The Lipogenic Regulator SREBP2 Induces Transferrin in Circulating Melanoma Cells and Suppresses Ferroptosis

Metastatic melanoma remains a highly lethal malignancy, despite breakthroughs in the targeted treatment of BRAF-mutant cases (1–3) and the application of immune checkpoint therapies irrespective of genotype (4–8). Melanomas with BRAF^V600E and associated oncogenic variants typically undergo rapid tumor shrinkage following treatment with combination BRAF and MEK inhibitors, although there is considerable variation in the degree of initial response, and virtually all cases recur with drug-resistant disease. The effectiveness of immune-targeted therapies appears to be determined in part by total mutational burden in the tumor and the associated presentation of neoantigens, which are typically high in melanoma (9–14), but only a third of patients have sustained responses (15, 16). For both targeted and immune-based therapies, innate and acquired resistance is compounded by tumor heterogeneity in signaling pathways, expression of cell surface epitopes, and intrinsic cell survival pathways.

The transition from primary melanoma to metastatic disease is characterized by blood-based dissemination of circulating tumor cells (CTC) to diverse metastatic sites, as is the progression from oligometastatic to widespread metastatic disease. Although melanoma cells are notoriously invasive and resistant to any therapeutic interventions other than immunologic and BRAF-targeted treatments, the exceptional environment in the bloodstream may provide new therapeutic opportunities to suppress metastasis.

Specifically, the high oxygen content of blood has been shown to render primary melanoma cells vulnerable to reactive oxygen species (ROS; ref. 17). Identifying innate mechanisms that confer resistance to ROS, and thereby enable a subset of melanoma cells to remain viable as they circulate in the blood, may thus provide new therapeutic targets to suppress metastatic precursors.

The small number of CTCs present within a blood specimen, admixed to billions of normal blood cells, presents significant technical challenges to their isolation and functional analysis (18). Neural crest–derived melanoma cells do not express the epithelial cell surface protein epithelial cell adhesion molecule EPCAM, which is traditionally used to capture CTCs using magnetically conjugated antibody enrichment (19, 20). Furthermore, melanoma cells display a high degree of heterogeneity in cell surface epitope expression, which complicates their direct capture using lineage- or tumor-specific antibody panels (21). In designing a tumor-agnostic strategy for isolating CTCs within blood specimens, we developed a platform (CTC-iChip) for efficient depletion of normal blood cells, thereby enriching for cancer cells irrespective of cell surface markers (22, 23). Taking advantage of microfluidic flow kinetics, this CTC-iChip achieves initial size-based exclusion of red blood cells and platelets, followed by inertial focusing of all nucleated blood cells into a single streamline, through which antibody-tagged leukocytes are magnetically separated from unlabeled CTCs. Across multiple tumor types, this platform achieves 10⁴ enrichment for CTCs, and we have applied a digital RNA-based readout to allow highly sensitive measurement of melanoma tumor cell burden in the blood (24). The enrichment of untagged and unmanipulated CTCs not only enhances their RNA quality for such diagnostic purposes, but also helps to preserve their cell viability for functional studies.

We have previously reported the establishment of long-term CTC cultures from blood specimens of women with hormone receptor–positive breast cancer, which are often oligoclonal in origin and which recapitulate somatic mutations acquired during the course of therapy, and their epigenetic cell states (25–27). Here, we established CTC cultures from blood samples of patients with metastatic melanoma, comparing their transcriptomes across different cases, as well as in multiple single CTC-derived isogenic lines from the same patient. In these cultured melanoma CTCs and in single CTCs freshly isolated from blood specimens, we find striking upregulation of SREBP-driven lipogenic pathways, together with iron homeostatic pathways, including the iron transport protein Transferrin (TF). The master regulator of cholesterol homeostasis SREBP2, encoded by the SREBF2 gene, directly induces expression of TF, which in turn suppresses ROS and drug-induced ferroptotic cell death. Modulating these pathways in mouse models has a dramatic effect on metastasis, whereas their overexpression within patient-derived CTCs is strongly correlated with an adverse clinical outcome. Thus, the coordinated overexpression of SREBP target genes and TF in melanoma CTCs points to a regulatory pathway linking lipogenesis with iron homeostasis, contributing to the ability of viable CTCs to overcome oxidative damage in the circulation.

We generated patient-derived CTC cultures following microfluidic enrichment from blood samples of patients with metastatic melanoma. Five independent cultures were established from four patients [out of a cohort of 37 patients undergoing treatment on Institutional Review Board (IRB)–approved protocols at Massachusetts General Hospital Cancer Center]. The CTC-iChip was used to deplete normal hematopoietic cells from 10 mL of whole blood, and the enriched, unlabeled CTCs were maintained in anchorage-independent media, under hypoxic conditions, and in the presence of heparin and RHO kinase inhibitor (refs. 22, 23, 25; see Methods). To confirm their identity as melanoma cells, the cultured CTCs were tested for expression of characteristic melanoma markers (ref. 24; Fig. 1A; Supplementary Fig. S1A and S1B) and shown to have shared mutational profiles with their respective parental tumors, including the canonical drug-sensitizing BRAF^V600E or NRAS^Q61K mutations, as well as displaying predicted BRAF and MEK inhibitor sensitivity patterns (Fig. 1A; Supplementary Fig. S1C and S1D). The melanoma CTC lines were tested for tumorigenesis potential in immunosuppressed NOD/SCID gamma (NSG) mice. All five cultured lines are highly tumorigenic following subcutaneous inoculation, and four of them (PEM-78 being the exception) generated metastases upon direct intravascular injection, either by tail-vein or intracardiac inoculation (Fig. 1B and C; Supplementary Fig. S1E–S1J). Both primary tumors and metastases generated from GFP-luciferase–tagged CTCs show preservation of characteristic melanosome markers (Fig. 1C; Supplementary Fig. S1F, S1H, and S1K). We selected two of these CTC lines, Mel-167 and Mel-182-2, for detailed functional studies.

