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2.
J Hematol Oncol ; 11(1): 76, 2018 06 04.
Article in English | MEDLINE | ID: mdl-29866143

ABSTRACT

BACKGROUND: We analyzed clinical associations of MET alterations in the plasma of patients with diverse malignancies. METHODS: Digital sequencing of circulating tumor DNA (ctDNA) (54-70 genes) was performed in 438 patients; 263 patients also had tissue sequencing (182-315 genes). The most represented tumor types were gastrointestinal (28.1%), brain (24.9%), and lung (23.2%). Most patients (71.2%) had recurrent/metastatic disease. RESULTS: MET alterations were observed in 31 patients (7.1%) and correlated with bone metastasis (P = 0.007), with TP53 (P = 0.001) and PTEN (P = 0.003) abnormalities, and with an increased number of alterations (median, 4 vs 1, P = 0.001) (all multivariable analyses). Patients with MET alterations demonstrated a significantly shorter median time to metastasis/recurrence (1.0 vs 10.4 months, P = 0.044, multivariable) and a poorer survival (30.6 vs 58.4 months, P = 0.013, univariate only). Of the 31 patients with MET alterations, 18 also had tissue testing; only two also had tissue MET alterations (11.1%); MET alterations were detected at a lower frequency in tissue (1.14%) compared to ctDNA (7.1%), with P = 0.0002. CONCLUSIONS: In conclusion, the detection of MET alterations by liquid biopsy is feasible. MET ctDNA alterations were associated with a poorer prognosis, higher numbers of genomic abnormalities, and bone metastases. The correlation with bone metastases may explain the higher frequency of MET alterations in blood ctDNA than in tissue (since bones are rarely biopsied) and the previous observations of bone-predominant responses to MET inhibitors. The high number of co-altered genes suggests that MET inhibitors may need to be combined with other agents to induce/optimize responses.


Subject(s)
Bone Neoplasms/secondary , Circulating Tumor DNA/blood , Hematologic Neoplasms/diagnosis , Proto-Oncogene Proteins c-met/metabolism , Aged , Female , Hematologic Neoplasms/blood , Hematologic Neoplasms/complications , Hematologic Neoplasms/pathology , Humans , Liquid Biopsy , Middle Aged , Prognosis , Proto-Oncogene Proteins c-met/antagonists & inhibitors , Proto-Oncogene Proteins c-met/genetics , Sequence Analysis, DNA
3.
J Natl Cancer Inst ; 107(11)2015 Nov.
Article in English | MEDLINE | ID: mdl-26378224

ABSTRACT

BACKGROUND: In order to ascertain the impact of a biomarker-based (personalized) strategy, we compared outcomes between US Food and Drug Administration (FDA)-approved cancer treatments that were studied with and without such a selection rationale. METHODS: Anticancer agents newly approved (September 1998 to June 2013) were identified at the Drugs@FDA website. Efficacy, treatment-related mortality, and hazard ratios (HRs) for time-to-event endpoints were analyzed and compared in registration trials for these agents. All statistical tests were two-sided. RESULTS: Fifty-eight drugs were included (leading to 57 randomized [32% personalized] and 55 nonrandomized trials [47% personalized], n = 38 104 patients). Trials adopting a personalized strategy more often included targeted (100% vs 65%, P < .001), oral (68% vs 35%, P = .001), and single agents (89% vs 71%, P = .04) and more frequently permitted crossover to experimental treatment (67% vs 28%, P = .009). In randomized registration trials (using a random-effects meta-analysis), personalized therapy arms were associated with higher relative response rate ratios (RRRs, compared with their corresponding control arms) (RRRs = 3.82, 95% confidence interval [CI] = 2.51 to 5.82, vs RRRs = 2.08, 95% CI = 1.76 to 2.47, adjusted P = .03), longer PFS (hazard ratio [HR] = 0.41, 95% CI = 0.33 to 0.51, vs HR = 0.59, 95% CI = 0.53 to 0.65, adjusted P < .001) and a non-statistically significantly longer OS (HR = 0.71, 95% CI = 0.61 to 0.83, vs HR = 0.81, 95% CI = 0.77 to 0.85, adjusted P = .07) compared with nonpersonalized trials. Analysis of experimental arms in all 112 registration trials (randomized and nonrandomized) demonstrated that personalized therapy was associated with higher response rate (48%, 95% CI = 42% to 55%, vs 23%, 95% CI = 20% to 27%, P < .001) and longer PFS (median = 8.3, interquartile range [IQR] = 5 vs 5.5 months, IQR = 5, adjusted P = .002) and OS (median = 19.3, IQR = 17 vs 13.5 months, IQR = 8, Adjusted P = .04). A personalized strategy was an independent predictor of better RR, PFS, and OS, as demonstrated by multilinear regression analysis. Treatment-related mortality rate was similar for personalized and nonpersonalized trials. CONCLUSIONS: A biomarker-based approach was safe and associated with improved efficacy outcomes in FDA-approved anticancer agents.


Subject(s)
Antineoplastic Agents/pharmacology , Biomarkers, Tumor , Drug Approval , Molecular Targeted Therapy , Clinical Trials as Topic , Humans , United States , United States Food and Drug Administration
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