Ciaran Mannion

Clinical decision support systems for improving diagnostic accuracy and achieving precision medicine.

As research laboratories and clinics collaborate to achieve precision medicine, both communities are required to understand mandated electronic health/medical record (EHR/EMR) initiatives that will be fully implemented in all clinics in the United States by 2015. Stakeholders will need to evaluate current record keeping practices and optimize and standardize methodologies to capture nearly all information in digital format. Collaborative efforts from academic and industry sectors are crucial to achieving higher efficacy in patient care while minimizing costs. Currently existing digitized data and information are present in multiple formats and are largely unstructured. In the absence of a universally accepted management system, departments and institutions continue to generate silos of information. As a result, invaluable and newly discovered knowledge is difficult to access. To accelerate biomedical research and reduce healthcare costs, clinical and bioinformatics systems must employ common data elements to create structured annotation forms enabling laboratories and clinics to capture sharable data in real time. Conversion of these datasets to knowable information should be a routine institutionalized process. New scientific knowledge and clinical discoveries can be shared via integrated knowledge environments defined by flexible data models and extensive use of standards, ontologies, vocabularies, and thesauri. In the clinical setting, aggregated knowledge must be displayed in user-friendly formats so that physicians, non-technical laboratory personnel, nurses, data/research coordinators, and end-users can enter data, access information, and understand the output. The effort to connect astronomical numbers of data points, including ‘-omics’-based molecular data, individual genome sequences, experimental data, patient clinical phenotypes, and follow-up data is a monumental task. Roadblocks to this vision of integration and interoperability include ethical, legal, and logistical concerns. Ensuring data security and protection of patient rights while simultaneously facilitating standardization is paramount to maintaining public support. The capabilities of supercomputing need to be applied strategically. A standardized, methodological implementation must be applied to developed artificial intelligence systems with the ability to integrate data and information into clinically relevant knowledge. Ultimately, the integration of bioinformatics and clinical data in a clinical decision support system promises precision medicine and cost effective and personalized patient care.

Maternal and Fetal Outcomes in Placenta Accreta After Institution of Team-Managed Care:

Introduction: Placenta accreta significantly contributes to maternal morbidity and mortality. We evaluated whether planned delivery and experienced, team-managed surgical intervention results in improved outcomes. We also examined whether risk factors differed for accreta, increta, and percreta and evaluated whether excess lower segment uterine vascularity correlates with disease severity. Methods: We retrospectively analyzed patients before versus after institution of a management protocol. Of the 58 044 deliveries over 10 years, there were 67 women whose pregnancies were histopathologically confirmed as placenta accreta, increta, or percreta (1/866). Clinical outcome measures were estimated blood loss (EBL), packed red blood cells (pRBCs) transfused, maternal and fetal complications, intensive care unit admission, and length of stay. Results: There were no maternal or infant deaths. In the managed cohort, EBL was reduced by 48% (P < .001), intraoperative pRBCs transfused by 40% (P < .01), total transfused pRBCs per case by 50% (P < .01), and surgical intensive care unit admissions by >50% (P < .01). Assessment of maternal risk factors by diagnosis revealed marked differences between accreta versus increta and percreta. Clinically assessed excess vascularity of the lower uterine segment correlated with disease severity. The incidence of neonatal complications was similar in both cohorts. Conclusions: Targeted delivery at 34 weeks and team-managed diagnosis, treatment, and care of patients with placenta accreta were associated with improved maternal, but not neonatal outcomes.

Endometrial Cancer Incidence in Breast Cancer Patients Correlating with Age and Duration of Tamoxifen Use: a Population Based Study

Background: Our study aimed to assess the endometrial cancer risk after tamoxifen adjuvant treatment for female breast cancer patients in Taiwan. Materials and Methods: A total of 74,280 breast cancer patients between January 1997 and December 2004 were included in the study; 39,411 received tamoxifen treatment and 34,869 did not. Tamoxifen-associated endometrial cancer was defined as endometrial cancer that occurred in patients at least 6-month after the diagnosis of breast cancer, who underwent tamoxifen treatment. Results: A total of 222 patients developed endometrial cancer, and of these,153 (69 %) were seen in patients with tamoxifen treatment, and 69 (31%) were seen in patients without the use of tamoxifen. The incidence of endometrial cancer was 0.388% (153/39,411) in patients with tamoxifen treatment, while was 0.198% (69/34,869) in patients without tamoxifen treatment. Logistic regression analysis demonstrated that tamoxifen use and age over 35 years were significantly correlated with development of endometrial cancer (p<0.001 and p=0.002, respectively). The odds ratio was 2.94 (95%CI, 2.13-4.06) for 3 years or longer tamoxifen use. The odds ratio was 4.08 (95%CI, 1.67-9.93) for women older than 35 years compared to those 35 or younger than 35 years. There were no significant differences in prior hormone exposure, hypertension and diabetes. Conclusions: To the best of our knowledge, this is the largest population based study that shows in patients with breast cancer, tamoxifen use for more than three years or patients older than 35 years was associated with a significantly increased risk for developing endometrial cancer.

