The impact of whole genome and transcriptome analysis (WGTA) on predictive biomarker discovery and diagnostic accuracy of advanced malignancies. (8th March 2022)
- Record Type:
- Journal Article
- Title:
- The impact of whole genome and transcriptome analysis (WGTA) on predictive biomarker discovery and diagnostic accuracy of advanced malignancies. (8th March 2022)
- Main Title:
- The impact of whole genome and transcriptome analysis (WGTA) on predictive biomarker discovery and diagnostic accuracy of advanced malignancies
- Authors:
- Tessier‐Cloutier, Basile
Grewal, Jasleen K
Jones, Martin R
Pleasance, Erin
Shen, Yaoqing
Cai, Ellen
Dunham, Chris
Hoang, Lynn
Horst, Basil
Huntsman, David G
Ionescu, Diana
Karnezis, Anthony N
Lee, Anna F
Lee, Cheng Han
Lee, Tae Hoon
Twa, David DW
Mungall, Andrew J
Mungall, Karen
Naso, Julia R
Ng, Tony
Schaeffer, David F
Sheffield, Brandon S
Skinnider, Brian
Smith, Tyler
Williamson, Laura
Zhong, Ellia
Regier, Dean A
Laskin, Janessa
Marra, Marco A
Gilks, C Blake
Jones, Steven JM
Yip, Stephen
… (more) - Abstract:
- Abstract: In this study, we evaluate the impact of whole genome and transcriptome analysis (WGTA) on predictive molecular profiling and histologic diagnosis in a cohort of advanced malignancies. WGTA was used to generate reports including molecular alterations and site/tissue of origin prediction. Two reviewers analyzed genomic reports, clinical history, and tumor pathology. We used National Comprehensive Cancer Network (NCCN) consensus guidelines, Food and Drug Administration (FDA) approvals, and provincially reimbursed treatments to define genomic biomarkers associated with approved targeted therapeutic options (TTOs). Tumor tissue/site of origin was reassessed for most cases using genomic analysis, including a machine learning algorithm (Supervised Cancer Origin Prediction Using Expression [SCOPE]) trained on The Cancer Genome Atlas data. WGTA was performed on 652 cases, including a range of primary tumor types/tumor sites and 15 malignant tumors of uncertain histogenesis (MTUH). At the time WGTA was performed, alterations associated with an approved TTO were identified in 39 (6%) cases; 3 of these were not identified through routine pathology workup. In seven (1%) cases, the pathology workup either failed, was not performed, or gave a different result from the WGTA. Approved TTOs identified by WGTA increased to 103 (16%) when applying 2021 guidelines. The histopathologic diagnosis was reviewed in 389 cases and agreed with the diagnostic consensus after WGTA in 94% ofAbstract: In this study, we evaluate the impact of whole genome and transcriptome analysis (WGTA) on predictive molecular profiling and histologic diagnosis in a cohort of advanced malignancies. WGTA was used to generate reports including molecular alterations and site/tissue of origin prediction. Two reviewers analyzed genomic reports, clinical history, and tumor pathology. We used National Comprehensive Cancer Network (NCCN) consensus guidelines, Food and Drug Administration (FDA) approvals, and provincially reimbursed treatments to define genomic biomarkers associated with approved targeted therapeutic options (TTOs). Tumor tissue/site of origin was reassessed for most cases using genomic analysis, including a machine learning algorithm (Supervised Cancer Origin Prediction Using Expression [SCOPE]) trained on The Cancer Genome Atlas data. WGTA was performed on 652 cases, including a range of primary tumor types/tumor sites and 15 malignant tumors of uncertain histogenesis (MTUH). At the time WGTA was performed, alterations associated with an approved TTO were identified in 39 (6%) cases; 3 of these were not identified through routine pathology workup. In seven (1%) cases, the pathology workup either failed, was not performed, or gave a different result from the WGTA. Approved TTOs identified by WGTA increased to 103 (16%) when applying 2021 guidelines. The histopathologic diagnosis was reviewed in 389 cases and agreed with the diagnostic consensus after WGTA in 94% of non‐MTUH cases ( n = 374). The remainder included situations where the morphologic diagnosis was changed based on WGTA and clinical data (0.5%), or where the WGTA was non‐contributory (5%). The 15 MTUH were all diagnosed as specific tumor types by WGTA. Tumor board reviews including WGTA agreed with almost all initial predictive molecular profile and histopathologic diagnoses. WGTA was a powerful tool to assign site/tissue of origin in MTUH. Current efforts focus on improving therapeutic predictive power and decreasing cost to enhance use of WGTA data as a routine clinical test. … (more)
- Is Part Of:
- Journal of pathology. Volume 8:Number 4(2022)
- Journal:
- Journal of pathology
- Issue:
- Volume 8:Number 4(2022)
- Issue Display:
- Volume 8, Issue 4 (2022)
- Year:
- 2022
- Volume:
- 8
- Issue:
- 4
- Issue Sort Value:
- 2022-0008-0004-0000
- Page Start:
- 395
- Page End:
- 407
- Publication Date:
- 2022-03-08
- Subjects:
- biomarker -- diagnostic -- WGTA -- pathology -- precision medicine -- oncology -- cancer of unknown primary -- machine learning
Pathology -- Periodicals
Diagnosis, Laboratory -- Periodicals
616.07 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2056-4538 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/cjp2.265 ↗
- Languages:
- English
- ISSNs:
- 2056-4538
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21871.xml