An RNA-Based Digital Circulating Tumor Cell Signature Is Predictive of Drug Response and Early Dissemination in Prostate Cancer

Published OnlineFirst January 4, 2018; DOI: 10.1158/2159-8290.CD-16-1406

Research Article

David T. Miyamoto1,2, Richard J. Lee1,3, Mark Kalinich1, Joseph A. LiCausi1, Yu Zheng1, Tianqi Chen4, John D. Milner1, Erin Emmons1, Uyen Ho1, Katherine Broderick1, Erin Silva1, Sarah Javaid1, Tanya Todorova Kwan1, Xin Hong1, Douglas M. Dahl1,5, Francis J. McGovern1,5, Jason A. Efstathiou1,2, Matthew R. Smith1,3, Lecia V. Sequist1,3, Ravi Kapur1, Chin-Lee Wu1,6, Shannon L. Stott1,3,7, David T. Ting1,3, Anita Giobbie-Hurder4, Mehmet Toner7,8, Shyamala Maheswaran1,8, and Daniel A. Haber1,3,9

Digital Expression Signatures of Prostate CTCs RESEARCH ARTICLE

abstract Blood-based biomarkers are critical in metastatic prostate cancer, where charac- teristic bone metastases are not readily sampled, and they may enable risk stratification in localized disease. We established a sensitive and high-throughput strategy for analyzing prostate circulating tumor cells (CTC) using microfluidic cell enrichment followed by digital quantitation of prostate-derived transcripts. In a prospective study of 27 patients with metastatic castration- resistant prostate cancer treated with first-line abiraterone, pretreatment elevation of the digital

CTCM score identifies a high-risk population with poor overall survival (HR= 6.0; P = 0.01) and short radiographic progression-free survival (HR = 3.2; P = 0.046). Expression of HOXB13 in CTCs identifies 6 of 6 patients with ≤12-month survival, with a subset also expressing the ARV7 splice variant. In a

second cohort of 34 men with localized prostate cancer, an elevated preoperative CTCL score predicts microscopic dissemination to seminal vesicles and/or lymph nodes (P < 0.001). Thus, digital quantitation of CTC-specific transcripts enables noninvasive monitoring that may guide treatment selection in both metastatic and localized prostate cancer.

SIGNIFICANCE: There is an unmet need for biomarkers to guide prostate cancer therapies, for curative treatment of localized cancer and for application of molecularly targeted agents in metastatic disease. Digital quantitation of prostate CTC-derived transcripts in blood specimens is predictive of abiraterone response in metastatic cancer and of early dissemination in localized cancer. Cancer Discov; 8(3); 1–16. ©2018 AACR.

See related commentary by Heitzer and Speicher, p. 269.

INTRODUCTION including potent suppressors of androgen synthesis (e.g., abiraterone), inhibitors of the androgen receptor (AR) itself The application of blood-based biomarkers is emerging as (e.g., enzalutamide), vaccine therapy (sipuleucel-T), cytotoxic an important strategy for individualizing therapeutic choices chemotherapy (docetaxel or cabazitaxel), bone-tropic radio- in prostate cancer in the settings of both metastatic and isotopes such as radium-223, and PARP inhibitors (4, 5). In localized disease. In advanced prostate cancer, typically char- this context, circulating tumor cell (CTC) quantitation has acterized by bone metastases that cannot be readily biopsied been proposed as a potential surrogate endpoint to facilitate for tumor sampling (1), multiple increasingly potent thera- the selection of treatment algorithms (6), although the small peutic regimens have been recently approved, resulting in a number of cells identified visually in blood specimens from pressing need for noninvasive tumor-specific predictors of patients with prostate cancer and the lack of specific molecular response (2, 3). In virtually all cases, metastatic prostate cancer determinants of response have limited its clinical utility (7). initially responds to androgen deprivation therapy (ADT), To date, most molecular alterations in prostate cancer which suppresses the primary driver of proliferation in this that have potential therapeutic implications have been cen- tissue. Responses, however, are limited in duration and the tered around the AR gene itself, including gene amplifica- development of metastatic castration-resistant prostate cancer tion or overexpression, activating mutations, or alterations (mCRPC) necessitates the application of alternative therapies, in transcriptional coactivators (8). Measuring AR signaling output through expression ratios of androgen-induced 1Massachusetts General Hospital Cancer Center, Boston, Massachusetts. versus androgen-repressed transcriptional targets has been 2Department of Radiation Oncology, Massachusetts General Hospital, Harvard proposed as an integrated readout for these complex AR Medical School, Boston, Massachusetts. 3Department of Medicine, Massa- pathway alterations (9). Multiple AR gene splicing variants chusetts General Hospital, Harvard Medical School, Boston, Massachusetts. encoding aberrant ligand-independent transcriptional acti- 4Department of Biostatistics & Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts. 5Department of Urology, Massachusetts vators have also been described in mCRPC (10). These AR General Hospital, Harvard Medical School, Boston, Massachusetts. 6Depart- isoforms are rarely expressed in primary prostate cancer, but ment of Pathology, Harvard Medical School, Boston, Massachusetts. 7Center they are readily detected in mCRPC, with single-cell RNA for Engineering in Medicine, Massachusetts General Hospital, Boston, sequencing (RNA-seq) of CTCs identifying multiple variants Massachusetts. 8Department of Surgery, Harvard Medical School, Boston, Massachusetts. 9Howard Hughes Medical Institute, Chevy Chase, Maryland. within different tumor cells from the same patient and even within individual CTCs (11). One of the most common vari- Note: Supplementary data for this article are available at Cancer Discovery Online (http://cancerdiscovery.aacrjournals.org/). ants, ARV7, is noteworthy in that it encodes a novel cryptic D.T. Miyamoto and R.J. Lee contributed equally to this article. exon, CE3, which may be detected using either CE3 exon- specific RNA-based PCR amplification or CE3 exon-targeted Corresponding Authors: Daniel A. Haber, Massachusetts General Hospital Cancer Center, Building 149, 13th Street, Boston, MA 02129. Phone: 617- IHC staining. In patients with mCRPC receiving AR-target- 726-7805; Fax: 161-7726-5637; E-mail: [email protected]; and ing therapies, detection of ARV7 in CTCs has been correlated Shyamala Maheswaran, [email protected] with a poor outcome (12–14). In addition to alterations in doi: 10.1158/2159-8290.CD-16-1406 AR signaling, additional pathways have been implicated ©2018 American Association for Cancer Research. in the progression toward androgen-independent disease,

