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Mitochondrial fission links ECM mechanotransduction to metabolic redox homeostasis and metastatic chemotherapy resistance

Nature Cell Biology volume 24, pages 168–180 (2022)Cite this article

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Abstract

Metastatic breast cancer cells disseminate to organs with a soft microenvironment. Whether and how the mechanical properties of the local tissue influence their response to treatment remains unclear. Here we found that a soft extracellular matrix empowers redox homeostasis. Cells cultured on a soft extracellular matrix display increased peri-mitochondrial F-actin, promoted by Spire1C and Arp2/3 nucleation factors, and increased DRP1- and MIEF1/2-dependent mitochondrial fission. Changes in mitochondrial dynamics lead to increased production of mitochondrial reactive oxygen species and activate the NRF2 antioxidant transcriptional response, including increased cystine uptake and glutathione metabolism. This retrograde response endows cells with resistance to oxidative stress and reactive oxygen species-dependent chemotherapy drugs. This is relevant in a mouse model of metastatic breast cancer cells dormant in the lung soft tissue, where inhibition of DRP1 and NRF2 restored cisplatin sensitivity and prevented disseminated cancer-cell awakening. We propose that targeting this mitochondrial dynamics- and redox-based mechanotransduction pathway could open avenues to prevent metastatic relapse.

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Fig. 1: ECM stiffness regulates cystine metabolism and glutathione oxidation.
Fig. 2: ECM stiffness regulates ROS levels.
Fig. 3: NRF2 activation on soft ECM potentiates cell resistance to exogenous oxidative stress.
Fig. 4: The antioxidant response induced by ECM stiffness is initiated by mtROS.
Fig. 5: ECM stiffness regulates mitochondrial fission through DRP1.
Fig. 6: ECM stiffness regulates fission via Spire1c- and Arp2/3-dependent peri-mitochondrial F-actin.
Fig. 7: A soft ECM increases resistance to cisplatin and As2O3 chemotherapy through NRF2 and DRP1.
Fig. 8: A soft metastatic niche protects dormant breast cancer cells from chemotherapy.

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Data availability

Previously published metabolomics data have been deposited to the Figshare database and are available at https://doi.org/10.6084/m9.figshare.7338764. The RNA sequencing data have been deposited to Gene EXpression Omnibus database as GSE189803. 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.

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Acknowledgements

We thank D. De Stefani for help with plasmids and advice on toroidal mitochondria, L. Scorrano and M. Zamberlan for protocols to measure mitochondrial morphology and reagents to study DRP1, C. Laterza for help with tissue sectioning, J. Weedon who contributed to the set-up of the bleomycin model, and I. Szabo for help with the transmission electron microscopy and critically reading the manuscript. This study was supported by: Worldwide Cancer Research grant no. 21-0156, AIRC Foundation Investigator grant no. 21392 and a CARIPARO Excellence Grant to S.D.; P.R. is supported by a Veronesi Foundation Postdoctoral Fellowship; AIRC Foundation Investigator grant no. 2018-ID 2135, AIRC Foundation Investigator Grant 5 per mille grant no. 22759, Ministero della Salute grant no. RCR-2019-23669115, Ministero della Salute grant no. NET-2016-02361632 and Istituto Oncologico Veneto to A.R.; Giovanni Armenise–Harvard Foundation and ERC Starting Grant (MetEpiStem) to G.M.; Canadian Institutes for Health Research (CIHR) Foundation Grant, National Institutes of Health grant nos R01-HL071115 and 1RC1HL099462, a Tier I Canada Research Chair and the William J. Henderson Foundation to S.L.A.; Longfonds (Voorhen Astma Fonds) BREATH Consortium, NIHR GOSH Biomedical Research Centre, the National Institute for Health Research grant no. NIHR-RP-2014-04-046 to P.D.C.; F.M. is supported by a GOSH BRC Catalyst Fellowship; University of Padua STARS Consolidator Grant 2019 to T.C.; University of Padua TWINING-VELT 2017 Grant to N.E.; and Fondazione IRP Città della Speranza to A.U.

