| Accession |
PRJCA014905 |
| Title |
Multi-view progression diagnosis of thyroid cancer by integrating platelet transcriptomes and blood routine tests |
| Relevance |
Medical |
| Data types |
Transcriptome or Gene expression
|
| Organisms |
Homo sapiens
|
| Description |
Thyroid cancer is the most common type of endocrine system cancers. The pre-cancer and early stages are usually benign or slowly growing, and do not need invasive treatments. While thyroid cancer enters its metastasized stage, thyroidectomy is recommended together with drug treatments. This study investigated the challenging classification task of four classes of samples, i.e., normal controls (N), thyroid adenomas (TA), papillary thyroid cancers (PTC) and metastasized papillary thyroid cancers (MPTC). We proposed a multi-view progression diagnosis framework ThyroidBloodTest to integrate the two views of RNA-seq platelet transcriptomes (View-T) and blood routine (View-B) features. Eleven feature selection algorithms and seven classifiers were evaluated for both views. The experimental data suggested the importances of choosing appropriate data analysis algorithms and feature engineering technique like principal component analysis (PCA). The best ThyroidBloodTest model achieved Acc=0.8750 for the four-class classification task of the N/TA/PTC/MPTC samples based on the integrated feature space of View-T and View-B. The cellular localization cytosol and three post-translational modification types acetylation/phosphorylation/ubiquitination were observed to be enriched in the proteins encoded by the View-T biomarkers. |
| Sample scope |
Monoisolate |
| Release date |
2023-03-13 |
| Publication |
| PubMed ID |
Article title |
Journal name |
DOI |
Year |
|
|
Multi-view progression diagnosis of thyroid cancer by integrating platelet transcriptomes and blood routine tests
|
Computers in Biology and Medicine
|
10.1016/j.compbiomed.2023.107613
|
2023
|
|
|
| Grants |
| Agency |
program |
Grant ID |
Grant title |
| National Natural Science Foundation of China (NSFC)
|
|
RA-2022-108
|
|
|
|
| Submitter |
yuling
shen (s_yl02@163.com)
|
| Organization |
Renji Hospital, School of Medicine, Shanghai Jiao Tong University |
| Submission date |
2023-02-13 |