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RESEARCH ARTICLE Miyamoto et al. including expression of the glucocorticoid receptor (15), digital PCR quantitation could provide a higher through- activation of the noncanonical WNT pathway (11), and evolu- put, more sensitive, and more specific readout of prostate tion of tumor cells toward a neuroendocrine phenotype (16). CTCs. We recently established such an assay for detection of In contrast to mCRPC, early-stage localized prostate cancer is liver-derived CTCs in patients with hepatocellular carcinoma often characterized by good prostate cancer–specific outcomes (28), and we reasoned that prostate-derived CTCs may also regardless of treatment modality, including radical prostatec- express specific transcripts that are unique to this tissue of tomy, radiotherapy, or active surveillance (17). However, a sub- origin and are undetectable in normal blood cells, even using set of patients is at high risk of tumor dissemination outside a highly sensitive digital PCR assay (Supplementary Fig. of the prostate gland, most often to the seminal vesicles and S1A). Microfluidic (CTC-iChip) depletion of hematopoietic pelvic lymph nodes, and eventually to bone. Standard clinico- cells from blood samples achieves 104 to 105 purification pathologic parameters including Gleason score, serum PSA, of CTCs, with approximately 500 white blood cells (WBC) and clinical T-stage (18, 19) and clinical nomograms (20, 21) remaining per 1 mL of initially processed whole blood (27). provide estimates for risk stratification, but they rely primarily The high quality of RNA within the purified CTCs allows on pathologic assessment of prostate core biopsies, which are the application of ddPCR, in which rare cDNA templates are subject to undersampling errors and often underestimate the encapsulated within lipid droplets, followed by PCR amplifi- true pathologic stage of the cancer (22, 23). Interestingly, CTCs cation and fluorescence scoring of positive droplets (29). The have been detected in the blood of a fraction of men with local- combination of initial microfluidic whole-cell enrichment ized prostate cancer, which are cleared within 24 hours of surgi- of CTCs from blood, followed by RNA-based digital PCR cal resection of the prostate, although the clinical significance of CTC-derived transcripts, thus allows exceptionally high- of these findings has not been established (24–26). sensitivity scoring of prostate cancer cells that have invaded Although CTCs provide a source of tumor material for the bloodstream. serial, noninvasive sampling of prostate cancer, their broad To test the application of this strategy for prostate CTC application in clinical monitoring has been precluded by detection, we first identified a panel of prostate-specific tran- technological hurdles, including complex platforms for scripts whose expression is virtually absent in normal hemat- rare cell isolation from blood samples and sophisticated opoietic cells, even using highly sensitive ddPCR detection. cell-based imaging and scoring. Recently, the development We selected multiple markers, both to address the known of microfluidic technologies has allowed efficient process- heterogeneity of prostate cancer cells, as well as to allow ing of blood specimens for CTC capture, including effi- interrogation of cellular signaling pathways, including AR cient depletion of hematopoietic cells to enable tumor activity. We derived an initial set of 40 candidate genes, both epitope–independent enrichment of untagged CTCs (27). from RNA-seq of single prostate CTCs (11), as well as from However, the reliance on microscopic imaging and quan- publicly available expression databases (Supplementary Fig. titation of immunofluorescence-based signals in enriched S1B; Supplementary Table S1). Eleven transcripts were identi- but impure CTC populations remains a critical limitation. fied as having high levels of expression in prostate tissue and/ We recently demonstrated, using single-cell RNA-seq of or prostate cancer, but without detectable RNA reads in nor- prostate CTCs isolated by negative depletion microfluidics, mal blood cells contaminating the microfluidic CTC-iChip that these microfluidically isolated circulating cancer cells product (Supplementary Fig. S1B). Multiple primers and contain highly intact RNA, readily distinguishable from conditions were optimized for a set of 8 genes, which together that of contaminating leukocytes in the CTC-iChip output, provided the most robust signal in rare prostate cancer cells thereby enabling RNA-based diagnostics (11). Assessment admixed with normal blood cells. To initially confirm dif- of CTC RNA molecular signatures using a droplet digital ferential expression of the selected genes, we used single-cell PCR (ddPCR) assay enables rapid and reliable detection of RNA-seq of CTCs individually isolated from patients with CTCs in hepatocellular carcinoma, and may allow for early metastatic prostate cancer, compared with RNA-seq of single detection of liver cancers (28). Here, we established an RNA- leukocytes contaminating the microfluidic CTC-iChip prod- based molecular signature that allows high throughput and uct. Indeed, single-cell RNA-seq reads for these transcripts highly quantitative detection of prostate CTCs following within 76 CTCs from 12 patients with metastatic prostate microfluidic enrichment. In a prospective trial of men with cancer show massive enrichment, compared with matched mCRPC treated with first-line abiraterone, we identify pre- single leukocytes (Fig. 1A; RNA-seq data from ref. 11 and dictive CTC-derived molecular markers of clinical outcome. GEO GSE67980). These genes include androgen-responsive Furthermore, in men with clinically localized prostate cancer transcripts KLK3 (PSA), KLK2, TMPRSS2, and AGR2; andro- undergoing radical prostatectomy, digital detection of CTCs gen-repressed transcripts FOLH1 (PSMA) and HOXB13; and is predictive of pathologic seminal vesicle invasion (SVI) and androgen-independent transcripts FAT1 and STEAP2. To lymph node dissemination identified at the time of surgery. avoid dilution of rare templates while enabling amplification of multiple markers, we designed a multiplex assay (2 RESULTS reactions with 4 genes per reaction), with differing relative ratios of FAM and HEX fluorescence to define the identity Generation of CTC Digital Signature Using of the amplified product (Fig. 1B; Supplementary Fig. S1C). Prostate Lineage Transcripts A multiclass support vector machine (SVM) classifier was Given the well-recognized limitations inherent in fluo- developed to automatically classify droplets according to rescence-based imaging and scoring of CTCs admixed with their position on the FAM/HEX coordinate system (Fig. 1D; contaminating blood cells, we tested whether RNA-based see Methods).

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Digital Expression Signatures of Prostate CTCs RESEARCH ARTICLE

Single prostate CTCs by patient A WBCs 6910 11 14 15 17 18 19 20 21 22 WBC1.1 WBC1.2 WBC1.3 WBC2.1 WBC2.2 Pr6.1.1 Pr6.1.2 Pr6.1.5 Pr9.1.1 Pr9.1.2 Pr9.1.3 Pr9.1.4 Pr9.1.6 Pr9.3.1 Pr9.3.6 Pr9.3.7 Pr9.3.8 Pr10.2.2 Pr11.1.1 Pr11.2.2 Pr11.3.1 Pr11.3.2 Pr11.3.3 Pr11.4.1 Pr11.4.2 Pr11.4.3 Pr11.4.4 Pr11.4.5 Pr11.4.6 Pr14.1.1 Pr14.2.1 Pr14.2.2 Pr14.2.3 Pr14.2.4 Pr14.2.5 Pr14.2.6 Pr14.3.1 Pr14.3.4 Pr14.3.5 Pr14.3.6 Pr15.1.1 Pr17.1.1 Pr22.1.12 Pr17.1.2 Pr17.2.1 Pr17.2.2 Pr18.1.1 Pr18.1.4 Pr18.1.5 Pr18.1.6 Pr18.1.7 Pr18.1.8 Pr18.2.1 Pr18.2.2 Pr18.2.3 Pr19.1.2 Pr19.1.3 Pr19.1.4 Pr19.1.5 Pr20.1.1 Pr21.1.1 Pr21.1.2 Pr21.1.3 Pr21.1.4 Pr21.1.5 Pr21.1.6 Pr21.1.7 Pr21.1.8 Pr21.1.9 Pr21.1.10 Pr21.1.11 Pr21.1.12 Pr22.1.2 Pr22.1.4 Pr22.1.5 Pr22.1.6 Pr22.1.7 Pr22.1.8 Pr22.1.9 Pr22.1.10 Pr22.1.11 AGR2 FAT1 FOLH1 HOXB13 KLK2 KLK3 STEAP2 TMPRSS2

Log10(RPM + 1)

0 123

B Multiplex prostate CTC assay C Cells spiked into blood 6,000 Reaction 1 Reaction 2 FOLH1 (FAM/HEX) (FAM/HEX) AGR2 TMPRSS2 KLK3 (100/0) (100/0) 4,000 HOXB13 FAT1 HOXB13 KLK3 (65/35) (70/30) STEAP2 KLK2 AGR2 2,000 (40/60) (50/50) KLK2

STEAP2 FOLH1 otal positive droplets T FAT1 (0/100) (0/100) 0 TMPRSS2 0 1351050 Number of LNCaP cells

D Reaction 1 Reaction 2 Reaction 1 EMPTY KLK2 TMPRSS2–FAT1 FAT1 STEAP2 TMPRSS2–KLK2 STEAP2–KLK2 Multiclass FAT1–KLK2 TMPRSS2–STEAP2

M M FAT1–STEAP2 TMPRSS2 SVM classifier FA FA Reaction 2 AGR2 HOXB13 KLK3–AGR2 AGR2–FOLH1 HOXB13–AGR2 KLK3–FOLH1 HEX HEX EMPTY HOXB13–FOLH1 KLK3–HOXB13 FOLH1 KLK3 FAT1 KLK3 TMPRSS2 Metastatic KLK2 HOXB13 patient AGR2

STEAP2 FOLH1

FAT1 KLK3 TMPRSS2 Localized KLK2 HOXB13 patient AGR2

STEAP2 FOLH1

FAT1 KLK3 TMPRSS2 Healthy KLK2 HOXB13 donor AGR2

STEAP2 FOLH1

Figure 1. A, Single-cell RNA-seq data showing expression of final selected genes in WBCs and single prostate CTCs isolated from patients with metastatic prostate cancer (data from GEO GSE67980). B, List of genes contained within each multiplex prostate CTC assay, with FAM/HEX ratio for each probe listed below. Genes in green font are androgen responsive, genes in red font are androgen repressed, and genes in blue font are androgen independent. C, Graph of d-CTC assay signal for varying numbers of LNCaP cells micromanipulated into healthy donor whole blood and processed using the CTC-iChip. D, Top, multiclass SVM classifier model to automatically classify positive droplet signals. Bottom three panels, representative multiplex ddPCR expression signal in CTCs from a patient with metastatic prostate cancer, a patient with localized prostate cancer, and a healthy donor.