Having established robust tumorigenic and metastatic competent CTC cultures, we compared their transcriptomic profiles with those of standard melanoma tumor–derived cell lines [Cancer Cell Line Encyclopedia (CCLE)] and primary and metastatic melanoma tumors [The Cancer Genome Atlas (TCGA); refs. 28, 29]. By gene set variation analysis (GSVA; ref. 30), we found that the most significantly enriched pathways in the CTC lines were those involved in lipogenesis (“SREBP_TARGET,” “FATTY_ACID_METABOLISM,” “ADIPOGENESIS,” and “CHOLESTEROL_HOMEOSTASIS”), along with iron-related pathways, including “OXIDATIVE_PHOSPHORYLATION,” “FERROPTOSIS,” and “IRON_ION_HOMEOSTASIS,” after correction for batch effect (Fig. 1D–F; Supplementary Fig. S2A and S2B). The dramatic enrichment of multiple pathways in CTC lines appears to be independent of tumor site of origin or differences in culture media and hypoxic conditions in vitro. A modest increase in SREBP_TARGET signatures is also observed in CCLE cell lines when compared with primary tumor samples (Fig. 1D; Supplementary Tables S1–S3). Thus, transcriptional profiling of cultured melanoma CTC lines from multiple patients compared with traditional melanoma cell lines and with primary melanoma specimens reveals concurrent upregulation of lipogenesis and iron-dependent metabolic signatures.

Mel-167 CTC cultures, established prior to any treatment administration from a patient who was newly diagnosed with metastatic melanoma, are multiclonal in origin. Despite having the characteristic BRAF^V600E drug-sensitizing mutation, the patient had only a transient (<3 months) clinical response to the standard combined BRAF/MEK inhibition regimen, suggesting the presence of intrinsically drug-resistant cancer cells at the time of diagnosis. Upon generating 13 single CTC-derived clones from the pretreatment specimen, we indeed observed a range of sensitivity to the BRAF inhibitor vemurafenib among these untreated cultured CTC clones (Fig. 2A and B). Defining the resistant versus sensitive clones as those with an IC₅₀ for vemurafenib that is either above or below that of the bulk CTC population, we first tested for mutational heterogeneity using whole-exome sequencing (WES) of four resistant clonal lines, versus two sensitive clones, the bulk parental Mel-167 culture, and the matched primary melanoma tumor (Supplementary Fig. S3A). No new driver mutations were detected across these clonally related lines that could account for the differential drug sensitivity. However, RNA sequencing (RNA-seq) profiles of all 13 isogenic CTC lines, followed by GSVA, identified lipogenesis pathways as being highly enriched in the drug-resistant CTC clones, compared with sensitive lines (CHOLESTEROL_HOMEOSTATIS, P = 0.0098; SREBF1_TARGET, P = 0.0135; SREBF2_TARGET, P = 0.0212; and SREBP_TARGET, P = 0.0201; Fig. 2C; Supplementary Fig. S3B). The individual clones were heterogeneous with respect to tumorigenic phenotypes (Supplementary Fig. S3C). Thus, upregulation of SREBP-dependent lipogenesis is correlated with innate resistance to BRAF inhibition, within a subset of untreated patient-derived isogenic clonal CTC lines.

To test the functional consequences of modulating SREBP activity in these untreated cultured melanoma CTCs, we achieved double knockdown of SREBF1 and SREBF2 using siRNA combinations in parental Mel-167 CTCs, showing significant enhancement of sensitivity to the BRAF inhibitor vemurafenib (Fig. 2D; Supplementary Fig. S3D). Conversely, doxycycline-inducible expression of a mature isoform of SREBP2, which bypasses normal cellular processing and directly translocates to the nucleus to activate lipogenic signaling (31), results in a high degree of resistance to vemurafenib (Fig. 2E). We also tested the effect of the SREBP inhibitor fatostatin: Mel-167 CTCs display strong cooperative sensitivity to vemurafenib and fatostatin in suppressing soft-agar colony number (Fig. 2F) and soft-agar colony size (Supplementary Fig. S3E), established in vitro correlates of tumorigenicity.

To test whether the effect of SREBP-dependent lipogenesis extends from innate resistance to vemurafenib in untreated melanoma cells to acquired drug-induced resistance, we cultured Mel-167 CTCs in the presence of 1 μmol/L vemurafenib for 3 months, generating two independent resistant CTC lines. In both resistant lines, we find a significant increase in expression of endogenous SREBF1 and SREBF2, along with increased expression of the SREBP target genes SCD and ACSL1 (Fig. 2G). Both Mel-167 CTC lines with acquired vemurafenib resistance display enhanced sensitivity to the SREBP inhibitor fatostatin, as measured by reduced number and size of soft-agar colonies (Fig. 2H; Supplementary Fig. S3F). Finally, consistent with an effect of lipogenic regulation on cellular redox potential, both SREBP-high, vemurafenib-resistant Mel-167 clones show an increased reduced-to-oxidized glutathione (GSH/GSSG) ratio, indicative of enhanced ROS-neutralizing capacity (Fig. 2I; total GSH and GSSG levels are shown in Supplementary Fig. S3G and S3H).

Taken together, resistance by BRAF-mutant CTCs to vemurafenib is correlated with SREBP activity, both among heterogeneous clonal cultures drawn from an untreated patient, as well as following in vitro drug selection to generate acquired resistance. Suppression of SREBP activity by knocking down both SREBF1 and SREBF2 or treatment with fatostatin abrogates this drug resistance phenotype, whereas ectopic SREBF2 expression alone is sufficient to dramatically enhance vemurafenib resistance.

SREBF1 and SREBF2 are central players of lipogenesis, with SREBF1 primarily linked to lipid metabolism and SREBF2 being the master regulator of cholesterol synthesis. Both SREBP paralogs are known to be aberrantly expressed in some cancers, although their functional significance in carcinogenesis remains poorly understood (32, 33). To determine which SREBF genes are functionally important in mediating the melanoma CTC tumorigenic and drug resistance phenotypes, we first compared SREBF1 and SREBF2 mRNA expression levels in CTC lines using RNA-seq. All five CTC lines showed higher abundance of SREBF2 mRNA, compared with SREBF1 (Supplementary Fig. S4A). Consistent with this finding, higher activity of SREBF2, compared with SREBF1, is detected by GSVA enrichment scores of SREBF1/2 target gene expression in these CTC lines (Supplementary Fig. S4B; Supplementary Table S2). We used specific antisense oligos (ASO) to effectively suppress SREBF1 or SREBF2 individually, or both together (SREBF1-KD, SREBF2-KD, and SREBF1/2-KD, respectively) in the Mel-167 CTC line (Fig. 3A), quantifying clonogenic growth in soft agar, a well-established correlate of tumorigenesis. SREBF2-KD significantly suppresses soft-agar growth, whereas SREBF1-KD has no effect (Fig. 3B). The combination of the two ASOs (SREBF1/2-KD) demonstrates modestly increased colony suppression, compared with SREBF2-KD alone (Fig. 3B, P = 0.0480 for SREBF2-KD vs. control and P = 0.0277 for SREBF1/2-KD vs. control). Interestingly, mTOR signaling has been implicated in lipogenic signaling (34), and although its inhibitor Torin 1 suppresses expression of SREBF1 in Mel-167 CTCs, it does not affect levels of SREBF2 (Supplementary Fig. S4C and S4D). Thus, although SREBF1 may enhance the effect of SREBF2, the latter is most relevant to Mel-167 CTC tumorigenesis.

