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Adavosertib selectively inhibits Wee1, which regulates intra-S and G2/M cell-cycle checkpoints. This study investigated dosing schedules for adavosertib monotherapy, determining the maximum tolerated dose (MTD) and recommended Phase II dose (RP2D) in patients with advanced solid tumors.Patients received oral adavosertib qd or bid on a 5/9 schedule (5 days on treatment, 9 days off) in 14-day cycles, or qd on one of two 5/2 schedules (weekly, or for 2 of 3 weeks) in 21-day cycles. Safety, efficacy, and pharmacokinetic analyses were performed.Sixty-two patients (female, 64.5%; median age, 61.5 years; most common primary tumors: lung [24.2%], ovary [21.0%]) received treatment (qd schedules, n = 50; bid schedules, n = 12) for 1.8 months (median). Median time to maximum adavosertib concentration was 2.2–4.1 h; mean half-life was 5–12 h. Adverse events (AEs) caused dose reductions, interruptions and discontinuations in 17 (27.4%), 25 (40.3%) and 4 (6.5%) patients, respectively. Most common grade ≥ 3 AEs were anemia, neutropenia (each n = 9, 14.5%) and diarrhea (n = 8, 12.9%). Seven (11.3%) patients experienced 10 treatment-related serious AEs (pneumonia n = 2 [3.2%], dehydration n = 2 [3.2%], anemia n = 1 [1.6%], febrile neutropenia n = 1 [1.6%], and thrombocytopenia n = 1 [1.6%]). Overall objective response rate was 3.4% (2/58); disease control rate was 48.4% (30/62); median progression-free survival was 2.7 months.MTDs were 125 mg (bid 5/9) and 300 mg (qd 5/9 and 5/2 for 2 of 3 weeks); RP2D was 300 mg (qd 5/2 for 2 of 3 weeks). The safety profile was manageable, acceptable, and generally concordant with the known safety profile.

PDF file 186K, Loss of heterozygosity on Chromosome 11p15.5

PDF file 250K, Recurrent amplicons

Supplementary Table S3: Genomic alterations across selected targets. See Figure 3 for additional details. Zoomable PDF.

PDF file 671K, BCOR alterations

PDF file 277K, Expressed mutations summary

PDF file 92K, Supplementary Legends

Supplementary Fig. S3: Co-mutation across all PACC tumors.

Additional detailed methods.

PDF file 145K, Recurrent Recurrence peaks of focal copy number change

PDF file 1441K, Genetic Lesions associated with "Fusion Negative" Alveolar cases

PDF file 1175K, Determination of a somatic score cutoff for WGS based on the verification by WES

Genomic alterations in lung adenocarcinoma displayed in Figure 2A.

Focal amplification and activating point mutation of the MET gene are well-characterized oncogenic drivers that confer susceptibility to targeted MET inhibitors. Recurrent somatic splice site alterations at MET exon 14 (METex14) that result in exon skipping and MET activation have been characterized, but their full diversity and prevalence across tumor types are unknown. Here, we report analysis of tumor genomic profiles from 38,028 patients to identify 221 cases with METex14 mutations (0.6%), including 126 distinct sequence variants. METex14 mutations are detected most frequently in lung adenocarcinoma (3%), but also frequently in other lung neoplasms (2.3%), brain glioma (0.4%), and tumors of unknown primary origin (0.4%). Further in vitro studies demonstrate sensitivity to MET inhibitors in cells harboring METex14 alterations. We also report three new patient cases with METex14 alterations in lung or histiocytic sarcoma tumors that showed durable response to two different MET-targeted therapies. The diversity of METex14 mutations indicates that diagnostic testing via comprehensive genomic profiling is necessary for detection in a clinical setting.Significance: Here we report the identification of diverse exon 14 splice site alterations in MET that result in constitutive activity of this receptor and oncogenic transformation in vitro. Patients whose tumors harbored these alterations derived meaningful clinical benefit from MET inhibitors. Collectively, these data support the role of METex14 alterations as drivers of tumorigenesis, and identify a unique subset of patients likely to derive benefit from MET inhibitors. Cancer Discov; 5(8); 850–9. ©2015 AACR.See related commentary by Ma, p. 802.See related article by Paik et al., p. 842.This article is highlighted in the In This Issue feature, p. 783

PDF file 258K, Genome wide copy number profile.

Supplementary Fig. S1: GTL16 gastric adenocarcinoma cells derived to be resistant to MET inhibition and containing a similar SND1-BRAF fusion are sensitive to trametinib.

XLSX file 2844K, Supplementary Tables S1-S10

Summary of MET exon 14 alterations.

