Systemic metastasis is the major cause of death from melanoma, the most lethal form of skin cancer. Although most patients with melanoma exhibit a substantial gap between onset of primary and metastatic tumors, signaling mechanisms implicated in the period of metastatic latency remain unclear. We hypothesized that melanoma circulating tumor cells (CTC) home to and reside in the bone marrow during the asymptomatic phase of disease progression. Using a strategy to deplete normal cell lineages (Lin), we isolated CTC-enriched cell populations from the blood of patients with metastatic melanoma, verified by the presence of putative CTCs characterized by melanoma-specific biomarkers and upregulated gene transcripts involved in cell survival and prodevelopment functions. Implantation of Lin population in NSG mice (CTC-derived xenografts, i.e., CDX), and subsequent transcriptomic analysis of ex vivo bone marrow–resident tumor cells (BMRTC) versus CTC identified protein ubiquitination as a significant regulatory pathway of BMRTC signaling. Selective inhibition of USP7, a key deubiquinating enzyme, arrested BMRTCs in bone marrow locales and decreased systemic micrometastasis. This study provides first-time evidence that the asymptomatic progression of metastatic melanoma can be recapitulated in vivo using patient-isolated CTCs. Furthermore, these results suggest that USP7 inhibitors warrant further investigation as a strategy to prevent progression to overt clinical metastasis.

Significance: These findings provide insights into mechanism of melanoma recurrence and propose a novel approach to inhibit systematic metastatic disease by targeting bone marrow-resident tumor cells through pharmacological inhibition of USP7.

Graphical Abstract:http://cancerres.aacrjournals.org/content/canres/78/18/5349/F1.large.jpg. Cancer Res; 78(18); 5349–62. ©2018 AACR.

Melanoma, the most aggressive skin cancer, frequently metastasizes to distant organs such as bone, lung, liver, and brain (1). Unlike localized melanoma, which can be surgically resected, metastatic melanoma with extranodal involvement is typically treated with systemic therapies including targeted and immune therapy (2). Although outcomes are improving due to new therapies, the majority of patients with stage IV melanoma will die from their disease (1, 2).

Metastasis is a multistep process that is initiated when tumor cells leave the primary tumor and traverse through the circulation to reach distinct organs (3, 4). While transiting through the peripheral blood, a subset of CTCs can home to the bone marrow where they reside in a state of sustained quiescence (parallel progression model of metastatic melanoma; ref. 5). The unique bone marrow microenvironment exerts temporal and spatial selection pressures that are conducive for the survival of cell clones retaining long-term, self-renewal ability while acquiring the necessary traits for successful organ colonization, even in the absence of overt local bone invasion (3, 5, 6). These bone marrow–resident tumor cells (BMRTC) are considered to be the “seeds” of future metastasis; targeting them for elimination or promoting the prolongation of their quiescent/growth-arrested state can therefore be a promising strategy to overcome or delay metastatic onset (5, 7). Accordingly, it is imperative to identify novel biomarkers for BMRTC detection and to develop new therapeutic strategies that can eliminate BMRTCs before they progress to overt metastasis.

Successful surgical resection of primary melanoma (with clear margins) along with satisfactory lymph node dissection does not always prevent the incidence of late metastatic recurrence (5, 8). This suggests that metastatic dissemination is an early event wherein melanoma cells remain dormant but viable in distant organs while retaining abilities to generate overt metastasis at a later time (3, 8–11). For example, using the RET.AAD melanoma mouse models, Eyles and colleagues demonstrated that the process of tumor cell dissemination preceded the onset of symptomatic metastasis (4). Furthermore, Ghossein and colleagues found that the presence of melanoma-specific transcripts in clinical blood and bone marrow samples is associated with shorter median survival of patients (12). Despite these reports pointing to bone marrow as the likely reservoir for disseminated CTCs, the precise role of BMRTCs in the pathogenesis of metastatic melanoma remains unclear and no significant progress has been made to target melanoma CTCs/BMRTCs for clinical metastasis prevention (4, 10–13).

We hypothesized that melanoma CTCs migrate to and reside in the bone marrow during asymptomatic progression of the disease. We report here the isolation of CTC-enriched populations from the peripheral blood of patients with metastatic melanoma, their expansion in immunocompromised mice, followed by their harvesting and subsequent immunophenotyping and molecular characterization. Using these approaches, we identified elevated USP7/PTEN expression as a distinct gene signature of BMRTCs. Furthermore, we demonstrated that inhibition of USP7 reduces the metastatic potential of BMRTCs by prolonging their arrest in bone marrow. Our investigations provide novel insights into the identity of BMRTCs that may be detectable in patients with melanoma during asymptomatic metastasis, and present data to support the evaluation of USP7 inhibitors in patients with melanoma at risk of developing metastasis.

Patient blood collection

Patients with melanoma with stage III or stage IV disease were accrued according to protocols approved by the Institutional Ethical Review Boards at the University of Texas MD Anderson Cancer Center (Houston, TX) and Houston Methodist Research Institute (HMRI, Houston, TX). All patient blood samples were collected after receiving informed written consent and according to the principles of Declaration of Helsinki. Clinical details of each patient and PTEN H-score, included in the study, are provided in Supplementary Table S1 and Supplementary Fig. S1. Peripheral blood (18–20 mL) was obtained at the middle of vein puncture and was collected in CellSave tubes (Menarini Silicon Biosystems, Inc.), or EDTA tubes under aseptic conditions. Samples were provided immediately to the laboratory for CTC isolation and analysis.

Antibodies and inhibitors used for the study

For multiparametric flow cytometry and DEPArray, primary antibodies were obtained from the following sources: FITC-CD45 (#304054; 1:200), FITC-CD34 (#343504; 1:200), FITC-CD105 (#323204; 1:200), FITC-CD90 (#328108; 1:200), FITC-CD73 (#344016; 1:200), FITC HLA-A/B/C antibody (#311404; 1:200), PerCP/Cy5.5-CD146 (#342014; 1:100), PE-Human NG2/MCSP (#FAB2585P, 1:100), BV421-Ki67 (#350506; 1:100) were obtained from BioLegend, anti–Melan-A antibody (# AC12-0297-03; 1:200) from Abcore, and FITC-Anti-S100 (#ab76749; 1:50) was purchased from Abcam.

For IHC, anti-human, anti–Melan-A antibody (#ab51061; 1:100), anti–tenascin-C (#ab108930, 1:100), and anti-p21 (#ab188224, 1:100) were purchased from Abcam; HLA-ABC (#565292; 1:100) from BD Biosciences; USP7 (#GTX125894; 1:200) from Genetex. PTEN antibody (#sc-7974; 1:20) was purchased from Santa Cruz Biotechnology. Anti-p53 antibody (#SAB4503021, 1:100) was purchased from Sigma, and CCP110 (#12780-I-AP, 1:100) antibody was obtained from Proteintech. Anti-mouse, USP7 (#26948-1-AP, 1:200), and PTEN (#603000-1-Ig, 1:200) antibodies were purchased from Proteintech. Alexa Fluor-conjugated anti-mouse, anti-rabbit secondary IgG antibodies used for immunofluorescence staining (1:500 dilution) were obtained from Cell Signaling Technology. USP7 inhibitors P5091 (#SML0770) and P22077 (#2301) were purchased from BioVision.

