Immune-related lncRNA classification of head and neck squamous cell carcinoma

lncRNAs'p potential roles in the pathogenesis of cancer via interacting with signaling pathways; special focus on lncRNA-mediated signaling dysregulation in lung cancer

Lung cancer ranks among the most lethal types of cancer globally, with a high occurrence and fatality rate. The spread of cancer to other parts of the body, known as metastasis, is the primary cause of treatment failure and death in lung cancer cases. Current approaches for treating advanced lung cancer typically involve a combination of chemotherapy and targeted therapy. However, the majority of patients ultimately develop resistance to these treatments, leading to a worsened prognosis. In recent years, cancer biology research has predominantly focused on the role of protein-encoding genes in cancer development. Long non-coding RNAs (lncRNAs) are transcripts over 200 nucleotides in length that do not encode proteins but are crucial RNA molecules involved in numerous biological functions. While many functions of lncRNAs remain unknown, some have been linked to human diseases, including cancer. Studies have demonstrated that lncRNAs interact with other large molecules in the cell, such as proteins, DNA, and RNA, influencing various critical aspects of cancer. LncRNAs play a significant role in regulating gene expression and have a crucial function in the transcriptional regulation of cancer cells. They mediate various biological and clinical processes such as invasion, metastasis, apoptosis, and cell proliferation. Dysregulation of lncRNAs has been found to impact the process of carcinogenesis through advanced technologies like RNA sequencing and microarrays. Collectively, these long non-coding RNAs hold promise as potential biomarkers and therapeutic targets for human cancers. In this segment, we provide a comprehensive summary of the literature on the characteristics and formation of lncRNAs, along with an overview of their current known roles in lung cancer.

The lncRNA TRG-AS1 promotes the growth of colorectal cancer cells through the regulation of P2RY10/GNA13

BACKGROUND

The lncRNA TRG-AS1 and its co-expressed gene P2RY10 are important for colorectal cancer (CRC) occurrence and development. The purpose of our research was to explore the roles of TRG-AS1 and P2RY10 in CRC progression.

METHODS

The abundance of TRG-AS1 and P2RY10 in CRC cell lines (HT-29 and LoVo) and normal colon cells FHC was determined and difference between CRC cells and normal cells was compared. LoVo cells were transfected with si-TRG-AS1 and si-P2RY10 constructs. Subsequently, the viability, colony formation, and migration of the transfected cells were analyzed using cell counting kit-8, clonogenicity, and scratch-wound/Transwell® assays, respectively. Cells overexpressing GNA13 were used to further explore the relationship between TRG-AS1 and P2RY10 along with their downstream functions. Finally, nude mice were injected with different transfected cell types to observe tumor formation in vivo.

RESULTS

TRG-AS1 and P2RY10 were significantly upregulated in HT-29 and LoVo compared to FHC cells. TRG-AS1 knockdown and P2RY10 silencing suppressed the viability, colony formation, and migration of LoVo cells. TRG-AS1 knockdown downregulated the expression of P2RY10, GNA12, and GNA13, while P2RY10 silencing downregulated the expression of TRG-AS1, GNA12, and GNA13. Additionally, GNA13 overexpression reversed the cell growth and gene expression changes in LoVo cells induced by TRG-AS1 knockdown or P2RY10 silencing. In vivo experiments revealed that CRC tumor growth was suppressed by TRG-AS1 knockdown and P2RY10 silencing.

CONCLUSIONS

TRG-AS1 knockdown repressed the growth of HT-29 and LoVo by regulating P2RY10 and GNA13 expression.

The Role of CXCL11 and its Receptors in Cancer: Prospective but Challenging Clinical Targets

Chemokine ligand 11 is a member of the CXC chemokine family and exerts its biological function mainly through binding to CXCR3 and CXCR7. The CXCL11 gene is ubiquitously overexpressed in various human malignant tumors; however, its specific mechanisms vary among different cancer types. Recent studies have found that CXCL11 is involved in the activation of multiple oncogenic signaling pathways and is closely related to tumorigenesis, progression, chemotherapy tolerance, immunotherapy efficacy, and poor prognosis. Depending on the specific expression of its receptor subtype, CXCL11 also has a complex 2-fold role in tumours; therefore, directly targeting the structure-function of CXCL11 and its receptors may be a challenging task. In this review, we summarize the biological functions of CXCL11 and its receptors and their roles in various types of malignant tumors and point out the directions for clinical applications.

Development of anoikis-related long non-coding RNA signature associated with prognosis and immune landscape in cutaneous melanoma patients

BACKGROUND

Anoikis is involved in many critical biological processes in tumors; however, function in CM is still unknown. In this study, the relevance between Anoikis-related lncRNAs (ARLs) and the clinicopathological characteristics of patients with CM was comprehensively assessed.

METHODS

Through analysis of TCGA dataset, ARLs were identified by using TCGA dataset. Based on the ARLs, a risk model was established to anticipate the prognosis of patients with CM, besides, the prediction accuracy of the model was evaluated. The immune infiltration landscape of patients with CM was assessed comprehensively, and the correlation between ARLs and immunity was elucidated. Immunotherapy and drug sensitivity analyses were applied to analyze the treatment response in patients with CM with diverse risk scores. Different subgroups were distinguished among the patients using consensus cluster analysis.

