Stepwise-edited, human melanoma models reveal mutations’ effect on tumor and microenvironment

Author:

Hodis Eran123ORCID,Triglia Elena Torlai1ORCID,Kwon John Y. H.12ORCID,Biancalani Tommaso1ORCID,Zakka Labib R.45,Parkar Saurabh1,Hütter Jan-Christian1,Buffoni Lorenzo1ORCID,Delorey Toni M.1ORCID,Phillips Devan1ORCID,Dionne Danielle1ORCID,Nguyen Lan T.1,Schapiro Denis16ORCID,Maliga Zoltan6ORCID,Jacobson Connor A.6ORCID,Hendel Ayal7ORCID,Rozenblatt-Rosen Orit1ORCID,Mihm Martin C.45,Garraway Levi A.12,Regev Aviv18ORCID

Affiliation:

1. Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.

2. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.

3. Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA.

4. Department of Dermatology, Brigham and Women’s Hospital, Boston, MA 02115, USA.

5. Harvard Medical School, Boston, MA 02115, USA.

6. Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.

7. The Mina and Everard Goodman Faculty of Life Sciences and Advanced Materials and Nanotechnology Institute, Bar-Ilan University, Ramat-Gan 52900, Israel.

8. Koch Institute for Integrative Cancer Research, Department of Biology, MIT, Cambridge, MA 02139, USA.

Abstract

Establishing causal relationships between genetic alterations of human cancers and specific phenotypes of malignancy remains a challenge. We sequentially introduced mutations into healthy human melanocytes in up to five genes spanning six commonly disrupted melanoma pathways, forming nine genetically distinct cellular models of melanoma. We connected mutant melanocyte genotypes to malignant cell expression programs in vitro and in vivo, replicative immortality, malignancy, rapid tumor growth, pigmentation, metastasis, and histopathology. Mutations in malignant cells also affected tumor microenvironment composition and cell states. Our melanoma models shared genotype-associated expression programs with patient melanomas, and a deep learning model showed that these models partially recapitulated genotype-associated histopathological features as well. Thus, a progressive series of genome-edited human cancer models can causally connect genotypes carrying multiple mutations to phenotype.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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