Identification of Potential Prognostic Long Non-Coding RNA Biomarkers for Predicting Recurrence in Patients with Cervical Cancer

Trinuclear ruthenium(II) polypyridyl complexes: Evaluation as photosensitizers for enhanced cervical cancer treatment

Trinuclear ruthenium(II) polypyridyl complexes anchored to benzimidazole-triazine / trisamine scaffolds were investigated as photosensitizers for photodynamic therapy. The trinuclear complexes were noted to produce a significant amount of singlet oxygen in both DMF and aqueous media, are photostable and show appreciable emission quantum yields (ɸem). In our experimental setting, despite the moderate phototoxic activity in the HeLa cervical cancer cell line, the phototoxic indices (PI) of the trinuclear complexes are superior relative to the PIs of a clinically approved photosensitizer, Photofrin®, and the pro-drug 5-aminolevulinic acid (PI: >7 relative to PI: >1 and PI: 4.4 for 5-aminolevulinic acid and Photofrin®, respectively). Furthermore, the ruthenium complexes were noted to show appreciable long-term cytotoxicity upon light irradiation in HeLa cells in a concentration-dependent manner. Consequently, this long-term activity of the ruthenium(II) polypyridyl complexes embodies their ability to reduce the probability of the recurrence of cervical cancer. Taken together, this presents a strong motivation for the development of polymetallic complexes as anticancer agents.

Molecular Characterization of Cuproptosis-related lncRNAs: Defining Molecular Subtypes and a Prognostic Signature of Ovarian Cancer

Cuproptosis, a newly discovered form of programmed cell death, relies on mitochondrial respiration, the chain of which has been found to be altered in ovarian cancer (OC). The current work probed into the effects of Cuproptosis on the prognosis, immune microenvironment and therapeutic response of OC based on Cuproptosis-related lncRNAs. Data on OC gene expression and clinical characteristics were collected from TCGA, ICGC and GEO databases, and mRNA and lncRNA were distinguished. Cuproptosis-related lncRNAs were screened for consensus clustering analysis. Differentially expressed lncRNAs (DElncRNAs) were identified between clusters, and least absolute shrinkage and selection operator (LASSO) and Cox regression analysis were performed to establish a prognostic signature. Its potential value in OC was evaluated by Gene Set Enrichment Analysis (GSEA), tumor cell mutation and immune microenvironment analysis, and response to immunotherapy and antineoplastic drugs. According to the classification scheme of Cuproptosis-related lncRNAs, OC was divided into four molecular subtypes, which were different in survival time, immune characteristics and somatic mutation. The prognostic signature between subtypes included 10 lncRNAs, which were significantly correlated with the prognosis, immune microenvironment related indexes, the expression of immune checkpoint molecules and the sensitivity of antineoplastic drug Paclitaxel and Gefitinib of OC. We examined the expression of ten LncRNAs in OC cell lines and found that LINC00189, ZFHX4-AS1, RPS6KA2-IT1 and C9orf106 were expressed elevated in OC cell lines, and LINC00861, LINC00582, DEPDC1-AS1, LINC01556, LEMD1-AS1, TYMSOS expression was decreased in OC cell lines. The results of CCK8 showed that the cell viability of OC cells decreased after inhibition of C9orf106, whereas the cell viability of OC cells increased after inhibition of LEMD1-AS1. This work revealed new Cuproptosis-related lncRNA molecular subtypes exhibiting tumor microenvironment (TME) heterogeneity for OC and proposed a prognostic signature that may have benefits in understanding the prognosis, pathological features and immune microenvironment of OC patients.

Adaptive optimization technology of a conformal infrared dome based on the Von Karman surface under hypersonic conditions

With the advent of the hypersonic era, diverse combat methods of hypersonic precision-guided weapons have been gradually developed. This study focuses on the precise design of a conformal infrared dome to accommodate different working conditions. To achieve this, an adaptive optimization technology for configuring conformal infrared domes is proposed, employing a multi-objective genetic algorithm. The technology enables the dome to dynamically balance its aerodynamic and imaging performance, taking into account the specific characteristics of each working condition. Moreover, it streamlines the design process of the conformal infrared domes. By optimizing the design with von Karman surfaces, we can overcome the limitations associated with the traditional quadric configuration. In order to evaluate its performance, a comparison was made with a conventional ellipsoid dome. The results indicate that, under the same working conditions, the air drag coefficient of the optimized infrared dome is reduced by 34.29% and that the peak signal-to-noise ratio of the distorted image from the infrared detection system is increased by 1.7%. We have demonstrated the effectiveness of the optimization method to balance aerodynamic performance and optical performance. Hopefully, our new method will improve the comprehensive performance of the infrared dome as well as the guidance capability of infrared detection technology.

