A novel network-based method identifies a cuproplasia-related pan-cancer gene signature to predict patient outcome.

Copper is a vital micronutrient involved in many biological processes and is an essential component of tumour cell growth and migration. Copper influences tumour growth through a process called cuproplasia, defined as abnormal copper-dependent cell-growth and proliferation. Copper-chelation therapy targeting this process has demonstrated efficacy in several clinical trials against cancer. While the molecular pathways associated with cuproplasia are partially known, genetic heterogeneity across different cancer types has limited the understanding of how cuproplasia impacts patient survival. Utilising RNA-sequencing data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets, we generated gene regulatory networks to identify the critical cuproplasia-related genes across 23 different cancer types. From this, we identified a novel 8-gene cuproplasia-related gene signature associated with pan-cancer survival, and a 6-gene prognostic risk score model in low grade glioma. These findings highlight the use of gene regulatory networks to identify cuproplasia-related gene signatures that could be used to generate risk score models. This can potentially identify patients who could benefit from copper-chelation therapy and identifies novel targeted therapeutic strategies.

IGF2BP1 is the first positive marker for anaplastic thyroid carcinoma diagnosis.

Anaplastic thyroid carcinomas (ATC) are rare, but represent the most lethal malignancy of the thyroid. Selective molecular markers and drivers distinguishing ATC from other thyroid carcinomas of follicular origin remain largely unknown, limiting advances in diagnosis and treatment. In a retrospective study, we analyzed gene expression in 36 ATC, 18 poorly differentiated, 132 papillary, and 55 follicular thyroid carcinoma, as well as 124 paired and unpaired normal thyroid tissues in three independent cohorts by RNA-sequencing and immunohistochemistry. RNA-sequencing data in the test cohort suggested selective ATC protein biomarkers. Evaluation of these revealed that ATCs are characterized by the de novo expression of various testis antigens, including melanoma-associated antigen A3 (MAGEA3), but most importantly the oncofetal IGF2 mRNA binding protein 1 (IGF2BP1). Shallow whole genome sequencing essentially excluded that IGF2BP1 upregulation results from gene copy number alterations. Immunohistochemical analyses in all three tumor cohorts confirmed the selective de novo expression of IGF2BP1 protein in ATC. In sum, 75% (27/36) of all tested ATC and 0.5% (1/204) of poorly and well-differentiated thyroid carcinoma tissue samples were positive for IGF2BP1 protein. This indicates that IGF2BP1 protein expression identifies ATC with a diagnostic odds ratio of 612 (95% CI: 74.6-5021). In addition, we found that MAGEA3 is exclusively, although less consistently upregulated in ATC, presenting with an odds ratio of 411 (95% CI: 23.8-7098.7). Importantly, we provide confirmatory evidence that IGF2BP1 and MAGEA3 expression distinguishes ATC from poorly differentiated thyroid carcinoma. IGF2BP1 furthermore identified ATC foci within low-grade follicular thyroid carcinoma. In conclusion, IGF2BP1 represents the most promising single-gene marker available for ATC, followed by MAGEA3, improving on current techniques. Robust markers are essential to help distinguish this high-grade malignancy from other thyroid carcinomas, to guide surgical decision making, therapy and post-resection/therapy monitoring strategies.

Hyaluronic Acid within Self-Assembling Nanoparticles: Endless Possibilities for Targeted Cancer Therapy.

Self-assembling nanoparticles (SANPs) based on hyaluronic acid (HA) represent unique tools in cancer therapy because they combine the HA targeting activity towards cancer cells with the advantageous features of the self-assembling nanosystems, i.e., chemical versatility and ease of preparation and scalability. This review describes the key outcomes arising from the combination of HA and SANPs, focusing on nanomaterials where HA and/or HA-derivatives are inserted within the self-assembling nanostructure. We elucidate the different HA derivatization strategies proposed for this scope, as well as the preparation methods used for the fabrication of the delivery device. After showing the biological results in the employed in vivo and in vitro models, we discussed the pros and cons of each nanosystem, opening a discussion on which approach represents the most promising strategy for further investigation and effective therapeutic protocol development.