Explore the vast range of titles available.

Over the past decades, research on cancer biology has focused on the involvement of protein-coding genes in cancer development. Long noncoding RNAs (lncRNAs), which are transcripts longer than 200 nucleotides that lack protein-coding potential, are an important class of RNA molecules that are involved in a variety of biological functions. Although the functions of a majority of lncRNAs have yet to be clarified, some lncRNAs have been shown to be associated with human diseases such as cancer. LncRNAs have been shown to contribute to many important cancer phenotypes through their interactions with other cellular macromolecules including DNA, protein and RNA. Here we describe the literature regarding the biogenesis and features of lncRNAs. We also present an overview of the current knowledge regarding the roles of lncRNAs in cancer from the view of various aspects of cellular homeostasis, including proliferation, survival, migration and genomic stability. Furthermore, we discuss the methodologies used to identify the function of lncRNAs in cancer development and tumorigenesis. Better understanding of the molecular mechanisms involving lncRNA functions in cancer is critical for the development of diagnostic and therapeutic strategies against tumorigenesis.

The application of a new generation of sequencing techniques has revealed that most of the genome has already been transcribed. However, only a small part of the genome codes proteins. The rest of the genome \"dark matter” belongs to divergent groups of non-coding RNA (ncRNA), that is not translated into proteins. There are two groups of ncRNAs, which include small and long non-coding RNAs (sncRNA and lncRNA respectively). Over the last decade, there has been an increased interest in lncRNAs and their interaction with cellular components. In this review, we presented the newest information about the human lncRNA interactome. The term lncRNA interactome refers to cellular biomolecules, such as nucleic acids, proteins, and peptides that interact with lncRNA. The lncRNA interactome was characterized in the last decade, however, understanding what role the biomolecules associated with lncRNA play and the nature of these interactions will allow us to better understand lncRNA's biological functions in the cell. We also describe a set of methods currently used for the detection of lncRNA interactome components and the analysis of their interactions. We think that such a holistic and integrated analysis of the lncRNA interactome will help to better understand its potential role in the development of organisms and cancers.

Background Long non-coding RNAs (lncRNAs) have a size of more than 200 bp and are known to regulate a host of crucial cellular processes like proliferation, differentiation and apoptosis by regulating gene expression. While small noncoding RNAs (ncRNAs) such as miRNAs, siRNAs, Piwi-interacting RNAs have been extensively studied in male germ cell development, the role of lncRNAs in spermatogenesis remains largely unknown. Objective In this article, we have reviewed the biology and role of lncRNAs in spermatogenesis along with the tools available for data analysis. Results and conclusions Till date, three microarray and four RNA-seq studies have been undertaken to identify lncRNAs in mouse testes or germ cells. These studies were done on pre-natal, post-natal, adult testis, and different germ cells to identify lncRNAs regulating spermatogenesis. In case of humans, five RNA-seq studies on different germ cell populations, including two on sperm, were undertaken. We compared three studies on human germ cells to identify common lncRNAs and found 15 lncRNAs (LINC00635, LINC00521, LINC00174, LINC00654, LINC00710, LINC00226, LINC00326, LINC00494, LINC00535, LINC00616, LINC00662, LINC00668, LINC00467, LINC00608, and LINC00658) to show consistent differential expression across these studies. Some of the targets of these lncRNAs included CENPB, FAM98B, GOLGA6 family, RPGR, TPM2, GNB5, KCNQ10T1, TAZ, LIN28A, CDKN2B, CDKN2A, CDKN1A, CDKN1B, CDKN1C, EZH2, SUZ12, VEGFA genes. A lone study on human male infertility identified 9879 differentially expressed lncRNAs with three (lnc32058, lnc09522, and lnc98497) of them showing specific and high expression in immotile sperm in comparison to normal motile sperm. A few lncRNAs (Mrhl, Drm, Spga-lncRNAs, NLC1-C, HongrES2, Tsx, LncRNA-tcam1, Tug1, Tesra, AK015322, Gm2044, and LncRNA033862) have been functionally validated for their roles in spermatogenesis. Apart from rodents and humans, studies on sheep and bull have also identified lncRNAs potentially important for spermatogenesis. A number of these non-coding RNAs are strong candidates for further research on their roles in spermatogenesis.

Numerous studies over the past few decades have shown that RNAs are multifaceted, multifunctional regulators of most cellular processes, contrary to the initial belief that they only act as mediators for translating DNA into proteins. LncRNAs, which refer to transcripts longer than 200nt and lack the ability to code for proteins, have recently been identified as central regulators of a variety of biochemical and cellular processes, particularly cancer. When they are abnormally expressed, they are closely associated with tumor occurrence, metastasis, and tumor staging. Therefore, through searches on Google Scholar, PubMed, and CNKI, we identified five five recently characterized lncRNAs–Lnc-SLC2A12-10:1, LncRNA BCRT1, lncRNA IGFBP4-1, LncRNA PCNAP1, and LncRNA CDC6–that have been linked to the promotion of cancer cell proliferation, invasion, and metastasis. Consequently, this review encapsulates the existing research and molecular underpinnings of these five newly identified lncRNAs across various types of cancer. It suggests that these novel lncRNAs hold potential as independent biomarkers for clinical diagnosis and prognosis, as well as candidates for therapeutic intervention. In parallel, we discuss the challenges inherent in the research on these five newly discovered lncRNAs and look forward to the avenues for future exploration in this field.

