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Identifying transcriptional programs underlying cancer drug response with TraCe-seq

Identifying transcriptional programs underlying cancer drug response with TraCe-seq

Summary

Genetic and non-genetic heterogeneity internal most cancers cell populations signify important challenges to anticancer therapies. We currently lack noteworthy easy programs to be taught the intention preexisting and adaptive aspects personal an impact on cellular responses to therapies. Right here, by conducting clonal neatly being mapping and transcriptional characterization the usage of expressed barcodes and single-cell RNA sequencing (scRNA-seq), now we personal got developed monitoring differential clonal response by scRNA-seq (TraCe-seq). TraCe-seq is a model that captures at clonal resolution the origin, destiny and differential early adaptive transcriptional programs of cells in a advanced inhabitants per traipse remedies. We musty TraCe-seq to benchmark how subsequent-generation dual epidermal improve teach receptor (EGFR) inhibitor–degraders overview to original EGFR kinase inhibitors in EGFR-mutant lung most cancers cells. We identified a loss of antigrowth project connected to targeted degradation of EGFR protein and an compulsory role of the endoplasmic reticulum (ER) protein processing pathway in anti-EGFR therapeutic efficacy. Our results imply that targeted degradation is never any longer repeatedly superior to enzymatic inhibition and set TraCe-seq as an manner to scrutinize how preexisting transcriptional programs personal an impact on therapy responses.

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Info availability

All data generated or analyzed all by this scrutinize are deposited to the European Genome–Phenome Archive (EGAS00001005405) and ArrayExpress (E-MTAB-10698). Offer data are supplied with this paper.

Code availability

No custom algorithms personal been musty within the scrutinize. Corpulent code shall be made readily accessible upon quiz.

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Secure references

Acknowledgements

We thank E. Plise, M. Beresini, H. La and F. Hsu for helping with compound characterizations.

Author info

Author notes

  1. Sayumi Yamazoe

    Existing deal with: Discovery Biotherapeutics, Bristol-Myers Squibb, Redwood Metropolis, CA, USA

Affiliations

  1. Division of Computational Biology and Bioinformatics, Genentech Inc., South San Francisco, CA, USA

    Matthew T. Chang, Thi Thu Thao Nguyen & Robert Piskol

  2. Division of Discovery Oncology, Genentech Inc., South San Francisco, CA, USA

    Matthew T. Chang, Frances Shanahan, Ingrid E. Wertz, Marie Evangelista, Shiva Malek, Scott A. Foster & Xin Ye

  3. Division of Discovery Chemistry, Genentech Inc., South San Francisco, CA, USA

    Steven T. Staben, Lewis Gazzard & Sayumi Yamazoe

  4. Division of Early Discovery Biochemistry, Genentech Inc., South San Francisco, CA, USA

    Ingrid E. Wertz

  5. Division of Microchemistry, Proteomics and Lipidomics, Genentech Inc., South San Francisco, CA, USA

    Yeqing Angela Yang & Zora Modrusan

  6. Division of Molecular Biology, Genentech Inc., South San Francisco, CA, USA

    Benjamin Haley

Contributions

M.T.C., M.E., S.M., S.A.F. and X.Y. designed the scrutinize. Y.A.Y. and Z.M. designed and done scRNA-seq. M.T.C., T.T.T.N. and R.P. done the bioinformatics diagnosis. B.H. and X.Y. designed the TraCe-seq vector. F.S., S.A.F. and X.Y. done cell custom experiments. S.T.S., L.G. and I.E.W. designed the EGFR degraders. S.Y. synthesized the EGFR CIDEs. The manuscript used to be written by M.T.C., S.A.F. and X.Y. and incorporated contributions from all authors.

Corresponding authors

Correspondence to
Scott A. Foster or Xin Ye.

Ethics declarations

Competing interests

All authors are or personal been employed by Genentech Inc., South San Francisco, CA, USA, at the time of their contribution to this work.

