Citations

Abstract Prior in vitro work in the human hepatoma cell lines Huh7 and HEP3B indicated that combination treatment of the BH3 mimetic, navitoclax, and the multi-kinase inhibitor, sorafenib, was more effective at inducing apoptosis than either compound alone. This current study was part of a phase I clinical trial to determine the maximum tolerated dose of concurrent navitoclax and sorafenib treatment in patients with relapsed or refractory solid organ tumors and sought to characterize the pharmacokinetics (PK) and pharmacodynamics (PD) of both agents in combination. Cleavage of cytokeratin 18 by caspase 3 was used as a biomarker for therapy-induced activation of apoptosis to determine if combination treatment results in an increase in apoptosis as previously observed in in vitro work. PK were assessed in 26 patients (ages 32 - 80) enrolled in a phase I clinical trial (NCT02143401). 150 mg of oral navitoclax was administered once daily for a seven day run-in (beginning Day -7) prior to 150 mg (Dose level 1) or 200 mg (Dose level 2) navitoclax concomitant treatment with 400 mg of twice daily oral sorafenib (Day 1). Samples for pharmacokinetic analysis were obtained on Day -7 and Day 1 prior to dosing and at 1, 2, 4, 8-12, and 24 hours post dosing. PK parameters were estimated by noncompartmental analysis using Phoenix® WinNonlin® Version 6.4. To examine the PD of both agents in combination, cytokeratin 18 cleavage was quantified by ELISA after the 7-day navitoclax run-in and on Day 2 or 4 and Day 8 of navitoclax and sorafenib combination treatment. PK estimates of maximum concentration, exposure, volume of distribution, and clearance for navitoclax on Day -7 and Day 1 were not significantly different, indicating a lack of navitoclax accumulation. Finally, no correlation was found between navitoclax exposure and apoptosis as indicated by cytokeratin-18 cleavage. This work was supported by the NCI Cancer Center Support Grant P30 CA15083 and NCI Experimental Therapeutics Phase I Grant UM1 CA186686. Citation Format: Emily J. Koubek, Brian A. Costello, Jun Yin, Renee M. McGovern, Sarah A. Buhrow, Renee A. Schoon, Carrie A. Strand, Yixing Jiang, Mitesh J. Borad, Naoko Takebe, Scott H. Kaufmann, Alex A. Adjei, Joel M. Reid. Pharmacokinetic analysis of navitoclax in combination with sorafenib in patients with relapsed or refractory solid organ tumors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT114.

Abstract Background: Atezolizumab (atezo) and bevacizumab (bev) combination therapy has demonstrated robust clinical activity in patients with unresectable HCC who have not received prior systemic therapy (Lee et al., APPLE 2019; Cheng et al., ESMO Asia 2019). In this exploratory analysis, we aimed to identify tumor-based molecular biomarkers that may be associated with clinical response or resistance to atezo + bev. We also investigated how VEGF blockade with bev could potentiate PD-L1 checkpoint inhibition with atezo in pts with advanced HCC. Methods: Archival tumor tissues or fresh biopsies taken prior to treatment were collected from HCC pts enrolled in the Phase 1b trial GO30140 (NCT02715531). Arm A (n = 104) was a single-arm evaluation of atezo + bev; Arm F (n = 119) was a randomized arm comparing atezo + bev with atezo. Whole-exome sequencing was carried out on these tumor tissues to determine tumor mutation burden (TMB). Gene expression in tumors was profiled by RNAseq analysis. The association between biomarker expression and clinical response (responders [R] vs. non-responders [NR]) or PFS was assessed by t-tests or Cox regression models, respectively. All p-values are descriptive. Results: In Arm A, 90/104 pts were biomarker evaluable. TMB was not associated with response to atezo + bev or PFS. In contrast, analysis of baseline tumor gene expression showed that pre-existing immunity appeared to be associated with clinical response and longer PFS, which included high expression of CD274 (PD-L1) (R vs. NR, p < 2.1 × 10−5; PFS: HR = 0.42 [0.25-0.72]), and T effector signature (GZMB, PRF1, CXCL9) (R vs. NR, p < 0.0004; PFS: HR = 0.46 [0.27-0.78]). Gene expression related to Notch pathway activation (i.e. high expression of HES1) appeared to be associated with lack of response to atezo + bev (p < 0.039) and shorter PFS (HR = 2.1 [1.3-3.6]). In Arm F, 91/119 pts were biomarker evaluable. High expression of VEGF receptor 2 (VEGFR2; HR = 0.36 [0.16-0.81]), Treg (HR = 0.35 [0.15-0.82]), myeloid inflammation (HR = 0.43 [0.19-0.95]), and TREM1/MDSC signatures (HR = 0.43 [0.19-0.94]) was associated with longer PFS in patients treated with atezo + bev than in those treated with atezo alone. Analysis of 12 serial biopsy pairs confirmed reduced levels of VEGFR2 and Treg signatures after atezo + bev treatment. Conclusion: We identified candidate biomarkers for predicting response to atezo + bev in HCC. Furthermore, the findings in Arm F are consistent with previous preclinical studies supporting a multi-faceted role of VEGF/VEGFR signaling in promoting immune suppression in addition to angiogenesis. Overall, the data presented here further support the mechanistic hypotheses on how anti-VEGF may combine with immune checkpoint blockade to increase its clinical benefit. As these results are exploratory, future study is needed to confirm these findings in a larger population. Citation Format: Andrew X. Zhu, Yinghui Guan, Alexander R. Abbas, Hartmut Koeppen, Shan Lu, Chih-Hung Hsu, Kyung-Hun Lee, Michael S. Lee, Aiwu Ruth He, Amit Mahipal, Beiying Ding, Jessica Spahn, Wendy Verret, Baek-Yeol Ryoo, Yulei Wang. Genomic correlates of clinical benefits from atezolizumab combined with bevacizumab vs. atezolizumab alone in patients with advanced hepatocellular carcinoma (HCC) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT044.

Abstract Background: PIM2 is overexpressed in hematopoietic and solid cancers, and is involved in multiple signaling pathways. In hematologic malignancies, PIM2 has been shown to be a pro-survival factor and demonstrated to be a possible therapeutic target. However, the role of PIM2 as a therapeutic target in solid cancers has not been fully elucidated. Methods: PIM2 expression was compared between normal and cancer tissues in The Cancer Genome Atlas (TCGA) datasets. Pan-PIM inhibitor treatment, as well as PIM2 overexpression/knockdown technique was utilized to investigate the PIM2 role in solid cancers. Multiple cancer models were utilized for in vitro and in vivo experiments to investigate if PIM2 as a therapeutic target and examine mechanism of anti-tumor activity by JP11646. Results: PIM2 was overexpressed in several types of cancer tissues, including breast, esophageal, head-neck, kidney, liver and endometrial cancers in TCGA. PIM2 overexpression promoted tumor growth in in vivo breast cancer mouse model. PIM2 inhibition by siRNA as well as pan-PIM inhibitor JP11646 activated apoptosis as seen by increased cleaved PARP. JP11646 treatment inhibited cancer cell proliferation in a dose-dependent manner in vitro in various types of solid cancers, including head-neck, ovarian, breast, prostate, liver, pancreatic, colorectal and non-small cell lung cancers. Interestingly, treatment with pan-PIM inhibitor JP11646 resulted in selective downregulation of PIM2 protein expression, but not PIM1 or PIM3 in breast cancer cell lines, BT549 and MDA-MB-231. The treatment also resulted in downregulation of phosphorylated downstream targets, 4EBP1 and TSC2 in breast cancer cells. However, additional proteasome inhibitor treatment blocked PIM2 downregulation and apoptosis activation was not seen. The result suggests that proteasome complex is required for PIM2 degradation which is necessary to induce apoptosis. JP11646 treatment inhibited tumor growth in breast, liver, pancreas, and non-small cell lung cancer in vivo xenograft models and was compared to multiple standard of care treatments showing advantage in lung tumors. Conclusion: We found that PIM2 promoted cancer progression in solid tumors. We show novel mechanism of JP11646 targeting PIM2 for degradation and induction of apoptosis. We show that PIM2 may serve as a novel therapeutic target for multiple types of solid cancers with enhanced therapeutic effect through protein degradation rather than kinase inhibition alone. Citation Format: Eriko Katsuta, Kazuaki Takabe, Alex Adjei, Mateusz Opyrchal. Novel mechanism of PIM2 inhibition leads to significant effect on solid tumors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6426.