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RESEARCH ARTICLE Miyamoto et al.

To validate the assay, we first micromanipulated individual teristic of this tumor type. To complement the quantitation cells of the prostate cancer cell line LNCaP and introduced of prostate lineage-based transcripts in CTCs, we developed these into 4 mL aliquots of whole blood from healthy donors, droplet PCR assays for both the TMPRSS2–ERG fusion tran- followed by processing through the CTC-iChip and ddPCR script, which is present in about half of prostate cancer cases quantitation. Introduction of a single LNCaP cell into a (30), and the ARV7 mRNA splice variant, which constitutes a control blood sample generated 150 positive droplets (SD = marker of resistance to AR-targeted therapies (12). Both tests 65.3), with a progressive increase in signal as 3, 5, 10, and were highly specific and sensitive when applied to individual 50 cells were spiked into the blood samples (5,562 ± 1,853 prostate cancer cells spiked into control whole-blood speci- droplets for 50 prostate cell input; Fig. 1C). The distribution mens, followed by CTC-iChip purification (Fig. 3A). When of signal among the 8 prostate lineage transcripts remained applied to blood samples from men with metastatic prostate comparable with increasing numbers of LNCaP cell input cancer, 5 of 15 (33%) patients with mCRPC had the TMPRSS2– (Supplementary Fig. S1D). ERG translocation, 8 (53%) had the ARV7 splice variant, and 4 (27%) had both cancer-associated transcripts in their CTC Scoring in Patients with Metastatic CTCs (Fig. 3B). Blood samples from 12 age-matched healthy Prostate Cancer male donors were negative for both transcripts (Fig. 3B). As We tested the digital CTC detection strategy in 12 patients expected, men whose CTCs were positive for TMPRSS2–ERG with metastatic prostate cancer, compared with 8 patients had archival primary tumors that were largely concordant with localized prostate cancer, 34 male healthy blood donors for that marker, as assessed by ddPCR (Fig. 3C). In contrast, (19 were >50 years old; 15 were <50 years old), and 5 female presence of ARV7 was discordant between primary prostate controls (see Supplementary Table S2 for clinical details). The cancers (1/15) and matched CTCs subsequently isolated from observed signal across all 8 markers is shown in Fig. 2A. Using these patients in the setting of metastatic disease (8/15; Fig. the 12 patients with metastatic prostate cancer (median age, 3C), consistent with its characterization as a marker that 67 years) and the 19 age-matched male controls (all age >50 emerges in the setting of treatment for advanced refractory years; median age, 63 years), we examined the signal-to-noise mCRPC (31). ratio for each of the 8 genes and derived a digital CTC score by weighing each of these in proportion to the median difference Prospective Monitoring of Patients on First-Line between patients with mCRPC and age-matched controls (Fig. Abiraterone Therapy 2B; Supplementary Fig. S2; see Methods). We identified this Virtually all patients with metastatic prostate cancer expe- measurement as CTCM score (for metastatic). A positive CTCM rience an initial clinical response to ADT, but subsequent score was present in 11 of 12 (92%) patients with metastatic treatments are marked by considerable heterogeneity. As prostate cancer, compared with 0 of 34 healthy male blood tumors develop castration resistance, about half of patients donors (P = 0.008). Under these stringent criteria, none of the have a sustained response to treatment with the potent 12 patients with localized prostate cancer had detectable CTCM androgen synthesis inhibitor abiraterone, whereas others scores. Interestingly, although we established scoring criteria have only a short response and would hence potentially for highest specificity in monitoring patients with metastatic benefit from other treatments or combination therapies (32). prostate cancer, low-level digital signal in several genes was pre- To test whether CTC-derived signatures provide predictive sent in some individuals with localized cancer (Fig. 2A). Among markers of response to AR-targeted therapies after ADT, we healthy individuals, very low-level signal was present, primarily prospectively evaluated 27 patients with mCRPC who were in androgen-independent transcripts such as the embryonic initiating abiraterone therapy in the first-line setting (Sup- cadherin FAT1, with females and men older than age 50 having plementary Table S3). higher background signal than men younger than age 50. We applied the RNA-based prostate CTCM score, ARV7, and Across patients with mCRPC, the total digital CTCM score TMPRSS2–ERG assays to microfluidically enriched CTCs at signal was not significantly correlated with serum PSA pro- the baseline pretreatment time point (Fig. 4A). To compare tein measurements (R2 = 0.03; P = 0.58; Fig. 2D), a find- the digital CTC assay with more traditional immunofluores- ing that is consistent with prior observations that visual cence-based detection of CTCs, each blood sample was pro- immunofluorescence-based enumeration of CTCs is not well cessed through the CTC-iChip, and the output was equally correlated well with serum PSA across different patients (24). divided between immunofluorescence-based microscopy scor- The levels of serum PSA were only slightly better correlated ing for protein expression of EPCAM, CK8, CK18, CK19, PSA, with the quantitation of CTC-derived KLK3 (PSA) mRNA and PSMA, in comparison with the digital CTC assay (Fig. (R2 = 0.36; P = 0.04; Fig. 2E). Taken together, these observa- 4A). As expected, concordance between microscopic scoring tions indicate that, by integrating multiple AR-dependent and digital readouts was evident in samples with high num- and independent transcripts within invasive tumor cells in bers of CTCs, but the digital CTC assay was far more sensitive the blood, the digital CTCM score provided information on in identifying cases below microscopic detection, even using disease status that is nonoverlapping and potentially orthog- sophisticated multispectral fluorescence-based imaging R( 2 = onal to serum PSA measurements. 0.01; P = 0.6; Fig. 4B). A poor correlation between serum PSA and digital CTC score was also noted in this cohort (R2 = 0.16; Detection of ARV7 and TMPRSS2–ERG Prostate P = 0.049; Supplementary Fig. S3A and S3B). Cancer–Specific Transcripts in CTCs With a median follow-up time of 13 months among living

Although recurrent missense mutations are rare in pros- patients, an elevated CTCM score was significantly predic- tate cancer, two specific RNA fusion transcripts are charac- tive of worse overall survival (Fig. 4C; HR = 6.0; P = 0.01)

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Digital Expression Signatures of Prostate CTCs RESEARCH ARTICLE

A Healthy donor controls Patients with prostate cancer (CTCs) Female Male (<50 yo) Male (>50 yo) Localized Metastatic HDF1 HDF2 HDF3 HDF4 HDF5 HDMY1 HDMY2 HDMY3 HDMY4 HDMY5 HDMY6 HDMY7 HDMY8 HDMY9 HDMY10 HDMY11 HDMY12 HDMY13 HDMY14 HDMY15 HDMO1 HDMO2 HDMO3 HDMO4 HDMO5 HDMO6 HDMO7 HDMO8 HDMO9 HDMO10 HDMO11 HDMO12 HDMO13 HDMO14 HDMO15 HDMO16 HDMO17 HDMO18 HDMO19 Pr1 Pr2 Pr3 Pr4 Pr5 Pr6 Pr7 Pr8 Pr9 Pr10 Pr11 Pr12 Pr13 Pr14 Pr15 Pr16 Pr17 Pr18 Pr19 Pr20 AGR2 FAT1 FOLH1 HOXB13 KLK2 KLK3 STEAP2 TMPRSS2

Prostate CTC –M score

Log10(droplets + 1)

0.0 0.5 1.0 1.5 2.0

B 8 C 10,000 CTCM score = (∑ (genei * weighti))/1,000 i = 1 1,000 scor e

Gene Weights FAT1 51.6 M 100 KLK2 14525.7 STEAP2 573.2 10 Average (MPi ) TMPRSS2 311.1 Weighti = Average (HDM ) AGR2 1160.0 i 1

