Abstract
Colorectal cancer (CRC) patient-derived organoids predict responses to chemotherapy. Here we used them to investigate relapse after treatment. Patient-derived organoids expand from highly proliferative LGR5+ tumor cells; however, we discovered that lack of optimal growth conditions specifies a latent LGR5+ cell state. This cell population expressed the gene MEX3A, is chemoresistant and regenerated the organoid culture after treatment. In CRC mouse models, Mex3a+ cells contributed marginally to metastatic outgrowth; however, after chemotherapy, Mex3a+ cells produced large cell clones that regenerated the disease. Lineage-tracing analysis showed that persister Mex3a+ cells downregulate the WNT/stem cell gene program immediately after chemotherapy and adopt a transient state reminiscent to that of YAP+ fetal intestinal progenitors. In contrast, Mex3a-deficient cells differentiated toward a goblet cell-like phenotype and were unable to resist chemotherapy. Our findings reveal that adaptation of cancer stem cells to suboptimal niche environments protects them from chemotherapy and identify a candidate cell of origin of relapse after treatment in CRC.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
RNA-seq data and microarray expression data that support the findings of this study have been deposited at GEO under accession numbers GSE163171, GSE187650, GSE163035 and GSE187512. scRNA-seq experiments were deposited in ArrayExpress under accession numbers E-MTAB-11145 and E-MTAB-11146. Previously published scRNA-seq data of CRC patient samples that were reanalyzed here are available at GEO under accession codes GSE132465, GSE132257 and GSE144735 and at ArrayExpress under code E-MTAB-8107. Previously published bulk RNA-seq and microarray expression data of CRC patient samples reanalyzed here are available at GEO under accession codes GSE14333 and GSE39582 and at TCGA Research Network (http://cancergenome.nih.gov/) under code TCGA-COAD. Previously published driver mutation data of CRC patient samples from the MSK-Impact cohort (v.crc_msk_2018) reanalyzed here are available at cBioPortal (https://www.cbioportal.org/). All other data supporting the findings of this study are available from the corresponding author on reasonable request. Source data are provided with this paper.
References
Van Cutsem, E., Cervantes, A., Nordlinger, B. & Arnold, D. The ESMO Guidelines Working Group. Metastatic colorectal cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 25, iii1–iii9 (2014).
Argilés, G. et al. Localised colon cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 31, 1291–1305 (2020).
Russo, M. et al. Adaptive mutability of colorectal cancers in response to targeted therapies. Science 366, 1473–1480 (2019).
Boumahdi, S. & de Sauvage, F. J. The great escape: tumour cell plasticity in resistance to targeted therapy. Nat. Rev. Drug Discov. 19, 39–56 (2020).
Shen, S., Vagner, S. & Robert, C. Persistent cancer cells: the deadly survivors. Cell 183, 860–874 (2020).
Rehman, S. K. et al. Colorectal cancer cells enter a diapause-like DTP state to survive chemotherapy. Cell 184, 226–242 (2021).
Dhimolea, E. et al. An embryonic diapause-like adaptation with suppressed myc activity enables tumor treatment persistence. Cancer Cell 39, 240–256 (2021).
Ooft, S. N. et al. Patient-derived organoids can predict response to chemotherapy in metastatic colorectal cancer patients. Sci. Transl. Med. 11, eaay2574 (2019).
Vlachogiannis, G. et al. Patient-derived organoids model treatment response of metastatic gastrointestinal cancers. Science 359, 920–926 (2018).
Ganesh, K. et al. A rectal cancer organoid platform to study individual responses to chemoradiation. Nat. Med. 25, 1607–1614 (2019).
Yao, Y. et al. Patient-derived organoids predict chemoradiation responses of locally advanced rectal cancer. Cell Stem Cell 26, 17–26 (2020).
Fujii, M. et al. A colorectal tumor organoid library demonstrates progressive loss of niche factor requirements during tumorigenesis. Cell Stem Cell 18, 827–838 (2016).