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Authors and Affiliations

  1. Department of Molecular Medicine (DMM), University of Padua, Padua, Italy

    Patrizia Romani, Nunzia Nirchio, Anna Urciuolo, Antonella Roveri, Marco Montagner & Sirio Dupont

  2. Department of Biology (DiBio), University of Padua, Padua, Italy

    Mattia Arboit & Graziano Martello

  3. Department of Surgery, Oncology and Gastroenterology (DiSCOG), University of Padua, Padua, Italy

    Vito Barbieri & Antonio Rosato

  4. Veneto Institute of Oncology IOV-IRCCS, Padua, Italy

    Vito Barbieri, Anna Tosi & Antonio Rosato

  5. Institute of Child Health, NIHR Biomedical Research Centre, Great Ormond Street Institute of Child Health, UCL, London, UK

    Federica Michielin, Soichi Shibuya, Thomas Benoist, Nicola Elvassore & Paolo De Coppi

  6. Department of Medicine, Queen’s University, Kingston, Ontario, Canada

    Danchen Wu, Charles Colin Thomas Hindmarch & Stephen L. Archer

  7. Department of Industrial Engineering (DII), University of Padua, Padua, Italy

    Monica Giomo & Nicola Elvassore

  8. Venetian Institute of Molecular Medicine (VIMM), Padua, Italy

    Monica Giomo & Nicola Elvassore

  9. Fondazione Istituto di Ricerca Pediatrica (IRP), Città della Speranza, Padua, Italy

    Anna Urciuolo

  10. Department of Biomedical Sciences (DSB), University of Padua, Padua, Italy

    Flavia Giamogante & Tito Calì

  11. Bioinformatics Platform, The Francis Crick Institute, London, UK

    Probir Chakravarty

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Contributions

P.R. carried out experiments and analysed data with help from N.N. M.A. retrieved raw data for gene-set enrichment analysis and performed RNA sequencing analysis, with support from G.M. A.T. and V.B. performed the immunohistochemistry and helped with the mouse experiments, with support from A.R. D.W. performed the analysis of mitochondrial morphology; C.C.T.H. and S.L.A. provided Drpitor1a and support. F.M., S.S. and T.B. prepared the mouse lung decellularized ECM slices and performed the lung infiltration experiments, with support from P.D.C. M.G. and A.U. performed the AFM measurements, with support from N.E. F.G. helped with the SPLICS experiments, with support from T.C. A.R. performed the GSH and GSSG quantifications. P.C. and M.M. helped with the gene-set enrichment analysis. S.D. conceptualized, coordinated and supervised the project, and wrote the manuscript.

Corresponding author

Correspondence to Sirio Dupont.

Ethics declarations

Competing interests

The invention of Drpitor1a is the subject of the US Patent Application 20200323829 by D.W. and S.L.A. The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Cell Biology thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available.

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Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 ECM stiffness regulates cystine metabolism and glutathione oxidation.

a, A simplified scheme depicting the major metabolic intermediates of the glutathione synthesis pathway, together with the enzymes mediating each reaction. In blue, the intermediates increased in MCF10A-RAS cells cultured in conditions of decreased actomyosin contractility. b, Representative gating scheme for quantification of FITC-labelled cystine uptake by flow cytometry. Cells without stain were used as negative control (outlined white area). Cells treated with Y27632 and ML7 (YM - orange) display increased uptake compared to DMSO (grey), while treatment with the sulfasalazine (SAS - magenta) inhibitor of the cystine transporter inhibits uptake. Scale bar, 50 μm. On the right: quantification of FITC-labelled cystine uptake. Data are mean and single points relative to DMSO (black bar). P-values by Dunnet’s test from a sample size of n = 4 biologically independent samples pooled across two independent experiments for each bar. c,d, Glutathione redox analysis using the mitochondrial mito-Grx1-roGFP2 sensor in MCF10A-RAS cells treated with YM (c), or cultured on stiff or soft Matrigel substrata (d). Data are mean and single cells. P-values by Dunnet’s test or Student’s t-test from a sample size of n = 21 in c and n = 31 in d cells pooled across two independent experiments for each bar. e-g, Direct quantification of reduced (GSH, e) and oxidized (GSSH, f) glutathione in extracts from MCF10A-RAS cells treated with YM for 24 h. The ratio of reduced to oxidized glutathione was calculated in g. Data are mean and single points. n = 2 independent experiments. Images in b,c are representative of two independent experiments with similar results. See Source Data Extended Data Fig. 1.

