Identification of key classification features of early cervical squamous cell carcinoma. (August 2021)
- Record Type:
- Journal Article
- Title:
- Identification of key classification features of early cervical squamous cell carcinoma. (August 2021)
- Main Title:
- Identification of key classification features of early cervical squamous cell carcinoma
- Authors:
- Wang, Xiaoxi
Cao, ACheng
Hou, ZhiChao
Li, Xiaoqin
Gao, Bin - Abstract:
- Highlights: An analysis process of cancer subtype classification based on multi-genomics data was established. Two subtypes of cervical squamous cell carcinoma with significant clinical differences were identified. Subtypes of early cervical squamous carcinoma are mainly driven by DNA methylation. The key classification features with key biological functions and accurate classification were identified. Abstract: Despite the tremendous progress in molecular analysis of pan-cancer, little is known regarding molecular classification of cervical squamous cell carcinoma. In this study, we adopted a multi-omics approach to identify potential key classification features of cervical squamous cell carcinoma. Specifically, we analyzed mRNA, and microRNA (miRNA) expression data, as well as DNA methylation and copy number variation in cervical squamous cell carcinoma cases, using datasets obtained from The Cancer Genome Atlas (TCGA). Moreover, we identified molecules in each dimension, as well as integrated and clustered filtered classification features, and used them to distinguish different subtypes. The resulting key classification features were used to establish a classification model for cervical squamous cell carcinoma. Our results revealed two cervical squamous cell carcinoma subtypes, with significant differences across clinical survival levels, as well as 8 key classification features of cervical squamous cell carcinomas. These findings are expected to provide importantHighlights: An analysis process of cancer subtype classification based on multi-genomics data was established. Two subtypes of cervical squamous cell carcinoma with significant clinical differences were identified. Subtypes of early cervical squamous carcinoma are mainly driven by DNA methylation. The key classification features with key biological functions and accurate classification were identified. Abstract: Despite the tremendous progress in molecular analysis of pan-cancer, little is known regarding molecular classification of cervical squamous cell carcinoma. In this study, we adopted a multi-omics approach to identify potential key classification features of cervical squamous cell carcinoma. Specifically, we analyzed mRNA, and microRNA (miRNA) expression data, as well as DNA methylation and copy number variation in cervical squamous cell carcinoma cases, using datasets obtained from The Cancer Genome Atlas (TCGA). Moreover, we identified molecules in each dimension, as well as integrated and clustered filtered classification features, and used them to distinguish different subtypes. The resulting key classification features were used to establish a classification model for cervical squamous cell carcinoma. Our results revealed two cervical squamous cell carcinoma subtypes, with significant differences across clinical survival levels, as well as 8 key classification features of cervical squamous cell carcinomas. These findings are expected to provide important references for early classification of cervical squamous cell carcinoma and identification of classification markers. … (more)
- Is Part Of:
- Computational biology and chemistry. Volume 93(2021)
- Journal:
- Computational biology and chemistry
- Issue:
- Volume 93(2021)
- Issue Display:
- Volume 93, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 93
- Issue:
- 2021
- Issue Sort Value:
- 2021-0093-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-08
- Subjects:
- Multi-omics -- Classification markers -- Subtype classification -- Cervical squamous cell carcinoma -- Early stage of cancer
Chemistry -- Data processing -- Periodicals
Biology -- Data processing -- Periodicals
Biochemistry -- Data processing
Biology -- Data processing
Molecular biology -- Data processing
Periodicals
Electronic journals
542.85 - Journal URLs:
- http://www.sciencedirect.com/science/journal/14769271 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.compbiolchem.2021.107531 ↗
- Languages:
- English
- ISSNs:
- 1476-9271
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3390.576700
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 17800.xml