# Pre-analytical variables of bioanalytes affecting the accuracy of PTCL diagnostic and prognostic genetic signatures > **NIH NIH U01** · UNIVERSITY OF NEBRASKA MEDICAL CENTER · 2022 · $359,962 ## Abstract Abstract Peripheral T-cell lymphomas (PTCL) represent approximately 12-15% of all NHL in the western world and are associated with dismal prognosis. Furthermore, the diagnosis is challenging as 30-50% of PTCL cases cannot be assigned to a specific entity and are categorized as PTCL-not otherwise specified (PTCL-NOS). We have defined robust gene expression signatures that can differentiate the five common PTCLs entities: angioimmunoblastic T-cell lymphoma (AITL), anaplastic lymphoma kinase positive anaplastic large-cell lymphoma (ALK (+) ALCL), ALK- negative anaplastic large-cell lymphoma (ALK (-) ALCL), adult T-cell leukemia/lymphoma (ATLL), and extra-nodal natural killer/T-cell lymphoma (ENKTCL). PTCL-NOS can be divided into two distinct biological and prognostic subgroups (PTCL-TBX21 and PTCL-GATA3 subgroups). We translated the RNA based diagnostic and prognostic algorithms for formalin fixed paraffin embedded (FFPE) tissues for widespread clinical usage with high sensitivity and specificity. We also identified distinguishing genetic lesions in PTCL subtypes using corresponding DNA , and demonstrated that such lesion can be validated using shallow whole genome analysis (sWGA) in corresponding plasma cell-free DNA, thus liquid biopsy can aid in diagnosis and disease monitoring. Since the biospecimen processing, and hence quality, varies significantly in routine clinical pathology laboratories, the reliability of RNA or DNA based signatures need to be evaluated under variable circumstances. It is essential to determine how the robustness of the assay may be affected by pre-analytical variables before the novel diagnostic tools can be applied to large studies or routine clinical practice. We hypothesize that a comprehensive evaluation of pre-analytical variables of biospecimen will lead to optimized bio-specimen procurement framework leading to improved diagnostic accuracy and reproducibility in tissue and liquid biopsy setting and can be standardized in an inter-CLIA lab setting for routine clinical practice/trials. This proposal aims to establish standardized, evidence-based procedures on bio-specimen (RNA/DNA) processing, storage and transportation to ensure accurate, reproducible assay performance. The identified conditions and parameters will be validated on prospective samples, preferably in a clinical trial setting, so findings can be correlated with clinical data. Thus, three specific aims are proposed: Specific Aim 1: To determine pre-analytical variables that affects the reliability of RNA-based assays in FFPE tissue Specific Aim 2: To identify pre-analytical factors affecting circulating tumor DNA (ct-DNA) detection and quantification in patients with PTCL Specific Aim 3: To validate harmonization of the pre-analytical variables in improving PTCL diagnostic or prognostic assay in an inter-CLIA (Clinical Laboratory Improvement Amendments) lab setting The studies will lead to robust protocols that optimize the preservation biomolecules... ## Key facts - **NIH application ID:** 10491082 - **Project number:** 5U01CA253218-02 - **Recipient organization:** UNIVERSITY OF NEBRASKA MEDICAL CENTER - **Principal Investigator:** Wing C. Chan - **Activity code:** U01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $359,962 - **Award type:** 5 - **Project period:** 2021-09-20 → 2026-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10491082 ## Citation > US National Institutes of Health, RePORTER application 10491082, Pre-analytical variables of bioanalytes affecting the accuracy of PTCL diagnostic and prognostic genetic signatures (5U01CA253218-02). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/10491082. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*