Abstract Somatic variants in cancer-relevant genes are interpreted from multiple partially overlapping perspectives. When considered in discovery and translational research endeavors, it is important to determine if a particular variant observed in a gene of interest is oncogenic/pathogenic or not, as such knowledge provides the foundation on which targeted cancer treatment research is based. In contrast, clinical applications are dominated by diagnostic, prognostic, or therapeutic interpretations which in part also depends on underlying variant oncogenicity/pathogenicity. The Association for Molecular Pathology, the American Society of Clinical Oncology, and the College of American Pathologists (AMP/ASCO/CAP) have published structured somatic variant clinical interpretation guidelines which specifically address diagnostic, prognostic, and therapeutic implications. These guidelines have been well-received by the oncology community. Many variant knowledgebases, clinical laboratories/centers have adopted or are in the process of adopting these guidelines. The AMP/ASCO/CAP guidelines also describe different data types which are used to determine oncogenicity/pathogenicity of a variant, such as: population frequency, functional data, computational predictions, segregation, and somatic frequency. A second collaborative effort created the European Society for Medical Oncology (ESMO) Scale for Clinical Actionability of molecular Targets to provide a harmonized vocabulary that provides an evidence-based ranking system of molecular targets that supports their value as clinical targets. However, neither of these clinical guideline systems provide systematic and comprehensive procedures for aggregating population frequency, functional data, computational predictions, segregation, and somatic frequency to consistently interpret variant oncogenicity/pathogenicity, as has been published in the ACMG/AMP guidelines for interpretation of pathogenicity of germline variants. In order to address this unmet need for somatic variant oncogenicity/pathogenicity interpretation procedures, the Variant Interpretation for Cancer Consortium (VICC, a GA4GH driver project) Knowledge Curation and Interpretation Standards (KCIS) working group (WG) has developed a Standard Operating Procedure (SOP) with contributions from members of ClinGen Somatic Clinical Domain WG, and ClinGen Somatic/Germline variant curation WG using an approach similar to the ACMG/AMP germline pathogenicity guidelines to categorize evidence of oncogenicity/pathogenicity as very strong, strong, moderate or supporting. This SOP enables consistent and comprehensive assessment of oncogenicity/pathogenicity of somatic variants and latest version of an SOP can be found at https://cancervariants.org/wg/kcis/. Citation Format: Peter Horak, Malachi Griffith, Arpad Danos, Beth A. Pitel, Subha Madhavan, Xuelu Liu, Jennifer Lee, Gordana Raca, Shirley Li, Alex H. Wagner, Shashikant Kulkarni, Obi L. Griffith, Debyani Chakravarty, Dmitriy Sonkin. A standard operating procedure for the interpretation of oncogenicity/pathogenicity of somatic mutations [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5707.

Abstract Comprehensive interpretation of a patient's cancer genome is a cross-disciplinary process requiring the expertise of oncologists, molecular pathologists, genetic counselors, genomic scientists, and bioinformaticians. The Variant Interpretation for Cancer Consortium (VICC) has created a non-clinical forum for the variant interpretation process by connecting experts from multiple academic institutions and industry to create a Virtual Molecular Tumor Board (VMTB). During VICC-VMTB sessions, experts retrospectively discuss de-identified, challenging patient cases in the context of genomic interpretation guidelines to evaluate a patient's profile across several distinct components: genomic variants; disease context; therapeutic history; family history; demographic information; genomic assay information; and variant allele frequency. These components are processed through the prism of publically available knowledge and expertise of VMTB members, resulting in a broad spectrum of clinically relevant assertions about the patient's disease that may be of prognostic, diagnostic, or predictive relevance. Through these evaluations, the VICC-VMTB primarily works as a means of illuminating challenges in genomic interpretation and advancing the objectives of domain-specific VICC working groups. Examples of challenges that have been highlighted by the VICC-VMTB forum include: 1) inconsistent disease and therapy ontologies across resources are being addressed by Disease Harmonization & Drug Harmonization working groups, respectively; 2) use of machine-learning and natural language processing into clinical-grade variant interpretation are being addressed by the AI-Assisted Curation working group; 3) aggregation and harmonization of knowledgebase data into a centralized resource is being addressed by the Data Licensing and Variant Harmonization working groups; 4) inefficiencies in