Sato, T. et al. Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal niche. Nature 459, 262–265 (2009).
Jung, P. et al. Isolation and in vitro expansion of human colonic stem cells. Nat. Med. 17, 1225–1227 (2011).
Sato, T. et al. Long-term expansion of epithelial organoids from human colon, adenoma, adenocarcinoma, and Barrett’s epithelium. Gastroenterology 141, 1762–1772 (2011).
van de Wetering, M. et al. Prospective derivation of a living organoid biobank of colorectal cancer patients. Cell 161, 933–945 (2015).
Batlle, E. & Clevers, H. Cancer stem cells revisited. Nat. Med. 23, 1124–1134 (2017).
Matano, M. et al. Modeling colorectal cancer using CRISPR–Cas9-mediated engineering of human intestinal organoids. Nat. Med. 21, 256–262 (2015).
Fumagalli, A. et al. Genetic dissection of colorectal cancer progression by orthotopic transplantation of engineered cancer organoids. Proc. Natl Acad. Sci. USA 114, E2357–E2364 (2017).
O’Rourke, K. P. et al. Transplantation of engineered organoids enables rapid generation of metastatic mouse models of colorectal cancer. Nat. Biotechnol. 35, 577–582 (2017).
Tauriello, D. V. F. et al. TGF-β drives immune evasion in genetically reconstituted colon cancer metastasis. Nature 554, 538–543 (2018).
Muzny, D. M. et al. Comprehensive molecular characterization of human colon and rectal cancer. Nature 487, 330–337 (2012).
Ayyaz, A. et al. Single-cell transcriptomes of the regenerating intestine reveal a revival stem cell. Nature 569, 121–125 (2019).
Nusse, Y. M. et al. Parasitic helminths induce fetal-like reversion in the intestinal stem cell niche. Nature 559, 109–113 (2018).
Han, T. et al. Lineage reversion drives WNT Independence in intestinal cancer. Cancer Discov. 10, 1590–1609 (2020).
Lupo, B. et al. Colorectal cancer residual disease at maximal response to EGFR blockade displays a druggable Paneth cell-like phenotype. Sci. Transl. Med. 12, eaax8313 (2020).
Barriga, F. M. et al. Mex3a marks a slowly dividing subpopulation of Lgr5+ intestinal stem cells. Cell Stem Cell 20, 801–816 (2017).
Morral, C. et al. Zonation of ribosomal DNA transcription defines a stem cell hierarchy in colorectal cancer. Cell Stem Cell 26, 845–861 (2020).
McFall, T. et al. A systems mechanism for KRAS mutant allele-specific responses to targeted therapy. Sci. Signal. 12, eaaw8288 (2019).
Herpers, B. et al. Functional patient-derived organoid screenings identify MCLA-158 as a therapeutic EGFR × LGR5 bispecific antibody with efficacy in epithelial tumors. Nat. Cancer 3, 418–436 (2022).
Cortina, C. et al. A genome editing approach to study cancer stem cells in human tumors. EMBO Mol. Med. 9, 869–879 (2017).
Lee, H.-O. et al. Lineage-dependent gene expression programs influence the immune landscape of colorectal cancer. Nat. Genet. 52, 594–603 (2020).
Barker, N. et al. Identification of stem cells in small intestine and colon by marker gene Lgr5. Nature 449, 1003–1007 (2007).
Schepers, A. G. et al. Lineage tracing reveals Lgr5+ stem cell activity in mouse intestinal adenomas. Science 337, 730–735 (2012).
Kozar, S. et al. Continuous clonal labeling reveals small numbers of functional stem cells in intestinal crypts and adenomas. Cell Stem Cell 13, 626–633 (2013).
Pereira, B. et al. MEX3A regulates Lgr5+ stem cell maintenance in the developing intestinal epithelium. EMBO Rep. 21, e48938 (2020).
Shimokawa, M. et al. Visualization and targeting of LGR5+ human colon cancer stem cells. Nature 545, 187–192 (2017).