RESULTS

A risk model based on six ARLs was set up to obtain an accurate prediction of the prognosis of patients with CM. There were distinctions in the immune landscape among CM patients with diverse risk scores and subgroups. Six prognosis-related ARLs were highly correlated with the number of immune cells. Patients with CM with different risk scores have various sensitivities to immunotherapy and antitumor drug treatments.

CONCLUSION

Our newly risk model associated with ARLs has considerable prognostic value for patients with CM. Not only has the risk model high prediction accuracy but it also indicates the immune status of CM patients, which will provide a new direction for the individualized therapy of patients with CM.

Comprehensive analysis of cuproptosis-related lncRNAs signature to predict prognosis in bladder urothelial carcinoma

BACKGROUND

Cuproptosis-related genes (CRGs) have been recently discovered to regulate the occurrence and development of various tumors by controlling cuproptosis, a novel type of copper ion-dependent cell death. Although cuproptosis is mediated by lipoylated tricarboxylic acid cycle proteins, the relationship between cuproptosis-related long noncoding RNAs (crlncRNAs) in bladder urothelial carcinoma (BLCA) and clinical outcomes, tumor microenvironment (TME) modification, and immunotherapy remains unknown. In this paper, we tried to discover the importance of lncRNAs for BLCA.

METHODS

The BLCA-related lncRNAs and clinical data were first obtained from The Cancer Genome Atlas (TCGA). CRGs were obtained through Coexpression, Cox regression and Lasso regression. Besides, a prognosis model was established for verification. Meanwhile, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, gene ontology (GO) analysis, principal component analysis (PCA), half-maximal inhibitory concentration prediction (IC50), immune status and drug susceptibility analysis were carried out.

RESULTS

We identified 277 crlncRNAs and 16 survival-related lncRNAs. According to the 8-crlncRNA risk model, patients could be divided into high-risk group and low-risk group. Progression-Free-Survival (PFS), independent prognostic analysis, concordance index (C-index), receiver operating characteristic (ROC) curve and nomogram all confirmed the excellent predictive capability of the 8-lncRNA risk model for BLCA. During gene mutation burden survival analysis, noticeable differences were observed in high- and low-risk patients. We also found that the two groups of patients might respond differently to immune targets and anti-tumor drugs.

CONCLUSION

The nomogram with 8-lncRNA may help guide treatment of BLCA. More clinical studies are necessary to verify the nomogram.

LncRNA TRG-AS1 inhibits bone metastasis of breast cancer by the miR-877-5p/WISP2 axis

TRG-AS1 has been proved to inhibit cancer progression, whereas its effect on bone metastases of breast cancer is unknown. In this study, we determined breast cancer patients with disease free survival is longer in breast cancer patients with high TRG-AS1 expression. Moreover, TRG-AS1 was downregulated in breast cancer tissues and even lower in bone metastatic tumor tissues. Compared with parental breast cancer cell MDA-MB-231, TRG-AS1 expression was downregulated in MDA-MB-231-BO cells with strong bone-metastatic characteristics. Next, the binding sites of miR-877-5p on TRG-AS1 and WISP2 mRNA were predicted and result showed that miR-877-5p could bind to 3'UTR of TRG-AS1 and WISP2. Subsequently, BMMs and MC3T3-E1 cells were cultured in the conditioned media of MDA-MB-231 BO cells transfected with TRG-AS1 overexpression vector, shRNA and/or miR-877-5p mimics or inhibitor and/or overexpression vector and small interfering RNA of WISP2. TRG-AS1 silencing or miR-877-5p overexpression promoted MDA-MB-231 BO cell proliferation and invasion. TRG-AS1 overexpressing reduced TRAP positive cells, decreased TRAP, Cathepsin K, c-Fos, NFATc1 and AREG expression in BMMs, and promoted OPG, Runx2 and Bglap2 expression, and decreased RANKL expression in MC3T3-E1 cells. Silencing WISP2 rescued the effect of TRG-AS1 on BMMs and MC3T3-E1 cells. In vivo results showed that tumor volumes significantly decreased in mice injected with LV-TRG-AS1 transfected MDA-MB-231 cells. TRG-AS1 knockdown markedly reduced the number of TRAP+ cells and the percentage of Ki-67+ cells and decreased E-cadherin expression in xenograft tumor mice. In summary, TRG-AS1 acts an endogenous RNA, inhibited breast cancer bone metastasis by competitively binding with miR-877-5p to upregulate WISP2 expression.

