{"id":102855,"date":"2025-08-28T08:46:09","date_gmt":"2025-08-28T08:46:09","guid":{"rendered":"https:\/\/www.newsbeep.com\/ca\/102855\/"},"modified":"2025-08-28T08:46:09","modified_gmt":"2025-08-28T08:46:09","slug":"mechanical-confinement-governs-phenotypic-plasticity-in-melanoma","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/ca\/102855\/","title":{"rendered":"Mechanical confinement governs phenotypic plasticity in melanoma"},"content":{"rendered":"<p>Zebrafish husbandry<\/p>\n<p>Stable transgenic zebrafish lines were kept at 28.5\u2009\u00b0C in a dedicated aquatics facility with a 14\u2009h on\/10\u2009h off light cycle. Casper fish with the following genotype were used for all experiments: mitfa-BRAFV600E;p53\u2212\/\u2212;mitfa\u2212\/\u2212. Fish were anaesthetized using Tricaine (MS-222; stock concentration of 4\u2009g\u2009l\u22121), diluted until the fish were immobilized. All animal procedures were approved by the Memorial Sloan Kettering Cancer Center Institutional Animal Care and Use Committee (protocol no. 12-05-008).<\/p>\n<p>Cloning of zebrafish CRISPR constructs<\/p>\n<p>To generate hmgb2a and hmgb2b CRISPR guide RNA (gRNA) plasmids for use in vivo, three gRNAs for each gene were subcloned into Gateway entry vectors containing zebrafish-optimized U6 gRNA promoters. The resulting 3\u00d7 gRNA plasmid was assembled through Gateway LR cloning. Validation of gRNA\/Cas9 activity in vivo was performed using the Alt-R CRISPR-Cas9 system (Integrated DNA Technologies (IDT)) by injecting single-guide RNAs (sgRNAs) and purified Cas9 protein into one-cell-stage zebrafish embryos. Genomic DNA was isolated from five to ten embryos 24\u2009h later, and mutation detection was performed using the Alt-R Genome Editing Detection Kit (IDT).<\/p>\n<p>Zebrafish gRNA sequences:<\/p>\n<p>hmgb2a sgRNA1: 5\u2032-GAAAAGTTCACCGAGGTCCC-3\u2032<\/p>\n<p>hmgb2a sgRNA2: 5\u2032-AAGGTGAAGGGCGACAACCC-3\u2032<\/p>\n<p>hmgb2a sgRNA3: 5\u2032-GACAACCCGGGCATCTCTAT-3\u2032<\/p>\n<p>hmgb2b sgRNA1: 5\u2032-CAAACCCAAGGGGAAGACGT-3\u2032<\/p>\n<p>hmgb2b sgRNA2: 5\u2032-CTCAAACTTGACCTTGTCGG-3\u2032<\/p>\n<p>hmgb2b sgRNA3: 5\u2032-AGAGAAGTTGACGGGCACGT-3\u2032<\/p>\n<p>NT sgRNA: 5\u2032-AACCTACGGGCTACGATACG-3\u2032<\/p>\n<p>Zebrafish in vivo electroporation<\/p>\n<p>Tumours were generated by means of TEAZ<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 68\" title=\"Callahan, S. J. et al. Cancer modeling by transgene electroporation in adult zebrafish (TEAZ). Dis. Models Mech. 11, dmm034561 (2018).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR68\" id=\"ref-link-section-d143698561e2960\" rel=\"nofollow noopener\" target=\"_blank\">68<\/a>. To generate hmgb2a\/hmgb2b knockout melanomas, adult 3-month-old to 6-month-old fish were randomly assigned to groups and injected with the following plasmids: miniCoopR\u2013GFP, mitfa:Cas9, Tol2, U6\u2013sgptena, U6\u2013sgptenb and either 394-zU6\u20133XsgRNA[hmgb2a] and 394-zU6\u20133XsgRNA[hmgb2b] or 394-zU6\u20133XsgRNA[NT]. Adult fish were anaesthetized using tricaine and injected with 1\u2009\u00b5l of plasmid mixture below the dorsal fin, immediately electroporated and moved to fresh water to recover. Tumour growth was imaged every 1\u20132\u2009weeks using a ZEISS Axio Zoom V16 fluorescence microscope. Male and female animals were used in equal proportions. No sample size calculation or blinding was performed.<\/p>\n<p>Cell culture<\/p>\n<p>The following cell lines were obtained from the American Type Culture Collection: A375 (<a href=\"https:\/\/www.atcc.org\/products\/crl-1619\" rel=\"nofollow noopener\" target=\"_blank\">CRL-1619<\/a>), SKMEL5 (<a href=\"https:\/\/www.atcc.org\/products\/htb-70\" rel=\"nofollow noopener\" target=\"_blank\">HTB-70<\/a>), MIA-PaCa-2 (<a href=\"https:\/\/www.atcc.org\/products\/crm-crl-1420\" rel=\"nofollow noopener\" target=\"_blank\">CRM-CRL-1420<\/a>), Panc-1 (<a href=\"https:\/\/www.atcc.org\/products\/crl-1469\" rel=\"nofollow noopener\" target=\"_blank\">CRL-1469<\/a>), HTB-4 (<a href=\"https:\/\/www.atcc.org\/products\/htb-4\" rel=\"nofollow noopener\" target=\"_blank\">T24<\/a>), HTB-9 (<a href=\"https:\/\/www.atcc.org\/products\/htb-9\" rel=\"nofollow noopener\" target=\"_blank\">5637<\/a>) and <a href=\"https:\/\/www.cellosaurus.org\/CVCL_0063?form=MG0AV3\" rel=\"nofollow noopener\" target=\"_blank\">HEK293T<\/a>. The cells were maintained in a 37\u2009\u00b0C and 5% CO2 humidified incubator. The cell lines were authenticated by the American Type Culture Collection and routinely checked to be free from Mycoplasma. The cells were cultured in DMEM (Gibco; 11965) supplemented with 10% fetal bovine serum (GeminiBio; 100-500).<\/p>\n<p>Transfection of siRNAs<\/p>\n<p>SiRNAs targeting the following genes were obtained from Horizon Discovery: HMGB2 (L-011689-00-0005), SYNE2 (L-019259-01-0005) and non-targeting control (D-001810-10-05). DharmaFECT 1 Transfection Reagent (Horizon Discovery; T-2001) was used to transfect 250,000 A375 cells per condition. The medium was changed after 24\u2009h, and experiments were performed 72\u2009h after changing the medium. HMGB2 knockdown was validated by western blot with an antibody targeting HMGB2 (MilliporeSigma; HPA053314). For gel source data, see Supplementary Fig.\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"supplementary material anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#MOESM1\" rel=\"nofollow noopener\" target=\"_blank\">1<\/a>. Downregulation of SYNE2 was validated by means of quantitative polymerase chain reaction (qPCR) with the following primers:<\/p>\n<p>SYNE2 F: 5\u2032-CAAAGCACAGGAAACTGAGGCAG-3\u2032<\/p>\n<p>SYNE2 R: 5\u2032-AGACAGTGGCAACGAGGACATG-3\u2032<\/p>\n<p>\u03b2-Actin F: 5\u2032-CACCAACTGGGACGACAT-3\u2032<\/p>\n<p>\u03b2-Actin R: 5\u2032-ACAGCCTGGATAGCAACG-3\u2032<\/p>\n<p>Cloning of human CRISPR constructs<\/p>\n<p>The lentiCRISPRv2 system<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 69\" title=\"Sanjana, N. E., Shalem, O. &amp; Zhang, F. Improved vectors and genome-wide libraries for CRISPR screening. Nat. Methods 11, 783&#x2013;784 (2014).