Cell-free human papillomavirus DNA kinetics after surgery for human papillomavirus-associated oropharyngeal cancer.

BACKGROUND: New ultrasensitive methods for detecting residual disease after surgery are needed in human papillomavirus-associated oropharyngeal squamous cell carcinoma (HPV+OPSCC). METHODS: To determine whether the clearance kinetics of circulating tumor human papillomavirus DNA (ctHPVDNA) is associated with postoperative disease status, a prospective observational study was conducted in 33 patients with HPV+OPSCC undergoing surgery. Blood was collected before surgery, postoperative days 1 (POD 1), 7, and 30 and with follow-up. A subcohort of 12 patients underwent frequent blood collections in the first 24 hours after surgery to define early clearance kinetics. Plasma was run on custom droplet digital polymerase chain reaction (ddPCR) assays for HPV genotypes 16, 18, 33, 35, and 45. RESULTS: In patients without pathologic risk factors for recurrence who were observed after surgery, ctHPVDNA rapidly decreased to <1 copy/mL by POD 1 (n = 8/8). In patients with risk factors for macroscopic residual disease, ctHPVDNA was markedly elevated on POD 1 (>350 copies/mL) and remained elevated until adjuvant treatment (n = 3/3). Patients with intermediate POD 1 ctHPVDNA levels (1.2-58.4 copies/mL) all possessed pathologic risk factors for microscopic residual disease (n = 9/9). POD 1 ctHPVDNA levels were higher in patients with known adverse pathologic risk factors such as extranodal extension >1 mm (P = .0481) and with increasing lymph nodes involved (P = .0453) and were further associated with adjuvant treatment received (P = .0076). One of 33 patients had a recurrence that was detected by ctHPVDNA 2 months earlier than clinical detection. CONCLUSIONS: POD 1 ctHPVDNA levels are associated with the risk of residual disease in patients with HPV+OPSCC undergoing curative intent surgery and thus could be used as a personalized biomarker for selecting adjuvant treatment in the future. LAY SUMMARY: Human papillomavirus-associated oropharyngeal squamous cell carcinoma (HPV+OPSCC) is increasing at epidemic proportions and is commonly treated with surgery. This report describes results from a study examining the clearance kinetics of circulating tumor HPV DNA (circulating tumor human papillomavirus DNA [ctHPVDNA]) following surgical treatment of HPV+OPSCC. We found that ctHPVDNA levels 1 day after surgery are associated with the risk of residual disease in patients with HPV+OPSCC and thus could be used as a personalized biomarker for selecting adjuvant treatment in the future. These findings are the first to demonstrate the potential utility of ctHPVDNA in patients with HPV+OPSCC undergoing surgery.

Flexible Acceptance Condition of Generics from a Probabilistic Viewpoint: Towards Formalization of the Semantics of Generics.

Formalization of the semantics of generics has been considered extremely challenging for their inherent vagueness and context-dependence that hinder a single fixed truth condition. The present study suggests a way to formalize the semantics of generics by constructing flexible acceptance conditions with comparative probabilities. Findings from our in-depth psycholinguistic experiment show that two comparative probabilities-cue validity and prevalence-indeed construct the flexible acceptance conditions for generics in a systematic manner that can be applied to a diverse types of generics: Acceptability of IS_A relational generics is mostly determined by prevalence without interaction with cue validity; feature-describing generics are endorsed acceptable with high cue validity, albeit mediated by prevalence; and acceptability of feature-describing generics with low cue validity is mostly determined by prevalence irrespective of cue validity. Such systematic patterns indicate a great potential for the formalization of the semantics of generics.

Unsupervised inference of implicit biomedical events using context triggers.

