SPINT1-AS1 Drives Cervical Cancer Progression via Repressing miR-214 Biogenesis

LncRNA SPINT1-AS1 enhances the Warburg effect and promotes the progression of osteosarcoma via the miR-135b-5p/PGAM1 axis

Osteosarcoma (OS) is a malignant bone tumor that originates from interstitial tissues and affects the health of children and adolescents. Long noncoding RNAs (lncRNAs) are an intriguing category of widely distributed endogenous RNAs involved in OS progression, many of which remain functionally uncharacterized. Herein, we observed an increased expression of lncRNA SPINT1-AS1 in OS tissues and cell lines. Further analysis confirmed that SPINT1-AS1 promotes the proliferation and metastasis of OS cells. Moreover, miR-135b-5p was identified as a downstream target of SPINT1-AS1. Through bioinformatics analysis, PGAM1 mRNA was validated as a target of miR-135b-5p via RIP and luciferase reporter assays. SPINT1-AS1 could enhance OS cell proliferation and metastasis by promoting aerobic glycolysis, acting as a ceRNA by binding to miR-135b-5p, thereby increasing PGAM1 expression. Taken together, these results indicate that SPINT1-AS1 functions as a tumor promoter and regulates OS cell progression through the miR-135b-5p/PGAM1 axis.

Disulfidptosis-associated LncRNA signature predicts prognosis and immune response in kidney renal clear cell carcinoma

BACKGROUND

Kidney renal clear cell carcinoma (KIRC) represents a significant proportion of renal cell carcinomas and is characterized by high aggressiveness and poor prognosis despite advancements in immunotherapy. Disulfidptosis, a novel cell death pathway, has emerged as a critical mechanism in various cellular processes, including cancer. This study leverages machine learning to identify disulfidptosis-related long noncoding RNAs (DRlncRNAs) as potential prognostic biomarkers in KIRC, offering new insights into tumor pathogenesis and treatment avenues.

RESULTS

Our analysis of data from The Cancer Genome Atlas (TCGA) led to the identification of 431 DRlncRNAs correlated with disulfidptosis-related genes. Five key DRlncRNAs (SPINT1-AS1, AL161782.1, OVCH1-AS1, AC131009.3, and AC108673.3) were used to develop a prognostic model that effectively distinguished between low- and high-risk patients with significant differences in overall survival and progression-free survival. The low-risk group had a favorable prognosis associated with a protective immune microenvironment and a better response to targeted drugs. Conversely, the high-risk group displayed aggressive tumor features and poor immunotherapy outcomes. Validation through qRT‒PCR confirmed the differential expression of these DRlncRNAs in KIRC cells compared to normal kidney cells, underscoring their potential functional significance in tumor biology.

CONCLUSIONS

This study established a robust link between disulfidptosis-related lncRNAs and patient prognosis in KIRC, underscoring their potential as prognostic biomarkers and therapeutic targets. The differential expression of these lncRNAs in tumor versus normal tissue further highlights their relevance in KIRC pathogenesis. The predictive model not only enhances our understanding of KIRC biology but also provides a novel stratification tool for precision medicine approaches, improving treatment personalization and outcomes in KIRC patients.

Development of a novel disulfidptosis-related lncRNA signature for prognostic and immune response prediction in clear cell renal cell carcinoma

Disulfidptosis, a novel form of regulated cell death, occurs due to the aberrant accumulation of intracellular cystine and other disulfides. Moreover, targeting disulfidptosis could identify promising approaches for cancer treatment. Long non-coding RNAs (lncRNAs) are known to be critically implicated in clear cell renal cell carcinoma (ccRCC) development. Currently, the involvement of disulfidptosis-related lncRNAs in ccRCC is yet to be elucidated. This study primarily dealt with identifying and validating a disulfidptosis-related lncRNAs-based signature for predicting the prognosis and immune landscape of individuals with ccRCC. Clinical and RNA sequencing data of ccRCC samples were accessed from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was conducted for the identification of the disulfidptosis-related lncRNAs. Additionally, univariate Cox regression analysis, Least Absolute Shrinkage and Selection Operator Cox regression, and stepwise multivariate Cox analysis were executed to develop a novel risk prognostic model. The prognosis-predictive capacity of the model was then assessed using an integrated method. Variation in biological function was noted using GO, KEGG, and GSEA. Additionally, immune cell infiltration, the tumor mutational burden (TMB), and tumor immune dysfunction and exclusion (TIDE) scores were calculated to investigate differences in the immune landscape. Finally, the expression of hub disulfidptosis-related lncRNAs was validated using qPCR. We established a novel signature comprised of eight lncRNAs that were associated with disulfidptosis (SPINT1-AS1, AL121944.1, AC131009.3, AC104088.3, AL035071.1, LINC00886, AL035587.2, and AC007743.1). Kaplan-Meier and receiver operating characteristic curves demonstrated the acceptable predictive potency of the model. The nomogram and C-index confirmed the strong correlation between the risk signature and clinical decision-making. Furthermore, immune cell infiltration analysis and ssGSEA revealed significantly different immune statuses among risk groups. TMB analysis revealed the link between the high-risk group and high TMB. It is worth noting that the cumulative effect of the patients belonging to the high-risk group and having elevated TMB led to decreased patient survival times. The high-risk group depicted greater TIDE scores in contrast with the low-risk group, indicating greater potential for immune escape. Finally, qPCR validated the hub disulfidptosis-related lncRNAs in cell lines. The established novel signature holds potential regarding the prognosis prediction of individuals with ccRCC as well as predicting their responses to immunotherapy.