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR69\" id=\"ref-link-section-d143698561e3082\" rel=\"nofollow noopener\" target=\"_blank\">69<\/a> was used to generate stable human knockout cell lines, and gRNAs targeting HMGB2 or ATAT1 were selected from the GeCKO2 library. Oligonucleotides containing each gRNA were obtained from IDT and cloned into the lentiCRISPRv2 backbone through restriction digest with BsmB1 and ligation with Quick Ligase (New England Biolabs). Ligated plasmids were transformed into Stbl3 bacteria (New England Biolabs) and sequenced to verify gRNA insertion. The final plasmids were used to create stable A375 and SK-MEL-5 lines using lentiviral transduction, as described below.<\/p>\n<p>Human gRNA sequences:<\/p>\n<p>HMGB2 sgRNA1: 5\u2032-CTGCACGAAGAAGGCGTACG-3\u2032<\/p>\n<p>HMGB2 sgRNA2: 5\u2032-AAGATCAAAAGTGAACACCC-3\u2032<\/p>\n<p>ATAT1 sgRNA1: 5\u2032-CCAGAAGAACATCTACAGTG-3\u2032<\/p>\n<p>ATAT1 sgRNA2: 5\u2032-CCTCACTGTAGATGTTCTTC-3\u2032<\/p>\n<p>NT sgRNA: 5\u2032-AACCTACGGGCTACGATACG-3\u2032<\/p>\n<p>Cloning of HMGB2 overexpression and deletion constructs<\/p>\n<p>To generate the HMGB2\u2013GFP plasmid, the human HMGB2 coding sequence in a pENTR backbone (Horizon Discovery; OHS5898-202621565) was combined with a C terminus EGFP tag using In-Fusion Cloning. The HMGB2\u2013GFP insert was then transferred into a lentiviral expression vector containing the cytomegalovirus promoter (pLX304; Addgene 25890) by means of Gateway cloning using LR Clonase II Plus (Thermo Fisher Scientific). Deletion constructs were generated through In-Fusion Cloning (Takeda Bioscience) using the HMGB2\u00a0open reading frame in the pENTR backbone as a template and were subsequently cloned into pLX304 by means of Gateway cloning, as described above. The primers were:<\/p>\n<p>HMGB2-\u0394A-box F: 5\u2032-CCAACAAGCCTCCCAAAGGTGATAAGAAGGG-3\u2032<\/p>\n<p>HMGB2-\u0394A-box R: 5\u2032-TGGGAGGCTTGTTGGGGTCTCCTTTACC-3\u2032<\/p>\n<p>HMGB2-\u0394B-box F: 5\u2032-CCAATGCTGCCAAGGGCAAAAGTGAAGC-3\u2032<\/p>\n<p>HMGB2-\u0394B-box R: 5\u2032-CCTTGGCAGCATTGGGGTCCTTTTTCTTCCC-3\u2032<\/p>\n<p>HMGB2-\u0394acidic tail F: 5\u2032-CATATCGTGACCCAGCTTTCTTGTACAAAG-3\u2032<\/p>\n<p>HMGB2-\u0394acidic tail R: 5\u2032-CTGGGTCACGATATGCAGCAATATCCTTTTC-3\u2032<\/p>\n<p>Generation of stable cell lines<\/p>\n<p>HMGB2OE, HMGB2\u2013GFP, HMGB2KO, HMGB2del, ATAT1KO and FastFUCCI stable cell lines were generated by means of lentiviral transduction. The FastFUCCI reporter plasmid was obtained from Addgene (86849). The HMGB2\u2013GFP reporter plasmid, HMGB2 gRNA+Cas9 plasmids, ATAT1 gRNA+Cas9 plasmids and non-targeting gRNA+Cas9 plasmids were assembled, as described above. The HMGB2OE plasmid was obtained from Horizon Discovery (OHS5897-202616132). Eight million HEK293T cells per condition were transfected with 1,200-ng lentiviral vector, 600-ng PAX2 plasmid and 300-ng MD2 plasmid using Effectene Transfection Reagent (QIAGEN). Virus was collected starting 24\u2009h after transfection. Viral supernatant was filtered (0.45-\u00b5m filter) before adding to A375 cells at a 1:1 ratio with medium and 10\u2009\u00b5g\u2009ml\u22121 of polybrene. Cells were infected for 72\u2009h, allowed to recover for 24\u2009h and then selected using blasticidin (5\u2009\u00b5g\u2009ml\u22121; 7\u201310\u2009days) or puromycin (1\u2009\u00b5g\u2009ml\u22121; 3\u2009days). For cell lines expressing a fluorescent reporter, cells were sorted using FACSAria III or FACSymphony S6 cell sorters (BD Biosciences). For HMGB2 overexpression and CRISPR lines, successful transduction was validated through western blot with an antibody targeting HMGB2 (MilliporeSigma; HPA053314). For ATAT1KO lines, knockdown was validated through qPCR. For gel source data, see Supplementary Fig.\u2009<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"supplementary material anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#MOESM1\" rel=\"nofollow noopener\" target=\"_blank\">1<\/a>.<\/p>\n<p>QPCR primer sequences:<\/p>\n<p>ATAT1 F: 5\u2032-CACAGTCCCACAGGTGAACA-3\u2032<\/p>\n<p>ATAT1 R: 5\u2032-CTCCCTGCTTGGAGTCTTGG-3\u2032<\/p>\n<p>\u03b2-Actin F: 5\u2032-CACCAACTGGGACGACAT-3\u2032<\/p>\n<p>\u03b2-Actin R: 5\u2032-ACAGCCTGGATAGCAACG-3\u2032<\/p>\n<p>In vitro confinement and imaging<\/p>\n<p>A375, HTB-4 and HTB-9 cells were subjected to overnight (approximately 16\u2009h) confinement at a height of 3\u2009\u00b5m using a static cell confiner (4Dcell). Pancreatic ductal adenocarcinoma cell lines (MIA-PaCa-2 and Panc-1) were confined at a 5-\u00b5m height owing to their larger size. The cells were plated 6\u2009h before imaging in fibronectin-coated glass-bottom 35-mm dishes (FluoroDish) or glass-bottom six-well plates (MatTek). The cells were allowed to attach before confinement was applied. Confined cells were incubated at 37\u2009\u00b0C and 5% CO2 overnight. For live imaging, dyes plus 10\u2009\u00b5M verapamil were added to the plated cells 2\u20133\u2009h before imaging. The dyes used for live imaging were SiR-tubulin (Spirochrome; 100\u2009nM) and SiR-DNA (Spirochrome; 250\u2009nM). Pharmacological inhibitors were added immediately before applying confinement. The inhibitors used were Taxol (Tocris; 1097), tubacin (Selleck Chemicals; S2239), nocodazole (Tocris; 1228) and trichostatin A (MilliporeSigma; T8552). Live imaging was performed on an LSM 880 (ZEISS) confocal microscope at 37\u2009\u00b0C and 5% CO2, at \u00d763 magnification and 5\u201310\u2009min of temporal resolution, using ZEN Black v.2.3 SP1 software (ZEISS). For immunofluorescence, cells were fixed with 4% paraformaldehyde for 15\u2009min at room temperature before proceeding with staining and imaging, as described below.