Source Data

Extended Data Fig. 2 ECM stiffness regulates ROS levels.

a, NADPH redox analysis using the iNap1 sensor in MCF10A-RAS cells treated with YM. Co-treatment with Diamide (DIA) and the G6PD inhibitor DHEA serves as positive control for NADPH depletion. iNapC is a NADP-insensitive and pH-sensitive control sensor (n = 35 cells pooled across two independent experiments for each bar; unpaired two-tailed Student’s t-test). b,c, Representative gating schemes and quantifications of DCFDA (b) and MitoSOX (c) oxidation by flow cytometry. Cells without stain were used as negative control (outlined white area). Cells treated with the positive control cumene hydroperoxide (CUM - purple) display increased uptake compared to DMSO (grey). Median intensity in the controls were set to 1, and other samples are relative to these (n = 6 biologically independent samples pooled across three independent experiments for each bar; unpaired two-tailed Student’s t-test). d-i, Quantification of reactive-oxygen species by the DCFDA and MitoSOX reagents in MCF10A, MCF10A-RAS and D2.0R cells. Median intensity in the controls were set to 1, and other samples are relative to these (in d n = 4 (STIFF) and n = 5 (all other conditions); in e n = 11 (DMSO) n = 6 (YM and SOFT) n = 5 (BLEBBI) n = 8 (STIFF); in f n = 4 (STIFF) n = 5 (all other condotions); in g n = 4 (DMSO and YM) n = 6 (STIFF and SOFT); in h n = 6 (DMSO, YM6h and YM 24 h) n = 4 (YM1h and YM 3 h); in i n = 5 (YM 1 h) and n = 6 (all other conditions) biologically independent samples pooled across two independent experiments; unpaired two-tailed Student’s t-test or Dunnet’s test). j, Representative gating scheme and quantification of C11-Bodipy-581/591 lipid peroxidation by flow cytometry. Cells without C11-Bodipy-581/591 were used as negative control (outlined white area). Cells treated with cumene hydroperoxide (CUM - purple) or with the GPX4 lipid hydroperoxide glutathione peroxidase inhibitor RSL3 (blue) for 3 h were used as positive controls. Mean intensity in the controls were set to 1, and other samples are relative to these (n = 4 biologically independent samples pooled across two independent experiments for each bar; Dunnet’s test). k,l, Quantification of C11-Bodipy-581/591 lipid peroxidation in MCF10A-RAS and D2.0R cells treated with YM for 3 h or cultured on Fibronectin-coated stiff or soft acrylamide hydrogels. Median intensity in the controls were set to 1, and other samples are relative to these (n = 4 biologically independent samples pooled across two independent experiments for each bar; unpaired two-tailed Student’s t-test). m, Immunofluorescence of 4-hydroxy-2-nonenal (4HNE) lipid peroxidation adducts in MCF10A-RAS cells cultured on stiff or soft Matrigel substrata for 24 h. Images are representative of at two experiments with similar results. Scale bar, 5 μm. Mean intensity in the controls were set to 1, and other samples are relative to these (n = 36 (STIFF) n = 34 (SOFT) cells pooled across two independent experiments; unpaired two-tailed Student’s t-test). Data are mean and single points. See Source Data Extended Data Fig. 2.

Source Data

Extended Data Fig. 3 ECM stiffness regulates NRF2 activity.

