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March 2018 CANCER DISCOVERY | 269
IN THE SPOTLIGHT
Digital Circulating Tumor Cell Analyses for Prostate Cancer Precision Oncology Ellen Heitzer 1 , 2 , 3 and Michael R. Speicher 1 , 2
1 Institute of Human Genetics, Diagnostic and Research Center for Molecu-lar BioMedicine, Medical University of Graz, Graz, Austria. 2 BioTechMed-Graz, Graz, Austria . 3 Christian Doppler Laboratory for Liquid Biopsies for Early Detection of Cancer, Graz, Austria . Corresponding Author: Michael R. Speicher , Medical University of Graz, Neue Stiftingtalstr. 6, Graz 8010, Austria. Phone: 4331-6385-73832; Fax: 4331-6385-79621; E-mail: [email protected] doi: 10.1158/2159-8290.CD-18-0075 ©2018 American Association for Cancer Research.
summary: In this issue of Cancer Discovery , Miyamoto and colleagues adapted their microfl uidic CTC-iChip isolation platform with a digital RNA-PCR readout for eight prostate-specifi c transcripts and two assays for the androgen receptor mRNA splice variant ARV7 and the TMPRSS2–ERG translocation transcript. In patients with metastatic castrate-resistant prostate cancer at initiating abiraterone therapy in a fi rst-line setting, the result-ing RNA-based digital circulating tumor cell signatures identifi ed patients with a shorter overall survival, and in patients with clinically localized disease, the signatures identifi ed those with seminal vesicle invasion and pelvic lymph node involvement. Cancer Discov; 8(3); 269–71. ©2018 AACR.
See related article by Miyamoto et al., p. 288 (7) .
Precision medicine attempts to understand disease at a deeper level with the aim of improving the ability to stratify patients by risk and to develop more targeted therapies. In oncology, molecular analyses of tumor material, which are often done by genetic analyses, are essential to realize preci-sion medicine. Further aims of precision oncology include the longitudinal tracking of tumors to measure response to applied interventions and to identify biomarkers and mecha-nisms of drug resistance ( 1 ).
In men, the most common malignancy is prostate cancer, which represents a major cause of cancer-related deaths. For the management of these patients, there are two scenarios that urgently need reliable prognostic information and bio-markers for realizing precision oncology. The fi rst scenario includes patients with metastatic castrate-resistant prostate cancer (mCRPC). Novel agents targeting the androgen recep-tor (AR) pathway, such as abiraterone or enzalutamide, have drastically changed outcome by slowing disease progression and improving survival ( 2 ). However, development of resist-ance is inevitable and means to predict progression-free sur-vival are currently lacking. The propensity of metastatic prostate cancer to spread to the bone hampers options to acquire tissue for repeated genetic analyses. The second sce-nario includes patients with localized disease for whom the diagnosis usually depends on systematic prostate biopsy by transperineal or transrectal access routes to obtain up to 12 tissue samples, which is associated with side effects such as bleeding, infections, or acute urinary retention. The selection of the primary treatment option, that is, expectant manage-ment, surgery, or radiation, represents a challenge ( 2 ). Hence,
both scenarios raise the question whether noninvasive means can be used to assess disease status and to predict treatment effi cacy.
To this end, “liquid biopsies,” tumor-derived components detectable in the peripheral blood of patients, that is, circu-lating tumor cells (CTC), circulating tumor DNA (ctDNA), or extracellular vesicles, are increasingly being used for clin-ical applications, such as early cancer detection, disease staging, monitoring for recurrence, prognostication, and selection of therapy ( 3 ). In the fi eld of urologic oncology, CTCs have been widely studied, and quantifi cation of CTCs, that is, establishing the number of CTCs in the peripheral blood, correlates with disease outcome ( 4 ). However, detailed molecular analyses of CTCs may provide much more infor-mation than a simple enumeration. For example, they pro-vide unique opportunities to study AR transcript variants, such as ARV7 , a truncated splice variant with no ligand-binding domain, which has recently been associated with a higher likelihood of primary resistance to androgen signal-ing inhibitors ( 5 ). Furthermore, single-cell RNA sequencing of prostate CTCs demonstrated substantial heterogeneity of AR splice variants ( 6 ).
In this issue of Cancer Discovery , Miyamoto and colleagues developed their CTC-based pool of technologies further to study CTCs as prognostic biomarkers in patients with pros-tate cancer ( 7 ). Because CTCs are rare in the peripheral blood and frequently account for merely one in a billion nucleated cells ( 8 ), a key step for molecular CTC analyses is enrichment and isolation of these cells. To this end, Miyamoto and col-leagues employed their microfl uidic (CTC-iChip) technology to deplete hematopoietic cells and to enrich CTCs ( Fig. 1 ). The CTC enrichment was followed by RNA-based digital droplet PCR (ddPCR) and a digital RNA-based scoring sys-tem, which the same group developed earlier for the detection of CTCs in patients with hepatocellular carcinoma ( 9 ). In the fi rst step, they curated prostate tissue–specifi c transcripts not detectable in normal blood cells. This resulted in a set of eight genes suitable for developing an RNA-based signa-ture, including four androgen-responsive transcripts [ KLK3 (PSA), KLK2 , TMPRSS2 , and AGR2 ], two androgen-repressed
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transcripts [FOLH1 (PSMA) and HOXB13], and two andro-gen-independent transcripts (FAT1 and STEAP2).
