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Related Concept Videos

Classification of Epithelial Tissues: Overview01:22

Classification of Epithelial Tissues: Overview

Epithelial tissues are classified according to the shape of the cells and the number of cell layers formed. Cell shapes can be squamous (flattened and thin), cuboidal (square-like, as wide as it is tall), or columnar (rectangular, taller than it is wide). Additionally, the nucleus shape helps identify the type of epithelial cells. Squamous cells have flattened disc-shaped nuclei, cuboidal cells have spherical nuclei, and columnar cells have elongated nuclei.
Based on the number of cell layers,...
Classification of Epithelial Tissues: Stratified Epithelium01:29

Classification of Epithelial Tissues: Stratified Epithelium

Stratified epithelium consists of several stacked layers of cells. They provide the durability to withstand constant physical and chemical attacks. Stratified epithelium is named after the shape of the most apical layer of cells. Stratified squamous epithelium is the most common type found in the human body. In this tissue, the apical cells are squamous, whereas the basal layer contains either columnar or cuboidal cells. The basal cells divide to form new daughter cells, which gradually become...
Classification of Epithelial Tissues: Glandular Epithelium01:20

Classification of Epithelial Tissues: Glandular Epithelium

The glandular epithelium is made of one or more epithelial cells modified to synthesize and secrete chemical substances. Glandular epithelia can be classified based on cell number. Unicellular glands have individual secretory cells scattered across the epithelial monolayer. In contrast, multicellular glands consist of a hollow tubular duct attached to the cluster of secretory cells located in the deep pockets.
Multicellular glands are formed during early development when epithelial budding...

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Related Experiment Video

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Tumor Subtype Classification Tool for HPV-associated Head and Neck Cancers.

Shiting Li1, Bailey F Garb1, Tingting Qin1

  • 1Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan, USA.

Biorxiv : the Preprint Server for Biology
|July 19, 2024
PubMed
Summary

A new machine learning classifier accurately subtypes Human Papillomavirus-positive Head and Neck Squamous Cell Carcinoma (HPV+ HNSCC) into IMU and KRT molecular subtypes. This tool aids in understanding distinct tumor characteristics and potential treatment strategies.

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Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Human Papillomavirus-associated Head and Neck Squamous Cell Carcinoma (HPV+ HNSCC) exhibits distinct molecular subtypes: IMU (immune strong) and KRT (highly keratinized).
  • These subtypes possess different carcinogenic pathways, clinical outcomes, and may require tailored treatment approaches.
  • A standardized method for classifying HPV+ HNSCC tumors into these subtypes is currently lacking.

Purpose of the Study:

  • To develop and validate a robust machine learning classifier for standardizing HPV+ HNSCC subtyping.
  • To investigate the clinical, demographic, and molecular features associated with each subtype through a meta-analysis of patient cohorts.

Main Methods:

  • RNA sequencing (RNA-seq) data from 229 HPV+ HNSCC samples across four cohorts were utilized.
  • An ensemble machine learning approach, incorporating five algorithms and multiple gene sets, was employed for classification.
  • Classifier performance was rigorously tested and validated on independent patient cohorts.

Main Results:

  • The developed classifier achieved 100% accuracy in the test set and demonstrated successful separation in validation cohorts.
  • Significant associations were identified between subtypes and 24 of 39 tested clinicodemographic and molecular variables.
  • The IMU subtype correlated with epithelial-mesenchymal transition and immune cell infiltration, while the KRT subtype showed higher keratinization and a higher proportion of female patients.

Conclusions:

  • This study presents a reliable RNA-seq-based classifier for subtyping HPV+ HNSCC into IMU and KRT categories.
  • The findings enhance the understanding of HPV+ HNSCC molecular subtypes and their associated features.
  • The developed tool and insights are crucial for advancing personalized treatment strategies in HPV+ HNSCC.