Oncogenic chimeric transcription factors drive tumor-specific transcription, processing, and translation of silent genomic regions.

Many cancers are characterized by gene fusions encoding oncogenic chimeric transcription factors (TFs) such as EWS::FLI1 in Ewing sarcoma (EwS). Here, we find that EWS::FLI1 induces the robust expression of a specific set of novel spliced and polyadenylated transcripts within otherwise transcriptionally silent regions of the genome. These neogenes (NGs) are virtually undetectable in large collections of normal tissues or non-EwS tumors and can be silenced by CRISPR interference at regulatory EWS::FLI1-bound microsatellites. Ribosome profiling and proteomics further show that some NGs are translated into highly EwS-specific peptides. More generally, we show that hundreds of NGs can be detected in diverse cancers characterized by chimeric TFs. Altogether, this study identifies the transcription, processing, and translation of novel, specific, highly expressed multi-exonic transcripts from otherwise silent regions of the genome as a new activity of aberrant TFs in cancer.

Dynamic Recruitment of Single RNAs to Processing Bodies Depends on RNA Functionality.

Cellular RNAs often colocalize with cytoplasmic, membrane-less ribonucleoprotein (RNP) granules enriched for RNA-processing enzymes, termed processing bodies (PBs). Here we track the dynamic localization of individual miRNAs, mRNAs, and long non-coding RNAs (lncRNAs) to PBs using intracellular single-molecule fluorescence microscopy. We find that unused miRNAs stably bind to PBs, whereas functional miRNAs, repressed mRNAs, and lncRNAs both transiently and stably localize within either the core or periphery of PBs, albeit to different extents. Consequently, translation potential and 3' versus 5' placement of miRNA target sites significantly affect the PB localization dynamics of mRNAs. Using computational modeling and supporting experimental approaches, we show that partitioning in the PB phase attenuates mRNA silencing, suggesting that physiological mRNA turnover occurs predominantly outside of PBs. Instead, our data support a PB role in sequestering unused miRNAs for surveillance and provide a framework for investigating the dynamic assembly of RNP granules by phase separation at single-molecule resolution.

Identification of CAF-related lncRNAs at the pan-cancer level represents a potential carcinogenic risk.

Cancer-associated fibroblasts (CAFs) are increasingly recognized as playing a crucial role in regulating cancer progression and metastasis. These cells can be activated by long non-coding RNAs (lncRNAs), promoting the malignant biological processes of tumor cells. Therefore, it is essential to understand the regulatory relationship between CAFs and lncRNAs in cancers. Here, we identified CAF-related lncRNAs at the pan-cancer level to systematically predict their potential regulatory functions. The identified lncRNAs were also validated using various external data at both tissue and cellular levels. This study has revealed that these CAF-related lncRNAs exhibit expression perturbations in cancers and are highly correlated with the infiltration of stromal cells, particularly fibroblasts and endothelial cells. By prioritizing a list of CAF-related lncRNAs, we can further distinguish patient subtypes that show survival and molecular differences. In addition, we have developed a web server, CAFLnc (https://46906u5t63.zicp.fun/CAFLnc/), to visualize our results. In conclusion, CAF-related lncRNAs hold great potential as a valuable resource for comprehending lncRNA functions and advancing the identification of biomarkers for cancer progression and therapeutic targets in cancer treatment.

Spatial Organization of Single mRNPs at Different Stages of the Gene Expression Pathway.

mRNAs form ribonucleoprotein complexes (mRNPs) by association with proteins that are crucial for mRNA metabolism. While the mRNP proteome has been well characterized, little is known about mRNP organization. Using a single-molecule approach, we show that mRNA conformation changes depending on its cellular localization and translational state. Compared to nuclear mRNPs and lncRNPs, association with ribosomes decompacts individual mRNAs, while pharmacologically dissociating ribosomes or sequestering them into stress granules leads to increased compaction. Moreover, translating mRNAs rarely show co-localized 5' and 3' ends, indicating either that mRNAs are not translated in a closed-loop configuration, or that mRNA circularization is transient, suggesting that a stable closed-loop conformation is not a universal state for all translating mRNAs.

