Quantitative Analysis of Circulating Tumor Cells Using RNA-Based Digital Scoring.

Circulating tumor cells (CTCs) provide valuable information about the molecular evolution of cancers, as they may initially respond and ultimately progress on therapy. As intact tumor cells isolated from the bloodstream, CTCs also enable assessment of heterogeneous subpopulations, and their analysis may include DNA, RNA, and protein biomarkers. New microfluidic cell isolation strategies greatly facilitate the challenge of enriching viable tumor cells from the billions of hematopoietic cells within a standard blood specimen. While counting and characterization of enriched CTCs have primarily relied on immunostaining for tumor cell-specific antigens, new RNA-based analytic platforms are providing new insight into the identity of CTCs and providing new tools for clinical applications. Single-cell RNA sequencing of CTCs reveals a high degree of heterogeneity among cancer cells from a single individual, while new digital RNA-based amplification platforms may now allow high-sensitivity and high-throughput quantitative scoring of CTCs for clinical applications. Here, we focus on transcriptomic analysis of CTCs and its relevance in understanding metastatic cancer progression and in developing diagnostic assays to monitor cancer.

An RNA-based signature enables high specificity detection of circulating tumor cells in hepatocellular carcinoma.

Circulating tumor cells (CTCs) are shed into the bloodstream by invasive cancers, but the difficulty inherent in identifying these rare cells by microscopy has precluded their routine use in monitoring or screening for cancer. We recently described a high-throughput microfluidic CTC-iChip, which efficiently depletes hematopoietic cells from blood specimens and enriches for CTCs with well-preserved RNA. Application of RNA-based digital PCR to detect CTC-derived signatures may thus enable highly accurate tissue lineage-based cancer detection in blood specimens. As proof of principle, we examined hepatocellular carcinoma (HCC), a cancer that is derived from liver cells bearing a unique gene expression profile. After identifying a digital signature of 10 liver-specific transcripts, we used a cross-validated logistic regression model to identify the presence of HCC-derived CTCs in nine of 16 (56%) untreated patients with HCC versus one of 31 (3%) patients with nonmalignant liver disease at risk for developing HCC (P < 0.0001). Positive CTC scores declined in treated patients: Nine of 32 (28%) patients receiving therapy and only one of 15 (7%) patients who had undergone curative-intent ablation, surgery, or liver transplantation were positive. RNA-based digital CTC scoring was not correlated with the standard HCC serum protein marker alpha fetoprotein (P = 0.57). Modeling the sequential use of these two orthogonal markers for liver cancer screening in patients with high-risk cirrhosis generates positive and negative predictive values of 80% and 86%, respectively. Thus, digital RNA quantitation constitutes a sensitive and specific CTC readout, enabling high-throughput clinical applications, such as noninvasive screening for HCC in populations where viral hepatitis and cirrhosis are prevalent.

Preexisting TP53-Variant Clonal Hematopoiesis and Risk of Secondary Myeloid Neoplasms in Patients With High-grade Ovarian Cancer Treated With Rucaparib.