a,b, qPCR for established NRF2 target genes in D2.0R and MCF10A cells treated with YM for 6 h (in a FTH1 n = 2 (DMSO) n = 4 (YM); HMOX1 n = 2 (DMSO) n = 4 (YM); NQO1 n = 2 (DMSO) n = 4 (YM); GCLC n = 2 (DMSO) n = 4 (YM); SLC7A11 n = 7 (DMSO) n = 5 (YM) independent samples pooled across two independent experiments; in b HMOX1 n = 8; FTH1 n = 8 (DMSO) n = 7 (YM); GCLC n = 8 (DMSO) n = 6 (YM); GCLM n = 8 (DMSO) n = 6 (YM); SLC7A11 n = 8 (DMSO) n = 6 (YM) independent samples pooled across two independent experiments; unpaired two-tailed Student’s t-tests. c qPCR for established NRF2 target genes in D2.0R cells cultured on Matrigel substrata of different stiffness. (Fth1 n = 7(STIFF) n = 5 (SOFT); Hmox1 n = 4; Nqo1 n = 7; Gclm n = 4; SLC7A11 n = 6 (STIFF) n = 5 (SOFT) independent samples pooled across two independent experiments; unpaired two-tailed Student’s t-tests. d qPCR for established NRF2 target genes in MCF10A-RAS (FTH1 n = 4; HMOX1 n = 6 (DMSO and YM) n = 4 (Ki696); NQO1 n = 6 (DMSO and YM) n = 4 (ki696); GCLC n = 6 (DMSO and YM) n = 4 (ki696) independent samples pooled across two independent experiments; unpaired two-tailed Student’s t-tests. e-g, qPCR for established YAP/TAZ targets in D2.0R (e) and NRF2 and YAP/TAZ target genes in MCF10A-RAS (f,g). YAP/TAZ targets serve as internal positive controls.(in e n = 4, in f n = 4, in g n = 10 samples pooled across two independent experiments for each bars; unpaired two-tailed Student’s t-tests). h, qPCR for established NRF2 target genes in MCF10A cells cultured on soft (E ≈ 0.2kPa) or stiff (E ≈ 50kPa) CollagenI-coated hydrogels of different stiffness (n = 4 samples pooled across two independent experiments for each bars; unpaired two-tailed Student’s t-tests). i, Quantification of active nuclear S40-phosphorylated NRF2 (pNRF2) intensity from immunofluorescence stainings of MCF10A-RAS and D2.0R cells cultured on stiff or soft Matrigel substrata. KI696 is a KEAP1 inhibitor used as a positive control. Mean levels in the controls were set to 1, and other samples are relative to these (n = 59 (DMSO) n = 60 (YM and ki696) cells were imaged for each condition, pooled across two independent experiments; unpaired two-tailed Student’s t-tests). j, qPCR to control for efficient knockdown of NEF2L2 (encoding for NRF2) in MCF10A-RAS (n = 10 (siCO) n = 8 (siNRF2a and siNRF2b) samples pooled across two independent experiments for each bars; unpaired two-tailed Student’s t-tests). k, Immunoblotting for endogenous NRF2 from extracts of MCF10A-RAS cells transfected with the indicated siRNAs. Equal total proteins were loaded in each lane, and GAPDH was used as loading control. Images are representative of two independent experiments with similar results. Unprocessed blots in Source Data Extended Data Fig. 3. j, qPCR to control for efficient knockdown of Nfe2L2 in D2.0R cells (n = 5 (shCO) n = 6 (shNrf2a and shNrf2b) samples pooled across two independent experiments for each bars; unpaired two-tailed Student’s t-tests). Data are mean and single points. mRNA expression data are relative to GAPDH levels; mean level in the control was set to 1, and other samples are relative to this. See Source Data Extended Data Fig. 3.

Source Data

Extended Data Fig. 4 Activation of NRF2 gene signatures in response to a soft ECM in published datasets.

