ArticleJournal of personalized medicine2024
RNA-Seq Analysis in Non-Small Cell Lung Cancer: What Is the Best Sample from Clinical Practice?
Article in Journal of personalized medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Diagnostic accuracy of next-generation sequencing (NGS) for identifying actionable mutations in advanced non-small cell lung cancer: Systematic Review and Meta-Analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Pooled it
- Next-Generation Sequencing in Differentiated Thyroid Cancer Patients Treated with Lenvatinib: Results and Challenges in Real-Life Practice.Current oncology (Toronto, Ont.) · 2026Article
- Pre-analytical Best Practices for RNA Sequencing from Small Biopsies and Cytologic Specimens.Molecular diagnosis & therapy · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
RNA-based next-generation sequencing (RNA-seq) represents the gold standard for detecting gene fusion in non-small cell lung cancer (NSCLC). Despite this, RNA instability makes the management of tissue samples extremely complex, resulting in a significant number of test failures with missing data or the need to switch to other techniques. In the present study, we analyzed pre-analytical variables in 140 tumor tissue samples from patients affected by NSCLC to detect features that increase the chances of successful RNA-seq. We found that the success rate of the analysis positively correlates with the RNA concentration and fragmentation index. Interestingly, small biopsies were more suitable samples than surgical specimens and cell blocks. Among surgical specimens, wedge resections demonstrated better results than lobectomy. Moreover, samples stored for less than 30 days (1 month) had a better chance of success than older samples. Defining the role of pre-analytical variables in RNA-seq allows the detection of more suitable samples for analysis and more effective planning of molecular-based diagnostic approaches in NSCLC.
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.