Data sources and applied methods for paclitaxel safety signal discernment.

Background: Following the identification of a late mortality signal, the Food and Drug Administration (FDA) convened an advisory panel that concluded that additional clinical study data are needed to comprehensively evaluate the late mortality signal observed with the use of drug-coated balloons (DCB) and drug-eluting stent (DES). The objective of this review is to (1) identify and summarize the existing clinical and cohort studies assessing paclitaxel-coated DCBs and DESs, (2) describe and determine the quality of the available data sources for the evaluation of these devices, and (3) present methodologies that can be leveraged for proper signal discernment within available data sources. Methods: Studies and data sources were identified through comprehensive searches. original research studies, clinical trials, comparative studies, multicenter studies, and observational cohort studies written in the English language and published from January 2007 to November 2021, with a follow-up longer than 36 months, were included in the review. Data quality of available data sources identified was assessed in three groupings. Moreover, accepted data-driven methodologies that may help circumvent the limitations of the extracted studies and data sources were extracted and described. Results: There were 39 studies and data sources identified. This included 19 randomized clinical trials, nine single-arm studies, eight registries, three administrative claims, and electronic health records. Methodologies focusing on the use of existing premarket clinical data, the incorporation of all contributed patient time, the use of aggregated data, approaches for individual-level data, machine learning and artificial intelligence approaches, Bayesian approaches, and the combination of various datasets were summarized. Conclusion: Despite the multitude of available studies over the course of eleven years following the first clinical trial, the FDA-convened advisory panel found them insufficient for comprehensively assessing the late-mortality signal. High-quality data sources with the capabilities of employing advanced statistical methodologies are needed to detect potential safety signals in a timely manner and allow regulatory bodies to act quickly when a safety signal is detected.

Development of an Integrated Platform Using Multidisciplinary Real-World Data to Facilitate Biomarker Discovery for Medical Products.

Translational multidisciplinary research is important for the Center for Devices and Radiological Health's efforts for utilizing real-world data (RWD) to enhance predictive evaluation of medical device performance in patient subpopulations. As part of our efforts for developing new RWD-based evidentiary approaches, including in silico discovery of device-related risk predictors and biomarkers, this study aims to characterize the sex/race-related trends in hip replacement outcomes and identify corresponding candidate single nucleotide polymorphisms (SNPs). Adverse outcomes were assessed by deriving RWD from a retrospective analysis of hip replacement hospital discharge data from the National Inpatient Sample (NIS). Candidate SNPs were explored using pre-existing data from the Personalized Medicine Research Project (PMRP). High-Performance Integrated Virtual Environment was used for analyzing and visualizing putative associations between SNPs and adverse outcomes. Ingenuity Pathway Analysis (IPA) was used for exploring plausibility of the sex-related candidate SNPs and characterizing gene networks associated with the variants of interest. The NIS-based epidemiologic evidence showed that periprosthetic osteolysis (PO) was most prevalent among white men. The PMRP-based genetic evidence associated the PO-related male predominance with rs7121 (odds ratio = 4.89; 95% confidence interval = 1.41-17.05) and other candidate SNPs. SNP-based IPA analysis of the expected gene expression alterations and corresponding signaling pathways suggested possible role of sex-related metabolic factors in development of PO, which was substantiated by ad hoc epidemiologic analysis identifying the sex-related differences in metabolic comorbidities in men vs. women with hip replacement-related PO. Thus, our in silico study illustrates RWD-based evidentiary approaches that may facilitate cost/time-efficient discovery of biomarkers for informing use of medical products.

In silico approaches for enhancing retrieval analysis as a source for discovery of implant reactivity-related mechanisms and biomarkers.

The ability to characterize implant debris in conjunction with corresponding immune and tissue-destructive responses renders retrieval analysis as an important tool for evaluating orthopedic devices. We applied advanced analytics and in silico approaches to illustrate the retrieval-based potential to elucidate host responses and enable discovery of corresponding biomarkers indicative of in vivo implant performance. Hip retrieval analysis was performed using variables based on immunostaining, polarized microscopy, and fretting-corrosion and oxidation analyses. Statistical analyses were performed in R. Hierarchical/k-means clustering and principal component analysis were used for data analysis and visualization. Correlation Engine (CE) and Ingenuity Pathway Analysis (IPA) were employed for in silico corroboration of putative biomarkers. Higher giant cell and histiocyte scores and positivity for CD68 and CD3 indicating infiltration with macrophages and T-cells, respectively, were detected mainly among older generation hips with higher ultra-high-molecular-weight-polyethylene loads. Our in silico analysis using pre-existing data on wear particle-induced loosening substantiated the role of CD68 in implant-induced innate responses and identified the CD68-related molecular signature that can be indicative of development of aseptic loosening and can be further corroborated for diagnostic/prognostic testing in clinical setting. Thus, this study confirmed the great potential of advanced analytics and in silico approaches for enhancing retrieval analysis applications to discovery of new biomarkers for optimizing implant-related preclinical testing and clinical management. © 2019 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater 108B:263-271, 2020.

