SARIFA as a new histopathological biomarker is associated with adverse clinicopathological characteristics, tumor-promoting fatty-acid metabolism, and might predict a metastatic pattern in pT3a prostate cancer.

BACKGROUND: Recently, we introduced Stroma-AReactive-Invasion-Front-Areas (SARIFA) as a novel hematoxylin-eosin (H&E)-based histopathologic prognostic biomarker for various gastrointestinal cancers, closely related to lipid metabolism. To date, no studies on SARIFA, which is defined as direct tumor-adipocyte-interaction, beyond the alimentary tract exist. Hence, the objective of our current investigation was to study the significance of SARIFA in pT3a prostate cancer (PCa) and explore its association with lipid metabolism in PCa as lipid metabolism plays a key role in PCa development and progression. METHODS: To this end, we evaluated SARIFA-status in 301 radical prostatectomy specimens and examined the relationship between SARIFA-status, clinicopathological characteristics, overall survival, and immunohistochemical expression of FABP4 and CD36 (proteins closely involved in fatty-acid metabolism). Additionally, we investigated the correlation between SARIFA and biochemical recurrence-free survival (BRFS) and PSMA-positive recurrences in PET/CT imaging in a patient subgroup. Moreover, a quantitative SARIFA cut-off was established to further understand the underlying tumor biology. RESULTS: SARIFA positivity occurred in 59.1% (n = 178) of pT3a PCas. Our analysis demonstrated that SARIFA positivity is strongly associated with established high-risk features, such as R1 status, extraprostatic extension, and higher initial PSA values. Additionally, we observed an upregulation of immunohistochemical CD36 expression specifically at SARIFAs (p = 0.00014). Kaplan-Meier analyses revealed a trend toward poorer outcomes, particularly in terms of BRFS (p = 0.1). More extensive tumor-adipocyte interaction, assessed as quantity-dependent SARIFA-status on H&E slides, is also significantly associated with high-risk features, such as lymph node metastasis, and seems to be associated with worse survival outcomes (p = 0.16). Moreover, SARIFA positivity appeared to be linked to more distant lymph node and bone metastasis, although statistical significance was slightly not achieved (both p > 0.05). CONCLUSIONS: This is the first study to introduce SARIFA as easy-and-fast-to-assess H&E-based biomarker in locally advanced PCa. SARIFA as the histopathologic correlate of a distinct tumor biology, closely related to lipid metabolism, could pave the way to a more detailed patient stratification and to the development of novel drugs targeting lipid metabolism in pT3a PCa. On the basis of this biomarker discovery study, further research efforts on the prognostic and predictive role of SARIFA in PCa can be designed.

Biomarkers and immunological parameters in haemophilia and rheumatoid arthritis patients: a comparative multiplexing laboratory study.

INTRODUCTION: Haemophilia (HA) and rheumatoid arthritis (RA) patients may develop joint damage caused by recurrent joint bleedings in HA or by chronic inflammation in RA. Only few data exist for biomarker studies in these patients. AIM: The objective of the present study is to assess a large array of biomarkers in peripheral blood samples obtained from HA patients without or with arthropathy and to compare pattern to RA patients and healthy controls. METHODS: A panel of biomarkers was assessed in 129 men (40 HA patients without arthropathy, 23 HA patients with arthropathy, 23 RA patients and 43 control subjects). 37 different biomarkers (cytokines, angiogenesis-related proteins) were analysed using a multiple analyte profiling technology and supplemented by acute phase proteins, coagulation and immunological parameters. RESULTS: Evidence for systemic inflammation was obtained by increased acute phase reactants in all patient groups. 13 or 14 from 42 soluble parameters demonstrated significant differences (p < .05) between HA patients without arthropathy and healthy controls, or between HA patients with arthropathy and healthy controls, respectively. Largely overlapping patterns were obtained except for interleukin-7 being increased in HA patients without arthropathy and being decreased in HA in the presence of arthropathy. CONCLUSIONS: In addition to data supporting systemic inflammation, we provide evidence for a common biomarker profile in HA patients and RA patients compared to healthy controls. A distinctive biomarker profile for HA patients with arthropathy did not appear except for interleukin-7 demonstrating specific changes depending on the absence or presence of arthropathy in HA patients.