Qu, M. et al. Establishment of intestinal organoid cultures modeling injury-associated epithelial regeneration. Cell Res. 31, 259–271 (2021).
Yui, S. et al. YAP/TAZ-dependent reprogramming of colonic epithelium links ECM remodeling to tissue regeneration. Cell Stem Cell 22, 35–49 (2018).
Mustata, R. C. et al. Identification of Lgr5-independent spheroid-generating progenitors of the mouse fetal intestinal epithelium. Cell Rep. 5, 421–432 (2013).
Kreso, A. et al. Variable clonal repopulation dynamics influence chemotherapy response in colorectal cancer. Science 339, 543–548 (2013).
de Sousa e Melo, F. et al. A distinct role for Lgr5+ stem cells in primary and metastatic colon cancer. Nature 543, 676–680 (2017).
Puig, I. et al. TET2 controls chemoresistant slow-cycling cancer cell survival and tumor recurrence. J. Clin. Invest. 128, 3887–3905 (2018).
Touil, Y. et al. Colon cancer cells escape 5FU chemotherapy-induced cell death by entering stemness and quiescence associated with the c-Yes/YAP axis. Clin. Cancer Res. 20, 837–846 (2014).
Hu, Z. et al. Quantitative evidence for early metastatic seeding in colorectal cancer. Nat. Genet. 51, 1113–1122 (2019).
De Conti, G., Dias, M. H. & Bernards, R. Fighting drug resistance through the targeting of drug-tolerant persister cells. Cancers 13, 1118 (2021).
Marine, J.-C., Dawson, S.-J. & Dawson, M. A. Non-genetic mechanisms of therapeutic resistance in cancer. Nat. Rev. Cancer 20, 743–756 (2020).
Seber, G. A. F. & Wild, C. J. Nonlinear Regression (John Wiley & Sons, 1989).
Ritz, C., Baty, F., Streibig, J. C. & Gerhard, D. Dose–response analysis using R. PLoS ONE 10, e0146021 (2016).
El Marjou, F. et al. Tissue-specific and inducible Cre-mediated recombination in the gut epithelium. Genesis 39, 186–193 (2004).
Colnot, S. et al. Liver-targeted disruption of Apc in mice activates β-catenin signaling and leads to hepatocellular carcinomas. Proc. Natl Acad. Sci. USA 101, 17216–17221 (2004).
Lombardo, Y. et al. Bone morphogenetic protein 4 induces differentiation of colorectal cancer stem cells and increases their response to chemotherapy in mice. Gastroenterology 140, 297–309 (2011).
Calon, A. et al. Stromal gene expression defines poor-prognosis subtypes in colorectal cancer. Nat. Genet. 47, 320–329 (2015).
Qian, J. et al. A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling. Cell Res. 30, 745–762 (2020).
Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902 (2019).
van Dijk, D. et al. Recovering gene interactions from single-cell data using data diffusion. Cell 174, 716–729 (2018).
Calon, A. et al. Dependency of colorectal cancer on a TGF-β-driven program in stromal cells for metastasis initiation. Cancer Cell 22, 571–584 (2012).
Cheung, T. H. & Rando, T. A. Molecular regulation of stem cell quiescence. Nat. Rev. Mol. Cell Biol. 14, 329–340 (2013).
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).
Jorissen, R. N. et al. DNA copy-number alterations underlie gene expression differences between microsatellite stable and unstable colorectal cancers. Clin. Cancer Res. 14, 8061–8069 (2008).
Cerami, E. et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2, 401–404 (2012).
Yaeger, R. et al. Clinical sequencing defines the genomic landscape of metastatic colorectal cancer. Cancer Cell 33, 125–136 (2018).
Sanchez-Vega, F. et al. Oncogenic signaling pathways in the Cancer Genome Atlas. Cell 173, 321–337 (2018).
Liao, Y., Smyth, G. K. & Shi, W. The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads. Nucleic Acids Res. 47, e47 (2019).
