Comprehensive analysis of prognostic immune-related genes and drug sensitivity in cervical cancer.

BACKGROUND: Cervical cancer (CC) is the leading cause of cancer-related death in women. A limited number of studies have investigated whether immune-prognostic features can be used to predict the prognosis of CC. This study aimed to develop an improved prognostic risk scoring model (PRSM) for CC based on immune-related genes (IRGs) to predict survival and determine the key prognostic IRGs. METHODS: We downloaded the gene expression profiles and clinical data of CC patients from the TCGA and GEO databases. The ESTIMATE algorithm was used to calculate the score for both immune and stromal cells. Differentially expressed genes (DEGs) in different subpopulations were analyzed by "Limma". A weighted gene co-expression network analysis (WGCNA) was used to establish a DEG co-expression module related to the immune score. Immune-related gene pairs (IRGPs) were constructed, and univariate- and Lasso-Cox regression analyses were used to analyze prognosis and establish a PRSM. A log-rank test was used to verify the accuracy and consistency of the scoring model. Identification of the predicted key IRG was ensured by the application of functional enrichment, DisNor, protein-protein interactions (PPIs) and heatmap. Finally, we extracted the key prognostic immune-related genes from the gene expression data, validated the key genes by immunohistochemistry and analyzed the correlation between their expression and drug sensitivity. RESULTS: A new PRSM was developed based on 22 IRGPs. The prognosis of the low-risk group in the model group (P < 0.001) and validation group (P = 0.039) was significantly better than that in the high-risk group. Furthermore, M1 and M2 macrophages were highly expressed in the low-risk group. Retinoic acid-inducible gene-I (RIG-I)-like receptors (RLRs) and the Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway were significantly enriched in the low-risk group. Three representative genes (CD80, CD28, and LCP2) were markers of CC prognosis. CD80 and CD28 may more prominent represent important indicators to improve patient prognosis. These key genes was positively correlated with drug sensitivity. Finally, we found that differences in the sensitivity to JNK inhibitors could be distinguished based on the use and risk grouping of this PRSM. CONCLUSIONS: The prognostic model based on the IRGs and key genes have potential clinical significance for predicting the prognosis of CC patients, providing a foundation for clinical prognosis judgment and individualized treatment.

Bromodomain and extraterminal (BET) proteins: biological functions, diseases, and targeted therapy.

BET proteins, which influence gene expression and contribute to the development of cancer, are epigenetic interpreters. Thus, BET inhibitors represent a novel form of epigenetic anticancer treatment. Although preliminary clinical trials have shown the anticancer potential of BET inhibitors, it appears that these drugs have limited effectiveness when used alone. Therefore, given the limited monotherapeutic activity of BET inhibitors, their use in combination with other drugs warrants attention, including the meaningful variations in pharmacodynamic activity among chosen drug combinations. In this paper, we review the function of BET proteins, the preclinical justification for BET protein targeting in cancer, recent advances in small-molecule BET inhibitors, and preliminary clinical trial findings. We elucidate BET inhibitor resistance mechanisms, shed light on the associated adverse events, investigate the potential of combining these inhibitors with diverse therapeutic agents, present a comprehensive compilation of synergistic treatments involving BET inhibitors, and provide an outlook on their future prospects as potent antitumor agents. We conclude by suggesting that combining BET inhibitors with other anticancer drugs and innovative next-generation agents holds great potential for advancing the effective targeting of BET proteins as a promising anticancer strategy.

Corrigendum: Long Non-Coding RNAs in the Tumor Immune Microenvironment: Biological Properties and Therapeutic Potential.

[This corrects the article DOI: 10.3389/fimmu.2021.697083.].

Nicotinamide N-Methyltransferase: A Promising Biomarker and Target for Human Cancer Therapy.

Cancer cells typically exhibit a tightly regulated program of metabolic plasticity and epigenetic remodeling to meet the demand of uncontrolled cell proliferation. The metabolic-epigenetic axis has recently become an increasingly hot topic in carcinogenesis and offers new avenues for innovative and personalized cancer treatment strategies. Nicotinamide N-methyltransferase (NNMT) is a metabolic enzyme involved in controlling methylation potential, impacting DNA and histone epigenetic modification. NNMT overexpression has been described in various solid cancer tissues and even body fluids, including serum, urine, and saliva. Furthermore, accumulating evidence has shown that NNMT knockdown significantly decreases tumorigenesis and chemoresistance capacity. Most importantly, the natural NNMT inhibitor yuanhuadine can reverse epidermal growth factor receptor tyrosine kinase inhibitor resistance in lung cancer cells. In this review, we evaluate the possibility of NNMT as a diagnostic biomarker and molecular target for effective anticancer treatment. We also reveal the exact mechanisms of how NNMT affects epigenetics and the development of more potent and selective inhibitors.

Identification and Validation in a Novel Quantification System of Ferroptosis Patterns for the Prediction of Prognosis and Immunotherapy Response in Left- and Right-Sided Colon Cancer.