<\/p>\n<p>In vitro proliferation and invasion assays<\/p>\n<p>The CyQUANT Direct Red Cell Proliferation Assay (Thermo Fisher Scientific; C35013) was used to assay cell proliferation. Cells were plated at a density of 500 cells per well in 96-well plates and allowed to grow for 72\u2009h. The cell number was quantified using the CyQUANT Direct Red Nuclei Acid Stain and Background Suppressor added at a 1:1 ratio to the cell culture medium, and the intensity was read out at 622\u2009nm on a plate reader. For invasion assays, VitroGel Cell Invasion Assay Kit (TheWell Bioscience; IA-VHM01-1P) and Cultrex Collagen I Cell Invasion Assay kit (Bio-Techne; 3457-096-K) were used. The cells were serum-starved overnight in DMEM, plated in the upper chamber of the invasion assay insert and allowed to migrate for 18\u2009h. The cell number was quantified using crystal violet or calcein staining.<\/p>\n<p>Immunofluorescence staining and imaging<\/p>\n<p>Cells were plated on glass CC2-coated chamber slides (Thermo Fisher Scientific) or fibronectin-coated glass-bottom dishes (FluoroDish) and allowed to attach for approximately 24\u2009h. The cells were fixed with 4% paraformaldehyde for 15\u2009min, permeabilized with 0.1% Triton in PBS and blocked in 10% goat serum (Thermo Fisher Scientific) for 1\u2009h at room temperature. The primary antibodies used were rabbit anti-HMGB2 (Abcam; ab124670), rabbit anti-HMGB1 (Abcam; ab18256), rabbit anti-HMGA1 (Abcam; ab129153), mouse anti-\u03b1-tubulin (MilliporeSigma; CP06), chick anti-\u03b2-tubulin (Novus Biologicals; NB100-1612), mouse anti-acetylated tubulin (MilliporeSigma; 6793), rabbit anti-acetylated tubulin (Cell Signaling Technology (CST); 5335), rat anti-tyrosinated tubulin (MilliporeSigma; MAB1864-I), mouse anti-polyglutamylated tubulin (MilliporeSigma; T9822), mouse anti-GFP (Abcam; ab1218), rabbit anti-H3Ac (MilliporeSigma; 06-599), mouse anti-Annexin V (Santa Cruz Biotechnology; sc-74438), rabbit anti-cleaved caspase-3 (CST; 9661), rabbit anti-cleaved PARP (CST; 5625), rabbit anti-YAP (CST; 14074), mouse anti-Twist (Abcam; ab50887), rabbit anti-Snail (CST; 3879), rabbit anti-SMAD3 (Abcam; ab40854) and rabbit anti-SYNE2 (Abcam; ab204308). All primary antibodies were used at 1:200. The cells were incubated with primary antibodies overnight at 4\u2009\u00b0C, washed in PBS and incubated with the appropriate fluorescently labelled secondary antibody (1:250). Alexa Fluor 488 conjugated phalloidin (CST; 8878S), when used, was added at 1:50, and Hoechst was added at 1:1,000. The cells were mounted in VECTASHIELD (Vector Laboratories) and allowed to cure overnight. Stained cells were imaged on a ZEISS LSM 880 confocal at \u00d740 or \u00d763 resolution using ZEN Black v.2.3 SP1 software (ZEISS). A Gaussian blur with a radius of 0.5\u20130.75\u2009pixels was occasionally applied to images to reduce noise for visualization purposes only.<\/p>\n<p>Staining of human tumour samples<\/p>\n<p>Human melanoma tissue microarrays were obtained from TissueArray.Com (Me481f). Slides were baked at 60\u2009\u00b0C for 20\u2009min and deparaffinized in consecutive xylene and ethanol washes. Antigen retrieval was performed using 1X IHC Antigen Retrieval Solution (Thermo Fisher Scientific; 00-4955-58) heated at 95\u2009\u00b0C for 20\u2009min in a pressure cooker. After washing in PBS, the samples were blocked in 10% goat serum (Thermo Fisher Scientific) for 1\u2009h at room temperature before incubation overnight at 4\u2009\u00b0C in the following primary antibodies, all diluted in blocking buffer at 1:200: rabbit anti-HMGB2 (Abcam; ab124670) and mouse anti-acetylated tubulin (MilliporeSigma; 6793). After washing in PBS, the slides were incubated with the appropriate fluorescently labelled secondary antibody (1:250) and Hoechst (1:1,000). After washing in PBS, a final incubation was performed with a fluorescently conjugated rabbit anti-S100a6 antibody (Abcam; ab204028; 1:250) to label tumour cells before mounting the slides in VECTASHIELD. The slides were imaged on a Pannoramic slide scanner (3DHISTECH) using a \u00d720\/0.8 numerical aperture objective, with higher-resolution images acquired on an LSM 880 confocal (ZEISS), as described above.<\/p>\n<p>Image analysis<\/p>\n<p>Images were analysed using CellProfiler<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 70\" title=\"Stirling, D. R. et al. CellProfiler 4: improvements in speed, utility and usability. BMC Bioinform. 22, 433 (2021).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR70\" id=\"ref-link-section-d143698561e3244\" rel=\"nofollow noopener\" target=\"_blank\">70<\/a>, TrackMate<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 71\" title=\"Ershov, D. et al. TrackMate 7: integrating state-of-the-art segmentation algorithms into tracking pipelines. Nat. Methods 19, 829&#x2013;832 (2022).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR71\" id=\"ref-link-section-d143698561e3248\" rel=\"nofollow noopener\" target=\"_blank\">71<\/a> and MATLAB v.R2021b and R2023b (MathWorks). For images of fixed cells, the cells were segmented in CellProfiler using Hoechst staining to generate a nuclei mask and phalloidin or other cytoskeletal staining to generate a whole-cell mask. The mean intensity per cell\/nucleus was quantified, and expression of nuclear-localized proteins was normalized to Hoechst intensity per nucleus. For quantification of live imaging data, HMGB2\u2013GFP intensity per cell over time was quantified using TrackMate. The resulting intensity data were analysed in MATLAB by fitting a line to each curve and automatically removing curves in which more than four data points differed from the line of best fit by more than 0.2\u2009a.u. In all cases, plotting and statistics were done in MATLAB. The images were assembled for figure preparation using Fiji (v.2.14).