Construction of a Prognostic Model for Predicting Colorectal Cancer Prognosis and Response to Immunotherapy Based on Cuproptosis-Associated lncRNAs

Targeting cuproptosis with nano material: new way to enhancing the efficacy of immunotherapy in colorectal cancer

Colorectal cancer has emerged as one of the predominant malignant tumors globally. Immunotherapy, as a novel therapeutic methodology, has opened up new possibilities for colorectal cancer patients. However, its actual clinical efficacy requires further enhancement. Copper, as an exceptionally crucial trace element, can influence various signaling pathways, gene expression, and biological metabolic processes in cells, thus playing a critical role in the pathogenesis of colorectal cancer. Recent studies have revealed that cuproptosis, a novel mode of cell death, holds promise to become a potential target to overcome resistance to colorectal cancer immunotherapy. This shows substantial potential in the combination treatment of colorectal cancer. Conveying copper into tumor cells via a nano-drug delivery system to induce cuproptosis of colorectal cancer cells could offer a potential strategy for eliminating drug-resistant colorectal cancer cells and vastly improving the efficacy of immunotherapy while ultimately destroy colorectal tumors. Moreover, combining the cuproptosis induction strategy with other anti-tumor approaches such as photothermal therapy, photodynamic therapy, and chemodynamic therapy could further enhance its therapeutic effect. This review aims to illuminate the practical significance of cuproptosis and cuproptosis-inducing nano-drugs in colorectal cancer immunotherapy, and scrutinize the current challenges and limitations of this methodology, thereby providing innovative thoughts and references for the advancement of cuproptosis-based colorectal cancer immunotherapy strategies.

Repositioning fluphenazine as a cuproptosis-dependent anti-breast cancer drug candidate based on TCGA database

Breast cancer is one of the most prevalent malignancies among women. Enhancing the prognosis is an effective approach to enhance the survival rate of breast cancer. Cuproptosis, a copper-dependent programmed cell death process, has been associated with patient prognosis. Inducing cuproptosis is a promising approach for therapy. However, there is currently no anti-breast cancer drug that induces cuproptosis. In this study, we repositioned the clinical drug fluphenazine as a potential agent for breast cancer treatment by inducing cuproptosis. Firstly, we utilized the Cancer Genome Atlas (TCGA) database and Connectivity Map (CMap) database to identify 22 potential compounds with anti-breast cancer activity through inducing cuproptosis. Subsequently, our findings demonstrated that fluphenazine effectively suppressed the viability of MCF-7 cells. Fluphenazine also significantly inhibited the viability of triple negative breast cancer cells MDA-MB-453 and MDA-MB-231. Furthermore, our study revealed that fluphenazine significantly down-regulated the expression of potential prognostic biomarkers associated with cuproptosis, increased copper ion levels, and reduced intracellular pyruvate accumulation. Additionally, it up-regulated the expression of FDX1 at both the mRNA and protein levels, which has been reported to play a crucial role in the induction of cuproptosis. These findings suggest that fluphenazine has the potential to be used as an anti-breast cancer drug by inducing cuproptosis. Therefore, this research provides an insight for the development of novel cuproptosis-dependent anti-cancer agents.

Relationships of SIGLEC family-related lncRNAs with clinical prognosis and tumor immune microenvironment in ovarian cancer

Long non-coding RNAs (lncRNAs) and Sialic acid-binding immunoglobulin-type lectin (SIGLEC) family members play an important role in proliferation, apoptosis, immune-cell activation and tumor development. However, the relationships of SIGLEC family-related lncRNAs with clinical prognosis and tumor immune microenvironment in ovarian cancer (OC) are still unclear. 426 SIGLEC family-related lncRNAs were obtained according to the screening criteria R > 0.4 and p < 0.05 using Pearson correlation analysis. A risk model contained AL133279.1, AL021878.2, AC078788.1, AC039056.2, AC008750.1 and AC007608.3 was conducted based on the univariate Cox regression analysis, a least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox regression analyses. OC patient were divided into high-and low-risk group based on the median riskscore. K-M curve and ROC curve revealed that risk model has an abuset prognostic potential for OC patients. Moreover, we successfully validated the prognostic value of the model in the internal datasets, external datasets and clinical sample dataset. Finally, we found that the riskscore was positively correlated with the vast majority of immune cell infiltration. In conclusion, our research identified that a novel SIGLEC family-related lncRNAs risk model to predict the prognosis of OC patients. SIGLEC family-related lncRNAs risk model also has a positive relationship with the tumor immune microenvironment of OC, which may provide a new direction for immunotherapy of OC.