What sequencing technologies can teach us about innate immunity.

For years, we have taken a reductionist approach to understanding gene regulation through the study of one gene in one cell at a time. While this approach has been fruitful it is laborious and fails to provide a global picture of what is occurring in complex situations involving tightly coordinated immune responses. The emergence of whole-genome techniques provides a system-level view of a response and can provide a plethora of information on events occurring in a cell from gene expression changes to splicing changes and chemical modifications. As with any technology, this often results in more questions than answers, but this wealth of knowledge is providing us with an unprecedented view of what occurs inside our cells during an immune response. In this review, we will discuss the current RNA-sequencing technologies and what they are helping us learn about the innate immune system.

Evolutionary comparison of lncRNAs in four cotton species and functional identification of LncR4682-PAS2-KCS19 module in fiber elongation.

Long non-coding RNAs (lncRNAs) play an important role in various biological processes in plants. However, there have been few reports on the evolutionary signatures of lncRNAs in closely related cotton species. The lncRNA transcription patterns in two tetraploid cotton species and their putative diploid ancestors were compared in this paper. By performing deep RNA sequencing, we identified 280 429 lncRNAs from 21 tissues in four cotton species. lncRNA transcription evolves more rapidly than mRNAs, and exhibits more severe turnover phenomenon in diploid species compared to that in tetraploid species. Evolutionarily conserved lncRNAs exhibit higher expression levels, and lower tissue specificity compared with species-specific lncRNAs. Remarkably, tissue expression of homologous lncRNAs in Gossypium hirsutum and G. barbadense exhibited similar patterns, suggesting that these lncRNAs may be functionally conserved and selectively maintained during domestication. An orthologous lncRNA, lncR4682, was identified and validated in fibers of G. hirsutum and G. barbadense with the highest conservatism and expression abundance. Through virus-induced gene silencing in upland cotton, we found that lncR4682 and its target genes GHPAS2 and GHKCS19 positively regulated fiber elongation. In summary, the present study provides a systematic analysis of lncRNAs in four closely related cotton species, extending the understanding of transcriptional conservation of lncRNAs across cotton species. In addition, LncR4682-PAS2-KCS19 contributes to cotton fiber elongation by participating in the biosynthesis of very long-chain fatty acids.

The emerging regulatory roles of non-coding RNAs associated with glucose metabolism in breast cancer.

Altered energy metabolism is one of the hallmarks of tumorigenesis and essential for fulfilling the high demand for metabolic energy in a tumor through accelerating glycolysis and reprogramming the glycolysis metabolism through the Warburg effect. The dysregulated glucose metabolic pathways are coordinated not only by proteins coding genes but also by non-coding RNAs (ncRNAs) during the initiation and cancer progression. The ncRNAs are responsible for regulating numerous cellular processes under developmental and pathological conditions. Recent studies have shown that various ncRNAs such as microRNAs, circular RNAs, and long noncoding RNAs are extensively involved in rewriting glucose metabolism in human cancers. In this review, we demonstrated the role of ncRNAs in the progression of breast cancer with a focus on outlining the aberrant expression of glucose metabolic pathways. Moreover, we have discussed the existing and probable future applications of ncRNAs to regulate energy pathways along with their importance in the prognosis, diagnosis, and future therapeutics for human breast carcinoma.

MicroRNAs: Harbingers and shapers of periodontal inflammation.

