In:
Veterinary and Comparative Oncology, Wiley, Vol. 21, No. 1 ( 2023-03), p. 73-81
Abstract:
Canine mammary gland tumours (CMTs) constitute the most common cancer in female dogs and comprise approximately 50% of all canine cancers. With the advent of high‐throughput technologies such as microarray and next‐generation sequencing, the molecular phenotyping (classification) of various cancers has been extensively developed. The present study used a canine RNA‐sequencing dataset, namely GSE119810, to classify 113 malignant CMTs and 64 matched normal samples via an unsupervised hierarchical algorithm with a view to evaluating the association between the resulting subtypes (clusters) ( n = 4) and clinical and molecular characteristics. Finally, a molecular classifier was developed, and it detected 1 high‐risk molecular subtype in the training dataset (GSE119810) and 2 independent validation datasets (GSE20718 and GSE22516). Our results revealed four molecular subtypes (C2–C5) in malignant CMTs. Furthermore, the normal samples constituted a distinct group in the clustering analysis. Marked significant associations were observed between the molecular subtypes (especially C5) and clinical/molecular features, including positive lymphatic invasion, high tumour grades, histopathology diagnoses, short survival and high TP53 mutation rates ( ps 〈 .05). The high‐risk subtype (C5) was further characterized through the development of a cell cycle‐based gene signature, which comprised 37 proliferation‐related genes according to the support vector machine algorithm. This signature identified the high‐risk group in both training and validation datasets ( ps 〈 .001). In the validation analysis, our potential classifier robustly predicted patients with positive lymphatic invasion, metastases and short survival.
Type of Medium:
Online Resource
ISSN:
1476-5810
,
1476-5829
Language:
English
Publisher:
Wiley
Publication Date:
2023
detail.hit.zdb_id:
2129634-0
SSG:
22
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