Phenotypic Profiling of Circulating Tumor Cells in Metastatic Prostate

Jul 2, 2019 - CTCs were identified as DAPI+/CK+/CD45–. Microfluidic device CTC counts were divided into CTCs captured in low-EpCAM zones 1 and 2 ...
0 downloads 0 Views 3MB Size
Download PDF
Letter pubs.acs.org/ac

Cite This: Anal. Chem. XXXX, XXX, XXX−XXX

Phenotypic Profiling of Circulating Tumor Cells in Metastatic Prostate Cancer Patients Using Nanoparticle-Mediated Ranking Brenda J. Green,† Vivian Nguyen,‡ Eshetu Atenafu,⊥ Phillip Weeber,‡ Bill T. V. Duong,§ Punithan Thiagalingam,‡ Mahmoud Labib,‡ Reza M. Mohamadi,‡ Aaron R. Hansen,⊥ Anthony M. Joshua,*,⊥,# and Shana O. Kelley*,†,‡,§,∥

Downloaded via 94.231.219.122 on July 21, 2019 at 13:34:00 (UTC). See https://pubs.acs.org/sharingguidelines for options on how to legitimately share published articles.

†

Institute of Biomaterials and Biomedical Engineering, University of Toronto, 144 College Street, Toronto, Ontario M5S 3M2, Canada ‡ Department of Pharmaceutical Sciences, University of Toronto, Toronto M5S 3M2, Canada § Department of Chemistry, University of Toronto, Toronto, Ontario M5S 3H6, Canada ∥ Department of Biochemistry, Faculty of Medicine, University of Toronto, Toronto, Ontario M5S 1A8, Canada ⊥ Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario M5G 2C1, Canada # Kinghorn Cancer Centre, St. Vincent’s Hospital Sydney, Darlinghurst, New South Wales 2010, Australia S Supporting Information *

ABSTRACT: The analysis of circulating tumor cells (CTCs) provides a means to collect information about the evolving properties of a tumor during cancer progression and treatment. For patients with metastatic prostate cancer, noninvasive serial measurements of bloodborne cells may provide a means to tailor therapeutic decisions based on an individual patient’s response. Here, we used a high-sensitivity profiling approach to monitor CTCs in patients with metastatic castrate-resistant prostate cancer (mCRPC) undergoing treatment with abiraterone and enzalutamide, two drugs used to treat advanced prostate cancer. The capture and profiling approach uses antibody-functionalized magnetic nanoparticles to sort cells according to protein expression levels. CTCs are tagged with magnetic nanoparticles conjugated to an antibody specific for the epithelial cell adhesion molecule (EpCAM) and sorted into four zones of a microfluidic device based on EpCAM expression levels. Our approach was compared to the FDA-cleared CellSearch method, and we demonstrate significantly higher capture efficiency of low-EpCAM cells compared to the commercial method. The nanoparticle-based approach detected CTCs from 86% of patients at baseline, compared to CellSearch which only detected CTCs from 60% of patients. Patients were stratified as prostate specific antigen (PSA) progressive versus responsive based on clinically acceptable definitions, and it was observed that patients with a limited response to therapy had elevated levels of androgen receptor variant 7 (ARV7) and the mesenchymal marker, N-cadherin, expressed on their CTCs. In addition, these CTCs exhibited lower EpCAM expression. The results highlight features of CTCs associated with disease progression on abiraterone or enzalutamide, including mesenchymal phenotypes and increased expression levels of ARV7. The use of a high-sensitivity method to capture and profile CTCs provides more informative data concerning the phenotypic properties of these cells as patients undergo treatment relative to an FDA-cleared method.

C

stood,3−6 but the plasticity exhibited by cells undergoing EMT may be linked to metastatic potential. CTCs are obtained via a blood draw and can provide information relating to the molecular-level properties of a tumor without requiring invasive diagnostic techniques such as tissue biopsy.7−9 Characterizing these rare cells in serial measurements, an approach referred to as liquid biopsy,9 may therefore provide a noninvasive means to inform treatment options and

irculating tumor cells (CTCs) are released from a primary tumor into the bloodstream.1 These rare cells are then responsible for formation of the metastatic lesions that lead to high rates of mortality.2 CTCs can adopt resilient phenotypes in hostile nonadherent environments to avoid programmed cell death and immune attack.1 During cancer progression, CTCs initially released into the bloodstream may possess an epithelial phenotype and express surface proteins such as cytokeratin and epithelial cell adhesion molecule (EpCAM). As the primary tumor progresses, CTCs can lose their epithelial markers, gain mesenchymal markers (N-cadherin, vimentin, fibronectin), and undergo an epithelial-to-mesenchymal transition (EMT).3 EMT and its role in disease progression is not definitively under© XXXX American Chemical Society