Genome-wide association reveals contribution of MRAS to painful temporomandibular disorder in males.

Painful temporomandibular disorders (TMDs) are the leading cause of chronic orofacial pain, but its underlying molecular mechanisms remain obscure. Although many environmental factors have been associated with higher risk of developing painful TMD, family and twin studies support a heritable genetic component as well. We performed a genome-wide association study assuming an additive genetic model of TMD in a discovery cohort of 999 cases and 2031 TMD-free controls from the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) study. Using logistic models adjusted for sex, age, enrollment site, and race, we identified 3 distinct loci that were significant in combined or sex-segregated analyses. A single-nucleotide polymorphism on chromosome 3 (rs13078961) was significantly associated with TMD in males only (odds ratio = 2.9, 95% confidence interval: 2.02-4.27, P = 2.2 × 10). This association was nominally replicated in a meta-analysis of 7 independent orofacial pain cohorts including 160,194 participants (odds ratio = 1.16, 95% confidence interval: 1.0-1.35, P = 2.3 × 10). Functional analysis in human dorsal root ganglia and blood indicated this variant is an expression quantitative trait locus, with the minor allele associated with decreased expression of the nearby muscle RAS oncogene homolog (MRAS) gene (beta = -0.51, P = 2.43 × 10). Male mice, but not female mice, with a null mutation of Mras displayed persistent mechanical allodynia in a model of inflammatory pain. Genetic and behavioral evidence support a novel mechanism by which genetically determined MRAS expression moderates the resiliency to chronic pain. This effect is male-specific and may contribute to the lower rates of painful TMD in men.

An in silico framework for integrating epidemiologic and genetic evidence with health care applications: ventilation-related pneumothorax as a case illustration.

OBJECTIVE: To illustrate an in silico integration of epidemiologic and genetic evidence that is being developed at the Center for Devices and Radiological Health/US Food and Drug Administration as part of regulatory research on postmarket device performance. In addition to using conventional epidemiologic evidence from registries, this innovative approach explores the vast potential of open-access omics databases for identifying genetic evidence pertaining to devices. MATERIAL AND METHODS: A retrospective analysis of Agency for Healthcare Research and Quality (AHRQ)/Healthcare Cost and Utilization Project (HCUPNet) data (2002-2011) was focused on the ventilation-related iatrogenic pneumothorax (Vent-IP) outcome in discharges with mechanical ventilation (MV) and continuous positive airway pressure (CPAP). The derived epidemiologic evidence was analyzed in conjunction with pre-existing genomic data from Gene Expression Omnibus/National Center for Biotechnology Information and other databases. RESULTS: AHRQ/HCUPNet epidemiologic evidence showed that annual occurrence of Vent-IP did not decrease over a decade. While the Vent-IP risk associated with noninvasive CPAP comprised about 0.5%, the Vent-IP risk due to longer-term MV reached 2%. Along with MV posing an independent risk for Vent-IP, female sex and white race were found to be effect modifiers, resulting in the highest Vent-IP risk among mechanically ventilated white females. The Vent-IP risk was also potentiated by comorbidities associated with spontaneous pneumothorax (SP) and fibrosis. Consistent with the epidemiologic evidence, expression profiling in a number of animal models showed that the expression of several collagens and other SP/fibrosis-related genes was modified by ventilation settings. CONCLUSION: Integration of complementary genetic evidence into epidemiologic analysis can lead to a cost- and time-efficient discovery of the risk predictors and markers and thus can facilitate more efficient marker-based evaluation of medical product performance.

Reduced PARP1 as a Serum Biomarker for Graft Rejection in Kidney Transplantation.