Extra info

Gape evaluate info Nature Biotechnology thanks Leor Weinberger and the diverse, nameless, reviewer(s) for their contribution to the sight evaluate of this work.

Publisher’s stamp Springer Nature remains neutral almost about jurisdictional claims in printed maps and institutional affiliations.

Extended data

Extended Info Fig. 1 Quality alter metrics for TraCe-seq barcode restoration and assignment.

(a) Single-cell RNA-seq results got from a combination of 5 cell lines labeled with diverse TraCe-seq barcodes respectively personal been visualized the usage of UMAP. Clustering used to be done per transcriptomic differences (left) and annotated by TraCe-seq barcode assigned (correct). Majority of cells of a given TraCe-seq barcode designate corresponded to a explicit cell line/cluster. (b) Heatmaps of high 3 marker genes from every cluster per TraCe-seq annotation in bulk RNA-seq (left panel) and scRNA-seq (correct panel). (c) Violin plots exhibiting expression of marker genes in every cell line amongst the combination. (d) The panel on the left shows FACS enrichment for the stay 50% eGFP-expressing cells (n = 20,000 cells personal been plotted). The four panels on the correct point to dropout rate of TraCe-seq barcodes compared to endogenously expressed genes sooner than and after FACS sorting in NCI-H1373 (920 unsorted cells, 3,987 sorted cells) and PC9 (965 unsorted cells, 21,043 sorted cells) cells. The crimson aspects signify the TraCe-seq barcodes, and blue aspects signify groups of endogenous genes with the same median uncooked counts shown on the x-axis. Error bars specified 2 original deviations from the median dropout rate for the endogenous genes. (e) Box space exhibiting cells with mis-assigned TraCe-seq barcodes had vastly lower barcode-expression stage (MIS 473 cells, COR 1,562 cells). The underside aspect of the field represents the most important quartile, and the stay aspect, the third quartile. The toll road represents the median. p mark used to be particular the usage of two-tailed Student’s t-take a look at.

Extended Info Fig. 2 Characterization of GNE-104 and GNE-069.

(a) Western blot exhibiting dose-dependent EGFR degradation prompted by GNE-104 in HCC827 cells. This extended dilution sequence connected to panel (b) used to be only conducted as soon as. (b) Western blot exhibiting assemble on EGFR and pEGFR by GNE-104 versus GNE-069 in HCC827 cells. Outcomes are handbook of two just experiments. (c) Western blot exhibiting extra free VHL ligand inhibits GNE-104 prompted EGFR protein degradation in HCC827 cells, whereas no results personal been noticed for GNE-069. This experiment used to be repeated 2 times with identical results. (d) Characterization of the biochemical efficiency (in direction of original EGFR mutant variants) and selectivity (towards a panel of 218 kinases) of GNE-104 and GNE-069 in in vitro kinase inhibition assays.

Offer data

Extended Info Fig. 3 Characterization of the response of PC9 cells to erlotinib, GNE-069, and GNE-104.

(a) Heatmap and dendrogram exhibiting survival patterns of 500 diverse PC9 clones enviornment to erlotinib (2 µM) or GNE-104 (1 µM) therapy for two months. Clonal abundance used to be particular by NGS barcode analyses from genomic DNA. Barcode enrichment personal been extremely reproducible internal particular person therapy and differed between erlotinib and GNE-104 remedies. (b–d) Comparison of the anti-improve results of erlotinib, GNE-069, and GNE-104 in PC9 cells by (b) clonogenic assay, scale bar, 1 mm, (c) cell counting in triplicates (200 K cells per neatly in 6-neatly plates), and (d) Incucyte imaging, scale bar, 200 µm. All three compounds personal been utilized at 1 µM. The experiments personal been repeated thrice with identical results. Erlotinib and GNE-069 had similar project by all three measures, whereas GNE-104 used to be much less efficacious.

Extended Info Fig. 4 TraCe-seq barcode enrichment and depletion analyses.

