Molecular profiling of cancer patients enables personalized combination therapy: the I-PREDICT study

Abstract

Cancer treatments have evolved from indiscriminate cytotoxic agents to selective genome- and immune-targeted drugs that have transformed the outcomes of some malignancies¹. Tumor complexity and heterogeneity suggest that the 'precision medicine' paradigm of cancer therapy requires treatment to be personalized to the individual patient^2-6. To date, precision oncology trials have been based on molecular matching with predetermined monotherapies^7-14. Several of these trials have been hindered by very low matching rates, often in the 5-10% range¹⁵, and low response rates. Low matching rates may be due to the use of limited gene panels, restrictive molecular matching algorithms, lack of drug availability, or the deterioration and death of end-stage patients before therapy can be implemented. We hypothesized that personalized treatment with combination therapies would improve outcomes in patients with refractory malignancies. As a first test of this concept, we implemented a cross-institutional prospective study (I-PREDICT, NCT02534675 ) that used tumor DNA sequencing and timely recommendations for individualized treatment with combination therapies. We found that administration of customized multidrug regimens was feasible, with 49% of consented patients receiving personalized treatment. Targeting of a larger fraction of identified molecular alterations, yielding a higher 'matching score', was correlated with significantly improved disease control rates, as well as longer progression-free and overall survival rates, compared to targeting of fewer somatic alterations. Our findings suggest that the current clinical trial paradigm for precision oncology, which pairs one driver mutation with one drug, may be optimized by treating molecularly complex and heterogeneous cancers with combinations of customized agents.

Extended Data Figure 1

Consolidated Standards of Reporting Trials (CONSORT) diagram, which includes the 149 patients that consented to I-PREDICT. * Treated evaluable patients includes patients who received >10 d of treatment for drugs given on a daily basis (generally drugs given by mouth) or at least two doses of a drug normally given every two weeks or more frequently (the latter generally being intravenous drugs). Only patients whose treatment was reviewed and validated by data analysis lockdown are included. ** One patient had inadequate tissue for NGS and declined biopsy; he was later reenrolled after he agreed to undergo biopsy. Note: One treated patient who initially was believed to have prior therapy was found, after data lockdown analysis, to have not received the prior regimen.

Figure 1. Molecular alterations targeted by matched therapies and impact of the Matching Score on treatment outcome.

A. Pie graph of the percentage of actionable aberrations in the indicated targets or target pathways for the 73 patients who received at least one matched drug. Since some patients had alterations targeted in multiple genes or pathways, the percentages do not add up to 100%. “Immune checkpoints” refers to amplification of the CD274 (PD-L1) and/or PDCD1LG2 (PD-L2) genes, positive PD-L1 expression (immunohistochemistry), high/intermediate tumor mutational burden, or high microsatellite instability; “MAPK pathway” refers to alterations in the KRAS, BRAF, GNAS, MEK1, NF2 or JAK2 genes; “ERBB pathway” refers to alterations in the ERBB2 or ERBB3 genes; “PI3K pathway” refers to alterations in the AKT1, AKT2, PIK3CA, PIK3R1 or PTEN genes; “FGF/FGFR” pathway refers to alterations/amplifications in the FGFR1/2/3, FGF3, FGF4, FGF6, FGF19, FGF23 or FRS2 genes; “Beta-catenin pathway” refers to alterations in the APC, CTNNB1 or FAT1 genes; “Cell cycle regulation” refers to alterations in the CDKN2A/B, CCND1/2 or CDK4/6 genes; “HGF/MET pathway” refers to alterations in the HGF or MET genes; “BRCA complex” refers to alterations in the BRCA1, BRCA2, ATM, BRIP or PALB2 genes; Estrogen receptor” refers to alterations in the ESR1 gene or estrogen receptor (ER) positivity as assessed by immunohistochemistry; “Other” refers to alterations in the MYC or EWSR1 genes. TP53, EGFR, PTCH1, and RET refer to alterations in the genes encoding these proteins. B. Pie graph of the percentage of actionable aberrations in the indicated targets or target pathways for the 28 patients who had a Matching Score >50%. In these 28 patients, a total of 67 molecular alterations were matched to treatments. C. Bar graph analyzing the percentage of patients with SD ≥6 months, partial response (PR), and complete response (CR) for patients with a Matching Score of ≤50% (N=49) versus >50% (N=20). P-values were computed using a binary logistic regression test. D. Bar graph analyzing the percentage of patients with a PFS ratio ≥1.3 versus PFS<1.3 for patients with a Matching Score of ≤50% (N=49) versus >50% (N=20). P-values were computed using a binary logistic regression test. E. Kaplan-Meier curves display progression-free survival (PFS) for patients with a Matching Score ≤50% (N=55) versus >50% (N=28). P-values are from the log-rank test (two-sided) F. Kaplan-Meier curves display overall survival (OS) for patients with a Matching Score ≤50% (N=55) versus >50% (N=28). P-values are from the log-rank test (two-sided). *Median OS not reached after a median follow up of 8.5 months.