PBMC isolation and CTC enrichment by multiparametric flow cytometry

Peripheral blood mononuclear cells (PBMC) were isolated by established procedures (14). Briefly, whole blood was treated with red blood cell lysis buffer (154 mmol/L NH4Cl, 10 mmol/L KHCO3, 0.1 mmol/L EDTA) at 1:25 ratio, followed by incubation at room temperature (25°C) for 5 minutes, then pelleting the remaining blood cells at 300 × g for 10 minutes. Mononucleated cell pellet was then washed twice with 1× PBS (with 5 mmol/L EDTA) and used for fluorescence labeling followed by multiparametric flow sorting (FACSAria II; BD Biosciences). Data recorded during cell sorting were analyzed by DIVA acquisition software version 8.0.1 (BD Biosciences). Antibodies and reagents described above were used. Data generated by FACS were analyzed by FlowJo V10.

Experimental xenografts

All animal study was approved by our Institutional Animal Care and Use Committee protocol. Immunodeficient animal experiments were performed using 4- to 8-week-old NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ (NSG) mice (The Jackson Laboratory). Flow-sorted Lin PBMCs (∼50,000 cells) derived from patient blood (8 mL volume) were injected in anesthetized NSG mice through intracardiac injection under aseptic conditions. Previous reports show that injection of melanoma cell lines (1 × 106 cells) with different metastatic abilities in immunodeficient mice typically develop overt macrometastases in 10 to 12 weeks (poorly metastatic) and 3 to 4 weeks (highly metastatic melanoma cell lines; ref. 15). Based upon this reference time-frame and considering that melanoma CTCs are rare cells with low transcriptional activity (Supplementary Fig. S2A and S2B; Supplementary Tables S2 and S3), xenograft mice were euthanized 6 months after injection with patient-isolated Lin cells (13, 16–19). This was based upon the reasoning that this period should suffice for in vivo selection and elimination of nontumor cells and successful establishment of a niche for resident single cells in systemic viscera and bone marrow. Peripheral blood, bone marrow, and organs were harvested for downstream analyses. Approximately 800 to 900 μL blood was collected in EDTA tubes by cardiac puncture of anesthetized mice. Animals were sacrificed soon afterwards and bone marrow/organ tissues were harvested. In particular, bone marrow was obtained from femur and tibia by flushing them out with 1× PBS with EDTA (5 mmol/L) using a 28 G × ½ needle, followed by centrifugation at 300 × g for 10 minutes. Blood and bone marrow were processed immediately for PBMC isolation and FACS analyses.

To study the effect of USP7 inhibitors on BMRTCs/CTCs, 2 to 3 immunodeficient mice were injected with Lin population (50,000 cells/mouse) selected from the same individual patient with melanoma (16 mL blood volume). One animal of each patient group was then treated with USP7 inhibitor (either P5091 or P22077). CTC-derived xenografts (CDX) were treated twice a week subcutaneously with USP7 inhibitors at an MTD [P22077 (15 mg/kg); P5091 (10 mg/kg); ref. 20]. Control vehicle consisted of 1× PBS (100 μL) injected in untreated CDXs. After 11 weeks of treatment, mice were sacrificed and necropsy performed.

Eight to 10-week-old, syngeneic mice C57BL/6J (n = 30) were purchased from The Jackson Laboratory. Xenografts were developed by intracardiac injection of aggressive B16F10 melanoma cells (ATCC; 50,000 cells/mouse) and treated with or without USP7 inhibitors (P5091 and P22077) at their MTD as described previously. After 3 weeks, each group of animals (n = 10) was euthanized and organs (bone marrow, lung, brain, liver, and lymph node) were harvested to perform hematoxylin and eosin (H&E) staining analyses. All melanoma cells were obtained from ATCC, DNA fingerprinted, and routinely validated for Mycoplasma-free testing at Characterized Cell Line Core Facility, MD Anderson, Houston, Texas.

Immunofluorescence and IHC

FACS-isolated CTCs were subjected to quick air-dry on Millennia 2000 adhesive glass slides (StatLab), and fixed with 4% paraformaldehyde (21). Cells were permeabilized (0.05% Triton X-100 in 1× PBS) for 30 minutes, followed by 30-minute incubation in blocking buffer (1% BSA + 1% normal goat serum in 1× PBS). Next, immunofluorescent cell staining was employed using selected primary and secondary antibodies. Magnified (×100) images were captured using Zeiss Axio Observer microscope Z1 (Carl Zeiss), and data were analyzed using Zeiss ZEN2 software. Harvested tissue was processed and stained for H&E and other IHC markers by the research pathology core at HMRI. Images were captured by using EVOS XL Cell Imaging System (Thermo Fisher Scientific). IHC images were taken and quantified by free-access ImageJ software. Reciprocal intensity (250 − y) was measured by subtracting the mean intensity of the stained area (y) from the maximum (250) unstained white area intensity as described previously (22). Student t test, type 2, paired 2 was used to calculate the difference in reciprocal intensity between two groups (USP7 inhibitors treated vs. untreated) for each protein.

DEPArray and CellSearch CTC interrogation

Flow-sorted CDX-derived HLA+/Melan-A+ were fixed with 2% paraformaldehyde for 20 minutes at 25°C followed by washing with 1× PBS to visualize cells at single-cell level. CTCs were then stained with appropriate antibodies, rewashed with the SB115 buffer, and loaded onto the DEPArray platform (Menarini Silicon Biosystems, Inc.). Cells were then detected and analyzed by using Cell Browser software v3.0 (Menarini Silicon Biosystems, Inc.), as reported previously (14, 21). For CellSearch CTC enumeration, harvested murine blood was spiked with blood from healthy donors and was processed using CellTracks circulating Melanoma Cell Kit and CellSearch platform (Menarini Silicon Biosystems, Inc.), following the manufacturer's guidelines.

RNA isolation and gene expression profiling

Total RNA isolation was performed using NucleoSpin RNA XS Isolation Kit (Macherey-Nagel, Inc.), then immediately provided to the sequencing/noncoding RNA core facility (MD Anderson Cancer Center). RNA and cDNA amplifications, quality controls, and gene expression arrays were performed using the human microarray platform (Clariom D, Affymetrix, Inc.). BMRTC/CTC samples were RNA-normalized using Affymetrix Powertool 1.18.0, and annotations were taken from Affymetrix version 36. Gene expression data analysis from each of BMRTC/CTC subsets (derived from asymptomatic CDX mice, with absence of histopathologic confirmed macrometastasis) was performed using Transcriptome Analysis Console 3.0.0.466 (Affymetrix, Inc.). Two-way ANOVA was performed to calculate fold change (FC) and P value. Pathway enrichment analyses were subsequently performed using the Ingenuity Pathway Analysis software version 01-07 (Qiagen, Inc.).