Wu, D. et al. ROAST: rotation gene set tests for complex microarray experiments. Bioinformatics 26, 2176–2182 (2010).
Efron, B. & Tibshirani, R. On testing the significance of sets of genes. Ann. Appl. Stat. 1, 107–129 (2007).
Muñoz, J. et al. The Lgr5 intestinal stem cell signature: robust expression of proposed quiescent ‘+4’ cell markers. EMBO J. 31, 3079–3091 (2012).
Acknowledgements
We thank the Clevers laboratory (Hubrecht laboratorium, Utrecht) and the Hub for organoids (Utrecht) for sharing PDOs. We are grateful to the patients who donated their samples for the study. We thank all members of the laboratory for support and discussions. We are grateful for the outstanding assistance by the IRB Barcelona core facilities for histopathology, functional genomics, mouse mutants and advanced digital microscopy as well as the flow cytometry, animal facilities of the UB/PCB and the CRG genomic unit. We thank A. Berenguer for expert support on statistics. C.M. and A.A.-V. have held La Caixa predoctoral fellowships. A.C.-S. and L.J.-G. acknowledge an FPU fellowship from the Spanish Ministry of education. H.H. is a Miguel Servet (CP14/00229) researcher funded by the Spanish Institute of Health Carlos III and the Agencia Estatal de Investigación and FEDER (SAF2017-89109-P). L.N. holds a Beatriu de Pinos fellowship from Generalitat de Catalunya. This work has been supported by ERC advanced grant 884623 (residual CRC), IMI grant PERSIST-SEQ, Spanish Ministry of Science PID2020-119917RB-I00 and 2017-SGR-698 (Generalitat de Catalunya). IRB Barcelona is the recipient of a Severo Ochoa Award of Excellence from MINECO. The single-cell profiling of CRC samples was supported by the Belgian Federation against Cancer grant nos. 2018-127 and 2016-133 and by a grant from Fondation Roi-Baudouin. S.T. is supported by a Senior Clinical Investigator award of the Research Foundation, Flanders.
Author information
Authors and Affiliations
Contributions
E.B. and A.A.-V. conceived the study, coordinated experiments and wrote the manuscript. A.A.-V. designed and performed key experiments including in vitro and in vivo lineage-tracing, generated Mex3a-CreErt2 knock-in mouse model. L.N. generated and characterized Mex3a KO MTOs. F.M.B. generated tdTomato-CreERT2 mice and Mex3a-floxed mice. A.C.-S. performed experiments of latency in triple-mutant MTOs in vitro and in vivo. S.C.-C. performed experiments of chemotherapy resistance in MTOs. L.J.-G., G.C. and H.H. provided support with scRNA-seq experiments. X.H.-M. performed all mice work. A.A.-V., C.M., D.S., C.C., S.C.-C., F.S. and G.T. generated CRISPR-engineered organoids. C.S.-O.A. and L.M. analyzed scRNA-seq data and performed statistical analysis. M.S. performed IHC. E.S. provided strategic support and helped with figures and manuscript writing. D.V.F.T. generated MTOs. S.T. granted access to scRNA-seq data. G.S. generated PDO7, CC09 and DA13. P.J. contributed expertise regarding chemotherapy in PDOs. E.B. supervised the study.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Cancer thanks Silvia Fre and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Specification of chemoresistant Mex3a+ cells in MTOs.
