The AACR Project GENIE is an international data-sharing consortium focused on generating an evidence base for precision cancer medicine by integrating clinical-grade cancer genomic data with clinical outcome data for tens of thousands of cancer patients treated at multiple institutions worldwide. In conjunction with the first public data release from approximately 19,000 samples, we describe the goals, structure, and data standards of the consortium and report conclusions from high-level analysis of the initial phase of genomic data. We also provide examples of the clinical utility of GENIE data, such as an estimate of clinical actionability across multiple cancer types (>30%) and prediction of accrual rates to the NCI-MATCH trial that accurately reflect recently reported actual match rates. The GENIE database is expected to grow to >100,000 samples within 5 years and should serve as a powerful tool for precision cancer medicine. Significance The AACR Project GENIE aims to catalyze sharing of integrated genomic and clinical datasets across multiple institutions worldwide, and thereby enable precision cancer medicine research, including the identification of novel therapeutic targets, design of biomarker-driven clinical trials, and identification of genomic determinants of response to therapy.

The fi broblast growth factor/fi broblast growth factor receptor (FGF/FGFR) signaling pathway plays a fundamental role in many physiologic processes, including embryogenesis, adult tissue homeostasis, and wound healing, by orchestrating angiogenesis. Ligand-independent and ligand-dependent activation have been implicated in a broad range of human malignancies and promote cancer progression in tumors driven by FGF/FGFR oncogenic mutations or amplifi cations, tumor neoangiogenesis, and targeted treatment resistance, thereby supporting a strong rationale for anti-FGF/FGFR agent development. Efforts are being pursued to develop selective approaches for use against this pathway by optimizing the management of emerging, classspecifi c toxicity profi les and correctly designing clinical trials to address these different issues.Signifi cance: FGF/FGFR pathway deregulations are increasingly recognized across different human cancers. Understanding the mechanisms at the basis of these alterations and their multiple roles in cancer promotion and drug resistance is a fundamental step for further implementation of targeted therapies and research strategies. Cancer Discov;3(3);

BackgroundMajor advances have been achieved in the characterization of early breast cancer (eBC) genomic profiles. Metastatic breast cancer (mBC) is associated with poor outcomes, yet limited information is available on the genomic profile of this disease. This study aims to decipher mutational profiles of mBC using next-generation sequencing.Methods and FindingsWhole-exome sequencing was performed on 216 tumor–blood pairs from mBC patients who underwent a biopsy in the context of the SAFIR01, SAFIR02, SHIVA, or Molecular Screening for Cancer Treatment Optimization (MOSCATO) prospective trials. Mutational profiles from 772 primary breast tumors from The Cancer Genome Atlas (TCGA) were used as a reference for comparing primary and mBC mutational profiles. Twelve genes (TP53, PIK3CA, GATA3, ESR1, MAP3K1, CDH1, AKT1, MAP2K4, RB1, PTEN, CBFB, and CDKN2A) were identified as significantly mutated in mBC (false discovery rate [FDR] < 0.1). Eight genes (ESR1, FSIP2, FRAS1, OSBPL3, EDC4, PALB2, IGFN1, and AGRN) were more frequently mutated in mBC as compared to eBC (FDR < 0.01). ESR1 was identified both as a driver and as a metastatic gene (n = 22, odds ratio = 29, 95% CI [9–155], p = 1.2e-12) and also presented with focal amplification (n = 9) for a total of 31 mBCs with either ESR1 mutation or amplification, including 27 hormone receptor positive (HR+) and HER2 negative (HER2−) mBCs (19%). HR+/HER2− mBC presented a high prevalence of mutations on genes located on the mechanistic target of rapamycin (mTOR) pathway (TSC1 and TSC2) as compared to HR+/HER2− eBC (respectively 6% and 0.7%, p = 0.0004). Other actionable genes were more frequently mutated in HR+ mBC, including ERBB4 (n = 8), NOTCH3 (n = 7), and ALK (n = 7). Analysis of mutational signatures revealed a significant increase in APOBEC-mediated mutagenesis in HR+/HER2− metastatic tumors as compared to primary TCGA samples (p < 2e-16). The main limitations of this study include the absence of bone metastases and the size of the cohort, which might not have allowed the identification of rare mutations and their effect on survival.ConclusionsThis work reports the results of the analysis of the first large-scale study on mutation profiles of mBC. This study revealed genomic alterations and mutational signatures involved in the resistance to therapies, including actionable mutations.

