Necroptosis throws novel insights on patient classification and treatment strategies for hepatocellular carcinoma

Role of N6-methyladenosine RNA modification in cancer

N6-methyladenosine (m6A) is the most abundant modification of RNA in eukaryotic cells. Previous studies have shown that m6A is pivotal in diverse diseases especially cancer. m6A corelates with the initiation, progression, resistance, invasion, and metastasis of cancer. However, despite these insights, a comprehensive understanding of its specific roles and mechanisms within the complex landscape of cancer is still elusive. This review begins by outlining the key regulatory proteins of m6A modification and their posttranslational modifications (PTMs), as well as the role in chromatin accessibility and transcriptional activity within cancer cells. Additionally, it highlights that m6A modifications impact cancer progression by modulating programmed cell death mechanisms and affecting the tumor microenvironment through various cancer-associated immune cells. Furthermore, the review discusses how microorganisms can induce enduring epigenetic changes and oncogenic effect in microorganism-associated cancers by altering m6A modifications. Last, it delves into the role of m6A modification in cancer immunotherapy, encompassing RNA therapy, immune checkpoint blockade, cytokine therapy, adoptive cell transfer therapy, and direct targeting of m6A regulators. Overall, this review clarifies the multifaceted role of m6A modification in cancer and explores targeted therapies aimed at manipulating m6A modification, aiming to advance cancer research and improve patient outcomes.

Quercetin-induced pyroptosis in colon cancer through NEK7-mediated NLRP3 inflammasome-GSDMD signaling pathway activation

Pyroptosis, a gasdermin-mediated lytic cell death, is a new hotspot topic in cancer research, and induction of tumor pyroptosis has emerged as a new target in cancer management. Quercetin (Que), a natural substance, demonstrates promising anticancer action. However, further information is required to fully comprehend the function and mechanism of Que in pyroptosis in colon cancer. This study revealed the underlying mechanism of Que-induced pyroptosis in colon cancer in vitro and in vivo. Que inhibited colon cancer cell growth through gasdermin D (GSDMD)-mediated pyroptosis. Depletion of GSDMD, rather than gasdermin E (GSDME), reversed the cytotoxic effects of Que on colon cancer cells. Que treatment upregulated NIMA-related kinase 7 (NEK7) protein expression, thus facilitating the assembly of the NLRP3 inflammasome and cleavage of GSDMD. NEK7 silencing resulted in colon cancer cell growth in vitro and in vivo. Mechanistically, NEK7 depression restrained the activation of the NLRP3 inflammasome-GSDMD pathway, thus attenuating pyroptosis triggered by Que in colon cancer cells. Furthermore, lower NEK7 and NLRP3 expression levels indicated colon cancer progression. Our results unveiled a novel pattern of anti-colon cancer activity of Que, and activation of NEK7-mediated pyroptosis is potentially a promising therapeutic target for colon cancer, which provides novel experimental proof for the clinical application of Que.

Development of a prognostic Neutrophil Extracellular Traps related lncRNA signature for soft tissue sarcoma using machine learning

Background

Soft tissue sarcoma (STS) is a highly heterogeneous musculoskeletal tumor with a significant impact on human health due to its high incidence and malignancy. Long non-coding RNA (lncRNA) and Neutrophil Extracellular Traps (NETs) have crucial roles in tumors. Herein, we aimed to develop a novel NETsLnc-related signature using machine learning algorithms for clinical decision-making in STS.

Methods

We applied 96 combined frameworks based on 10 different machine learning algorithms to develop a consensus signature for prognosis and therapy response prediction. Clinical characteristics, univariate and multivariate analysis, and receiver operating characteristic curve (ROC) analysis were used to evaluate the predictive performance of our models. Additionally, we explored the biological behavior, genomic patterns, and immune landscape of distinct NETsLnc groups. For patients with different NETsLnc scores, we provided information on immunotherapy responses, chemotherapy, and potential therapeutic agents to enhance the precision medicine of STS. Finally, the gene expression was validated through real-time quantitative PCR (RT-qPCR).