IMPORTANCE: A total of 1% to 3% of patients treated with a poly(adenosine diphosphate-ribose) polymerase inhibitor for high-grade ovarian cancer (HGOC) develop therapy-related myeloid neoplasms (t-MNs), which are rare but often fatal conditions. Although the cause of these t-MNs is unknown, clonal hematopoiesis of indeterminate potential (CHIP) variants can increase the risk of primary myeloid malignant neoplasms and are more frequent among patients with solid tumors. OBJECTIVES: To examine whether preexisting CHIP variants are associated with the development of t-MNs after rucaparib treatment and how these CHIP variants are affected by treatment. DESIGN, SETTING, AND PARTICIPANTS: This retrospective genetic association study used peripheral blood cell (PBC) samples collected before rucaparib treatment from patients in the multicenter, single-arm ARIEL2 (Study of Rucaparib in Patients With Platinum-Sensitive, Relapsed, High-Grade Epithelial Ovarian, Fallopian Tube, or Primary Peritoneal Cancer) (n = 491; between October 30, 2013, and August 9, 2016) and the multicenter, placebo-controlled, double-blind ARIEL3 (Study of Rucaparib as Switch Maintenance Following Platinum-Based Chemotherapy in Patients With Platinum-Sensitive, High-Grade Serous or Endometrioid Epithelial Ovarian, Primary Peritoneal or Fallopian Tube Cancer) (n = 561; between April 7, 2014, and July 19, 2016), which tested rucaparib as HGOC therapy in the treatment and maintenance settings, respectively. The follow-up data cutoff date was September 1, 2019. Of 1052 patients in ARIEL2 and ARIEL3, PBC samples from 20 patients who developed t-MNs (cases) and 44 randomly selected patients who did not (controls) were analyzed for the presence of CHIP variants using targeted next-generation sequencing. Additional longitudinal analysis was performed on available ARIEL2 samples collected during treatment and at the end of treatment. MAIN OUTCOMES AND MEASURES: Enrichment analysis of preexisting variants in 10 predefined CHIP-associated genes in cases relative to controls; association with clinical correlates. RESULTS: Among 1052 patients (mean [SE] age, 61.7 [0.3] years) enrolled and dosed in ARIEL2 and ARIEL3, 22 (2.1%) developed t-MNs. The t-MNs were associated with longer overall exposure to prior platinum therapies (13.2 vs 9.0 months in ARIEL2, P = .04; 12.4 vs 9.6 months in ARIEL3, P = .003). The presence of homologous recombination repair gene variants in the tumor, either germline or somatic, was associated with increased prevalence of t-MNs (15 [4.1%] of 369 patients with HGOC associated with an HRR gene variant vs 7 [1.0%] of 683 patients with wild-type HGOC, P = .002). The prevalence of preexisting CHIP variants in TP53 but not other CHIP-associated genes at a variant allele frequency of 1% or greater was significantly higher in PBCs from cases vs controls (9 [45.0%] of 20 cases vs 6 [13.6%] of 44 controls, P = .009). TP53 CHIP was associated with longer prior exposure to platinum (mean 14.0 months of 15 TP53 CHIP cases vs 11.1 months of 49 non-TP53 CHIP cases; P = .02). Longitudinal analysis showed that preexisting TP53 CHIP variants expanded in patients who developed t-MNs. CONCLUSIONS AND RELEVANCE: The findings of this genetic association study suggest that preexisting TP53 CHIP variants may be associated with t-MNs after rucaparib treatment.

Molecular and clinical determinants of response and resistance to rucaparib for recurrent ovarian cancer treatment in ARIEL2 (Parts 1 and 2).

ARIEL2 (NCT01891344) is a single-arm, open-label phase 2 study of the PARP inhibitor (PARPi) rucaparib in relapsed high-grade ovarian carcinoma. In this post hoc exploratory biomarker analysis of pre- and post-platinum ARIEL2 samples, RAD51C and RAD51D mutations and high-level BRCA1 promoter methylation predict response to rucaparib, similar to BRCA1/BRCA2 mutations. BRCA1 methylation loss may be a major cross-resistance mechanism to platinum and PARPi. Genomic scars associated with homologous recombination deficiency are irreversible, persisting even as platinum resistance develops, and therefore are predictive of rucaparib response only in platinum-sensitive disease. The RAS, AKT, and cell cycle pathways may be additional modulators of PARPi sensitivity.

A Digital RNA Signature of Circulating Tumor Cells Predicting Early Therapeutic Response in Localized and Metastatic Breast Cancer.

The multiplicity of new therapies for breast cancer presents a challenge for treatment selection. We describe a 17-gene digital signature of breast circulating tumor cell (CTC)-derived transcripts enriched from blood, enabling high-sensitivity early monitoring of response. In a prospective cohort of localized breast cancer, an elevated CTC score after three cycles of neoadjuvant therapy is associated with residual disease at surgery (P = 0.047). In a second prospective cohort with metastatic breast cancer, baseline CTC score correlates with overall survival (P = 0.02), as does persistent CTC signal after 4 weeks of treatment (P = 0.01). In the subset with estrogen receptor (ER)-positive disease, failure to suppress ER signaling within CTCs after 3 weeks of endocrine therapy predicts early progression (P = 0.008). Drug-refractory ER signaling within CTCs overlaps partially with presence of ESR1 mutations, pointing to diverse mechanisms of acquired endocrine drug resistance. Thus, CTC-derived digital RNA signatures enable noninvasive pharmacodynamic measurements to inform therapy in breast cancer.Significance: Digital analysis of RNA from CTCs interrogates treatment responses of both localized and metastatic breast cancer. Quantifying CTC-derived ER signaling during treatment identifies patients failing to respond to ER suppression despite having functional ESR1. Thus, noninvasive scoring of CTC-RNA signatures may help guide therapeutic choices in localized and advanced breast cancer. Cancer Discov; 8(10); 1286-99. ©2018 AACR. This article is highlighted in the In This Issue feature, p. 1195.