WTA amplification and qRT-PCR

mRNA and cDNA amplification were carried out from isolated RNA using REPLI-g single-cell WTA Amplification Kit, according to the manufacturer's instructions (Qiagen, Inc.). Amplified cDNA was purified using the ExoSAP method (Affymetrix; #78202.4X.1.ML), and subjected to qRT-PCR using the SensiFAST SYBR Hi-ROX Kit (Bioline, #BIO-92020). CT values were normalized with housekeeping gene β-actin and log2 (−ΔΔCT) were calculated. Student t test, type 2, paired 2 was performed to obtain the P value of each gene. Primer sequences for each gene are shown in Supplementary Table S4.

Whole-genome amplification and next-generation sequencing

Whole-genome amplification (WGA) was performed by REPLI-g Single-Cell WGA Kit, according to the manufacturer's instructions (Qiagen, Inc.). Briefly, the pool of CTC subsets was lysed and denatured followed by amplification to obtain intact amplified DNA of 10 kb. Ion Torrent next-generation sequencing (NGS) was performed by using Ion AmpliSeq Cancer Hotspot Panel v2 (Thermo Fisher Scientific, #4475346). Libraries were constructed using amplified DNA and loaded on Ion Torrent Pmt sequencer. Sequences were assembled with human reference hg19 assembly and variant analyses were performed by Advaita iVariantGuide (http://www.advaitabio.com/ipathwayguide). Analyses were based on NGS for the detection of somatic mutations in the coding sequence of a minimum of 46 genes (range 46–128), which were performed on DNAs extracted from samples in the CLIA-certified molecular diagnostic laboratory (University of Texas MD Anderson Cancer Center).

Mitochondrial DNA assessment and cell surface and intranuclear flow cytometry

The ratio of mitochondrial DNA (mtDNA) to nuclear DNA (nDNA) copies was used to verify cell proliferative status (MTN index; ref. 23). The mitochondrial target was strategically selected within the noncoding displacement loop (MTDL) of the mtGenome because of the rare occurrence of large-scale deletions that are common to other areas, for example, the major arc55. Single-copy and low variability β2-microglobulin (B2M) gene was selected as the nuclear target. Relative quantitative PCR (qPCR) was performed and MTN index was calculated [MTN index = 2 × 2ΔCT, where ΔCT = (CTB2M − CTMTDL)].

We used the Permiflow method (US patent #US7326577 B2) of cell fixation for concomitant cell surface (e.g., HLA+/Mel-A+), and intranuclear staining of target proteins (e.g., Ki67) in CDX-derived cell populations, as described previously (14). Briefly, xenograft-isolated bone marrow and blood PBMCs were first stained with the live/dead fixable Zombie NIR dye (BioLegend, #423105, 1:100) for 15 minutes, followed by two sequential washes with 1× PBS. All samples were then fixed and permeabilized with the Permiflow solution by incubating at 42°C for 1 hour, followed by washing with 1× PBS. Cells were then resuspended in staining buffer and stained with appropriate antibodies for flow cytometric analyses.

Isolation and validation of melanoma CTC-enriched cell populations isolated from patients' blood

CTCs derived from patients display significant heterogeneity in cell surface biomarkers, epitomized by the coexistence of tumor-initiating and stem cell populations within a single blood draw (16, 17). A consequence of this diversity is that multiple marker-based platforms (including CellSearch, the only FDA-cleared platform for clinical CTC testing), and cell size-based microfiltration devices are unable to capture the entire spectrum of CTC subtypes that may be biologically and/or clinically relevant in cancer progression (18, 24, 25). Because there is no universal melanoma CTC marker capable of identifying the heterogeneous CTC subgroups, particularly clones that may transit to- and from the bone marrow, we used immunocompromised mice for the in vivo selection of cells capable of bone marrow homing and residence. To implement this strategy, we first employed multiparametric flow cytometry to deplete normal cell lineages present in the peripheral blood of patients with melanoma (patients enrolled in this study are listed in Supplementary Table S1), thereby enriching cell populations containing putative as well as uncharacterized abnormal cell populations (here referred as Lin cells). Flow cytometric gating consisted of doublet discrimination and dead cell (DAPI+) elimination, followed by depletion of leukocytes (CD45+), circulating endothelial cells (CD34+), and mesenchymal stem cells (CD73+/CD90+/CD105+; Fig. 1A). Using this strategy, we successfully captured putative melanoma CTCs identified by the presence of established melanoma markers (Melan-A and S100) from the peripheral blood of 8 patients with melanoma validated through immunofluorescence (Fig. 1B; ref. 16). Second, we performed Ion Torrent next-generation DNA sequencing and analyzed the genetic profiles of 409 oncogenes and tumor suppressor genes of CTCs (Lin and Melan-A+ cells) derived from two independent patients with melanoma (patients #9 and #10). We identified 176 and 231 clinicopathologic mutations in respective patients (#9 and #10), present on NF1, KRAS, TP53, RB1, ATM, and EGFR genes (Fig. 1C; Supplementary Table S5A and S5B), confirming the neoplastic identity of these cells. Of note, CTCs from one of the analyzed patients (patient #10) harbored a melanoma-associated mutation in CDKN2A (p.Ala148Thr; COSM3736958; https://www.ncbi.nlm.nih.gov/clinvar/variation). We also confirmed the presence of skin cancer–associated mutations in XPA (c.-4A>G), ERCC1 (p.Asn118Asn), and ERCC5 (p.Gly1534Arg; https://www.ncbi.nlm.nih.gov/clinvar/variation). Third, to validate that melanoma patient–isolated Lin cells (patients #2, #3, #4, and #7) were distinct from normal PBMCs, we performed whole-genome microarray analyses on these cells (n = 4), and compared them with the gene expression profiles of PBMCs derived from healthy donors (n = 9). PBMC dataset (GSE100054) was specifically chosen because it was obtained using the same human microarray platform (Clariom D; Affymetrix, Inc.). A total of 15,056 genes were upregulated and 23,430 genes were downregulated (fold change <−2 or >2, P = 0.05) in Lin cell populations compared with healthy donor PBMCs, suggesting low transcriptional activity (Fig. 1D and E; Supplementary Table S2). Unsupervised hierarchical clustering showed distinct gene expression patterns in Lin and PBMC cell populations. (Fig. 1F). Lin populations possessed significantly higher expression of BAGE, MAGEA1, B4GALNT1, DCD, and S100A3 confirming the presence of specific melanoma-associated markers within this population (Supplementary Table S3; refs. 16, 19, 26). Downstream pathway enrichment analyses in Lin cell pools predicted increased activation of nuclear receptor and oncogenic signaling, along with inhibition of immune regulation and progrowth signaling pathways (Supplementary Fig. S3; Supplementary Tables S6 and S7). These findings were reflected in cellular functions, for example, upregulated transcripts implicated in cell survival and prodevelopment functions with a concomitant decrease in pathways involved in cell proliferation and inflammation. Collectively, these results asserted the presence of putative and uncharacterized melanoma CTCs in Lin cell populations isolated by multiparametric flow cytometry.

Figure 1.