FOLH1 640.8 Prostate CT C HOXB13 473.4 0.1 KLK3 3152.9

Female ctrls Loc prost ca Met prost ca

Male ctrls (<50Male yo) ctrls (>50 yo)

D Serum PSA vs. CTCM score E Serum PSA vs. KLK3 in CTCs 10,000 10,000

1,000 1,000 score

M 100 100

10 10

1 1 R 2 =0.03 KLK3 droplets/mL R 2 =0.36 Prostate CTC P =0.58 P =0.04 0.1 0.1

110 100 1,000 10,000 110 100 1,000 10,000 Serum PSA (ng/mL) Serum PSA (ng/mL)

Figure 2. A, Heat map showing d-CTC assay signal for each gene in blood obtained from healthy donor controls, patients with localized prostate cancer, and patients with metastatic prostate cancer. B, Equation for prostate CTCM score, with weights for each gene based on the relative signal-to- noise ratio in metastatic patients relative to healthy donors (see Methods). C, Graph showing the quantitation of CTCM score signal after application of the prostate CTCM score in healthy donor controls, patients with localized prostate cancer, and patients with metastatic prostate cancer (metastatic patient without signal is Pr17). D and E, Graphs of relationships between prostate CTC score and serum PSA, and CTC ddPCR KLK3 signal and serum PSA in patients with mCRPC. and rapid radiographic progression after abiraterone in the regulated genes HOXB13, FOLH1, KLK2, KLK3, and AGR2 were first-line setting (Fig. 4D; HR= 3.2; P = 0.046). Similar results each individually significantly predictive of lower overall sur- were obtained using immunofluorescence microscopy–based vival (Supplementary Fig. S3E), and almost all of these AR- CTC enumeration (Supplementary Fig. S3C and S3D), con- regulated genes were also predictive for worse radiographic firming the known correlation between CTC enumeration progression-free survival (Supplementary Fig. S3F). In par- and prognosis in metastatic prostate cancer (33). Of the ticular, expression within CTCs of HOXB13, a gene associ- genes that comprise the CTCM score, expression of the AR- ated with aberrant AR signaling and with more aggressive

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A ARV7 assay TMPRSS2–ERG assay (cells spiked into blood) (cells spiked into blood) 100 12,000 10,000 80 8,000 60 6,000 40 4,000

ARV7 droplets ARV7 20 2,000

0 TMPRSS2–ERG droplets 0 013510 50 013510 50 Number of 22Rv1 cells Number of VCaP cells

B Patients with metastatic prostate cancer Healthy donors ARV7 ARV7 − +−+

− 64 − 12 0

+ 1 4 + 0 0 TMPRSS2–ERG TMPRSS2–ERG

C Concordance between CTCs and matched archival biopsies ARV7

Pr27 Pr28 PrA13 Pr26 Pr9 PrA1 Pr21 Pr22 Pr23 Pr24 PrA14 Pr25 Pr29 PrA8 PrA16 Concordance: 40% Archival biopsy Kappa: −0.134 CTC McNemar test: P = 0.0455

ddPCR + ddPCR TMPRSS2–ERG −

Pr27 Pr28 PrA13 Pr21 Pr22 Pr23 Pr24 PrA16 PrA14 Pr26 Pr9 Pr25 Pr27 PrA1 PrA8 Concordance: 80% Archival biopsy Kappa: 0.571 CTC McNemar test: P = 1.000

Figure 3. A, Graph of ddPCR signal for ARV7 (no preamplification) and TMPRSS2–ERG (after specific targeted amplification; see Methods) for varying numbers of 22Rv1 cells and VCaP cells, respectively, micromanipulated into healthy donor whole blood and processed using the CTC-iChip. B, Tables showing number of patients with metastatic prostate cancer and healthy donors with ARV7 ddPCR signal and/or TMPRSS2–ERG ddPCR signal. C, Con- cordance of ARV7 and TMPRSS2–ERG status in prostate CTCs and matched archival formalin-fixed, paraffin-embedded specimens of prostate cancer biopsy or prostatectomy tissues from patients with prostate cancer, as measured by ddPCR assays. hormone-refractory prostate cancer, was significantly corre- ARV7 in pretreatment blood samples revealed a range of 0 to lated with worse overall survival (Fig. 4E; HR = 11.8; P = 0.004; 220 transcripts per mL blood (median = 1.0). ARV7 expres- median 12 months vs. not reached), as well as radiographic pro- sion was detectable at a level higher than 2 SDs above the gression (Supplementary Fig. S4A; HR = 3.9; P = 0.011; median mean signal in healthy donors in 4 of 22 patients (18%) at 5 months vs. not reached). the pretreatment time point. In this setting, the presence of a Expression of the ARV7 mRNA splice variant has been high level of ARV7 in CTCs was predictive of shorter overall detected in patients with mCRPC, where it has been shown to survival (Fig. 4F) and radiographic progression-free survival predict resistance to abiraterone and enzalutamide (12–14). (Supplementary Fig. S4B), particularly at a threshold greater Applying the digital CTC assay to patients in this prospective than 14.7 transcripts per mL (see Methods). In contrast to study of first-line abiraterone, quantitative measurement of ARV7, the presence of TMPRSS2–ERG translocation in CTCs

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Digital Expression Signatures of Prostate CTCs RESEARCH ARTICLE

A B Cell imaging vs. CTCM score 10,000 mCRPC Treatment Abiraterone 1st line after ADT (N = 27) discontinuation 1,000 100 score 10 Digital CTCM score M Pretreatment CTC blood draw 1 enrichment CTC Cell imaging 0.1 R 2 = 0.01 (enumeration) P = 0.6 0.01 0.11 10 100 1,000 CTCs/7.5 mL blood

C CTCM score pretreatment (OS) D CTCM score pretreatment (R-PFS) 1.00 1.00 ++ ++ +++++ + 0.75 ++++ 0.75 ++ ++ P = 0.01 + 0.50 HR = 6.0 0.50

OS ++

+ R-PFS ++ ++ 0.25 0.25 P = 0.046 HR = 3.2 0.00 0.00 0612 18 24 0612 18 24 Time (months) Time (months)

CTCM score Number at risk CTCM score Number at risk ≤79.42 17 16 10 62 ≤79.42 17 12 721 >79.42 10 6310 >79.42 10 2000

HOXB13 (OS) ARV7 (OS) E F G HOXB13 vs. ARV7 1.00 +++++++ 1.00 + + +++ 1,000 + + ++++ + 0/0 + 2/2 0.75 0.75 +++ P = 0.004 0.50 0.50 100 + ++ OS OS HR = 11.8

0.25 + 0.25 P < 0.001 HR = 28.8 10 0.00 0.00 0612 18 24 0612 18 24 (transcripts/mL) 1 Time (months) Time (months) 0/11 4/9

HOXB13 Number at risk ARV7 Number at risk ARV7 0.1 ≤2.39 14 13 852 ≤14.73 20 16 830 >2.39 13 9520 >14.73 21000 0.1110 1001,000 HOXB13 (transcripts/mL)

Alive >12 mo Dead at 12 mo

Figure 4. A, Schema for prospective study of first-line abiraterone in patients with mCRPC, with pretreatment blood draw followed CTC assessments using digital CTCM score and immunofluorescence cell imaging for CTC enumeration. B, Graph of relationship between digital CTCM score and CTC enumeration based on cell imaging at the pretreatment time point. C and D, Kaplan–Meier curves for overall survival (OS) and radiographic progression-free survival (R-PFS) by CTCM score at the pretreatment time point. E and F, Kaplan–Meier curves for OS by HOXB13 and ARV7 CTC signal at the pretreatment time point. Five patients had pretreatment data available for HOXB13 but not for ARV7. G, Graph of relationship between HOXB13 and ARV7 CTC signal (transcripts/mL blood) for CTC samples at the pretreatment time point for patients for whom data were available for both HOXB13 and ARV7. Red squares represent patients who died within 12 months of treatment initiation, and blue circles represent those who were alive.