Received: April 7, 2019 Accepted: July 2, 2019 Published: July 2, 2019 A

DOI: 10.1021/acs.analchem.9b01697 Anal. Chem. XXXX, XXX, XXX−XXX

Letter

Analytical Chemistry

Figure 1. High-efficiency capture of low-EpCAM CTCs from prostate cancer patients. (A,B) Schematic of patient sample collection and processing through the microfluidic device. CTCs are captured from metastatic castrate resistant prostate cancer (mCRPC) patients (n = 36) receiving enzalutamide or abiraterone. Briefly, whole blood is incubated with magnetic nanoparticles (MNPs) conjugated to EpCAM and introduced into the device at a flow rate of 600 μL/h in the presence of an external magnetic field. CTCs are trapped in different zones based on their expression level of EpCAM. (C) LnCaP and PC3 cells were profiled with the microfluidic device. (n = 292 LnCaP cells and n = 343 PC3 cells). High-EpCAM LnCaP cells are trapped primarily in zone 1, whereas low-EpCAM expressing PC3 cells are trapped in zones 3 and 4. (D) Capture efficiency of LnCaP and PC3 cells in the microfluidic device compared to CellSearch (n = 138 LnCaP cells and n = 96 PC3 cells). Cells were spiked in 1 mL of whole blood. Statistics are performed with two-tailed t test, *p < 0.05.

structures, including capture of epithelial and EMT-like CTCs by dual- targeting of both EpCAM/CD133 and EpCAM/stemcell marker 63B6, or single- targeting of podoplanin.16,51,52 The deformability of CTCs as they pass through microfluidic constrictions has also been used for the isolation of these cells17,18 and for the isolation of clusters using bifurcating traps under low shear stress conditions.19 In our laboratory, we developed a nanoparticle-mediated capture and profiling approach that allows CTCs to be isolated from blood on the basis of markers including surface proteins20 and mRNAs.21 This approach exhibits high levels of sensitivity

monitor patient responsiveness. However, the capture and analysis of CTCs is very challenging due to their low concentration in blood. Effective capture requires a high level of specificity and the ability to handle very low numbers of target cells from a billion-fold excess of normal cells. Microfluidic sorting technologies have the potential to improve detection of heterogeneous CTC populations. Devices featuring EpCAMfunctionalized-microposts and other nanomaterials,10−12 basement-membrane coated chips,13 discrete cell adhesion surfaces,14 and lateral displacement microarrays have been developed.15 Several recent studies have profiled heterogeneous CTC populations using antibody-functionalized microfluidic B

DOI: 10.1021/acs.analchem.9b01697 Anal. Chem. XXXX, XXX, XXX−XXX

Letter

Analytical Chemistry Table 1. Patient Demographicsa

and can report on low levels of CTCs in patient samples, and the phenotypic and genotypic properties of these rare cells. The analysis of CTCs in prostate cancer (PCa) patients is an important capability that may lead to new approaches for treatment monitoring.8,22−26 PCa CTCs with an EMT phenotype have been identified in various studies, and the transition between epithelial-like and mesenchymal-like states has been linked to aggressive metastatic behavior.27−31 CellSearch is the only FDA-cleared CTC assay presently and defines favorable or unfavorable CTC counts as 50% decline from baseline measured twice 3 to 4 weeks apart. PSA progression is defined as the first PSA rise that is ≥25% and ≥2 ng/mL above the nadir, confirmed 3 or more weeks later. If there is no initial decline from baseline, PSA progression is defined as ≥25% and ≥2 ng/mL after 12 weeks.

and to the number of EpCAM molecules on the cell surface. Cells with higher EpCAM expression experience a higher magnetic force and are trapped in early zones, while cells with lower EpCAM experience a lower magnetic force and are trapped in later zones. This allows for the spatial sorting of cells on the basis of EpCAM expression, which is crucial for monitoring CTCs as they progress through EMT.34,42

To verify the performance of this approach, the capture and profiling of two prostate cancer cells lines, LnCaP and PC3, were pursued. LnCaP cells have a high level of EpCAM protein expression, while PC3 cells have a lower level.43 The level of expression for these cell lines was reflected in the capture profile observed, with LnCaP cells trapped in the earlier zones of the device and PC3 cells trapped in the later zones of the device D

