ArticleMolecular cancer2010
Small nucleolar RNA signatures as biomarkers for non-small-cell lung cancer.
Article in Molecular cancer, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 174 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
174 citing papers in PubMed, 1 synthesis or guideline pooled it, 306 citations in OpenAlex.
- Small Nucleolar RNAs as Diagnostic and Prognostic Biomarkers in Cancer: A Systematic Review and Meta-Analysis.Technology in cancer research & treatmentPooled it
- Machine learning approaches for cancer prognosis and diagnosis via non-coding RNA: a comprehensive review.Briefings in bioinformatics · 2026Review
- Review
- SCARNA20 influences the occurrence and development of lung cancer by inhibiting tumor cell proliferation, migration, and invasion.Journal of thoracic disease · 2026Article
- Hepatitis virus-associated B cell non-Hodgkin's lymphoma involves dysregulated epigenetic and RNA-mediated regulatory gene expression and altered snoRNA transcription.Scientific reports · 2026Article
- Serum small extracellular vesicle-associated snoRNA panel adds diagnostic value to CEA and CYFRA21-1 for non-small cell lung cancer: an exploratory single-center study.Frontiers in oncology · 2026Article
- Small Nucleolar RNAs (snoRNAs) in Cancer: From Biogenesis to Clinical Potential.OncoTargets and therapy · 2026Review
- Gene regulation by non-Coding RNAs in infertility: a mechanistic review.Journal of ovarian research · 2025Review
- ESAE-SDA: ensemble sparse autoencoder framework for epigenomics-informed snoRNA-disease associations prediction.BMC bioinformatics · 2025Article
- Characterization of small nucleolar RNA retaining transcripts in human normal and cancer cells.Non-coding RNA research · 2025Article
- Small Nucleolar RNAs: Biological Functions and Diseases.MedComm · 2025Review
- SNORA47 affects stemness and chemotherapy sensitivity via EBF3/RPL11/c-Myc axis in luminal A breast cancer.Molecular medicine (Cambridge, Mass.) · 2025Article
- Footprints in the Sno: investigating the cellular and molecular mechanisms of SNORD116.Open biology · 2025Review
- Review
- The diagnostic value of serum exosomal SNORD116 and SNORA21 for NSCLC patients.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Article
- MicroRNAs in breast cancer-new frontiers in diagnosis, targeted therapy, and prognosis assessment.Frontiers in oncology · 2025Review
- GL4SDA: Predicting snoRNA-disease associations using GNNs and LLM embeddings.Computational and structural biotechnology journal · 2025Article
- Serum exosomal small nucleolar RNA (snoRNA) signatures as a predictive biomarker for benign and malignant pulmonary nodules.Cancer cell international · 2024Article
- Small Nucleolar RNAs in Solid Tumors: A Brief Review of the Literature on These Potential Biomarkers.Asian Pacific journal of cancer prevention : APJCP · 2024Review
- SnoRNAs: Exploring Their Implication in Human Diseases.International journal of molecular sciences · 2024Review
114 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
backgroundNon-small-cell lung cancer (NSCLC) is the leading cause of cancer death. Early detection of NSCLC will improve its outcome. The current techniques for NSCLC early detection are either invasive or have low accuracy. Molecular analyses of clinical specimens present promising diagnostic approaches. Non-coding RNAs (ncRNAs) play an important role in tumorigenesis and could be developed as biomarkers for cancer. Here we aimed to develop small nucleolar RNAs (snoRNAs), a common class of ncRNAs, as biomarkers for NSCLC early detection. The study comprised three phases: (1) profiling snoRNA signatures in 22 NSCLC tissues and matched noncancerous lung tissues by GeneChip Array, (2) validating expressions of the signatures by RT-qPCR in the tissues, and (3) evaluating plasma expressions of the snoRNAs in 37 NSCLC patients, 26 patients with chronic obstructive pulmonary disease (COPD), and 22 healthy subjects.
resultsIn the surgical tissues, six snoRNAs were identified, which were overexpressed in all tumour tissues compared with their normal counterparts. The overexpressions of the genes in tumors were confirmed by RT-qPCR. The snoRNAs were stably present and reliably detectable in plasma. Of the six genes, three (SNORD33, SNORD66 and SNORD76) displayed higher plasma expressions in NSCLC patients compared with the cancer-free individuals (All < 0.01). The use of the three genes produced 81.1% sensitivity and 95.8% specificity in distinguishing NSCLC patients from both normal and COPD subjects. The plasma snoRNA expressions were not associated with stages and histological types of NSCLC (All > 0.05).
conclusionsThe identified snoRNAs provide potential markers for NSCLC early detection.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.