Isolation, validation, and molecular characterization of de novo Lin cell population. A, Enrichment of viable Lin cell population (CD45/CD34/CD90/CD73/CD105 cells) from the blood of 8 patients with melanoma through multiparametric flow sorting (patients #1–8). B, Validation of FACS procedures by melanoma markers (S100 and Melan-A) expression in Lin cell population through immunofluorescence staining. Representative images are shown. Scale bar, 10 μmol/L. C, Genetic mutational profiling of Lin/Melan-A+ cell populations derived from two representative patients with melanoma (patients #9 and #10) by AmpliSeq Ion Torrent Cancer Hotspot Panel V2. Number of missense, nonsense, and silent mutations of each patient is indicated. D, Differential gene expression profiling of Lin cell population from patients with melanoma (n = 4; patients #2, #3, #4, and #7), compared with dataset of PBMCs isolated from blood of normal healthy donors (GSE100054; n = 9). Two-way ANOVA were performed to calculate FC and P value. E, Scatter plots showing global gene expression changes of Lin cell population. F, Hierarchical clustering showing distinct transcriptomic signatures of Lin cell population versus PBMCs.

Figure 1.

Isolation, validation, and molecular characterization of de novo Lin cell population. A, Enrichment of viable Lin cell population (CD45/CD34/CD90/CD73/CD105 cells) from the blood of 8 patients with melanoma through multiparametric flow sorting (patients #1–8). B, Validation of FACS procedures by melanoma markers (S100 and Melan-A) expression in Lin cell population through immunofluorescence staining. Representative images are shown. Scale bar, 10 μmol/L. C, Genetic mutational profiling of Lin/Melan-A+ cell populations derived from two representative patients with melanoma (patients #9 and #10) by AmpliSeq Ion Torrent Cancer Hotspot Panel V2. Number of missense, nonsense, and silent mutations of each patient is indicated. D, Differential gene expression profiling of Lin cell population from patients with melanoma (n = 4; patients #2, #3, #4, and #7), compared with dataset of PBMCs isolated from blood of normal healthy donors (GSE100054; n = 9). Two-way ANOVA were performed to calculate FC and P value. E, Scatter plots showing global gene expression changes of Lin cell population. F, Hierarchical clustering showing distinct transcriptomic signatures of Lin cell population versus PBMCs.

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Expansion of melanoma patient–isolated Lin cells in vivo

To evaluate whether Lin cells isolated from patients with melanoma could recapitulate the metastatic cascade, we first injected Lin cell populations (n = 8) into the left ventricle of immunodeficient mice (patients #1–8). Mice were euthanized at the predesignated study endpoint (6 months), after collecting blood by cardiac puncture. Bone marrow from long bones (femur, tibia, and humerus) and organs typically affected by metastatic melanoma (lung, brain, and liver) were collected for downstream analyses. Interestingly, although routine histopathologic inspection did not identify any macrometastatic disease in these organs, extensive IHC analyses employing human (HLA-ABC) and melanoma (Melan-A) biomarkers detected discrete resident human melanoma cells in multiple murine organs (CDXs; Supplementary Fig. S4A and S4B; ref. 27). Second, to assess the presence of human melanoma CTCs in blood of CDX models (derived from patient #4), we spiked CDX blood with healthy donor blood and performed analyses using the CellSearch platform to visualize and enumerate CTCs. We identified eight DAPI+/CD45/Melan-A+ cells from 500 μL of murine blood by CellSearch (Fig. 2A). Next, we harvested blood and bone marrow for PBMC isolation followed by multiparametric flow sorting, and isolated HLA+/Melan-A+ex vivo CTCs and BMRTCs (Fig. 2B). We validated the veracity of flow procedures by immunofluorescence analyses, detecting the presence of human (HLA) and melanoma (Melan-A) markers in HLA+/Melan-A+ FACS-sorted populations (Fig. 2C). Third, we confirmed the heterogeneity of a pool of melanoma markers (Melan-A/CD146/NG2/S100) in CDX-derived BMRTC/CTC populations (patient #3) by the DEPArray (Fig. 2D; refs. 16, 17). The DEPArray is an antigen-agnostic CTC capturing technology that separates viable rare cells at a single-cell level. An additional important aspect of this system is the absence of shear force stress on cells during recovery (14). We identified, analyzed, and quantitated heterogeneous melanoma cell populations displaying specific melanoma markers in FACS-sorted HLA+/Melan-A+ cell population derived from BMRTCs/CTCs of the same CDX mice: Melan-A+/S100+/CD146+/NG2+ (BMRTCs = 27; CTCs = 8), Melan-A+/S100/CD146+/NG2 (BMRTCs = 11; CTCs = 10), Melan-A+/S100+/CD146+/NG2 (BMRTCs = 11; CTCs = 14), and Melan-A+/S100/CD146/NG2 (BMRTCs = 0; CTCs = 14; Fig. 2D). Fourth, we performed genetic profiling for a family of 50 key cancer genes by Ion Torrent NGS on ex vivo BMRTCs and CTCs (patients #3 and 4). We discovered novel mutations in PIK3CA, NRAS, KRAS, ERBB4, PTEN, and APC genes along with two hotspot cosmic mutations (COSM21451 and COSM25085) in the PIK3CA gene using hg19 human genome assembly as reference (Fig. 2B; Supplementary Table S8). Finally, we performed differential gene expression analysis of ex vivo versus de novo CTCs (Lin/CTC-enriched population) from paired patient samples (patients #2, #3, #4, and #7) by human microarray profiling (Clariom D; Affymetrix, Inc.). We observed 3,777 significantly upregulated and 3,879 significantly downregulated transcripts (FC = 2.5; P = 0.05) when CTCs versus Lin/CTC-enriched population-derived microarray data were compared. We also observed 12,431 significantly overlapping genes between arrays of these population (P = 0.05; Supplementary Fig. S5). Collectively, these results demonstrate that CTC-enriched cell populations isolated from melanoma patients and expanded in CDX models could be successfully harvested from blood and bone marrow of these mice.

Figure 2.

Isolation and validation of melanoma patient CTCs/BMRTCs from CDXs. A, Capture, visualization, and enumeration of human melanoma CTCs by CellSearch (CD45/CD34/DAPI+/Melan-A+ cells; patient #4). B, Multiparametric flow cytometry gating used to isolate human melanoma cells from bone marrow and blood of CDXs models (DAPI/HLA+/Melan-A+ cells). Table showing number of genomic mutations (50 cancer gene sequencing panel) analyzed by AmpliSeq Ion Torrent in representative patients (see Materials and Methods for details). C, Immunofluorescence visualization of patient-derived CTCs and BMRTCs from CDXs. Scale bar, 10 μm. D, Representative images of ex vivo CTCs and BMRTCs isolated by the DEPArray (patient #3).

Figure 2.

Isolation and validation of melanoma patient CTCs/BMRTCs from CDXs. A, Capture, visualization, and enumeration of human melanoma CTCs by CellSearch (CD45/CD34/DAPI+/Melan-A+ cells; patient #4). B, Multiparametric flow cytometry gating used to isolate human melanoma cells from bone marrow and blood of CDXs models (DAPI/HLA+/Melan-A+ cells). Table showing number of genomic mutations (50 cancer gene sequencing panel) analyzed by AmpliSeq Ion Torrent in representative patients (see Materials and Methods for details). C, Immunofluorescence visualization of patient-derived CTCs and BMRTCs from CDXs. Scale bar, 10 μm. D, Representative images of ex vivo CTCs and BMRTCs isolated by the DEPArray (patient #3).