Supplementary Table S1A: Genes analyzed for base substitutions, short insertions/deletions, and copy number alterations (DNA). Supplementary Table S1B: Genes analyzed for rearrangements (DNA).

Supplementary Fig. S2: Loss of function mutations in select tumor suppressor genes.

PDF file 1261K, Reverse Transcription PCR of PAX3-FOXO1 in cell line 7250_PF

Previously characterized MET exon 14 alterations.

PDF file 1573K, Loss of heterozygosity across RMS tumor samples.

PDF file 3294K, Germline alteration of TP53 in patient RMS212

Supplementary Table S2A: Genes analyzed for base substitutions, short insertions/deletions, and copy number alterations (DNA). Supplementary Table S2B: Genes analyzed for rearrangements (DNA). Supplementary Table S2C: Genes analyzed for rearrangements (RNA). Zoomable PDF.

This file contains supplemental tables S1-S7. The data contained are as follows: (Table S1) Gene lists on the FoundationOne assay, (Table S2) Sample counts per disease, (Table S3) Foundation Medicine sample counts compared to TCGA sample counts, (Table S4) Genes with altered frequencies between local and metastatic disease, (Table S5) Merged MutationAssessor and PolyPhen-2 outputs, (Table S6) Enrichment of NOTCH1 alterations across diseases, (Table S7) Curated list of tumor suppressor genes on the FoundationOne assay.

In vitro resistance modeling coupled with molecular analysis of autopsy tumor samples from patients with acquired resistance to epidermal growth factor receptor (EGFR) inhibitors in lung cancer reveal novel biological insights into mechanisms of disease progression. These kinds of studies will facilitate the development of rationally targeted therapies in the era of genetically informed cancer medicine. Clin Cancer Res; 16(22); 5371–3. ©2010 AACR.

Long tail distribution of the top 50 altered genes in pediatric sarcoma (S1); Long tail distribution of the top 50 altered genes in pediatric extracranial embryonal tumors (S2); Long tail distribution of the top 50 altered genes in pediatric brain tumors (S3); Long tail distribution of the top 50 altered genes in pediatric heme malignancies (S4); Long tail distribution of the top 50 altered genes in pediatric carcinomas (S5); Long tail distribution of the top 50 altered genes in pediatric gonadal tumors (S6); Known fusions identified in the pediatric cohort (S7); Tileplots showing the pattern of co-occurring alterations with novel MLL3 mutations (S8); Tileplot showing the pattern of co-occurring alterations with a novel PRSS1 mutation (S9); Tileplot showing the pattern of co-occurring alterations with novel DKC1 deletions (S10).

Related Article from Highly Active Antitumor Therapy (HAATT) for Epidermal Growth Factor Receptor–Mutant Lung Cancer

Figure S1: Distribution of systemic therapies received. Figure S2: Number of sequenced samples per patient. Figure S3: Subgroup-defining genomic lesions in IDH-wildtype and -mutant gliomas. Figure S4: Frequency of mutations in primary tumors. Figure S5: Frequency of glioma type-defining genes. Figure S6: Outcome by enhancement and cell-cycle alteration status. Figure S7: Alteration of key functional groups in IDH-WT astrocytic tumors. Figure S8: Cell-cycle alterations and outcome in 1p19q-intact IDH WT tumors. Figure S9: Rate of alkylating therapy-induced hypermutation by WHO class. Figure S10: Frequency of actionable alterations. Figure S11: BRAF hotspot mutations in glioma. Figure S12: MR brain images for three patients receiving MAPK-directed therapy.

Gene lists for Version 1 of the FoundationOne Assay (S1); Gene lists for Version 2 of the FoundationOne Assay (S2); Gene lists for Version 3 of the FoundationOne Assay (S3); Gene lists for Version 4 of the FoundationOne Assay (S4); Gene lists for Version 5 of the FoundationOne Assay (S5); Distribution of samples across different FoundationOne assays (S6); Filtered variants of unknown significance (S7).

Expanded methods for the study.

