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Diverse alterations associated with resistance to KRAS(G12C) inhibition


Inactive state-selective KRAS(G12C) inhibitors1,2,3,4,5,6,7,8 demonstrate a 30–40% response rate and result in approximately 6-month median progression-free survival in patients with lung cancer9. The genetic basis for resistance to these first-in-class mutant GTPase inhibitors remains under investigation. Here we evaluated matched pre-treatment and post-treatment specimens from 43 patients treated with the KRAS(G12C) inhibitor sotorasib. Multiple treatment-emergent alterations were observed across 27 patients, including alterations in KRAS, NRAS, BRAF, EGFR, FGFR2, MYC and other genes. In preclinical patient-derived xenograft and cell line models, resistance to KRAS(G12C) inhibition was associated with low allele frequency hotspot mutations in KRAS(G12V or G13D), NRAS(Q61K or G13R), MRAS(Q71R) and/or BRAF(G596R), mirroring observations in patients. Single-cell sequencing in an isogenic lineage identified secondary RAS and/or BRAF mutations in the same cells as KRAS(G12C), where they bypassed inhibition without affecting target inactivation. Genetic or pharmacological targeting of ERK signalling intermediates enhanced the antiproliferative effect of G12C inhibitor treatment in models with acquired RAS or BRAF mutations. Our study thus suggests a heterogenous pattern of resistance with multiple subclonal events emerging during G12C inhibitor treatment. A subset of patients in our cohort acquired oncogenic KRAS, NRAS or BRAF mutations, and resistance in this setting may be delayed by co-targeting of ERK signalling intermediates. These findings merit broader evaluation in prospective clinical trials.

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Fig. 1: Genetic alterations associated with resistance to sotorasib treatment.
Fig. 2: Treatment-emergent alterations in preclinical models.
Fig. 3: Temporal tracking of treatment-emergent alterations.
Fig. 4: Effect of co-targeting ERK signalling intermediates.

Data availability

The data supporting the findings of this study are available within the paper and its supplementary information files. The data have been deposited in the Sequence Read Archive (PRJNA756044). Genomic and associated clinical data for patients are available in cBioPortal for Cancer Genomics at and/or may be requested by qualified researchers from Amgen clinical studies. Complete details are available at: Materials, reagents or other experimental data are available upon reasonable request from the corresponding author. Source data are provided with this paper.

Code availability

The analysis was performed using standard protocols with previously described computational tools. No custom code was used in this study.


  1. 1.

    Ostrem, J. M., Peters, U., Sos, M. L., Wells, J. A. & Shokat, K. M. K-Ras(G12C) inhibitors allosterically control GTP affinity and effector interactions. Nature 503, 548–551 (2013).

    ADS  CAS  Article  Google Scholar 

  2. 2.

    Lito, P., Solomon, M., Li, L. S., Hansen, R. & Rosen, N. Allele-specific inhibitors inactivate mutant KRAS G12C by a trapping mechanism. Science 351, 604–608 (2016).

    ADS  CAS  Article  Google Scholar 

  3. 3.

    Patricelli, M. P. et al. Selective inhibition of oncogenic KRAS output with small molecules targeting the inactive state. Cancer Discov. 6, 316–329 (2016).

    CAS  Article  Google Scholar 

  4. 4.

    Janes, M. R. et al. Targeting KRAS mutant cancers with a covalent G12C-specific inhibitor. Cell 172, 578–589.e17 (2018).

    CAS  Article  Google Scholar 

  5. 5.

    Canon, J. et al. The clinical KRAS(G12C) inhibitor AMG 510 drives anti-tumour immunity. Nature 575, 217–223 (2019).

    ADS  CAS  Article  Google Scholar 

  6. 6.

    Hallin, J. et al. The KRAS(G12C) inhibitor MRTX849 provides insight toward therapeutic susceptibility of KRAS-mutant cancers in mouse models and patients. Cancer Discov. 10, 54–71 (2020).

    CAS  Article  Google Scholar 

  7. 7.

    Kim, D., Xue, J. Y. & Lito, P. Targeting KRAS(G12C): from inhibitory mechanism to modulation of antitumor effects in patients. Cell 183, 850–859 (2020).

    CAS  Article  Google Scholar 

  8. 8.

    Xue, J. Y. et al. Rapid non-uniform adaptation to conformation-specific KRAS(G12C) inhibition. Nature 577, 421–425 (2020).

    ADS  CAS  Article  Google Scholar 

  9. 9.