To identify SREBF2-regulated genes mediating these tumor-enhancing effects, we undertook chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq), defining direct SREBF2 transcriptional targets in cultured melanoma CTCs. Well-established SREBP targets implicated in lipogenesis are readily identified by ChIP-seq (Fig. 3C; Supplementary Table S4). However, additional in vivo SREBP-binding sites are also identified in the promoters of multiple genes involved in ferroptosis and iron homeostasis (Fig. 3C; Supplementary Table S4), supporting the coordinated expression of these pathways, previously observed in multiple CTC lines (Fig. 1D–F). Key to the intersection between these pathways appears to be the iron-binding protein TF: Comparing the set of genes commonly upregulated across the cultured melanoma CTCs versus primary tumors, metastases, and CCLE melanoma lines (N = 586) with the set of genes whose promoters are bound by SREBP2 in CTCs (N = 3,813), we identified 258 candidate targets, of which the most highly upregulated hit was TF (mean fold change = 54.19; Fig. 3D; Supplementary Fig. S5A). In an independent analysis, we compared RNA-seq transcriptional profiles of two melanoma CTC lines versus their individually matched archival tumor specimens: Mel-167 (CTCs vs. matched primary tumor) and PEM-22 (CTCs vs. six patient-matched–independent metastatic lesions). Among 10 differentially expressed transcripts shared in these two pairwise comparisons (genes upregulated > 32-fold in CTCs), TF was the most highly differentially expressed (first hit in PEM-22, fourth in Mel-167; Supplementary Fig. S5B). Interestingly, endogenous TF expression is also significantly upregulated in the clonally derived Mel-167 CTC lines with intrinsic vemurafenib resistance, compared with the sensitive isogenic clones (Supplementary Fig. S5C). We therefore selected the iron-binding protein TF as a novel candidate SREBP2 target, with potential relevance to lipogenic regulation of iron metabolism and tumorigenesis.

Direct visualization of the ChIP-seq reads confirms a sharp peak of SREBP binding at the site of the TF gene promoter (Fig. 3E). The promoter contains two adjacent predicted SREBP-binding sites (Catalog of Inferred Sequence Binding Preferences; ref. 35): motifs M2388_1.02, ATGAGGTGAT, and M6488_1.02, GGGTTGGGAGAGG (Fig. 3F; Supplementary Fig. S5D). Direct in vivo binding of SREBP2 to TF promoter fragments containing the two predicted sites is evident using ChIP followed by PCR amplification of the DNA sequences (ChIP-qPCR; Fig. 3F; Supplementary Fig. S5D). We note that ASOs targeting SREBF2 suppress TF expression effectively, whereas knockdown of SREBF1 has a mild effect on TF expression in Mel-167 CTCs (Fig. 3G). Soft-agar growth suppression is observed only in SREBF2-KD but not in SREBF1-KD Mel-167 CTCs (Fig. 3B), and a modest enhancement of TF suppression is evident with the combined knockdown (Fig. 3G). mTOR inhibition, which suppresses SREBF1 but not SREBF2 expression, also does not affect TF expression (Supplementary Fig. S4C and S4D). Finally, to confirm the functional consequence of these chromatin-binding studies, we used doxycycline-inducible SREBF2, demonstrating robust induction of TF mRNA and TF protein expression in cultured melanoma CTCs (Fig. 3H and I). Taken all together, TF is a novel SREBF2 target gene in melanoma CTCs, raising the possibility that it may contribute to the lipogenic tumorigenesis phenotype through modulation of iron homeostasis and ferroptosis.

TF plays a critical role in regulating iron trafficking and metabolism. It is normally expressed only in the liver, from which it is secreted into the bloodstream where it binds tightly to iron, ultimately interacting with the TF receptor expressed by multiple cell types and internalized (36). Although expression of the TF receptor (TFRC) gene is common in cancer (37), TF transcripts are rarely detected except in liver and in some cell types in the brain (38, 39). To exclude the possibility that aberrant TF expression in CTCs results from in vitro culture conditions, we undertook single-cell RNA-seq of individually picked melanoma CTCs following microfluidic enrichment from primary blood specimens. Among 76 individual CTCs freshly isolated from 22 patients and validated to be melanoma cells by their expression of melanoma lineage markers (24), 7 (9.2%) expressed TF mRNA [mean expression = 17.64, transcripts per million (TPM); Fig. 4A]. Such fresh CTCs include both viable and preapoptotic cells with variable RNA quality. However, TF expression is detectable in as many as 9 of 20 (45%) single CTCs that have been incubated in culture medium for 4 to 8 weeks, a condition in which only viable CTCs persist, but before they initiate in vitro proliferation (mean expression = 90.14 TPM; Fig. 4A). TF expression is neither evident in individually selected leukocytes nor detectable in similarly isolated prostate or hormone receptor–positive breast CTCs, suggesting a melanoma-specific pathway (Supplementary Fig. S5E; refs. 25, 40, 41).

Because TF is primarily a secreted protein, we tested whether a fraction might be retained intracellularly. We compared the liver cancer–derived HepG2 cells with the melanoma CTC Mel-167, demonstrating comparable levels of TF mRNA (Supplementary Fig. S6A). Minimal baseline levels of TF protein are present in the culture medium that is used to maintain either HepG2 or Mel-167, with or without addition of FBS or B27 supplements (Supplementary Fig. S6B). Following cell culture, TF is detectably secreted into the conditioned medium, and under comparable conditions, we calculate that Mel-167 CTCs secrete 45% of the TF secreted by HepG2 cells (Supplementary Fig. S6C). However, compared with HepG2 cells, Mel-167 CTCs retain 620% higher levels of TF intracellularly (Supplementary Fig. S6D; calculated as 19.22 ng/mL from 1 million cells for Mel-167 vs. 3.10 ng for HepG2 cells), with cell fractionation experiments showing most of the intracellular TF present in cytoplasmic and membrane fractions (Supplementary Fig. S6E). Intracellular retention of TF protein in Mel-167 CTCs may be partially explained by the presence of alternatively spliced transcripts, approximately 1.4% of which lack the secretion signal sequence that spans exons 1 and 2 (Supplementary Fig. S6F and S6G). Alternatively, it is also possible that an increase in secreted TF may result in more recycled TF–TFRC complex within the endosomal compartment.

