Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

lncRNA - Long Non-coding RNAs

lncRNA - Long Non-coding RNAs

In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Loss of the USP22 deubiquitylase confers resistance to chemotherapy in small cell lung cancer.

Nature communications·2026

Same author

Germline CDK12 variants in aggressive prostate cancer.

Cancer discovery·2026

Same author

3D pathology-guided microdissection.

Nature methods·2026

Same author

Succinate dehydrogenase loss suppresses pyrimidine biosynthesis via succinate-mediated inhibition of aspartate transcarbamylase.

Nature metabolism·2026

Same author

Tolerance and Resistance to Targeted Therapy in NSCLC: Emerging Concepts and Strategies.

JTO clinical and research reports·2026

Same author

Deep learning-based non-invasive profiling of tumor transcriptomes from cell-free DNA for precision oncology.

bioRxiv : the preprint server for biology·2026

Search research articles

Related Experiment Video

Updated: Mar 28, 2026

Multidimensional Coculture System to Model Lung Squamous Carcinoma Progression

Multidimensional Coculture System to Model Lung Squamous Carcinoma Progression

Published on: March 17, 2020

Beyond Histology: A Unified Transcriptomic Atlas Defines Lung Cancer Biologic States and Subtypes.

Sonali Arora¹, Laavan Suresh², H Nayanga Thirimanne¹

¹Human Biology Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.

Biorxiv : the Preprint Server for Biology

|March 27, 2026

Summary

This study maps lung cancer's molecular landscape using RNA sequencing from over 1,500 tumors. It reveals distinct transcriptional states and vulnerabilities, redefining lung cancer as a continuum.

Keywords:

RNA-Seq copy number gene fusions lung cancer pathways tumor subtyping

More Related Videos

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors

Published on: September 20, 2016

Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer

Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer

Published on: September 8, 2023

Related Experiment Videos

Last Updated: Mar 28, 2026

Multidimensional Coculture System to Model Lung Squamous Carcinoma Progression

Multidimensional Coculture System to Model Lung Squamous Carcinoma Progression

Published on: March 17, 2020

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors

Published on: September 20, 2016

Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer

Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer

Published on: September 8, 2023

Area of Science:

Oncology
Genomics
Bioinformatics

Background:

Lung cancer presents significant molecular heterogeneity across its histological subtypes.
Current understanding of lung cancer's molecular landscape at scale remains incomplete.

Purpose of the Study:

To construct a unified molecular reference landscape of lung cancer.
To identify conserved transcriptional states and subtype-specific vulnerabilities.

Main Methods:

Analysis of raw RNA sequencing data from 1,558 lung tumors (adenocarcinoma, squamous cell carcinoma, small cell lung cancer).
Application of batch correction and PaCMAP for molecular atlas generation.
Consensus clustering to resolve molecular subtypes and annotation with clinical/biological metadata.

Main Results:

Tumors organized into a continuous atlas along proliferative, metabolic, and immune axes, rather than strict histology.
Nine robust molecular clusters were identified, including unique subgroups for adenocarcinoma and distinct states for small cell and squamous carcinomas.
Spatially-restricted expression revealed state-specific vulnerabilities and actionable targets.

Conclusions:

Lung cancer is redefined as a structured continuum of transcriptional states.
The molecular atlas provides a framework for understanding subtype-specific biology and translational relevance.
This approach enables quantitative assessment of model fidelity using patient-derived xenografts.