DOI: 10.1021/acs.analchem.9b01697 Anal. Chem. XXXX, XXX, XXX−XXX

Letter

Analytical Chemistry

Figure 3. mCRPC CTCs exhibit a low-EpCAM phenotype. CTCs were profiled with the microfluidic device (CTCs/mL) and separated into (A) highEpCAM (zone 1 and zone 2) and (B) low-EpCAM (zone 3 and zone 4) counts. (C) CellSearch CTC counts (CTCs/mL). Patients were profiled at 0 weeks and 9−22 weeks on-treatment. The dotted line separates PSA responsive vs progressive patients (refer to definition in the Materials and Methods). CTC counts were obtained from 36 mCRPC patients receiving abiraterone or enzalutamide. CTCs were identified as DAPI+/CK+/CD45−. Each dot represents a patient CTC count. Box plots represent standard error of the mean. The central square represents the mean, and the line represents the median.

(Figure 1C). Despite the difference in capture profiles and EpCAM expression levels, the overall capture efficiency for both cell lines was high (∼90%) and within error (Figure 1D). The capture efficiency and sensitivity of the nanoparticlemediated approach was compared to that achieved with the CellSearch technology (Figure 1D). While the capture efficiency of the LnCaP cells was only slightly lower using CellSearch versus the nanoparticle-based method, a marked decrease in capture efficiency was observed for the PC3 cells. This trend indicates that CTC recovery using CellSearch is sensitive to EpCAM levels. It is noteworthy that the ∼35% of PC3 cells captured using CellSearch likely correspond to the ∼30% of cells captured in zones 1 and 2 of the microfluidic device, indicating that the low-EpCAM cells in zones 3 and 4 are those not detectable using CellSearch. Profiling CTCs for Patients with mCRPC. To test this approach on clinical specimens, CTCs were tracked from 36 mCRPC patients over a median treatment time of 13 weeks (Table 1). Primary treatment for the patients studied included prostatectomy (39%), radiation therapy (53%), brachytherapy (6%), or focal therapy (3%). All patients received prior androgen therapy, including Luteinizing Hormone Releasing Hormone (LHRH) agonists, antiandrogens, steroid, or immune therapy (Table S1). Patients did not receive prior treatment of abiraterone, enzalutamide, nor docetaxel. At the onset of the

study, patients exhibited metastatic disease in the bone (50%) or lymph nodes (22%) or both (17%) (Tables S2 and S3). CTCs isolated from mCRPC patients were stratified as highEpCAM (zone 1 and zone 2) and low-EpCAM (zone 3 and zone 4) (Figure 1B). Post-capture, CTCs were identified using immunostaining with anti-cytokeratin (Ck), anti-N-cadherin (NCad), anti-AR, anti-ARV7, and anti-CD45 fluorescently tagged antibodies in separate microfluidic devices. mCRPC CTCs were primarily (88%) trapped in low-EpCAM zones 3 and 4 of the microfluidic device (Figure 2 and Figure 3). The capture profile corresponds with zone profiles of tumorigenic PC3 cells (Figure 1C, Figure S9). The microfluidic device detected CTCs from 86% of patients at baseline (week 0) and 77% of patients undergoing treatment (9−22 weeks). In comparison, CellSearch only detected CTCs from 60% of patients at baseline and in 18% of patients during treatment. Patients were stratified as PSA responsive or progressive based on the Prostate Cancer Clinical Trials Working Group criteria (PCWG3),32 (Materials and Methods, Figures S10 and S11). The dynamic change of CTC counts over disease progression is associated with a significant prognostic effect and previously correlated with PSA response.35,29,44 In our study, we observed a detectable increase in low-EpCAM CTCs in progressive patients between the baseline measurement and treatment time point (6 ± 2 and 11 ± 3 CTCs/mL, respectively; Figure 3B). The CellSearch analysis conducted with these same samples did not E