Eukaryotic genomes encode thousands of RNA molecules; however, only a minimal fraction is translated into proteins. Among the non-coding elements, long non-coding RNAs (lncRNAs) play important roles in diverse biological processes. LncRNAs are associated mainly with the regulation of the expression of the genome; nonetheless, their study has just scratched the surface. This is somewhat due to the lack of widespread conservation at the sequence level, in addition to their relatively low and highly tissue-specific expression patterns, which makes their exploration challenging, especially in plant genomes where only a few of these molecules have been described completely. Recently published high-quality genomes of crop plants, along with new computational tools, are considered promising resources for studying these molecules in plants. This review briefly summarizes the characteristics of plant lncRNAs, their presence and conservation, the different protocols to find these elements, and the limitations of these protocols. Likewise, it describes their roles in different plant physiological phenomena. We believe that the study of lncRNAs can help to design strategies to reduce the negative effect of biotic and abiotic stresses on the yield of crop plants and, in the future, help create fruits and vegetables with improved nutritional content, higher amounts of compounds with positive effects on human health, better organoleptic characteristics, and fruits with a longer postharvest shelf life.

Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, and disulfidptosis is a newly discovered mechanism of programmed cell death. However, the effects of disulfidptosis-related lncRNAs (DR-lncRNAs) in LUAD have yet to be fully elucidated. The aim of the present study was to identify and validate a novel lncRNA-based prognostic marker that was associated with disulfidptosis. RNA-sequencing and associated clinical data were obtained from The Cancer Genome Atlas database. Univariate Cox regression and lasso algorithm analyses were used to identify DR-lncRNAs and to establish a prognostic model. Kaplan-Meier curves, receiver operating characteristic curves, principal component analysis, Cox regression, nomograms and calibration curves were used to assess the reliability of the prognostic model. Functional enrichment analysis, immune infiltration analysis, somatic mutation analysis, tumor microenvironment and drug predictions were applied to the risk model. Reverse transcription-quantitative PCR was subsequently performed to validate the mRNA expression levels of the lncRNAs in normal cells and tumor cells. These analyses enabled a DR-lncRNA prognosis signature to be constructed, consisting of nine lncRNAs; U91328.1, LINC00426, MIR1915HG, TMPO-AS1, TDRKH-AS1, AL157895.1, AL512363.1, AC010615.2 and GCC2-AS1. This risk model could serve as an independent prognostic tool for patients with LUAD. Numerous immune evaluation algorithms indicated that the low-risk group may exhibit a more robust and active immune response against the tumor. Moreover, the tumor immune dysfunction exclusion algorithm suggested that immunotherapy would be more effective in patients in the low-risk group. The drug-sensitivity results showed that patients in the high-risk group were more sensitive to treatment with crizotinib, erlotinib or savolitinib. Finally, the expression levels of AL157895.1 were found to be lower in A549. In summary, a novel DR-lncRNA signature was constructed, which provided a new index to predict the efficacy of therapeutic interventions and the prognosis of patients with LUAD.

Transforming growth factor β (TGF-β) is a secreted cytokine that regulates cell proliferation, migration, and the differentiation of a plethora of different cell types. Consistent with these findings, TGF-β plays a key role in controlling embryogenic development, inflammation, and tissue repair, as well as in maintaining adult tissue homeostasis. TGF-β elicits a broad range of context-dependent cellular responses, and consequently, alterations in TGF-β signaling have been implicated in many diseases, including cancer. During the early stages of tumorigenesis, TGF-β acts as a tumor suppressor by inducing cytostasis and the apoptosis of normal and premalignant cells. However, at later stages, when cancer cells have acquired oncogenic mutations and/or have lost tumor suppressor gene function, cells are resistant to TGF-β-induced growth arrest, and TGF-β functions as a tumor promotor by stimulating tumor cells to undergo the so-called epithelial-mesenchymal transition (EMT). The latter leads to metastasis and chemotherapy resistance. TGF-β further supports cancer growth and progression by activating tumor angiogenesis and cancer-associated fibroblasts and enabling the tumor to evade inhibitory immune responses. In this review, we will consider the role of TGF-β signaling in cell cycle arrest, apoptosis, EMT and cancer cell metastasis. In particular, we will highlight recent insights into the multistep and dynamically controlled process of TGF-β-induced EMT and the functions of miRNAs and long noncoding RNAs in this process. Finally, we will discuss how these new mechanistic insights might be exploited to develop novel therapeutic interventions.

Noncoding RNAs (ncRNAs) constitute the majority of the human transcribed genome. This largest class of RNA transcripts plays diverse roles in a multitude of cellular processes, and has been implicated in many pathological conditions, especially cancer. The different subclasses of ncRNAs include microRNAs, a class of short ncRNAs; and a variety of long ncRNAs (lncRNAs), such as lincRNAs, antisense RNAs, pseudogenes, and circular RNAs. Many studies have demonstrated the involvement of these ncRNAs in competitive regulatory interactions, known as competing endogenous RNA (ceRNA) networks, whereby lncRNAs can act as microRNA decoys to modulate gene expression. These interactions are often interconnected, thus aberrant expression of any network component could derail the complex regulatory circuitry, culminating in cancer development and progression. Recent integrative analyses have provided evidence that new computational platforms and experimental approaches can be harnessed together to distinguish key ceRNA interactions in specific cancers, which could facilitate the identification of robust biomarkers and therapeutic targets, and hence, more effective cancer therapies and better patient outcome and survival.