To determine the functional consequences of aberrant TF expression in melanoma CTCs, we tested the effect of two independent short hairpin RNAs (shRNA) in Mel-167 CTCs. TF knockdown (TF-KD) using either of these shRNA constructs leads to a modest reduction in proliferation under baseline in vitro culture conditions (reduced by 34.5% for shTF #1, P = 0.0272, and 35.5% for shTF #2, P = 0.0384, at day 4 of growth when compared with shControl; Fig. 4B; Supplementary Fig. S7A and S7B), but a marked suppression of clonogenic activity by 65.9% for shTF #1 (P = 0.0026) and 84.8% for shTF #2 (P = 0.0013) in soft agar (Fig. 4C; Supplementary Fig. S7C). Subcutaneous tumor formation is suppressed by either shRNA construct in Mel-167 CTCs (a reduction in tumor size by 69.2% for shTF #1, P = 0.0011, and 88.9% for shTF #2 as compared with shControl, P = 0.0008; Fig. 4D), and metastatic colonization following tail-vein injection is abrogated, as measured by whole-mouse imaging [in vivo imaging system (IVIS); Fig. 4E and F], as well as histologic analysis of lung, liver, and kidney metastases (Supplementary Fig. S7D–S7F).

To confirm the specificity of this effect, we generated a synthetic TF cDNA, in which mutation of three third-position nucleotides in the coding region of TF confers resistance to knockdown by shTF #1, without affecting expression levels (TF^ALT, Supplementary Fig. S8A and S8B). In Mel-167, as well as in Mel-182-2, a second, independently isolated CTC line derived from another patient with metastatic melanoma, TF-KD was effectively rescued by ectopic expression of TF^ALT, resulting in restitution of TF mRNA and protein expression (Supplementary Fig. S8C–S8F). In both CTC-derived cell lines, TF depletion leads to the suppression in soft-agar colony growth, which is largely rescued by overexpression of TF^ALT (Mel-167: P = 0.0004 comparing shTF #1 with shTF #1 + Rescue; Mel-182-2: P = 0.0027 comparing shTF #1 with Control; P = 0.0159 comparing shTF #1 with shTF #1 + Rescue; Supplementary Fig. S8G and S8H). Therefore, in melanoma CTCs that have acquired aberrant expression of TF, its suppression compromises tumorigenic phenotypes.

Although the function of TF in regulating iron levels in the blood circulation is well established, it may also play a role in regulating intracellular iron through a sequestration mechanism, similar to iron-complexed ferritin, the primary source of intracellular iron storage (42). Depletion of intracellular iron may compromise key iron-dependent pathways, whereas its overabundance may trigger iron-dependent cell death pathways, such as ferroptosis (43, 44). Gene set enrichment analysis (GSEA) shows a predominant signaling pathway upregulated in TF-KD Mel-167 CTCs to be “REACTIVE_OXYGEN_SPECIES” (P = 0.0049, Fig. 5A; Supplementary Table S5). Indeed, TF-KD cells have a significant increase in ROS compared with shRNA controls, as measured by a fluorescent reporter (68% increase for shTF #1, P = 0.0028; 118% increase for shTF #2, P = 0.0104; Fig. 5B). Similarly, lipid peroxidation is strikingly increased in TF-KD melanoma CTCs, compared with controls (Fig. 5C). This effect is iron-dependent because cotreatment of Mel-167 CTCs with the iron chelator deferoxamine (DFO; 50 μmol/L) results in restoration of lipid ROS to normal levels, comparable to those observed following TF rescue through expression in Mel-167 CTCs of the synthetic shRNA-resistant cDNA TF^ALT (Fig. 5C). Similar effects on lipid peroxidation following TF-KD and rescue by either DFO or the TF^ALT construct are evident in the second CTC line Mel-182-2 (Supplementary Fig. S8I).

Consistent with these findings, TF-KD CTCs show increased sensitivity to the ferroptosis inducer RSL3 (45) compared with control, indicating that the increased ROS and lipid peroxidation are correlated with heightened susceptibility to ferroptosis (Fig. 5D). Mel-167 CTCs, which carry the BRAF^V600E mutation, also show increased sensitivity to vemurafenib following TF-KD (Fig. 5E), suggesting that failure to suppress lipid peroxidation may also result in enhanced killing by BRAF inhibitors in melanoma CTCs. Previous studies have reported that BRAF inhibitor–resistant melanoma cells exhibit increased sensitivity to ferroptosis (46, 47), suggesting cross-talk between these two druggable survival pathways. Ferroptosis itself is dependent on GPX4, which detoxifies lipid ROS at the expense of reduced GSH, leading us to assess the GSH/GSSH ratio as a measure of redox balance. Indeed, the ratio of GSH/GSSG is significantly reduced in shTF-treated cells, an effect that is rescued by expression of the synthetic TF^ALT construct (Fig. 5F; total GSH and GSSG levels are shown in Supplementary Fig. S8J and S8K). Given the potent effect of TF-KD on soft-agar clonogenic potential of melanoma CTCs, we tested a number of experimental rescue conditions. Both the antiferroptosis drug ferrostatin-1 (0.5 μmol/L) and the lipophilic antioxidant vitamin E (50 μmol/L) partially rescued the clonogenic suppression mediated by either of the two TF shRNA constructs (Fig. 5G and H). Both of these antioxidants also have a moderate effect on baseline soft-agar colony formation by melanoma CTCs. These observations are consistent with the role of TF expression in quenching intracellular free iron within melanoma CTCs.

To test the potential TF iron sequestration mechanism, we generated Mel-167 and Mel-182-2 CTCs with ectopic overexpression of TF. In both CTC lines, TF overexpression (Supplementary Fig. S8L and S8M) results in a significantly reduced pool of labile free iron, consistent with a sequestration mechanism (Fig. 5I; Supplementary Fig. S8N). To further test the functional effects of TF overexpression, we selected the CCLE melanoma cell line IGR-37, which does not express high levels of endogenous TF. Ectopic overexpression of TF in these cells leads to a reduction in lipid peroxidation (Supplementary Fig. S9A and S9B). Interestingly, ectopic expression of the mature and activated SREBF2 similarly reduces lipid peroxidation (Supplementary Fig. S9A and S9B). Ectopic overexpression of either TF or SREBF2 in IGR-37 melanoma cells also confers relative resistance to the ferroptosis inducer RSL3 (Supplementary Fig. S9C and S9D). Altogether, these observations support a model whereby TF expression regulates the intracellular labile free iron pool, affecting ROS and lipid peroxidation, with consequences for cellular susceptibility to ferroptosis.

