As an astrocytic protein specific to the central nervous system, S100b is a potentially useful marker in outcome prediction after traumatic brain injury (TBI). Some studies have questioned the validity of S100b, citing the extracerebral origins of the protein as reducing the specificity of the marker. This study evaluated S100b as a prognostic biomarker in adult subjects with severe TBI (sTBI) by comparing outcomes with S100b temporal profiles generated from both cerebrospinal fluid (CSF) (n = 138 subjects) and serum (n = 80 subjects) samples across a 6-day time course. Long-bone fracture, Injury Severity Score (ISS), and isolated head injury status were variables used to assess extracerebral sources of S100b in serum. After TBI, CSF and serum S100b levels were increased over healthy controls across the first 6 days post-TBI (p ≤ 0.005 and p ≤ 0.031). Though CSF and serum levels were highly correlated during early time points post-TBI, this association diminished over time. Bivariate analysis showed that subjects who had temporal CSF profiles with higher S100b concentrations had higher acute mortality (p < 0.001) and worse Glasgow Outcome Scale (GOS; p = 0.002) and Disability Rating Scale (DRS) scores (p = 0.039) 6 months post-injury. Possibly as a result of extracerebral sources of S100b in serum, as represented by high ISS scores (p = 0.032), temporal serum profiles were associated with acute mortality (p = 0.015). High CSF S100b levels were observed in women (p = 0.022) and older subjects (p = 0.004). Multivariate logistic regression confirmed CSF S100b profiles in predicting GOS and DRS and showed mean and peak serum S100b as acute mortality predictors after sTBI.

Over the last decade, biomarker research has identified potential biomarkers for the diagnosis, prognosis, and management of traumatic brain injury (TBI). Several cerebrospinal fluid (CSF) and serum biomarkers have shown promise in predicting long-term outcome after severe TBI. Despite this increased focus on identifying biomarkers for outcome prognostication after a severe TBI, several challenges still exist in effectively modeling the significant heterogeneity observed in TBI-related pathology, as well as the biomarker-outcome relationships. Biomarker data collected over time are usually summarized into single-point estimates (e.g., average or peak biomarker levels), which are, in turn, used to examine the relationships between biomarker levels and outcomes. Further, many biomarker studies to date have focused on the prediction power of biomarkers without controlling for potential clinical and demographic confounders that have been previously shown to affect long-term outcome. In this article, we demonstrate the application of a practical approach to delineate and describe distinct subpopulations having similar longitudinal biomarker profiles and to model the relationships between these biomarker profiles and outcomes while taking into account potential confounding factors. As an example, we demonstrate a group-based modeling technique to identify temporal S100 calcium-binding protein B (S100b) profiles, measured from CSF over the first week post-injury, in a sample of adult subjects with TBI, and we use multivariate logistic regression to show that the prediction power of S100b biomarker profiles can be superior to the prediction power of single-point estimates.

This study was partly funded by a grant from the Robert Wood Johnson Foundation for use in data creation. Maciejewski was supported by a Research Career Scientist Award from the Department of Veterans Affairs (RCS 10-391) and owns stock in Amgen. Farley reports consultancy fees from Daiichi Sankyo outside of the conduct of this study. The other authors report no financial or other conflicts of interest related to the subject of this article. The views expressed in this article are those of the authors and do not reflect the position or policy of the Centers for Medicare & Medicaid Services, University of North Carolina at Chapel Hill, Department of Veteran Affairs, or Duke University. Study design and concept were contributed by Amin and Domino, along with Farley and Maciejewski. Domino collected the data, and data interpretation was performed primarily by Amin, along with Domino, with assistance from Farley and Maciejewski. The manuscript was primarily written by Amin, along with Domino, and revised by all the authors.

The biochemical cascades associated with cell death after traumatic brain injury (TBI) involve both pro-survival and pro-apoptotic proteins. We hypothesized that elevated cerebrospinal fluid (CSF) Bcl-2 and cytochrome C (CytoC) levels over time would reflect cellular injury response and predict long-term outcomes after TBI. Cerebrospinal fluid Bcl-2 and CytoC levels were measured for 6 days after injury for adults with severe TBI (N=76 subjects; N=277 samples). Group-based trajectory analysis was used to generate distinct temporal biomarker profiles that were compared with Glasgow Outcome Scale (GOS) and Disability Rating Scale (DRS) scores at 6 and 12 months after TBI. Subjects with persistently elevated temporal Bcl-2 and CytoC profiles compared with healthy controls had the worst outcomes at 6 and 12 months (P≤0.027). Those with CytoC profiles near controls had better long-term outcomes, and those with declining CytoC levels over time had intermediate outcomes. Subjects with Bcl-2 profiles that remained near controls had better outcomes than those with consistently elevated Bcl-2 profiles. However, subjects with Bcl-2 values that started near controls and steadily rose over time had 100% good outcomes by 12 months after TBI. These results show the prognostic value of Bcl-2 and CytoC profiles and suggest a dynamic apoptotic and pro-survival response to TBI.