DOI: 10.1021/acs.analchem.9b01697 Anal. Chem. XXXX, XXX, XXX−XXX

Letter

Analytical Chemistry

Figure 4. Low-EpCAM CTCs exhibit increased ARV7 levels and reduced epithelial properties. (A) Representative immunofluorescent images obtained from patient CTCs isolated from the four zones of the microfluidic device. CTCs are identified as DAPI+/CK+/ARV7+/CD45− and obtained with a 50× objective (CD45 image is not shown in the panel). (B,C) Relative fluorescent intensity of androgen receptor variant 7 (ARV7) and cytokeratin CTCs captured in the four zones of the microfluidic device (n = 76 CTCs, n = 104 CTCs, respectively). Fluorescent intensities are obtained using immunofluorescence image analysis. (D) Percentage of androgen receptor variant 7 (ARV7) CTCs: cytokeratin positive CTCs for responsive versus progressive patients. (E) Percentage of N-cadherin positive CTCs: cytokeratin positive CTCs for responsive versus progressive patients. Zone 3 and zone 4 counts were considered for CTC ratio analysis. CTCs are captured with EpCAM-MNPs in separate microfluidic devices: in the first device, CTCs are identified as DAPI+/CK+/CD45−; in the second device, CTCs are identified as DAPI+/CK+/ARV7+/CD45−; and in the third device, CTCs are identified as DAPI+/NCad+/CD45−. CTC counts are obtained at 0- and 9−22-weeks on-treatment. Statistics were performed with the Mann−Whitney test. *p < 0.05 is significant.

Low-EpCAM CTCs Exhibit Increased ARV7 Levels and Reduced Epithelial Properties Associated with Progressive Patients. To complement the EpCAM-based profiling described above, we used our microfluidic approach to study other phenotypic markers. The presence of the ARV7 androgen

exhibit the same trend, and the overall counts were very low (≤1 CTCs/mL; Figure 3C, Figure S12). These results are consistent with prior demonstration that CellSearch does not effectively detect mesenchymal CTCs with an enhanced capacity for metastasis.25 F

DOI: 10.1021/acs.analchem.9b01697 Anal. Chem. XXXX, XXX, XXX−XXX

Letter

Analytical Chemistry

to treatment and shift toward lower EpCAM levels during patient treatment with abiraterone or enzalutamide. Progressive patients had increased percentages of N-cadherin-positive and ARV7-positive CTCs compared to responsive patients. Overall, this study identifies CTC biomarkers associated with diseaseprogressive patients and suggests that mesenchymal properties and increased ARV7 expression levels may be linked to sustained CTC presence in circulation. The ability to profile low-EpCAM CTC subtypes provides an important capability for monitoring patients with advanced cancers.

receptor splice variant was monitored as a function of the microfluidic capture zone for patient CTCs as shown in Figure 4. While levels of cytokeratin, an epithelial marker, decreased in later zones, the levels of ARV7 increased (Figure 4A,B). Interestingly, this observation indicates that less epithelial CTCs may harbor truncated AR. The percentage of CTCs captured in low-EpCAM zones significantly increased from 57% at baseline to 70% during treatment (Figure S4). The median zone values for baseline and 9−22 weeks of treatment are 3.3 CTCs/mL and 3.5 CTCs/mL, respectively, indicating a shift toward reduced EpCAM phenotype over the treatment period. Expression of EMTrelated genes in CTCs may be associated with mCRPC, such as reduced cytokeratin levels and increased N-cadherin expression.29 Using the microfluidic device, we have previously demonstrated that CTCs with low epithelial phenotypes exhibited invasive features, such as enhanced collagen uptake and folate-induced NAD(P)H metabolism.41 In addition, we previously observed that CTCs in vivo were trapped in lowEpCAM zones, and mice receiving docetaxel chemotherapy exhibited a phenotypic shift in CTC profiles toward lowerEpCAM zones after 6 weeks of treatment.45,46 Thus, the shift toward lower-EpCAM zones in mCRPC patients may suggest increased invasiveness of the residual tumor cells. The proportion of ARV7-positive and N-cadherin-positive CTCs were assessed in progressive patients relative to responsive patients (Figure 4D,E). At baseline, the percentage of ARV7-positive CTCs relative to cytokeratin-positive CTCs was 52% and 26% for progressive vs responsive patients, respectively. In comparison, the baseline percentage of Ncadherin-positive CTCs relative to cytokeratin-positive CTCs was 213% and 66% for progressive vs responsive patients, respectively. AR-positive CTCs did not vary between progressive and responsive patients (80% and 79%, respectively) (Figure S7). Progressive patients exhibit a higher incidence of bone metastases relative to responsive patients prior to the onset of abiraterone or enzalutamide treatment (67% vs 55%, respectively, Figure S1). The increased incidence of bone metastases prior to the administrative of abiraterone/enzalutamide may correlate with higher proportions of ARV7-positive and N-cadherin-positive CTCs detected in these patients. Increased incidence of ARV7 are considered an adaptive response to androgen deprivation therapy.47 The two most accepted clinical assays for evaluating the presence of ARV7 in CTCs include the label-free immunofluorescent assay from Epic Sciences47 and the mRNA-based AdnaTest platform.48,49 Elevated ARV7 expression levels have been associated with resistance to treatment with enzalutamide or abiraterone, lower PSA response rates, and reduced overall survival.50 Thus, tracking heterogeneous populations of CTCs at different stages of disease progression may significantly influence clinical decisions.