The concordant expression of lipogenic and iron metabolic pathways observed in melanoma CTCs raises the possibility that these two pathways are mutually interregulated. We have shown that SREBP2 binds to the TF gene promoter and directly induces its expression, but modulation of TF levels themselves appears to affect SREBP targets, potentially through more indirect mechanisms. Indeed, TF-KD in melanoma CTCs leads to a reduction in expression of SREBP target genes: GSEA pathway analysis of RNA-seq data in TF-KD CTCs identifies lipogenesis as the most prominently downregulated pathway category, such as “SREBP_TARGET” (P = 0.0024, as well as “SREBF1/2_TARGET,” P = 0.0022 for both pathways) and “CHOLESTEROL_HOMEOSTASIS” (P = 0.0025; Fig. 6A and B; Supplementary Table S5). Conversely, ectopic expression of TF leads to upregulation of the downstream SREBP target transcripts SCD and ACSL1 (Fig. 6C; Supplementary Fig. S8M). Furthermore, the suppression of ACSL1 protein expression resulting from shRNA knockdown of TF is fully rescued by expression of the nondegradable TF^ALT construct (Supplementary Fig. S8E and S8F). Interestingly, addition of cholesterol (10 μg/mL), an endpoint of lipogenic pathways, rescues TF-KD clonogenic suppression (Fig. 6D and E). Thus, the iron homeostasis and lipogenic pathways appear to be mutually coregulated in melanoma CTCs, with SREBP2 directly activating the TF promoter, whereas TF expression may lead more indirectly to modulation of SREBP target gene expression and lipogenesis.

To extend these findings from cultured melanoma CTCs to freshly isolated individual CTCs from patients with metastatic melanoma, we undertook comprehensive single-cell RNA-seq of 76 individual CTCs collected from 22 patients using microfluidic CTC-iChip isolation, followed by confirmation of cell identity by expression of melanoma lineage markers (Fig. 7A). Hierarchical clustering analysis reveals a well-demarcated subpopulation of CTCs, “cluster 2,” comprising 43 of the 76 single CTCs (57%), with concerted upregulation of lipogenic programs (“SREBF2_TARGET,” “ADIPOGENESIS,” and “FATTY_ACID_METABOLISM”), iron homeostasis signatures (“IRON_ION_HOMEOSTASIS”), and proliferation (“MYC_TARGETS_V1 & V2”; comparing Cluster 2 vs. Cluster 1 CTCs, Fig. 7A; Supplementary Fig. S10A–S10D; Supplementary Table S6). Cluster 2 CTCs also show signatures of increased energy production that is iron-dependent (“OXIDATIVE_PHOSPHORYLATION”; Fig. 7A; Supplementary Table S6). The enrichment of these pathways in Cluster 2 CTCs remains significant even if only CTCs from patients receiving immunotherapy were analyzed (a total of 53 CTCs from 18 patients; Supplementary Table S6). Because the majority of patients with melanoma whose CTCs were analyzed here were enrolled on immune checkpoint therapies and some were treated with BRAF/MEK-targeted therapies (Supplementary Table S7), hence we were able to test whether these signatures were associated with responsive disease (RD) or progressive disease (PD), as measured by clinical imaging within a median of 74 days (-4 to 122) after CTC sampling (disease response was defined using RECIST1.1; see Supplementary Table S7). Within a given patient blood draw containing two or more CTCs, a high (>60%) fraction of CTCs expressing signatures of “Lipogenesis” (SREBF2_TARGET), “Proliferation” (MYC_TARGETS_V2), and “Iron_Homeostasis” (IRON_ION_HOMEOSTASIS; GSVA row Z-score > 0) was highly associated with treatment failure, irrespective of treatment modality (Fig. 7B). Breaking these down into individual gene expression signatures, for patients with a high “Lipogenesis” signature, 5 of 6 progressed on therapy, versus 0 of 10 patients with low-signature CTCs (P = 0.0014); for patients with high “Proliferation” CTCs, 4 of 5 progressed on treatment, compared with 1 of 11 patients with low-signature CTCs (P = 0.0128); for patients with a high “Iron_Homeostasis” signature, 4 of 6 progressed, compared with 1 of 10 patients with low-signature CTCs (P = 0.0357); finally, for patients with a high “Oxi_Phos” signature, 3 of 4 progressed, compared with 2 of 12 patients with a low signature (P = 0.0632; Fig. 7B). Thus, sampling CTC transcriptomic heterogeneity by single-cell pathway-level analyses within a patient blood sample may identify subclonal populations of CTCs, with treatment-resistant signatures, correlated with adverse clinical outcome. Extending from these small pilot studies to large clinical datasets, we find that SREBF2 expression itself is highly correlated with reduced survival in patients with metastatic melanoma (TCGA high-purity metastases samples, P = 0.0057), irrespective of treatment modality, an association that is not observed in localized primary tumors (TCGA high-purity primary tumor, P = 0.21; Fig. 7C; Supplementary Fig. S10E; Supplementary Table S8).

Cancer heterogeneity is increasingly recognized as a major cause of therapeutic resistance, with outgrowth of either preexisting or treatment-induced clonal subpopulations ultimately leading to disease progression (48). CTCs, comprising single metastatic precursor cells circulating in the bloodstream, thus provide an exceptional window into the diversity of drug-resistant phenotypes, while at the same time offering insight into vulnerabilities of cancer cells as they briefly transit through the high-oxygen blood environment (49). In this study using single-cell RNA-seq applied to melanoma CTCs, we have uncovered the aberrant coexpression of the lipogenic regulator SREBP2 and the iron-binding protein TF, modulating the cellular response to ferroptosis, with implications for both tumorigenesis and drug resistance (Fig. 7D). In both melanoma CTC-derived long-term cultures and individual CTCs freshly isolated from patient-derived blood specimens, we find coregulation of lipogenic and iron homeostasis pathways. Together, they denote a subset of CTCs with treatment-resistant phenotypes, associated with an adverse clinical outcome. Before initiation of BRAF-targeted therapy, we established multiple clonally derived CTC lines from a single patient with melanoma, demonstrating a degree of cellular heterogeneity in intrinsic drug susceptibility that is correlated with endogenous SREBP activity. As these cultured CTCs are treated with vemurafenib, they display further overexpression of endogenous SREBP, and direct ectopic manipulation of SREBF2 profoundly modulates their drug sensitivity.