Results

Using the weighted gene co-expression network analysis (WGCNA) algorithm, we identified NETsLncs. Subsequently, we constructed a prognostic NETsLnc signature with the highest mean c-index by combining machine learning algorithms. The NETsLnc-related features showed excellent and stable performance for survival prediction in STS. Patients in the low NETsLnc group, associated with improved prognosis, exhibited enhanced immune activity, immune infiltration, and tended toward an immunothermal phenotype with a potential immunotherapy response. Conversely, patients with a high NETsLnc score showed more frequent genomic alterations and demonstrated a better response to vincristine treatment. Furthermore, RT-qPCR confirmed abnormal expression of several signature lncRNAs in STS.

Conclusion

In conclusion, the NETsLnc signature shows promise as a powerful approach for predicting the prognosis of STS. which not only deepens our understanding of STS but also opens avenues for more targeted and effective treatment strategies.

The implication of necroptosis-related lncRNAs in orchestrating immune infiltration and predicting therapeutic efficacy in colon adenocarcinoma: an integrated bioinformatic analysis with preliminarily experimental validation

Background: Necroptosis contributes significantly to colon adenocarcinoma (COAD). We aim to assess the relationship between immunoinfiltration and stemness in COAD patients through the development of a risk score profile using necroptosis-related long noncoding RNAs (NRLs). Methods: Our study was based on gene expression data and relevant clinical information from The Cancer Genome Atlas (TCGA). Necroptosis-related genes (NRGs) were obtained from the Kyoto Encyclopedia of Genes and Genome (KEGG) database. Pearson correlation analysis, Cox regression, and least absolute shrinkage and selection operator (LASSO) regression were used to determine the NRL prognositic signature (NRLPS). NRLs expression was examined using qRT-PCR method. Several algorithms were used to identify relationships between immune cell infiltration and NRLPS risk scores. Further analysis of somatic mutations, tumor stemness index (TSI), and drug sensitivity were also explored. Results: To construct NRLPS, 15 lncRNAs were investigated. Furthermore, NRLPS patients with high-risk subgroups had lower survival rates than that of patients with low-risk subgroups. Using GSEA analysis, NRL was found to be enriched in Notch, Hedgehog and Smoothened pathways. Immune infiltration analysis showed significant differences in CD8+ T cells, dendritic cell DCs, and CD4+ T cells between the two risk groups. In addition, our NRLPS showed a relevance with the regulation of tumor microenvironment, tumor mutation burden (TMB) and stemness. Finally, NRLPS demonstrated potential applications in predicting the efficacy of immunotherapy and chemotherapy in patients with COAD. Conclusion: Based on NRLs, a prognostic model was developed for COAD patients that allows a personalized tailoring immunotherapy and chemotherapy to be tailored.

Targeting of non-apoptotic cancer cell death mechanisms by quercetin: Implications in cancer therapy

The ultimate goal of cancer treatment is to kill cancer cells, based on the use of various therapeutic agents, such as chemotherapy, radiotherapy, or targeted therapy drugs. Most drugs exert their therapeutic effects on cancer by targeting apoptosis. However, alterations in apoptosis-related molecules and thus assisting cells to evade death, eventually lead to tumor cell resistance to therapeutic drugs. The increased incidence of non-apoptotic cell death modes such as induced autophagy, mitotic catastrophe, senescence, and necrosis is beneficial to overcoming multidrug resistance mediated by apoptosis resistance in tumor cells. Therefore, investigating the function and mechanism of drug-induced non-apoptotic cell death modes has positive implications for the development of new anti-cancer drugs and therapeutic strategies. Phytochemicals show strong potential as an alternative or complementary medicine for alleviating various types of cancer. Quercetin is a flavonoid compound widely found in the daily diet that demonstrates a significant role in inhibiting numerous human cancers. In addition to direct pro-tumor cell apoptosis, both in vivo and in vitro experiments have shown that quercetin exerts anti-tumor properties by triggering diverse non-apoptotic cell death modes. This review summarized the current status of research on the molecular mechanisms and targets through which quercetin-mediated non-apoptotic mode of cancer cell death, including autophagic cell death, senescence, mitotic catastrophe, ferroptosis, necroptosis, etc.