Group testing can improve the cost-efficiency of prospective-retrospective biomarker studies.

BACKGROUND: Cancer treatment is increasingly dependent on biomarkers for prognostication and treatment selection. Potential biomarkers are frequently evaluated in prospective-retrospective studies in which biomarkers are measured retrospectively on archived specimens after completion of prospective clinical trials. In light of the high costs of some assays, random sampling designs have been proposed that measure biomarkers for a random sub-sample of subjects selected on the basis of observed outcome and possibly other variables. Compared with a standard design that measures biomarkers on all subjects, a random sampling design can be cost-efficient in the sense of reducing the cost of the study substantially while achieving a reasonable level of precision. METHODS: For a biomarker that indicates the presence of some molecular alteration (e.g., mutation in a gene), we explore the use of a group testing strategy, which involves physically pooling specimens across subjects and assaying pooled samples for the presence of the molecular alteration of interest, for further improvement in cost-efficiency beyond random sampling. We propose simple and general approaches to estimating the prognostic and predictive values of biomarkers with group testing, and conduct simulation studies to validate the proposed estimation procedures and to assess the cost-efficiency of the group testing design in comparison to the standard and random sampling designs. RESULTS: Simulation results show that the proposed estimation procedures perform well in realistic settings and that a group testing design can have considerably higher cost-efficiency than a random sampling design. CONCLUSIONS: Group testing can be used to improve the cost-efficiency of biomarker studies.

Biomarker time out.

The advancement of knowledge relies on scientific investigations. The timing between asking a question and data collection defines if a study is prospective or retrospective. Prospective studies look forward from a point in time, are less prone to bias and are considered superior to retrospective studies. This conceptual framework conflicts with the nature of biomarker research. New candidate biomarkers are discovered in a retrospective manner. There are neither resources nor time for prospective testing in all cases. Relevant sources for bias are not covered. Ethical questions arise through the time penalty of an overly dogmatic concept. The timing of sample collection can be separated from testing biomarkers. Therefore the moment of formulating a hypothesis may be after sample collection was completed. A conceptual framework permissive to asking research questions without the obligation to bow to the human concept of calendar time would simplify biomarker research, but will require new safeguards against bias.

Trifluridine/Tipiracil Based Chemoradiation in locally Advanced Rectal Cancer: The Phase I/II TARC Trial.

BACKGROUND: Optimizing functional outcomes and securing long-term remissions are key goals in managing patients with locally advanced rectal cancer. In this proof-of-concept study, we set out to further optimize neoadjuvant therapy by integrating the radiosensitizer trifluridine/tipiracil and explore the potential of cell free tumor DNA (ctDNA) to monitor residual disease. METHODS: About 10 patients were enrolled in the phase I dose finding part which followed a 3 + 3 dose escalation design. Tipiracil/trifluridine was administered concomitantly to radiotherapy. ctDNA monitoring was performed before and after chemoradiation with patient-individualized digital droplet PCRs. RESULTS: No dose-limiting toxicities were observed at the maximum tolerated dose level of 2 × 35 mg/m² trifluridine/tipiracil. There were 9 grade 3 adverse events, of which 8 were hematologic with anemia and leukopenia. Chemoradiation yielded a pathological complete response in 1 out of 8 assessable patients, downstaging in nearly all patients, and 1 clinical complete response referred for watchful waiting. Three of 4 assessable patients with residual tumor cells at pathological assessment remained liquid biopsy positive after chemoradiation, but 1 turned negative. CONCLUSION: In this exploratory phase I trial, the novel combination of neoadjuvant trifluridine/tipiracil and radiotherapy proved to be feasible, tolerable, and effective. However, the application of liquid biopsy as a potential marker for therapeutic de-escalation in the neoadjuvant setting requires additional research and prospective validation. The trial was registered at ClinicalTrials.gov: NCT04177602.

