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. 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. 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. A biomarker-based approach was safe and associated with improved efficacy outcomes in FDA-approved anticancer agents.

Background: The phosphatidylinositol 3‐kinase (PI3K) pathway is frequently altered in cancer. This report describes the landscape of PI3K alterations in solid tumors as well as co‐alterations serving as potential resistance/attenuation mechanisms. Methods: Consecutive samples were analyzed in a commercial Clinical Laboratory Improvement Amendment‐certified laboratory using comprehensive genomic profiling performed by next‐generation sequencing (315 genes). The co‐alterations evaluated included the Erb‐B2 receptor tyrosine kinase 2 ( ERBB2 ), ERBB3 , ERBB4 , RAS , MET proto‐oncogene tyrosine kinase ( MET ), and mitogen‐activated protein kinase kinase ( MAP2K ) genes as well as tumor protein 53 ( TP53 ), estrogen receptor 1 ( ESR1 ), and androgen receptor ( AR). Results: Alterations in any of 18 PI3K‐pathway associated genes were identified in 44% of 60,991 tumors. Although single base and insertions/deletions (indels) were the most frequent alterations, copy number changes and rearrangements were identified in 11% and 0.9% of patients, respectively. Overall, the most frequently altered genes were PIK3 catalytic subunit α ( PIK3CA ) (13%), phosphatase and tensin homolog ( PTEN ) (9%), and serine/threonine kinase 11 ( STK11 ) (5%). Tumor types that frequently harbored at least 1 PI3K alteration were uterine (77%), cervical (62%), anal (59%), and breast (58%) cancers. Alterations also were discerned frequently in tumors with carcinosarcoma (89%) and squamous cell carcinoma (62%) histologies. Tumors with a greater likelihood of co‐occurring PI3K pathway and MAPK pathway alterations included colorectal cancers (odds ratio [OR], 1.64; P < .001), mesotheliomas (OR, 2.67; P = .024), anal cancers (OR, 1.98; P = .03), and nonsquamous head and neck cancers (OR, 2.03; P = .019). The co‐occurrence of ESR1 and/or AR alterations with PI3K alterations was statistically significant in bladder, colorectal, uterine, prostate, and unknown primary cancers. Conclusions: Comprehensive genomic profiling reveals altered PI3K‐related genes in 44% of solid malignancies, including rare disease and histology types. The frequency of alterations and the co‐occurrence of resistance pathways vary by tumor type, directly affecting opportunities for targeted therapy.

Immune checkpoint inhibitors have unique toxicities and response kinetics compared with cytotoxic and gene-targeted anticancer agents. We investigated the impact of innovative/accelerated immunotherapy drug development/approval models on the accuracy of safety and efficacy assessments by searching the FDA website. Initial phase I trials for each agent were reviewed and safety and efficacy data compared with that found in later trials leading to regulatory approvals of the same agents. As of June 2017, the FDA approved six checkpoint inhibitors for a variety of cancer types. All checkpoint inhibitors received a priority review status and access to at least two additional FDA special access programs, more often breakthrough therapy designation and accelerated approval. Median clinical development time (investigational new drug application to approval) was 60.77 months [avelumab had the shortest timeline (52.33 months)]. Response rates during early phase I trials (median = 16%) are higher than for phase I trials of other agents (with the exception of gene-targeted agents tested with a biomarker). Doses approved were usually not identical to doses recommended on phase I trials. Approximately 50% of types of immune-related and 43% of types of clinically relevant toxicities from later trials were identified in early-phase trials. Even so, treatment-related mortality remains exceedingly low in later studies (0.33% of patients). In conclusion, efficacy and safety of immune checkpoint inhibitors appear to be reasonably predicted from the dose-finding portion of phase I trials, indicating that the fast-track development of these agents is safe and justified. Clin Cancer Res; 24(8); 1785–94. ©2017 AACR.

Background: Phyllodes tumors are uncommon breast tumors that account for less than 0.5% of all breast malignancies. After metastases develop, the prognosis is poor, with very few patients living more than 1 year. The biology of this unusual cancer is not understood and, consequently, no potential targets for treatments are currently available. There has been an exponential increase in the number of commercially available tumor profiling services. Herein, we report a case of metastatic malignant phyllodes tumor for which a comprehensive molecular analysis was performed by using Clinical Laboratory Improvement Amendments (CLIA)-certified labs, providing new insights into the potential opportunities for molecularly targeted therapies for this extremely rare disease.Methods: Next-generation sequencing was performed by using the FoundationOne™ platform (Foundation Medicine, Cambridge, MA). Whole-genome array-based comparative genomic hybridization (array CGH) was performed by using the DNAarray™ (CombiMatrix Diagnostics, Irvine, CA). Immunohistochemical and morphoproteomics analysis were performed at Consultative proteomics^®, The University of Texas, UT Health Medical School, Houston,TX (Robert E Brown Lab); Clarient Diagnostics, Aliso Viejo, CA; and Caris Life Sciences Target one, Irving, TX, USA.Results: Next-generation sequencing showed 3 aberrant genes: activating mutation Q61L onNRAS; inactivating mutations Q504* and K740* onRB1; andTP53loss. Whole-genome array-based comparative genomic hybridization (array CGH) revealed amplifications of chromosome (chr.) 1 (CKS1Bgene), chr. 8 (MYCgene), and chr. 9 (CDKN2Agene) Deletions of chr. 17 (TP53), chr. 10 (GATA3), chr. 11 (FGF4andCCND1genes), and chr.22 (PDGFβ). Immunohistochemical analysis for relevant markers showed a positive staining for transducing-like enhancer of split (TLE) 3; secreted protein acidic and rich in cysteine (SPARC) was expressed at 2-3+ in the cytoplasm of the tumors cells, whereas mammalian target of rapamycin (mTOR) was expressed up to 2+ in the nuclei of the tumor cells.Conclusions: We describe for the first time anNRASmutation with concomitant activation ofPI3K/Akt/mTORin phyllodes tumor. We also found markers for sensitivity to taxane-based therapies, especially albumin-bound paclitaxel. Exploring the biology of rare malignancies by CLIA certified labs may be reasonable strategy for the development of targeted treatments.

We analyzed clinical associations of MET alterations in the plasma of patients with diverse malignancies. 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. 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. 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.