■

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.analchem.9b01697. Materials and Methods section along with supporting data and tables (PDF)

■

AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. *E-mail: [email protected]. ORCID

Mahmoud Labib: 0000-0003-4565-2056 Shana O. Kelley: 0000-0003-3360-5359 Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS We thank the ECTI facility at the University of Toronto for their clean room facilities. We also thank the Province of Ontario (Ontario Research Fund-Research Excellence), the Natural Sciences and Engineering Council, and the Canadian Institutes of Health Research for grants that supported this work.

■

REFERENCES

(1) Pawelek, J. M.; Chakraborty, A. K. Nat. Rev. Cancer 2008, 8 (5), 377−86. (2) Racila, E.; Euhus, D.; Weiss, A. J.; Rao, C.; McConnell, J.; Terstappen, L. W.; Uhr, J. W. Proc. Natl. Acad. Sci. U. S. A. 1998, 95 (8), 4589−94. (3) Mehlen, P.; Puisieux, A. Nat. Rev. Cancer 2006, 6 (6), 449−58. (4) Yu, M.; Bardia, A.; Wittner, B. S.; Stott, S. L.; Smas, M. E.; Ting, D. T.; Isakoff, S. J.; Ciciliano, J. C.; Wells, M. N.; Shah, A. M.; Concannon, K. F.; Donaldson, M. C.; Sequist, L. V.; Brachtel, E.; Sgroi, D.; Baselga, J.; Ramaswamy, S.; Toner, M.; Haber, D. A.; Maheswaran, S. Science 2013, 339 (6119), 580−4. (5) Jin, X.; Mu, P. Breast Cancer: Basic Clin. Res. 2015, 9s1, 23−34. (6) Green, B. J.; Panagiotakopoulou, M.; Pramotton, F. M.; Stefopoulos, G.; Kelley, S. O.; Poulikakos, D.; Ferrari, A. Nano Lett. 2018, 18, 2140. (7) Green, B. J.; Saberi Safaei, T.; Mepham, A.; Labib, M.; Mohamadi, R. M.; Kelley, S. O. Angew. Chem., Int. Ed. 2016, 55 (4), 1252−65. (8) Poudineh, M.; Sargent, E. H.; Pantel, K.; Kelley, S. O. Nat. Biomed. Eng. 2018, 2 (2), 72−84. (9) Alix-Panabieres, C.; Pantel, K. Nat. Rev. Cancer 2014, 14 (9), 623− 31. (10) Nagrath, S.; Sequist, L. V.; Maheswaran, S.; Bell, D. W.; Irimia, D.; Ulkus, L.; Smith, M. R.; Kwak, E. L.; Digumarthy, S.; Muzikansky, A.; Ryan, P.; Balis, U. J.; Tompkins, R. G.; Haber, D. A.; Toner, M. Nature 2007, 450 (7173), 1235−9. (11) Stott, S. L.; Hsu, C. H.; Tsukrov, D. I.; Yu, M.; Miyamoto, D. T.; Waltman, B. A.; Rothenberg, S. M.; Shah, A. M.; Smas, M. E.; Korir, G.

■

CONCLUSION We profiled CTCs from 36 mCRPC patients receiving abiraterone or enzalutamide over a median treatment time of 13 weeks. CTCs were captured in a microfluidic device which trapped low-EpCAM cells with high efficiency and sorted these cells into zones based on the expression level of EpCAM. Overall, the microfluidic device was capable of tracking lowEpCAM CTCs over the treatment period, which were largely missed by CellSearch. CTCs correlate with the responsiveness G