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Divergent transcriptomic signatures between ex vivo BMRTCs and CTCs

To determine functional differences between BMRTCs and CTCs, we performed transcriptome profiling of HLA+/Melan-A+ cell populations obtained from CDX (derived from patients #1–8) bone marrow, and blood. We used paired BMRTC/CTC populations derived from eight CDX models (showing absence of macrometastatic disease) generated by injecting Lin cell population from individual patients with metastatic melanoma (n = 8), and performed human microarray profiling (Clariom D; Affymetrix, Inc.). Analyses identified 3,645 differentially expressed genes; 2,439 genes were upregulated, whereas 1,206 genes were downregulated (FC = 2.5, P-value = 0.05) in BMRTCs versus CTCs (Fig. 3A and B). Divergent transcriptomic signatures of BMRTCs/CTCs in CDX models reflected the differential behavior of Lin cells owing to their spatial niche (Fig. 3A and B; Supplementary Fig. S6). Subsequent pathway enrichment analyses showed that the top five upregulated canonical pathways were EIF2 signaling, actin cytoskeleton, systemic lupus erythematosus, hypoxia signaling, and, notably, the protein ubiquitination pathway (Fig. 3B; Supplementary Table S9). Molecular and cellular functional annotations also indicated that BMRTCs upregulated genes involved in gene expression, RNA posttranslational modifications, protein synthesis, cell cycle, and cell survival with a concomitant decrease in cell death and apoptosis. Second, because the distinct gene expression pattern of ex vivo BMRTCs may have been conferred by the osteogenic niche during their residence in bone marrow and could be a reflection of their dependence on these unique signaling mechanisms, we focused on individual genes in the protein ubiquitination pathway that were most strikingly elevated in BMRTCs. We found that PTEN, a known tumor suppressor gene, and Ubiquitin Specific Peptidase 7 (USP7), a deubiquitinating enzyme involved in posttranslational modifications, were significantly upregulated (PTEN, FC = 219, P = 0.0028; USP7, FC = 5, P = 0.0072) in ex vivo BMRTCs (Fig. 3B; refs. 28, 29). To confirm these findings, we assessed USP7 and PTEN expression on FACS-sorted HLA+/Melan-A+ex vivo BMRTCs/CTCs by immunofluorescence, and observed elevated expression of USP7 and PTEN in BMRTCs (Fig. 3C). Next, we performed survival analyses of USP7/PTEN gene expression in patients (n = 114) with cutaneous melanoma whose data were obtained from The Cancer Genome Atlas database by employing Oncolnc software tool (http://www.oncolnc.org/; ref. 30). Kaplan–Meier survival analyses show that high expression of USP7 correlated with decreased patient survival, whereas PTEN expression was not significantly associated (log-rank P values of 0.0167 vs. 0.112; HR, 1.598 vs. 0.7937 with 95% confidence interval; Fig. 3D). In addition, we did not observe any correlation between patient's PTEN mutational status and its expression on CDX-derived BMRTCs population. Collectively, these findings revealed that USP7 is uniquely upregulated in ex vivo BMRTCs and correlates with shorter patient survival.

Figure 3.

Transcriptional profiling of patients with melanoma BMRTCs versus CTCs in CDXs. A, Hierarchical clustering (FC = 2.5; P = 0.05). B, Volcano plot showing differentially expressed genes in ex vivo BMRTCs versus CTCs by human array (Clariom D; Affymetrix, Inc.); two-way ANOVA was performed to calculate FC and P value [patients #1–8; BMRTCs = 2 and CTCs = 1 (shown below)]. Table displaying significantly altered top canonical pathways in ex vivo BMRTC versus CTC population. C, Increased expression of USP7-PTEN axis in BMRTs versus CTCs by immunofluorescence analyses (scale bar, 10 μm). Graph shows the number of USP7 and PTEN+ cells in BMRTC/CTC populations. One-sample t test was performed to compare the P value. D, Kaplan–Meier plot analyses of USP7 and PTEN performed using cutaneous melanoma patients' The Cancer Genome Atlas database (n = 114; http://www.oncolnc.org/). Blue/red lines indicate USP7 and PTEN low/high expression, respectively. Log rank P value and HR (USP7 = 1.599 and PTEN = 0.7937) were calculated by GraphPad Prism ver7 (95% confidence interval).

Figure 3.

Transcriptional profiling of patients with melanoma BMRTCs versus CTCs in CDXs. A, Hierarchical clustering (FC = 2.5; P = 0.05). B, Volcano plot showing differentially expressed genes in ex vivo BMRTCs versus CTCs by human array (Clariom D; Affymetrix, Inc.); two-way ANOVA was performed to calculate FC and P value [patients #1–8; BMRTCs = 2 and CTCs = 1 (shown below)]. Table displaying significantly altered top canonical pathways in ex vivo BMRTC versus CTC population. C, Increased expression of USP7-PTEN axis in BMRTs versus CTCs by immunofluorescence analyses (scale bar, 10 μm). Graph shows the number of USP7 and PTEN+ cells in BMRTC/CTC populations. One-sample t test was performed to compare the P value. D, Kaplan–Meier plot analyses of USP7 and PTEN performed using cutaneous melanoma patients' The Cancer Genome Atlas database (n = 114; http://www.oncolnc.org/). Blue/red lines indicate USP7 and PTEN low/high expression, respectively. Log rank P value and HR (USP7 = 1.599 and PTEN = 0.7937) were calculated by GraphPad Prism ver7 (95% confidence interval).

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USP7 inhibition modulates metastatic competence and proliferative properties of CDX-isolated BMRTCs/CTCs

We investigated the effects of USP7 inhibitors on metastatic competency of BMRTCs as melanoma-derived, bone marrow–associated CTC population. We performed drug susceptibility assays in CDXs using two clinically relevant USP7 inhibitors: P5091 and P22077. We injected Lin cells (50,000 cells/mouse) from 6 patients with melanoma (patients #11–16) simultaneously into 13 NSG mice and treated mice in parallel with: P5091, P22077, or vehicle (PBS). Mice were euthanized after 11 weeks of treatment and visceral organs and CTCs from blood and bone marrow were harvested for downstream analysis. After euthanization, vehicle and USP7 inhibitor-treated CDX mice (11 weeks of USP7 inhibitor treatment) injected with Lin cell population from the same individual patient, we performed IHC to assess USP7 and PTEN expression in bone marrow and lung as most common metastatic melanoma sites (1). We found a significant reduction of USP7, PTEN, and Melan-A+ cells in bone marrow and lung tissues (micrometastatic disease) in USP7 inhibitor-treated versus PBS-treated CDXs, revealing that USP7 targeting leads to a significant reduction of metastatic competency in patient-derived, bone marrow–associated CTCs (Fig. 4A–E; Supplementary Fig. S7A–S7E).

