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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...

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Related Experiment Video

Updated: Sep 16, 2025

Identification of OTX1 and OTX2 As Two Possible Molecular Markers for Sinonasal Carcinomas and Olfactory Neuroblastomas

Identification of OTX1 and OTX2 As Two Possible Molecular Markers for Sinonasal Carcinomas and Olfactory Neuroblastomas

Published on: February 28, 2019

Magnifying Glass on Sinonasal NUT Carcinoma Heterogeneity via Spatial Transcriptomics.

Diana Bell^1,2, Garret Choby², Michelle Afkhami³

¹Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.

|July 7, 2025

Summary

This summary is machine-generated.

Spatial transcriptomics reveals cellular diversity in Nuclear protein in testis (NUT) carcinomas (NCs), correlating with histopathology. This approach offers insights into tumor heterogeneity and potential therapeutic targets for aggressive NCs.

Keywords:

NUT carcinoma PRAME spatial transcriptomics tumoral heterogeneity

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Area of Science:

Oncology
Genomics
Spatial Biology

Background:

Nuclear protein in testis (NUT) carcinomas (NCs) are rare, aggressive tumors with known genetic alterations.
Tumoral heterogeneity in NCs is poorly understood, impacting treatment resistance and metastasis.
Spatial transcriptomics (ST) offers a novel method to explore tissue architecture and cellular interactions.

Observation:

Three sinonasal NC cases were analyzed using 10X Genomics Visium Spatial Gene Expression.
Transcriptomic data were processed and visualized using 10X Genomics Loupe Browser.
Distinct transcriptomic clusters correlated with histologic regions (tumor, stroma, normal epithelium).

Findings:

Statistically distinct transcriptomic clusters were identified in all NC cases.
Cluster composition mirrored morphologic features across tumor and normal tissue regions.
NC#3 exhibited fewer tumor clusters compared to NC#1 and NC#2.

Implications:

Spatial transcriptomic profiling aligns with NC histopathology while revealing significant cell type diversity.
Tumor heterogeneity within NCs, and across different NC cases, was elucidated.
Neural gene expression in a rapidly lethal NC case (NC#3) warrants further investigation for tumor progression insights.