DOI: 10.1021/acs.analchem.9b01697 Anal. Chem. XXXX, XXX, XXX−XXX

Letter

Analytical Chemistry K.; Floyd, F. P., Jr.; Gilman, A. J.; Lord, J. B.; Winokur, D.; Springer, S.; Irimia, D.; Nagrath, S.; Sequist, L. V.; Lee, R. J.; Isselbacher, K. J.; Maheswaran, S.; Haber, D. A.; Toner, M. Proc. Natl. Acad. Sci. U. S. A. 2010, 107 (43), 18392−7. (12) Yoon, H. J.; Kim, T. H.; Zhang, Z.; Azizi, E.; Pham, T. M.; Paoletti, C.; Lin, J.; Ramnath, N.; Wicha, M. S.; Hayes, D. F.; Simeone, D. M.; Nagrath, S. Nat. Nanotechnol. 2013, 8 (10), 735−41. (13) Zhang, Y.; Wu, M.; Han, X.; Wang, P.; Qin, L. Angew. Chem., Int. Ed. 2015, 54 (37), 10838−42. (14) Witek, M. A.; Aufforth, R. D.; Wang, H.; Kamande, J. W.; Jackson, J. M.; Pullagurla, S. R.; Hupert, M. L.; Usary, J.; Wysham, W. Z.; Hilliard, D.; Montgomery, S.; Bae-Jump, V.; Carey, L. A.; Gehrig, P. A.; Milowsky, M. I.; Perou, C. M.; Soper, J. T.; Whang, Y. E.; Yeh, J. J.; Martin, G.; Soper, S. A. npj Precis. Oncol. 2017, 1, 24. (15) Liu, Z.; Lee, Y.; Jang, J.; Li, Y.; Han, X.; Yokoi, K.; Ferrari, M.; Zhou, L.; Qin, L. Sci. Rep. 2015, 5, 14272. (16) Yoneda, K.; Kuwata, T.; Chikaishi, Y.; Mori, M.; Kanayama, M.; Takenaka, M.; Oka, S.; Hirai, A.; Imanishi, N.; Kuroda, K.; Ichiki, Y.; Ohnaga, T.; Tanaka, F. Cancer Sci. 2019, 110 (2), 726−733. (17) Byun, S.; Son, S.; Amodei, D.; Cermak, N.; Shaw, J.; Kang, J. H.; Hecht, V. C.; Winslow, M. M.; Jacks, T.; Mallick, P.; Manalis, S. R. Proc. Natl. Acad. Sci. U. S. A. 2013, 110 (19), 7580−5. (18) Shaw Bagnall, J.; Byun, S.; Begum, S.; Miyamoto, D. T.; Hecht, V. C.; Maheswaran, S.; Stott, S. L.; Toner, M.; Hynes, R. O.; Manalis, S. R. Sci. Rep. 2015, 5, 18542. (19) Sarioglu, A. F.; Aceto, N.; Kojic, N.; Donaldson, M. C.; Zeinali, M.; Hamza, B.; Engstrom, A.; Zhu, H.; Sundaresan, T. K.; Miyamoto, D. T.; Luo, X.; Bardia, A.; Wittner, B. S.; Ramaswamy, S.; Shioda, T.; Ting, D. T.; Stott, S. L.; Kapur, R.; Maheswaran, S.; Haber, D. A.; Toner, M. Nat. Methods 2015, 12 (7), 685−91. (20) Poudineh, M.; Aldridge, P. M.; Ahmed, S.; Green, B. J.; Kermanshah, L.; Nguyen, V.; Tu, C.; Mohamadi, R. M.; Nam, R. K.; Hansen, A.; Sridhar, S. S.; Finelli, A.; Fleshner, N. E.; Joshua, A. M.; Sargent, E. H.; Kelley, S. O. Nat. Nanotechnol. 