Pyroptosis-related lncRNA prognostic signatures for cutaneous melanoma and tumor microenvironment status

Aims: To explore whether the expression of pyroptosis-related lncRNAs makes a difference in the prognosis and antitumor immunity of cutaneous melanoma (CM) patients. Methods: A series of analyses were conducted to establish a prognostic risk model and validate its accuracy. Immune-related analyses were performed to further assess the associations among immune status, tumor microenvironment and the prognostic risk model. Results: Eight pyroptosis-related lncRNAs relevant to prognosis were ascertained and applied to establish the prognostic risk model. The low-risk group had a higher overall survival rate. Conclusion: The established prognostic risk model presents better prediction ability for the prognosis of CM patients and provides new possible therapeutic targets for CM.

A model based on immune-related lncRNA pairs and its potential prognostic value in immunotherapy for melanoma

A model based on long non-coding RNA (lncRNA) pairs independent of expression quantification was constructed to evaluate prognosis melanoma and response to immunotherapy in melanoma. RNA sequencing data and clinical information were retrieved and downloaded from The Cancer Genome Atlas and the Genotype-Tissue Expression databases. We identified differentially expressed immune-related lncRNAs (DEirlncRNAs), matched them, and used least absolute shrinkage and selection operator and Cox regression to construct predictive models. The optimal cutoff value of the model was determined using a receiver operating characteristic curve and used to categorize melanoma cases into high-risk and low-risk groups. The predictive efficacy of the model with respect to prognosis was compared with that of clinical data and ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data). Then, we analyzed the correlations of risk score with clinical characteristics, immune cell invasion, anti-tumor, and tumor-promoting activities. Differences in survival, degree of immune cell infiltration, and intensity of anti-tumor and tumor-promoting activities were also evaluated in the high- and low-risk groups. A model based on 21 DEirlncRNA pairs was established. Compared with ESTIMATE score and clinical data, this model could better predict outcomes of melanoma patients. Follow-up analysis of the model's effectiveness showed that patients in the high-risk group had poorer prognosis and were less likely to benefit from immunotherapy compared with those in the low-risk group. Moreover, there were differences in tumor-infiltrating immune cells between the high-risk and low-risk groups. By pairing the DEirlncRNA, we constructed a model to evaluate the prognosis of cutaneous melanoma independent of a specific level of lncRNA expression.

Role of MicroRNA-214 in Dishevelled1-Modulated β-catenin Signalling in Non-Small Cell Lung Cancer Progression

Background: The mortality of patients with non-small cell lung cancer (NSCLC) is rather high. This is largely because of the lack of specific targets and understanding of the molecular mechanism for early diagnosis. Dishevelled (Dvl) dysregulation leads to malignant progression. We confirmed that Dvl1 expression is associated with a poor prognosis of patients with NSCLC. However, how Dvl1 transmits signals through the Wnt/β-catenin pathway remains unknown. Methods: In this study, the expression levels of Dvl1 and β-catenin in resected NSCLC samples were immunohistochemically analysed. Dvl1 cDNA and small interfering RNA against β-catenin were transfected into NSCLC cells, and their effects on canonical Wnt signalling and biological behaviour of NSCLC cells were analysed. Using bioinformatics analyses, an interaction between microRNA (miR)-214 and β-catenin was identified; miR-214 expression was determined in NSCLC tissues using quantitative real-time polymerase chain reaction. An exogenous miR-214 (mimic) was used to analyse the biological behaviour of NSCLC cells and the effect of Dvl1 on canonical Wnt activation. Results: Dvl1 overexpression in NSCLC tissues as well as Dvl1 and β-catenin nuclear coexpression were significantly associated with poor prognosis of NSCLC (P < 0.05). Additionally, Dvl1 promoted Wnt/β-catenin signalling to enhance the malignant phenotype of NSCLC cells. Moreover, miR-214 directly targeted the 3' untranslated region of β-catenin to inhibit the activation of canonical Wnt signalling induced by Dvl1. Conclusions: Our results suggest that Dvl1 is a potential therapeutic target for NSCLC and that miR-214 plays an inhibitory role in Dvl1-mediated activation of Wnt/β-catenin signalling in NSCLC cells, which could affect NSCLC progression.