SREBPs are aberrantly activated in several cancer types, including subsets of glioblastoma, melanoma, kidney cancer, prostate cancer, and breast cancer (32, 50–53). Although previous studies have linked PI3K and KRAS oncogenic signals to SREBP1/2 activation (34, 51, 54), the actual consequences of SREBP1/2 signaling on tumorigenesis are uncertain. SREBP2 ChIP-seq studies identify core target genes involved in cholesterol synthesis, glucose breakdown, and fatty acid synthesis, which may contribute to supporting the increased bioenergetic demands of proliferating tumor cells (33, 55). In the context of melanoma CTCs, however, we unexpectedly observed that a substantial fraction of SREBP2-bound promoters regulate genes involved in iron homeostasis, in addition to classic lipogenic genes. Among these, TF is noteworthy for both its level of induction by SREBP2 and the dramatic consequences of its knockdown on tumorigenesis and metastasis phenotypes.

The intracellular functions of the iron-binding transporter TF are poorly characterized. In CTCs with elevated endogenous TF expression, we find that its knockdown increases intracellular ROS and lipid peroxidation, lowering the GSH/GSSG ratio and mediating a reduction in soft-agar colony formation that is rescued by the lipophilic antioxidants ferrostatin and vitamin E. TF-KD also enhances cellular sensitivity to the ferroptosis inducer RSL3, as well as to the BRAF inhibitor vemurafenib. Conversely, overexpression of TF in CTCs reduces labile free iron pools, consistent with a sequestration mechanism, and its ectopic expression in melanoma cells that lack endogenous TF expression leads to reduced lipid peroxidation and increased resistance to RSL3. Although most TF protein is secreted from cells, a fraction is retained intracellularly, likely the result of alternative pre-mRNA splicing that excludes the 5′ secretion signal sequence. Although we favor the concept that TF mediates iron sequestration intracellularly, we cannot exclude the possibility that it binds iron within the extracellular microenvironment, thereby reducing intracellular iron levels. As such, an iron-transporting protein that is physiologically secreted by liver cells into the bloodstream appears to have been adapted by some cancer cells to help regulate intracellular iron levels.

The essential role of iron in heme biosynthesis and in multiple enzymatic reactions is well established, but the contribution of cellular iron levels to spontaneous and drug-induced ferroptosis is increasingly appreciated as a critical feature of cancer cell biology that may be harnessed to modulate existing therapies (43, 44, 56). TF is physiologically produced by the liver, and it regulates iron homeostasis through the TFRC, which is expressed in most tissues. Although TFRC is overexpressed in many tumors (37, 57), TF itself has not been implicated in malignancy. In TFRC-overexpressing cells, addition of iron-loaded TF to the culture medium increases iron import and appears to promote ferroptosis through iron overload (58). In contrast, in the setting of melanoma CTCs with endogenous expression of TF, it appears to function as a quencher of intracellular iron, leading to suppression of ferroptosis. Consistent with the importance of tightly regulated intracellular iron pools, we find that intracellular TF protein is abundant in melanoma CTCs, and its suppression increases their levels of ROS and oxidized lipids. Thus, melanoma CTCs appear to have hijacked this liver-specific gene to modulate the availability of labile iron pools, oxidative stress, and ferroptosis sensitivity.

The functional consequences of TF overexpression in melanoma CTCs appear to be considerable. Suppression of endogenous TF in these cells dramatically abrogates their blood-borne metastatic potential and to a lesser extent their primary tumorigenesis. Soft-agar clonogenic ability is also suppressed by TF-KD, with a relatively modest effect on in vitro proliferation. Together, these observations highlight the important role played by ROS stress in controlling metastatic propensity, and they point to the unexpected role of a major iron-transporting protein in mediating resistance to oxidative stress. The role of oxidative stress in the blood circulation as a critical suppressor of cancer metastasis has recently emerged, through the paradoxical role of antioxidants as prometastatic effectors (17, 59–62). Indeed, although early studies had pointed to the cellular damage and potential tumorigenic effects of ROS, and hence the potential benefit of antioxidants (61, 63–65), recent findings have demonstrated the positive impact of ROS in limiting blood-borne metastasis. In mouse models, systemic injections of the antioxidant N-acetyl-cysteine (NAC) enhance metastatic tumor formation following intravascular inoculation of primary human melanoma cells (17). In an endogenous mouse model of malignant melanoma, in vivo administration of NAC or the vitamin E analogue Trolox accelerates tumor progression and lymph node metastasis (66). Similarly, using single-cell RNA-seq of prostate cancer CTCs, we previously noted overexpression of multiple gene signatures involved in antioxidative defense, including β-hemoglobin, whose induction by KLF4 contributes to blood-borne metastasis (41, 62). While this work was under revision, Ubellacker and colleagues described a model whereby metastasizing melanoma cells are initially shielded from ferroptosis as they spread through low oxygen tension lymphatic channels, enhancing their subsequent ability to resist ROS stress during subsequent intravascular dissemination (67). Among the mechanisms employed by CTCs to circumvent oxidative stress in the bloodstream, the SREBP2-mediated induction of TF constitutes a novel pathway that may provide unique therapeutic opportunities.

In vitro, iron chelation using DFO suppresses ferroptosis, consistent with the iron requirement for lipid peroxidation (68). Altering serum iron levels to increase tumor cell ferroptosis is not feasible; however, inhibitors of lipogenesis may provide an intriguing opportunity to suppress the SREBP–TF pathway. Epidemiologic studies have produced conflicting results as to the general effectiveness of statins on cancer outcomes (69–73). These inconsistent clinical findings may reflect the distinct lipogenesis dependencies of different cancer types, interpatient heterogeneity, as well as different timing of drug administration as part of large observational clinical studies. Our results using melanoma CTC models raise the possibility that the short transit of tumor cells through the bloodstream may provide a unique window of opportunity to target these cells at a time of extraordinary ROS stress. As such, targeting the SREBP pathway in the context of melanoma with a high risk for metastatic recurrence may present a potential therapeutic strategy. Taken together, the cross-talk between SREBP and TF reveals a new and potentially therapeutically relevant vulnerability of highly refractory metastatic precursor cells.

Written informed consent was obtained from patients with metastatic melanoma undergoing evaluation or treatment at the Massachusetts General Hospital Cancer Center, and blood collections (10–15 mL) were performed as per IRB protocol (DF/HCC-0500), in accordance with the U.S. ethical guidelines. CTCs were microfluidically enriched from peripheral blood samples, using high-efficiency negative depletion of hematopoietic cells to isolate untagged and potentially viable cancer cells, as previously described (CTC-iChip; refs. 22, 23). All CTC lines were maintained under anchorage-independent culture condition as described previously (25). Standard melanoma cell lines IGR-37, SKML28, GAK, and A375 were obtained from the ATCC. CTC and ATCC cell lines used in this study have been authenticated using the short tandem repeat profiling method (Genetica) and tested for Mycoplasma contamination using a Mycoalert kit (Lonza, catalog no. LT07-218) before experiments. Mouse models of tumorigenesis and metastasis were generated using cultured Mel-167 and Mel-182-2 CTC lines in immunocompromised NOD/SCID Il2rg^−/− mice, according to guidelines approved by the Massachusetts General Hospital (MGH) Institutional Animal Care and Use committee (IACUC No. 2010N000006).