BACKGROUND: Event extraction from the biomedical literature is one of the most actively researched areas in biomedical text mining and natural language processing. However, most approaches have focused on events within single sentence boundaries, and have thus paid much less attention to events spanning multiple sentences. The Bacteria-Biotope event (BB-event) subtask presented in BioNLP Shared Task 2016 is one such example; a significant amount of relations between bacteria and biotope span more than one sentence, but existing systems have treated them as false negatives because labeled data is not sufficiently large enough to model a complex reasoning process using supervised learning frameworks. RESULTS: We present an unsupervised method for inferring cross-sentence events by propagating intra-sentence information to adjacent sentences using context trigger expressions that strongly signal the implicit presence of entities of interest. Such expressions can be collected from a large amount of unlabeled plain text based on simple syntactic constraints, helping to overcome the limitation of relying only on a small number of training examples available. The experimental results demonstrate that our unsupervised system extracts cross-sentence events quite well and outperforms all the state-of-the-art supervised systems when combined with existing methods for intra-sentence event extraction. Moreover, our system is also found effective at detecting long-distance intra-sentence events, compared favorably with existing high-dimensional models such as deep neural networks, without any supervised learning techniques. CONCLUSIONS: Our linguistically motivated inference model is shown to be effective at detecting implicit events that have not been covered by previous work, without relying on training data or curated knowledge bases. Moreover, it also helps to boost the performance of existing systems by allowing them to detect additional cross-sentence events. We believe that the proposed model offers an effective way to infer implicit information beyond sentence boundaries, especially when human-annotated data is not sufficient enough to train a robust supervised system.

OncoSearch: cancer gene search engine with literature evidence.

In order to identify genes that are involved in oncogenesis and to understand how such genes affect cancers, abnormal gene expressions in cancers are actively studied. For an efficient access to the results of such studies that are reported in biomedical literature, the relevant information is accumulated via text-mining tools and made available through the Web. However, current Web tools are not yet tailored enough to allow queries that specify how a cancer changes along with the change in gene expression level, which is an important piece of information to understand an involved gene's role in cancer progression or regression. OncoSearch is a Web-based engine that searches Medline abstracts for sentences that mention gene expression changes in cancers, with queries that specify (i) whether a gene expression level is up-regulated or down-regulated, (ii) whether a certain type of cancer progresses or regresses along with such gene expression change and (iii) the expected role of the gene in the cancer. OncoSearch is available through http://oncosearch.biopathway.org.

DigSee: Disease gene search engine with evidence sentences (version cancer).

Biological events such as gene expression, regulation, phosphorylation, localization and protein catabolism play important roles in the development of diseases. Understanding the association between diseases and genes can be enhanced with the identification of involved biological events in this association. Although biological knowledge has been accumulated in several databases and can be accessed through the Web, there is no specialized Web tool yet allowing for a query into the relationship among diseases, genes and biological events. For this task, we developed DigSee to search MEDLINE abstracts for evidence sentences describing that 'genes' are involved in the development of 'cancer' through 'biological events'. DigSee is available through http://gcancer.org/digsee.

E3Net: a system for exploring E3-mediated regulatory networks of cellular functions.

Ubiquitin-protein ligase (E3) is a key enzyme targeting specific substrates in diverse cellular processes for ubiquitination and degradation. The existing findings of substrate specificity of E3 are, however, scattered over a number of resources, making it difficult to study them together with an integrative view. Here we present E3Net, a web-based system that provides a comprehensive collection of available E3-substrate specificities and a systematic framework for the analysis of E3-mediated regulatory networks of diverse cellular functions. Currently, E3Net contains 2201 E3s and 4896 substrates in 427 organisms and 1671 E3-substrate specific relations between 493 E3s and 1277 substrates in 42 organisms, extracted mainly from MEDLINE abstracts and UniProt comments with an automatic text mining method and additional manual inspection and partly from high throughput experiment data and public ubiquitination databases. The significant functions and pathways of the extracted E3-specific substrate groups were identified from a functional enrichment analysis with 12 functional category resources for molecular functions, protein families, protein complexes, pathways, cellular processes, cellular localization, and diseases. E3Net includes interactive analysis and navigation tools that make it possible to build an integrative view of E3-substrate networks and their correlated functions with graphical illustrations and summarized descriptions. As a result, E3Net provides a comprehensive resource of E3s, substrates, and their functional implications summarized from the regulatory network structures of E3-specific substrate groups and their correlated functions. This resource will facilitate further in-depth investigation of ubiquitination-dependent regulatory mechanisms. E3Net is freely available online at http://pnet.kaist.ac.kr/e3net.