(a) Deep NGS sequencing of TraCe-seq clonal abundance derived from genomic DNA (x-axis) correlates with scRNA-seq derived TraCe-seq clonal abundance (y-axis). Cutoff (crimson) shown of minimal TraCe-seq barcode for downstream clonal depletion analyses shown in panel (d). (b) Pairwise comparisons of TraCe-seq clonal abundance below diverse therapy circumstances, x and y-axes are abundance of a given TraCe-seq barcoded clone below indicated circumstances labeled at the stay and to the correct of the plots respectively. Pearson correlation coefficient of the barcode abundance distributions are shown. (c) Distribution of log2 fold alternate of TraCe-seq barcode in every therapy condition compared to baseline. (d) Heatmap exhibiting relative abundance of depleted TraCe-seq barcodes upon erlotinib, GNE-069, or GNE-104 remedies.

Extended Info Fig. 5 Clonogenic assay confirming differential project of EGFR kinase inhibitors versus degrader GNE-104.

(a) Clonogenic assay exhibiting differential anti-improve results of GNE-104 compared to erlotinib or GNE-069 all over four diverse EGFR-mutant lung most cancers cell lines. Scale bar, 1 mm. (b) Quantification of relative viability of the same four EGFR-mutant lung most cancers cell lines shown in panel (a) below degrader GNE-104 or non-degrader alter GNE-069 therapy relative to erlotinib over 14 days the usage of CellTiter-Glo luminescent cell viability assay. Experiments in (a, b) personal been spin in parallel. Outcomes are handbook of two–4 just experiments (relying upon the cell line). (c) Clonogenic assay exhibiting that high concentration of free VHL ligand (10 µM) did no longer personal an impact on cellular response to erlotinib or GNE-069 in PC9 cells. The VHL slothful enantiomer used to be incorporated as a extra alter. Scale bar, 2 mm. An analogous results personal been noticed the usage of two diverse vigorous VHL ligands.

Extended Info Fig. 6 Abundance of therapy resistant versus restful TraCe-seq barcodes amongst inferred trajectories.

(a) Density space exhibiting distribution of cells with kinase inhibitor resistant versus kinase inhibitor restful TraCe-seq barcodes within the UMAP command enviornment to erlotinib/GNE-069 therapy. Each grey dot represents an particular person cell. (b) Comparison of resistant versus restful barcode category distributions at the stay UMAP cluster of the four inferred trajectories. Path a, b, and c personal been every dominated by no longer no longer as much as one resistant clone category (inferred to signify adaptation/resistance), whereas Path d had the excellent relative abundance of drug restful clones thus personal been inferred to signify response. (c) Density space exhibiting distribution of cells with degrader resistant barcodes enviornment to GNE-104 therapy versus kinase inhibitor erlotinib/GNE-069 remedies. Each grey dot represents an particular person cell.

Extended Info Fig. 7 Extra characterization of cells treated with siEGFR and kinase inhibitors or osimertinib plus allosteric EGFR degrader.

(a) Schematic exhibiting the siEGFR experimental setup in PC9 and HCC4006 cells. (b) Western blot diagnosis of total EGFR and pEGFR enviornment to the indicated therapy for two days. The experiment used to be repeated 2 times with identical results. (c) Marketing consultant qRT-PCR diagnosis of key MAPK pathway transcriptional targets in PC9 cells treated below indicated circumstances for three days. (d) Marketing consultant qRT-PCR diagnosis of key transcription targets of MAPK pathway in HCC4006 cells below indicated circumstances for five days. (e) Clonogenic assay exhibiting siEGFR promoted survival of HCC4006 cells below EGFR kinase inhibitors erlotinib and osimertinib remedies. Scale bar, 1 mm. The experiment used to be repeated 4 times with identical results. (f) Marketing consultant qRT-PCR diagnosis of key transcriptional targets of the MAPK pathway in NCI-H1975 cells below indicated circumstances on day 3. N.D., no longer detected. All error bars within the bar graphs (c, d, and f) signify s.d., and the centers of the error bars signify the point out of n = 3 biologically dependent technical replicates. The experiments in panels c, d, and f personal been repeated 2 times (biologically just) with identical results.