<\/p>\n<p>Fluorescence recovery after photobleaching<\/p>\n<p>A375 cells expressing HMGB2\u2013GFP were confined for approximately 18\u2009h before FRAP measurements. FRAP was done on an LSM 880 confocal at 37\u2009\u00b0C with 5% CO2 using a \u00d763 oil immersion lens and ZEN Black v.2.3 SP1 software (ZEISS). A 5-\u00b5m circular diameter region of interest was defined within the nucleus of each cell before photobleaching at 405\u2009nm and 488\u2009nm wavelengths for ten pulses. One time point was acquired before photobleaching. Fluorescence recovery was imaged at 0.2-s intervals for a total of 20\u2009s. All analyses were performed in MATLAB. For analysis, fluorescence within the region of interest was normalized to the fluorescence at the initial time point (before photobleaching). Samples in which the fluorescence within the region of interest was not bleached to at least 25% of the pre-bleaching value were automatically removed from the analysis. Each recovery curve was fitted with a two-component exponential using the function \u2018fit\u2019 with the \u2018exp2\u2019 parameter: F(t)\u2009=\u2009y0\u2009+\u2009A1(1\u2009\u2212\u2009e\u2212t\/\u03c41)\u2009+\u2009A2(1\u2009\u2212\u2009e\u2212t\/\u03c42), where y0 represents the fluorescence immediately after photobleaching, A1 represents the amplitude of the fast-diffusing population, A2 represents the amplitude of the slow-diffusing population, t is time and \u03c41 and \u03c42 correspond to the time constants for the fast-diffusing and slow-diffusing populations, respectively.<\/p>\n<p>Atomic force microscopy<\/p>\n<p>Cells were plated on glass-bottom Petri dishes (FluoroDish FD35) and confined for 18\u2009h, as described above. Immediately after removing the dish from the confiner, cell stiffness was measured using a NanoWizard V microscope (JPK Bruker) in QI Advanced mode. The samples were maintained at 37\u2009\u00b0C during imaging using the PetriDishHeater (Bruker). For cell stiffness mapping, 1-\u03bcm-diameter spherical AFM probe (silicon nitride cantilever; nominal spring constant k\u2009=\u20090.2\u2009N\u2009m\u22121; SAA-SPH-1UM; Bruker) was used. Each spring constant of the AFM probe was measured using the thermal noise method in liquid at 37\u2009\u00b0C. For the stiffness mapping, a 2\u2009nN set point was used (60\u2009\u03bcm\u2009\u00d7\u200960\u2009\u03bcm image size with 32\u2009\u00d7\u200932\u2009pixels of resolution) to ensure up to 10\u201320% sample indentation to avoid glass surface influence. The data were processed with JPK Data Processing software using the Hertz model with 0.5 Poisson ratio as a fit parameter. To calculate nuclear stiffness, force maps were segmented on the basis of the corresponding cell height measurements to extract the nuclear region.<\/p>\n<p>TurboID experimentsGeneration of TurboID constructs<\/p>\n<p>Cloning of TurboID constructs and validation was performed, as described in a previous study<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 35\" title=\"Cho, K. F. et al. Proximity labeling in mammalian cells with TurboID and split-TurboID. Nat. Protoc. 15, 3971&#x2013;3999 (2020).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR35\" id=\"ref-link-section-d143698561e3348\" rel=\"nofollow noopener\" target=\"_blank\">35<\/a>. The cyto-TurboID plasmid was obtained from Addgene. For TurboID\u2013HMGB2, the TurboID cassette was amplified by polymerase chain reaction and cloned into pENTR\u2013HMGB2 at the N terminus of HMGB2 using In-Fusion Cloning. For nuclear localization signal\u2013TurboID, an entry vector was assembled using In-Fusion Cloning, containing the TurboID cassette, followed by three consecutive nuclear localization signal sequences. The pENTR\u2013TurboID\u2013HMGB2 and pENTR\u2013TurboID\u20133XNLS constructs were subcloned into the pLX304 backbone by Gateway cloning using LR Clonase II Plus (Thermo Fisher Scientific). Stable A375 cell lines were generated, as described above, and expression and localization of the TurboID fusion protein were confirmed by immunofluorescence targeting haemagglutinin (found at the N terminus of the TurboID cassette). The TurboID activity was validated by pulsing the cells with 10\u2009mM biotin (MilliporeSigma; 1071508), followed by both western blotting and immunofluorescence using fluorescently labelled streptavidin. IRDye 800CW Streptavidin (LI-COR; 926-32230) was used for western blotting, and streptavidin conjugated to Alexa Fluor 488 (Thermo Fisher Scientific; S11223) or Alexa Fluor 555 (Thermo Fisher Scientific; S21381) was used for immunofluorescence.<\/p>\n<p>Sample preparation<\/p>\n<p>For mass spectrometry experiments, ten million cells per condition and replicate were plated in 15-cm dishes. The medium was removed from the dishes and replaced with 10\u2009mM biotin for 1\u2009h. The labelling reaction was stopped by placing the dishes on ice and washing the cells five times with ice-cold PBS. The cells were then detached by scraping in ice-cold PBS and then pelleted and resuspended in radio-immunoprecipitation assay buffer\u2009+\u2009protease inhibitors. The cells were lysed by means of sonication (10% amplitude; 2\u2009s per cycle; six cycles), and Bradford assay was used to measure the protein concentration. For each sample, 1-mg protein was incubated with streptavidin magnetic beads (Thermo Fisher Scientific; 88817) in radio-immunoprecipitation assay buffer overnight with rotation at 4\u2009\u00b0C. The next day, the beads were pelleted using a magnetic rack, the supernatant was removed and the beads were washed once in 50\u2009mM Tris\u2013HCl (pH\u20097.5) and twice in 2\u2009M urea in 50\u2009mM Tris\u2013HCl (pH\u20097.5).<\/p>\n<p>Protein digestion<\/p>\n<p>The beads were resuspended in 80\u2009ml of 2\u2009M urea and 50\u2009mM EPPS (pH\u20098.5) and treated with dl-dithiothreitol (1\u2009mM final concentration) for 30\u2009min at 37\u2009\u00b0C with shaking (1,100\u2009rpm) on a Thermomixer (Thermo Fisher Scientific). Free cysteine residues were alkylated with 2-iodoacetamide (3.67\u2009mM final concentration) for 45\u2009min at 25\u2009\u00b0C at 1,100\u2009rpm in the dark. The reaction was quenched using 3.67\u2009mM dithiothreitol, and LysC (750\u2009ng) was added, followed by incubation for 1\u2009h at 37\u2009\u00b0C at 1,150\u2009rpm. Finally, trypsin (750\u2009ng) was added, followed by incubation for 16\u2009h at 37\u2009\u00b0C at 1,150\u2009rpm. After incubation, the digest was acidified to pH less than 3 with the addition of 50% of trifluoroacetic acid (TFA), and the peptides were desalted on Sep-Pak C18 cartridges (Waters). Briefly, the cartridges were conditioned by sequential addition of (1) 100% methanol; (2) 70% acetonitrile (ACN)\/0.1% TFA; and (3) 5% ACN\/0.1% TFA twice. After conditioning, the acidified peptide digest was loaded onto the cartridge. The stationary phase was washed with 5% ACN\/0.1% formic acid twice. Finally, peptides were eluted using 70% ACN\/0.1% formic acid twice. Eluted peptides were dried under vacuum in a SpeedVac centrifuge followed by reconstitution in 12\u2009\u03bcl of 0.1% formic acid, sonication and transfer to an autosampler vial. Peptide yield was quantified using NanoDrop (Thermo Fisher Scientific).