Recovery of Recurrent Laryngeal Nerve Function With Neoadjuvant Treatment: Neural Characterization.

OBJECTIVES: Neoadjuvant targeted therapy has emerged as a promising treatment strategy for locally aggressive thyroid cancer. Its impact on tumor and adjacent tissues remains a nascent area of study. Here we report on a series of six subjects with locally advanced thyroid cancer and recurrent laryngeal nerve (RLN) paralysis who experienced recovery of RLN function with neoadjuvant treatment and describe the morphologic and electrophysiologic characteristics of these recovered nerves. METHODS: This is a multicenter retrospective review. Descriptive analysis was conducted to examine the following parameters for recovered nerves: (1) nerve morphology, characterized as Type A (involving epineurium only) versus Type B (extending beyond epineurium); (2) proximal stimulability (normal vs. abnormal vs. absent); and (3) surgical management (resection vs. preservation). RESULTS: Six subjects with unilateral VFP were identified. Median time to return of VF mobility was 3 months (range 2-13.5). All nerves (100%) were noted to have Type A morphology at surgery. Proximal stimulability was normal in four subjects (66.7%), abnormal in one (16.7%), and absent in one (16.7%). Nerves that had improvement of function through neoadjuvant therapy were able to be surgically preserved in five subjects (83.3%). CONCLUSIONS: This represents the first characterization of RLNs that have recovered function with neoadjuvant treatment of locally advanced thyroid cancer. Although much remains unknown, our findings indicate carcinomatous neural invasion is a reversible process and recovered nerves may demonstrate normal morphology and electrophysiologic activity. LEVEL OF EVIDENCE: 4 Laryngoscope, 134:3415-3419, 2024.

CoMAGC: a corpus with multi-faceted annotations of gene-cancer relations.

BACKGROUND: In order to access the large amount of information in biomedical literature about genes implicated in various cancers both efficiently and accurately, the aid of text mining (TM) systems is invaluable. Current TM systems do target either gene-cancer relations or biological processes involving genes and cancers, but the former type produces information not comprehensive enough to explain how a gene affects a cancer, and the latter does not provide a concise summary of gene-cancer relations. RESULTS: In this paper, we present a corpus for the development of TM systems that are specifically targeting gene-cancer relations but are still able to capture complex information in biomedical sentences. We describe CoMAGC, a corpus with multi-faceted annotations of gene-cancer relations. In CoMAGC, a piece of annotation is composed of four semantically orthogonal concepts that together express 1) how a gene changes, 2) how a cancer changes and 3) the causality between the gene and the cancer. The multi-faceted annotations are shown to have high inter-annotator agreement. In addition, we show that the annotations in CoMAGC allow us to infer the prospective roles of genes in cancers and to classify the genes into three classes according to the inferred roles. We encode the mapping between multi-faceted annotations and gene classes into 10 inference rules. The inference rules produce results with high accuracy as measured against human annotations. CoMAGC consists of 821 sentences on prostate, breast and ovarian cancers. Currently, we deal with changes in gene expression levels among other types of gene changes. The corpus is available at http://biopathway.org/CoMAGCunder the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0). CONCLUSIONS: The corpus will be an important resource for the development of advanced TM systems on gene-cancer relations.

Pembrolizumab-Induced Acquired Amegakaryocytic Thrombocytopenia and Successful Combination Treatment With Eltrombopag, Romiplostim and Cyclosporine: A Brief Communication.

Pembrolizumab is a humanized antibody directed against the programmed death-1 receptor on the cell surface, resulting in a T-cell-mediated immune response against tumor cells that can be complicated by immune-related adverse events. Here we present a novel case of pembrolizumab-induced acquired amegakaryocytic thrombocytopenia (AAT) in a patient with metastatic nasopharyngeal carcinoma. AAT is an incredibly rare and challenging entity for which there is no standardized treatment. We discuss our therapeutic approach using a calcineurin inhibitor and thrombopoietin receptor agonists for successful treatment of AAT and resumption of multiagent cytotoxic chemotherapy.