Molecular skin fluorescence imaging: A tool for evaluating early melanoma development.

A novel approach to melanoma diagnosis-in vivo molecular skin fluorescence imaging (mSFI)-was developed to identify premalignant changes in the form of tissue remodeling related to melanoma development in humans by imaging the proximal microenvironment of lesions. The method was tested using a fluorescent peptide (ORL-1) which binds to αvß3 integrin, a molecule associated with invasive melanoma development. A cut off score of 7 was established, differentiating melanomas from nonmelanoma nevi with 100% sensitivity, and 95.7% specificity, while identifying dysplastic nevi with the potential for melanoma development.

Testing Overall and Subpopulation Treatment Effects with Measurement Errors.

There is a growing interest in the discovery of important predictors from many potential biomarkers for therapeutic use. In particular, a biomarker has predictive value for treatment if the treatment is only effective for patients whose biomarker values exceed a certain threshold. However, biomarker expressions are often subject to measurement errors, which may blur the biomarker's predictive capability in patient classification and, as a consequence, may lead to inappropriate treatment decisions. By taking into account the measurement errors, we propose a new testing procedure for the overall and subpopulation treatment effects in the multiple testing framework. The proposed method bypasses the permutation or other resampling procedures that become computationally infeasible in the presence of measurement errors. We conduct simulation studies to examine the performance of the proposed method, and illustrate it with a data example.

Ensuring sample quality for blood biomarker studies in clinical trials: a multicenter international study for plasma and serum sample preparation.

BACKGROUND: Sample quality is critical for biomarker detection in oncology, and platelet degradation and contamination in plasma have a remarkable impact on the ability to accurately quantify many blood-based biomarkers. Platelet factor 4 (PF4) can be used as an indicator to monitor sample quality. This multicenter study aimed to determine the impact of critical components of the blood sample handling process on platelet degradation/contamination and to establish an optimal method for collecting platelet-poor plasma samples. METHODS: At each of six participating centers, blood samples were drawn from 12-13 healthy volunteers. Serum and plasma samples were prepared from whole blood samples using nine different methods that have been commonly used in ongoing multicenter trials. PF4 levels in the prepared samples were measured by enzyme-linked immunosorbent assay (ELISA). Paired t-tests were used for statistical analysis. RESULTS: Blood samples were collected from 74 subjects enrolled in six centers. PF4 levels were significantly higher in serum samples than in plasma samples (P<0.001), in plasma samples from blood that sat at room temperature for 5 minutes (P=0.021), in plasma samples prepared at an insufficient centrifugal force (P<0.001), and in plasma samples prepared from blood that sat for longer than 4 hours on ice (P=0.001). For each method, the PF4 levels did not differ significantly among the centers or between Chinese and American subjects. The methods that resulted in normal levels of PF4 involved keeping blood samples on ice for 30 minutes to <4 hours and centrifugation at 2,500-3,000 ×g for 30 min. CONCLUSIONS: This multicenter study evaluated multiple blood sample handling conditions for minimizing platelet degradation during plasma serum preparation and determined an optimal method for preparing platelet-poor plasma. The findings of this study can be applied in future blood biomarker studies.

Searching for non-genetic molecular and imaging PTSD risk and resilience markers: Systematic review of literature and design of the German Armed Forces PTSD biomarker study.

Biomarkers allowing the identification of individuals with an above average vulnerability or resilience for posttraumatic stress disorder (PTSD) would especially serve populations at high risk for trauma exposure like firefighters, police officers and combat soldiers. Aiming to identify the most promising putative PTSD vulnerability markers, we conducted the first systematic review on potential imaging and non-genetic molecular markers for PTSD risk and resilience. Following the PRISMA guidelines, we systematically screened the PubMed database for prospective longitudinal clinical studies and twin studies reporting on pre-trauma and post-trauma PTSD risk and resilience biomarkers. Using 25 different combinations of search terms, we retrieved 8151 articles of which we finally included and evaluated 9 imaging and 27 molecular studies. In addition, we briefly illustrate the design of the ongoing prospective German Armed Forces (Bundeswehr) PTSD biomarker study (Bw-BioPTSD) which not only aims to validate these previous findings but also to identify novel and clinically applicable molecular, psychological and imaging risk, resilience and disease markers for deployment-related psychopathology in a cohort of German soldiers who served in Afghanistan.