Periodontal disease is an inflammatory reaction of the periodontal tissues to oral pathogens. In the present review we discuss the intricate effects of a regulatory network of gene expression modulators, microRNAs (miRNAs), as they affect periodontal morphology, function and gene expression during periodontal disease. These miRNAs are small RNAs involved in RNA silencing and post-transcriptional regulation and affect all stages of periodontal disease, from the earliest signs of gingivitis to the regulation of periodontal homeostasis and immunity and to the involvement in periodontal tissue destruction. MiRNAs coordinate periodontal disease progression not only directly but also through long non-coding RNAs (lncRNAs), which have been demonstrated to act as endogenous sponges or decoys that regulate the expression and function of miRNAs, and which in turn suppress the targeting of mRNAs involved in the inflammatory response, cell proliferation, migration and differentiation. While the integrity of miRNA function is essential for periodontal health and immunity, miRNA sequence variations (genetic polymorphisms) contribute toward an enhanced risk for periodontal disease progression and severity. Several polymorphisms in miRNA genes have been linked to an increased risk of periodontitis, and among those, miR-146a, miR-196, and miR-499 polymorphisms have been identified as risk factors for periodontal disease. The role of miRNAs in periodontal disease progression is not limited to the host tissues but also extends to the viruses that reside in periodontal lesions, such as herpesviruses (human herpesvirus, HHV). In advanced periodontal lesions, HHV infections result in the release of cytokines from periodontal tissues and impair antibacterial immune mechanisms that promote bacterial overgrowth. In turn, controlling the exacerbation of periodontal disease by minimizing the effect of periodontal HHV in periodontal lesions may provide novel avenues for therapeutic intervention. In summary, this review highlights multiple levels of miRNA-mediated control of periodontal disease progression, (i) through their role in periodontal inflammation and the dysregulation of homeostasis, (ii) as a regulatory target of lncRNAs, (iii) by contributing toward periodontal disease susceptibility through miRNA polymorphism, and (iv) as periodontal microflora modulators via viral miRNAs.

Long non-coding RNA-mediated modulation of endoplasmic reticulum stress under pathological conditions.

Endoplasmic reticulum (ER) stress, which ensues from an overwhelming protein folding capacity, activates the unfolded protein response (UPR) in an effort to restore cellular homeostasis. As ER stress is associated with numerous diseases, it is highly important to delineate the molecular mechanisms governing the ER stress to gain insight into the disease pathology. Long non-coding RNAs, transcripts with a length of over 200 nucleotides that do not code for proteins, interact with proteins and nucleic acids, fine-tuning the UPR to restore ER homeostasis via various modes of actions. Dysregulation of specific lncRNAs is implicated in the progression of ER stress-related diseases, presenting these molecules as promising therapeutic targets. The comprehensive analysis underscores the importance of understanding the nuanced interplay between lncRNAs and ER stress for insights into disease mechanisms. Overall, this review consolidates current knowledge, identifies research gaps and offers a roadmap for future investigations into the multifaceted roles of lncRNAs in ER stress and associated diseases to shed light on their pivotal roles in the pathogenesis of related diseases.

Altered expression levels of long non-coding natural antisense transcripts overlapping the UGT73C6 gene affect rosette size in Arabidopsis thaliana.

Natural antisense long non-coding RNAs (lncNATs) are involved in the regulation of gene expression in plants, modulating different relevant developmental processes and responses to various stimuli. We have identified and characterized two lncNATs (NAT1UGT73C6 and NAT2UGT73C6 , collectively NATsUGT73C6 ) from Arabidopsis thaliana that are transcribed from a gene fully overlapping UGT73C6, a member of the UGT73C subfamily of genes encoding UDP-glycosyltransferases (UGTs). Expression of both NATsUGT73C6 is developmentally controlled and occurs independently of the transcription of UGT73C6 in cis. Downregulation of NATsUGT73C6 levels through artificial microRNAs results in a reduction of the rosette area, while constitutive overexpression of NAT1UGT73C6 or NAT2UGT73C6 leads to the opposite phenotype, an increase in rosette size. This activity of NATsUGT73C6 relies on its RNA sequence and, although modulation of UGT73C6 in cis cannot be excluded, the observed phenotypes are not a consequence of the regulation of UGT73C6 in trans. The NATsUGT73C6 levels were shown to affect cell proliferation and thus individual leaf size. Consistent with this concept, our data suggest that the NATsUGT73C6 influence the expression levels of key transcription factors involved in regulating leaf growth by modulating cell proliferation. These findings thus reveal an additional regulatory layer on the process of leaf growth. In this work, we characterized at the molecular level two long non-coding RNAs (NATsUGT73C6 ) that are transcribed in the opposite direction to UGT73C6, a gene encoding a glucosyltransferase involved in brassinosteroid homeostasis in A. thaliana. Our results indicate that NATsUGT73C6 expression influences leaf growth by acting in trans and by modulating the levels of transcription factors that are involved in the regulation of cell proliferation.