The joint role of methylation and immune-related lncRNAs in ovarian cancer: Defining molecular subtypes and developing prognostic signature

INTRODUCTION

Complex outcome of ovarian cancer (OC) stems from the tumor immune microenvironment (TIME) influenced by genetic and epigenetic factors. This study aimed to comprehensively explored the subclasses of OC through lncRNAs related to both N6-methyladenosine (m6A)/N1-methyladenosine (m1A)/N7-methylguanosine (m7G)/5-methylcytosine (m5C) in terms of epigenetic variability and immune molecules and develop a new set of risk predictive systems.

MATERIAL AND METHODS

The lncRNA data of OC were collected from TCGA. Spearman correlation analysis on lncRNA data of OC with immune-related gene expression and with m6A/m5C/m1A/m7G were respectively conducted. The m6A/m5C/m1A/m7G-related m6A/m5C/m1A/m7G related immune lncRNA subtypes were identified on the basis of the prognostic lncRNAs. Heterogeneity among subtypes was evaluated by tumor mutation analysis, tumor microenvironment (TME) component analysis, response to immune checkpoint blocked (ICB) and chemotherapeutic drugs. A risk predictive system was developed based on the results of Cox regression analysis and random survival forest analysis of the differences between each specific cluster and other clusters.

RESULTS

Three m6A/m5C/m1A/m7G-related immune lncRNA subtypes of OC showing distinct differences in prognosis, mutation pattern, TIME components, immunotherapy and chemotherapy response were identified. A set of risk predictive system consisting of 10 lncRNA for OC was developed, according to which the risk score of samples in each OC dataset was calculated and risk type was defined.

CONCLUSIONS

This study classified three m6A/m5C/m1A/m7G-related immune lncRNA subtypes with distinct heterogeneous mutation patterns, TME components, ICB therapy and immune response, and provided a set of risk predictive system consisted of 10 lncRNA for OC.

L-RAPiT: A Cloud-Based Computing Pipeline for the Analysis of Long-Read RNA Sequencing Data

Long-read sequencing (LRS) has been adopted to meet a wide variety of research needs, ranging from the construction of novel transcriptome annotations to the rapid identification of emerging virus variants. Amongst other advantages, LRS preserves more information about RNA at the transcript level than conventional high-throughput sequencing, including far more accurate and quantitative records of splicing patterns. New studies with LRS datasets are being published at an exponential rate, generating a vast reservoir of information that can be leveraged to address a host of different research questions. However, mining such publicly available data in a tailored fashion is currently not easy, as the available software tools typically require familiarity with the command-line interface, which constitutes a significant obstacle to many researchers. Additionally, different research groups utilize different software packages to perform LRS analysis, which often prevents a direct comparison of published results across different studies. To address these challenges, we have developed the Long-Read Analysis Pipeline for Transcriptomics (L-RAPiT), a user-friendly, free pipeline requiring no dedicated computational resources or bioinformatics expertise. L-RAPiT can be implemented directly through Google Colaboratory, a system based on the open-source Jupyter notebook environment, and allows for the direct analysis of transcriptomic reads from Oxford Nanopore and PacBio LRS machines. This new pipeline enables the rapid, convenient, and standardized analysis of publicly available or newly generated LRS datasets.

Long Intergenic Non-Protein Coding RNA 173 in Human Cancers

Long non-coding RNAs belong to non-coding RNAs (ncRNAs) with a length of more than 200 nucleotides and limited protein-coding ability. Growing research has clarified that dysregulated lncRNAs are correlated with the development of various complex diseases, including cancer. LINC00173 has drawn researchers' attention as one of the recently discovered lncRNAs. Aberrant expression of LINC00173 affects the initiation and progression of human cancers. In the present review, we summarize the recent considerable research on LINC00173 in 11 human cancers. Through the summary of the abnormal expression of LINC00173 and its potential molecular regulation mechanism in cancers, this article indicates that LINC00173 may serve as a potential diagnostic biomarker and a target for drug therapy, thus providing novel clues for future related research.