Osteomyelitis of the Patella Caused by Legionella anisa

ABSTRACT A 51-year-old man with a history of stage IV angioimmunoblastic T-cell lymphoma was diagnosed with osteomyelitis of the patella. Legionella anisa was identified by 16S rRNA gene sequencing and culture. The patient had pneumonia 2 months prior to this osteomyelitis episode. L. anisa was retrospectively detected in his lung tissue by 16S rRNA gene sequencing and was considered the source of the L. anisa that caused his patella osteomyelitis.

Ex vivo replication of phenotypic functions of osteocytes through biomimetic 3D bone tissue construction

Osteocytes, residing as 3-dimensionally (3D) networked cells in bone, are well known to regulate bone and mineral homeostasis and have been recently implicated to interact with cancer cells to influence the progression of bone metastases. In this study, a bone tissue consisting of 3D-networked primary human osteocytes and MLO-A5 cells was constructed using: (1) the biomimetic close-packed assembly of 20-25μm microbeads with primary cells isolated from human bone samples and MLO-A5 cells and (2) subsequent perfusion culture in a microfluidic device. With this 3D tissue construction approach, we replicated ex vivo, for the first time, the mechanotransduction function of human primary osteocytes and MLO-A5 cells by correlating the effects of cyclic compression on down-regulated SOST and DKK1 expressions. Also, as an example of using our ex vivo model to evaluate therapeutic agents, we confirmed previously reported findings that parathyroid hormone (PTH) decreases SOST and increases the ratio of RANKL and OPG. In comparison to other in vitro models, our ex vivo model: (1) replicates the cell density, phenotype, and functions of primary human osteocytes and MLO-A5 cells and (2) thus provides a clinically relevant means of studying bone diseases and metastases.

Tumor-to-tumor metastasis: report of two cases of renal cell carcinoma metastasizing to microcystic serous cystadenoma of the pancreas.

Metastatic cancer to the pancreas accounts for less than 2% of all pancreatic malignancies. In contrast to other metastatic tumors, renal cell carcinoma (RCC) has a propensity to metastasize as a solitary pancreatic lesion. While symptomatic patients may present with obstructive jaundice, abdominal pain, or gastrointestinal bleeding, the diagnosis of metastatic pancreatic involvement is often made in asymptomatic patients, during follow-up evaluation in the aftermath of an initial diagnosis of renal cell carcinoma. Microcystic serous cystadenoma of the pancreas is an uncommon pancreatic exocrine neoplasm that morphologically resembles conventional (clear cell) RCC, in so far as both tumors are characterized by neoplastic cells with clear cytoplasm, relatively uniform nuclei and scant associated tumor stroma. Herein, we report 2 immunohistochemically confirmed cases of unsuspected metastatic RCC to the pancreas, with the metastatic tumor in each case confined to a preexisting microcystic serous cystadenoma of the pancreas.

Ex vivo construction of human primary 3D–networked osteocytes

A human bone tissue model was developed by constructing ex vivo the 3D network of osteocytes via the biomimetic assembly of primary human osteoblastic cells with 20-25μm microbeads and subsequent microfluidic perfusion culture. The biomimetic assembly: (1) enabled 3D-constructed cells to form cellular network via processes with an average cell-to-cell distance of 20-25μm, and (2) inhibited cell proliferation within the interstitial confine between the microbeads while the confined cells produced extracellular matrix (ECM) to form a mechanically integrated structure. The mature osteocytic expressions of SOST and FGF23 genes became significantly higher, especially for SOST by 250 folds during 3D culture. The results validate that the bone tissue model: (1) consists of 3D cellular network of primary human osteocytes, (2) mitigates the osteoblastic differentiation and proliferation of primary osteoblast-like cells encountered in 2D culture, and (3) therefore reproduces ex vivo the phenotype of human 3D-networked osteocytes. The 3D tissue construction approach is expected to provide a clinically relevant and high-throughput means for evaluating drugs and treatments that target bone diseases with in vitro convenience.