Detection of neurofilament-H in serum as a diagnostic tool to predict injury severity in patients who have suffered mild traumatic brain injury.

OBJECT: In previous studies of traumatic brain injury (TBI), neural biomarkers of injury correlate with injury severity and predict neurological outcome. The object of this paper was to characterize neurofilament-H (NFL-H) as a predictor of injury severity in patients who have suffered mild TBI (mTBI). Thus, the authors hypothesized that phosphorylated NFL-H (pNFL-H) levels are higher in mTBI patients than in healthy controls and identify which subjects experienced a more severe injury such as skull fractures, intracranial hemorrhaging, and/or contusions as detected by CT scans. METHODS: In this prospective clinical study, blood (8 ml) was collected from subjects (n = 34) suffering from mTBI (as defined by the American Congress of Rehabilitation and Glasgow Coma Scale scores between 13 and 15) at Parkland Hospital, Dallas, Texas, on Days 1 and 3 after injury). Additional clinical findings from the CT scans were also used to categorize the TBI patients into those with and those without clinical findings on the scans (CT+ and CTgroups, respectively). The serum levels of pNFL-H were measured using the enzyme-linked immunosorbent assay. RESULTS: Compared with healthy controls, the mTBI patients exhibited a significant increase in the serum levels of pNFL-H on Days 1 (p = 0.00001) and 3 (p = 0.0001) after TBI. An inverse correlation was observed between pNFL-H serum levels and Glasgow Coma Scale scores, which was significant. Additionally, using receiver operating characteristic curve analysis to compare the mTBI cases with controls to determine sensitivity and specificity, an area under the curve of 100% was achieved for both (p = 0.0001 for both). pNFL-H serum levels were only significantly higher on Day 1 in mTBI patients in the CT+ group (p < 0.008) compared with the CT- group. The area under the curve (82.5%) for the CT+ group versus the CT- group was significant (p = 0.021) with a sensitivity of 87.5% and a specificity of 70%, using a cutoff of 1071 pg/ml of pNFL-H in serum. CONCLUSIONS: This study describes the serum profile of pNFL-H in patients suffering from mTBI with and without CT findings on Days 1 and 3 after injury. These results suggest that detection of pNFL-H may be useful in determining which individuals require CT imaging to assess the severity of their injury.

Resampling Procedures for Making Inference under Nested Case-control Studies.

The nested case-control (NCC) design have been widely adopted as a cost-effective solution in many large cohort studies for risk assessment with expensive markers, such as the emerging biologic and genetic markers. To analyze data from NCC studies, conditional logistic regression (Goldstein and Langholz, 1992; Borgan et al., 1995) and maximum likelihood (Scheike and Juul, 2004; Zeng et al., 2006) based methods have been proposed. However, most of these methods either cannot be easily extended beyond the Cox model (Cox, 1972) or require additional modeling assumptions. More generally applicable approaches based on inverse probability weighting (IPW) have been proposed as useful alternatives (Samuelsen, 1997; Chen, 2001; Samuelsen et al., 2007). However, due to the complex correlation structure induced by repeated finite risk set sampling, interval estimation for such IPW estimators remain challenging especially when the estimation involves non-smooth objective functions or when making simultaneous inferences about functions. Standard resampling procedures such as the bootstrap cannot accommodate the correlation and thus are not directly applicable. In this paper, we propose a resampling procedure that can provide valid estimates for the distribution of a broad class of IPW estimators. Simulation results suggest that the proposed procedures perform well in settings when analytical variance estimator is infeasible to derive or gives less optimal performance. The new procedures are illustrated with data from the Framingham Offspring Study to characterize individual level cardiovascular risks over time based on the Framingham risk score, C-reactive protein (CRP) and a genetic risk score.