Supplementary tables S1-S3 and Supplementary figures S1-Se

This is the legend for the supplemental figure

Enhancements in clinical-grade next-generation sequencing (NGS) have fueled the advancement of precision medicine in the clinical oncology field. Here, we survey the molecular profiles of 1,113 patients with diverse malignancies who successfully underwent clinical-grade NGS (236–404 genes) in an academic tertiary cancer center. Among the individual tumors examined, the majority showed at least one detectable alteration (97.2%). Among 2,045 molecular aberrations was the involvement of 302 distinct genes. The most commonly altered genes were TP53 (47.0%), CDKN2A (18.0%), TERT (17.0%), and KRAS (16.0%), and the majority of patients had tumors that harbored multiple alterations. Tumors displayed a median of four alterations (range, 0–29). Most individuals had at least one potentially actionable alteration (94.7%), with the median number of potentially actionable alterations per patient being 2 (range, 0–13). A total of 1,048 (94.2%) patients exhibited a unique molecular profile, with either genes altered or loci within the gene(s) altered being distinct. Approximately 13% of patients displayed a genomic profile identical to at least one other patient; although genes altered were the same, the affected loci may have differed. Overall, our results underscore the complex heterogeneity of malignancies and argue that customized combination therapies will be essential to optimize cancer treatment regimens. Cancer Res; 77(22); 6313–20. ©2017 AACR.

Genomic profiling is widely predicted to become a standard of care in clinical oncology, but more effective data sharing to accelerate progress in precision medicine will be required. Here, we describe cancer-associated genomic profiles from 18,004 unique adult cancers. The dataset was composed of 162 tumor subtypes including multiple rare and uncommon tumors. Comparison of alteration frequencies to The Cancer Genome Atlas identified some differences and suggested an enrichment of treatment-refractory samples in breast and lung cancer cohorts. To illustrate novelty within the dataset, we surveyed the genomic landscape of rare diseases and identified an increased frequency of NOTCH1 alterations in adenoid cystic carcinomas compared with previous studies. Analysis of tumor suppressor gene patterns revealed disease specificity for certain genes but broad inactivation of others. We identified multiple potentially druggable, novel and known kinase fusions in diseases beyond those in which they are currently recognized. Analysis of variants of unknown significance identified an enrichment of SMAD4 alterations in colon cancer and other rare alterations predicted to have functional impact. Analysis of established, clinically relevant alterations highlighted the spectrum of molecular changes for which testing is currently recommended, as well as opportunities for expansion of indications for use of approved targeted therapies. Overall, this dataset presents a new resource with which to investigate rare alterations and diseases, validate clinical relevance, and identify novel therapeutic targets. Cancer Res; 77(9); 2464–75. ©2017 AACR.

Supplemental Table S3 displays the Foundation Medicine 323 gene panel for hematological malignancies.

Detailed genetic results

Photomicrographs of two ETV6-NTRK3 fusion cases.

Purpose:This study assessed the efficacy, safety, and pharmacokinetics of adavosertib in combination with four chemotherapy agents commonly used in patients with primary platinum-resistant ovarian cancer.Patients and Methods:Women with histologically or cytologically confirmed epithelial ovarian, fallopian tube, or peritoneal cancer with measurable disease were enrolled between January 2015 and January 2018 in this open-label, four-arm, multicenter, phase II study. Patients received adavosertib (oral capsules, 2 days on/5 days off or 3 days on/4 days off) in six cohorts from 175 mg once daily to 225 mg twice daily combined with gemcitabine, paclitaxel, carboplatin, or pegylated liposomal doxorubicin. The primary outcome measurement was overall response rate.Results:Three percent of patients (3/94) had confirmed complete response and 29% (27/94) had confirmed partial response. The response rate was highest with carboplatin plus weekly adavosertib, at 66.7%, with 100% disease control rate, and median progression-free survival of 12.0 months. The longest median duration of response was in the paclitaxel cohort (12.0 months). The most common grade ≥3 adverse events across all cohorts were neutropenia [45/94 (47.9%) patients], anemia [31/94 (33.0%)], thrombocytopenia [30/94 (31.9%)], and diarrhea and vomiting [10/94 (10.6%) each].Conclusions:Adavosertib showed preliminary efficacy when combined with chemotherapy. The most promising treatment combination was adavosertib 225 mg twice daily on days 1–3, 8–10, and 15–17 plus carboplatin every 21 days. However, hematologic toxicity was more frequent than would be expected for carboplatin monotherapy, and the combination requires further study to optimize the dose, schedule, and supportive medications.

Supplemental Table S1 displays the Foundation Medicine 236 gene panel.

This file contains: cellularity distribution, exon coverage distribution, variant filtering flow chart, detailed disease distributions, FMvTCGA long tail plots by local/metastatic disease, local disease versus plural fluid in FM lung adeno, adenoid cystic carcinoma tile plot, summary of known fusions observed in novel diseases, ERBB2 tile plot in cervical cancers, TCGA MET CN to expression correlation, tile plot of AKT1 E17K colorectal tumors, and distribution of alterations in tumor suppressor genes.

Supplemental Table S4 displays the Foundation Medicine 404 Gene Panel for hematologic malignancies.