A serum proteomics platform enabling expression Profiling in transplantation-associated clinical subsets gives an opportunity to identify non-invasive biomarkers that can accurately predict transplant outcome. In this study, we attempted to identify candidate serum biomarkers that could predict kidney allograft rejection/injury, regardless of its etiological and therapeutic heterogeneity. Using serum samples collected from kidney transplantation patients and healthy controls, we first employed Clontech-500 Ab microarrays to Profile acute rejection (AR) and chronic graft injury (CGI) versus stable graft function (SF) and normal kidneys (NK). Using GenePattern analysis of duplicate arrays on pooled samples, we identified gender-independent biomarkers PARP1, MAPK1, SRP54, DP1, and p57 (FDR ≈ 25%), the concordant downregulation of which represented a detrimental Profile common for both rejection/ injury types (AR-CGI). The reverse phase arrays qualified a 2-fold upregulation of PARP1 with an ROC of 0.87 in individual samples from patients with SF vs. AR-CGI rendering serum PARP1 as a biomarker for early prognosis. Ingenuity Pathways Analysis (IPA) connected PARP1 to some other markers (MAPK1), elucidating their possible interactions and connections to the immune response and graft-versus-host disease signaling. The downregulation of serum PARP1 in the damaged graft tissues, represents a perspective non-invasive marker, predicting the failing kidney graft, regardless of rejection/injury causes or gender. Thus, the successful identification of PARP1 as a bio-marker in limited patient cohorts demonstrates that serum proteomics platform empowered by the GenePattern- and IPA-based Bioinformatics algorithm can guarantee a successful development of the clinically applicable prognostic biomarker panel.

Elevated expression levels of ANXA11, integrins ß3 and α3, and TNF-α contribute to a candidate proteomic signature in urine for kidney allograft rejection.

PURPOSE: Kidney transplantation is the treatment of choice for end stage renal disease, with long-term allograft loss being the major obstacle, and for which potential treatments are based on a histological diagnosis. The problem is that markers for predicting graft rejection are limited in number, are invasive, and are quite non-specific. We have hypothesized that protein biomarkers might be discovered in the urine of patients when acute or chronic rejection might be occurring. EXPERIMENTAL DESIGN: We have established a workflow in which initial screening for candidate biomarkers is first performed using urine samples on large-scale antibody microarrays. This approach generated several dozen candidates. The next step is to qualify some of the strongest signals using the high-throughput Reverse Capture Protein Microarray platform. RESULTS: Four top candidates including ANXA11, Integrin α3, Integrin ß3 and TNF-α, initially identified by the antibody microarray platform, were all qualified using Reverse Capture Protein Microarrays. We also used receiver operating condition (ROC) curves to independently quantify the specificity and sensitivity of these four analytes. CONCLUSIONS AND CLINICAL RELEVANCE: The present data suggest that these novel four analytes in the urine, together or independently, may contribute to a robust and quantitative urine proteomic signature for diagnosing acute or chronic rejection of renal allografts.

Annexin-A7 protects normal prostate cells and induces distinct patterns of RB-associated cytotoxicity in androgen-sensitive and -resistant prostate cancer cells.

The tumor suppressor role of annexin-A7 (ANXA7) was previously demonstrated by cancer susceptibility in Anxa7(+/-)-mice and by ANXA7 loss in human cancers, especially in hormone-resistant prostate tumors. To gain mechanistic insights into ANXA7 tumor suppression, we undertook an in vitro study in which we compared wild-type (WT)-ANXA7 and dominant-negative (DN)-ANXA7 effects to a conventional tumor suppressor p53 in prostate cancer cells with different androgen sensitivity. Unlike p53 (which caused cell growth arrest and apoptosis to a noticeable extent in benign PrEC), WT-ANXA7 demonstrated profound cytotoxicityin androgen-sensitive LNCaP as well as in the androgen-resistant DU145 and PC3 prostate cancer cells, but not in PrEC. In androgen-sensitive LNCaP, WT-ANXA7 decreased low-molecular-weight (LMW) AR protein forms and maintained higher retinoblastoma 1 (RB1)/phospho-RB1 ratio. In contrast, DN-ANXA7 (which lacks phosphatidylserine liposome aggregation properties) increased LMW-AR forms and hyperphosphorylated RB1 that was consistent with the lack of DN-ANXA7 cytotoxicity. According to the microarray-based Ingenuity Pathways Analysis, a major WT-ANXA7 effect in androgen-sensitive LNCaP constituted of upregulation of the RB1-binding transcription factor E2F1 along with its downstream proapoptotic targets such as ASK1 and ASPP2. These results suggested a reversal of the RBdependent repression of the proapoptotic E2F-mediated transcription. However, DN-ANXA7 increased RB1/2 (but not E2F1) expression and induced the proliferation-promoting ERK5, thereby maintaining the RB-dependent repression of E2F-mediated apoptosis in LNcaP. On the other hand, in androgen-resistant cells, WT-ANXA7 tumor suppressor effects involved PTEN and NFkB pathways. Thus, ANXA7 revived the RB-associated cell survival control and overcame androgen resistance and dysfunctional status of major tumor suppressors commonly mutated in prostate cancer. Published 2009 UICC.