The long non-coding RNA LINDA restrains cellular collapse following DNA damage in Arabidopsis thaliana.

The genomic integrity of every organism is endangered by various intrinsic and extrinsic stresses. To maintain genomic integrity, a sophisticated DNA damage response (DDR) network is activated rapidly after DNA damage. Notably, the fundamental DDR mechanisms are conserved in eukaryotes. However, knowledge about many regulatory aspects of the plant DDR is still limited. Important, yet little understood, regulatory factors of the DDR are the long non-coding RNAs (lncRNAs). In humans, 13 lncRNAs functioning in DDR have been characterized to date, whereas no such lncRNAs have been characterized in plants yet. By meta-analysis, we identified the putative long intergenic non-coding RNA induced by DNA damage (LINDA) that responds strongly to various DNA double-strand break-inducing treatments, but not to replication stress induced by mitomycin C. After DNA damage, LINDA is rapidly induced in an ATM- and SOG1-dependent manner. Intriguingly, the transcriptional response of LINDA to DNA damage is similar to that of its flanking hypothetical protein-encoding gene. Phylogenetic analysis of putative Brassicales and Malvales LINDA homologs indicates that LINDA lncRNAs originate from duplication of a flanking small protein-encoding gene followed by pseudogenization. We demonstrate that LINDA is not only needed for the regulation of this flanking gene but also fine-tuning of the DDR after the occurrence of DNA double-strand breaks. Moreover, Δlinda mutant root stem cells are unable to recover from DNA damage, most likely due to hyper-induced cell death.

Review on Long Non-Coding RNAs as Biomarkers and Potentially Therapeutic Targets for Bacterial Infections.

The confrontation between humans and bacteria is ongoing, with strategies for combating bacterial infections continually evolving. With the advancement of RNA sequencing technology, non-coding RNAs (ncRNAs) associated with bacterial infections have garnered significant attention. Recently, long ncRNAs (lncRNAs) have been identified as regulators of sterile inflammatory responses and cellular defense against live bacterial pathogens. They are involved in regulating host antimicrobial immunity in both the nucleus and cytoplasm. Increasing evidence indicates that lncRNAs are critical for the intricate interactions between host and pathogen during bacterial infections. This paper emphatically elaborates on the potential applications of lncRNAs in clinical hallmarks, cellular damage, immunity, virulence, and drug resistance in bacterial infections in greater detail. Additionally, we discuss the challenges and limitations of studying lncRNAs in the context of bacterial infections and highlight clear directions for this promising field.

MicroRNAs and long non-coding RNAs during transcriptional regulation and latency of HIV and HTLV.

Human immunodeficiency virus (HIV) and human T cell leukemia virus (HTLV) have replicative and latent stages of infection. The status of the viruses is dependent on the cells that harbour them and on different events that change the transcriptional and post-transcriptional events. Non-coding (nc)RNAs are key factors in the regulation of retrovirus replication cycles. Notably, micro (mi)RNAs and long non-coding (lnc)RNAs are important regulators that can induce switches between active transcription-replication and latency of retroviruses and have important impacts on their pathogenesis. Here, we review the functions of miRNAs and lncRNAs in the context of HIV and HTLV. We describe how specific miRNAs and lncRNAs are involved in the regulation of the viruses' transcription, post-transcriptional regulation and latency. We further discuss treatment strategies using ncRNAs for HIV and HTLV long remission, reactivation or possible cure.

CANTATAdb 3.0: An Updated Repository of Plant Long Non-Coding RNAs.