<\/p>\n<p>Mass spectrometry<\/p>\n<p>Peptides were separated on a 25-cm column with a 75-mm diameter and 1.7-mm particle size composed of C18 stationary phase (IonOpticks; Aurora 3 1801220) using a gradient from 2% to 35% B over 90\u2009min and then to 95% B for 7\u2009min (buffer A, 0.1% formic acid in high-performance liquid chromatography-grade water; buffer B, 99.9% ACN and 0.1% formic acid) with a flow rate of 300\u2009nl\u2009min\u22121 using a nanoElute 2 system (Bruker). Mass spectrometry data were acquired on a timsTOF HT (Bruker) with a CaptiveSpray source (Bruker) using a data-independent acquisition parallel accumulation\u2013serial fragmentation (PASEF) method (dia-PASEF). The mass range was set from 100 to 1700\u2009m\/z, and the ion mobility range was set from 0.60\u2009V\u2009s\u2009cm\u22122 (collision energy of 20\u2009eV) to 1.6\u2009V\u2009s\u2009cm\u22122 (collision energy of 59\u2009eV) with a ramp time of 100\u2009ms and an accumulation time of 100\u2009ms. The dia-PASEF settings included a mass range of 400.0\u20131,201.0\u2009Da, mobility range of 0.60\u20131.60 and a cycle time estimate of 1.80\u2009s. The dia-PASEF windows were set with a mass width of 26.00\u2009Da, mass overlap of 1.00\u2009Da and 32 mass steps per cycle.<\/p>\n<p>Data analysis<\/p>\n<p>Raw data files were processed using Spectronaut v.18.5 (Biognosys) and searched with the Pulsar search engine with a human UniProt protein database downloaded on 15 August 2023 (226,261 entries). Cysteine carbamidomethylation was specified as a fixed modification, whereas methionine oxidation, acetylation of the protein N terminus and deamidation (NQ) were set as variable modifications. A maximum of two trypsin missed cleavages were permitted. Searches used a reversed sequence decoy strategy to control peptide FDR, and 1% FDR was set as the threshold for identification. Unpaired t-test was used to calculate P value in differential analysis, and volcano plot was generated on the basis of log2FC and q value (multiple testing corrected P value using Benjamini\u2013Hochberg method). A q value\u2009\u2264\u20090.05 was considered the statistically significant cut-off.<\/p>\n<p>Mouse experiments<\/p>\n<p>Mouse in vivo studies were performed in accordance with the guidelines approved by the Memorial Sloan Kettering Cancer Center Institutional Animal Care and Use Committee and Research Animal Resource Center. The mice were housed under pathogen-free conditions, in an environment with controlled temperature (21.5\u2009\u00b0C\u2009\u00b1\u20091.5\u2009\u00b0C) and humidity (55%\u2009\u00b1\u200910%) and under 12\u2009h light\/dark cycles. For the drug efficacy studies, 6-week-old to 8-week-old athymic female mice (The Jackson Laboratory) were injected subcutaneously with five million A375 cells in a 50:50 mix with Matrigel (Corning). Once tumours reached an average volume of 100\u2009mm3, the mice were randomized into two treatment groups (n\u2009=\u20094\u20136 mice per group) to receive either a vehicle control or trametinib (1\u2009mg\u2009kg\u22121) in combination with dabrafenib (30\u2009mg\u2009kg\u22121). Both drugs were delivered through oral gavage daily five times for 3\u2009weeks. The mice were observed daily throughout the treatment period for signs of morbidity\/mortality. Tumours were measured twice weekly using calipers, and volume was calculated using the following formula: length\u2009\u00d7\u2009width2\u2009\u00d7\u20090.52. Body weight was also assessed twice weekly. For the HMGB2 deletion construct growth curve studies, tumour cells were implanted, as described above, and tumour volume was measured twice weekly. The animals were monitored until their tumour size reached 1,500\u2009mm3, at which point tumours were collected, fixed in 10% formalin for 24\u2009h, transferred to 70% ethanol and processed for histology. In accordance with limits established by the Memorial Sloan Kettering Cancer Center (MSKCC) Institutional Animal Care and Use Committee, the mice were euthanized when tumour burden exceeded 1,500\u2009mm3. These limits were not exceeded in any of the experiments. Histology was performed by HistoWiz using the following antibodies for immunohistochemistry: mouse anti-BRAFV600E (Abcam; ab228461) and rabbit anti-acetylated tubulin (Abcam; ab179484). Two biological replicates consisting of four to six mice per condition (for a total of 10\u201311 mice per group) were performed for both experiments. No sample size calculation or blinding was performed.<\/p>\n<p>Bulk RNA-seq and analysis<\/p>\n<p>For bulk RNA-seq of A375 and SKMEL5 cells overexpressing HMGB2, three replicates of approximately one million cells each were pelleted and resuspended in TRIzol before snap freezing. For bulk RNA-seq of confined A375 cells, 200,000 cells were plated in each well of a six-well plate. Three wells were confined for approximately 18\u2009h using a six-well static confiner (4Dcell) at 3-\u00b5m height, whereas the remaining three wells were left unconfined. The cells were then collected in TRIzol, pooling the three wells for each condition to generate samples of approximately 600,000 cells each. This process was repeated for a total of three independent biological replicates per condition. Library preparation and sequencing were done by Azenta Life Sciences. Raw sequencing reads were processed using FastQC (Babraham Bioinformatics) and Trimmomatic<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 72\" title=\"Bolger, A. M., Lohse, M. &amp; Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114&#x2013;2120 (2014).