Mechanistic Contributions of lncRNAs to Cellular Signaling Pathways Crucial to the Lifecycle of Human Papillomaviruses

Papillomaviruses are ubiquitous epitheliotropic viruses with double-stranded circular DNA genomes of approximately 8000 base pairs. The viral life cycle is somewhat unusual in that these viruses can establish persistent infections in the mitotically active basal epithelial cells that they initially infect. High-level viral genome replication ("genome amplification"), the expression of capsid proteins, and the formation of infectious progeny are restricted to terminally differentiated cells where genomes are synthesized at replication factories at sites of double-strand DNA breaks. To establish persistent infections, papillomaviruses need to retain the basal cell identity of the initially infected cells and restrain and delay their epithelial differentiation program. To enable high-level viral genome replication, papillomaviruses also need to hold the inherently growth-arrested terminally differentiated cells in a replication-competent state. To provide ample sites for viral genome synthesis, they target the DNA damage and repair machinery. Studies focusing on delineating cellular factors that are targeted by papillomaviruses may aid the development of antivirals. Whilst most of the current research efforts focus on protein targets, the majority of the human transcriptome consists of noncoding RNAs. This review focuses on one specific class of noncoding RNAs, long noncoding RNAs (lncRNAs), and summarizes work on lncRNAs that may regulate the cellular processes that are subverted by papillomavirus to enable persistent infections and progeny synthesis.

MicroRNAs as Potential Tools for Predicting Cancer Patients’ Susceptibility to SARS-CoV-2 Infection and Vaccination Response

Coronavirus disease (COVID-19) is an infectious disease that is caused by a highly contagious and severe acute respiratory syndrome—coronavirus 2 (SARS-CoV-2). This infection started to spread across the world in 2019 and rapidly turned into a global pandemic, causing an urgent necessity for treatment strategies development. The mRNA vaccines against SARS-CoV-2 can trigger an immune response, providing genetic information that allows the production of spike glycoproteins. MiRNAs play a crucial role in diverse key cellular processes, including antiviral defense. Several miRNAs are described as key factors in SARS-CoV-2 human infection through the regulation of ACE2 levels and by the inhibition of SARS-CoV-2 replication and spike expression. Consequently, these molecules have been considered as highly promising biomarkers. In numerous human malignancies, it has been recognized that miRNAs expression is dysregulated. Since miRNAs can target SARS-CoV-2-associated mRNAs, in cancer patients, the deregulation of these molecules can impair the immune response to the vaccines. Therefore, in this review, we propose a miRNA profile of seven SARS-CoV-2-related miRNAs, namely miR-214, miR-98-5p, miR-7-5p, miR-24-3p, miR-145-5p, miR-223-3p and miR-15b-5p, that are deregulated in a high number of cancers and have the potential to be used as prognostic biomarkers to stratify cancer patients.

The Regulatory Functions and the Mechanisms of Long Non-Coding RNAs in Cervical Cancer

Cervical cancer is one of the leading causes of death in gynecology cancer worldwide. High-risk human papillomaviruses (HPVs) are the major etiological agents for cervical cancer. Still, other factors also contribute to cervical cancer development because these cancers commonly arise decades after initial exposure to HPV. So far, the molecular mechanisms underlying the pathogenesis of cervical cancer are still quite limited, and a knowledge gap needs to be filled to help develop novel strategies that will ultimately facilitate the development of therapies and improve cervical cancer patient outcomes. Long non-coding RNAs (lncRNAs) have been increasingly shown to be involved in gene regulation, and the relevant role of lncRNAs in cervical cancer has recently been investigated. In this review, we summarize the recent progress in ascertaining the biological functions of lncRNAs in cervical cancer from the perspective of cervical cancer proliferation, invasion, and metastasis. In addition, we provide the current state of knowledge by discussing the molecular mechanisms underlying the regulation and emerging role of lncRNAs in the pathogenesis of cervical cancer. Comprehensive and deeper insights into lncRNA-mediated alterations and interactions in cellular events will help develop novel strategies to treat patients with cervical cancer.