CANTATAdb 3.0 is an updated database of plant long non-coding RNAs (lncRNAs), containing 571,688 lncRNAs identified across 108 species, including 100 Magnoliopsida (flowering plants), a significant expansion from the previous version. A notable feature is the inclusion of 112,980 lncRNAs that are expressed specifically in certain plant organs or embryos, indicating their potential role in development and organ-specific processes. In addition, CANTATAdb 3.0 includes 74,886 pairs of evolutionarily conserved lncRNAs found across 47 species and inferred from genome-genome alignments as well as conserved lncRNAs obtained using a similarity search approach in 5,479 species pairs, which would further aid in the selection of lncRNAs for functional studies. Interestingly, we find that conserved lncRNAs with tissue-specific expression patterns tend to occupy the same plant organ across different species, pointing toward conserved biological roles. The database now offers extended search capabilities and downloadable data in popular formats, further facilitating research on plant lncRNAs.

GAE-LGA: integration of multi-omics data with graph autoencoders to identify lncRNA-PCG associations.

Long non-coding RNAs (lncRNAs) can disrupt the biological functions of protein-coding genes (PCGs) to cause cancer. However, the relationship between lncRNAs and PCGs remains unclear and difficult to predict. Machine learning has achieved a satisfactory performance in association prediction, but to our knowledge, it is currently less used in lncRNA-PCG association prediction. Therefore, we introduce GAE-LGA, a powerful deep learning model with graph autoencoders as components, to recognize potential lncRNA-PCG associations. GAE-LGA jointly explored lncRNA-PCG learning and cross-omics correlation learning for effective lncRNA-PCG association identification. The functional similarity and multi-omics similarity of lncRNAs and PCGs were accumulated and encoded by graph autoencoders to extract feature representations of lncRNAs and PCGs, which were subsequently used for decoding to obtain candidate lncRNA-PCG pairs. Comprehensive evaluation demonstrated that GAE-LGA can successfully capture lncRNA-PCG associations with strong robustness and outperformed other machine learning-based identification methods. Furthermore, multi-omics features were shown to improve the performance of lncRNA-PCG association identification. In conclusion, GAE-LGA can act as an efficient application for lncRNA-PCG association prediction with the following advantages: It fuses multi-omics information into the similarity network, making the feature representation more accurate; it can predict lncRNA-PCG associations for new lncRNAs and identify potential lncRNA-PCG associations with high accuracy.

LINC01116-dependent upregulation of RNA polymerase I transcription drives oncogenic phenotypes in lung adenocarcinoma.

BACKGROUND: Hyperactive RNA Polymerase I (Pol I) transcription is canonical in cancer, associated with malignant proliferation, poor prognosis, epithelial-mesenchymal transition, and chemotherapy resistance. Despite its significance, the molecular mechanisms underlying Pol I hyperactivity remain unclear. This study aims to elucidate the role of long noncoding RNAs (lncRNAs) in regulating Pol I transcription in lung adenocarcinoma (LUAD). METHODS: Bioinformatics analyses were applied to identify lncRNAs interacting with Pol I transcriptional machinery. Fluorescence in situ hybridization was employed to examine the nucleolar localization of candidate lncRNA in LUAD cells. RNA immunoprecipitation assay validated the interaction between candidate lncRNA and Pol I components. Chromatin isolation by RNA purification and Chromatin Immunoprecipitation (ChIP) were utilized to confirm the interactions of candidate lncRNA with Pol I transcriptional machinery and the rDNA core promoter. Functional analyses, including lncRNA knock-in and knockdown, inhibition of Pol I transcription, quantitative PCR, cell proliferation, clonogenicity, apoptosis, cell cycle, wound-healing, and invasion assays, were performed to determine the effect of candidate lncRNA on Pol I transcription and associated malignant phenotypes in LUAD cells. ChIP assays and luminometry were used to investigate the transcriptional regulation of the candidate lncRNA. RESULTS: We demonstrate that oncogenic LINC01116 scaffolds essential Pol I transcription factors TAF1A and TAF1D, to the ribosomal DNA promoter, and upregulate Pol I transcription. Crucially, LINC01116-driven Pol I transcription activation is essential for its oncogenic activities. Inhibition of Pol I transcription abrogated LINC01116-induced oncogenic phenotypes, including increased proliferation, cell cycle progression, clonogenicity, reduced apoptosis, increased migration and invasion, and drug sensitivity. Conversely, LINC01116 knockdown reversed these effects. Additionally, we show that LINC01116 upregulation in LUAD is driven by the oncogene c-Myc, a known Pol I transcription activator, indicating a functional regulatory feedback loop within the c-Myc-LINC01116-Pol I transcription axis. CONCLUSION: Collectively, our findings reveal, for the first time, that LINC01116 enhances Pol I transcription by scaffolding essential transcription factors to the ribosomal DNA promoter, thereby driving oncogenic activities in LUAD. We propose the c-Myc-LINC01116-Pol I axis as a critical oncogenic pathway and a potential therapeutic target for modulating Pol I transcription in LUAD.