a, Quantification of organoid growth of APT MTOs (Apcmut, p53mut, Tgfbr2mut) in absence of EGF compared to complete stem cell medium (SC med.). Dashed lines indicate the day EGF was re-added. n = 4 technical replicates (independent tissue culture wells), linear model on log-transformed values with no adjustment for multiple comparisons. Scale bars: 50 µm. b, Viability (ATP measurements) of APT MTOs grown in complete SC medium versus medium lacking EGF upon treatment with increasing concentrations of SN38. Trend line was calculated using LOESS model, n = 3 technical replicates (independent tissue culture wells). c, Heat map summarizing the effect on organoid growth under suboptimal niche conditions (absence of EGF or presence of TGFβ1) vs growth in SC complete medium (with EGF and no TGF-β1) in MTOs with the indicated genotypes. d, Heat map summarizing the increase in SN38 IC50 values promoted by absence of EGF or presence of TGFβ1 in MTOs with different genotypes. Color scale shows normalized IC50s compared to IC50s in SC medium. e, Viability (ATP quantification) of APS, AKP and AKP + S MTOs grown in complete SC medium versus no EGF + TGF-β1 medium upon treatment with increasing concentrations of 5FU, Oxaliplatin and SN38. Trend line was calculated using LOESS model, n = 3 technical replicates (independent tissue culture wells). f. Scheme and viability of APS organoids in increasing concentrations of SN38 in complete or medium with no EGF in latent-recovered organoids. LOESS model, n = 3 replicates. g, Relevant GSEAs obtained after RNA sequencing analysis of APT MTOs grown in SC medium versus medium with no EGF respectively. Profiling was performed at day 7. Left panels indicate signatures related to functional pathways (Function); right panels indicate GSEAs related to cell identity of different cell populations (Identity). Gene sets are ordered based on their -log10-pvalue, dashed line indicates p-value = 0.05, calculated with rotation gene set testing for linear models. Signatures are detailed in Supplementary Table 6. LRC, label-retaining cell. h, Mex3a mRNA expression levels in APT MTOs grown in the absence of EGF vs control SC medium (n = 4 independent experiments). Boxes represent the first and third quartiles. The line within the box indicates adjusted values of Mex3a mRNA corrected by experimental batch. Whiskers indicate maximum and minimum values. Linear model with no adjustment for multiple comparisons. Data in panels a, b, e and f are presented as mean values +/− SEM. Experiments in a, b, e and f were conducted 3 times with equivalent results.
Extended Data Fig. 2 Response of PDOs to chemotherapy and characterization of MEX3A+ cells in human CRC samples.
a, Viability (ATP quantification) of a collection of human patient derived organoids grown in complete SC medium versus medium lacking EGF and supplemented with active TGFβ1 upon treatment with increasing concentrations of 5FU, Oxaliplatin and SN38. Trend line was calculated using LOESS model. n = 3 technical replicates (independent tissue culture wells). b, Distribution of epithelial CRC cells according to KI67 and LGR5 signatures levels in each individual CRC patient sample. Cells are colored by MEX3A expression c. Stratification of patients according to high or low (split by median) average levels of the signature of Lgr5-high/Mex3a-high cells. P value and HR are adjusted by age, gender, mismatch repair status and AJCC stage using a multivariate statistical model, with no adjustment for multiple comparisons. d. Risk of relapse (log HR) expressed as a continuous variable of the Lgr5-high/Mex3a-high signature (Z-scored). Same covariates as in c were included in the statistical model. No adjustment for multiple comparisons e-f, Analogous analyses to c and d, for the gene expression signature of the Lgr5-high/Mex3a-low population. No adjustment for multiple comparisons. See Supplementary Table 3 for detailed cohort description.
Extended Data Fig. 3 Characterization of Mex3a+ cells in adenomas arising in Apcmin/+ mice.