Offer data

Extended Info Fig. 8 Characterization of GNE-640 and GNE-641.

(a) Chemical constructions of allosteric EGFR ligand EAI-045, GNE-641 (vigorous degrader), and GNE-640 (slothful degrader). (b) Western blot exhibiting that addition of the free VHL ligand can rescue the EGFR degradation upon GNE-641 therapy in NCI-H1975 cells. GNE-640 used to be incorporated as a extra alter. An analogous results personal been noticed with a connected vigorous/slothful EGFR allosteric degrader pair. (c) Clonogenic assay exhibiting very modest single agent project of EAI-045, GNE-640, or GNE-641 in NCI-H1975 cells compared to osimertinib. Scale bar, 1 mm. The experiment used to be repeated 2 times with identical results. (d) Quantifications exhibiting relative viability of NCI-H1975 cells co-treated with 0.1 µM osimertinib and 1 µM allosteric degrader GNE-641 (or non-degrader GNE-640) compared to treated with osimertinib by myself over 14 days the usage of CellTiter-Glo luminescent cell viability assay. Viability is normalized to osimertinib by myself. Outcomes are handbook of two just experiments. (e) Clonogenic assay exhibiting allosteric degrader GNE-641 but no longer the non-degrader alter GNE-640 promoted survival of NCI-H3255 cells below osimertinib therapy. Scale bar, 4 mm. The experiment used to be repeated 2 times with identical results.

Offer data

Extended Info Fig. 9 Pharmacological modulation of ER stress alters response to EGFR kinase inhibitors and degrader.

(a) Schematic exhibiting pharmacological modulators of ER stress pathway. (b) Marketing consultant qRT-PCR diagnosis of key pro-loss of life genes downstream of ER stress in HCC4006 cells below the indicated circumstances on day 5. (c) Marketing consultant qRT-PCR quantification of pro-loss of life integrated stress response genes downstream of ER stress and key transcriptional targets of the MAPK pathway in NCI-H1975 cells below indicated therapy circumstances on day 3. N.D., no longer detected. (d) Clonogenic assay exhibiting attenuation of osimertinib acitivity by ISRIB in NCI-H1975 cells. Scale bar, 1 mm. The experiment used to be repeated thrice with identical results. (e) Clonogenic assay exhibiting very low non-toxic doses of ER stress inducers effectively enhanced project of GNE-104. Scale bar, 1 mm. The experiment used to be repeated 4 times with identical results. (f) Marketing consultant qRT-PCR quantifications of key pro-loss of life genes downstream of ER stress in PC9 cells treated below the indicated circumstances on day 3. Error bars within the bar graphs (b, c, and f) signify s.d., and the centers of the error bars signify the point out of n = 3 biologically dependent technical replicates. The experiments in panel b, c personal been repeated 2 times (biologically just) and in panel f used to be repeated thrice (biologically just) with identical results.

Extended Info Fig. 10 PERK activator CCT020312 potentiates project of FDA-popular EGFR kinase inhibitors.

(a–c) Marketing consultant qRT-PCR quantification of pro-loss of life genes downstream of ER stress and MAPK purpose genes in PC9 cells (a, b) and NCI-H1975 cells (c) below the indicated circumstances on day 3. Error bars signify s.d., and the centers of the error bars signify the point out of n = 3 biologically dependent technical replicates. These experiments personal been repeated 2 times (biologically just) with identical results. (d) Quantification exhibiting EGFRi+CCT020312 combinations personal been more effective in inducing cell loss of life compared to the single brokers the usage of Caspase-Glo3/7 assay system. Error bars signify s.d., and the centers of the error bars signify the point out (n = 3 biologically just samples). The experiment used to be repeated 2 times with identical results.

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Chang, M.T., Shanahan, F., Nguyen, T.T.T. et al. Identifying transcriptional programs underlying most cancers drug response with TraCe-seq.
Nat Biotechnol (2021). https://doi.org/10.1038/s41587-021-01005-3

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