knowledgebase search functions are being addressed by the Search working group; 5) determination of accurate prediction of biological consequences of rare variants is being addressed by the In Silico Interpretation working group; and 6) standardization of genomic variant curation is being addressed by the Knowledge Curation and Interpretation Standards working group. These VICC working groups provide dedicated expert assemblies intended to specifically tackle these challenges, further increasing the breadth for which genomic information can be made useful in cancer variant interpretation. The VICC-VMTB has been a pertinent link between cancer genomes and clinical interpretation. We are confident VICC-VMTB will continue to be a gateway of acceleration and progress needed in the field of cancer interpretation to provide accurate and efficient answers for our patients in the future. Citation Format: Beth A. Pitel, Shruti Rao, Catherine Del Vecchio Fitz, Subha Madhavan, Rodrigo Dientsmann, Peter Horak, Ian King, Susan M. Mockus, Gordana Raca, Damian T. Rieke, Peter Rogan, Dmitriy Sonkin, David Tamborero, Ioannis S. Vlachos, Brian Walsh, Jeremy L. Warner, Malachi Griffith, Obi L. Griffith, Debyani Chakravarty, Alex H. Wagner. The Virtual Molecular Tumor Board of the Variant Interpretation for Cancer Consortium: A systematic gateway connecting cancer genome interpretation and progress in genomic knowledgebases in cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3222.

Abstract The Clinical Genome (ClinGen) Resource is a US National Human Genome Research Institute (NHGRI)-funded program dedicated to building an expert curated and freely available central resource that defines the clinical relevance of genes and variants for use in precision medicine. Teams of experts in various clinical domains come together as working groups within ClinGen to facilitate the interpretation, annotation and utilization of genes-variants for clinical application. Somatic Cancer is one such ClinGen Clinical Domain Working Group (CDWG) that consists of over 90 members worldwide, including clinicians, clinical laboratory diagnosticians, genomic scientists and bioinformaticians. Members of this CDWG identify high priority somatic variants in different cancer types that require expert curation and consensus in their clinical interpretation. In order to accurately implement practice guidelines/standards for variant interpretation, the Somatic Cancer CDWG recently established a somatic Variant Curation Expert Panel (VCEP) approval process. Based on their interest and clinical domain expertise, a subset of the CDWG members formed somatic VCEPs to perform authoritative curation on the shortlisted genes-somatic variants within the context of a disease, therapeutic indication or biological pathway. Expert curation within these VCEPs is performed by utilizing guidelines such as those recommended by AMP/ASCO/CAP (Li et al. 2017) and the Somatic Cancer CDWG (Ritter et al. 2016). Wherever necessary, the somatic VCEPs will develop: 1) gene- and disease-specific modifications to address gaps in existing variant assessment guidelines, 2) quantitative approaches for variant interpretation, and 3) implement standardized protocols for annotating somatic variants in genes for a specific disease, drug or biological pathway. Furthermore, ClinGen recently formed the Cancer Variant Interpretation (CVI) committee to provide support, review and feedback on the provisional somatic variant interpretation proposals developed by the VCEPs. The CVI provides somatic VCEPs with a preliminary approval before the final approval by the ClinGen CDWG oversight committee and ultimately ‘expert panel' status in ClinVar, an NCBI-maintained database of clinically relevant gene variants. NTRK fusions in cancer is the first Somatic VCEP going through the ClinGen Somatic Expert Panel approval process. Alterations in the FGFR pathway in GU cancers is the second somatic VCEP under consideration. The Somatic CDWG uses the CIViC (Clinical Interpretation of Variants in Cancer) platform for curation of somatic variants. To date, the CDWG has curated 268 evidence items relating to cancer variants in CIViC, 6 assertions, and 33 evidence source suggestions. The ultimate goal of the Somatic CDWG is to enhance the usability, dissemination and implementation of cancer somatic changes in the ClinGen resource and other cancer variant knowledgebases. Citation Format: Shruti Rao, Deborah Ritter, Arpad Danos, Gordana Raca, Angshumoy Roy, Kilannin Krysiak, Wan-Hsin Lin, Erica Barnell, Matthew McCoy, Beth Pitel, Dmitriy Sonkin, Jue Wang, Seyed Ali Hosseini, Shamini Selvarajah, Ian King, Rashmi Kanagal-Shamana, Xinjie Xu, Jeremy L. Warner, Funda Meric-Bernstam, Jason D. Merker, Marilyn Li, Alex H. Wagner, Malachi Griffith, Obi L. Griffith, Shashikant Kulkarni, Subha Madhavan. ClinGen somatic cancer working group: Disseminating standardized cancer molecular diagnostic data and evidence through global collaboration and expert curation [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3215.