a, Gating strategy to assess Lgr5_GFP + versus Mex3a_Tom+ cells in healthy crypts and adenomas. Lgr5_GFP- cells result from the mosaic expression of the Lgr5_GFP reporter cassette. Gene expression profile showed that Lgr5 was the only gene significantly upregulated in Lgr5+ versus Lgr5- within the Mex3a_Tomato-high population (Extended Table 4). b, Mex3a mRNA levels measured by RT-qPCR in Mex3a_tdTomato-positive and negative cells isolated from adenomas (n = 3 mice, paired two-tailed t-test). c, Quantification of percentages of Mex3a+ cells within Lgr5_GFP+ cells of adenoma-derived organoids cultured in the indicated conditions. n = 5 independent experiments, Paired two-tailed Wilcoxcon test. d, Representative flow cytometry profile of dissociated Mex3aTom/+ adenoma organoids cultured under the indicated conditions. n = 8, 7 and 4 organoids, for control, no EGF and +TGF-β1 respectively. Paired two-tailed Wilcoxon test. e, Organoid formation efficiency of tumor cell populations isolated from adenomas by FACs (number of organoids formed after 10 days / number of seeded cells). n = 3 independent experiments. Data are relative to Lgr5_GFP + /Mex3a_tdTomato- cells. f, Mean organoid size of adenoma organoids from (e). n = 3 independent experiments. Data are relative to Lgr5_GFP+/Mex3a_tdTomato- cells. g, Distribution of tdTomato+ and tdTomato- cells within the Lgr5_GFP+ population sorted from adenomas and analyses of the resulting organoids from each population. n = 3 independent experiments, Linear model with no adjustment for multiple comparisons after boxcox on panels e, f and g. h, i, Flow cytometry quantification of percentages of Mex3a_tdTomato+ cells of adenoma organoids originated from Mex3a_tdTomato-;Lgr5_GFP + (h) or Mex3a_tdTomato + ;Lgr5_GFP + (i) cells cultured in SC media, no EGF and with TGF-β1 for 7 days (n = 4 independent experiments), unpaired two-tailed Wilcoxcon test. j, RT-qPCR analysis of Mex3a and tdTomato mRNA in sorted tdTomato+ cells 16 h after Tamoxifen inoculation n = 3 mice, Paired two-tailed t-test. k, Violin plot showing the distribution of clone sizes generated by Mex3a and Lgr5 cells over time. n = 10 (day 2), 9 (day 7), 4 (day 15) mice for Mex3a, n = 5 mice for Lgr5 tracing at each time point. Mixed effects linear model, with no adjustment for multiple comparisons. The frequency of populations is referred to the number of viable cells, and data in panels in b, c, e, f, g, h, i and j are presented as mean values +/− SEM.
Extended Data Fig. 4 Histology of Mex3a mutant intestines.
a, Schematic representation of the generation of an intestinal specific Mex3a KO. Briefly, animals homozygous for a LoxP-flanked Mex3a allele were crossed with a Villin-CreERT2. Tamoxifen induction promoted the recombination of the LoxP sites, resulting in an intestinal Mex3a KO. See methods for details. b, Representative images of enteroendocrine- (ChgA), Tuft- (Dclk1), Goblet (Periodic acid-Schiff-Alcian Blue (PAS-AB)), pan-differentiated- (Keratin20), intestinal stem- (Olfm4) and Paneth- (Lysozyme) cells. n = 3 independent mice per genotype. Quantifications in Fig. 4b. Scale Bar 100 µm.
Extended Data Fig. 5 Mex3a+ cells regenerate organoids after chemotherapy in A, AP and AKP MTOs.