American Head and Neck Society Endocrine Surgery Section and International Thyroid Oncology Group consensus statement on mutational testing in thyroid cancer: Defining advanced thyroid cancer and its targeted treatment.

BACKGROUND: The development of systemic treatment options leveraging the molecular landscape of advanced thyroid cancer is a burgeoning field. This is a multidisciplinary evidence-based statement on the definition of advanced thyroid cancer and its targeted systemic treatment. METHODS: An expert panel was assembled, a literature review was conducted, and best practice statements were developed. The modified Delphi method was applied to assess the degree of consensus for the statements developed by the author panel. RESULTS: A review of the current understanding of thyroid oncogenesis at a molecular level is presented and characteristics of advanced thyroid cancer are defined. Twenty statements in topics including the multidisciplinary management, molecular evaluation, and targeted systemic treatment of advanced thyroid cancer are provided. CONCLUSIONS: With the growth in targeted treatment options for thyroid cancer, a consensus definition of advanced disease and statements regarding the utility of molecular testing and available targeted systemic therapy is warranted.

Cell-Free HPV DNA Provides an Accurate and Rapid Diagnosis of HPV-Associated Head and Neck Cancer.

PURPOSE: HPV-associated head and neck squamous cell carcinoma (HPV+HNSCC) is the most common HPV-associated malignancy in the United States and continues to increase in incidence. Current diagnostic approaches for HPV+HNSCC rely on tissue biopsy followed by histomorphologic assessment and detection of HPV indirectly by p16 IHC. Such approaches are invasive and have variable sensitivity. EXPERIMENTAL DESIGN: We conducted a prospective observational study in 140 subjects (70 cases and 70 controls) to test the hypothesis that a noninvasive diagnostic approach for HPV+HNSCC would have improved diagnostic accuracy, lower cost, and shorter diagnostic interval compared with standard approaches. Blood was collected, processed for circulating tumor HPV DNA (ctHPVDNA), and analyzed with custom ddPCR assays for HPV genotypes 16, 18, 33, 35, and 45. Diagnostic performance, cost, and diagnostic interval were calculated for standard clinical workup and compared with a noninvasive approach using ctHPVDNA combined with cross-sectional imaging and physical examination findings. RESULTS: Sensitivity and specificity of ctHPVDNA for detecting HPV+HNSCC were 98.4% and 98.6%, respectively. Sensitivity and specificity of a composite noninvasive diagnostic using ctHPVDNA and imaging/physical examination were 95.1% and 98.6%, respectively. Diagnostic accuracy of this noninvasive approach was significantly higher than standard of care (Youden index 0.937 vs. 0.707, P = 0.0006). Costs of noninvasive diagnostic were 36% to 38% less than standard clinical workup and the median diagnostic interval was 26 days less. CONCLUSIONS: A noninvasive diagnostic approach for HPV+HNSCC demonstrated improved accuracy, reduced cost, and a shorter time to diagnosis compared with standard clinical workup and could be a viable alternative in the future.

Hospitalization rates and 30-day all-cause mortality among head and neck cancer patients and survivors with COVID-19.