The Role of Long Noncoding RNAs on Male Infertility: A Systematic Review and In Silico Analysis

Male infertility is a complex disorder affecting many couples worldwide. Long noncoding RNAs (lncRNAs) regulate important cellular processes; however, a comprehensive understanding of their role in male infertility is limited. This systematic review investigates the differential expressions of lncRNAs in male infertility or variations in lncRNA regions associated with it. The PRISMA guidelines were used to search Pubmed and Web of Science (1 June 2022). Inclusion criteria were human participants, patients diagnosed with male infertility, and English language speakers. We also performed an in silico analysis investigating lncRNAs that are reported in many subtypes of male infertility. A total of 625 articles were found, and after the screening and eligibility stages, 20 studies were included in the final sample. Many lncRNAs are deregulated in male infertility, and interactions between lncRNAs and miRNAs play an important role. However, there is a knowledge gap regarding the impact of variants found in lncRNA regions. Furthermore, eight lncRNAs were identified as differentially expressed in many subtypes of male infertility. After in silico analysis, gene ontology (GO) and KEGG enrichment analysis of the genes targeted by them revealed their association with bladder and prostate cancer. However, pathways involved in general in tumorigenesis and cancer development of all types, such as p53 pathways, apoptosis, and cell death, were also enriched, indicating a link between cancer and male infertility. This evidence, however, is preliminary. Future research is needed to explore the exact mechanism of action of the identified lncRNAs and investigate the association between male infertility and cancer.

Necroptosis-related lncRNA signature predicts prognosis and immune response for cervical squamous cell carcinoma and endocervical adenocarcinomas

Necroptosis, a programmed form of necrotic cell death, plays critical regulatory roles in the progression and metastatic spread of cancers such as cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). However, there are few articles systematically analyzing the necroptosis-related long non-coding RNAs (NRlncRNAs) correlated with CESC patients. Both RNA-sequencing and clinical data of CESC patients are downloaded from TCGA database in this study. Pearson correlation analysis, least absolute shrinkage, operator algorithm selection and Cox regression model are employed to screen and create a risk score model of eleven-NRlncRNAs (MIR100HG, LINC00996, SNHG30, LINC02688, HCG15, TUBA3FP, MIAT, DBH-AS1, ERICH6-AS1SCAT1, LINC01702) prognostic. Thereafter, a series of tests are carried out in sequence to evaluate the model for independent prognostic value. Gene set enrichment analytic paper, Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analytic paper make it clear that immune-related signaling pathways are very rich in the high-risk subgroup. Additionally, the prognostic risk score model is correlated to immune cell infiltration, potential immune checkpoint, immune function, immune micro-environmental and m6A-related gene. Mutation frequency in mutated genes and survival probability trend are higher in the low-risk subgroup in most of test cases when compared to the high-risk subgroup. This study constructs a renewed prognostic model of eleven-NRlncRNAs, which may make some contribution to accurately predicting the prognosis and the immune response from CESC patients, and improve the recognition of CESC patients and optimize customized treatment regimens to some extent.

Underexpression of LINC00173 in TCF3/PBX1-Positive Cases Is Associated With Poor Prognosis in Children With B-Cell Precursor Acute Lymphoblastic Leukemia

Background

B-cell precursor acute lymphoblastic leukemia (BCP-ALL) is the most frequent pediatric cancer worldwide. Despite improvements in treatment regimens, approximately 20% of the cases cannot be cured, highlighting the necessity for identifying new biomarkers to improve the current clinical and molecular risk stratification schemes. We aimed to investigate whether LINC00173 is a biomarker in ALL and to explore its expression level in other human cancer types.

Methods

A nested case-control study including Mexican children with BCP-ALL was conducted. LINC00173 expression was evaluated by qRT-PCR using hydrolysis probes. To validate our findings, RNA-seq expression data from BCP-ALL and normal tissues were retrieved from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Genotype-Tissue Expression (GTEx) repositories, respectively. LINC00173 expression was also evaluated in solid tumors by downloading available data from The Cancer Genome Atlas (TCGA).

