Identification of immune-based prostate cancer subtypes using mRNA expression. Issue 1 (29th January 2021)
- Record Type:
- Journal Article
- Title:
- Identification of immune-based prostate cancer subtypes using mRNA expression. Issue 1 (29th January 2021)
- Main Title:
- Identification of immune-based prostate cancer subtypes using mRNA expression
- Authors:
- Song, Jukun
Wang, Wei
Yuan, Yiwen
Ban, Yong
Su, Jiaming
Yuan, Dongbo
Chen, Weihong
Zhu, Jianguo - Abstract:
- Abstract: Immune infiltration in Prostate Cancer (PCa) was reported to be strongly associated with clinical outcomes. However, previous research could not elucidate the diversity of different immune cell types that contribute to the functioning of the immune response system. In the present study, the CIBERSORT method was employed to evaluate the relative proportions of immune cell profiling in PCa samples, adjacent tumor samples and normal samples. Three types of molecular classification were identified in tumor samples using the 'CancerSubtypes' package of the R software. Each subtype had specific molecular and clinical characteristics. In addition, functional enrichment was analyzed in each subtype. The submap and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms were also used to predict clinical response to the immune checkpoint blockade. Moreover, the Genomics of Drug Sensitivity in Cancer (GDSC) database was employed to screen for potential chemotherapeutic targets for the treatment of PCa. The results showed that Cluster I was associated with advanced PCa and was more likely to respond to immunotherapy. The findings demonstrated that differences in immune responses may be important drivers of PCa progression and response to treatment. Therefore, this comprehensive assessment of the 22 immune cell types in the PCa Tumor Environment (TEM) provides insights on the mechanisms of tumor response to immunotherapy and may help clinicians explore the development of newAbstract: Immune infiltration in Prostate Cancer (PCa) was reported to be strongly associated with clinical outcomes. However, previous research could not elucidate the diversity of different immune cell types that contribute to the functioning of the immune response system. In the present study, the CIBERSORT method was employed to evaluate the relative proportions of immune cell profiling in PCa samples, adjacent tumor samples and normal samples. Three types of molecular classification were identified in tumor samples using the 'CancerSubtypes' package of the R software. Each subtype had specific molecular and clinical characteristics. In addition, functional enrichment was analyzed in each subtype. The submap and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms were also used to predict clinical response to the immune checkpoint blockade. Moreover, the Genomics of Drug Sensitivity in Cancer (GDSC) database was employed to screen for potential chemotherapeutic targets for the treatment of PCa. The results showed that Cluster I was associated with advanced PCa and was more likely to respond to immunotherapy. The findings demonstrated that differences in immune responses may be important drivers of PCa progression and response to treatment. Therefore, this comprehensive assessment of the 22 immune cell types in the PCa Tumor Environment (TEM) provides insights on the mechanisms of tumor response to immunotherapy and may help clinicians explore the development of new drugs. … (more)
- Is Part Of:
- Bioscience reports. Volume 41:Issue 1(2021)
- Journal:
- Bioscience reports
- Issue:
- Volume 41:Issue 1(2021)
- Issue Display:
- Volume 41, Issue 1 (2021)
- Year:
- 2021
- Volume:
- 41
- Issue:
- 1
- Issue Sort Value:
- 2021-0041-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-01-29
- Subjects:
- CIBERSORT algorithm -- Clinical application -- Immunotherapy -- Prostate cancer -- Tumor-infiltrating immune cells
Molecular biology -- Periodicals
Cytology -- Periodicals
572.8 - Journal URLs:
- http://www.bioscirep.org/ ↗
http://firstsearch.oclc.org ↗ - DOI:
- 10.1042/BSR20201533 ↗
- Languages:
- English
- ISSNs:
- 0144-8463
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 2089.611600
British Library HMNTS - ELD Digital store - Ingest File:
- 15868.xml