Co-Clinical Trials: An Innovative Drug Development Platform for Cholangiocarcinoma

Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging

Preclinical imaging is a critical component in translational research with significant complexities in workflow and site differences in deployment. Importantly, the National Cancer Institute's (NCI) precision medicine initiative emphasizes the use of translational co-clinical oncology models to address the biological and molecular bases of cancer prevention and treatment. The use of oncology models, such as patient-derived tumor xenografts (PDX) and genetically engineered mouse models (GEMMs), has ushered in an era of co-clinical trials by which preclinical studies can inform clinical trials and protocols, thus bridging the translational divide in cancer research. Similarly, preclinical imaging fills a translational gap as an enabling technology for translational imaging research. Unlike clinical imaging, where equipment manufacturers strive to meet standards in practice at clinical sites, standards are neither fully developed nor implemented in preclinical imaging. This fundamentally limits the collection and reporting of metadata to qualify preclinical imaging studies, thereby hindering open science and impacting the reproducibility of co-clinical imaging research. To begin to address these issues, the NCI co-clinical imaging research program (CIRP) conducted a survey to identify metadata requirements for reproducible quantitative co-clinical imaging. The enclosed consensus-based report summarizes co-clinical imaging metadata information (CIMI) to support quantitative co-clinical imaging research with broad implications for capturing co-clinical data, enabling interoperability and data sharing, as well as potentially leading to updates to the preclinical Digital Imaging and Communications in Medicine (DICOM) standard.

Advances in 3D culture systems for therapeutic discovery and development in brain cancer

This review focuses on recent advances in 3D culture systems that promise more accurate therapeutic models of the glioblastoma multiforme (GBM) tumor microenvironment (TME), such as the unique anatomical, cellular, and molecular features evident in human GBM. The key components of a GBM TME are outlined, including microbiomes, vasculature, extracellular matrix (ECM), infiltrating parenchymal and peripheral immune cells and molecules, and chemical gradients. 3D culture systems are evaluated against 2D culture systems and in vivo animal models. The main 3D culture techniques available are compared, with an emphasis on identifying key gaps in knowledge for the development of suitable platforms to accurately model the intricate components of the GBM TME.

RTK25: A Comprehensive Molecular Profiling Strategy in Cholangiocarcinoma Using an Integrated Bioinformatics Approach

Cholangiocarcinoma (CCA) is a heterogeneous group of malignancies that primarily originate from the bile duct. Tumor heterogeneity is a prime characteristic of CCA and considering the scarcity of approved targeted therapy drugs, this makes precision oncology impractical in CCA. Stratifying patients based on their molecular signature and biomarker-guided therapy may offer a conducive solution. Receptors tyrosine kinases (RTK) are potential targets for novel therapeutic strategies in CCA as RTK signaling is dysregulated in CCA. This study aims to identify targetable RTK profile in CCA using a bioinformatic approach. We discovered that CCA samples could be grouped into molecular subtypes based on the gene expression profile of selected RTKs (RTK25). Using the RTK25 gene list, we discovered five distinct molecular subtypes of CCA in this cohort. Tyrosine kinase inhibitors that target each RTK profile and their subsequent molecular signatures were also discovered. These results suggest that certain RTKs correlate with each other, indicating that tailored dual inhibition of RTKs may be more favorable than monotherapy. The results from this study can direct future investigative attention towards validating this concept in in vivo and in vitro systems. Ultimately, this will facilitate biomarker-guided clinical trials for the successful approval of novel therapeutic options in CCA.