Abstract The use of clinical gene sequencing is now commonplace, and genome analysts and molecular pathologists are often tasked with the labor-intensive process of interpreting the clinical significance of large numbers of tumor variants. Numerous independent knowledgebases have been constructed to alleviate this manual burden, however these knowledgebases are non-interoperable. As a result, the analyst is left with a difficult tradeoff: for each knowledgebase used the analyst must understand the nuances particular to that resource and integrate its evidence accordingly when generating the clinical report, but for each knowledgebase omitted there is increased potential for missed findings of clinical significance.The Variant Interpretation for Cancer Consortium (VICC; cancervariants.org) was formed as a driver project of the Global Alliance for Genomics and Health (GA4GH; ga4gh.org) to address this concern. VICC members include representatives from several major somatic interpretation knowledgebases including CIViC, OncoKB, Jax-CKB, the Weill Cornell PMKB, the IRB-Barcelona Cancer Biomarkers Database, and others. Previously, the VICC built and reported on a harmonized meta-knowledgebase of 19,551 biomarker associations of harmonized variants, diseases, drugs, and evidence across the constituent resources.In that study, we analyzed the frequency with which the tumor samples from the AACR Project GENIE cohort would match to harmonized associations. Variant matches increased dramatically from 57% to 86% when broader matching to regions describing categorical variants were allowed. Unlike precise sequence variants with specified alternate alleles, categorical variants describe a collection of potential variants with a common feature, such as “V600” (non-valine alleles at the 600 residue), “Exon 20 mutations” (all non-silent mutations in exon 20), or “Gain-of-function” (hypermorphic alterations that activate or amplify gene activity). However, matching observed sequence variants to categorical variants is challenging, as the latter are typically only described as unstructured text. Here we describe the expressive and computational GA4GH Variation Representation specification (vr-spec.readthedocs.io), which we co-developed as members of the GA4GH Genomic Knowledge Standards work stream. This specification provides a schema for common, precise forms of variation (e.g. SNVs and Indels) and the method for computing identifiers from these objects. We highlight key aspects of the specification and our work to apply it to the characterization of categorical variation, showcasing the variant terminology and classification tools developed by the VICC to support this effort. These standards and tools are free, open-source, and extensible, overcoming barriers to standardized variant knowledge sharing and search. Citation Format: Alex H. Wagner, Reece K. Hart, Larry Babb, Robert R. Freimuth, Adam Coffman, Yonghao Liang, Beth Pitel, Angshumoy Roy, Matthew Brush, Jennifer Lee, Anna Lu, Thomas Coard, Shruti Rao, Deborah Ritter, Brian Walsh, Susan Mockus, Peter Horak, Ian King, Dmitriy Sonkin, Subha Madhavan, Gordana Raca, Debyani Chakravarty, Malachi Griffith, Obi L. Griffith. Harmonization standards from the Variant Interpretation for Cancer Consortium [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1096.