The Two Faces of Immune-Related lncRNAs in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a group of cancers originating from the mucosal epithelium in the oral cavity, larynx, oropharynx, nasopharynx, and hypopharynx. Molecular factors can be key in the diagnosis, prognosis, and treatment of HNSCC patients. Long non-coding RNAs (lncRNAs) are molecular regulators composed of 200 to 100,000 nucleotides that act on the modulation of genes that activate signaling pathways associated with oncogenic processes such as proliferation, migration, invasion, and metastasis in tumor cells. However, up until now, few studies have discussed the participation of lncRNAs in modeling the tumor microenvironment (TME) to generate a protumor or antitumor environment. Nevertheless, some immune-related lncRNAs have clinical relevance, since AL139158.2, AL031985.3, AC104794.2, AC099343.3, AL357519.1, SBDSP1, AS1AC108010.1, and TM4SF19-AS1 have been associated with overall survival (OS). MANCR is also related to poor OS and disease-specific survival. MiR31HG, TM4SF19-AS1, and LINC01123 are associated with poor prognosis. Meanwhile, LINC02195 and TRG-AS1 overexpression is associated with favorable prognosis. Moreover, ANRIL lncRNA induces resistance to cisplatin by inhibiting apoptosis. A superior understanding of the molecular mechanisms of lncRNAs that modify the characteristics of TME could contribute to increasing the efficacy of immunotherapy.

Characterization of tumor immune microenvironment and cancer therapy for head and neck squamous cell carcinoma through identification of a genomic instability-related lncRNA prognostic signature

Head and neck squamous cell carcinoma (HNSCC) represents one of the most prevalent and malignant tumors of epithelial origins with unfavorable outcomes. Increasing evidence has shown that dysregulated long non-coding RNAs (lncRNAs) correlate with tumorigenesis and genomic instability (GI), while the roles of GI-related lncRNAs in the tumor immune microenvironment (TIME) and predicting cancer therapy are still yet to be clarified. In this study, transcriptome and somatic mutation profiles with clinical parameters were obtained from the TCGA database. Patients were classified into GI-like and genomic stable (GS)-like groups according to the top 25% and bottom 25% cumulative counts of somatic mutations. Differentially expressed lncRNAs (DElncRNAs) between GI- and GS-like groups were identified as GI-related lncRNAs. These lncRNA-related coding genes were enriched in cancer-related KEGG pathways. Patients totaling 499 with clinical information were randomly divided into the training and validation sets. A total of 18 DElncRNAs screened by univariate Cox regression analysis were associated with overall survival (OS) in the training set. A GI-related lncRNA signature that comprised 10 DElncRNAs was generated through least absolute shrinkage and selection operator (Lasso)-Cox regression analysis. Patients in the high-risk group have significantly decreased OS vs. patients in the low-risk group, which was verified in internal validation and entire HNSCC sets. Integrated HNSCC sets from GEO confirmed the notable survival stratification of the signature. The time-dependent receiver operating characteristic curve demonstrated that the signature was reliable. In addition, the signature retained a strong performance of OS prediction for patients with various clinicopathological features. Cell composition analysis showed high anti-tumor immunity in the low-risk group which was evidenced by increased infiltrating CD8+ T cells and natural killer cells and reduced cancer-associated fibroblasts, which was convinced by immune signatures analysis via ssGSEA algorithm. T helper/IFNγ signaling, co-stimulatory, and co-inhibitory signatures showed increased expression in the low-risk group. Low-risk patients were predicted to be beneficial to immunotherapy, which was confirmed by patients with progressive disease who had high risk scores vs. complete remission patients. Furthermore, the drugs that might be sensitive to HNSCC were identified. In summary, the novel prognostic GILncRNA signature provided a promising approach for characterizing the TIME and predicting therapeutic strategies for HNSCC patients.

A Ferroptosis-Related Gene Signature for Overall Survival Prediction and Immune Infiltration in Lung Squamous Cell Carcinoma

Background: Ferroptosis is associated with cancer initiation and progression. However, the molecular mechanism and prognostic value of ferroptosis-related genes in lung squamous cell carcinoma (LUSC) are poorly understood.

Methods: The mRNA expression profiles, methylation data, and clinical information of patients with LUSC were downloaded from TCGA and GEO database. Ferroptosis-related differentially expressed genes (DEGs) were identified between cancerous and non-cancerous tissues, and their prognostic value was systemically investigated by bioinformatic analyses.

Results: A ferroptosis-related gene signature (ALOX5, TFRC, PHKG2, FADS2, NOX1) was constructed using multivariate Cox regression analysis and represented as a risk score. Overall survival (OS) probability was significantly lower in the high-risk group than in the low-risk group (P<0.001), and receiver operating characteristic curve showed a good predictive capacity (AUC = 0.739). The risk score was an independent prognostic factor for LUSC. A nomogram was constructed to predict the OS probabilities at 1, 3, and 5 years. High-risk score was associated with increased immune infiltration, lower methylation levels, higher immune checkpoint genes expression levels, and better chemotherapy response. Cell adhesion molecules, focal adhesion, and extracellular matrix receptor interaction were the main pathways in the high-risk group. The signature was validated using the TCGA test cohort, entire TCGA cohort, GSE30219, GSE157010, GSE73403, and GSE4573 datasets. The gene disorders in patients with LUSC were validated using real-time PCR and single-cell RNA sequencing analysis.

Conclusions: A ferroptosis-related gene signature was constructed to predict OS probability in LUSC. This could facilitate novel therapeutic methods and guide individualized therapy.