Fibroblast growth factor receptors in cancer: genetic alterations,diagnostics, therapeutic targets and mechanisms of resistance

Fibroblast growth factor receptors (FGFRs) are aberrantly activated through single-nucleotide variants, gene fusions and copy number amplifications in 5–10% of all human cancers, although this frequency increases to 10–30% in urothelial carcinoma and intrahepatic cholangiocarcinoma. We begin this review by highlighting the diversity of FGFR genomic alterations identified in human cancers and the current challenges associated with the development of clinical-grade molecular diagnostic tests to accurately detect these alterations in the tissue and blood of patients. The past decade has seen significant advancements in the development of FGFR-targeted therapies, which include selective, non-selective and covalent small-molecule inhibitors, as well as monoclonal antibodies against the receptors. We describe the expanding landscape of anti-FGFR therapies that are being assessed in early phase and randomised controlled clinical trials, such as erdafitinib and pemigatinib, which are approved by the Food and Drug Administration for the treatment of FGFR3-mutated urothelial carcinoma and FGFR2-fusion cholangiocarcinoma, respectively. However, despite initial sensitivity to FGFR inhibition, acquired drug resistance leading to cancer progression develops in most patients. This phenomenon underscores the need to clearly delineate tumour-intrinsic and tumour-extrinsic mechanisms of resistance to facilitate the development of second-generation FGFR inhibitors and novel treatment strategies beyond progression on targeted therapy.Subject terms: Cancer, Cancer     

Real-World Palbociclib Use in HR+/HER2− Advanced Breast Cancer in Canada: The IRIS Study

Background: Palbociclib is a selective cyclin-dependent kinase (CDK) 4/6 inhibitor used in combination with aromatase inhibitors or fulvestrant for patients with hormone receptor-positive (HR+) human epidermal growth factor receptor 2 (HER2)-negative advanced/metastatic breast cancer (ABC/MBC). Palbociclib was the first CDK 4/6 inhibitor approved for HR+/HER2− ABC/MBC treatment in Canada in combination with letrozole (P+L) as an initial endocrine-based therapy (approved March 2016), or with fulvestrant (P+F) following disease progression after prior endocrine therapy (approved May 2017). The Ibrance Real World Insights (IRIS) study ({"type":"clinical-trial","attrs":{"text":"NCT03159195","term_id":"NCT03159195"}}NCT03159195) collected real-world outcomes data for palbociclib-treated patients in several countries, including Canada. Methods: This retrospective chart review included women with HR+/HER2− ABC/MBC receiving P+L or P+F in Canada. Physicians reviewed medical records for up to 14 patients, abstracting demographic and clinical characteristics, treatment patterns, and clinical outcomes. Progression-free rates (PFRs) and survival rates (SRs) at 6, 12, 18, and 24 months were estimated via Kaplan–Meier analysis. Results: Thirty-three physicians examined medical records for 247 patients (P+L, n = 214; P+F, n = 33). Median follow-up was 8.8 months for P+L and 7.0 months for P+F. Most patients were initiated on palbociclib 125 mg/d (P+L, 90.2%; P+F, 84.8%). Doses were reduced in 16.6% of P+L and 14.3% of P+F patients initiating palbociclib at 125 mg/d. The PFR for P+L was 90.3% at 12 months and 78.2% at 18 months; corresponding SRs were 95.6% and 93.0%. For P+F, 6-month PFR was 91.0%; 12-month SR was 100.0%. Conclusions: Dose reduction rates were low and PFR and SR were high in this Canadian real-world assessment of P+L and P+F treatments, suggesting that palbociclib combinations are well tolerated and effective.     

Validation of PATHFx 2.0: An open-source tool for estimating survival in patients undergoing pathologic fracture fixation

Treatment decisions in patients with metastatic bone disease rely on accurate survival estimation. We developed the original PATHFx models using expensive, proprietary software and now seek to provide a more cost-effective solution. Using open-source machine learning software to create PATHFx version 2.0, we asked whether PATHFx 2.0 could be created using open-source methods and externally validated in two unique patient populations. The training set of a well-characterized, database records of 189 patients and the bnlearn package within R Version 3.5.1 (R Foundation for Statistical Computing), was used to establish a series of Bayesian belief network models designed to predict survival at 1, 3, 6, 12, 18, and 24 months. Each was externally validated in both a Scandinavian (n = 815 patients) and a Japanese (n = 261 patients) data set. Brier scores and receiver operating characteristic curves to assessed discriminatory ability. Decision curve analysis (DCA) evaluated whether models should be used clinically. DCA showed that the model should be used clinically at all time points in the Scandinavian data set. For the 1-month time point, DCA of the Japanese data set suggested to expect better outcomes assuming all patients will survive greater than 1 month. Brier scores for each curve demonstrate that the models are accurate at each time point. Statement of Clinical Significance: we successfully transitioned to PATHFx 2.0 using open-source software and externally validated it in two unique patient populations, which can be used as a cost-effective option to guide surgical decisions in patients with metastatic bone disease.