2017, 12 (3), 274−281. (21) Labib, M.; Mohamadi, R. M.; Poudineh, M.; Ahmed, S. U.; Ivanov, I.; Huang, C. L.; Moosavi, M.; Sargent, E. H.; Kelley, S. O. Nat. Chem. 2018, 10 (5), 489−495. (22) Pantel, K.; Brakenhoff, R. H.; Brandt, B. Nat. Rev. Cancer 2008, 8 (5), 329−40. (23) Ligthart, S. T.; Coumans, F. A. W.; Attard, G.; Mulick Cassidy, A.; de Bono, J. S.; Terstappen, L. W. M. M. PLoS One 2011, 6 (11), e27419. (24) Watson, P. A.; Arora, V. K.; Sawyers, C. L. Nat. Rev. Cancer 2015, 15 (12), 701−11. (25) Lowes, L. E.; Goodale, D.; Xia, Y.; Postenka, C.; Piaseczny, M. M.; Paczkowski, F.; Allan, A. L. Oncotarget 2016, 7 (46), 76125−76139. (26) Antonarakis, E. S.; Lu, C.; Luber, B.; Wang, H.; Chen, Y.; Zhu, Y.; Silberstein, J. L.; Taylor, M. N.; Maughan, B. L.; Denmeade, S. R.; Pienta, K. J.; Paller, C. J.; Carducci, M. A.; Eisenberger, M. A.; Luo, J. J. Clin. Oncol. 2017, 35 (19), 2149−2156. (27) Satelli, A.; Batth, I.; Brownlee, Z.; Mitra, A.; Zhou, S.; Noh, H.; Rojas, C. R.; Li, H.; Meng, Q. H.; Li, S. Oncotarget 2017, 8 (30), 49329−49337. (28) Armstrong, A. J.; Marengo, M. S.; Oltean, S.; Kemeny, G.; Bitting, R. L.; Turnbull, J. D.; Herold, C. I.; Marcom, P. K.; George, D. J.; Garcia-Blanco, M. A. Mol. Cancer Res. 2011, 9 (8), 997−1007. (29) Chen, C. L.; Mahalingam, D.; Osmulski, P.; Jadhav, R. R.; Wang, C. M.; Leach, R. J.; Chang, T. C.; Weitman, S. D.; Kumar, A. P.; Sun, L.; Gaczynska, M. E.; Thompson, I. M.; Huang, T. H. Prostate 2013, 73 (8), 813−26. (30) Mitra, A.; Mishra, L.; Li, S. Oncotarget 2015, 6 (13), 10697− 10711. (31) Chang, L.; Graham, P. H.; Hao, J.; Ni, J.; Bucci, J.; Cozzi, P. J.; Kearsley, J. H.; Li, Y. Cell Death Dis. 2013, 4, e875. (32) Scher, H. I.; Morris, M. J.; Stadler, W. M.; Higano, C.; Basch, E.; Fizazi, K.; Antonarakis, E. S.; Beer, T. M.; Carducci, M. A.; Chi, K. N.; Corn, P. G.; de Bono, J. S.; Dreicer, R.; George, D. J.; Heath, E. I.; Hussain, M.; Kelly, W. K.; Liu, G.; Logothetis, C.; Nanus, D.; Stein, M. N.; Rathkopf, D. E.; Slovin, S. F.; Ryan, C. J.; Sartor, O.; Small, E. J.;