Dysregulation of long non-coding RNA gene expression pathways in monocytes of type 2 diabetes patients with cardiovascular disease.

BACKGROUND: Monocytes play a central role in the pathophysiology of cardiovascular complications in type 2 diabetes (T2D) patients through different mechanisms. We investigated diabetes-induced changes in lncRNA genes from T2D patients with cardiovascular disease (CVD), long-duration diabetes, and poor glycemic control. METHODS: We performed paired-end RNA sequencing of monocytes from 37 non-diabetes controls and 120 patients with T2D, of whom 86 had either macro or microvascular disease or both. Monocytes were sorted from peripheral blood using flow cytometry; their RNA was purified and sequenced. Alignments and gene counts were obtained with STAR to reference GRCh38 using Gencode (v41) annotations followed by batch correction with CombatSeq. Differential expression analysis was performed with EdgeR and pathway analysis with IPA software focusing on differentially expressed genes (DEGs) with a p-value < 0.05. Additionally, differential co-expression analysis was done with csdR to identify lncRNAs highly associated with diabetes-related expression networks with network centrality scores computed with Igraph and network visualization with Cytoscape. RESULTS: Comparing T2D vs. non-T2D, we found two significantly upregulated lncRNAs (ENSG00000287255, FDR = 0.017 and ENSG00000289424, FDR = 0.048) and one significantly downregulated lncRNA (ENSG00000276603, FDR = 0.017). Pathway analysis on DEGs revealed networks affecting cellular movement, growth, and development. Co-expression analysis revealed ENSG00000225822 (UBXN7-AS1) as the highest-scoring diabetes network-associated lncRNA. Analysis within T2D patients and CVD revealed one lncRNA upregulated in monocytes from patients with microvascular disease without clinically documented macrovascular disease. (ENSG00000261654, FDR = 0.046). Pathway analysis revealed DEGs involved in networks affecting metabolic and cardiovascular pathologies. Co-expression analysis identified lncRNAs strongly associated with diabetes networks, including ENSG0000028654, ENSG00000261326 (LINC01355), ENSG00000260135 (MMP2-AS1), ENSG00000262097, and ENSG00000241560 (ZBTB20-AS1) when we combined the results from all patients with CVD. Similarly, we identified from co-expression analysis of diabetes patients with a duration ≥ 10 years vs. <10 years two lncRNAs: ENSG00000269019 (HOMER3-AS10) and ENSG00000212719 (LINC02693). The comparison of patients with good vs. poor glycemic control also identified two lncRNAs: ENSG00000245164 (LINC00861) and ENSG00000286313. CONCLUSION: We identified dysregulated diabetes-related genes and pathways in monocytes of diabetes patients with cardiovascular complications, including lncRNA genes of unknown function strongly associated with networks of known diabetes genes.

Evaluation of high-density lipoprotein-bound long non-coding RNAs in subjects with familial hypercholesterolaemia.