BACKGROUND: The impact of COVID-19 on patients with cancer is emerging, but data are urgently needed for head and neck cancer (HNC) patients or survivors who are inherently high-risk for severe illness and mortality with SARS-CoV-2 infection. METHODS: This multi-institution, academic cohort study collected comprehensive data on clinical risk factors, COVID-19 symptoms and viral testing patterns, information about hospitalization rates, and predictors of survival among HNC patients with active disease or in remission. The primary endpoint was 30-day all-cause mortality from the date of confirmed COVID-19. We performed multivariate analysis to understand the prognostic value of clinical and laboratory parameters on outcomes. RESULTS: Thirty-two patients with COVID-19 and HNC were included. Median age was 70 (range: 38-91) with 38% aged 75+, and 34% resided in long-term care facilities (LTCF). Thirteen (41%) had active cancer, with 6 (19%) on cancer therapy within 4 weeks of COVID-19 diagnosis. New or worsening cough and fatigue were the most commonly reported presenting symptoms. More than 30% required >1 SARS-CoV-2 test before confirming a positive result. Twenty (63%) required hospitalization. At data cutoff, 7 (22%) had died (1 on active cancer treatment), with a 30-day all-cause mortality of 18.9% (95%CI: 11.4-33.6) among all patients, and 71.5% (95%CI: 38.2-92.3) among those requiring intensive care unit (ICU) admission. ICU admission and residing in a LTCF predicted worse outcomes (p < 0.01), while age, gender, and recent treatment did not. CONCLUSIONS: We observed high 30-day all-cause mortality among HNC patients with COVID-19, but most were not on active cancer therapy.

A phase II trial of all-trans retinoic acid (ATRA) in advanced adenoid cystic carcinoma.

BACKGROUND: Effective therapies are lacking for recurrent, metastatic adenoid cystic carcinoma (R/M ACC) and preclinical models suggest retinoic acid agonists inhibit ACC growth. This phase II trial evaluated all-trans retinoic acid (ATRA) as a novel therapy for ACC. METHODS: Patients with R/M ACC (any site) with clinical and/or radiographic progression ≤12 months prior to study entry were eligible. Cohort 1 (CH1) received ATRA 45 mg/m2 split oral daily dosing on days 1-14 of a 28-day cycle; Cohort 2 (CH2) received the same dosing continuously. Primary endpoint was best overall response rate (CR + PR) (RECIST v1.1). Secondary endpoints: safety and progression-free survival (PFS). Exploratory analyses: ATRA impact on MYB expression and genomic predictors of response. RESULTS: Eighteen patients enrolled. There were no responses, but 61% (11/18) had stable disease (SD) and 28% (5/18) progression as best response; 11% (2/18) unevaluable. Median duration of stability: 3.7 months (95%CI, 1.9-3.9). One patient (CH1) remains on drug with SD approaching 1 year. Half of those who received prior VEGFR therapy achieved SD (4/8). At median follow up of 7.9 months, median PFS was 3.2 months (95%CI, 1.8-3.9). N = 1 required dose adjustment; N = 1 came off drug for toxicity. There were no grade 3-4 adverse events. NOTCH1 and PI3K pathway alterations were most frequent. Low MYB protein expression was associated with longer duration of stability on ATRA (P < 0.01). CONCLUSION(S): While the trial did not meet its prespecified response endpoint, ATRA alone or in combination may be a low toxicity treatment for disease growth stabilization in R/M ACC.

Glycemic control and burnt-out diabetes in ESRD.

Treatment of early diabetes mellitus, the most common cause of chronic kidney disease (CKD), may prevent or slow the progression of diabetic nephropathy and lower mortality and the incidence of cardiovascular disease in the general diabetic population and in patients with early stages of CKD. It is unclear whether glycemic control in patients with advanced CKD, including those with end-stage renal disease (ESRD) who undergo maintenance dialysis treatment is beneficial. Aside from the uncertain benefits of treatment in ESRD, hypoglycemic interventions in this population are also complicated by the complex changes in glucose homeostasis related to decreased kidney function and to dialytic therapies, occasionally leading to spontaneous resolution of hyperglycemia and normalization of hemoglobin A1c levels, a condition which might be termed "burnt-out diabetes." Further difficulties in ESRD are posed by the complicated pharmacokinetics of antidiabetic medications and the serious flaws in our available diagnostic tools used for monitoring long-term glycemic control. We review the physiology and pathophysiology of glucose homeostasis in advanced CKD and ESRD, the available antidiabetic medications and their specifics related to kidney function, and the diagnostic tools used to monitor the severity of hyperglycemia and the therapeutic effects of available treatments, along with their deficiencies in ESRD. We also review the concept of burnt-out diabetes and summarize the findings of studies that examined outcomes related to glycemic control in diabetic ESRD patients, and emphasize areas in need of further research.