a, Gene-Set Enrichment Analysis (GSEA) was performed on genes upregulated by culturing MCF10A cells on stiff 2D Matrigel-coated plates (red) or soft 3D Matrigel gels (blue). NRF2 signatures: KEAP/SFN (normalized enrichment score NES = −1.53 P < 0.0001 false discovery rate FDR = 0.038), LIST (NES = −1.91 P < 0.0001 FDR < 0.0001), PANIERI (NES = −1.75 P < 0.0001 FDR = 0.0006), HER2 (NES = −1.80 P < 0.001 FDR = 0.0005). YAP/TAZ (NES = 2.01 P < 0.0001 FDR < 0.0001) and SREBP (NES = −1.47 P < 0.017 FDR 0.06) serve as positive controls for gene signatures regulated by ECM stiffness. b, GSEA was performed on genes upregulated by culturing D2.0R cells on stiff Matrigel+Collagen-I gels (red) or soft Matrigel gels (blue). NRF2 signatures: KEAP/SFN (NES = −2.11 P < 0.0001 FDR < 0.0001), LIST (NES = −2.11 P < 0.0001 FDR < 0.0001), HER2 (NES = −1.86 P < 0.001 FDR = 0.0008). YAP/TAZ (NES = 1.64 P = 0.004 FDR = 0.009) and SREBP (NES = −1.77 P < 0.0001 FDR = 0.0026) serve as positive controls for gene signatures regulated by ECM stiffness. c, GSEA was performed on genes upregulated by culturing human MDA-MB-453 breast cancer cells on stiff (red) Fibronectin-coated plates or soft (blue) acrylamide hydrogels. NRF2 signatures: KEAP/SFN (NES = −3.25 P < 0.001 FDR < 0.001), LIST (NES = −3.60 P < 0.001 FDR < 0.001), HER2 (NES = −4.50 P < 0.001 FDR < 0.001). The YAP/TAZ signature (NES = 1.71 P = 0.025 FDR = 0.048 Zhao NES = 2.43 P < 0.001 FDR < 0.001) serves as positive control for genes regulated by ECM stiffness. d, Heatmap of NRF2 target genes in RNAseq data of mouse MMTV-PyMT breast cancer cells cultured ex vivo on Fibronectin-coated plates, stiff or soft acrylamide hydrogels. Each column is an independent biological sample (n = 4 for each condition); each line is a single gene. Expression levels for each gene were normalized relative to the mean expression on plates, which was set to 1 (white). Black and blue indicate downregulation and upregulation (P < 0.05), respectively. YAP/TAZ target genes serve as positive controls. e, GSEA was performed on genes regulated in matched cases of pre-treatment fine-needle aspiration (PRE, red) and the respective post neoadjuvant treatment operative sample (POST, blue) of primary breast cancer patients. Neoadjuvant treatment is known to reduce tumour stiffness. NRF2 signatures: KEAP/SFN (NES = −1.32 P = 0.012 FDR = 0.096), LIST (NES = −1.34 P = 0.11 FDR = 0.088), PANIERI (NES = −1.34 P = 0.093 FDR = 0.087). SREBP (NES = −1.94 P < 0.001 FDR < 0.001) and YAP/TAZ (NES = 2.56 P < 0.001 FDR < 0.001) serve as positive controls for gene signatures regulated by ECM stiffness. f, Heatmap of NRF2 and YAP target levels in n = 7 patient-matched stiff keloid tissue or soft normal skin. Each column represents -log2(keloid/skin) values for a single patient; each line is a single gene probe; genes ranked according to expression in patient #1. Black and blue indicate downregulation and upregulation (P < 0.05), respectively. YAP target genes serve as positive controls. g,h, qPCR for established HSF1 target genes in MCF10A cells cultured on Fibronectin-coated stiff or soft hydrogels (g), or transfected on plastics with control (siCO) or with YAP/TAZ siRNAs (h). Data are mean and single points. mRNA expression data are relative to GAPDH levels; mean level in the control was set to 1, and other samples are relative to this (n = 2 biologically independent samples from one experiment). See Source Data Extended Data Fig. 4.

Source Data

Extended Data Fig. 5 ECM stiffness regulates resistance to oxidative stress.

a, Representative gating scheme for quantification of CytoGrx1-roGFP2 by flow cytometry. Cells without CytoGrx1-roGFP2 expression were used as negative control (outlined white area). Cells treated with cumene hydroperoxide (CUM, purple) for 10 min. to induce glutathione oxidation were used as positive control (n = 4 biologically independent samples pooled across two independent experiments for each bar; unpaired two-tailed Student’s t-test). b, Cell survival by the resazurin assay in MCF10A cells with the indicated knockdowns, plated on stiff or soft Matrigel substrata, and treated for 48 h with Cumene hydroperoxide (CUM). Mean cell number in controls was set to 100%, and all other samples are relative to this (n = 12 biologically independent samples pooled across two independent experiments for each bar; Dunnet’s tests). c, Cell survival of MCF10A-RAS cells transfected with the indicated KEAP1 siRNAs and treated for 48 h with Cumene hydroperoxide (CUM). Mean cell number in Stiff controls was set to 100%, and all other samples are relative to this (n = 12 biologically independent samples pooled across two independent experiments for each bar; Dunnet’s test). d, qPCR to control for efficient knockdown of KEAP1 in MCF10A-RAS. mRNA expression data are relative to GAPDH levels; mean level in the control was set to 1, and other samples are relative to this (n = 4 biologically independent samples from two independent experiments; Dunnet’s test). e, Immunoblotting for endogenous KEAP1 from extracts of MCF10A-RAS cells transfected with the indicated siRNAs. Equal total proteins were loaded in each lane, and GAPDH was used as loading control. Images are representative of two independent experiments with similar results. Unprocessed blots in Source Data Extended Data Fig. 5. f, Cell survival of MCF10A-RAS cells transfected with the indicated NRF1 siRNA, plated on stiff or soft Matrigel substrata, and treated for 48 h with Cumene hydroperoxide (CUM). Mean cell number in Stiff controls was set to 100%, and all other samples are relative to this (n = 12 biologically independent samples pooled across two independent experiments for each bar; unpaired two-tailed Student’s t-tests). g, qPCR for NFE2L1 (encoding for NRF1) and NFE2L2 (encoding for NRF2) expression levels in MCF10A-RAS transfected with NRF1 siRNAs. mRNA expression data are relative to GAPDH levels; mean level in the control was set to 1, and other samples are relative to this (n = 6 biologically independent samples from two independent experiments; Dunnet’s test). h,i, Cell survival of MCF10A-RAS cells treated for 48 h with Erastin (ERA, g) or RSL3 (h) alone and together with the anti-ferroptosis compounds Liproxstatin-1 (LIP) or Ferrostatin (FER). Mean cell number in Stiff controls was set to 100%, and all other samples are relative to this (in h n = 7 (VEHICLE DMSO, ERASTIN 10μM FER, ERASTIN 10μM LIP, ERASTIN 30μM DMSO) n = 6 (ERASTIN 10μM DMSO) n = 8 (all other conditions) biologically independent samples pooled from a single experiment; in i n = 8 (VEHICLE) n = 6 (RSL3 5μM LIP) n = 7 (all other conditions) biologically independent samples pooled from a single experiment; Dunnet’s tests). j, qPCR for YAP/TAZ targets in MCF10A-RAS cells used as a control for differential stiffness of the Matrigel substrata within the extracellular flux analyser plates (see Fig. 4f). mRNA expression data are relative to GAPDH levels; mean level in the control was set to 1, and other samples are relative to this (n = 6 biologically independent samples from three independent experiments; unpaired two-tailed Student’s t-tests). k, qPCR for YAP/TAZ targets in D2.0R cells used as a control for differential stiffness of the Matrigel substrata within the extracellular flux analyser plates (see Fig. 4g). mRNA expression data are relative to GAPDH levels; mean level in the control was set to 1, and other samples are relative to this (n = 4 biologically independent samples from two independent experiments; unpaired two-tailed Student’s t-tests). Data are mean and single points. See Source Data Extended Data Fig. 5.