Abstract Background: Persons of African ancestry (AA) experience a 1.5-2-fold risk of multiple myeloma (MM) compared to persons of European ancestry (EA). We assembled a set of MM patients with self-reported AA in order to evaluate the contribution of genetics to etiology in this high-risk group. Methods: Here we present the results of a meta-analysis of two GWAS in 1,813 cases and 8,871 controls of AA. We also conducted an admixture mapping scan to identify risk alleles associated with local ancestry, fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA, and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. Finally, we conducted an eQTL analysis measuring gene expression in those genes harboring a risk variant in malignant plasma cells from 292 of the patients from a single site. Results: In GWAS analysis, we identified two suggestive novel loci located at 9p24.3 and 9p13.1 at P<1 × 10-6, but no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. 20 of the 23 known EA risk variants showed directional consistency and 9 replicated at P<0.05 in AA individuals. In eight regions, we identified markers that better capture MM risk in persons of AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95%CI: 1.56, 2.11) increased MM risk compared to those with average risk (25-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P= 5.1 × 10–12). Conclusion: Our study shows that common genetic variation contributes to MM risk individuals of AA. This abstract is also being presented as Poster C040. Citation Format: Zhaohui Du, Niels Weinhold, Gregory Chi Song, Kristen A. Rand, David J. Van Den Berg, Amie E. Hwang, Xin Sheng, Victor Hom, Sikander Ailawadhi, Ajay K. Nooka, Seema Singhal, Karen Pawlish, Edward Peters, Cathryn Bock, Ann Mohrbacher, Alexander Stram, Sonja I. Berndt, William J. Blot, Graham Casey, Victoria L. Stevens, Rick Kittles, Phyllis J. Goodman, W. Ryan Diver, Anselm Hennis, Barbara Nemesure, Eric A. Klein, Benjamin A. Rybicki, Janet L. Stanford, John S. Witte, Lisa Signorello, Esther M. John, Leslie Bernstein, Antoinette Stroup, Owen W. Stephens, Maurizio Zangari, Frits Van Rhee, Andrew Olshan, Wei Zheng, Jennifer J. Hu, Regina Ziegler, Sarah J. Nyante, Sue Ann Ingles, Michael Press, John David Carpten, Stephen Chanock, Jayesh Mehta, Graham A Colditz, Jeffrey Wolf, Thomas G. Martin, Michael Tomasson, Mark A. Fiala, Howard Terebelo, Nalini Janakiraman, Laurence Kolonel, Kenneth C. Anderson, Loic Le Marchand, Daniel Auclair, Brian C.-H. Chiu, Elad Ziv, Daniel Stram, Ravi Vij, Leon Bernal-Mizrachi, Gareth J. Morgan, Jeffrey A. Zonder, Carol Ann Huff, Sagar Lonial, Robert Z. Orlowski, David V. Conti, Christopher A. Haiman, Wendy Cozen. A meta-analysis of genome-wide association study and eQTL analysis of multiple myeloma among African Americans [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr PR05.

Glial fibrillary acidic protein (GFAP) is cleared by the Food and Drug Administration (FDA) to determine need for head computed tomography (CT) within 12 h after mild traumatic brain injury (TBI) (Glasgow Coma Score [GCS] 13–15); S100 calcium-binding protein B (S100B) serves this function in Europe. This phase 1 biomarker cohort analysis of the multi-center, observational Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study compares GFAP's diagnostic performance, measured on a rapid point-of-care platform, against protein S100B to predict intracranial abnormalities on CT within 24 h post-injury across the spectrum of TBI (GCS 3–15). Head CT scan performed in TBI subjects and blood was collected for all consenting subjects presenting to 18 United States level 1 trauma centers. Plasma was analyzed on a point-of-care device prototype assay for GFAP and serum was analyzed for S100B. In 1359 patients with TBI (GCS 3–15), mean (standard deviation [SD]) age = 40.1 (17.0) years; 68% were male. Plasma GFAP levels were significantly higher in CT+ TBI subjects (median = 1358 pg/mL, interquartile range [IQR]: 472–3803) than in CT- TBI subjects (median = 116 pg/mL, IQR: 26–397) or orthopedic trauma controls ( n = 122; median = 13 pg/mL, IQR: 7–20), p < 0.001. Serum S100B levels were likewise higher in CT+ TBI subjects (median = 0.17 μg/L, IQR: 0.09–0.38) than in CT- TBI subjects (median = 0.10 μg/L, IQR: 0.06–0.18), p < 0.001. Receiver operating characteristic curves were generated for prediction of intracranial injury on admission CT scan; area under the curve (AUC) for GFAP was significantly higher than for S100B in the same cohort (GFAP AUC – 0.85, 95% confidence interval [CI] 0.83–0.87; S100B AUC – 0.67, 95% CI 0.64-0.70; p < 0.001). GFAP, measured on a point-of-care platform prototype assay, has high discriminative ability to predict intracranial abnormalities on CT scan in patients with TBI across the full injury spectrum of GCS 3–15 through 24 h post-injury. GFAP substantially outperforms S100B.