    Hong, D. S. et al. KRAS(G12C) inhibition with sotorasib in advanced solid tumors. N. Engl. J. Med. 383, 1207–1217 (2020).

    CAS  Article  Google Scholar 

  10. 10.

    Pylayeva-Gupta, Y., Grabocka, E. & Bar-Sagi, D. RAS oncogenes: weaving a tumorigenic web. Nat. Rev. Cancer 11, 761–774 (2011).

    CAS  Article  Google Scholar 

  11. 11.

    Simanshu, D. K., Nissley, D. V. & McCormick, F. RAS proteins and their regulators in human disease. Cell 170, 17–33 (2017).

    CAS  Article  Google Scholar 

  12. 12.

    Karoulia, Z., Gavathiotis, E. & Poulikakos, P. I. New perspectives for targeting RAF kinase in human cancer. Nat. Rev. Cancer 17, 676–691 (2017).

    CAS  Article  Google Scholar 

  13. 13.

    Riely, G. J. et al. Frequency and distinctive spectrum of KRAS mutations in never smokers with lung adenocarcinoma. Clin. Cancer Res. 14, 5731–5734 (2008).

    CAS  Article  Google Scholar 

  14. 14.

    Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature 511, 543-550 (2014).

    ADS  Article  Google Scholar 

  15. 15.

    Riely, G. J. et al. 99O_PR KRYSTAL-1: activity and preliminary pharmacodynamic (PD) analysis of adagrasib (MRTX849) in patients (Pts) with advanced non-small cell lung cancer (NSCLC) harboring KRASG12C mutation. J. Thoracic Oncol. 16, S751–S752 (2020).

  16. 16.

    Misale, S. et al. KRAS G12C NSCLC models are sensitive to direct targeting of KRAS in combination with PI3K inhibition. Clin. Cancer Res. 25, 796–807 (2019).

    CAS  Article  Google Scholar 

  17. 17.

    Boned Del Rio, I. et al. SHOC2 complex-driven RAF dimerization selectively contributes to ERK pathway dynamics. Proc. Natl Acad. Sci. USA 116, 13330–13339 (2019).

    Article  Google Scholar 

  18. 18.

    Jones, G. G. et al. SHOC2 phosphatase-dependent RAF dimerization mediates resistance to MEK inhibition in RAS-mutant cancers. Nat. Commun. 10, 2532 (2019).

    ADS  Article  Google Scholar 

  19. 19.

    Wohlhieter, C. A. et al. Concurrent mutations in STK11 and KEAP1 promote ferroptosis protection and SCD1 dependence in lung cancer. Cell Rep. 33, 108444 (2020).

    CAS  Article  Google Scholar 

  20. 20.

    Gao, Y. et al. V211D mutation in MEK1 causes resistance to MEK inhibitors in colon cancer. Cancer Discov. 9, 1182–1191 (2019).

    CAS  Article  Google Scholar 

  21. 21.

    Miles, L. A. et al. Single-cell mutation analysis of clonal evolution in myeloid malignancies. Nature 587, 477–482 (2020).

    ADS  CAS  Article  Google Scholar 

  22. 22.

    Pellegrino, M. et al. High-throughput single-cell DNA sequencing of acute myeloid leukemia tumors with droplet microfluidics. Genome Res. 28, 1345–1352 (2018).

    CAS  Article  Google Scholar 

  23. 23.

    Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    CAS  Article  Google Scholar 

  24. 24.

    Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009).

    Article  Google Scholar 

  25. 25.

    Kim, D. et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 14, R36 (2013).

    Article  Google Scholar 

  26. 26.

    Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    Article  Google Scholar 

  27. 27.

    McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

    CAS  Article  Google Scholar 

  28. 28.

    Cheng, D. T. et al. Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT): a hybridization capture-based next-generation sequencing clinical assay for solid tumor molecular oncology. J. Mol. Diagn. 17, 251–264 (2015).

    CAS  Article  Google Scholar 

  29. 29.

    Zehir, A. et al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nat. Med. 23, 703–713 (2017).

    CAS  Article  Google Scholar 

  30. 30.

    Xue, Y. et al. An approach to suppress the evolution of resistance in BRAF(V600E)-mutant cancer. Nat. Med. 23, 929–937 (2017).

