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Figure S1 Whole-Genome Bisulfite Sequencing of Single CTCs and CTC Clusters, Related to Figure 1 Show full caption (A) CTC capture efficiency from blood spiked with BR16 or BRx50 single CTCs and CTC clusters, using the Parsortix device (n = 2 per cell line with 500 single CTCs and 150 CTC clusters). Error bars represent SEM. (B) 250 single BR16-GFP+ and 250 single BR16-RFP+ cells are spiked in blood and CTCs are enriched using the Parsortix device. Captured CTCs are of single color, revealing no artificial cluster formation during processing (n = 2). Error bars represent SEM. (C) Representative pictures of single CTCs and CTC clusters from breast cancer patients, enriched with the Parsortix microfluidic device and stained for EpCAM, HER2 and EGFR (green). White blood cells (WBCs) are counterstained with CD45 (red). (D and E) Bar graph showing the percent of CpG sites that are covered in individual CTC clusters and single CTCs from patients (D) and xenografts (E). (F and G) Principal component analysis of patient-derived (F) and xenograft-derived (G) single CTCs and CTC clusters, based on all features with p ≤ 0.05. (H and I) Metaplots showing the percentage (%) of CpG methylation at CpG islands (H) and reference genes (I) in CTC clusters (blue line) and single CTCs (dotted red line). TSS: Transcription Start Site; TES: Transcription End Site. (J–L) Hypergeometric gene set enrichment analysis of promoters (J), gene bodies (K) and super-enhancers (L) displaying ≥ 20% methylation difference (p value ≤ 0.01) in xenograft-derived CTC clusters compared to single CTCs. Gene sets with adjusted p value ≤ 0.05 are shown for promoters (J) and gene bodies (K). For super-enhancers (L), the top-20 significant gene sets with adjusted p value ≤ 0.05 are shown. Gene sets related to PRC2 activity are highlighted in red. (M) Histogram showing mapped reads in patient CTCs corresponding to a methylated cytosine (C) (red) or a thymine (T) (blue; corresponding to a bisulfite-converted, unmethylated cytosine) in representative regions that include binding sites for OCT4, SOX2, NANOG and SIN3A (shaded-orange box). n = number of CpGs covered.

Figure 1 Whole-Genome Bisulfite Sequencing Analysis of CTCs from Breast Cancer Patients and Xenografts Show full caption (A) Heatmap showing methylation variable regions with ≥ 80% methylation difference between patient-derived CTC clusters and single CTCs (false discovery rate [FDR] < 0.05). (B) Heatmap showing methylation variable regions with ≥ 70% methylation difference between xenograft-derived CTC clusters and single CTCs (FDR < 0.05). (C and D) Normalized enrichment score (NES) representing enrichment (NES ≥ 3.4) of transcription factor binding sites (TFBSs) in CTC cluster hypomethylated regions (blue) and single CTC hypomethylated regions (red) of patients (C) or xenografts (D), identified using i-cisTarget. (E and F) Integrated gene ontology (GO) and pathway enrichment analysis of TFBSs identified using i-cisTarget in hypomethylated regions of both patient- and xenograft-derived CTC clusters (E) or single CTCs (F). The bars represent the percentage of genes detected per GO and pathway term with p ≤ 0.05. See also Figure S1 and Tables S1 and S2

We first sought to identify active transcription factor networks by means of accessible TFBSs in single and clustered human breast CTCs, matched within individual liquid biopsies, through a genome-wide single-cell resolution DNA methylation analysis. To this end, blood samples were drawn from 43 patients with progressive breast cancer and processed with the Parsortix device (), a microfluidic technology that allows a size-based, antigen-agnostic enrichment of CTCs from unprocessed blood samples, specifically adapted to achieve a capture rate of >97.2% for single CTCs and >99.3% for CTC clusters, and no artificial cluster formation during sample processing ( Figures S1 A and S1B). Upon capture, live CTCs were stained for cell surface expression of EpCAM, HER2, and EGFR, and counterstained with antibodies against CD45 to identify contaminant leukocytes ( Figure S1 C). Upon staining verification, we identified matched single and clustered CTCs in 19% of the analyzed samples (8/43 patients), and a