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR72\" id=\"ref-link-section-d143698561e3454\" rel=\"nofollow noopener\" target=\"_blank\">72<\/a> before alignment to the human genome hg38. All downstream analyses were performed in R (v.4.3.1). Differential gene expression was analysed using DESeq2 (ref.\u2009<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 73\" title=\"Love, M. I., Huber, W. &amp; Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR73\" id=\"ref-link-section-d143698561e3458\" rel=\"nofollow noopener\" target=\"_blank\">73<\/a>) with the default parameters. GSEA was performed using the fgsea<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 74\" title=\"Korotkevich, G. et al. Fast gene set enrichment analysis. Preprint at bioRxiv &#010;                https:\/\/doi.org\/10.1101\/060012&#010;                &#010;               (2016).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR74\" id=\"ref-link-section-d143698561e3462\" rel=\"nofollow noopener\" target=\"_blank\">74<\/a> R package (v.1.26) with Gene Ontology biological process pathway sets from MSigDB<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 75\" title=\"Liberzon, A. et al. Molecular signatures database (MSigDB) 3.0. Bioinformatics 27, 1739&#x2013;1740 (2011).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR75\" id=\"ref-link-section-d143698561e3466\" rel=\"nofollow noopener\" target=\"_blank\">75<\/a>.<\/p>\n<p>Bulk ATAC-seq and analysis<\/p>\n<p>Samples containing approximately 100,000 cells each were centrifuged at 700g for 5\u2009min at 4\u2009\u00b0C before being resuspended in 500-\u00b5l growth medium supplemented with 10% DMSO. The cells were frozen at \u221280\u2009\u00b0C overnight before library preparation and sequencing were performed by Azenta Life Sciences. Sequencing reads were trimmed and filtered for quality control using TrimGalore (v.0.6.7) with a quality setting of 15, Cutadapt<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 76\" title=\"Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, 10 (2011).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR76\" id=\"ref-link-section-d143698561e3481\" rel=\"nofollow noopener\" target=\"_blank\">76<\/a> (v.4.0) and FastQC v.0.12.1. Reads were aligned to the human genome assembly hg38 using Bowtie 2 (ref.\u2009<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 77\" title=\"Langmead, B. &amp; Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357&#x2013;359 (2012).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR77\" id=\"ref-link-section-d143698561e3485\" rel=\"nofollow noopener\" target=\"_blank\">77<\/a>) (v.2.3.5.1) and were deduplicated using MarkDuplicates from Picard (Broad Institute; v.2.16). Peaks were identified using MACS2 (ref.\u2009<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 78\" title=\"Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR78\" id=\"ref-link-section-d143698561e3489\" rel=\"nofollow noopener\" target=\"_blank\">78<\/a>) with a P-value setting of 0.001 using a publicly available melanocyte dataset (<a href=\"https:\/\/www.ncbi.nlm.nih.gov\/geo\/query\/acc.cgi?acc=GSM3191792\" rel=\"nofollow noopener\" target=\"_blank\">GSM3191792<\/a>) as control. To generate a global peak atlas, blacklisted regions were removed before merging all peaks within a 500-bp region and quantifying reads using featureCounts. Differentially enriched peaks were identified using DESeq2 (ref.\u2009<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 73\" title=\"Love, M. I., Huber, W. &amp; Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR73\" id=\"ref-link-section-d143698561e3504\" rel=\"nofollow noopener\" target=\"_blank\">73<\/a>). Peak gene mapping was done by assigning all intergenic peaks to that gene and, in other cases, by genomic distance to the transcription start site. Pathway was analysed using clusterProfiler<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 79\" title=\"Yu, G., Wang, L.-G., Han, Y. &amp; He, Q.-Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16, 284&#x2013;287 (2012).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR79\" id=\"ref-link-section-d143698561e3508\" rel=\"nofollow noopener\" target=\"_blank\">79<\/a>. Tornado plots were generated with deepTools<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 80\" title=\"Ram&#xED;rez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 44, W160&#x2013;W165 (2016).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR80\" id=\"ref-link-section-d143698561e3512\" rel=\"nofollow noopener\" target=\"_blank\">80<\/a> (v.3.5.1) functions (computeMatrix and plotHeatmap), with genes annotated from the indicated pathway sets. Motif enrichment was analysed using Homer<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 81\" title=\"Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576&#x2013;589 (2010).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR81\" id=\"ref-link-section-d143698561e3516\" rel=\"nofollow noopener\" target=\"_blank\">81<\/a> (v.4.11.1) functions (findMotifsGenome and annotatePeaks).