Source Data

Extended Data Fig. 6 ECM stiffness regulates mitochondrial fission through DRP1.

a, Quantification of mitochondria length in D2.0R cells transfected with mitoRFP and treated with YM (n = 128 (DMSO) n = 117(YM) mitochondria pooled across 10 cells per condition in two independent experiments for each bar; unpaired two-tailed Student’s t-tests). The same set of images was analysed by automated classification of mitochondrial length (centre) and by MFC analysis (right). Data are mean and single mitochondria (left), mean and s.d. (centre) and mean and single pictures (right). b, Quantification of mitochondria content by MitoTracker staining in MCF10A-RAS and D2.0R cells treated with YM. Median level in the control was set to 1, and other samples are relative to this (n = 7 biologically independent samples pooled across three independent experiments for MCF10A-RAS; n = 4 biologically independent samples pooled across two independent experiments for D2.0R). c, Quantification of mitochondrial DNA content in MCF10A-RAS cells treated with YM, based on qPCR for three different mtDNA loci. mtDNA levels are relative to genomic DNA (gDNA) levels; mean level in the control was set to 1, and other samples are relative to this (n = 6 biologically independent samples from two independent experiments). d, qPCR for DRP1 in MCF10A cells treated with YM. mRNA expression data are relative to GAPDH levels; mean level in the control was set to 1, and other samples are relative to this (n = 6 biologically independent samples from three independent experiments). e, Immunoblotting for endogenous total and phosphorylated DRP1 (p616, p637) from extracts of MCF10A-RAS cells treated with ROCK/MLCK inhibitors. Equal total proteins were loaded in each lane, and GAPDH was used as loading control. f,g. qPCR to control for efficient knockdown of DRP1 in MCF10A-RAS (f) or in D2.0R (g). mRNA expression data are relative to GAPDH levels; mean level in the control was set to 1, and other samples are relative to this (n = 4 biologically independent samples from two independent experiments for each bar; unpaired two-tailed Student’s t-test in MCF10A-RAS, Dunnet’s test in D2.0R). h. Immunoblotting for endogenous DRP1 from extracts of MCF10A-RAS cells transfected with the indicated siRNAs. Equal total proteins were loaded in each lane, and GAPDH was used as loading control. i. Quantification of mtROS in MCF10A-RAS cells with knockdown of the indicated fission factors, and treated with YM. Median intensity in the control were set to 1, and other samples are relative to these (n = 8 biologically independent samples pooled across four independent experiments for siCO bars; n = 4 biologically independent samples pooled across two independent experiments for other bars; unpaired two-tailed Student’s t-tests). j-m. qPCR in MCF10A-RAS to control for efficient knockdown of the FIS1, MFF, MIEF1 and MIEF2 fission factors. mRNA expression data are relative to GAPDH levels; mean level in the control was set to 1, and other samples are relative to this (n = 4 biologically independent samples from two independent experiments for each bar; Dunnet’s tests). n. Oxygen Consumption Rate (OCR) analysis performed on monolayers of MCF10A-RAS cells transfected with control (siCO) or DRP1 siRNA and plated on stiff or soft Matrigel substrata (n = 20 biologically independent samples pooled across two independent experiments). o. OCR analysis on cells were treated with Drpitor1a (n = 20 biologically independent samples pooled across two independent experiments). p. OCR analysis performed on monolayers of D2.0R cells stably expressing control (shCo.) or DRP1a shRNA and cultured on stiff or soft Matrigel substrata (n = 20 biologically independent samples pooled across two independent experiments). q. OCR analysis on cells were treated with Drpitor1a (n = 20 biologically independent samples pooled across two independent experiments). Images in e,h are representative of two independent experiments with similar results. Unprocessed blots in Source Data Extended Data Fig. 6. Data are mean and single points, except n-q (mean and s.d. - shaded areas). See Source Data Extended Data Fig. 6.