FLAG-tagged SREBF2 and TF constructs were obtained from Addgene (SREBF2 #26807 and TF #67240) and subcloned into pInducer10 vector using restriction enzymatic digestion (5′ using Age1 and 3′ using Mlu1). Lentiviral shRNAs were purchased from The RNAi Consortium (TRC) shRNA libraries of the Broad Institute. The targeting sequences for TF are shTF #1 5-ACTACAATAAGAGCGATAATT-3 and shTF #2 5-TACACCAGAGGCAGGGGTATTT-3.

For ex vivo culture of melanoma CTCs, microfluidically processed samples were incubated in hypoxic, anchorage-independent conditions as described in Yu and colleagues (25) with modifications. CTC cultures were grown in ultralow attachment plates (Corning) containing tumor sphere medium consisting of RPMI-1640 medium (with phenol red) supplemented with EGF (20 ng/mL), basic FGF (20 ng/mL), B27 (10 mL, 50× in stock), 1× Antibiotic–Antimycotic (Life Technologies), 5 μg/mL Heparin (Stemcell Technologies), and 100 nmol/L Rock inhibitor Y-27632 (EMD Millipore). Cells were cultured in a humid 37°C incubator with 5% CO₂ and 4% O₂. Medium was replenished 2 to 3 times per week, until CTCs initiated in vitro proliferation (4–8 weeks) with the following components included in CTC culture media: Mel-182 and Pem-22 blood samples were processed through the CTC-iChip using a recently developed blood stabilization method (74) followed by three-dimensional fibrin Matrigel culture initially and switched to anchorage-independent condition after initial proliferation.

For primary tumorigenesis assays, NOD/SCID Il2rg^−/− mice (6–8 weeks old, female) were injected s.c. in the left flank with cultured CTCs, and tumors were harvested when they reached 2 cm in diameter. For metastasis assays, 100,000 to 500,000 cells were injected intravascularly (tail vein or intracardiac). Metastatic burden was monitored 2 to 3 times per week using in vivo luciferase imaging using the IVIS (PerkinElmer). Mice were sacrificed at 8 to 10 weeks after tumor cell inoculation or at the first sign of discomfort as per IACUC guidelines.

Cultured CTCs were resuspended in growth media containing 0.4% low-melting agarose (Sigma, type VII). Soft agarose (0.5 mL of 1% soft agarose solution) was layered and solidified at room temperature in 24-well plates before adding the cell–agar mixture. Freshly plated cells were incubated at 4°C for 6 minutes to ensure solidification of the soft agar, and 0.5 mL of culture medium was added to each well. Colony formation was assayed after 4 weeks by staining with colorimetric MTT assay. Plates were photographed under identical standardized settings, and colonies were scored using an automated Matlab script.

Melanoma CTCs were seeded in 6-well plates the day before siRNA introduction by Lipofectamine RNAiMAX (Thermo Fisher, catalog no. 13778030) transfection. ON_TARGET plus smart pool siRNA was used to target SREBF1 (Dharmacon, catalog no. L-006891-00-0005) and SREBF2 (catalog no. L-009549-00-0005). Growth media were replaced once after 12 hours of transfection, and siRNA knockdown efficiency was assessed by qPCR 48 hours after transfection. shRNAs in lentiviral backbone against TF and scramble shRNA control vector were purchased from the TRC shRNA library at Broad Institute. shRNA lentiviruses were produced and packaged in 293T cells as described previously (75). Virus transduction was carried out in CTCs incubated in sealed 6-well plates by centrifugation followed by puromycin (2 μg/mL) selection for 6 to 8 days.

Cultured CTCs were refreshed with growth media in suspension the day before drug exposure and then split into ultralow attachment 96-well plates (Corning Costar-3474) at a density of 1,000 cells per well. Serial dilutions of each drug were added to the media, and cell viability was measured 5 days after drug exposure using CellTiter-Glo2.0 (Promega, catalog no. G9243).

Control or TF-KD CTCs were incubated with fresh media the day before ROS detection. Cells with 1x ROS fluorescent probe (Abcam, catalog no. ab186029) were incubated at 37°C for 1 hour in CTC growth chamber. ROS quantification was performed using flow cytometry (calculated based on the geometric mean), and relative ROS level was calculated and normalized to control shRNA-treated CTCs.

CTC cells were preincubated with fresh media 24 hours before the experiment. Cells were stained with 1x BODIPY 581/591 C11 lipid peroxidation sensor (Invitrogen, catalog no. D3861) for 30 minutes at 37°C. After the incubation, CTCs were washed with PBS and sent for flow cytometry quantification. The fraction of cells positive for oxidized BODIPY 581/591 C11 signal (shifts in emission peaks from 590 to 510 nm upon oxidation) was analyzed and normalized to control shRNA-treated CTCs.

RNA was extracted by a column purification kit (QIAGEN RNeasy), followed by treatment with DNAse I and oligo-dT–based reverse transcription using Superscript III. qRT-PCR was performed using SYBR Green reagents on an ABI 7500 fast real-time PCR platform. For immunoblotting, cells were washed once with cold TBS [20 mmol/L Tris-HCl (pH 7.5) and 150 mmol/L NaCl] and lysed using cell lysis buffer containing 1x TBS, 10 mmol/L β-glycerophosphate, 5 mmol/L EGTA, 1 mmol/L Na₄P₂O₇, 5 mmol/L NaF, 0.5% Triton X-100, 1 mmol/L Na₃VO₄, 1 mmol/L dithiothreitol, and protease inhibitor cocktail (Roche). Following SDS-PAGE, antibody-tagged proteins were detected using Western Lightning Plus-ECL reagent (PerkinElmer) after SDS-PAGE. Primary antibodies used in the experiment are rabbit anti-FLAG (1:1,000; Invitrogen, catalog no. PA1-984B); rabbit anti-TF (1:2,000; Invitrogen, catalog no. PA3-913); mouse anti-TFRC (1:2,000; Life Technologies, catalog no. 136800), and rabbit anti-GAPDH (1:2,000; Cell Signaling Technology, catalog no. 2118S).