These eight genes were then applied in two multiplex assays with four genes in each reaction, each gene having a different relative ratio of the two fluorochromes FAM and HEX for unique identification (Fig. 1). The droplets were classified with a newly developed multiclass support vector
machine based on their FAM–HEX ratios. Spike-in experi-ments with cells from the prostate cancer cell line LNCaP suggested that a single tumor cell among millions of normal mononucleated blood cells might be detectable with this assay, as it generated enough positive droplets. As expected, the number of positive droplets increased with the number of LNCaP cells spiked into blood. In addition, ddPCR assays were added for two prostate lineage-based transcripts, that is, the TMPRSS2–ERG fusion transcript, present in approxi-mately 50% of prostate cancers, and the ARV7 mRNA splice variant, an established marker of resistance to AR-targeted therapies.
Comparing the proportions of the signal-to-noise ratios of the eight genes between 12 patients with mCRPC and age-matched controls allowed establishment of a digital “CTCM Score.” Whereas 11 of 12 (92%) patients with metastatic pros-tate cancer had a positive CTCM score, none of the healthy male blood donors (n = 34) reached the cutoff. The CTCM score was not correlated with serum PSA, confirming earlier observations.
The CTCM score was then applied to blood collected at initiating abiraterone therapy in a first-line setting from 27 patients with metastatic disease. Abiraterone prolongs the mean overall survival (OS) by impeding androgen bio-synthesis as a potent CYP17 inhibitor (2). However, the mechanisms underlying resistance to abiraterone remain largely unknown and biomarkers to predict who will benefit most from this treatment are lacking. Hence, Miyamoto and colleagues tested whether their CTCM score and the ARV7 and TMPRSS2–ERG assays applied to microfluidocally enriched CTCs may serve as predictive biomarkers. With a median follow-up time of 13 months, an increased CTCM score was found to predict worse OS to treatment with abi-raterone. Interestingly, expression of the AR-regulated gene HOXB13 was most significantly associated with poor OS. The homeobox transcription factor gene HOXB13 belongs to a superfamily of genes considered critical to animal embryonic development, and the G84E allele in HOXB13 has been shown to predispose to hereditary prostate cancer (2). As HOXB13 overexpression has been described in androgen-independent tumors, HOXB13 expression in CTCs may indi-cate aberrant AR signaling in mCRPC. Furthermore, the ARV7 assay was also predictive for shorter OS, whereas the TMPRSS2–ERG assay was not, confirming that this fusion is a relatively early event in prostate tumorigenesis and not related to disease course.
A particular challenge for liquid biopsies are localized dis-eases, for which an abundance of liquid biopsy components in peripheral blood is unlikely and approaches suitable in metastatic disease are not applicable. Indeed, localized pros-tate cancer can have a very different prognosis so that its management could greatly benefit from biomarkers reliably indicating the efficacy and safety of local treatment. To this end, Miyamoto and colleagues tested whether their quantita-tive digital scoring platform might improve CTC detection in 34 patients with clinically localized disease. However, due to low levels of transcripts in this cohort, a whole-transcriptome amplification was introduced prior to the ddPCR to enhance the signal (Fig. 1). Using the same eight genes with a dif-ferent weighting of transcripts resulted in a weighted score
Figure 1. A novel sensitive strategy to analyze CTCs in men with pros-tate cancer is based on two technologies: first, microfluidic cell enrich-ment (CTC-iChip), and second, RNA-based digital droplet-PCR, including evaluation using sophisticated bioinformatics tools. The CTC-iChip depletes hematopoietic cells from blood samples, resulting in a relatively enriched CTC population. After RNA extraction and preparation of cDNA, RNA-based ddPCR assays for eight prostate-specific transcripts, which are not expressed in normal hematopoietic cells, are classified with a multiclass support vector machine. For each gene, a weight was generated on the basis of their expression, and CTCM and CTCL scores were calculated for patients with metastatic and localized diseases, respectively. For patients with metastatic disease, two additional assays for the AR mRNA splice variant ARV7 and the TMPRSS2–ERG transloca-tion transcript expression were developed. In patients with mCRPC and at initiating abiraterone therapy in a first line setting, both the CTCM score and the ARV7 assay were predictive for shorter overall survival, whereas the TMPRSS2–ERG assay was not. In patients with clinically localized disease, the CTCL score was predictive for seminal vesicle invasion and pelvic lymph node involvement.