E3Miner: a text mining tool for ubiquitin-protein ligases.

Ubiquitination is a regulatory process critically involved in the degradation of >80% of cellular proteins, where such proteins are specifically recognized by a key enzyme, or a ubiquitin-protein ligase (E3). Because of this important role of E3s, a rapidly growing body of the published literature in biology and biomedical fields reports novel findings about various E3s and their molecular mechanisms. However, such findings are neither adequately retrieved by general text-mining tools nor systematically made available by such protein databases as UniProt alone. E3Miner is a web-based text mining tool that extracts and organizes comprehensive knowledge about E3s from the abstracts of journal articles and the relevant databases, supporting users to have a good grasp of E3s and their related information easily from the available text. The tool analyzes text sentences to identify protein names for E3s, to narrow down target substrates and other ubiquitin-transferring proteins in E3-specific ubiquitination pathways and to extract molecular features of E3s during ubiquitination. E3Miner also retrieves E3 data about protein functions, other E3-interacting partners and E3-related human diseases from the protein databases, in order to help facilitate further investigation. E3Miner is freely available through http://e3miner.biopathway.org.

Automatic Scoring of Semantic Fluency.

In neuropsychological assessment, semantic fluency is a widely accepted measure of executive function and access to semantic memory. While fluency scores are typically reported as the number of unique words produced, several alternative manual scoring methods have been proposed that provide additional insights into performance, such as clusters of semantically related items. Many automatic scoring methods yield metrics that are difficult to relate to the theories behind manual scoring methods, and most require manually-curated linguistic ontologies or large corpus infrastructure. In this paper, we propose a novel automatic scoring method based on Wikipedia, Backlink-VSM, which is easily adaptable to any of the 61 languages with more than 100k Wikipedia entries, can account for cultural differences in semantic relatedness, and covers a wide range of item categories. Our Backlink-VSM method combines relational knowledge as represented by links between Wikipedia entries (Backlink model) with a semantic proximity metric derived from distributional representations (vector space model; VSM). Backlink-VSM yields measures that approximate manual clustering and switching analyses, providing a straightforward link to the substantial literature that uses these metrics. We illustrate our approach with examples from two languages (English and Korean), and two commonly used categories of items (animals and fruits). For both Korean and English, we show that the measures generated by our automatic scoring procedure correlate well with manual annotations. We also successfully replicate findings that older adults produce significantly fewer switches compared to younger adults. Furthermore, our automatic scoring procedure outperforms the manual scoring method and a WordNet-based model in separating younger and older participants measured by binary classification accuracy for both English and Korean datasets. Our method also generalizes to a different category (fruit), demonstrating its adaptability.

Monitoring the evolutionary aspect of the Gene Ontology to enhance predictability and usability.

BACKGROUND: Much effort is currently made to develop the Gene Ontology (GO). Due to the dynamic nature of information it addresses, GO undergoes constant updates whose results are released at regular intervals as separate versions. Although there are a large number of computational tools to aid the development of GO, they are operating on a particular version of GO, making it difficult for GO curators to anticipate the full impact of particular changes along the time axis on a larger scale. We present a method for tapping into such an evolutionary aspect of GO, by making it possible to keep track of important temporal changes to any of the terms and relations of GO and by consequently making it possible to recognize associated trends. RESULTS: We have developed visualization methods for viewing the changes between two different versions of GO by constructing a colour-coded layered graph. The graph shows both versions of GO with highlights to those GO terms that are added, removed and modified between the two versions. Focusing on a specific GO term or terms of interest over a period, we demonstrate the utility of our system that can be used to make useful hypotheses about the cause of the evolution and to provide new insights into more complex changes. CONCLUSIONS: GO undergoes fast evolutionary changes. A snapshot of GO, as presented by each version of GO alone, overlooks such evolutionary aspects, and consequently limits the utilities of GO. The method that highlights the differences of consecutive versions or two different versions of an evolving ontology with colour-coding enhances the utility of GO for users as well as for developers. To the best of our knowledge, this is the first proposal to visualize the evolutionary aspect of GO.