total of 18 marker-positive single CTCs and 29 marker-positive CTC clusters from four patients were individually micromanipulated and deposited in lysis buffer for single-cell resolution whole-genome bisulfite sequencing ( Table S1 ) (). In parallel, we isolated spontaneously generated GFP-labeled single CTCs and CTC clusters from three mouse xenograft models, including two human breast CTC-derived cell lines (BR16 and BRx50) and the human breast cancer cell line MDA-MB 231 (lung metastatic variant, referred to as LM2) (). In this setting, we individually micromanipulated 71 single CTCs and 48 CTC clusters ( Table S1 ) and also processed them for single-cell resolution whole-genome bisulfite sequencing (). Samples with a low coverage (< 1,000 unique CpGs) or a low bisulfite conversion efficiency (CG/CHG/CHH < 97%)—corresponding to 10.7% of patient-derived samples and 0.8% of xenograft-derived samples—were excluded from the analysis, resulting in a total of 89 single CTCs and 71 CTC clusters from patients and xenografts. On average, we achieved 3.68% CpG coverage for single CTCs and 5.86% CpG coverage for CTC clusters, in line with recent single-cell whole-genome bisulfite sequencing studies () ( Figures S1 D and S1E; Table S2 ). As expected, principal component analysis (PCA) mainly segregated CTCs based on the patient of origin or the specific xenograft model ( Figures S1 F and S1G). Metagene plot of CpG methylation revealed comparable methylation levels between single CTCs and CTC clusters across CpG islands, gene bodies, upstream (promoters) and downstream regions, including a drop of CpG methylation around the transcriptional start site, as expected ( Figures S1 H and S1I). We then specifically investigated differentially methylated regions (DMRs) between single CTCs and CTC clusters, evaluating average methylation levels in overlapping 5-kb windows, as previously established for single-cell DMR analysis (). For patient-derived CTCs, with this approach we identified 3,347 DMRs with a ≥ 80% methylation difference between single CTCs and CTC clusters. Of these, 1,305 regions were hypomethylated in CTC clusters and 2,042 were hypomethylated in single CTCs ( Figure 1 A). We then looked at xenograft-derived CTCs, and to evaluate a comparable number of DMRs as found in patients, we assessed overlapping regions with a ≥ 70% methylation difference between single CTCs and CTC clusters. We found a total of 1,430 DMRs, of which 909 hypomethylated in CTC clusters and 521 hypomethylated in single CTCs ( Figure 1 B). We then analyzed DMRs from both patient- and xenograft-derived CTCs using i-cisTarget (). With this analysis, among hypomethylated regions that are specific to either single CTCs or CTC clusters, we found a significant enrichment for several TFBSs, many of which overlapped between patient- and xenograft-derived CTCs ( Figures 1 C and 1D), thus allowing us to define specific hypomethylated TFBSs that globally characterize either single CTCs or CTC clusters in both patients and xenografts. Integrated gene ontology (GO) and pathway analysis of global CTC cluster hypomethylated TFBSs revealed a remarkable enrichment for stemness-related transcription factors that coordinately regulate proliferation and pluripotency, including OCT4, NANOG, SOX2, and SIN3A, paralleling embryonic stem cell (ESCs) biology ( Figure 1 E) (). Differently, single CTCs featured hypomethylation of other TFBSs, including those that are occupied by MEF2C, JUN, MIXL1, and SHOX2, commonly enriched in various cancers (), yet independent of a core pluripotency network ( Figure 1 F) (). To gain insights into more subtle changes in DNA methylation occurring specifically within promoters, gene bodies, and super enhancer regions, we carried out hypergeometric-based gene set enrichment analysis of genomic features in xenograft-derived CTCs (displaying a higher homogeneity compared to patient-derived CTCs). Consistently, this analysis revealed hypermethylation and H3K27me3 repression of Polycomb-repressive complex 2 (PRC2) target gene promoters and gene bodies (including those for SUZ12 and EED) in CTC clusters ( Figures S1 J–S1L), as previously alluded to in cancer specimens with stem-like and proliferative features () and mirroring ESCs biology ().