was not predictive of clinical outcome (Supplementary Figs. two markers in the 22 patients with mCRPC who had been S4C and S3D). tested for both (Fig. 4G). Of 6 patients who had early death To examine the predictive value of combining pretreat- on first-line abiraterone, all 6 were positive forHOXB13 ment detection of CTC-derived markers HOXB13 and ARV7 expression, whereas only 2 had an elevated level of ARV7 in identifying patients at high risk of early death (≤12 (Fig. 4G and Supplementary Fig. S4F). Six of 13 men (46%) months) following first-line abiraterone, we examined these with HOXB13-positive signal had early death, compared with

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0 of 14 patients (0%) without HOXB13 expression in CTCs early prostate cancer dissemination. Elevated expression of (Supplementary Fig. S4E; P = 0.006). Thus, although ARV7 several individual genes within the prostate CTC assay gene expression above the digital threshold of 14.7 transcripts panel was significantly associated with SVI FAT1( , FOLH1, per mL blood is highly specific for prediction of progres- KLK2, KLK3, and TMPRSS2) and lymph node involvement sion on first-line abiraterone,HOXB13 expression identifies (FAT1, FOLH1, KLK2, KLK3, HOXB13, and TMPRSS2; Sup- additional nonresponding patients, in whom suppression of plementary Fig. S5B and S5C). androgen production is insufficient to achieve a sustained We developed a weighted CTC score for early dissemina- tumor response. tion in localized prostate cancer (CTCL score) using differen- tial weighting of individual genes based on their predictive CTC Signatures in Patients with Localized value for SVI or lymph node involvement (Fig. 5B; Supple- Prostate Cancer mentary Fig. S5B). A preoperative CTCL score higher than Given the potential utility of the CTC score in guiding two SDs above the average healthy donor signal was strongly therapy for metastatic prostate cancer, we explored whether associated with pathologic SVI or lymph node involvement a similar analysis may also be informative in the setting of discovered at the time of radical prostatectomy (Fig. 5C; P < localized prostate cancer. Compared with metastatic pros- 0.001). This association remained significant even after per- tate cancer, fewer men with localized prostate cancer have forming a leave-one-out cross-validation with the complete detectable CTCs using traditional CTC imaging analyses, and radical prostatectomy dataset (Supplementary Fig. S6A; see the number of CTCs per mL of blood is considerably lower Methods). A leave-one-out cross-validated (LOOCV) CTCL (24–26, 34). We therefore tested whether a highly quantita- score in localized prostate cancer was not significantly cor- tive digital scoring platform might improve CTC detection in related with biopsy Gleason score (Supplementary Fig. S6B), early disease and potentially help distinguish between aggres- grade group (Supplementary Fig. S6C), or preoperative serum sive and indolent localized prostate cancer. PSA (Supplementary Fig. S6D). Comparison of the LOOCV

The CTCM score described above generates relatively low CTCL score and standard clinicopathologic risk groupings levels of signal in men with localized prostate cancer (Fig. showed that the CTCL score had superior predictive value 2A). We therefore applied a whole-transcriptome amplifica- in this cohort with respect to prediction of pathologic SVI tion (WTA) step prior to the ddPCR assay to amplify the or lymph node involvement (Fig. 5D–F). For patients with a

CTC transcript signal (Fig. 5A; see Methods). This WTA- high CTCL score, the positive predictive value (PPV) for SVI based droplet digital prostate assay was applied prospec- or lymph node invasion was 100% (3/3 patients), compared tively to a cohort of 34 men who had a diagnosis of clinically with a PPV of 33% (3/9) for patients with a high score in the localized prostate cancer and who were scheduled for radi- commonly used D’Amico clinical risk group (Fig. 5D and F; cal prostatectomy (Supplementary Table S4). Of these 34 ref. 18), and a PPV of 60% (3/5) in the UCSF CAPRA score patients, 13 (38%) had a preoperative prostate biopsy reveal- (Fig. 5E and F; ref. 21). The negative predictive value (NPV) ing Gleason score 6 (grade group 1) disease, 15 (44%) had was similar for all three measures (90% for CTCL score, 88% Gleason score 7 (grade group 2 or 3) disease, and 6 (18%) for D’Amico, and 90% for CAPRA; Fig. 5F). The use of com- had a Gleason score of 8 or higher (grade group 4 or 5). binations of the CTCL score together with either CAPRA or None of these patients had evidence of SVI or lymph node D’Amico risk groupings did not appreciably increase the PPV metastases on standard preoperative radiographic imag- or NPV for preoperative prediction of SVI or (21) involvement ing, thereby making them candidates for surgical resec- (Fig. 5F). Despite the small sample size, these observations tion (79.4% of patients had a pelvic MRI or abdomen and raise the possibility that digital CTC analyses may help pre- pelvis CT scan; Supplementary Table S4). However, follow- dict the presence or absence of early dissemination in patients ing radical prostatectomy, 6 patients (18%) were found on undergoing surgical resection for a presumed localized pros- pathologic examination of the resected surgical specimen tate cancer. to have evidence of SVI, pelvic lymph node involvement, or a combination of both features, signifying microscopic dissemination of cancer outside the prostate gland (Sup- DISCUSSION plementary Table S4). Notably, preoperative digital CTC By combining microfluidic enrichment of unfixed CTCs signal was highly associated with pathologic evidence of with digital quantitation of CTC-derived RNA, we describe a

Figure 5. A, Schema for patients with clinically localized prostate cancer treated with radical prostatectomy in this study. B, Equation for CTCL score, with weights for each gene based on the relative signal in localized patients with pathologic SVI or lymph node (LN) involvement, compared with those without microscopic cancer dissemination (see Methods). C, Table showing relationship between the preoperative CTCL score and microscopic SVI or pelvic LN involvement (“invasion”) identified at the time radical prostatectomy. “High” and “low” CTCL scores were determined on the basis of the presence of signal higher than 2 SDs above the average signal in healthy donor controls. D and E, Graphs of relationship between preoperative LOOCV CTCL score and D’Amico Risk Group or UCSF CAPRA score. Red dots represent patients who had microscopic SVI or pelvic LN involvement identified on pathologic examination of the radical prostatectomy specimen, whereas blue dots represent patients who did not have SVI or LN involvement. Perpendicular dashed line represents a threshold of 2 SDs above the average CTCL score signal in healthy donor controls. Numbers depict the number of data points (patients) in each sextant. F, Table showing positive predictive value (PPV) and negative predictive value (NPV) of D’Amico (high risk), CAPRA (high risk), CTCL score (high), and CTCL score/CAPRA combinations for prediction of microscopic SVI or LN involvement identified at radical prostatectomy.

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Digital Expression Signatures of Prostate CTCs RESEARCH ARTICLE

Localized prostate cancer Pathology and (n = 34) Radical prostatectomy follow-up

Whole Pretreatment CTC transcriptome CTCL score blood draw enrichment amplification

B 8 C CTCL score = ∑ (genei * weighti ) i = 1

ave (invasivei) Weight = i CTCL score ave (noninvasivei ) High (n = 3) Low (n = 31) Gene Weights AGR2 1.5 FAT1 4.8 + 33 FOLH1 8.2 P < 0.001 HOXB13 39.4 Invasion KLK2 796.9 − 028 KLK3 729.7 STEAP2 2.0 TMPRSS2 5.3

D CTCL score (LOOCV) vs. D’Amico risk group E CTCL score (LOOCV) vs. CAPRA score

High High 6 7 2 3 2 Intermediate 4 Intermediate

14 1 16 1 CAPRA score 2 Low

Low 10 0 0 12 0 0 246 0246

Log (CTCL score + 1) 10 Log10(CTCL score + 1) SVI(−) and LN(−) SVI(−) and LN(−) SVI(+) or LN(+) SVI(+) or LN(+)

F CTCL score (high) CTCL score (high) D’Amico (high) CAPRA (high) CTCL score (high) and CAPRA (high) or CAPRA (high)

PPV 33% (3/9) 60% (3/5) 100% (3/3) 100% (2/2) 67% (4/6)

NPV 88% (22/25) 90% (26/29) 90% (28/31) 88% (28/32) 93% (26/28)