Table S1: Patient-level clinical annotation. Table S2: Sample-level clinical annotation. Table S3: Patient-level treatment lines. Table S4: Gene panels for targeted sequencing. Table S5: Somatic mutations. Table S6: Gene-level copy number alterations. Table S7: Hotspot mutations in 3,130 sequenced glioma patients. Table S8: Pathogenic and likely pathogenic germline variants identified. Table S9: Pathways and gene content for cohort-wide pathway-level analyses.

Purpose:The genomic landscape of gliomas has been characterized and now contributes to disease classification, yet the relationship between molecular profile and disease progression and treatment response remain poorly understood.Experimental Design: We integrated prospective clinical sequencing of 1,004 primary and recurrent tumors from 923 glioma patients with clinical and treatment phenotypes.Results:Thirteen percent of glioma patients harbored a pathogenic germline variant, including a subset associated with heritable genetic syndromes and variants mediating DNA repair dysfunctions (29% of the total) that were associated with somatic biallelic inactivation and mechanism-specific somatic phenotypes. In astrocytomas, genomic alterations in effectors of cell-cycle progression correlated with aggressive disease independent of IDH mutation status, arose preferentially in enhancing tumors (44% vs. 8%, P < 0.001), were associated with rapid disease progression following tumor recurrence (HR = 2.6, P = 0.02), and likely preceded the acquisition of alkylating therapy-associated somatic hypermutation. Thirty-two percent of patients harbored a potentially therapeutically actionable lesion, of whom 11% received targeted therapies. In BRAF-mutant gliomas, response to agents targeting the RAF/MEK/ERK signaling axis was influenced by the type of mutation, its clonality, and its cellular and genomic context.Conclusions:These data reveal genomic correlates of disease progression and treatment response in diverse types of glioma and highlight the potential utility of incorporating genomic information into the clinical decision-making for patients with glioma.

Details for variant processing, analysis of TCGA data, and the FM mutation hotspot caller.

Supplemental Table S2 displays the Foundation Medicine 315 gene panel for solid tumors.

Pediatric cancers are generally characterized by low mutational burden and few recurrently mutated genes. Recent studies suggest that genomic alterations may help guide treatment decisions and clinical trial selection. Here, we describe genomic profiles from 1,215 pediatric tumors representing sarcomas, extracranial embryonal tumors, brain tumors, hematologic malignancies, carcinomas, and gonadal tumors. Comparable published datasets identified similar frequencies of clinically relevant alterations, validating this dataset as biologically relevant. We identified novel ALK fusions in a neuroblastoma (BEND5–ALK) and an astrocytoma (PPP1CB–ALK), novel BRAF fusions in an astrocytoma (BCAS1–BRAF) and a ganglioglioma (TMEM106B–BRAF), and a novel PAX3–GLI2 fusion in a rhabdomyosarcoma. Previously characterized ALK, NTRK1, and PAX3 fusions were observed in unexpected malignancies, challenging the "disease-specific" alterations paradigm. Finally, we identified recurrent variants of unknown significance in MLL3 and PRSS1 predicted to have functional impact. Data from these 1,215 tumors are publicly available for discovery and validation. Cancer Res; 77(2); 509–19. ©2017 AACR.

Purpose: Patients with epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma develop acquired resistance to EGFR tyrosine kinase inhibitors (TKI) after a median of 10 to 16 months. In half of these cases, a second EGFR mutation, T790M, underlies acquired resistance. We undertook this study to examine the clinical course of patients harboring the T790M mutation following progression on TKI.Experimental Design: EGFR-mutant lung cancer patients with acquired resistance to EGFR TKIs were identified as part of a prospective rebiopsy protocol in which postprogression tumor specimens were collected for molecular analysis. Postprogression survival and characteristics of disease progression were compared in patients with and without T790M.Results: We identified T790M in the initial rebiopsy specimens from 58 of 93 patients (62%, 95% CI: 52–72). T790M was more common in biopsies of lung/pleura tissue and lymph nodes than in more distant sites (P = 0.014). Median postprogression survival was 16 months (interquartile range = 9–29 months); patients with T790M had a significantly longer postprogression survival (P = 0.036). Patients without T790M more often progressed in a previously uninvolved organ system (P = 0.014) and exhibited a poorer performance status at time of progression (P = 0.007).Conclusions: Among patients with acquired resistance to EGFR TKIs, the presence of T790M defines a clinical subset with a relatively favorable prognosis and more indolent progression. Knowledge of T790M status is therefore important both for the clinical care of these patients and for the optimal design and interpretation of clinical trials in this setting. Clin Cancer Res; 17(6); 1616–22. ©2010 AACR.

Supplementary Figures S1-S2.