<\/p>\n<p>ChIP sequencingSample preparation and sequencing<\/p>\n<p>For profiling of HMGB2 binding in A375 and SKMEL5 cells, freshly collected cells (approximately 20\u2009million cells\/replicate\/condition) were crosslinked first with 1.5\u2009mM of EGS (Thermo Fisher Scientific; 21565) for 20\u2009min at room temperature and subsequently with 1% formaldehyde (Thermo Fisher Scientific; 28906) for 40\u2009min at 4\u2009\u00b0C. The reaction was quenched by the addition of glycine to the final concentration of 0.125\u2009M. Fixed cells were washed twice with PBS and resuspended in SDS buffer (100\u2009mM NaCl, 50\u2009mM Tris\u2013HCl (pH\u20098.0), 5\u2009mM EDTA, 0.5% SDS and 1\u00d7 protease inhibitor cocktail; Roche). The resulting nuclei were spun down, resuspended in the immunoprecipitation buffer (100\u2009mM NaCl, 100\u2009mM Tris\u2013HCl (pH\u20098.0), 5\u2009mM EDTA and 5% Triton X-100) at 1\u2009ml per 0.5\u2009million cells mixed in 2:1 ratio, with the addition of 1\u00d7 protease inhibitor cocktail (MilliporeSigma; 11836170001). The nuclei were processed on a Covaris E220 Focused-ultrasonicator to achieve an average fragment length of 200\u2013300\u2009bp with the following parameters: peak incident power\u2009=\u2009140, duty factor\u2009=\u20095, cycles per burst\/burst per second\u2009=\u2009200 and time\u2009=\u200920\u2009min (for A375 cells) or 45\u2009min (for SKMEL5 cells). Chromatin concentrations were estimated using the Pierce BCA Protein Assay Kit (Thermo Fisher Scientific; 23227) according to the manufacturer\u2019s instructions. The immunoprecipitation reactions were set up in 500\u2009\u00b5l of the immunoprecipitation buffer in Protein LoBind Tubes (Eppendorf; 22431081) and pre-cleared with 50\u2009\u00b5l of Dynabeads Protein G (Thermo Fisher Scientific; 10004D) for 2\u2009h at 4\u2009\u00b0C. After pre-clearing, the samples were transferred into new Protein LoBind Tubes and incubated overnight at 4\u2009\u00b0C with 5\u2009\u00b5g of HMGB2 (Abcam; ab67282), V5 (Abcam; ab9116; used for SKMEL5 ChIP only) and H3K4me3 (Epicypher; 13-0041) antibodies. For normalization purposes, 5\u2009\u00b5l of Drosophila spike-in chromatin (Active Motif; 53083) and 2\u2009\u00b5l of spike-in antibody (Active Motif; 61686) were added to each reaction. The next day, 50\u2009\u00b5l of BSA-blocked Dynabeads Protein G was added to each reaction and incubated for 2\u2009h at 4\u2009\u00b0C. The beads were then washed twice with low-salt washing buffer (150\u2009mM NaCl, 1% Triton X-100, 0.1% SDS, 2\u2009mM EDTA and 20\u2009mM Tris\u2013HCl (pH\u20098.0)), twice with high-salt washing buffer (500\u2009mM NaCl, 1% Triton X-100, 0.1% SDS, 2\u2009mM EDTA and 20\u2009mM Tris\u2013HCl (pH\u20098.0)), twice with LiCL wash buffer (250\u2009mM LiCl, 10\u2009mM Tris\u2013HCl (pH\u20098.0), 1\u2009mM EDTA, 1% Na deoxycholate and 1% IGEPAL CA-630) and once with TE buffer (10\u2009mM Tris\u2013HCl (pH\u20098.0) and 1\u2009mM EDTA). The samples were then reverse-crosslinked overnight in the elution buffer (1% SDS and 0.1\u2009M NaHCO3) and purified using the ChIP DNA Clean &amp; Concentrator kit (Zymo Research; D5205) following the manufacturer\u2019s instructions. After quantification of the recovered DNA fragments, libraries were prepared using the ThruPLEX DNA-Seq Kit (Takara Bio; R400676) following the manufacturer\u2019s instructions, purified with SPRIselect magnetic beads (Beckman Coulter; B23318) and quantified using a Qubit Flex fluorometer (Thermo Fisher Scientific) and profiled using TapeStation (Agilent). The libraries were sent to MSKCC Integrated Genomics Operation core facility for sequencing on an Illumina NovaSeq 6000 (approximately 30\u201340\u2009million 100-bp paired-end reads per library).<\/p>\n<p>Data analysis<\/p>\n<p>ChIP\u2013seq reads were trimmed and filtered for quality and library adaptors using TrimGalore (v.0.4.5) with a quality setting of 15 and running cutadapt<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 76\" title=\"Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, 10 (2011).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR76\" id=\"ref-link-section-d143698561e3545\" rel=\"nofollow noopener\" target=\"_blank\">76<\/a> (v.1.15) and FastQC (v.0.11.5). Reads were aligned to human assembly hg38 using Bowtie 2 (v.2.3.4.1) (ref.\u2009<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 77\" title=\"Langmead, B. &amp; Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357&#x2013;359 (2012).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR77\" id=\"ref-link-section-d143698561e3549\" rel=\"nofollow noopener\" target=\"_blank\">77<\/a>) and were deduplicated using MarkDuplicates in Picard Tools (v.2.16.0). To ascertain enriched regions, MACS2 (ref.\u2009<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 78\" title=\"Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR78\" id=\"ref-link-section-d143698561e3553\" rel=\"nofollow noopener\" target=\"_blank\">78<\/a>) was used with a P-value setting of 0.001 and run against a matched control for each condition. A peak atlas was created by combining the superset of all peaks using the \u2018merge\u2019 function in the BEDTools suite (v.2.29.2). Read density profiles were created using deepTools \u2018bamCoverage\u2019 (v.3.3.0), normalized to ten million uniquely mapped reads and with read pile-ups extended to 200\u2009bp. The tool featureCounts (v.1.6.1) was used to build a raw count matrix, and DESeq2 was used to calculate the differential enrichment for all pairwise contrasts for experiments with replicates. For single-sample data, MACS2 was run by swapping bams of different conditions to find differential regions. Peak gene associations were created by assigning all intragenic peaks to that gene, whereas intergenic peaks were assigned using the linear genomic distance to the transcription start site. GSEA<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 82\" title=\"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&#x2013;15550 (2005).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR82\" id=\"ref-link-section-d143698561e3560\" rel=\"nofollow noopener\" target=\"_blank\">82<\/a> was performed with the pre-ranked option and default parameters, in which each gene was assigned the single peak with the largest (in magnitude) log2FC associated with it. Composite and tornado plots were created using deepTools<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 80\" title=\"Ram&#xED;rez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 44, W160&#x2013;W165 (2016).