Figure 4.

USP7 inhibitors affect the metastatic potency of BMRTCs population in CDXs. A–E, Histopathologic Melan-A evaluation with colocalization of USP7 and PTEN staining in lung and bone marrow (BM) tissues from USP7 inhibitor-treated versus untreated CDXs (immunodeficient mice; patients #11–15). Black arrows, positive staining for respective markers. HLA and H&E staining of the same region are shown in extended Fig. 7 of “Supplementary information” (Supplementary Fig. S7A–S7E). Graph showing semiquantitative estimation of USP7/PTEN staining by using ImageJ software. Student t test, type 2, paired 2 were performed to calculate the P value. Scale bar, 100 μm.

Figure 4.

USP7 inhibitors affect the metastatic potency of BMRTCs population in CDXs. A–E, Histopathologic Melan-A evaluation with colocalization of USP7 and PTEN staining in lung and bone marrow (BM) tissues from USP7 inhibitor-treated versus untreated CDXs (immunodeficient mice; patients #11–15). Black arrows, positive staining for respective markers. HLA and H&E staining of the same region are shown in extended Fig. 7 of “Supplementary information” (Supplementary Fig. S7A–S7E). Graph showing semiquantitative estimation of USP7/PTEN staining by using ImageJ software. Student t test, type 2, paired 2 were performed to calculate the P value. Scale bar, 100 μm.

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We also investigated the effects of the USP7 inhibitors on metastatic competency in a syngeneic mice model. We injected metastasis-competent B16F10 melanoma cells through intracardiac procedure in syngeneic C57BL/6J mice. We grouped mice into three categories (n = 10 for each group): (i) PBS-treated control group and groups treated with USP7 inhibitors (ii) P5091 and (iii) P22077, respectively. Mice were euthanized after 21 days, and bone marrow, lung, liver, lymph node, and brain tissues were harvested for analysis. Histopathologic evaluation showed a significant reduction of melanoma metastasis in with both USP7 inhibitors versus untreated control mice groups (Fig. 5A and B). Third, we investigated the effect of USP7 inhibitors on nuclear-cytoplasmic localization of PTEN (Supplementary Fig. S8; ref. 28). We observed significant reduction of nuclear:cytoplasmic PTEN ratio on BMRTC population derived from USP7 inhibitor treated versus untreated CDXs (Supplementary Fig. S8A and S8B). However, we observed restoration of nuclear PTEN in lung mets of mice treated with USP7 inhibitors versus untreated (Supplementary Fig. S8B and S8C). This suggests that distinct microenvironment properties influence the USP7 regulation of PTEN expression.

Figure 5.

USP7 inhibitors affect the metastatic potency of BMRTC population in syngeneic mice. A, Representative H&E staining of lung, bone marrow (BM), liver, brain, and lymph node tissue section derived from syngeneic mice treated versus untreated with USP7 inhibitors. B, Five to eight images of each mouse were quantified for melanoma cells in distant tissue organs. Student t test, type 2, paired 2 were performed to calculate the P value. Scale bar, 100 μm.

Figure 5.

USP7 inhibitors affect the metastatic potency of BMRTC population in syngeneic mice. A, Representative H&E staining of lung, bone marrow (BM), liver, brain, and lymph node tissue section derived from syngeneic mice treated versus untreated with USP7 inhibitors. B, Five to eight images of each mouse were quantified for melanoma cells in distant tissue organs. Student t test, type 2, paired 2 were performed to calculate the P value. Scale bar, 100 μm.

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Fourth, we investigated the effects of USP7 inhibitors on the metastatic competency of ex vivo BMRTCs, considering that roles of USP7 in the pathogenesis of metastatic melanoma remain unclear. We assessed USP7 inhibitors' effect on the proliferative capacity of ex vivo BMRTCs and CTCs (derived from patients #13 and #14) by performing flow cytometric analyses for Ki67, a marker of cellular proliferation (14). We detected greater percentage of Ki67-high cells in CTCs versus BMRTCs irrespective of USP7 inhibitor treatment [P5091: 89.1% (CTCs) vs. 68.4% (BMRTCs); P22077: 91.5% (CTCs) vs. 42.4% (BMRTCs); Fig. 6A]. We observed increased percentage of Ki67high among ex vivo BMRTCs isolated from USP7 inhibitor-treated versus untreated CDXs. Conversely, we did not observe any difference in Ki67 status among ex vivo CTCs isolated from USP7 inhibitors-treated versus untreated CDXs. Furthermore, because mtDNA copy number is an indicator of mitochondrial biogenesis and proliferative potency (31), we compared mtDNA versus nuclear DNA content ratios in ex vivo BMRTCs versus CTCs of six CDX mice (derived from patients #12, #13, and #14). Quantitative PCR showed significantly higher MTN index in BMRTCs derived from USP7 inhibitor-treated versus untreated CDX mice (Fig. 6B). In addition, CellSearch analyses of ex vivo BMRTCs/CTCs from CDXs (derived from patient #12) treated with USP7 inhibitors showed higher number of melanoma CTCs (CD45/CD34/DAPI+/Melan-A+ cells) in BMRTCs versus corresponding CTCs (Fig. 6C). Cumulatively, these findings suggest that USP7 inhibition causes a significant reduction of metastatic competency of BMRTCs by restricting melanoma cell population within bone marrow locales (Figs. 4A–E, 5A–B, and 6A–C; Supplementary Fig. S7A–S7E).

Figure 6.

Effects of USP7 inhibitors on the proliferative ability of patient BMRTCs/CTCs and BMRTC gene expression isolated from CDXs. A, Effects of USP7 inhibitors on Ki67 HLA+/Melan-A+ BMRTC/CTC populations. Mean fluorescence intensity (MFI) of Ki-67 via intracellular multiparametric flow cytometry (patients #13 and #14). Details of procedures and reagents used are described in the Materials and Methods. B, MTN index of FACS-sorted HLA+/Melan-A+ population derived from CDXs (n = 3) paired bone marrow and blood (patients #12, #13, and #14). Total gDNA was extracted and purified, then subjected to MTN determination using qPCR. C, Capture, visualization, and enumeration of CTCs by CellSearch analyses of melanoma patient BMRTCs/CTCs isolated from CDXs treated with or without USP7 inhibitors (patient #12). A total of 500 μL of CDX blood was collected and analyzed according to CellSearch specifications (CD45/CD34/DAPI+/Melan-A+ cells). Displayed are BMRTC/CTC numbers/500 μL blood per treatment condition. D, Differential gene expression profiling of BMRTC population isolated from CDXs treated with and without USP7 inhibitors. E, Scatter plot showing differentially expressed genes in BMRTCs by human array (Clariom D; Affymetrix, Inc.). Two-way ANOVA was performed to calculate FC and P value (FC = 2, P = 0.05). F, Hierarchical clustering (FC = 2.5, P = 0.05) showing differential expressed genes in BMTRCs isolated from CDXs treated versus untreated USP7 inhibitors P5091 (patients #11 and 12) and P22077 (patients #12 and 16). Upregulated/downregulated genes are highlighted in red/black, respectively. G, Validation of microarray data by qPCR analyses. Relative mRNA expression and SD were calculated for each gene. Student t test, type 2, paired 2 were performed to calculate respective P values.