ANXA7 expression represents hormone-relevant tumor suppression in different cancers.

Tumor suppressor function of ubiquitously expressed Annexin-A7, ANXA7 (10q21) that is involved in exocytosis and membrane fusion was based on cancer prone phenotype in Anxa7(+/-) mice as well as ANXA7 role in human prostate and breast cancers. To clarify ANXA7 biomarker and tumor suppressor function, we analyzed its expression pattern in comparison to the prostate-specific biomarker NKX3.1. Immunohistochemistry-based ANXA7 and NKX3.1 protein expression was analyzed on human tissue microarrays of 4,061 specimens from a wide spectrum of the histopathologically well-characterized tumors in different stages compared to corresponding normal tissues. Decreased ANXA7 expression was mostly associated with high invasive potential in multiple tumors. Although some metastases retained relatively high ANXA7 rates compared to primary cancer tissues, the lymph node metastases from different sites (including prostate and breast) had decreased ANXA7 expression in comparison to the intact lymphatic tissues. Major ANXA7 downregulation pattern was deviated in tumors of glandular (especially neuroendocrine) origin. ANXA7 and NKX3.1 proteins were synexpressed in the male urogenital system and adrenal gland. Gene expression profiling in prostate and breast cancers (SMD) revealed distinct hormone-related profiles for NKX3.1 and ANXA7, where ANXA7 expression correlated with steroid sulfatase which has a pivotal role in steroidogenesis. Abundant protein presence in adrenal gland and its loss in hormone-refractory prostate cancer indicated that ANXA7 can be relevant to steroidogenesis and androgen sensitivity in particular. With tumor suppressor pattern validated in different tumors, ANXA7 can be an attractive diagnostic and therapeutic target associated with the hormone and/or neurotransmitter-mediated modulation of tumorigenesis.

Distinct effects of annexin A7 and p53 on arachidonate lipoxygenation in prostate cancer cells involve 5-lipoxygenase transcription.

Tumor suppressor function for Annexin A7 (ANXA7; 10q21) is based on cancer-prone phenotype in Anxa7(+/-) mouse and ANXA7 prognostic role in human cancers. Because ANXA7-caused liposome aggregation can be promoted by arachidonic acid (AA), we hypothesized that the phospholipid-binding tumor suppressor ANXA7 is associated with AA cascade. In a comparative study of ANXA7 versus canonical tumor suppressor p53 effects on AA lipoxygenation pathway in the p53-mutant and androgen-insensitive DU145 prostate cancer cells, both tumor suppressors altered gene expression of major 5-lipoxygenase (LOX) and 15-LOXs, including response to T helper 2 (Th2)-cytokine [interleukin-4 (IL-4)] and endogenous steroids (mimicked by dexamethasone). Wild-type and mutant ANXA7 distinctly affected expression of the dexamethasone-induced 15-LOX-2 (a prostate-specific endogenous tumor suppressor) as well as the IL-4-induced 15-LOX-1. On the other hand, wild-type p53 restored 5-LOX expression in DU145 to levels comparable to benign prostate epithelial cells. Using mass spectrometry of DNA affinity-enriched nuclear proteins, we detected different proteins that were bound to adjacent p53 and estrogen response elements in the 5-LOX promoter in DU145 cells introduced with ANXA7 versus p53. Sex hormone regulator 17-beta hydroxysteroid dehydrogenase 4 was identified under p53 introduction, which induced the 5-LOX expression. Meantime, nuclear proteins bound to the same 5-LOX promoter site under introduction of ANXA7 (that was associated with the repressed 5-LOX) were identified as zinc finger proteins ZNF433 and Aiolos, pyrin domain-containing NALP10, and the p53-regulating DNA repair enzyme APEX1. Thus, ANXA7 and p53 can distinctly regulate LOX transcription that is potentially relevant to the AA-mediated cell growth control in tumor suppression.