Making adjustments to event annotations for improved biological event extraction.

BACKGROUND: Current state-of-the-art approaches to biological event extraction train statistical models in a supervised manner on corpora annotated with event triggers and event-argument relations. Inspecting such corpora, we observe that there is ambiguity in the span of event triggers (e.g., "transcriptional activity" vs. 'transcriptional'), leading to inconsistencies across event trigger annotations. Such inconsistencies make it quite likely that similar phrases are annotated with different spans of event triggers, suggesting the possibility that a statistical learning algorithm misses an opportunity for generalizing from such event triggers. METHODS: We anticipate that adjustments to the span of event triggers to reduce these inconsistencies would meaningfully improve the present performance of event extraction systems. In this study, we look into this possibility with the corpora provided by the 2009 BioNLP shared task as a proof of concept. We propose an Informed Expectation-Maximization (EM) algorithm, which trains models using the EM algorithm with a posterior regularization technique, which consults the gold-standard event trigger annotations in a form of constraints. We further propose four constraints on the possible event trigger annotations to be explored by the EM algorithm. RESULTS: The algorithm is shown to outperform the state-of-the-art algorithm on the development corpus in a statistically significant manner and on the test corpus by a narrow margin. CONCLUSIONS: The analysis of the annotations generated by the algorithm shows that there are various types of ambiguity in event annotations, even though they could be small in number.

Prospective Study Evaluating Na18F PET/CT in Predicting Clinical Outcomes and Survival in Advanced Prostate Cancer.

UNLABELLED: This prospective pilot study evaluated the ability of Na(18)F PET/CT to detect and monitor bone metastases over time and its correlation with clinical outcomes and survival in advanced prostate cancer. METHODS: Sixty prostate cancer patients, including 30 with and 30 without known bone metastases by conventional imaging, underwent Na(18)F PET/CT at baseline, 6 mo, and 12 mo. Positive lesions were verified on follow-up scans. Changes in SUVs and lesion number were correlated with prostate-specific antigen change, clinical impression, and overall survival. RESULTS: Significant associations included the following: SUV and prostate-specific antigen percentage change at 6 mo (P = 0.014) and 12 mo (P = 0.0005); SUV maximal percentage change from baseline and clinical impression at 6 mo (P = 0.0147) and 6-12 mo (P = 0.0053); SUV change at 6 mo and overall survival (P = 0.018); number of lesions on Na(18)F PET/CT and clinical impression at baseline (P < 0.0001), 6 mo (P = 0.0078), and 12 mo (P = 0.0029); and number of lesions on Na(18)F PET/CT per patient at baseline and overall survival (P = 0.017). In an exploratory analysis, paired (99m)Tc-methylene diphosphonate bone scans ((99m)Tc-BS) were available for 35 patients at baseline, 19 at 6 mo, and 14 at 12 mo (68 scans). Malignant lesions on Na(18)F PET/CT (n = 57) were classified on (99m)Tc-BS as malignant 65% of the time, indeterminate 25% of the time, and negative 10% of the time. Additionally, 69% of paired scans showed more lesions on Na(18)F PET/CT than on (99m)Tc-BS. CONCLUSION: The baseline number of malignant lesions and changes in SUV on follow-up Na(18)F PET/CT significantly correlate with clinical impression and overall survival. Na(18)F PET/CT detects more bone metastases earlier than (99m)Tc-BS and enhances detection of new bone disease in high-risk patients.

A graphic tool for curating molecular interaction networks from the literature.

We propose a graphic tool for curating molecular interaction networks constructed from the literature by information extraction (IE). In order to turn preliminary results from IE into useful biomedical resources, we propose to use a controlled environment in which visualization and IE work synergistically. The usability of the proposed graphic tool is shown with respect to the identification of incorrectly extracted results that are due to the much troubling coordination phenomena in natural language texts. Through the experiment on molecular interactions in Saccaharomyces cerevisiae, we have seen a meaningful increase (from 91.5% to 97.5%) in the number of correctly extracted interaction information.