Figure 6.

Effects of USP7 inhibitors on the proliferative ability of patient BMRTCs/CTCs and BMRTC gene expression isolated from CDXs. A, Effects of USP7 inhibitors on Ki67 HLA+/Melan-A+ BMRTC/CTC populations. Mean fluorescence intensity (MFI) of Ki-67 via intracellular multiparametric flow cytometry (patients #13 and #14). Details of procedures and reagents used are described in the Materials and Methods. B, MTN index of FACS-sorted HLA+/Melan-A+ population derived from CDXs (n = 3) paired bone marrow and blood (patients #12, #13, and #14). Total gDNA was extracted and purified, then subjected to MTN determination using qPCR. C, Capture, visualization, and enumeration of CTCs by CellSearch analyses of melanoma patient BMRTCs/CTCs isolated from CDXs treated with or without USP7 inhibitors (patient #12). A total of 500 μL of CDX blood was collected and analyzed according to CellSearch specifications (CD45/CD34/DAPI+/Melan-A+ cells). Displayed are BMRTC/CTC numbers/500 μL blood per treatment condition. D, Differential gene expression profiling of BMRTC population isolated from CDXs treated with and without USP7 inhibitors. E, Scatter plot showing differentially expressed genes in BMRTCs by human array (Clariom D; Affymetrix, Inc.). Two-way ANOVA was performed to calculate FC and P value (FC = 2, P = 0.05). F, Hierarchical clustering (FC = 2.5, P = 0.05) showing differential expressed genes in BMTRCs isolated from CDXs treated versus untreated USP7 inhibitors P5091 (patients #11 and 12) and P22077 (patients #12 and 16). Upregulated/downregulated genes are highlighted in red/black, respectively. G, Validation of microarray data by qPCR analyses. Relative mRNA expression and SD were calculated for each gene. Student t test, type 2, paired 2 were performed to calculate respective P values.

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Effects of USP7 inhibitors on ex vivo BMRTCs/CTCs

To delineate genes involved in the metastatic potency of BMRTCs and affected by USP7 inhibition, we performed comparative transcriptional profiling of ex vivo BMRTCs from paired vehicle versus USP7 inhibitor-treated CDX mice (derived from patients #11, #12, and #16). Differential gene expression profiling revealed 321 significantly altered genes (138 upregulated, 183 downregulated) in BMRTCs treated with USP7 inhibitors (Fig. 6D and E). CDX-derived BMRTCs clustered together in two groups when hierarchical clustering was performed (FC = 2, P = 0.05), suggesting that USP7 affected BMRTCs by a distinct gene signature (Fig. 6F). We also evaluated USP7-altered, metastasis-competent targets in distinct CDX-derived BMRTCs and found significantly four upregulated (POLE, CCP110, SMAD13, and MTND4LP12) and nine downregulated (TNC, FBXO25, RGS22, PDE1A, GPCPD1, ABSB4, SERINC3, EIF3F, and UBXN4) genes associated with metastatic colonization. Furthermore, miRNA analyses revealed upregulation of MIR885-5p, MIR9-1, MIR6870, and MIR3657 and downregulation of MIR4719, MIR 548A2, MIR548AE1, MIR548AJ1, and MIR548AX2 transcripts in USP7-modulated BMRTCs. Quantitative PCR revealed significant downregulation of USP7, PTEN, TNC, and GPCPD1 transcripts in HLA+/Melan-A+ex vivo BMRTCs derived from CDXs treated with USP7 inhibitors (P5091 and P22077) versus vehicle (Fig. 6G). RGS22 transcripts were significantly downregulated in CDX BMRTCs when treated with inhibitor P22077 only, but not with inhibitor P5091 versus vehicle (Fig. 6G). Furthermore, expression of genes involved in cell invasion (TNC, SERINC3, ABSB4, and SMAD13), cell migration (TNC, ASB4, RGS22, and GPCPD1), cell proliferation (MIR885-p and CCP110), and cell apoptosis (TNC, FBXO25, PDE1A, EIF3F) were decreased by USP7 inhibitor treatment, possibly highlighting regulatory roles of USP7 at various metastatic steps during melanoma progression (Fig. 7; refs. 32–39). Next, to determine the role of USP7 inhibition in BMRTC-driven lung colonization, we performed IHC for two USP7-modulated markers (TNC and CCP110) in lung tissue of CDX mice treated versus untreated with USP7 inhibitors (derived from patients #11, #15, and #16). IHC quantification shows significant upregulation of CCP110 and downregulation of TNC in CDX-derived lung tissue treated versus untreated with USP7 inhibitors (P = 0.05; Supplementary Fig. S9A–S9D). Of relevance, USP7 inhibition has been shown to play a role in MDM2 degradation, which leads to reactivation of tumor suppressor genes p53 and p21, resulting in tumor growth inhibition (40). Accordingly, we quantified p53 and p21 expression in lung and bone marrow tissues (derived from patients #13 and #15) of CDXs treated versus untreated with USP7 inhibitors (Supplementary Fig. S10A–S10D). IHC quantification shows significantly elevated expression of p53 and p21 on lung and bone marrow tissue derived from CDX mice treated with versus without USP7 inhibitors (P = 0.05).

Figure 7.

Model representing the asymptomatic progression of melanoma in patient-derived xenografts and effects of USP7 inhibition, either as a potential direct action on cells already disseminated to distant organs or as a result of USP7 targeting BMRTCs.

Figure 7.

Model representing the asymptomatic progression of melanoma in patient-derived xenografts and effects of USP7 inhibition, either as a potential direct action on cells already disseminated to distant organs or as a result of USP7 targeting BMRTCs.

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This study provides first-time evidence that asymptomatic progression of metastatic melanoma can be recapitulated in vivo using patient-isolated CTCs, and demonstrates that melanoma CTCs at advanced disease stages contain heterogeneous cell pools bearing distinct characteristics associated with bone marrow versus blood locales. In addition, we show that USP7 plays critical roles in BMRTC metastatic potential by regulating genes related to cellular proliferation, apoptosis, and cell migration. Complementing previous investigations that have characterized the genetic landscape of primary and metastatic melanoma lesions, we demonstrate that transcriptional subtyping of melanoma CTCs provides key insights into the molecular mechanisms that regulate metastatic potency by proposing a novel rationale-based approach for targeting BMRTCs (5, 7, 8, 10, 11, 13, 16, 17). In contrast to the majority of CTC studies that have largely elucidated the spatial attributes of peripheral blood-based CTCs in the context of metastasis, we provide insights into the primordial stages of CTC dissemination and survival in bone marrow without progression to overt metastasis.

