Circulating miRNA panels as a novel non-invasive diagnostic, prognostic, and potential predictive biomarkers in non-small cell lung cancer (NSCLC).

Background: Non-small cell lung cancer (NSCLC) is characterised by its aggressiveness and poor prognosis. Early detection and accurate prediction of therapeutic responses remain critical for improving patient outcomes. In the present study, we investigated the potential of circulating microRNA (miRNA) as non-invasive biomarkers in patients with NSCLC.

Transcription factors interact with RNA to regulate genes.

Transcription factors (TFs) orchestrate the gene expression programs that define each cell's identity. The canonical TF accomplishes this with two domains, one that binds specific DNA sequences and the other that binds protein coactivators or corepressors. We find that at least half of TFs also bind RNA, doing so through a previously unrecognized domain with sequence and functional features analogous to the arginine-rich motif of the HIV transcriptional activator Tat.

Tumour mutations in long noncoding RNAs enhance cell fitness.

Long noncoding RNAs (lncRNAs) are linked to cancer via pathogenic changes in their expression levels. Yet, it remains unclear whether lncRNAs can also impact tumour cell fitness via function-altering somatic "driver" mutations. To search for such driver-lncRNAs, we here perform a genome-wide analysis of fitness-altering single nucleotide variants (SNVs) across a cohort of 2583 primary and 3527 metastatic tumours.

Multi-hallmark long noncoding RNA maps reveal non-small cell lung cancer vulnerabilities.

Long noncoding RNAs (lncRNAs) are widely dysregulated in cancer, yet their functional roles in cancer hallmarks remain unclear. We employ pooled CRISPR deletion to perturb 831 lncRNAs detected in KRAS-mutant non-small cell lung cancer (NSCLC) and measure their contribution to proliferation, chemoresistance, and migration across two cell backgrounds. Integrative analysis of these data outperforms conventional "dropout" screens in identifying cancer genes while prioritizing disease-relevant lncRNAs with pleiotropic and background-independent roles.

Is Evolutionary Conservation a Useful Predictor for Cancer Long Noncoding RNAs? Insights from the Cancer LncRNA Census 3.

Evolutionary conservation is a measure of gene functionality that is widely used to prioritise long noncoding RNAs (lncRNA) in cancer research. Intriguingly, while updating our Cancer LncRNA Census (CLC), we observed an inverse relationship between year of discovery and evolutionary conservation. This observation is specific to cancer over other diseases, implying a sampling bias in the selection of lncRNA candidates and casting doubt on the value of evolutionary metrics for the prioritisation of cancer-related lncRNAs.

Cancer LncRNA Census 2 (CLC2): an enhanced resource reveals clinical features of cancer lncRNAs.

Long non-coding RNAs (lncRNAs) play key roles in cancer and are at the vanguard of precision therapeutic development. These efforts depend on large and high-confidence collections of cancer lncRNAs. Here, we present the Cancer LncRNA Census 2 (CLC2).

Tumor-Educated Platelet RNA for the Detection and (Pseudo)progression Monitoring of Glioblastoma.

Tumor-educated platelets (TEPs) are potential biomarkers for cancer diagnostics. We employ TEP-derived RNA panels, determined by . We assessed specificity by comparing the spliced RNA profile of TEPs from glioblastoma patients with multiple sclerosis and brain metastasis patients (validation series, n = 157; accuracy, 80%; AUC, 0.

Blood platelet RNA enables the detection of multiple sclerosis.

Background: In multiple sclerosis (MS), clinical assessment, MRI and cerebrospinal fluid are important in the diagnostic process. However, no blood biomarker has been confirmed as a useful tool in the diagnostic work-up.

Objectives: Blood platelets contain a rich spliced mRNA repertoire that can alter during megakaryocyte development but also during platelet formation and platelet circulation.

CASPR, an analysis pipeline for single and paired guide RNA CRISPR screens, reveals optimal target selection for long non-coding RNAs.

Motivation: CRISPR-Cas9 loss-of-function (LOF) pooled screening promises to identify which long non-coding RNAs (lncRNAs), amongst the many thousands to have been annotated so far, are capable of mediating cellular functions. The two principal LOF perturbations, CRISPR-inhibition and CRISPR-deletion, employ one and two guide RNAs, respectively. However, no software solution has the versatility to identify hits across both modalities, and the optimal design parameters for such screens remain poorly understood.

Correction: Determination of the presence of 5-methylcytosine in Paramecium tetraurelia.

[This corrects the article DOI: 10.1371/journal.pone.

Determination of the presence of 5-methylcytosine in Paramecium tetraurelia.

5-methylcytosine DNA methylation regulates gene expression and developmental programming in a broad range of eukaryotes. However, its presence and potential roles in ciliates, complex single-celled eukaryotes with germline-somatic genome specialization via nuclear dimorphism, are largely uncharted. While canonical cytosine methyltransferases have not been discovered in published ciliate genomes, recent studies performed in the stichotrichous ciliate Oxytricha trifallax suggest de novo cytosine methylation during macronuclear development.

Swarm Intelligence-Enhanced Detection of Non-Small-Cell Lung Cancer Using Tumor-Educated Platelets.

Blood-based liquid biopsies, including tumor-educated blood platelets (TEPs), have emerged as promising biomarker sources for non-invasive detection of cancer. Here we demonstrate that particle-swarm optimization (PSO)-enhanced algorithms enable efficient selection of RNA biomarker panels from platelet RNA-sequencing libraries (n = 779). This resulted in accurate TEP-based detection of early- and late-stage non-small-cell lung cancer (n = 518 late-stage validation cohort, accuracy, 88%; AUC, 0.