Search

Purpose: Precision oncology is widely discussed, but cohort studies are limited. We previously reported our prospective experience of precision oncology in solid tumors, and here we report our longitudinal experience, focusing on therapeutic impact. Patients and Methods: We conducted a retrospective review of 600 consecutive patients seen at Cleveland Clinic from 2013 to 2016 for treatment of incurable solid tumor malignancies for whom tumor genomic profiling was ordered using FoundationOne (Cambridge, MA). Results were discussed at our multidisciplinary genomics tumor board. Data analyzed included subsequent therapy and overall survival (OS). Results: Median age was 59 years (range, 18 to 94 years), 308 (51.3%) were female, and 533 (88.8%) were white. Targeted therapy was recommended in 310 patients (51.7%). After results, 313 patients (52.2%) started any subsequent therapy; of these, 95 (30%; 15.8% overall) received genomics-driven therapy (G), and 218 (70%) received non–genomics-driven treatment (NG). For the G versus NG group, the on-label, off-label, and clinical trial therapy breakdowns were 23% versus 88%, 47% versus 3%, and 30% versus 9%, respectively. Median OS for patients receiving no therapy after tumor genomic profiling was 5.5 months; for the G and NG groups, it was 18 (P <.001) and 14.4 (P <.001) months, respectively (P = NS for G v NG). The use of G increased from 10% in the first 250-patient cohort (reported earlier) to 20% in the subsequent 350-patient cohort. Conclusion: Tumor genomic profiling influenced treatment in 15.8% of patients. More patients received treatment via clinical trials in the G cohort, and although not statistically significant, there was a trend toward increased OS in the G (v NG) group. These data can further guide real-world applications of precision oncology. [ABSTRACT FROM AUTHOR]

Purpose: Patients with breast cancer experience progression and respond to treatment in diverse ways, but prognostic and predictive tools for the oncologist are limited. We have used gene expression data to guide the production of hundreds of novel antibody reagents to discover novel diagnostic tools for stratifying carcinoma patients., Patients and Methods: One hundred forty novel and 23 commercial antisera, selected on their ability to differentially stain tumor samples, were used to stain paraffin blocks from a retrospective breast cancer cohort. Cox proportional hazards and regression tree analysis identified minimal panels of reagents able to predict risk of recurrence. We tested the prognostic association of these prospectively defined algorithms in two independent cohorts., Results: In both validation cohorts, the Kaplan-Meier estimates of recurrence confirmed that both the Cox model using five reagents (p53, NDRG1, CEACAM5, SLC7A5, and HTF9C) and the regression tree model using six reagents (p53, PR, Ki67, NAT1, SLC7A5, and HTF9C) distinguished estrogen receptor (ER)-positive patients with poor outcomes. The Cox model was superior and distinguished patients with poor outcomes from patients with good or moderate outcomes with a hazard ratio of 2.21 (P = .0008) in validation cohort 1 and 1.88 (P = .004) in cohort 2. In multivariable analysis, the calculated risk of recurrence was independent of stage, grade, and lymph node status. A model proposed for ER-negative patients failed validation in the independent cohorts., Conclusion: A panel of five antibodies can significantly improve on traditional prognosticators in predicting outcome for ER-positive breast cancer patients.

Purpose: Metastatic breast cancer (MBC) is incurable; its treatment is palliative. We investigated whether the presence of circulating tumor cells (CTCs) predicts treatment efficacy, progression-free survival (PFS), and overall survival (OS) in patients with newly diagnosed MBC who were about to start first-line therapy., Patients and Methods: One hundred seventy-seven patients with measurable MBC were enrolled onto a prospective study. Eighty-three of the 177 patients were entering first-line treatment, and these patients are the focus of this analysis. CTCs from 7.5 mL of whole blood drawn before treatment initiation (baseline) and monthly thereafter for up to 6 months were isolated and enumerated using immunomagnetics., Results: The mean (+/- standard deviation) follow-up time was 11.1 +/- 4.4 months (median, 12.2 months). Forty-three patients (52%) had > or = five CTCs at baseline. The median PFS was 7.2 months (95% CI, 4.9 to 9.4 months), and the median OS was more than 18 months. Patients with > or = five CTCs at baseline and at first follow-up (4 weeks) had a worse prognosis than patients with less than five CTCs (baseline: median PFS, 4.9 v 9.5 months, respectively; log-rank, P = .0014; median OS, 14.2 v > 18 months, respectively; log-rank, P = .0048; first follow-up: median PFS, 2.1 v 8.9 months, respectively; log-rank, P = .0070; median OS, 11.1 v > 18 months, respectively; log-rank, P = .0029). CTCs before and after the initiation of therapy were strong, independent prognostic factors., Conclusion: Detection of CTCs before initiation of first-line therapy in patients with MBC is highly predictive of PFS and OS. This technology can aid in appropriate patient stratification and design of tailored treatments.