a, Schematic representation of CRISPR–Cas9-based generation of AKP advanced colorectal cancer organoids from Mex3a-creERT2 AP organoids. b, Representative image and flow cytometry plot of an AKP organoid 16 hours after addition of 4-OH-Tamoxifen. Values indicate mean ± s.e.m. n = 3 independent experiments. c, Representative images of AKP organoids 16 h after addition of 4-OH-Tamoxifen in complete stem cell medium or in medium supplemented with TGF-β1 for 7 days. Scale bar 50 µm. d, AKP and APS bearing Mex3a-creERT2 alleles were treated with Tamoxifen in complete stem cell media. After 16 h, organoids were cultured in absence of EGF (APS) or presence of TGF-β1 (AKP) for 4 days. Percentage of tdTomato+ cells was quantified by flow cytometry (n = 3 independent experiments), Linear model no adjustment for multiple comparisons. e, tdTomato-positive cells cultured in Stem Cell Media were recovered by flow cytometry at 1d, 5d or 10 days post recombination. mRNA abundance was measured by RT-qPCR (n = 3 independent experiments, paired two-tailed t-test) f, Recombination in Mex3a+ cells present in AKP organoids was induced with Tamoxifen 16 h before addition of chemotherapy. Organoids were treated during 3 days and then allowed to recover for 30 days. Representative pictures of organoids at different time points are shown. Scale bar 50 µm. g, Lineage-tracing of Mex3a+ cells in organoids derived from APCMin/+ mice. Recombination was induced with Tamoxifen 16 h before addition of chemotherapy. Organoids were treated during 3 days and then allowed to recover for 20 days. h, Representative pictures of Adenoma organoids at different time points are shown. Scale bar 50 µm i, Flow cytometry quantification of tdTomato+ cells in adenomas referred to the number of viable cells over time (n = 4 independent organoids). Scale bar 50 µm. Linear model with no adjustment for multiple comparisons. j, Schematic representation of introduction of p53 null alleles in Mex3acreERT2/+ adenomas organoids. k, p53-/- APC-/- organoids were induced with Tamoxifen 16 h before addition of chemotherapy. Proportion of tdTomato+ cells over live cells was calculated by Flow cytometry. n = 2 independent organoids, linear model with no adjustment for multiple comparisons. Data in panels d, e, i and k are presented as mean values +/− SEM.
Extended Data Fig. 6 Regeneration of liver metastases after chemotherapy by Mex3a + tumor cells.
a, Representative images of tdTomato immunohistochemistry in liver sections containing metastases generated by Mex3a-CreERT2 APS (Apcmut, p53mut, Smad4KO) MTOs at experimental endpoints (d117 after tamoxifen induction), in control and FOLFIRI-treated mice. Scale bar 2 mm. b, Example of a residual tdTomato+ micro-metastatic lesion-derived from Mex3a-traced cells (d117 after tamoxifen induction). Scale Bar 1 mm for low magnification, 100 µm for detail. c, Percentage of tdTomato+ area occupied versus the metastasis size. Each dot is a metastasis and the colors indicate a different mouse. n = 25 tumors, 5 mice. d, ISH of Mex3a and LGR5 in Mex3a-traced cells (tdTomato + ) in metastasis regenerated after FOLFIRI treatment. The arrow indicates an area with Mex3a negative cells, and the arrowhead points to Mex3a positive cells. Scale bar 50 µM.
Extended Data Fig. 7 Analysis of transcriptional cell states during chemotherapy and after recovery in AKP MTO cultures.
a, Experimental design b-e Violin plots for key marker genes of b, Lgr5 ISCs; c, Fetal progenitors/revival stem cells; d, YAP target genes; and e, proliferative cells. Expression in both tdTomato+ and tdTomato- cells after FOLFIRI treatment and recovery are shown. f-g, UMAP representation of untreated MTOs (NT) and sorted tdTomato+ and tdTomato- cells 4d after FOLFIRI treatment and upon recovery (30d). Note the overlapping distribution of tdTomato+ and tdTomato- cells. h-m, Mex3a levels or average expression of the indicated gene signatures in individual tdTomato+ cells represented in UMAPs (left panels). Signatures are detailed in Supplementary Table 6. Violin plots (right panels) compare expression levels in tdTomato+ and tdTomato- cells after FOLFIRI treatment and upon recovery.
Extended Data Fig. 8 Analysis of transcriptional cell states during chemotherapy and after recovery in APS MTOs.
a, Experimental design. b, UMAP representation of untreated MTOs (NT) and sorted tdTomato+ and tdTomato- cells 4d after FOLFIRI treatment and upon recovery (30d). c, Mex3a expression overlaps in tdTomato+ and tdTomato- cells after recovery. d-i, Mex3a levels or average expression of the indicated gene signatures in individual cells represented in UMAPs (left panels) and violin plots (right panels). Signatures are indicated in Supplementary Table 6. Levels in both tdTomato+ and tdTomato- are shown. j, RT- qPCR analysis of the expression of Mex3a, Lgr5 and two fetal progenitors/revival stem cell marker gens – Anxa3 and Basp1 - during FOLFIRI treatment and recovery. Error bars indicate mean ± SEM. n = 4 independent experiments. Unpaired two-tailed t-test was applied to calculate p-values.