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AR-targeted High CTC score M therapy resistant Metastatic CRPC: Digital CTC next-line therapy after ADT CTCs analysis AR-targeted Low CTC score WBCs M therapy sensitive

High risk of High CTCL score Localized prostate cancer: Digital CTC SVI or LN(+) risk stratification analysis prior to local therapy (after WTA) Low risk of Low CTC score L SVI or LN(+) RBCs

Figure 6. Schematic showing potential clinical applications of digital CTC analysis in metastatic and localized prostate cancer, including prediction of resistance to AR-targeted therapy in mCRPC (CTCM score), and risk of microscopic dissemination to seminal vesicles or lymph nodes in clinically localized prostate cancer (CTCL score). RBC, red blood cell.

highly sensitive and specific assay for noninvasive sampling rent cancer-specific mutations, which are relatively infrequent of prostate cancer. The digital RNA-based scoring overcomes in prostate cancer (35). several limitations of cell imaging–based CTC analyses, In addition to prostate lineage-based RNA markers, aber- including the requirement for calibration and thresholding rant AR mRNA splice variant and TMPRSS2–ERG transloca- of multiple immunofluorescence microscopy parameters and tion transcript expression provide a high degree of specificity manual verification of individual images. In addition, the for prostate cancer, and they also require the use of RNA high sensitivity and specificity of sequence-based approaches, measurements in blood-based analyses. In this context, the which are readily multiplexed to simultaneously interrogate microfluidic depletion of normal hematopoietic cells from multiple markers, provide greatly improved signal over tra- blood specimens is particularly effective in preserving RNA ditional cell imaging methods. We demonstrate potential integrity within CTCs, which are not subject to antibody applications of this digital CTC assay in the settings of both manipulation or fixation and thus provide excellent signal metastatic and clinically localized prostate cancer (Fig. 6). In for digital PCR quantitation. Along with microfluidic CTC a prospective study of men on first-line abiraterone therapy isolation, digital scoring of CTC signal for both prostate line- for mCRPC, quantitative digital CTC measurements of both age transcripts and prostate cancer–specific transcripts can be normal prostatic transcripts and aberrant RNA products readily automated for high-throughput analyses, making it a identify a patient subset that is poorly responsive to AR- practical tool for clinical applications. targeted therapy. In a second study of men undergoing radi- The recent development of multiple potent treatment cal prostatectomy for localized prostate cancer, digital CTC modalities for metastatic prostate cancer brings with it the analysis predicts for the presence of clinically significant need to identify predictive biomarkers of response (1). To cancer dissemination that is not detected by standard preop- date, the most significant markers have focused on the dem- erative clinical imaging and could affect the choice of curative onstration of continued activity of the androgen receptor, intervention. which is targeted by many therapies for mCPRC. Molecu- Conceptually, the application of a digital RNA-based PCR lar imaging–based strategies to measure androgen signaling output to microfluidic CTC-enriched cell populations pre- have been demonstrated in some cases, but the availability sents several important advantages. First, the use of puri- of blood-based sampling would greatly enhance the utility fied whole CTCs in the bloodstream as the source of RNA of such monitoring (36). We have previously reported that increases the likelihood that the measured signal is derived scoring of CTCs for expression of the androgen-driven pro- from invasive cancer cells, as opposed to normal tissues or tein PSA versus the androgen-repressed protein PSMA can indolent cancers. Second, the analysis of cancer cells within be translated into an “AR-on” versus “AR-off” CTC immuno- a background of normal blood cells enables the use of tissue fluorescence-based signature (9). In treatment-naïve patients, lineage-based RNA transcripts that are not unique to cancer, virtually all CTCs have an “AR-on” signal, which converts to thereby expanding the number of available biomarkers and “AR-off” following initiation of ADT. Patients with mCRPC, confirming the tissue of origin for these circulating cancer however, frequently show simultaneous expression of “AR- cells. Third, lineage RNA-based CTC measurements may be on” and “AR-off” protein signatures, consistent with aberrant applied to virtually all prostate cancers, without the need AR signaling. In this context, the predictive value of CTC- to develop individualized genotype assays based on primary derived HOXB13 mRNA is of particular interest. HOXB13 is tumor sequencing, nor do they rely on the presence of recur- a lineage-specific modulator of AR transcriptional activity,

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Digital Expression Signatures of Prostate CTCs RESEARCH ARTICLE which has been shown to interact with AR and reprogram the limited sampling of the prostate at the time of diagnostic AR cistrome during prostate tumorigenesis (37). HOXB13 is biopsy (22, 23). In the cohort described here, patients with normally repressed by AR signaling; hence, its abundance in high preoperative CTCL scores were subsequently found CTCs from men with mCRPC is consistent with aberrant AR at the time of radical prostatectomy to have a high rate of signaling. Of note, germline mutations in HOXB13 have been SVI or pelvic lymph node involvement. These findings were correlated with increased susceptibility to prostate cancer not predicted by histopathologic analysis of the diagnostic (38). Taken together, overexpression of HOXB13 within pros- biopsies, by preoperative serum PSA level, or by clinical or tate CTCs may identify cancers in which altered AR signaling radiographic staging. As expected, the frequency of micro- pathways contribute to disease progression, thereby lessen- scopic dissemination discovered at the time of surgery was ing the effectiveness of abiraterone and other AR-targeted low (6/34 cases; 18%), but these findings may have impor- therapies. tant clinical consequences, and all six cases were referred for ARV7 has recently emerged as a readily measurable bio- consideration of postoperative radiotherapy and/or ADT, marker for acquired androgen pathway independence, pre- thereby incurring the potential for additional treatment- dicting resistance to abiraterone or enzalutamide therapy related adverse events. Additional clinical follow-up of our (12, 13). Discordant results as to the predictive value of ARV7 cohort is necessary to determine whether the preopera- measurements most likely result from different CTC or exo- tive CTCL score correlates with biochemical recurrence and some-based detection assays (39), as well as their application other prostate cancer–specific outcomes. If confirmed in in patients at different stages of treatment and disease pro- larger studies, the high predictive value of the CTCL score gression. For instance, in large retrospective clinical trials, for microscopic dissemination of early prostate cancer may ARV7 was detectable in CTCs from only 3% of patients prior provide a biomarker to help identify high-risk patients who to second-line therapy using an immunofluorescence assay may benefit from alternative treatment approaches, includ- (13), and in 12.1% of patients using qRT-PCR (14). Although ing neoadjuvant preoperative systemic therapies, or radio- our prospective cohort was relatively small, the application therapy in combination with novel systemic therapies. In of a sensitive and quantitative digital CTC assay in patients addition, although this study involved single CTC measure- who are relatively early in their disease course provides a ments performed preoperatively and standardized against novel perspective on the significance ofARV7 positivity. separate control cohorts, serial longitudinal monitoring of