    CAS  Article  Google Scholar 

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We thank M. Mroczkowski for her insight on the manuscript. We also thank C. Rudin for providing STK11 and KEAP1 knockout cells and G. Caponigro for providing LXH254. P.L. is supported in part by the NIH/NCI (1R01CA23074501 and 1R01CA23026701A1), the Pew Charitable Trusts, the Damon Runyon Cancer Research Foundation and the American Lung Association. Y.Z. is supported in part by the Charles H. Revson Senior Fellowship in Biomedical Science (21-31). J.Y.X. is supported in part by the NRSA F30 program (1F30CA232549-01). E.d.S. is supported in part by the MSKCC Pilot Center for Precision Disease Modeling program (U54 OD020355). K.C.A. is supported in part by a Career Development Award from the LUNGevity foundation. J.S.R.-F. is supported in part by the Breast Cancer Research Foundation and Gerald Leigh Charitable Trust. B.W. is supported in part by Cycle for Survival and Breast Cancer Research Foundation grants. J.R.-F. and B.W. are supported in part by the NIH/NCI P50 CA247749 01 grant. Y.R.M.-G. is supported by a Young Investigator Award from Conquer Cancer from the ASCO Foundation and has received training through an institutional K30 grant (CTSA UL1TR00457). We acknowledge the Josie Robertson Investigator Program at MSKCC, a Medical Scientist Training Program grant to the Weill Cornell–Rockefeller–Sloan Kettering Tri-Institutional MD-PhD Program (T32GM007739) and the MSKCC Support Grant-Core Grant program (P30 CA008748). We also acknowledge the use of the Integrated Genomics Operation Core, funded by the NCI Cancer Center Support Grant (P30 CA08748), Cycle for Survival, and the Marie-Josée and Henry R. Kravis Center for Molecular Oncology. Clinical study funding was provided by Amgen Inc.

Author information




Y.Z., Y.R.M.-G., J.Y.X., A.A., J.R.L., B.T.L. and P.L. designed the study and analysed the data. Y.Z., J.Y.X, J.L., T.T.M., R.S.R., D.K. and C.L. performed the experiments and/or provided key scientific input. A.B. and E.d.S. helped perform in vivo studies. Y.R.M.-G., K.C.A., A.E.S., G.R. and B.T.L. helped to identify clinical specimens and carried out chart review for emergent alterations. A.A. and J.R.L. helped to carry out review of the clinical trial repository to identify emergent alterations. A.Y.S., D.M., P.A. and J.R.L. performed data collection and analysis. A.F.D.C.P., B.W. and J.S.R.-F. helped to carry out single-cell DNA sequencing. K.S.A., B.R.L. and M.B. helped to carry out bulk sequencing studies and data analysis. Y.Z., Y.R.M.-G., J.Y.X., A.A. and P.L. were the main writers of the manuscript. All other authors reviewed the manuscript and contributed to writing it.

Corresponding author

Correspondence to Piro Lito.

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Competing interests

P.L. reports grants to his institution from Amgen, Mirati, Revolution Medicines, Boehringer Ingelheim and Virtec Pharmaceuticals; is listed as an inventor on patents filed by MSKCC on the treatment of BRAF-mutant or KRAS-mutant cancers; and reports consulting fees from Black Diamond Therapeutics, AmMax Bio, Repare Therapeutics and compensated scientific advisory board activity in Revolution Medicines and Boehringer Ingelheim. J.S.R.-F. reports receiving personal/consultancy fees from Goldman Sachs, REPARE Therapeutics, Paige.AI and Eli Lilly; holds membership of the scientific advisory boards of VolitionRx, REPARE Therapeutics and Paige.AI, membership of the Board of Directors of Grupo Oncoclinicas, and ad hoc membership of the scientific advisory boards of Roche Tissue Diagnostics, Ventana Medical Systems, Novartis, Genentech and InVicro, outside the scope of this study; and owns Paige.AI and REPARE Therapeutic stocks. Y.R.M.-G. received support for travel, accommodation and expenses from AstraZeneca. M.B. reports consulting fees from Roche and Eli Lilly. A.A., A.S., D.M., P.A. and J.R.L. are employees and shareholders of Amgen Inc. All other authors declare no competing interests.

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Extended data figures and tables

Extended Data Fig. 1 Characteristics of patients with lung cancer with an exceptional response to sotorasib treatment.

a, Percent of patients with baseline alterations in the indicated genes. No significant differences by Fisher exact test. b, KRAS(G12C) allele frequency in baseline plasma specimens. c, As in b but only patients with available archival/baseline tissue are plotted. d, Baseline tumour burden, as determined by the sum of the longest diameter in RECIST target lesions. Two tailed p values from Mann-Whitney tests are shown in bd. The lines denote median values. In a, b and d: n = 8 (CR/LTR) and n = 28 (Other) patients, whereas in c: n = 5 (CR/LTR) and n = 8 (Other) patients.