Smith, M. R.; Sternberg, C. N.; Taplin, M. E.; Wilding, G.; Nelson, P. S.; Schwartz, L. H.; Halabi, S.; Kantoff, P. W.; Armstrong, A. J. J. Clin. Oncol. 2016, 34 (12), 1402−18. (33) Tucci, M.; Scagliotti, G. V.; Vignani, F. Future Oncol. 2015, 11 (1), 91−106. (34) Liu, W.; Yin, B.; Wang, X.; Yu, P.; Duan, X.; Liu, C.; Wang, B.; Tao, Z. Oncol. Lett. 2017, 14 (2), 1223−1232. (35) De Laere, B.; Oeyen, S.; Van Oyen, P.; Ghysel, C.; Ampe, J.; Ost, P.; Demey, W.; Hoekx, L.; Schrijvers, D.; Brouwers, B.; Lybaert, W.; Everaert, E.; Van Kerckhove, P.; De Maeseneer, D.; Strijbos, M.; Bols, A.; Fransis, K.; Beije, N.; de Kruijff, I.; van Dam, V.; Brouwer, A.; van Dam, P. J.; Van den Eynden, G.; Rutten, A.; Sleijfer, S.; Vandebroek, J.; Van Laere, S.; Dirix, L. Prostate 2018, 78 (6), 435−445. (36) Scher, H. I.; Fizazi, K.; Saad, F.; Taplin, M. E.; Sternberg, C. N.; Miller, K.; de Wit, R.; Mulders, P.; Chi, K. N.; Shore, N. D.; Armstrong, A. J.; Flaig, T. W.; Flechon, A.; Mainwaring, P.; Fleming, M.; Hainsworth, J. D.; Hirmand, M.; Selby, B.; Seely, L.; de Bono, J. S. N. Engl. J. Med. 2012, 367 (13), 1187−97. (37) Loriot, Y.; Bianchini, D.; Ileana, E.; Sandhu, S.; Patrikidou, A.; Pezaro, C.; Albiges, L.; Attard, G.; Fizazi, K.; De Bono, J. S.; Massard, C. Ann. Oncol. 2013, 24 (7), 1807−12. (38) Brand, L. J.; Dehm, S. M. Curr. Drug Targets 2013, 14 (4), 441− 449. (39) van der Steen, T.; Tindall, D. J.; Huang, H. Int. J. Mol. Sci. 2013, 14 (7), 14833−59. (40) Mohamadi, R. M.; Besant, J. D.; Mepham, A.; Green, B.; Mahmoudian, L.; Gibbs, T.; Ivanov, I.; Malvea, A.; Stojcic, J.; Allan, A. L.; Lowes, L. E.; Sargent, E. H.; Nam, R. K.; Kelley, S. O. Angew. Chem., Int. Ed. 2015, 54 (1), 139−43. (41) Green, B. J.; Kermanshah, L.; Labib, M.; Ahmed, S. U.; Silva, P. N.; Mahmoudian, L.; Chang, I. H.; Mohamadi, R. M.; Rocheleau, J. V.; Kelley, S. O. ACS Appl. Mater. Interfaces 2017, 9 (24), 20435−20443. (42) Poudineh, M.; Labib, M.; Ahmed, S.; Nguyen, L. N.; Kermanshah, L.; Mohamadi, R. M.; Sargent, E. H.; Kelley, S. O. Angew. Chem., Int. Ed. 2017, 56 (1), 163−168. (43) Xu, Y.; Zhao, H.; Hou, J. Tumor Biol. 2014, 35 (7), 6695−700. (44) Wilbaux, M.; Tod, M.; De Bono, J.; Lorente, D.; Mateo, J.; Freyer, G.; You, B.; Henin, E. CPT: Pharmacometrics Syst. Pharmacol. 2015, 4 (5), 277−85. (45) Kermanshah, L.; Poudineh, M.; Ahmed, S.; Nguyen, L. N. M.; Srikant, S.; Makonnen, R.; Pena Cantu, F.; Corrigan, M.; Kelley, S. O. Lab Chip 2018, 18 (14), 2055−2064. (46) Muhanna, N.; Mepham, A.; Mohamadi, R. M.; Chan, H.; Khan, T.; Akens, M.; Besant, J. D.; Irish, J.; Kelley, S. O. Nanomedicine 2015, 11 (7), 1613−20. (47) Scher, H. I.; Lu, D.; Schreiber, N. A.; Louw, J.; Graf, R. P.; Vargas, H. A.; Johnson, A.; Jendrisak, A.; Bambury, R.; Danila, D.; McLaughlin, B.; Wahl, J.; Greene, S. B.; Heller, G.; Marrinucci, D.; Fleisher, M.; Dittamore, R. JAMA Oncol 2016, 2 (11), 1441−1449. (48) Antonarakis, E. S.; Lu, C.; Wang, H.; Luber, B.; Nakazawa, M.; Roeser, J. C.; Chen, Y.; Mohammad, T. A.; Chen, Y.; Fedor, H. L.; Lotan, T. L.; Zheng, Q.; De Marzo, A. M.; Isaacs, J. T.; Isaacs, W. B.; Nadal, R.; Paller, C. J.; Denmeade, S. R.; Carducci, M. A.; Eisenberger, M. A.; Luo, J. N. Engl. J. Med. 2014, 371 (11), 1028−38. (49) Antonarakis, E. S.; Lu, C.; Luber, B.; Wang, H.; Chen, Y.; Nakazawa, M.; Nadal, R.; Paller, C. J.; Denmeade, S. R.; Carducci, M. A.; Eisenberger, M. A.; Luo, J. JAMA Oncol 2015, 1 (5), 582−91. (50) Crespo, M.; van Dalum, G.; Ferraldeschi, R.; Zafeiriou, Z.; Sideris, S.; Lorente, D.; Bianchini, D.; Rodrigues, D. N.; Riisnaes, R.; Miranda, S.; Figueiredo, I.; Flohr, P.; Nowakowska, K.; de Bono, J. S.; Terstappen, L. W.; Attard, G. Br. J. Cancer 2015, 112 (7), 1166−74. (51) Zeinali, M.; Murlidhar, V.; Fouladdel, S.; Shao, S.; Zhao, L.; Cameron, H.; Bankhead, A., III; Shi, J.; Cuneo, K. C.; Sahai, V.; Azizi, E.; Wicha, M. S.; Hafner, M.; Simeone, D. M.; Nagrath, S. Adv. Biosystems 2018, 2 (12), 1800228. (52) Kang, Y.-T.; Kim, Y. J.; Bu, J.; Chen, S.; Cho, Y.-H.; Lee, H. M.; Ryu, C. J.; Lim, Y.; Han, S.-W. Sens. Actuators, B 2018, 260, 320−330.

H

DOI: 10.1021/acs.analchem.9b01697 Anal. Chem. XXXX, XXX, XXX−XXX