalek
Andrew Navia Andrew Navia
Jennyfer Galvez-Reyes Jennyfer Galvez-Reyes
Nolawit Mulugeta Nolawit Mulugeta
Peter Winter Peter Winter

Raghavan et al.▾ Raghavan, S.*, Winter, P.S.*, Navia, A.W.*, Williams, H.L.*, DenAdel, A., Lowder, K.E., Galvez-Reyes, J., Kalekar, R.L., Mulugeta, N., Kapner, K.S., Raghavan, M.S., Borah, A.A., Liu, N., Vayrynen, S.A., Costa, A.D., Ng, R.W.S., Wang, J., Hill, E.K., Ragon, D.Y., Brais, L.K., Jaeger, A.M., Spurr, L.F., Li, Y.Y., Cherniack, A.D., Booker, M.A., Cohen, E.F., Tolstorukov, M.Y., Wakiro, I., Rotem, A., Johnson, B.E., McFarland, J.M., Sicinska, E.T., Jacks, T.E., Sullivan, R.J., Shapiro, G.I., Clancy, T.E., Perez, K., Rubinson, D.A., Ng, K., Cleary, J.M., Crawford, L., Manalis, S.R., Nowak, J.A., Wolpin, B.M.#, Hahn, W.C.#, Aguirre, A.J.#, Shalek, A.K.#

Cell , Volume 184

December, 2021

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.