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR80\" id=\"ref-link-section-d143698561e3567\" rel=\"nofollow noopener\" target=\"_blank\">80<\/a> (v.3.3.0) by running computeMatrix and plotHeatmap on normalized bigwigs with average signal sampled in 25-bp windows and flanking region defined by the surrounding 2\u2009kb. Motif signatures were obtained using Homer<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 81\" title=\"Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576&#x2013;589 (2010).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR81\" id=\"ref-link-section-d143698561e3571\" rel=\"nofollow noopener\" target=\"_blank\">81<\/a> (v.4.5).<\/p>\n<p>Reanalysis of human melanoma scRNA-seq data<\/p>\n<p>Human melanoma scRNA-seq data from a previous study<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 7\" title=\"Jerby-Arnon, L. et al. A cancer cell program promotes T cell exclusion and resistance to checkpoint blockade. Cell 175, 984&#x2013;997 (2018).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR7\" id=\"ref-link-section-d143698561e3584\" rel=\"nofollow noopener\" target=\"_blank\">7<\/a> were downloaded from Gene Expression Omnibus (GEO) (<a href=\"https:\/\/www.ncbi.nlm.nih.gov\/geo\/query\/acc.cgi?acc=GSE115978\" rel=\"nofollow noopener\" target=\"_blank\">GSE115978<\/a>). All analyses were performed in R using Seurat<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 83\" title=\"Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573&#x2013;3587 (2021).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR83\" id=\"ref-link-section-d143698561e3595\" rel=\"nofollow noopener\" target=\"_blank\">83<\/a> (v.4.4.0 and v.5.0.1). The count matrix was normalized using sctransform. Clustering was done using Seurat functions (FindNeighbors and FindClusters) with a resolution of 0.8. Cell types and treatment status were annotated using metadata from the original publication<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 7\" title=\"Jerby-Arnon, L. et al. A cancer cell program promotes T cell exclusion and resistance to checkpoint blockade. Cell 175, 984&#x2013;997 (2018).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR7\" id=\"ref-link-section-d143698561e3599\" rel=\"nofollow noopener\" target=\"_blank\">7<\/a>. Cell types were classified using gene lists from a previous study<a data-track=\"click\" data-track-action=\"reference anchor\" data-track-label=\"link\" data-test=\"citation-ref\" aria-label=\"Reference 2\" title=\"Tsoi, J. et al. Multi-stage differentiation defines melanoma subtypes with differential vulnerability to drug-induced iron-dependent oxidative stress. Cancer Cell 33, 890&#x2013;904 (2018).\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#ref-CR2\" id=\"ref-link-section-d143698561e3603\" rel=\"nofollow noopener\" target=\"_blank\">2<\/a> and the Seurat function AddModuleScore with default parameters. Module scores were scaled between 0 and 1. Cells were classified by differentiation state on the basis of the highest expression score for the given gene modules. Differentially expressed genes were calculated using the Seurat function FindMarkers with default parameters. GSEA was performed using fgsea, as described above.<\/p>\n<p>Statistics and reproducibility<\/p>\n<p>All statistical analyses and plotting were performed in either R (for RNA-seq and ATAC-seq data; v.4.3.1) or MATLAB (for imaging data; v.R2021b). For scRNA-seq data, P values were calculated using the Wilcoxon rank-sum test with Bonferroni\u2019s correction for multiple groups (R function pairwise.wilcox.test). Pearson correlation coefficients and corresponding P values were calculated using the R function cor.test. For differential expression analyses of bulk RNA-seq and bulk ATAC-seq data, P values were calculated in DESeq2 using the Wald test. For image analysis, P values were calculated using MATLAB functions (anova1 and multcompare) using the Tukey post hoc test. To calculate the cell migration velocity, the Euclidean distance travelled by individual cells across time points was measured using the MATLAB function pdist, and the velocity was calculated by dividing by the time step. For mouse experiments, we performed a series of likelihood ratio tests to investigate growth rate differences. A biexponential model was fit to the growth curve using maximum likelihood estimation to obtain estimates for the early-time and late-time growth rates, with a single exponential fit to vehicle data. For all representative images shown, the images represent at least three independent replicates.<\/p>\n<p>Reporting summary<\/p>\n<p>Further information on research design is available in the\u00a0<a data-track=\"click\" data-track-label=\"link\" data-track-action=\"supplementary material anchor\" href=\"http:\/\/www.nature.com\/articles\/s41586-025-09445-6#MOESM2\" rel=\"nofollow noopener\" target=\"_blank\">Nature Portfolio Reporting Summary<\/a> linked to this article.<\/p>\n","protected":false},"excerpt":{"rendered":"Zebrafish husbandry Stable transgenic zebrafish lines were kept at 28.5\u2009\u00b0C in a dedicated aquatics facility with a 14\u2009h&hellip;\n","protected":false},"author":2,"featured_media":102856,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[25],"tags":[49,48,59227,5123,59228,316,1099,59229,1100,66,59230],"class_list":{"0":"post-102855","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-genetics","8":"tag-ca","9":"tag-canada","10":"tag-cancer-imaging","11":"tag-cancer-microenvironment","12":"tag-cancer-models","13":"tag-genetics","14":"tag-humanities-and-social-sciences","15":"tag-melanoma","16":"tag-multidisciplinary","17":"tag-science","18":"tag-tumour-heterogeneity"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/posts\/102855","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/comments?post=102855"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/posts\/102855\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/media\/102856"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/media?parent=102855"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/categories?post=102855"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ca\/wp-json\/wp\/v2\/tags?post=102855"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}