Freshly isolated individual CTCs were selected using a micromanipulator and introduced into a 0.5 mL tube with 7 mL of 1x lysis buffer (Takara, catalog no. 634891) containing recombinant RNase inhibitor (0.4 U/mL; Takara, catalog no. 2313A), snap-frozen, and maintained at −80°C until processing. Single-cell lysates were transferred into 96-well plates (Eppendorf, 951020401), and RNA extraction and cleanup were carried out using Agencourt RNAClean XP Solid Phase Reversible Immobilization beads (Beckman Coulter, A63987). Prior to library construction using the Nextera XT library Prep Kit (Illumina, FC-131-1096), two steps of quality control were done to evaluate the concentration of each single cell, using Qubit dsDNA High Sensitivity Assay Kit (Life Technologies, Q32854), according to the manufacturer's instructions. Single-cell CTC libraries were prepared using a modified Smart-Seq2 protocol (76). Combined libraries were sequenced on a NextSeq 500 sequencer (Illumina) using the 75 cycles kit, with paired-end 38-base reads and dual barcoding.

Detailed computational analytic methods can be found in the Supplementary Methods.

Statistical analyses were performed using R 3.5.1. An empirical Bayes moderated t test was used for two-group comparison of gene expression values. Two-sided Welch t test was used for two-group comparison of GSVA enrichment scores.

All RNA-seq and ChIP-seq data associated with this article are deposited into Gene Expression Omnibus repository with the accession number GSE157745 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE157745). The WES of melanoma CTC lines (as shown in Supplementary Fig. S3A) will be provided upon request.

X. Hong reports patents for PCT/US2016/024367 and PCT/US2017/058855 issued. R.J. Sullivan reports grants and personal fees from Merck, grants from Amgen, and personal fees from Novartis, Eisai, Iovance, AstraZeneca, Pfizer, Array, Asana Biosciences, Replimune, and Bristol Myers Squibb outside the submitted work. M. Sade-Feldman reports grants from Dr. Miriam and Sheldon G. Adelson Medical Research Foundation during the conduct of the study; in addition, M. Sade Feldman has a patent for Methods for Predicting Outcomes of Checkpoint Inhibition and Treatment Thereof pending. G.M. Boland reports other from Novartis and Nektar Therapeutics, and grants from Olink Proteomics, Palleon Pharmaceuticals, and Takeda Oncology outside the submitted work. S.S. Freeman reports a patent for Methods for Predicting Outcomes of Checkpoint Inhibition and Treatment Thereof pending. N. Hacohen reports personal fees from BioNTech/Neon and Related Sciences outside the submitted work. D.T. Ting reports other from TellBio, Inc., during the conduct of the study; in addition, D.T. Ting also reports personal fees and other from ROME Therapeutics; other from PanTher Therapeutics; personal fees from Third Rock Ventures, Foundation Medicine, Inc., EMD Millipore Sigma, NanoString Technologies, and Pfizer; and grants from PureTech Health and Ribon Therapeutics outside the submitted work. M. Toner has equity in a start-up called TellBio interested in the use of CTCs for both diagnostics and therapeutics. G. Getz reports grants from IBM during the conduct of the study, receives research funds from Pharmacyclics, and is an inventor on patent applications related to ABSOLUTE, MutSig, MSMuTect, MSMutSig, MSIDetect, POLYSOLVER, and TensorQTL, in addition, G. Getz is a founder and consultant and holds privately held equity in Scorpion Therapeutics. S. Maheswaran has equity in TellBio; in addition, S. Maheswaran has a patent for CTC diagnostics pending. D.A. Haber has equity in TellBio; in addition, D.A. Haber has a patent for CTC diagnostics pending. No disclosures were reported by the other authors.

X. Hong: Conceptualization, formal analysis, investigation, writing–original draft. W. Roh: Formal analysis, investigation, writing–original draft. R.J. Sullivan: Resources, investigation, writing–review and editing. K.H.K. Wong: Formal analysis, investigation, writing–review and editing. B.S. Wittner: Formal analysis, investigation, writing–original draft. H. Guo: Formal analysis, investigation, writing–original draft. T.D. Dubash: Formal analysis, investigation, writing–review and editing. M. Sade-Feldman: Formal analysis, investigation, writing–review and editing. B. Wesley: Formal analysis, investigation, writing–review and editing. E. Horwitz: Formal analysis, investigation, writing–review and editing. G.M. Boland: Resources, writing–review and editing. D.L. Marvin: Formal analysis, investigation, writing–review and editing. T. Bonesteel: Formal analysis, investigation, writing–review and editing. C. Lu: Formal analysis, investigation, writing–review and editing. F. Aguet: Formal analysis, investigation, writing–review and editing. R. Burr: Formal analysis, investigation, writing–review and editing. S.S. Freeman: Formal analysis, writing–review and editing. L. Parida: Investigation, writing–review and editing. K. Calhoun: Investigation, writing–review and editing. M.K. Jewett: Investigation, writing–review and editing. L.T. Nieman: Formal analysis, investigation, writing–review and editing. N. Hacohen: Formal analysis, investigation, writing–original draft. A.M. Näär: Resources, formal analysis, writing–review and editing. D.T. Ting: Formal analysis, writing–review and editing. M. Toner: Formal analysis, supervision, writing–original draft. S.L. Stott: Supervision, investigation, writing–original draft. G. Getz: Supervision, investigation, writing–original draft. S. Maheswaran: Conceptualization, formal analysis, supervision, investigation, writing–original draft. D.A. Haber: Conceptualization, formal analysis, supervision, investigation, writing–original draft.

The authors thank the patients who participated in this study and L. Libby for administrative support. This work was supported by grants from the National Institutes of Health [2RO1CA129933 (to D.A. Haber), 2U01EB012493 (to M. Toner, D.A. Haber, and S. Maheswaran), 5U01EB012493 (to M. Toner), and 5P41EB002503 (to M. Toner)], Howard Hughes Medical Institute (to D.A. Haber), ESSCO Breast Cancer Research Fund (to S. Maheswaran), National Foundation for Cancer Research (to D.A. Haber), Wang Pediatric Brain Tumor Collaborative and MGH Claflin Distinguished Scholar Award (to S.L. Stott), MGH Research Scholar Award (to A.M. Näär), Broad/IBM Cancer Resistance Research Project (to G. Getz), National Science Foundation (PHY-1549535 to D.T. Ting), Stand Up To Cancer (SU2C; to D.T. Ting), Lustgarten Foundation (2015-002, to D.T. Ting), and ACD_Biotechne (to D.T. Ting).