PURPOSE A large-panel gene expression analysis was conducted to identify biomarkers associated with the effectiveness of adding palbociclib to fulvestrant. METHODS The PALOMA-3 (ClinicalTrials.gov identifier: NCT01942135 ) trial randomly assigned 521 endocrine-pretreated patients with metastatic breast cancer to receive palbociclib plus fulvestrant or placebo plus fulvestrant. Primary analysis was first conducted on 10 genes on the basis of pathway biology and evidence from previous studies followed by a systematic panel-wide search among 2,534 cancer-related genes. The association of gene expression with the effect of palbociclib on progression-free survival (PFS) was evaluated using Cox proportional hazards regression analysis, with gene expression as a continuous variable or dichotomized by median. An independent breast cancer cohort from the Preoperative Palbociclib (POP) Clinical Trial (ClinicalTrials.gov identifier: NCT02008734 ) was used for validation, in 61 patients with primary breast cancer treated with 2 weeks of palbociclib. RESULTS In the PALOMA-3 trial, 302 patients had tumor tissue analyzed (palbociclib arm, 194 patients; placebo arm, 108 patients). Palbociclib efficacy was lower in patients with high versus low cyclin E1 ( CCNE1) mRNA expression (median PFS: palbociclib arm, 7.6 v 14.1 months; placebo arm, 4.0 v 4.8 months, respectively; interaction P unadjusted = .00238; false discovery rate–adjusted P = .0238). CCNE1 mRNA was more predictive in metastatic than in archival primary biopsy tissue samples. No significant interaction was found between treatment and expression levels of CDK4, CDK6, cyclin D1, and RB1. Palbociclib was efficacious in both luminal A and luminal B tumors. High CCNE1 mRNA expression was associated with poor antiproliferative activity of palbociclib in the POP trial ( P = .005). CONCLUSION Addition of palbociclib to fulvestrant demonstrated efficacy in all biomarker groups, although high CCNE1 mRNA expression was associated with relative resistance to palbociclib.

Aberrant b-catenin expression as determined by assessment of its subcellular localization constitutes a surrogate marker of Wnt signalling pathway activation and has been reported in a subset of breast cancers. The association of b-catenin/Wnt pathway activation with clinical outcome and the mechanisms leading to its activation in breast cancers still remain a matter of controversy. The aims of this study were to address the distribution of b-catenin expression in invasive breast cancers, the correlations between b-catenin expression and clinicopathological features and survival of breast cancer patients, and to determine whether aberrant b-catenin expression is driven by CTNNB1 (b-catenin encoding gene) activating mutations. Immunohistochemistry was performed on a tissue microarray containing 245 invasive breast carcinomas from uniformly treated patients, using two anti-b-catenin monoclonal antibodies. Selected samples were subjected to CTNNB1 exon 3 mutation analysis by direct gene sequencing. A good correlation between the two b-catenin antibodies was observed (Spearman's r 40.62, Po0.001). Respectively, 31 and 11% of the cases displayed lack/reduction of b-catenin membranous expression and nuclear accumulation. Complete lack of b-catenin expression was significantly associated with invasive lobular carcinoma histological type. Subgroup analysis of non-lobular cancers or non-lobular grade 3 carcinomas revealed that lack/reduction of b-catenin membranous expression and/or nuclear accumulation were significantly associated with oestrogen receptor negativity, absence of HER2 gene amplification and overexpression, lack/reduction of E-cadherin expression and tumours of triple-negative and basal-like phenotype. Univariate survival analysis revealed a significant association between b-catenin nuclear expression and shorter metastasis-free and overall survival in the whole cohort; however, b-catenin nuclear expression was not an independent predictor of outcome in multivariate analysis. No CTNNB1 mutations were identified in the 28 selected breast carcinomas analysed. In conclusion, b-catenin/Wnt pathway activation is preferentially found in triple-negative/basal-like breast carcinomas, is associated with poor clinical outcome and is unlikely to be driven by CTNNB1 mutations in breast cancer.

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The development of precision medicine for the management of metastatic breast cancer is an appealing concept; however, major scientific and logistical challenges hinder its implementation in the clinic. The identification of driver mutational events remains the biggest challenge, because, with the few exceptions of ER, HER2, PIK3CA and AKT1, no validated oncogenic drivers of breast cancer exist. The development of bioinformatic tools to help identify driver mutations, together with assessment of pathway activation and dependency should help resolve this issue in the future. The occurrence of secondary resistance, such as ESR1 mutations, following endocrine therapy poses a further challenge. Ultra-deep sequencing and monitoring of circulating tumour DNA (ctDNA) could permit early detection of the genetic events underlying resistance and inform on combination therapy approaches. Beside these scientific challenges, logistical and operational issues are a major limitation to the development of precision medicine. For example, the low incidence of most candidate genomic alterations hinders randomized trials, as the number of patients to be screened would be too high. We discuss these limitations and the solutions, which include scaling-up the number of patients screened for identifying a genomic alteration, the clustering of genomic alterations into pathways, and the development of personalized medicine trials.

CNB can be used with confidence for ER and HER2 determination. For PgR, due to a substantial discordance between CNB and EB, results from CNB should be used with caution.