Results

A lower expression of LINC00173 in BCP-ALL cases compared to normal subjects was observed (p < 0.05). ALL patients who carry the TCF3/PBX1 fusion gene displayed lower expression of LINC00173 in contrast to other BCP-ALL molecular subtypes (p < 0.04). LINC00173 underexpression was associated with a high risk to relapse (HR = 1.946, 95% CI = 1.213-3.120) and die (HR = 2.073, 95% CI = 1.211-3.547). Patients with TCF3/PBX1 and underexpression of LINC00173 had the worst prognosis (DFS: HR = 12.24, 95% CI = 5.04-29.71; OS: HR = 11.19, 95% CI = 26-32). TCGA data analysis revealed that underexpression of LINC00173 is also associated with poor clinical outcomes in six new reported tumor types.

Conclusion

Our findings suggest that LINC00173 is a biomarker of poor prognosis in BCP-ALL and other types of cancer. We observed an association between the expression of LINC00173 and TCF3/PBX1 and the risk to relapse and die in BCP-ALL, which is worse in TCF3/PBX1-positive cases displaying underexpression of LINC00173. Experimental studies are needed to provide insight into the LINC00173 and TCF3/PBX relationship.

Identification of Three Prognosis-Related Differentially Expressed lncRNAs Driven by Copy Number Variation in Thyroid Cancer

Thyroid cancer as the malignant tumor with the highest incidence in the endocrine system also shows a fast growth and development. In this work, we developed a new method to identify copy number variation- (CNV-) driven differentially expressed lncRNAs in thyroid cancer for predicting cancer prognosis. The data of RNA sequencing, CNV, methylation, mutation, and clinical details of thyroid cancer were obtained from the Cancer Genome Atlas database (TCGA). Molecular subtypes were clustered by iClusterPlus. Weighted gene co-expression network analysis (WGCNA) was employed to show co-expression modules. DEseq2 was conducted to identify protein coding genes (PCGs) and differentially expressed lncRNAs. CNV was detected using GISTIC 2.0. Three molecular subtypes were identified, and 68 differentially expressed lncRNAs (DElncRNAs) related to cancer were found among different molecular subtypes. CNV of FOXD2-AS1, FAM181A-AS1, and RNF157-AS1 was associated with overall survival and was involved in cancer-related pathways. These three DElncRNAs discovered based on CNV could serve as prognostic biomarkers to predict prognosis for thyroid cancer and new targets to explore molecular drugs.

Long Intergenic Nonprotein Coding RNA 173 Inhibits Tumor Growth and Promotes Apoptosis by Repressing Sphingosine Kinase 1 Protein Expression in Pancreatic Cancer

Pancreatic cancer is a common malignant tumor worldwide. Extensive studies have been conducted on the functional role of long noncoding RNAs in pancreatic cancer. In this study, long intergenic nonprotein coding RNA 173 (LINC00173) was highly expressed in pancreatic cancer tissues. In vitro functional experiments showed that LINC00173 overexpression inhibited the proliferation and invasion of pancreatic cancer cells and promoted cell apoptosis in MIA PaCa-2 and PANC-1 cells. RNA sequencing analysis and Western blot assays demonstrated that LINC00173 reduced the expression of sphingosine kinase 1 (SPHK1) and then inhibited the protein expression of activated phospho-protein kinase B (AKT) and NF-κB. In vivo functional assays also revealed that LINC00173 inhibited the growth of pancreatic cancer xenografts, repressed cell proliferation, promoted cell apoptosis, and inhibited SPHK1 expression. The combined results of this study indicate that LINC00173 inhibits pancreatic cancer progression by repressing SPHK1 expression. Improving LINC00173 may represent a therapeutic strategy for pancreatic cancer in the future.

