Comprehensive Profiling Reveals Prognostic and Immunogenic Characteristics of Necroptosis in Soft Tissue Sarcomas

Revealing the potential of necroptosis-related genes in prognosis, immune characteristics, and treatment strategies for head and neck squamous cell carcinoma

Necroptosis is a recently discovered apoptotic mechanism that has been linked to tumor formation, prognosis, and treatment response. However, the relationship between the TME and NRGs remains unclear. In this study, we analyzed the expression patterns of NRGs in 769 HNSCC cases from two distinct data sets. Our findings revealed distinct genetic groups and a correlation between patient clinical features, prognosis, TME cell infiltration characteristics, and NRG alterations. We then developed an NRG model to predict OS and confirmed its accuracy in predicting OS in HNSCC patients. Moreover, we have devised a precise nomogram that enhances the clinical utility of the NRG model substantially. The low-risk group had a better OS, and they were associated with immune suppression, more mutated genes, and higher TIDE scores. The risk score also had a significant correlation with the CSC index and susceptibility to anti-tumor agents. Our study provides insights into how NRGs affect prognosis, clinically significant features, TME, and immunotherapy response in HNSCC. With a better knowledge of NRGs in HNSCC, we could assess the prognosis and develop immunotherapy regimens that are more successful at opening up new doors.

Integrative analysis of TROAP with molecular features, carcinogenesis, and related immune and pharmacogenomic characteristics in soft tissue sarcoma

Soft tissue sarcoma (STS) is an uncommon malignancy that often carries a grim prognosis. Trophinin-associated protein (TROAP) is augmented in a variety of tumors and can affect tumor proliferation. Nevertheless, the prognostic value and specific functions of TROAP in STS are still vague. Herein, we display that TROAP exhibits an augmented trend in STS, and its elevation correlates with a poor prognosis of STS. Furthermore, its reduction is related to increased immune cell infiltration, enhanced stroma, and elevation of immune activation. Meanwhile, the TROAP-derived genomic signature is validated to predict patient prognosis, immunotherapy, and drug response reliably. A nomogram constructed based on age, metastatic status, and a TROAP-derived risk score of an STS individual could be used to quantify the survival probability of STS. In addition, in vitro experiments have demonstrated that TROAP is overexpressed in STS, and the downregulation of TROAP could affect the proliferation, migration, metastasis, and cell cycle of STS cells. In summary, the TROAP expression is elevated in STS tissues and cells, which is related to the poor prognosis and malignant biological behaviors of STS. It could act as a potential prognostic biomarker for diagnosis and treatment of STS.

Necroptosis in the sarcoma immune microenvironment: From biology to therapy

Apoptosis resistance remains a major obstacle to treatment failure in sarcoma. Necroptosis is a caspase-independent programmed cell death, investigated as a novel strategy to eradicate anti-apoptotic tumor cells. The process is mediated by the receptor-interacting proteins kinase family and mixed lineage kinase domain-like proteins, which is morphologically similar to necrosis. Recent studies suggest that necroptosis in the tumor microenvironment has pro- or anti-tumor effects on immune response and cancer development. Necroptosis-related molecules display a remarkable value in prognosis prediction and therapeutic response evaluation of sarcoma. Furthermore, the induction of tumor necroptosis has been explored as a feasible therapeutic strategy against sarcoma and to synergize with immunotherapy. This review discusses the dual roles of necroptosis in the immune microenvironment and tumor progression, and explores the potential of necroptosis as a new target for sarcoma treatment.

Integrated analysis of necroptosis-related genes for evaluating immune infiltration and colon cancer prognosis

Background

Colon cancer (CC) is the second most common gastrointestinal malignancy. About one in five patients have already developed distant metastases at the time of initial diagnosis, and up to half of patients develop distant metastases from initial local disease, which leads to a poor prognosis for CC patients. Necroptosis plays a key role in promoting tumor growth in different tumors. The purpose of this study was to construct a prognostic model composed of necroptosis-related genes (NRGs) in CC.

Methods

The Cancer Genome Atlas was used to obtain information on clinical features and gene expression. Gene expression differential analysis, weighted gene co-expression network analysis, univariate Cox regression analysis and the least absolute shrinkage and selection operator regression algorithm were utilized to identify prognostic NRGs. Thereafter, a risk scoring model was established based on the NRGs. Biological processes and pathways were identified by gene ontology and gene set enrichment analysis (GSEA). Further, protein-protein interaction and ceRNA networks were constructed based on mRNA-miRNA-lncRNA. Finally, the effect of necroptosis related risk score on different degrees of immune cell infiltration was evaluated.

Results

CALB1, CHST13, and SLC4A4 were identified as NRGs of prognostic significance and were used to establish a risk scoring model. The time-dependent receiver operating characteristic curve analysis revealed that the model could well predict the 1-, 3-, and 5-year overall survival (OS). Further, GSEA suggested that the NRGs may participate in biological processes, such as the WNT pathway and JAK-Stat pathway. Eight key hub genes were identified, and a ceRNA regulatory network, which comprised 1 lncRNA, 5 miRNAs and 3 mRNAs, was constructed. Immune infiltration analysis revealed that the low-risk group had significantly higher immune-related scores than the high-risk group. A nomogram of the model was constructed based on the risk score, necroptosis, and the clinicopathological features (age and TNM stage). The calibration curves implied that the model was effective at predicting the 1-, 3-, and 5-year OS of CC.