Employing a negative selection strategy to deplete normal cell populations of blood, we implanted patient Lin cells in immunodeficient mice to generate CDX models that can faithfully recapitulate the early events of melanoma metastasis. Lin cell populations not only had overexpression of melanoma markers, but also harbored mutations on multiple melanoma oncogenes, demonstrating their atypical nature (Fig. 1A–F; Supplementary Table S5; refs. 14, 41). Furthermore, combining the use of an antigen-agnostic platform (DEPArray) with genomic sequencing, we show that melanoma CTCs home to and reside in the bone marrow of CDX mice when injected with patient-isolated Lin cell population (Figs. 2A–D and 4A–E). We consider this approach useful for establishing patient-derived xenograft models particularly when patient tumor tissue may not be available.

Whole-genome transcriptomic arrays and qPCR for individual target genes identified distinct transcriptional signatures of ex vivo melanoma BMRTCs, potentially reflecting effects of bone marrow microenvironment on BMRTC gene expression. In addition, the proportion of Ki67-low cells was approximately 50% higher in ex vivo BMRTCs versus CTCs, suggesting that BMRTCs contain a distinct cell subpopulation that may be in a state of subdued proliferation (Fig. 6A). However, we did not observe any correlation between high Ki67 index present in USP7 inhibitors–treated BMRTCs population and metastatic burden in visceral organs or bone. Of note, Ki67 as a good indicator of proliferation and present in G1–M and S phases of cell cycle while absent in the G0 phase (42). Therefore, this is likely due to the effect of USP7 inhibitors, which arrests the Ki67+ BMRTC population at G1–S phase of cell cycle and inhibits their metastatic potential (43, 44). This suggests that USP7 inhibitors, although augmenting the proliferative potency of BMRTCs, do not augment their dissemination from bone marrow to generate lethal metastasis. Interestingly, we detected BMRTC-specific mutations in SMAD4 and APC genes, suggesting that besides affecting gene expression, bone marrow microenvironment may impart temporal selective pressures on BMRTCs, resulting in their acquiring unique mutations (Fig. 2B; Supplementary Table S8; ref. 5).

The deubiquitinase enzyme USP7 is involved in the posttranslational modification of PTEN altering its tumor-suppressive activity. Loss of PTEN function in patients with melanoma has been linked to significantly faster progression to overt brain metastasis along with poorer overall survival (45). In our CDX models, we found significantly higher USP7 expression that colocalized with PTEN in BMRTCs when compared with ex vivo CTCs (Figs. 3A–D and 4A–E). It is likely that the high expression of USP7 transcripts detected in BMRTCs reflects the intrinsic behavior of heterogeneous CTC pool as well as properties of the bone marrow microenvironment. This is because: (i) patient-derived CTCs contain a heterogeneous pool of melanoma cells and CTC subsets have the tendency to seed the bone marrow and (ii) USP7 modulates the osteogenic differentiation of mesenchymal stem cells in bone marrow (5, 46). Kaplan–Meier survival analyses indicated that high USP7 (but not PTEN) expression is significantly associated with decreased overall survival of patients with melanoma (Fig. 3D), while targeting USP7 with specific inhibitors reduced ex vivo CTC numbers at metastatic organ sites along with a concomitant decrease in USP7 and PTEN expression (Figs. 4A–E and 5A and B). Our immunohistopathologic evaluation shows a significant upregulation of p53 and p21 expression in lung and bone marrow tissues derived from CDX mice treated with USP7 inhibitors versus PBS-treated group (Supplementary Fig. S10A–S10D); however, we did not observe a significant difference in p53 transcript expression between ex vivo BMRTCs versus CTCs (28, 40). However, gene expression microarray analysis of USP7 inhibitor treated versus untreated ex vivo BMRTCs revealed several candidate genes significantly affected by USP7 inhibition (Fig. 6D–F). Among them, TNC and FBXO25 are genes implicated in the development of metastatic melanoma, breast and non–small cell lung cancers (32, 33, 47). Furthermore, downregulation of genes involved in cell migration (RGS22, GPCPD1 and ASB4) and invasion (TNC, SERINC3, ABSB4 and SMAD13) was also detected, suggesting that USP7 inhibition may impede BMRTC reshedding from bone marrow, arresting them in bone marrow locales (35–37, 48). USP7 inhibition also decreased the expression of proliferation-related biomarkers (Ki67 and MTN indices; Fig. 6A–F), possibly by affecting genes (e.g., CCP110, POLE, p21 and p53; Supplementary Figs. S9A–S9D and S10A–S10D) that arrest BMRTC cell-cycle progression and may induce senescent phenotype (38, 39). Collectively, these findings suggest that USP7 plays a central role in mediating melanoma CTC residence in bone marrow (Figs. 6A–G and 7).

Our study has some limitations. First, analyses were performed on a low number of patients; therefore, we cannot conclude that all patients with melanoma follow these models and pathways. Second, we profiled a limited number of cells in each patient, which, although done stochastically, may have some inherent sampling bias. Third, although we suggest that USP7 inhibition–mediated reduction of micrometastasis is not a direct effect on cells already disseminated to distant organs, we cannot exclude a direct effect of USP7 inhibition on these cells. However, our results demonstrate that melanoma patient–isolated CTCs home to and reside in bone marrow, and emphasize the relevance of determining the prognostic value of bone marrow–associated, CTC-derived cell populations. The systematic interrogation of these BMRTCs identified USP7 as an important mediator of BMRTC-specific signaling and provided evidence that applying USP7 inhibitors in clinical settings can be relevant to eliminate residual melanoma cells in bone marrow and thereby prevent further metastatic spread.

M.T. Tetzlaff is a consultant/advisory board member of Seattle Genetics, Novartis, and Myriad Genetics. M.A. Davies reports receiving commercial research grants from GSK, Astrazeneca, Roche/Genentech, Oncothyreon, and Sanofi-Aventis and is consultant/advisory board member of GSK, Novartis, BMS, Sanofi-Aventis, Syndax, and Nanostring. No potential conflicts of interest were disclosed by the other authors.

Conception and design: M. Vishnoi, D. Boral, D. Marchetti

Development of methodology: M. Vishnoi, D. Boral

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): M. Vishnoi, H. Liu, W. Yin, M.L. Sprouse, D. Goswami-Sewell, M.T. Tetzlaff, M.A. Davies, I.C. Glitza Oliva

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): M. Vishnoi, D. Boral, M.L. Sprouse, W. Yin, D. Goswami-Sewell, M.T. Tetzlaff

Writing, review, and/or revision of the manuscript: M. Vishnoi, D. Boral, M.T. Tetzlaff, M.A. Davies, I.C. Glitza Oliva, D. Marchetti

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): M. Vishnoi, H. Liu, W. Yin

Study supervision: D. Marchetti

This study was supported by the NIH grants (1 R01 CA 216991 and 1 R01 CA 160335 to D. Marchetti); the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation (to M.A. Davies); the AIM at Melanoma Foundation (to M.A. Davies); and by philanthropic support from the MD Anderson Melanoma Shot Program (to M.A. Davies). We are thankful to Dr. David Haviland, Director of the Flow Cytometry Core at Houston Methodist Research Institute (HMRI), Dr. Zhubo Wei of the Biostatistics core at HMRI, and to Dr. Chang-Gong Liu, Director of the sequencing and ncRNA core at MD Anderson Cancer Center for their respective expertise.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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