Interrogation of transcriptomic changes associated with drug-induced hepatic sinusoidal dilatation in colorectal cancer

Drug-related sinusoidal dilatation (SD) is a common form of hepatotoxicity associated with oxaliplatin-based chemotherapy used prior to resection of colorectal liver metastases (CRLM). Recently, hepatic SD has also been associated with anti-delta like 4 (DLL4) cancer therapies targeting the NOTCH pathway. To investigate the hypothesis that NOTCH signaling plays an important role in drug-induced SD, gene expression changes were examined in livers from anti-DLL4 and oxaliplatin-induced SD in non-human primate (NHP) and patients, respectively. Putative mechanistic biomarkers of bevacizumab (bev)-mediated protection against oxaliplatin-induced SD were also investigated. RNA was extracted from whole liver sections or centrilobular regions by laser-capture microdissection (LCM) obtained from NHP administered anti-DLL4 fragment antigen-binding (F(ab’)2 or patients with CRLM receiving oxaliplatin-based chemotherapy with or without bev. mRNA expression was quantified using high-throughput real-time quantitative PCR. Significance analysis was used to identify genes with differential expression patterns (false discovery rate (FDR) < 0.05). Eleven (CCL2, CCND1, EFNB2, ERG, ICAM1, IL16, LFNG, NOTCH1, NOTCH4, PRDX1, and TGFB1) and six (CDH5, EFNB2, HES1, IL16, MIK67, HES1 and VWF) candidate genes were differentially expressed in the liver of anti-DLL4- and oxaliplatin-induced SD, respectively. Addition of bev to oxaliplatin-based chemotherapy resulted in differential changes in hepatic CDH5, HEY1, IL16, JAG1, MMP9, NOTCH4 and TIMP1 expression. This work implicates NOTCH and IL16 pathways in the pathogenesis of drug-induced SD and further explains the hepato-protective effect of bev in oxaliplatin-induced SD observed in CRLM patients

Molecular imaging in the development of a novel treatment paradigm for glioblastoma (GBM): an integrated multidisciplinary commentary.

Current therapeutic strategies against glioblastoma (GBM) have failed to prevent disease progression and recurrence effectively. The part played by molecular imaging (MI) in the development of novel therapies has gained increasing traction in recent years. For the first time, using expertise from an integrated multidisciplinary group of authors, herein we present a comprehensive evaluation of state-of-the-art GBM imaging and explore how advances facilitate the emergence of new treatment options. We propose a novel next-generation treatment paradigm based on the targeting of multiple hallmarks of cancer evolution that will heavily rely on MI

Interrogating open issues in cancer precision medicine with patient-derived xenografts.

Patient-derived xenografts (PDXs) have emerged as an important platform to elucidate new treatments and biomarkers in oncology. PDX models are used to address clinically relevant questions, including the contribution of tumour heterogeneity to therapeutic responsiveness, the patterns of cancer evolutionary dynamics during tumour progression and under drug pressure, and the mechanisms of resistance to treatment. The ability of PDX models to predict clinical outcomes is being improved through mouse humanization strategies and the implementation of co-clinical trials, within which patients and PDXs reciprocally inform therapeutic decisions. This Opinion article discusses aspects of PDX modelling that are relevant to these questions and highlights the merits of shared PDX resources to advance cancer medicine from the perspective of EurOPDX, an international initiative devoted to PDX-based research