First, we note that detection of this splice variant in patients the CTCL score may ultimately allow individualization of with mCRPC in the first-line setting does not by itself indi- the baseline signal for each patient, with potential applica- cate resistance to abiraterone; however, the elevation of CTC tions in monitoring men with indolent prostate cancers ARV7 transcript levels above a specific threshold is highly undergoing active surveillance for early indication of disease predictive of adverse outcome. Single-cell RNA-seq has dem- progression. Thus, RNA-based digital CTC scoring provides onstrated considerable heterogeneity among AR splice vari- a highly sensitive and quantitative blood-based marker to ants even among CTCs from the same individual (11); hence, complement standard clinical parameters, with the goal of the quantitative scoring provided by digital PCR analysis optimizing treatment algorithms in both early and advanced may provide a robust and standardized platform. Second, prostate cancer. the observation that downstream indicators of altered AR signaling (e.g., HOXB13) are more commonly elevated than ARV7 and are more predictive of adverse outcome suggests METHODS that ARV7 is only one of a number of markers that predict reduced efficacy of AR-targeted therapies. Larger prospective Patients and Clinical Specimens clinical trials of both prostate lineage markers and ARV7 will All studies were conducted in accordance with Belmont Report be required to extend these findings and define the relative ethical guidelines. Patients with a diagnosis of prostate cancer utility of monitoring CTC-derived markers in guiding ther- provided informed written consent to one of two Institutional apy with abiraterone and other AR-targeted therapies. The Review Board–approved protocols, DF/HCC 05-300 or DF/HCC 13-209. A total of 88 patients donated 20 mL of blood for CTC recent application of combined therapies in the initial treat- analysis, including 46 patients with metastatic prostate cancer ment of high-risk metastatic prostate cancer, including the and 42 patients with localized prostate cancer (see Supplementary combination of docetaxel and ADT (40) and the combina- Tables S2–S4). Patients with mCRPC starting abiraterone included tion of abiraterone and ADT (41), raises the possibility that the first 27 evaluable subjects of an ongoing, single-arm, 40-patient, risk stratification may also enable individualized therapies in investigator-initiated pilot study evaluating CTCs in patients receiv- advanced disease. ing abiraterone at standard dosing (see Supplementary Table S3; Finally, using WTA to enhance signal, we tested the poten- ClinicalTrials.gov NCT01961843). Subjects were required to have tial application of digital CTC scoring in the evaluation mCRPC, rising PSA >2 ng/dL, good overall performance status, of clinically localized prostate cancer. In this context, the and adequate organ function. Subjects signed informed consent. primary challenge is accurate risk stratification to guide The study drug was supplied by Janssen LLC; all data collection and interpretation were performed by the authors. The complete the reduction in therapeutic interventions in cases at lower clinical and CTC evaluation from the study will be reported sepa- risk, while providing more aggressive treatment of high-risk rately upon completion of the study. Disease status and therapy disease. Standard risk stratification tools and nomograms, at the time of CTC collection for each of the metastatic patients based on clinical staging and prostate core biopsies, are often are provided in Supplementary Tables S2 and S3. For a subset of unreliable in predicting the microscopic extent of disease these patients, matched archival formalin-fixed, paraffin-embedded identified at the time of surgery, likely due in part to the (FFPE) primary tumor tissues were sectioned, macrodissected for

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>70% tumor content, and subjected to RNA extraction, prior to targeted amplification was performed using TaqMan PreAmp Master processing for ddPCR (see below). Mix (Invitrogen) prior to ddPCR using a separate set of nested prim-

For testing of the CTCL score, 34 patients with clinically localized ers (see below) to increase the sensitivity of the assay. To analyze CTCs prostate cancer who were scheduled to undergo radical prostatec- from patients with localized prostate cancer (for the CTCL score), WTA tomy donated 20 mL of blood prior to surgery. Detailed clinical and was performed to amplify the RNA prior to subjecting to ddPCR. pathologic characteristics for these patients with localized prostate cancer are provided in Supplementary Table S4. ddPCR Primers A list of potential gene candidates for the prostate CTC ddPCR CTC Isolation assay was generated using publicly available databases as well as CTCs were isolated from fresh whole blood donated by patients single-cell RNA-seq data (see Supplementary Table S1). A multi- or healthy donors following leukocyte depletion using the micro- step approach using qRT-PCR and ddPCR was developed to test fluidic CTC-iChip as described previously. To maximize recovery of the specificity of ddPCR primers and probes designed to detect intact CTCs with high-quality RNA, blood samples were processed these transcripts (Supplementary Fig. S1A). Candidate primers within 4 hours of being collected from the patient. The total time and probes were tested for signal in cancer cell cDNA and absence for CTC isolation after receipt of fresh blood samples in the labo- of signal in leukocyte cDNA using the ABI 7500 and Bio-Rad ratory was approximately 2.5 hours. Briefly, whole blood samples CFX96 Real-Time PCR Systems. One nanogram of total cDNA were spiked with biotinylated antibodies against CD45 (R&D Sys- was used per qRT-PCR reaction. Primer/probe combinations for tems, clone 2D1), CD66b (AbD Serotec, clone 80H3), and CD16 genes that showed signal in cell lines and absence of signal in (Janssen Diagnostics), followed by incubation with Dynabeads healthy donor leukocytes by qRT-PCR were further validated MyOne Streptavidin T1 (Invitrogen) to achieve magnetic labeling using ddPCR. Each primer/probe combination was tested using and depletion of white blood cells. After processing of whole blood cDNA prepared from CTC-iChip products of healthy donor males with the CTC-iChip and collecting the enriched CTC product on and patients with prostate cancer using the ddPCR platform, as ice, cells were centrifuged at 4,750 rpm and flash-frozen in liquid above (Bio-Rad). The sequences of the primers and probes used nitrogen in the presence of RNAlater (Ambion) to preserve RNA for each gene in the Prostate CTC ddPCR Assay are provided in integrity. Supplementary Table S5.

RNA Extractions, cDNA Synthesis, and WTA Immunofluorescence and Cell Imaging CTC samples were subjected to RNA extraction using the RNeasy Isolated CTCs were subjected to immunofluorescence staining Plus Micro Kit (Qiagen). FFPE primary prostate tumor tissues were using previously established protocols, with modifications. Briefly, subjected to RNA extraction using the Allprep DNA/RNA FFPE Kit the CTC-iChip product was fixed for 10 minutes in 1% formal- (Qiagen), using xylene deparaffinization and a 16-hour incubation dehyde/P188 Kolliphor and plated onto poly-l-lysine–coated glass in proteinase K solution at 56°C prior to RNA extraction. cDNA slides (Sigma Aldrich) using a Shandon Cytospin 4 and EZ Mega was prepared from purified RNA using SuperScript III First-Strand funnel (Thermo Fisher Scientific), centrifuging at 2,000 rpm orf 5 Synthesis System (Life Technologies). WTA was performed on RNA minutes. The cells were dried for 10 minutes and immunostained using the SMARTer Ultra Low Input RNA Kit, version 4 (Clontech with antibodies against CK8/18 (C11, mouse IgG1, Janssen) and Laboratory). CK19 (A53, mouse IgG2a, Janssen) conjugated to Alexa Fluor 488 (Invitrogen), PSA (D6B1, rabbit IgG, Cell Signaling Technology), Cell Culture and Cell Line Spiking Experiments PSMA (J591, mouse IgG, N.H. Bander) conjugated to Alexa Fluor LNCaP (2009), VCaP (2010), and 22Rv1 (2013) cells were 555 (Invitrogen), CD45 (HI30, mouse IgG1, BioLegend), and CD16 obtained from the ATCC in the years indicated and grown in the (3G8, mouse IgG1, BioLegend) and CD66b (G10FS, mouse IgG1, recommended medium. All cell lines were authenticated by short BioLegend) conjugated to Alexa Fluor 647 (Invitrogen), followed by tandem repeat profiling and tested negative forMycoplasma on a goat anti-rabbit secondary antibody conjugated to Alexa Fluor 549 yearly basis, most recently in August 2016 for experiments in this (Invitrogen) and DAPI. article. Cells were used in all experiments within 15 to 20 passages Stained slides were imaged using an automated multispectral from thawing. To test the limit of detection for the ddPCR assay, imaging microscope (PerkinElmer Vectra 2.0.8) at ×20 magnification cell spiking experiments were performed as follows. Single prostate using DAPI, FITC, Cy3, and Cy5 filters. Vectra and InForm software cancer cells were manually manipulated using 10-μm Eppendorf (PerkinElmer) were used for automated image capture and spectral TransferMan NK2 transfer tips into Kolliphor P188 buffer and unmixing into 5 channels. Human validation of candidate CTCs spiked under direct microscopic visualization (Nikon Eclipse Ti-U was performed using CellReview software (PerkinElmer), using a inverted microscope) into 4-mL aliquots of healthy donor male minimum signal threshold of 50, 50, and 15 for cytokeratin, PSA, and blood. The spiked samples were then processed using the CTC- PSMA markers, respectively. iChip as described above. Multiclass SVM Classifier ddPCR To generate training and validation sets for the multiclass SVM cDNA and primer/probe mixes were combined with ddPCR Super- classifier, 10 ng of LNCaP cell cDNA was loaded into each ddPCR mix for Probes (Bio-Rad) in a 96-well plate and loaded onto Bio-Rad’s reaction. By appropriately isolating each probe set combination into automated droplet generator. Droplets were subjected to thermal separate PCR reactions (individual reactions with probes for only one cycling using a modified 45-cycle PCR with a 70°C step-down in of the genes of interest, and reactions with probes for only two genes between the denaturation and annealing steps. Following thermal of interest to allow for the unambiguous identification of the result- cycling, droplets containing the transcript of interest were detected ant double-positive droplets), we could confidently manually curate via fluorescence with the QX200 Droplet Reader System (Bio-Rad). In the FAM/HEX values that corresponded to a given class of single- or general, ddPCR assays for CTCs isolated from patients with metastatic double-positive droplet. These data were manually classified using the prostate cancer were performed without a preamplification step, with FlowJo software package and then imported into MATLAB. A custom the exception of the TMPRSS2–ERG assay, for which a 14-cycle specific MATLAB script was used to generate and validate a multiclass SVM