Extended Data Fig. 9 Single cell transcriptomic analysis of AKP Mex3a KO1 MTOs.
a, Cell distribution represented as UMAPs of two independent WT (WT1 and WT2) versus Mex3a KO1 AKP MTOs in untreated conditions and after treatment with FOLFIRI for 2 days or 5 days. Note that no viable cells were recovered from KO1 at 5d post-treatment. b,d,f,h,j, UMAPs showing average expression levels of the indicated signatures. Signatures are detailed in Supplementary Table 6. c,e,g,i,k, Violin plots for key marker genes of the indicated cell populations and cell states.
Extended Data Fig. 10 Single cell transcriptomic analysis of AKP Mex3a KO2 MTO.
a. Cell distribution represented as UMAPs of two independent WT (WT1 and WT2) versus Mex3a KO2 AKP MTOs in untreated conditions and after treatment with FOLFIRI for 2 days or 5 days. b. Representation of Mex3a expression in UMAPs comparing WT1 + 2 (right) versus KO2 AKP MTOs (left). Arrow points at Mex3a-high cells. c,e,g,i, k, UMAPs showing average expression levels of the indicated signatures in UMAPs (left) and violin plots (right). Signatures are detailed in Supplementary Table 6. d,f,h,j l, Violin plots for key marker genes of the indicated populations and cell states.
Supplementary information
Supplementary Tables
Supplementary Tables 1 to 7.
Supplementary Video 1
Lineage-tracing of Mex3a+ progeny in APS MTOs under control conditions.
Supplementary Video 2
Lineage-tracing of Mex3a+ progeny in APS MTOs under FOLFOX treatment.
Source data
Source Data Fig. 1
Statistical source data.
Source Data Fig. 2
Statistical source data.
Source Data Fig. 3
Statistical source data.
Source Data Fig. 4
Statistical source data.
Source Data Fig. 5
Statistical source data.
Source Data Fig. 6
Statistical source data.
Source Data Fig. 7
Statistical source data.
Source Data Fig. 8
Statistical source data.
Source Data Fig. 8
Unprocessed western blot.
Source Data Extended Data Fig. 1
Statistical source data.
Source Data Extended Data Fig. 2
Statistical source data.
Source Data Extended Data Fig. 3
Statistical source data.
Source Data Extended Data Fig. 5
Statistical source data.
Source Data Extended Data Fig. 6
Statistical source data.
Source Data Extended Data Fig. 8
Statistical source data.
Rights and permissions
About this article
Cite this article
Álvarez-Varela, A., Novellasdemunt, L., Barriga, F.M. et al. Mex3a marks drug-tolerant persister colorectal cancer cells that mediate relapse after chemotherapy. Nat Cancer 3, 1052–1070 (2022). https://doi.org/10.1038/s43018-022-00402-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s43018-022-00402-0
This article is cited by
-
Mex-3 RNA binding family member A (MEX3A)/circMPP6 complex promotes colorectal cancer progression by inhibiting autophagy
Signal Transduction and Targeted Therapy (2024)
-
Expected and unexpected effects after systemic inhibition of Hippo transcriptional output in cancer
Nature Communications (2024)
-
Clusterin: a marker and mediator of chemoresistance in colorectal cancer
Cancer and Metastasis Reviews (2024)
-
Organoids as a biomarker for personalized treatment in metastatic colorectal cancer: drug screen optimization and correlation with patient response
Journal of Experimental & Clinical Cancer Research (2024)
-
Membrane to cortex attachment determines different mechanical phenotypes in LGR5+ and LGR5- colorectal cancer cells
Nature Communications (2024)
