Pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) is strongly associated with favorable outcome. We examined the utility of serial circulating tumor DNA (ctDNA) testing for predicting pCR and risk of metastatic recurrence. Cell-free DNA (cfDNA) was isolated from 291 plasma samples of 84 high-risk early breast cancer patients treated in the neoadjuvant I-SPY 2 TRIAL with standard NAC alone or combined with MK-2206 (AKT inhibitor) treatment. Blood was collected at pretreatment (T0), 3 weeks after initiation of paclitaxel (T1), between paclitaxel and anthracycline regimens (T2), or prior to surgery (T3). A personalized ctDNA test was designed to detect up to 16 patient-specific mutations (from whole-exome sequencing of pretreatment tumor) in cfDNA by ultra-deep sequencing. The median follow-up time for survival analysis was 4.8 years. At T0, 61 of 84 (73%) patients were ctDNA positive, which decreased over time (T1: 35%; T2: 14%; and T3: 9%). Patients who remained ctDNA positive at T1 were significantly more likely to have residual disease after NAC (83% non-pCR) compared with those who cleared ctDNA (52% non-pCR; odds ratio 4.33, P = 0.012). After NAC, all patients who achieved pCR were ctDNA negative (n = 17, 100%). For those who did not achieve pCR (n = 43), ctDNA-positive patients (14%) had a significantly increased risk of metastatic recurrence [hazard ratio (HR) 10.4; 95% confidence interval (CI) 2.3-46.6]; interestingly, patients who did not achieve pCR but were ctDNA negative (86%) had excellent outcome, similar to those who achieved pCR (HR 1.4; 95% CI 0.15-13.5). Lack of ctDNA clearance was a significant predictor of poor response and metastatic recurrence, while clearance was associated with improved survival even in patients who did not achieve pCR. Personalized monitoring of ctDNA during NAC of high-risk early breast cancer may aid in real-time assessment of treatment response and help fine-tune pCR as a surrogate endpoint of survival.
Background: Despite advances in early detection and therapies, cancer is still one of the most common causes of death worldwide. Since each tumor is unique, there is a need to implement personalized care and develop robust tools for monitoring treatment response to assess drug efficacy and prevent disease relapse.Main body: Recent developments in liquid biopsies have enabled real-time noninvasive monitoring of tumor burden through the detection of molecules shed by tumors in the blood. These molecules include circulating tumor nucleic acids (ctNAs), comprising cell-free DNA or RNA molecules passively and/or actively released from tumor cells. Often highlighted for their diagnostic, predictive, and prognostic potential, these biomarkers possess valuable information about tumor characteristics and evolution. While circulating tumor DNA (ctDNA) has been in the spotlight for the last decade, less is known about circulating tumor RNA (ctRNA). There are unanswered questions about why some tumors shed high amounts of ctNAs while others have undetectable levels. Also, there are gaps in our understanding of associations between tumor evolution and ctNA characteristics and shedding kinetics. In this review, we summarize current knowledge about ctNA biology and release mechanisms and put this information into the context of tumor evolution and clinical utility.Conclusions: A deeper understanding of the biology of ctDNA and ctRNA may inform the use of liquid biopsies in personalized medicine to improve cancer patient outcomes.
Circulating tumor DNA (ctDNA) analysis may improve early-stage breast cancer treatment via non-invasive tumor burden assessment. To investigate subtype-specific differences in the clinical significance and biology of ctDNA shedding, we perform serial personalized ctDNA analysis in hormone receptor (HR)-positive/HER2-negative breast cancer and triple-negative breast cancer (TNBC) patients receiving neoadjuvant chemotherapy (NAC) in the I-SPY2 trial. ctDNA positivity rates before, during, and after NAC are higher in TNBC than in HR-positive/HER2-negative breast cancer patients. Early clearance of ctDNA 3 weeks after treatment initiation predicts a favorable response to NAC in TNBC only. Whereas ctDNA positivity associates with reduced distant recurrence-free survival in both subtypes. Conversely, ctDNA negativity after NAC correlates with improved outcomes, even in patients with extensive residual cancer. Pretreatment tumor mRNA profiling reveals associations between ctDNA shedding and cell cycle and immune-associated signaling. On the basis of these findings, the I-SPY2 trial will prospectively test ctDNA for utility in redirecting therapy to improve response and prognosis.