Source Data

Extended Data Fig. 7 A soft ECM increases resistance to Cisplatin and As2O3 chemotherapy through NRF2 and DRP1 in MCF10A-RAS cells.

a,b, Cell survival of MCF10A-RAS cells treated for 48 h with the indicated concentrations of Cisplatin (a) or As2O3 (b), in the absence or presence of the antioxidant N-Acetyl-L-cysteine (NAC, 5 mM) (in a n = 14 (VEHICLE) n = 13 (VEHICLE NAC) n = 15 (CISPLATIN 5μM) n = 16 (CISPLATIN 20 μM) biologically independent samples pooled across two independent experiments; in b n = 22 (VEHICLE and As2O3 20μM) n = 19 (VEHICLE NAC) n = 21 (As2O3 5μM) biologically independent samples pooled across two independent experiments; Dunnet’s tests). c,d, Cell survival assay in MCF10A-RAS cells cultured on stiff Matrigel-coated plates or soft Matrigel gels, and treated for 48 h with the indicated concentrations of Cisplatin (c) or As2O3 (d) (n = 16 biologically independent samples pooled across two independent experiments for each bar; Dunnet’s test). e, Cell survival assay in MCF10A-RAS cells treated for 48 h with the indicated concentrations of Doxorubicin (DOXO), in the absence or presence of N-Acetyl-L-cysteine (NAC, 5 mM) (n = 16 biologically independent samples pooled across two independent experiments for each bar). f, Cell survival assay in MCF10A-RAS cells cultured on stiff Matrigel-coated plates (black) or soft Matrigel gels (green), and treated for 48 h with the indicated concentrations of Doxorubicin (DOXO) (n = 14 biologically independent samples pooled across two independent experiments for each bar). g, Cell survival of MCF10A-RAS cells transiently transfected as indicated and cultured on stiff Matrigel-coated plates or soft Matrigel gels, and treated for 48 h with the indicated concentration of Cisplatin. (n = 8 (siCO and siNRF2b CISPLATIN SOFT) n = 6 (all other conditions) biologically independent samples pooled across two independent experiments; Dunnet’s test). h. Cell survival of MCF10A-RAS cells transiently transfected as indicated, cultured on stiff Matrigel-coated plates or soft Matrigel gels, and treated for 48 h with the indicated concentration of Cisplatin. Where indicated cells were also treated with the DRP1 inhibitor Drpitor1a. (n = 14 (siCO) n = 12 (siDRP1) n = 16 (DRPITOR1A) biologically independent samples pooled across two independent experiments; Dunnet’s test). Data are mean and single points. Mean expression in untreated controls were set to 100%, and all other samples are relative to this. See Source Data Extended Data Fig. 7.