Background: This study aimed to establish a novel quantification system of ferroptosis patterns and comprehensively analyze the relationship between ferroptosis score (FS) and the immune cell infiltration (ICI) characterization, tumor mutation burden (TMB), prognosis, and therapeutic sensitivity in left-sided and right-sided colon cancers (LCCs and RCCs, respectively). Methods: We comprehensively evaluated the ferroptosis patterns in 444 LCCs and RCCs based on 59 ferroptosis-related genes (FRGs). The FS was constructed to quantify ferroptosis patterns by using principal component analysis algorithms. Next, the prognostic value and therapeutic sensitivities were evaluated using multiple methods. Finally, we performed weighted gene co-expression network analysis (WGCNA) to identify the key FRGs. The IMvigor210 cohort, TCGA-COAD proteomics cohort, and Immunophenoscores were used to verify the predictive abilities of FS and the key FRGs. Results: Two ferroptosis clusters were determined. Ferroptosis cluster B demonstrated a high degree of congenital ICI and stromal-related signal enrichment with a poor prognosis. The prognosis, response of targeted inhibitors, and immunotherapy were significantly different between high and low FS groups (HSG and LSG, respectively). HSG was characterized by high TMB and microsatellite instability-high subtype with poor prognosis. Meanwhile, LSG was more likely to benefit from immunotherapy. ALOX5 was identified as a key FRG based on FS. Patients with high protein levels of ALOX5 had poorer prognoses. Conclusion: This work revealed that the evaluation of ferroptosis subtypes will contribute to gaining insight into the heterogeneity in LCCs and RCCs. The quantification for ferroptosis patterns played a non-negligible role in predicting ICI characterization, prognosis, and individualized immunotherapy strategies.

Long Non-Coding RNAs in the Tumor Immune Microenvironment: Biological Properties and Therapeutic Potential.

Cancer immunotherapy (CIT) is considered a revolutionary advance in the fight against cancer. The complexity of the immune microenvironment determines the success or failure of CIT. Long non-coding RNA (lncRNA) is an extremely versatile molecule that can interact with RNA, DNA, or proteins to promote or inhibit the expression of protein-coding genes. LncRNAs are expressed in many different types of immune cells and regulate both innate and adaptive immunity. Recent studies have shown that the discovery of lncRNAs provides a novel perspective for studying the regulation of the tumor immune microenvironment (TIME). Tumor cells and the associated microenvironment can change to escape recognition and elimination by the immune system. LncRNA induces the formation of an immunosuppressive microenvironment through related pathways, thereby controlling the escape of tumors from immune surveillance and promoting the development of metastasis and drug resistance. Using lncRNA as a therapeutic target provides a strategy for studying and improving the efficacy of immunotherapy.

Exosomes: Powerful weapon for cancer nano-immunoengineering.

Cancer immunotherapy (CIT) that targets the tumor immune microenvironment is regarded as a revolutionary advancement in the fight against cancer. The success and failure of CIT are due to the complexity of the immunosuppressive microenvironment. Cancer nanomedicine is a potential adjuvant therapeutic strategy for immune-based combination therapy. Exosomes are natural nanomaterials that play a pivotal role in mediating intercellular communications and package delivery in the tumor microenvironment. They affect the immune response or the effectiveness of immunotherapy. In particular, exosomal PD-L1 promotes cancer progression and resistance to immunotherapy. Exosomes possess high bioavailability, biological stability, targeting specificity, low toxicity, and immune characteristics, which indicate their potential for cancer therapy. They can be engineered to act as effective cancer therapeutic tools that activate anti-tumor immune response and start immune surveillance. In the current review, we introduce the role of exosomes in a tumor immune microenvironment, highlight the application of engineered exosomes to CIT, and discuss the challenges and prospects for clinical application.

Development and Validation of a Prognostic Signature Based on Immune Genes in Cervical Cancer.

BACKGROUND: Cervical cancer is one of the most common types of gynecological malignancies worldwide. This study aims to develop an immune signature to predict survival in cervical cancer. METHOD: The gene expression data of 296 patients with cervical cancer from The Cancer Genome Atlas database (TCGA) and immune-related genes from the Immunology Database and Analysis Portal (ImmPort) database were included in this study. The immune signature was developed based on prognostic genes. The validation dataset was downloaded from the Gene Expression Omnibus (GEO) database. RESULT: The immune signature namely immune-based prognostic score (IPRS) was developed with 229 genes. Multivariate analysis revealed that the IPRS was an independent prognostic factor for overall survival (OS) and progression-free survival (PFS) in patients with cervical cancer. Patients were stratified into high IPRS and low IPRS groups, and those in the high IPRS group were associated with better survival, which was validated in the validation set. A nomogram with IPRS and stage was constructed to predict mortality in cervical cancer. CONCLUSIONS: We developed a robust prognostic signature IPRS that could be used to predict patients' survival outcome.

Deubiquitinating Enzymes Orchestrate the Cancer Stem Cell-Immunosuppressive Niche Dialogue: New Perspectives and Therapeutic Potential.

Cancer stem cells (CSCs) are sparks for igniting tumor recurrence and the instigators of low response to immunotherapy and drug resistance. As one of the important components of tumor microenvironment, the tumor associated immune microenvironment (TAIM) is driving force for the heterogeneity, plasticity and evolution of CSCs. CSCs create the inhibitory TAIM (ITAIM) mainly through four stemness-related signals (SRSs), including Notch-nuclear factor-κB axis, Hedgehog, Wnt and signal transducer and activator of transcription. Ubiquitination and deubiquitination in proteins related to the specific stemness of the CSCs have a profound impact on the regulation of ITAIM. In regulating the balance between ubiquitination and deubiquitination, it is crucial for deubiquitinating enzymes (DUBs) to cleave ubiquitin chains from substrates. Ubiquitin-specific peptidases (USPs) comprise the largest family of DUBs. Growing evidence suggests that they play novel functions in contribution of ITAIM, including regulating tumor immunogenicity, activating stem cell factors, upregulating the SRSs, stabilizing anti-inflammatory receptors, and regulating anti-inflammatory cytokines. These overactive or abnormal signaling may dampen antitumor immune responses. The inhibition of USPs could play a regulatory role in SRSs and reversing ITAIM, and also have great potential in improving immune killing ability against tumor cells, including CSCs. In this review, we focus on the USPs involved in CSCs signaling pathways and regulating ITAIM, which are promising therapeutic targets in antitumor therapy.