Identification of medicinal compounds as potential inhibitors for mutated isocitrate dehydrogenases against chondrosarcoma

Chondrosarcoma Resistance to Radiation Therapy: Origins and Potential Therapeutic Solutions

Chondrosarcoma is a malignant cartilaginous tumor that is particularly chemoresistant and radioresistant to X-rays. The first line of treatment is surgery, though this is almost impossible in some specific locations. Such resistances can be explained by the particular composition of the tumor, which develops within a dense cartilaginous matrix, producing a resistant area where the oxygen tension is very low. This microenvironment forces the cells to adapt and dedifferentiate into cancer stem cells, which are described to be more resistant to conventional treatments. One of the main avenues considered to treat this type of tumor is hadrontherapy, in particular for its ballistic properties but also its greater biological effectiveness against tumor cells. In this review, we describe the different forms of chondrosarcoma resistance and how hadrontherapy, combined with other treatments involving targeted inhibitors, could help to better treat high-grade chondrosarcoma.

Identification of novel mycocompounds as inhibitors of PI3K/AKT/mTOR pathway against RCC

PI3K/AKT/mTOR pathway is one of the frequently disrupted signaling pathways in renal cell carcinoma (RCC) that plays a significant role in tumor formation, disease progression and therapeutic resistance. Therefore, novel natural molecules targeting the critical proteins of this pathway will provide the best alternative to existing drugs, which are toxic and develops resistance. Recent studies have recognized the anti-cancer therapeutic potential of mycocompounds. The current study is focused on screening various mycocompounds from Astraeus hygrometricus against key cancer signaling proteins phosphoinositide 3-kinase (PI3K), protein kinase B, PKB (AKT1) and mammalian target of rapamycin (mTOR). We also studied in-silico cancer cells cytotoxicity and ADMET (absorption, distribution, metabolism, excretion and toxicity) profiles to elucidate the molecular mechanism against RCC and also to uncover the pharmacokinetic profile of these compounds. Astrakurkurone and Ergosta-4,6, 8-(14) 22-tetraene-3-one were the two most efficacious compounds with highest interaction scores and bonding. These compounds were both active against RCC4 and VMRC-RCZ cell lines of RCC. The ADME profiles of both were satisfactory based on druglikeness and bioavailability score criteria. Thus, this proposed study identified astrakurkurone and ergosta-4,6, 8-(14) 22-tetraene-3-one as potential anticancer drug candidates, and provides comparative structural insight into their binding to the 3 protein kinases.

Crosstalk of Redox-Related Subtypes, Establishment of a Prognostic Model and Immune Responses in Endometrial Carcinoma

Simple Summary

In order to explore the role of redox as a prognostic indicator in endometrial carcinoma (EC), we detected the expression patterns of 55 redox-related genes (RRGs) in EC cohorts from public databases. Performing consensus cluster algorithm, we determined four molecular subclusters based on RRGs which had significant differences in overall survival (OS) and immune activities of EC patients. Furthermore, we developed a prognostic risk model on the basis of the redox-related subtype by stepwise Cox regression analyses. All EC patients were divided into high-risk and low-risk groups according to the median value of risk score. Our proposed model could accurately assess the clinical outcome and had favorable independent ability in EC cases. Moreover, our signature can serve as a predictor for immune status and chemotherapy sensitivity.

Abstract

Redox plays a central part in the pathogeneses and development of tumors. We comprehensively determined the expression patterns of redox-related genes (RRGs) in endometrial carcinoma (EC) cohorts from public databases and identified four different RRG-related clusters. The prognosis and the characteristics of TME cell infiltration of RRGcluster C patients were worse than those of other RRG clusters. When it comes to the gene cluster, there were great differences in clinicopathology traits and immunocyte infiltration. The RRG score was calculated by Cox analyses, and an RRG-based signature was developed. The risk score performed well in the EC cohort. Samples were separated into two risk subgroups with the standard of the value of the median risk score. Low-risk patients had a better prognosis and higher immunogenicity. In addition, RRG score was closely associated with immunophenoscore, microsatellite instability, tumor mutation burden, tumor stem cell index, copy number variation and chemotherapy sensitivity. The nomogram accurately predicted the prognosis of patients, and our model showed better performance than other published models. In conclusion, we built a prognostic model of RRGs which can help to evaluate clinical outcomes and guide more effective treatment.