A Systems-Based Key Innovation-Driven Approach Infers Co-option of Jaw Developmental Programs During Cancer Progression

Usage of the National Cancer Institute Cancer Research Data Commons by Researchers: A Scoping Review of the Literature

PURPOSE

Over the past decade, significant surges in cancer data of all types have happened. To promote sharing and use of these rich data, the National Cancer Institute's Cancer Research Data Commons (CRDC) was developed as a cloud-based infrastructure that provides a large, comprehensive, and expanding collection of cancer data with tools for analysis. We conducted this scoping review of articles to provide an overview of how CRDC resources are being used by cancer researchers.

METHODS

A thorough literature search was conducted to identify all relevant publications. We included publications that directly cited CRDC resources to specifically examine the impact and contributions of CRDC by itself. We summarized the distributions and trends of how CRDC components were used by the research community and discussed current research gaps and future opportunities.

RESULTS

In terms of CRDC resources used by the research community, encouraging trends in utilization were observed, suggesting that CRDC has become an important building block for fostering a wide range of cancer research. We also noted a few areas where current applications are rather lacking and provided insights on how improvements can be made by CRDC and research community.

CONCLUSION

CRDC, as the foundation of a National Cancer Data Ecosystem, will continue empowering the research community to effectively leverage cancer-related data, uncover novel strategies, and address the needs of patients with cancer, ultimately combatting this disease more effectively.

"In the light of evolution:" keratins as exceptional tumor biomarkers

Keratins (KRTs) are the intermediate filament-forming proteins of epithelial cells, classified, according to their physicochemical properties, into "soft" and "hard" keratins. They have a key role in several aspects of cancer pathophysiology, including cancer cell invasion and metastasis, and several members of the KRT family serve as diagnostic or prognostic markers. The human genome contains both, functional KRT genes and non-functional KRT pseudogenes, arranged in two uninterrupted clusters on chromosomes 12 and 17. This characteristic renders KRTs ideal for evolutionary studies. Herein, comprehensive phylogenetic analyses of KRT homologous proteins in the genomes of major taxonomic divisions were performed, so as to fill a gap in knowledge regarding the functional implications of keratins in cancer biology among tumor-bearing species. The differential expression profiles of KRTs in diverse types of cancers were investigated by analyzing high-throughput data, as well. Several KRT genes, including the phylogenetically conserved ones, were found to be deregulated across several cancer types and to participate in a common protein-protein interaction network. This indicates that, at least in cancer-bearing species, these genes might have been under similar evolutionary pressure, perhaps to support the same important function(s). In addition, semantic relations between KRTs and cancer were detected through extensive text mining. Therefore, by applying an integrative in silico pipeline, the evolutionary history of KRTs was reconstructed in the context of cancer, and the potential of using non-mammalian species as model organisms in functional studies on human cancer-associated KRT genes was uncovered.

p73 isoforms meet evolution of metastasis

Cancer largely adheres to Darwinian selection. Evolutionary forces are prominent during metastasis, the final and incurable disease stage, where cells acquire combinations of advantageous phenotypic features and interact with a dynamically changing microenvironment, in order to overcome the metastatic bottlenecks, while therapy exerts additional selective pressures. As a strategy to increase their fitness, tumors often co-opt developmental and tissue-homeostasis programs. Herein, 25 years after its discovery, we review TP73, a sibling of the cardinal tumor-suppressor TP53, through the lens of cancer evolution. The TP73 gene regulates a wide range of processes in embryonic development, tissue homeostasis and cancer via an overwhelming number of functionally divergent isoforms. We suggest that TP73 neither merely mimics TP53 via its p53-like tumor-suppressive functions, nor has black-or-white-type effects, as inferred by the antagonism between several of its isoforms in processes like apoptosis and DNA damage response. Rather, under dynamic conditions of selective pressure, the various p73 isoforms which are often co-expressed within the same cancer cells may work towards a common goal by simultaneously activating isoform-specific transcriptional and non-transcriptional programs. Combinatorial co-option of these programs offers selective advantages that overall increase the likelihood for successfully surpassing the barriers of the metastatic cascade. The p73 functional pleiotropy-based capabilities might be present in subclonal populations and expressed dynamically under changing microenvironmental conditions, thereby supporting clonal expansion and propelling evolution of metastasis. Deciphering the critical p73 isoform patterns along the spatiotemporal axes of tumor evolution could identify strategies to target TP73 for prevention and therapy of cancer metastasis.

Novel integrated workflow allows production and in-depth quality assessment of multifactorial reprogrammed skeletal muscle cells from human stem cells

Skeletal muscle tissue engineering aims at generating biological substitutes that restore, maintain or improve normal muscle function; however, the quality of cells produced by current protocols remains insufficient. Here, we developed a multifactor-based protocol that combines adenovector (AdV)-mediated MYOD expression, small molecule inhibitor and growth factor treatment, and electrical pulse stimulation (EPS) to efficiently reprogram different types of human-derived multipotent stem cells into physiologically functional skeletal muscle cells (SMCs). The protocol was complemented through a novel in silico workflow that allows for in-depth estimation and potentially optimization of the quality of generated muscle tissue, based on the transcriptomes of transdifferentiated cells. We additionally patch-clamped phenotypic SMCs to associate their bioelectrical characteristics with their transcriptome reprogramming. Overall, we set up a comprehensive and dynamic approach at the nexus of viral vector-based technology, bioinformatics, and electrophysiology that facilitates production of high-quality skeletal muscle cells and can guide iterative cycles to improve myo-differentiation protocols.