Francisco J. Sánchez-Rivera

Francisco J. Sánchez-Rivera

Eisen and Chang Career Development Professor; Intramural Faculty, Koch Institute

Francisco J. Sánchez-Rivera aims to understand how genetic variation shapes normal physiology and disease, with a focus on cancer.

617-715-3389

Phone

76-361A

Office

fsr@mit.edu

Email

Koch Institute for Integrative Cancer Research

Location

Lab Website
Paul Thompson

Assistant

617-258-0480

Assistant Phone

Education

  • PhD, 2016, Biology, MIT
  • BS, 2008, Microbiology, University of Puerto Rico at Mayagüez

Research Summary

The overarching goal of the Sánchez-Rivera laboratory is to elucidate the cellular and molecular mechanisms by which genetic variation shapes normal physiology and disease, particularly in the context of cancer. To do so, we develop and apply genome engineering technologies, genetically-engineered mouse models (GEMMs), and single cell lineage tracing and omics approaches to obtain comprehensive biological pictures of disease evolution at single cell resolution. By doing so, we hope to produce actionable discoveries that could pave the way for better therapeutic strategies to treat cancer and other diseases.

Awards

  • V Foundation Award, 2022
  • Hanna H. Gray Fellowship, Howard Hughes Medical Institute, 2018-2026
  • GMTEC Postdoctoral Researcher Innovation Grant, Memorial Sloan Kettering Cancer Center, 2020-2022
  • 100 inspiring Hispanic/Latinx scientists in America, Cell Mentor/Cell Press, 2020

Key Publications

  1. High-throughput evaluation of genetic variants with prime editing sensor libraries. Gould, SI, Wuest, AN, Dong, K, Johnson, GA, Hsu, A, Narendra, VK, Atwa, O, Levine, SS, Liu, DR, Sánchez Rivera, FJ et al.. 2025. Nat Biotechnol 43, 1648-1662.
    doi: 10.1038/s41587-024-02172-9PMID:38472508
  2. A prime editor mouse to model a broad spectrum of somatic mutations in vivo. Ely, ZA, Mathey-Andrews, N, Naranjo, S, Gould, SI, Mercer, KL, Newby, GA, Cabana, CM, Rideout, WM 3rd, Jaramillo, GC, Khirallah, JM et al.. 2024. Nat Biotechnol 42, 424-436.
    doi: 10.1038/s41587-023-01783-yPMID:37169967
  3. Base editing sensor libraries for high-throughput engineering and functional analysis of cancer-associated single nucleotide variants. Sánchez-Rivera, FJ, Diaz, BJ, Kastenhuber, ER, Schmidt, H, Katti, A, Kennedy, M, Tem, V, Ho, YJ, Leibold, J, Paffenholz, SV et al.. 2022. Nat Biotechnol 40, 862-873.
    doi: 10.1038/s41587-021-01172-3PMID:35165384
  4. Keap1 mutation renders lung adenocarcinomas dependent on Slc33a1. Romero, R, Sánchez-Rivera, FJ, Westcott, PMK, Mercer, KL, Bhutkar, A, Muir, A, González Robles, TJ, Lamboy Rodríguez, S, Liao, LZ, Ng, SR et al.. 2020. Nat Cancer 1, 589-602.
    doi: 10.1038/s43018-020-0071-1PMID:34414377
  5. Rapid modelling of cooperating genetic events in cancer through somatic genome editing. Sánchez-Rivera, FJ, Papagiannakopoulos, T, Romero, R, Tammela, T, Bauer, MR, Bhutkar, A, Joshi, NS, Subbaraj, L, Bronson, RT, Xue, W et al.. 2014. Nature 516, 428-31.
    doi: 10.1038/nature13906PMID:25337879

Recent Publications

  1. Dominant-negative TP53 mutations potentiated by the HSF1-regulated proteostasis network. Halim, S, Sebastian, RM, Liivak, KE, Patrick, JE, Hui, T, Amici, DR, Giacomelli, AO, Rios, P, Butty, VL, Hahn, WC et al.. 2026. Mol Cell 86, 345-361.e6.
    doi: 10.1016/j.molcel.2025.12.013PMID:41539306
  2. Nutrient requirements of organ-specific metastasis in breast cancer. Abbott, KL, Subudhi, S, Ferreira, R, Gültekin, Y, Steinbuch, SC, Munim, MB, Ramesh, DL, Honeder, SE, Kumar, AS, Wu, M et al.. 2026. Nature , .
    doi: 10.1038/s41586-025-09898-9PMID:41501456
  3. CAR-adapted PIK3CD base editing enhances T cell anti-tumor potency. Bucher, P, Brückner, N, Kortendieck, J, Grimm, M, Schleicher, JT, Bartels, K, Hardy, S, Rausch, M, Wurzer, H, Thiemann, M et al.. 2026. Nat Cancer , .
    doi: 10.1038/s43018-025-01099-7PMID:41495526
  4. Publisher Correction: Computational prediction of human genetic variants in the mouse genome. Dong, K, Gould, SI, Li, M, Sánchez Rivera, FJ. 2025. Nat Biotechnol , .
    doi: 10.1038/s41587-025-02991-4PMID:41466062
  5. Computational prediction of human genetic variants in the mouse genome. Dong, K, Gould, SI, Li, M, Sánchez Rivera, FJ. 2025. Nat Biotechnol , .
    doi: 10.1038/s41587-025-02925-0PMID:41413243
  6. Mutant p53: evolving perspectives. Efe, G, Cunningham, K, Rustgi, AK, Prives, C, Manfredi, JJ, Sánchez-Rivera, FJ. 2026. Genes Dev 40, 4-25.
    doi: 10.1101/gad.353408.125PMID:41397879
  7. A functional map of CDK-drug interactions at single amino acid resolution. Gould, SI, Acosta, J, Bielo, LB, Jaboldinov, A, Johnson, GA, Contreras, ME, Wuest, AN, Brémont, E, Toure, MA, Xiang, Y et al.. 2025. bioRxiv , .
    doi: 10.1101/2025.11.02.685764PMID:41279360
  8. A specific form of cPRC1 containing CBX4 is co-opted to mediate oncogenic gene repression in diffuse midline glioma. Lagan, E, Gannon, D, Silva, AJ, Bibawi, P, Doherty, AM, Nimmo, D, McCole, R, Monger, C, Genesi, GL, Vanderlinden, A et al.. 2025. Mol Cell 85, 2110-2127.e7.
    doi: 10.1016/j.molcel.2025.04.026PMID:40403727
  9. It's prime time for multiplexed prime editing. Wu, K, Sánchez-Rivera, FJ. 2025. Cell Genom 5, 100852.
    doi: 10.1016/j.xgen.2025.100852PMID:40209678
  10. Using Prime Editing Guide Generator (PEGG) for high-throughput generation of prime editing sensor libraries. Gould, SI, Sánchez-Rivera, FJ. 2025. Methods Enzymol 712, 437-451.
    doi: 10.1016/bs.mie.2025.01.006PMID:40121083
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Photo credit: Adam Lerner