Source data

Extended Data Fig. 2 Treatment-emergent alterations in patient-derived xenograft models.

a, PDX-bearing mice were treated with sotorasib (100 mpk, Lu1, Lu10), adagrasib (100 mpk, Lu3, Lu7, Re1, Co1) or MRTX1257 (50 mpk, Lu36, Lu69). The dotted line represents a tumour size of ~500 mm3, which was used to determine latency (n = 4, mean ± s.e.m.). b, Characteristics of patient derived xenograft models. c, d, VAFs or estimated copy numbers for the indicated variants (c) or genes (d). A large number of mutations were identified in Lu36, including several BRAF alterations. Re1 had a baseline BRAF(E26D) variant, which has been reported as germline. See Supplementary Data 3 for a complete list of alterations.

Source data

Extended Data Fig. 3 Characterization of cell lines with acquired G12Ci resistance.

a, G12Ci-sensitive lung cancer cells (H358) were selected in the absence (H358T) or in the presence of G12Ci-treatment (see Methods), either in cell-culture (1M) or in athymic mice followed by cell-culture (R1, R2). b, The indicated cell lines were treated with sotorasib (left) or adagrasib (right) for 72h to determine the effect on cell proliferation (n = 3, mean ± s.e.m). c, d, Resistant (1M, R1, R2) or parental (P) cells were treated with the indicated inhibitors for two weeks to determine the effect of cell viability by crystal violet staining. A representative of two independent experiments is shown. e, Athymic mice bearing parental (H358T, Par) or resistant (R1, R2) cell line xenografts were treated with vehicle or MRTX1257 (50 mpk) to determine the effect on tumour growth (n = 5, mean ± s.e.m). f, g, The indicated cell lines were treated with increasing concentrations of sotorasib for 2 h (f) or with 1μM over time (g). The effect on KRAS signalling was determined by immunoblotting. A representative of at least two independent experiments for each cell line is shown. For gel source data, see Supplementary Fig. 1.

Source data

Extended Data Fig. 4 Single-cell modelling of G12Ci-resistant models.

a, Boxplots (median, upper and lower quartiles, and outliers) showing the distribution of the allele frequency (VAF) for the indicated variants across subclonal populations in G12Ci-resistant models. b, A neighbour-joining tree showing the relationship of the single-cells originating from the indicated parental or resistant models. The circular heat map indicates the presence (blue) or absence (white) of the indicated variants in each single cell.

Source data

Extended Data Fig 5 Secondary RAS mutations in the absence of KRAS-directed therapy.

a, Heat map of 304 KRAS-mutant biopsy specimens harbouring multiple RAS variants. b, Alluvial plot showing the pairings of mutations across samples. Residues with cancer-associated hotspot mutations are labelled. c, As in a but only KRAS(G12C) mutant samples are shown. d, Frequency of 2oRAS mutations in samples with KRAS(G12C) (left) or any KRAS mutation (right). All specimens were sequenced using MSK-IMPACT.

Source data

Extended Data Fig. 6 Propensity of treatment-emerging alterations to attenuate KRAS(G12C) inhibition.

ag, H358 cells expressing the indicated variants under dox-inducible promoters (af) or H358 cells with CRISPR/CAS9 mediated deletion of KEAP1 or STK11 (g, ref. 19.), were treated as shown to determine the effect on signalling intermediates by immunoblotting (a) or cell viability (bg) using cell titre glow. In bf, n = 3, in g, n = 4. Mean ± s.e.m. are shown. A representative of at least two independent experiments is shown. For gel source data of a, see Supplementary Fig. 1.