Identification and Analysis of An Epigenetically Regulated Five-lncRNA Signature Associated With Outcome and Chemotherapy Response in Ovarian Cancer

The deregulation of long non-coding RNAs (lncRNAs) by epigenetic alterations has been implicated in cancer initiation and progression. However, the epigenetically regulated lncRNAs and their association with clinical outcome and therapeutic response in ovarian cancer (OV) remain poorly investigated. This study performed an integrative analysis of DNA methylation data and transcriptome data and identified 419 lncRNAs as potential epigenetically regulated lncRNAs. Using machine-learning and multivariate Cox regression analysis methods, we identified and developed an epigenetically regulated lncRNA expression signature (EpiLncRNASig) consisting of five lncRNAs from the list of 17 epigenetically regulated lncRNAs significantly associated with outcome. The EpiLncRNASig could stratify patients into high-risk groups and low-risk groups with significantly different survival and chemotherapy response in different patient cohorts. Multivariate Cox regression analyses, after adjusted by other clinical features and treatment response, demonstrated the independence of the DEpiLncSig in predicting survival. Functional analysis for relevant protein-coding genes of the DEpiLncSig indicated enrichment of known immune-related or cancer-related biological pathways. Taken together, our study not only provides a promising prognostic biomarker for predicting outcome and chemotherapy response but also will improve our understanding of lncRNA epigenetic regulation mechanisms in OV.

Selection of Treatment Regimens for Recurrent Cervical Cancer

OBJECTIVE

The selection of individualized treatment for recurrent cervical cancer is challenging. This study aimed to investigate the impact of various therapies on survival outcomes after recurrence.

METHODS

Eligible patients were diagnosed with recurrent cervical cancer between March 2012 and April 2018. Postrecurrence progression-free survival (PFS) and overall survival (OS) were investigated in the whole cohort and in subgroups, categorized by recurrence site and prior radiotherapy history, using a multivariate model that incorporated treatment for primary and recurrent tumors, histological pathology, and FIGO staging.

RESULTS

Two hundred and sixty recurrent cervical cancer patients were included. As of March 1, 2020, the median postrecurrence PFS and OS were 7.0 (range 0-94) and 24.0 (1.8-149.1) months, respectively. In a multivariate model measured by PFS, radiotherapy was superior to other therapies for the whole cohort (p=0.029) and recurrence only within the pelvic cavity (p=0.005), but the advantages of radiotherapy disappeared in patients with a history of radiotherapy (p values >0.05). For recurrence only beyond the pelvic cavity, combination therapy resulted in improved PFS (p=0.028). For recurrence both within and beyond the pelvic cavity, no therapy regimen provided additional PFS benefits (p values >0.05). Radiotherapy and combination therapy were also associated with improved postrecurrence OS for recurrence within the pelvic cavity (p=0.034) and only beyond the pelvic cavity (p=0.017), respectively.

CONCLUSIONS

In cervical cancer patients, postrecurrence radiotherapy can improve PFS and OS for patients with recurrence within the pelvic cavity and without prior radiotherapy. For recurrence beyond the pelvic cavity or cases with a history of radiotherapy, combination or individualized therapy may provide potential survival benefits.

The dual functions of the long noncoding RNA CASC15 in malignancy

Emerging evidence has demonstrated that long noncoding RNAs (lncRNAs) play vital roles in tumorigenesis and progression. LncRNAs can participate in various biological processes, such as cell growth, anti-apoptosis functions, migration, and invasion. Cancer susceptibility candidate 15 (CASC15) is a cancer-related lncRNA that has been reported to play opposite roles in the pathogenesis of different types of cancers. Studies have shown that CASC15 is downregulated in ovarian cancer and neuroblastoma, acting mainly as a tumour suppressor, while it is highly expressed and carcinogenic in hepatocellular carcinoma (HCC), lung cancer, tongue squamous cell carcinoma, gastric cancer, colorectal cancer, cervical cancer, and breast cancer. Furthermore, aberrant CASC15 expression is associated with tumorigenesis, progression, and patient outcomes via regulation of target genes and signalling pathways. In this review, we summarize current data concerning the regulatory functions and underlying mechanisms of CASC15 in tumour development. We also highlight its potential clinical utility as a biomarker for early detection or as a therapeutic target in human cancers.