BACKGROUND: Long non-coding RNAs (lncRNAs) could be attractive circulating biomarkers for cardiovascular risk stratification in subjects at high atherosclerotic cardiovascular disease risk such as familial hypercholesterolaemia (FH). Our aim was to investigate the presence of lncRNAs carried by high-density lipoprotein (HDL) in FH subjects and to evaluate the associations of HDL-lncRNAs with lipoproteins and mechanical vascular impairment assessed by pulse wave velocity (PWV). METHODS: This was a retrospective observational study involving 94 FH subjects on statin treatment. Biochemical assays, HDL purification, lncRNA and PWV analyses were performed in all subjects. RESULTS: LncRNA HIF1A-AS2, LASER and LEXIS were transported by HDL; moreover, HDL-lncRNA LEXIS was associated with Lp(a) plasma levels (p < .01). In a secondary analysis, the study population was stratified into two groups based on the Lp(a) median value. The high-Lp(a) group exhibited a significant increase of PWV compared to the low-Lp(a) group (9.23 ± .61 vs. 7.67 ± .56, p < .01). While HDL-lncRNA HIF1A-AS2 and LASER were similar in the two groups, the high-Lp(a) group exhibited a significant downregulation of HDL-lncRNA LEXIS compared to the low-Lp(a) group (fold change -4.4, p < .0001). Finally, Lp(a) and HDL-lncRNA LEXIS were associated with PWV (for Lp(a) p < .01; for HDL-lncRNA LEXIS p < .05). CONCLUSIONS: LncRNA HIF1A-AS2, LASER and LEXIS were transported by HDL; moreover, significant relationships of HDL-lncRNA LEXIS with Lp(a) levels and PWV were found. Our study suggests that HDL-lncRNA LEXIS may be useful to better identify FH subjects with more pronounced vascular damage.

Autophagy-related lncRNAs and exosomal lncRNAs in colorectal cancer: focusing on lncRNA-targeted strategies.

Autophagy is a cellular process that involves the degradation and recycling of cellular components, including damaged proteins and organelles. It is an important mechanism for maintaining cellular homeostasis and has been implicated in various diseases, including cancer. Long non-coding RNAs (lncRNAs) are a class of RNA molecules that do not code for proteins but instead play regulatory roles in gene expression. Emerging evidence suggests that lncRNAs can influence autophagy and contribute to the development and progression of colorectal cancer (CRC). Several lncRNAs have been identified as key players in modulating autophagy in CRC. The dysregulation of autophagy and non-coding RNAs (ncRNAs) in CRC suggests a complex interplay between these two factors in the pathogenesis of the disease. Modulating autophagy may sensitize cancer cells to existing therapies or improve the efficacy of new treatment approaches. Additionally, targeting specific lncRNAs involved in autophagy regulation could potentially be used as a therapeutic intervention to inhibit tumor growth, metastasis, and overcome drug resistance in CRC. In this review, a thorough overview is presented, encompassing the functions and underlying mechanisms of autophagy-related lncRNAs in a range of critical areas within tumor biology. These include cell proliferation, apoptosis, migration, invasion, drug resistance, angiogenesis, and radiation resistance.

Exploration of Extracellular Vesicle Long Non-Coding RNAs in Serum of Patients with Cervical Cancer.

INTRODUCTION: Cervical cancer (CC) is the fourth most common cancer type and a leading cause of cancer-related deaths in women worldwide. Its underlying molecular mechanisms are unclear. Cancer cell-derived extracellular vesicles (EVs) are involved in cancer development and progression by delivering regulatory factors, including microRNAs and long non-coding RNAs (lncRNAs). METHODS: Here, we identified the EV lncRNA expression profiles associated with different developmental stages of CC using next-generation sequencing. EVs from the serum of patients with stages I-III CC and healthy donors were characterized using EV marker immunoblotting and transmission electron microscopy. RESULTS: The EV concentration increases with progression of the disease. Most particles had a 100-250-nm diameter, and their sizes were similar in all groups. We identified many lncRNAs that were uniquely and differentially expressed (DE) in patients with different stages of CC. The pathway analysis results indicated that the upregulated DE EV lncRNAs abundant in stages I and II were associated with cell proliferation and inflammation and cancer progression pathways, respectively. LINC00941, LINC01910, LINC02454, and DSG2-AS1 were highly expressed, suggesting poor overall survival of CC patients. Interestingly, DSG2-AS1 was associated with the human papillomavirus infection pathway through AKT3, DLG1, and COL6A2 genes. CONCLUSION: This is the first study that reports the levels of EVs and their lncRNA contents change during cancer development, demonstrating the existence of a unique vesicle-mediated cell-to-cell communication network underlying cancer progression.