CTC-iChip
Blood
RNA extraction from CTCs and preparation of cDNA
RNA-based ddPCR foreight prostate-specific genes
TMPRSS2–ERGassay
Not predictiveof clinical outcome
Predictive forshorter overall survival
ARV7assay
CTCMscore
CTCLscore
Multiclass support vectormachine classifier
Patients with metastatic disease (n = 27)at abiraterone therapy (1st line)
Patients withclnically localized disease (n = 34)
Predictive for seminal invasionand pelvic lymph node involvement
In cases with localized tumorsWhole-transcriptome amplification
RBC
RBC, red blood cells WBC, white blood cells
WBC
CTC, circulating tumor cells
CTC
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March 2018 CANCER DISCOVERY | 271
for localized disease (CTCL score). This CTCL score applied preoperatively was strongly associated with seminal vesicle invasion and pelvic lymph node involvement, indicating early prostate cancer dissemination.
The work by Miyamoto and colleagues significantly extends options of CTC analyses and offers solutions to eminent problems in the management of patients with prostate cancer. Furthermore, the intriguing data of HOXB13 expression illustrate that digital CTC signatures may also provide insight into the biology of cancer cell dissemination. The LNCaP cell spike-in experiments suggest that transcripts from a single cell may be detectable, but the exact specificity and sensitivity of the CTC scores will have to be determined in larger clinical trials. A particular challenge will be whether this approach may allow distinguishing between localized low-grade prostate cancers, which are often harmless, and high-grade prostate cancers, which usually require treatment. Moreover, due to the low case numbers in this study, the value of the digital CTC signatures will have to be confirmed in larger studies, ideally in prospective multicenter clinical trials. The success of such larger studies will depend on the availability of the CTC-iChip, which is not offered on a com-mercial basis and which is available only in the laboratory of the authors. CTCs have evolved to be the preferred liquid biopsy component for the analysis of AR splice variants such as ARV7. However, somatic copy-number alterations, gene fusions, and point mutations can also be determined by ctDNA analyses (10), which do not require sophisticated equipment such as the CTC-iChip. It will be interesting to see which liquid biopsy approach will eventually be most broadly used in clinical applications, in particular for the detection of minimal residual disease. In summary, there is no doubt that liquid biopsies will evolve to be an indispensable tool in precision oncology, and this study is a big step forward in improving management for the most frequent tumor in men, that is, prostate cancer.
Disclosure of Potential Conflicts of InterestNo potential conflicts of interest were disclosed.
AcknowledgmentsThe work in our laboratory is supported by CANCER-ID, a pro-
ject funded by the Innovative Medicines Joint Undertaking (IMI JU), by Servier, the Austrian National Bank (ÖNB, grant# 16917), the Austrian Science Fund (FWF, grant# P28949-B28), by the Bio-TechMed-Graz flagship project “EPIAge,” and by the Christian Dop-pler Research Fund for Liquid Biopsies for Early Detection of Cancer.
Published online March 2, 2018.
RefeRenCes 1. Kumar-Sinha C, Chinnaiyan AM. Precision oncology in the age of
integrative genomics. Nat Biotechnol 2018;36:46–60. 2. Attard G, Parker C, Eeles RA, Schroder F, Tomlins SA, Tannock I,
et al. Prostate cancer. Lancet 2016;387:70–82. 3. Wan JC, Massie C, Garcia-Corbacho J, Mouliere F, Brenton JD, Caldas
C, et al. Liquid biopsies come of age: towards implementation of cir-culating tumour DNA. Nat Rev Cancer 2017;17:223–38.
4. Scher HI, Jia X, de Bono JS, Fleisher M, Pienta KJ, Raghavan D, et al. Circulating tumour cells as prognostic markers in progressive, cas-tration-resistant prostate cancer: a reanalysis of IMMC38 trial data. Lancet Oncol 2009;10:233–9.
5. Antonarakis ES, Lu C, Wang H, Luber B, Nakazawa M, Roeser JC, et al. AR-V7 and resistance to enzalutamide and abiraterone in pros-tate cancer. N Engl J Med 2014;371:1028–38.
6. Miyamoto DT, Zheng Y, Wittner BS, Lee RJ, Zhu H, Broderick KT, et al. RNA-Seq of single prostate CTCs implicates noncanonical Wnt signaling in antiandrogen resistance. Science 2015;349:1351–6.
7. Miyamoto DT, Lee RJ, Kalinich M, LiCausi JA, Zheng Y, Chen T, et al. An RNA-based digital circulating tumor cell signature is predictive of drug response and early dissemination in prostate cancer. Cancer Discov 2018;8:288–303.
8. Alix-Panabieres C, Pantel K. Clinical applications of circulating tumor cells and circulating tumor DNA as liquid biopsy. Cancer Discov 2016;6:479–91.
9. Kalinich M, Bhan I, Kwan TT, Miyamoto DT, Javaid S, LiCausi JA, et al. An RNA-based signature enables high specificity detection of circulating tumor cells in hepatocellular carcinoma. Proc Natl Acad Sci U S A 2017;114:1123–8.
10. Ulz P, Belic J, Graf R, Auer M, Lafer I, Fischereder K, et al. Whole-genome plasma sequencing reveals focal amplifications as a driving force in metastatic prostate cancer. Nat Commun 2016;7:12008.
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