Molecular landscape of recurrent cervical cancer

Cervical cancer (CC) is a major gynecological problem in developing and underdeveloped countries. Despite the significant advancement in early detection and treatment modalities, several patients recur. Moreover, the molecular mechanisms responsible for CC recurrence remains obscure. The patients with CC recurrence often show poor prognosis and significantly high mortality rates. The clinical management of recurrent CC depends on treatment history, site, and extent of the recurrence. Owing to poor prognosis and limited treatment options, recurrent CC often presents a challenge to the clinicians. Several in vitro, in vivo, and patient studies have led to the identification of the critical molecular changes responsible for CC recurrence. Both aberrant genetic and epigenetic modifications leading to altered cell signaling pathways have been reported to impact CC recurrence. Researchers are currently trying to dissect the molecular pathways in CC and translate these findings for better management of disease. This article attempts to review the existing knowledge of disease relapse, accompanying challenges, and associated molecular players in CC.

Long non-coding RNA HCG11 sponging miR-522-3p inhibits the tumorigenesis of non-small cell lung cancer by upregulating SOCS5

BACKGROUND

Numerous studies have shown that long non-coding RNA (lncRNA) is involved in various human diseases including non-small cell lung cancer (NSCLC). The aim of this study was to explore the potential role of lncRNA HCG11 in the pathogenesis of NSCLC.

METHODS

The mRNA expression of HCG11, miR-522-3p and SOCS5 was detected by RT-qPCR. The regulatory mechanism of lncRNA HCG11 was investigated by CCK-8, transwell and dual luciferase reporter assays.

RESULTS

Downregulation of lncRNA HCG11 and upregulation of miR-522-3p were found in NSCLC tissues and cells, and abnormal expressions of lncRNA HCG11 and miR-522-3p were related to adverse clinical outcomes of NSCLC patients. LncRNA HCG11 acted as a molecular sponge for miR-522-3p. Functionally, lncRNA HCG11 inhibited cell viability, migration and invasion in NSCLC by downregulating miR-522-3p. Further, miR-522-3p directly targeted SOCS5. lncRNA HCG11 could positively regulate SOCS5 expression in NSCLC. In addition, HCG11 downregulation or miR-522-3p overexpression abolished the inhibitory effect of SOCS5 on cell viability, migration and invasion in NSCLC.

CONCLUSIONS

LncRNA HCG11 inhibits cell viability, migration and invasion in NSCLC by functioning as a ceRNA of miR-522-3p to upregulate SOCS5.

An optimal prognostic model based on gene expression for clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of RCC; however, prognostic prediction tools for ccRCC are scant. Developing mRNA or long non-coding RNA (lncRNA)-based risk assessment tools may improve the prognosis in patients with ccRCC. RNA-sequencing and prognostic data from patients with ccRCC were downloaded from The Cancer Genome Atlas and the European Bioinformatics Institute Array database at the National Center for Biotechnology Information. Differentially expressed (DE) RNAs (DERs) and prognostic DERs were screened between less favorable and favorable prognoses using the limma package in R 3.4.1, and analyzed using univariate and multivariate Cox regression analyses, respectively. Risk score models were constructed using optimal combinations of DEmRNAs and DElncRNAs identified using the Least Absolute Shrinkage And Selection Operator Cox regression model of the penalized package. Associations between risk score models and overall survival time were evaluated. Independent prognostic clinical factors were screened using univariate and multivariate Cox regression analyses, and nomogram models were constructed. Gene Ontology biological processes and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were conducted using the clusterProfiler package in R3.4.1. A total of 451 DERs were identified, including 404 mRNAs and 47 lncRNAs, between less favorable and favorable prognoses, and 269 DERs, including 233 mRNAs and 36 lncRNAs, were identified as independent prognostic factors. Optimal combinations including 10 DEmRNAs or 10 DElncRNAs were screened using four risk score models based on the status or expression levels of the 10 DEmRNAs or 10 DElncRNAs. The model based on the expression levels of the 10 DEmRNAs had the highest prognostic power. These prognostic DEmRNAs may be involved in biological processes associated with the inflammatory response, complement and coagulation cascades and neuroactive ligand-receptor interaction pathways. The present validated risk assessment tool based on the expression levels of these 10 DEmRNAs may help to identify patients with ccRCC at a high risk of mortality. These 10 DEmRNAs in optimal combinations may serve as prognostic biomarkers and help to elucidate the pathogenesis of ccRCC.