Prolactin Induced Protein (PIP) is a potential biomarker for early stage and malignant breast cancer

OBJECTIVES Breast cancer (BC) is the second leading cause of cancer-related mortality in women. Bioinformatic analysis and expression screening showed that Prolactin Induced Protein (PIP) was differentially expressed in BC. The objective of this investigation was to characterize the expression pattern of PIP, an aspartyl proteinase, in malignant and non-malignant breast tissues. MATERIALS AND METHODS Real time quantitative PCR was employed to analyze PIP and androgen receptor (AR) mRNA levels in BC cell lines and 190 normal tissues and tumor samples. The tumor specimens were categorized based on TNM classification, anatomic stage, histologic grade and molecular subtype and expression pattern evaluated. To detect protein levels, immunohistochemistry followed by semi quantitative scoring was employed in the examination of 517 normal, benign, and invasive BC tissues. RESULTS We observed substantial downregulation of PIP transcription in cancer samples compared to normal breast tissue. mRNA levels were significantly downregulated (93 fold, P < 0.005) in advanced grades compared to lower grades. Transcript levels were also significantly lower (22 fold, P < 0.05) in triple negative tumors compared to hormone receptor positive tumors. Significant downregulation was observed in early stage samples of triple negative and hormone receptor positive tumors. Though PIP protein showed a wide range of expression levels in BC, early stage samples showed significant downregulation. CONCLUSIONS PIP mRNA is significantly downregulated in early stage BC compared to normal breast tissue. Consequently, low PIP mRNA expression in BC tissues could potentially be used as a tissue based biomarker to assist pathologists in confirmation of early stage BC diagnosis.

STAG2 Is a Biomarker for Prediction of Recurrence and Progression in Papillary Non–Muscle-Invasive Bladder Cancer

Purpose: Most bladder cancers are early-stage tumors known as papillary non–muscle-invasive bladder cancer (NMIBC). After resection, up to 70% of NMIBCs recur locally, and up to 20% of these recurrences progress to muscle invasion. There is an unmet need for additional biomarkers for stratifying tumors based on their risk of recurrence and progression. We previously identified STAG2 as among the most commonly mutated genes in NMIBC and provided initial evidence in a pilot cohort that STAG2-mutant tumors recurred less frequently than STAG2 wild-type tumors. Here, we report a STAG2 biomarker validation study using two independent cohorts of clinically annotated papillary NMIBC tumors from the United States and Europe. Experimental Design: The value of STAG2 immunostaining for prediction of recurrence was initially evaluated in a cohort of 82 patients with papillary NMIBC (“Georgetown cohort”). Next, the value of STAG2 immunostaining for prediction of progression to muscle invasion was evaluated in a progressor-enriched cohort of 253 patients with papillary NMIBC (“Aarhus cohort”). Results: In the Georgetown cohort, 52% of NMIBC tumors with intact STAG2 expression recurred, whereas 25% of STAG2-deficient tumors recurred (P = 0.02). Multivariable analysis identified intact STAG2 expression as an independent predictor of recurrence (HR = 2.4; P = 0.05). In the progressor-enriched Aarhus cohort, 38% of tumors with intact STAG2 expression progressed within 5 years, versus 16% of STAG2-deficient tumors (P < 0.01). Multivariable analysis identified intact STAG2 expression as an independent predictor of progression (HR = 1.86; P = 0.05). Conclusions: STAG2 IHC is a simple, binary, new assay for risk stratification in papillary NMIBC. Clin Cancer Res; 24(17); 4145–53. ©2018 AACR.

Human trophoblast epithelial-mesenchymal transition in abnormally invasive placenta

Abstract Differentiation of first trimester human placental cytotrophoblast (CTB) from an anchoragedependent epithelial phenotype into the mesenchymal-like invasive extravillous trophoblast (EVT) is crucial in the development of the maternal–fetal interface. We showed previously that differentiation of first trimester CTB to EVT involves an epithelial-mesenchymal transition (EMT). Here we compare the epithelial-mesenchymal characteristics of CTB and EVT derived from normal third trimester placenta or placenta previa versus abnormally invasive placenta (AIP). CTB and EVT were isolated from normal term placenta or placenta previa following Caesarean section and EVT from AIP following Caesarean hysterectomy. Cell identity was validated by measurement of cytokeratin-7 and HLA-G. Comparing normal term CTB with EVT from normal term placenta or placenta previa for differential expression analysis of genes associated with the EMT showed changes in >70% of the genes probed. While demonstrating a mesenchymal phenotype relative to CTB, many of the gene expression changes in third trimester EVT were reduced relative to the first trimester EVT. We suggest that third trimester EVT are in a more constrained, metastable state compared to first trimester equivalents. By contrast, EVT from AIP demonstrate characteristics that are more mesenchymal than normal third trimester EVT, placing them closer to first trimester EVT on the EMT spectrum, consistent with a more invasive phenotype. Summary Sentence Extravillous trophoblast cells from abnormally invasive placenta demonstrate more mesenchymal characteristics than normal third trimester cells, consistent with an overinvasive phenotype.