Source Data

Extended Data Fig. 8 Controls to experiments shown in main Fig. 8.

a, A simplified model of the mechanical conditions used throughout Fig. 8. Cells are seeded in a soft microenvironment (wavy lines: in vitro BM ECM, ex vivo decellularized lung ECM, in vivo lung tissue) or directly in stiff conditions (straight bold lines: lung ECM slices treated with Ribose or derived from fibrotic mice). Cancer cells remodel the ECM, such that they stiffen their microenvironment at late time points (LATE: 14 days in vitro, 1.5 months in vivo). b, Quantification of tissue stiffness by atomic force microscopy on mouse mammary glands and normal lungs, using frozen tissue microtome sections. Data are mean and single points (n = 4 and n = 3 tissue sections from two mice). c, YAP/TAZ immunofluorescence in D2.0R cells cultured on normal and Ribose-stiffened (RIB) lung ECM slices. Images are representative of two independent experiments with similar results. Scale bars, 25 μm. d, Collagen-I and YAP/TAZ immunofluorescence in D2.0R cells cultured on normal and fibrosis-stiffened (FIB) lung ECM slices. Images are representative of two independent experiments with similar results. Scale bars, 25 μm. e, qPCR to control for efficient regulation of YAP/TAZ in D2.0R cells infiltrated into normal or fibrotic (FIB) lung ECM scaffolds. Data are mean and single points; mRNA expression data are relative to GAPDH levels; mean level in the control was set to 1, and other samples are relative to this (n = 7 biologically independent samples from two independent experiments for bars 1 and 2; n = 2 biologically independent samples from one single experiment for bars 3). See Source Data Extended Data Fig. 8.

Source Data

Extended Data Fig. 9 Controls to in vivo experiments shown in main Fig. 8.

a, Experimental set-up to study D2.0R metastatic cell behaviour in mice. D2.0R cells expressing EGFP and Firefly-luciferase (EGFP/Luc) were injected via the tail vein to induce metastatic dissemination into the lungs and their initial cell number was quantified by intravital bioluminescence imaging (BLI). After letting cells settle for one week, mice were injected i.p. with Cisplatin or with the equivalent volume of vehicle (1xPBS) for four consecutive rounds. Cell growth was monitored after every injection and then every 11 days. b, EGFP/Luc D2.0R cells expressing the indicated shRNAs were injected via the tail vein mixed at a 1:1 ratio together with mCherry D2.0R cells to induce metastatic spread into the lungs. After three days, the ratio of red/green cells in the lung parenchyma was quantified to measure extravasation efficiency. Scale bars, 20 μm. Images are representative of three mice with similar results. Data are mean and single points (n = 3 mice for each condition). c, Intravital imaging of mice with lung metastases from EGFP/Luc D2.0R cells quantified in Fig. 8l, taken at day 90. The rainbow LUT was used to visualize the radiance. Images are representative of six mice with similar results per condition. d, Quantification of activated Caspase-3 in D2.0R cells disseminated to the mouse lung after treatment with two doses of Cisplatin (see scheme above) (n = 2 mice). On the right, an immunofluorescent picture with spectral unmixing showing GFP-positive D2.0R cells (cyan) disseminated into the lung parenchyma and one example of a double-positive Caspase-3/GFP cell (yellow). Tissue sections were also stained with CD31 (magenta) to visualize blood vessels. Scale bar, 20 μm. e, Intravital imaging of mice with lung metastases from EGFP/Luc D2.0R cells quantified in Fig. 8m, taken at day 75. The rainbow LUT was used to visualize the radiance. Images are representative of six mice with similar results per condition. Data are mean and single points. See Source Data Extended Data Fig. 9.

Source Data

Extended Data Fig. 10 Proposed model.

A simplified model that recapitulates the main findings of the manuscript, ordered in time after shifting cells to a soft microenvironment. On a soft ECM, cells develop reduced actomyosin tension, which is associated with increased formation of peri-mitochondrial F-actin, increased DRP1-dependent mitochondrial fission and enhanced mtROS production. mtROS activate a NRF2-dependent antioxidant metabolic response which includes increased cysteine uptake and glutathione synthesis. Functionally, this response has two main outcomes: it keeps redox balance in the face of increased ROS and glutathione oxidation (upward facing arrow), and it results in a better ability of cells to resist exogenous oxidative stress and ROS-dependent chemotherapy (downward facing arrow), compared to cells in a stiff microenvironment. mt is an abbreviation for mitochondria.

Supplementary information

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

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Romani, P., Nirchio, N., Arboit, M. et al. Mitochondrial fission links ECM mechanotransduction to metabolic redox homeostasis and metastatic chemotherapy resistance. Nat Cell Biol 24, 168–180 (2022). https://doi.org/10.1038/s41556-022-00843-w

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