Conclusion

Our NRG-based prognostic model can assist in the evaluation of CC prognosis and the identification of therapeutic targets for CC.

Comprehensive analysis of a novel cuproptosis-related lncRNA signature associated with prognosis and tumor matrix features to predict immunotherapy in soft tissue carcinoma

Background: A crucial part of the malignant processes of soft tissue sarcoma (STS) is played by cuproptosis and lncRNAs. However, the connection between cuproptosis-related lncRNAs (CRLs) and STS is nevertheless unclear. As a result, our objective was to look into the immunological activity, clinical significance, and predictive accuracy of CRLs in STS. Methods: The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, respectively, provided information on the expression patterns of STS patients and the general population. Cuproptosis-related lncRNA signature (CRLncSig) construction involved the univariate, multivariate, and least absolute shrinkage and selection operator Cox regression analysis. The predictive performance of the CRLncSig was evaluated using a serial analysis. Further research was done on the connections between the CRLncSig and the tumor immune milieu, somatic mutation, immunotherapy response, and chemotherapeutic drug susceptibility. Notably, an in vitro investigation served to finally validate the expression of the hallmark CRLs. Results: A novel efficient CRLncSig composed of seven CRLs was successfully constructed. Additionally, the low-CRLncSig group's prognosis was better than that of the high-CRLncSig group's based on the new CRLncSig. The innovative CRLncSig then demonstrated outstanding, consistent, and independent prognostic and predictive usefulness for patients with STS, according to the evaluation and validation data. The low-CRLncSig group's patients also displayed improved immunoreactivity phenotype, increased immune infiltration abundance and checkpoint expression, and superior immunotherapy response, whereas those in the high-CRLncSig group with worse immune status, increased tumor stemness, and higher collagen levels in the extracellular matrix. Additionally, there is a noticeable disparity in the sensitivity of widely used anti-cancer drugs amongst various populations. What's more, the nomogram constructed based on CRLncSig and clinical characteristics of patients also showed good predictive ability. Importantly, Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR) demonstrated that the signature CRLs exhibited a significantly differential expression level in STS cell lines. Conclusion: In summary, this study revealed the novel CRLncSig could be used as a promising predictor for prognosis prediction, immune activity, tumor immune microenvironment, immune response, and chemotherapeutic drug susceptibility in patients with STS. This may provide an important direction for the clinical decision-making and personalized therapy of STS.

Development of necroptosis-related gene signature to predict the prognosis of colon adenocarcinoma

Colon adenocarcinoma (COAD) is a common malignancy and has a high mortality rate. However, the current tumor node metastasis (TNM) staging system is inadequate for prognostic assessment of COAD patients. Therefore, there is an urgent need to identify reliable biomarkers for the prognosis COAD patients. The aberrant expression of necroptosis-related genes (NRGs) is reported to be associated with tumorigenesis and metastasis. In the present work, we compared the expression profiles of NRGs between COAD patients and normal individuals. Based on seven differentially expressed NRGs, a risk score was defined to predict the prognosis of COAD patients. The validation results from both training and independent external cohorts demonstrated that the risk score is able to distinguish the high and low risk COAD patients with higher accuracies, and is independent of the other clinical factors. To facilitate its clinical use, by integrating the proposed risk score, a nomogram was built to predict the risk of individual COAD patients. The C-index of the nomogram is 0.75, indicating the reliability of the nomogram in predicting survival rates. Furthermore, two candidate drugs, namely dapsone and xanthohumol, were screed out and validated by molecular docking, which hold the potential for the treatment of COAD. These results will provide novel clues for the diagnosis and treatment of COAD.

Characterizing the prognostic and therapeutic value of necroptosis in sarcoma based on necroptosis subtypes

Necroptosis, a type of necrotic cell death independent of caspase regulation, is mainly mediated by receptor interacting serine/threonine kinase 1 (RIPK1), receptor interacting serine/threonine kinase 3 (RIPK3) and mixed lineage kinase domain-like (MLKL). Necroptosis plays an essential role in many tumors. However, the potential roles of necroptosis in tumor microenvironment (TME) of sarcoma (SARC) remain unknown. This study analyzed the expression, prognosis, genetic alterations of necroptosis genes in SARC. We identified two subtypes (cluster A and B) by performing unsupervised consensus clustering. Cluster A and B greatly differed in prognosis and immune infiltration, with cluster A showing more favorable prognosis, higher immune infiltration and higher expression levels of necroptosis genes than cluster B. Based on the differentially expressed genes (DEGs) between two clusters, a necroptosis scoring system was developed for predicting overall survival of SARC patients. Patients with high necroptosis score had worse survival status, with a decreased infiltration level of most immune cells. Our findings demonstrated the potential role of necroptosis in regulating tumor microenvironment and the prognostic value of necroptosis-related genes for SARC patients.