Source data

Extended Data Fig. 7 Progressive attenuation of KRAS(G12C) singling inhibition during drug selection.

a, b, KRAS(G12C) mutant cells were expanded in the presence of G12Ci-treatment to establish isogenic lineages (1M, R1 and R2) with acquired resistance. Serial passages (p) from the indicated lineages were assayed to determine the magnitude and duration of ERK inhibition (a) or cleaved PARP induction (b) after drug re-challenge for 0-72h. In the 1M series, p15 and p25 denote passages when the selection drug concentration was increased. The experiment was carried out several passages later. p0 denotes parental cells. pERK and cPARP immunoblots were quantified with imageJ and their expression level was normalized to time 0. c, Unlabelled parental (H358) cells and BFP-labelled derivatives expressing dox-inducible NRAS(Q61K) were co-cultured in the presence of dox and/or sotorasib for 72h (n = 4, mean ± s.e.m). d, Parental H358 cells or their derivatives expressing NRAS(Q61K) (100%) were treated in the presence of sotorasib in the presence or absence of dox for 72h (n = 4, mean ± s.e.m.). Norm: min-max normalization. e, f, RFP-labelled parental (H358) cells and GFP-labelled derivatives expressing dox-inducible NRAS(Q61K) were co-cultured in the presence of dox and/or sotorasib for 72h to determine the distribution of subpopulations (e) by FACS (n = 20,000 independent single cells) and the effect of the minor 2oNRAS subclone on the major KRAS(G12C)-mutant parental subpopulation (f). A representative of two independent experiments is shown in e, f.

Source data

Extended Data Fig. 8 Selective vulnerabilities in resistant cells harbouring KRAS and NRAS mutations.

a, Parental H358 (sensitive) and R1 (resistant) cells expressing CAS9 were transfected with a genome-wide sgRNA library. The cells were treated in triplicate with either DMSO or G12Ci (sotorasib, 1 µM) for 14 days. The scaled mean expression of four independent sgRNAs targeting the indicate genes is shown. b, c, Parental or resistant cells expressing control (sgNT) or SHOC2-specific sgRNAs were subjected to immunoblotting to determine the expression of SHOC2 (b) or the effect on the indicated signalling intermediates (c). df, Parental (d), R1 (e) and R2 (f) cells were treated with either DMSO or sotorasib for 10 days to determine the effect on cell number (n = 4, mean ± s.e.m). gh, R1 cells expressing NRAS-specific siRNAs were treated with sotorasib for the indicated times to determine the effect on signalling intermediates (g) or proliferation (h, n = 6, mean ± s.e.m). A representative of at least two independent experiments is shown. For gel source data, see Supplementary Fig. 1.

Source data

Extended Data Fig. 9 Co-targeting ERK-signalling enhances KRAS(G12C) inhibition in models harbouring secondary RAS/BRAF mutations.

a, b, The indicated models were treated with sotorasib (1 µM) in combination with trametinib (25 nM, a) or LXH254 (2 µM; b) to determine the effect on ERK signalling intermediates. For gel source data, see Supplementary Fig. 1. c, Resistant and parental cell lines were treated with G12Ci (sotorasib, 1 µM; adagrasib, 200 nM or MRTX1257, 200 nM) in combination with a RAFdi (LXH254, 2µM), MEKi (trametinib, 50 nM) or ERKi (SCH984, 500 nM) to determine the effect on cell viability. df, H358 cells expressing the dox-induced variants shown were treated with sotorasib (1 µM) alone or in combination with the noted inhibitors to determine the effect on cell viability over time, using cell titre glow (d, n = 4 and e, n = 6; mean is shown) or crystal violet staining (f, 10 days). A representative of two independent repeats is shown.

Source data

Extended Data Fig. 10 Targeting KRAS(G12C) in combination with MAPK intermediates in vivo.

Mice bearing the indicated cell line (a, n = 5, mean ± s.e.m.) or patient-derived xenograft (b, n = 4, mean ± s.e.m.) were treated with the inhibitors shown to determine the effect on tumour growth. Fractional differences in tumour volume over time are shown.

Source data

Supplementary information

Supplementary Information

A merged PDF containing: Supplementary Discussion; Supplementary References (31–43);Supplementary Table 1 (primers for amplicon sequencing); Supplementary Fig. 1 (images of western blots).

Reporting Summary

Supplementary Data 1

Additional clinical information on patients treated with sotorasib.

Supplementary Data 2

Single-cell sequencing data of parental H358 and G12Ci resistant cell lines.

Supplementary Data 3

Bulk targeted exome sequencing of PDX models.

Supplementary Data 4

Bulk sequencing data for parental H358 and G12Ci resistant cell lines.

Supplementary Data 5

Raw counts and analysed data from sgRNA screens in parental H358 and R1 resistant cells.

Source data

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Zhao, Y., Murciano-Goroff, Y.R., Xue, J.Y. et al. Diverse alterations associated with resistance to KRAS(G12C) inhibition. Nature 599, 679–683 (2021).

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