Circulating biomarkers are urgently needed in hepatocellular carcinoma (HCC). The aims of this study were to determine the feasibility of detecting and isolating circulating tumor cells (CTCs) in HCC patients using enrichment for epithelial cell adhesion molecule (EpCAM) expression, to examine their prognostic value, and to explore CTC-based DNA sequencing in metastatic HCC patients compared to a control cohort with non-malignant liver diseases (NMLD). Whole blood was obtained from patients with metastatic HCC or NMLD. CTCs were enumerated by CellSearch then purified by immunomagnetic EpCAM enrichment and fluorescence-activated cell sorting. Targeted ion semiconductor sequencing was performed on whole genome-amplified DNA from CTCs, tumor specimens, and peripheral blood mononuclear cells (PBMC) when available. Twenty HCC and 10 NMLD patients enrolled. CTCs ≥ 2/7.5 mL were detected in 7/20 (35%, 95% confidence interval: 12%, 60%) HCC and 0/9 eligible NMLD (p = 0.04). CTCs ≥ 1/7.5 mL was associated with alpha-fetoprotein ≥ 400 ng/mL (p = 0.008) and vascular invasion (p = 0.009). Sequencing of CTC DNA identified characteristic HCC mutations. The proportion with ≥ 100x coverage depth was lower in CTCs (43%) than tumor or PBMC (87%) (p < 0.025). Low frequency variants were higher in CTCs (p < 0.001). CTCs are detectable by EpCAM enrichment in metastatic HCC, without confounding false positive background from NMLD. CTC detection was associated with poor prognostic factors. Sequencing of CTC DNA identified known HCC mutations but more low-frequency variants and lower coverage depth than FFPE or PBMC.
The number of circulating tumor cells (CTCs) in metastatic prostate cancer patients provides prognostic and predictive information. However, it is the molecular characterization of CTCs that offers insight into the biology of these tumor cells in the context of personalized treatment. We developed a novel approach to isolate CTCs away from hematopoietic cells with high purity, enabling genomic analysis of these cells. The isolation protocol involves immunomagnetic enrichment followed by fluorescence activated cell sorting (IE/FACS). To evaluate the feasibility of isolation of CTCs by IE/FACS and downstream genomic profiling, we conducted a pilot study in patients with metastatic castration resistant prostate cancer (CRPC). Twenty (20) sequential CRPC patients were assayed using CellSearch™. Twelve (12) patients positive for CTCs were subjected to immunomagnetic enrichment and fluorescence activated cell sorting (IE/FACS) to isolate CTCs. Genomic DNA of CTCs was subjected to whole genome amplification (WGA) followed by gene copy number analysis via array comparative genomic hybridization (aCGH). CTCs from nine (9) patients successfully profiled were observed to have multiple copy number aberrations including those previously reported in primary prostate tumors such as gains in 8q and losses in 8p. High-level copy number gains at the androgen receptor (AR) locus were observed in 7 (78%) cases. Comparison of genomic profiles between CTCs and archival primary tumors from the same patients revealed common lineage. However, high-level copy number gains in the AR locus were observed in CTCs, but not in the matched archival primary tumors. We developed a new approach to isolate prostate CTCs without significant leukocyte admixture, and to subject them to genome-wide copy number analysis. Our assay may be utilized to explore genomic events involved in cancer progression, e.g. development of castration resistance and to monitor therapeutic efficacy of targeted therapies in clinical trials in a relatively non-invasive manner.
Introduction: The molecular biology involving neoadjuvant chemotherapy (NAC) response is poorly understood. To elucidate the impact of NAC on the breast cancer transcriptome and its association with clinical outcome, we analyzed gene expression data derived from serial tumor samples of patients with breast cancer who received NAC in the I-SPY 1 TRIAL. Methods: Expression data were collected before treatment (T1), 24–96 hours after initiation of chemotherapy (T2) and at surgery (TS). Expression levels between T1 and T2 (T1 vs. T2; n = 36) and between T1 and TS (T1 vs. TS; n = 39) were compared. Subtype was assigned using the PAM50 gene signature. Differences in early gene expression changes (T2 − T1) between responders and nonresponders, as defined by residual cancer burden, were evaluated. Cox proportional hazards modeling was used to identify genes in residual tumors associated with recurrence-free survival (RFS). Pathway analysis was performed with Ingenuity software. Results: When we compared expression profiles at T1 vs. T2 and at T1 vs. TS, we detected significantly altered expression of 150 and 59 transcripts, respectively. We observed notable downregulation of proliferation and immune-related genes at T2. Lower concordance in subtype assignment was observed between T1 and TS (62 %) than between T1 and T2 (75 %). Analysis of early gene expression changes (T2 − T1) revealed that decreased expression of cell cycle inhibitors was associated with poor response. Increased interferon signaling (TS − T1) and high expression of cell proliferation genes in residual tumors (TS) were associated with reduced RFS. Conclusions: Serial gene expression analysis revealed candidate immune and proliferation pathways associated with response and recurrence. Larger studies incorporating the approach described here are warranted to identify predictive and prognostic biomarkers in the NAC setting for specific targeted therapies. Clinical trial registration: ClinicalTrials.gov identifier: NCT00033397. Registered 9 Apr 2002.