Background: Pathological complete response (pCR) is accepted by FDA as a surrogate endpoint for accelerated approval of targeted agents in combination with chemotherapy based on better long-term outcomes compared to residual disease (Cortazar 2014). Methods: The multi-center, adaptively-randomized I-SPY2 platform trial uses pCR as the primary endpoint to identify investigational agents that will improve outcomes in women with stage 2/3 breast cancer with high risk of early recurrence, across all signatures, based on hormone receptor (HR), HER2, and 70-gene (MammaPrint) status. For patients with HR+ HER2- tumors, only 70-gene (Mammaprint) high-risk patients are enrolled. To date, 1200+ patients have been randomized to one of 14 arms: control (paclitaxel followed by AC); veliparib/carboplatin; neratinib; MK2206; trebananib; trastuzumab/pertuzumab; ado-trastuzumab emtansine/pertuzumab; pembrolizumabx4; ganitumab/metformin; ganetespib; PLX-3397. 7 agents graduated in at least one signature (&gt; 85% probability of success in a 300-patient phase III confirmatory trial); 2 did not graduate; 1 stopped for toxicity, and 3 are enrolling (patritumab/trastuzumab, talazoparib/irinotecan, pembrolizumabx8). Local pathologists were centrally trained using the Residual Cancer Burden (RCB) assessment to ensure uniform evaluation and response classification; RCB 0 = pCR. Results: We evaluated the relationship between pCR and event free (EFS) and distant disease free survival (DDFS) in the first 522 pts (median follow-up:2.5 years). 180 pts achieved pCR (36%) while 338 did not (RCB=1-3). There were 82 EFS and 65 DRFS events. Over the entire group (including all arms), pCR was highly associated with 3-year EFS (p&lt;0.001 for both). Pts achieving pCR had a 3% recurrence risk (RR) at 3 years; those with non-pCR had 24% RR over this time period. For distant recurrence, the 3-year RR with pCR was 2%, compared to 20% in pts with non-pCR. As expected, pCR rates varied by breast cancer subtype (HR+/HER2: 18% (35/196), HR+/HER2+: 40% (33/82), HR-/HER2+:68% (34/50), HR-/HER2-:41% (76/188)). The relationship between pCR and EFS was significant and clinically impactful within each subtype.  3-year survival (pCR group)Hazard Ratio OverallOverallHR+/HER2-HER2+TNBCEFS97%0.08 (0.03-0.23)0.14 (0.02-1.04)0 (NA)0.11 (0.03-0.37)DDFS98%0.08 (0.03-0.26)0.17 (0.01-1.23)0 (NA)0.09 (0.02-0.40) Conclusions: The first long-term efficacy results from the I-SPY2 TRIAL demonstrate that achieving pCR is a very strong surrogate endpoint for improved EFS and DDFS in a high-risk population, across all treatment arms, regardless of subtype. I-SPY2 shows substantially lower estimated EFS hazards for patients achieving pCR, compared to the 5 yr EFS hazard ratio for pCR vs not in Cortazar (hazard ratio 0.49), demonstrating important differences between a metaanalysis compared to a platform trial with uniform high-risk eligibility, standardized pathology assessment, and multiple targeted therapies. Our data support the use of pCR as a primary endpoint for accelerated approval of new drugs if EFS is evaluated in the same population. Based on these findings, the I-SPY2 TRIAL will test whether therapy can be deescalated or escalated for individual patients with the goal of achieving pCR for all. Citation Format: Yee D, DeMichele A, Isaacs C, Symmans F, Yau C, Albain KS, Hylton NM, Forero-Torres A, van't Veer LJ, Perlmutter J, Rugo HS, Melisko M, Chen Y-Y, Balassanian R, Krings G, Datnow B, Hasteh F, Tipps A, Weidner N, Zhang H, Tickman R, Thornton S, Ritter J, Amin K, Klein M, Chen B, Keeney G, Ocal T, Feldman M, Klipfel N, Sattar H, Mueller J, Gwin K, Baker G, Kallakury B, Zeck J, Duan X, Ersahin C, Gamez R, Troxell M, Mansoor A, Grasso LeBeau L, Sams S, Wisell J, Wei S, Harada S, Vinh T, Stamatakos MD, Tawfik O, Fan F, Adams A, Rendi M, Minton S, Magliocco A, Sahoo S, Fang Y, Hirst G, Singhrao R, Asare SM, Wallace AM, Chien AJ, Ellis ED, Han HS, Clark AS, Boughey JC, Elias AD, Nanda R, Korde L, Murthy R, Lang J, Northfelt D, Khan Q, Edmiston KK, Viscusi R, Haley B, Kemmer K, Zelnak A, Berry DA, Esserman LJ. Pathological complete response predicts event-free and distant disease-free survival in the I-SPY2 TRIAL [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr GS3-08.