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Digital Expression Signatures of Prostate CTCs RESEARCH ARTICLE classifier with 30% of the droplets partitioned prior to SVM train- the date of radiographic progression, death, or censor. Survival curves ing and allocated as the testing set. To best match new ddPCR data were generated using the Kaplan–Meier method and compared using derived from patient CTCs to the initial LNCaP results used to train the log-rank test. Two-sided P values <0.05 were considered statistically the SVM, a user is asked to manually confirm that the four single significant. Statistical analyses were performed using R, version 3.3.1. positive droplets for a given reaction are located within the appropri- ate area on the FAM/HEX plot. If the user determines that they are Disclosure of Potential Conflicts of Interest not, the user can translate the origin of the data via the MATLAB R.J. Lee reports receiving a commercial research grant from Jans- command line. Raw data files and MATLAB scripts with detailed com- sen LLC and is a consultant/advisory board member for the same. menting available upon request. D.T. Ting reports receiving a commercial research grant from Affy- metrix and has received speakers bureau honoraria from the same. CTCM Score S. Maheswaran has ownership interest in a patent on the CTC-iCHIP. To generate a weighted digital CTC score in metastatic prostate D.A. Haber has received a commercial research grant from Janssen, cancer, blood samples were obtained from 34 male healthy donors has ownership interest in pending patent applications, and is a con- and 12 patients with metastatic prostate cancer, processed using the sultant/advisory board member for Janssen. No potential conflicts of iChip, and analyzed using the multiplex ddPCR assay (see Results; interest were disclosed by the other authors. Fig. 2A; Supplementary Fig. S2). For each gene i in the 8-gene assay, the average number of positive droplets per sample in the 34 male Authors’ Contributions healthy donor samples (HDi) was compared with the average number Conception and design: D.T. Miyamoto, R.J. Lee, S. Javaid, D.M. Dahl, of positive droplets per sample in the 12 patients with metastatic M.R. Smith, S. Maheswaran, D.A. Haber MPi prostate cancer (MPi; Supplementary Fig. S2). The ratio Ri = HDi was Development of methodology: D.T. Miyamoto, M. Kalinich, T. Chen, calculated for each gene i. Using each ratio Ri as a weighting factor J.D. Milner, U. Ho, S. Javaid, T.T. Kwan, X. Hong, R. Kapur, S.L. Stott, for each gene i, the CTC score was then derived as follows: D.T. Ting, M. Toner, S. Maheswaran Acquisition of data (provided animals, acquired and managed n   patients, provided facilities, etc.): D.T. Miyamoto, R.J. Lee, J.A. LiCausi, CTCRM score =  ∑()ii*/D  1,000  i=1  Y. Zheng, J.D. Milner, E. Emmons, K. Broderick, E. Silva, S. Javaid, X. Hong, D.M. Dahl, F.J. McGovern, J.A. Efstathiou, M.R. Smith, L.V. Sequist, where i is each gene, n is the number of genes assayed, Ri is the C.-L. Wu weighting factor for each gene i, and Di is the number of positive Analysis and interpretation of data (e.g., statistical analysis, droplets for gene i for any given CTC sample (see Fig. 2B for full biostatistics, computational analysis): D.T. Miyamoto, R.J. Lee, equation used in this study). M. Kalinich, Y. Zheng, T. Chen, J.D. Milner, S. Javaid, J.A. Efstathiou, To determine the optimal division points within the CTC score and C.-L. Wu, S.L. Stott, A. Giobbie-Hurder, S. Maheswaran, D.A. Haber individual genes for overall survival and radiographic progression- Writing, review, and/or revision of the manuscript: D.T. Miyamoto, free survival within the abiraterone mCRPC cohort, the algorithm of R.J. Lee, T. Chen, J.D. Milner, T.T. Kwan, X. Hong, D.M. Dahl, Contal-O’Quigley was applied to the data using leave-one-out jack- J.A. Efstathiou, M.R. Smith, L.V. Sequist, C.-L. Wu, M. Toner, S. knife resampling. Each iteration of the algorithm produced an estimate Maheswaran, D.A. Haber of the “best” division point based on the data. The mode of the distribu- Administrative, technical, or material support (i.e., reporting or tion of “best” values was carried forward as the selected cut-off point for organizing data, constructing databases): D.T. Miyamoto, R.J. Lee, each individual gene. The advantage of using the algorithmic approach L.V. Sequist, D.T. Ting, M. Toner, S. Maheswaran, D.A. Haber is that it is objective and is designed to find the “best” division that the Study supervision: D.T. Miyamoto, R.J. Lee, D.M. Dahl, L.V. Sequist, data can provide, unlike splitting at the median or quartiles. M. Toner, S. Maheswaran, D.A. Haber Other (development of the technology and product for isolation CTCL Score of CTCs): R. Kapur All analyses were performed using R version 3.3.1, and the R scripts used are available upon request. Patient data were imported into the Acknowledgments R computing environment, and the CAPRA and D’Amico scores were We thank Janssen for clinical trial support, C. Gurski for clini- calculated as described previously. The CTCL score was generated by cal research support, and L. Libby and L. Nieman for technical dividing the average number of transcripts for a given gene in the inva- assistance. This work was supported by awards from the Prostate sive samples by the average number of transcripts for a given gene in Cancer Foundation (to D.T. Miyamoto, D.A. Haber, M.R. Smith, and the noninvasive sample to generate a gene weight. Next, each gene for R.J. Lee), Charles Evans Foundation (to D.A. Haber), Department a given sample was multiplied by that gene’s weight, and the resulting of Defense (W81XWH-12-1-0153; to D.T. Miyamoto), Howard weighted gene counts summed to provide a CTCL score (Fig. 5B). To Hughes Medical Institute (to D.A. Haber), National Institute of Bio- generate an estimation of this approach’s performance on new data, medical Imaging and Bioengineering (2U01EB012493; to M. Toner we performed LOOCV (42); all subsequent claims are based on these and D.A. Haber), National Institute of General Medical Sciences LOOCV results. To define a threshold value delineating “CTCL posi- (T32GM007753; to M. Kalinich), NIH, National Cancer Institute tive” from “CTCL negative,” we calculated the CTCL score (using the (2R01CA129933; to D.A. Haber), Burroughs Wellcome Fund (to D.T. entire radical prostatectomy patient data to generate gene weights) for Ting), and the MGH-Johnson & Johnson Center for Excellence in a panel of 30 age-matched male healthy donors. CTCL positivity was CTC Technologies (to M. Toner and S. Maheswaran). defined as the mean healthy donor CTCL score plus twice the SD of 2 the healthy donor CTCL score. A χ test was performed to determine The costs of publication of this article were defrayed in part by whether CTCL positivity was associated with invasion (Fig. 5C). the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 Statistical Analyses solely to indicate this fact. Overall survival was defined as the interval between the start of therapy and the date of death or censor. Radiographic progression-free Received December 14, 2016; revised November 22, 2017; accepted survival was defined as the interval between the start of therapy and December 27, 2017; published OnlineFirst January 4, 2018.

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Digital Expression Signatures of Prostate CTCs RESEARCH ARTICLE

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An RNA-Based Digital Circulating Tumor Cell Signature Is Predictive of Drug Response and Early Dissemination in Prostate Cancer

David T. Miyamoto, Richard J. Lee, Mark Kalinich, et al.

Cancer Discov Published OnlineFirst January 4, 2018.

Updated version Access the most recent version of this article at: doi:10.1158/2159-8290.CD-16-1406

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