» Articles » PMID: 29258857

Understanding Preanalytical Variables and Their Effects on Clinical Biomarkers of Oncology and Immunotherapy

Overview
Specialty Oncology
Date 2017 Dec 21
PMID 29258857
Citations 30
Authors
Affiliations
Soon will be listed here.
Abstract

Identifying a suitable course of immunotherapy treatment for a given patient as well as monitoring treatment response is heavily reliant on biomarkers detected and quantified in blood and tissue biospecimens. Suboptimal or variable biospecimen collection, processing, and storage practices have the potential to alter clinically relevant biomarkers, including those used in cancer immunotherapy. In the present review, we summarize effects reported for immunologically relevant biomarkers and highlight preanalytical factors associated with specific analytical platforms and assays used to predict and gauge immunotherapy response. Given that many of the effects introduced by preanalytical variability are gene-, transcript-, and protein-specific, biospecimen practices should be standardized and validated for each biomarker and assay to ensure accurate results and facilitate clinical implementation of newly identified immunotherapy approaches.

Citing Articles

Regulatory, Translational, and Operational Considerations for the Incorporation of Biomarkers in Drug Development.

Hatcher H, Stankeviciute S, Learn C, Qu A Ther Innov Regul Sci. 2025; .

PMID: 40057669 DOI: 10.1007/s43441-025-00763-5.


Canadian Consensus Recommendations for Predictive Biomarker Testing in Gastric and Gastroesophageal Junction Adenocarcinoma.

Brezden-Masley C, Fiset P, Cheung C, Arnason T, Bateman J, Borduas M Curr Oncol. 2024; 31(12):7770-7786.

PMID: 39727695 PMC: 11674259. DOI: 10.3390/curroncol31120572.


Analysis of DNA Methylation in Gliomas: Assessment of Preanalytical Variables.

Bomsztyk K, Mar D, Denisenko O, Powell S, Vishnoi M, Yin Z Lab Invest. 2024; 104(12):102160.

PMID: 39426568 PMC: 11709230. DOI: 10.1016/j.labinv.2024.102160.


Circulating tumour DNA analysis for early detection of lung cancer: a systematic review.

Lam W, Bai J, Ma M, Cheung Y, Jiang P Ann Transl Med. 2024; 12(4):64.

PMID: 39118954 PMC: 11304429. DOI: 10.21037/atm-23-1572.


Insight into the Functional Dynamics and Challenges of Exosomes in Pharmaceutical Innovation and Precision Medicine.

Sharma A, Yadav A, Nandy A, Ghatak S Pharmaceutics. 2024; 16(6).

PMID: 38931833 PMC: 11206934. DOI: 10.3390/pharmaceutics16060709.


References
1.
Xie Q, Gao W, Li J, Qiao T, Jin J, Deng H . Correlation of cortisol in 1-cm hair segment with salivary cortisol in human: hair cortisol as an endogenous biomarker. Clin Chem Lab Med. 2011; 49(12):2013-9. DOI: 10.1515/CCLM.2011.706. View

2.
Herbst R, Soria J, Kowanetz M, Fine G, Hamid O, Gordon M . Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature. 2014; 515(7528):563-7. PMC: 4836193. DOI: 10.1038/nature14011. View

3.
Kalmar A, Peterfia B, Wichmann B, Patai A, Bartak B, Nagy Z . Comparison of Automated and Manual DNA Isolation Methods for DNA Methylation Analysis of Biopsy, Fresh Frozen, and Formalin-Fixed, Paraffin-Embedded Colorectal Cancer Samples. J Lab Autom. 2015; 20(6):642-51. DOI: 10.1177/2211068214565903. View

4.
Nielsen T, Wallden B, Schaper C, Ferree S, Liu S, Gao D . Analytical validation of the PAM50-based Prosigna Breast Cancer Prognostic Gene Signature Assay and nCounter Analysis System using formalin-fixed paraffin-embedded breast tumor specimens. BMC Cancer. 2014; 14:177. PMC: 4008304. DOI: 10.1186/1471-2407-14-177. View

5.
Grasselli J, Elez E, Caratu G, Matito J, Santos C, Macarulla T . Concordance of blood- and tumor-based detection of RAS mutations to guide anti-EGFR therapy in metastatic colorectal cancer. Ann Oncol. 2017; 28(6):1294-1301. PMC: 5834108. DOI: 10.1093/annonc/mdx112. View