Structured digital tables on the Semantic Web: toward a structured digital literature

In parallel to the growth in bioscience databases, biomedical publications have increased exponentially in the past decade. However, the extraction of high-quality information from the corpus of scientific literature has been hampered by the lack of machine-interpretable content, despite text-mining advances. To address this, we propose creating a structured digital table as part of an overall effort in developing machine-readable, structured digital literature. In particular, we envision transforming publication tables into standardized triples using Semantic Web approaches. We identify three canonical types of tables (conveying information about properties, networks, and concept hierarchies) and show how more complex tables can be built from these basic types. We envision that authors would create tables initially using the structured triples for canonical types and then have them visually rendered for publication, and we present examples for converting representative tables into triples. Finally, we discuss how ‘stub' versions of structured digital tables could be a useful bridge for connecting together the literature with databases, allowing the former to more precisely document the later

RNA editing contributes to epitranscriptome diversity in chronic lymphocytic leukemia

RNA editing—primarily conversion of adenosine to inosine (A > I)—is a widespread posttranscriptional mechanism, mediated by Adenosine Deaminases acting on RNA (ADAR) enzymes to alter the RNA sequence of primary transcripts. Hence, in addition to somatic mutations and alternative RNA splicing, RNA editing can be a further source for recoding events. Although RNA editing has been detected in many solid cancers and normal tissue, RNA editing in chronic lymphocytic leukemia (CLL) has not been addressed so far. We determined global RNA editing and recurrent, recoding RNA editing events from matched RNA-sequencing and whole exome sequencing data in CLL samples from 45 untreated patients. RNA editing was verified in a validation cohort of 98 CLL patients and revealed substantially altered RNA editing profiles in CLL compared with normal B cells. We further found that RNA editing patterns were prognostically relevant. Finally, we showed that ADAR knockout decreased steady state viability of MEC1 cells and made them more susceptible to treatment with fludarabine and ibrutinib in vitro. We propose that RNA editing contributes to the pathophysiology of CLL and targeting the RNA editing machinery could be a future strategy to maximize treatment efficacy

Temporal muscle thickness is an independent prognostic marker in melanoma patients with newly diagnosed brain metastases.

OBJECTIVES: The purpose of this study was to evaluate the prognostic relevance of temporal muscle thickness (TMT) in melanoma patients with newly diagnosed brain metastases. METHODS: TMT was retrospectively assessed in 146 melanoma patients with newly diagnosed brain metastases on cranial magnetic resonance images. Chart review was used to retrieve clinical parameters, including disease-specific graded prognostic assessment (DS-GPA) and survival times. RESULTS: Patients with a TMT > median showed a statistically significant increase in survival time (13 months) compared to patients with a TMT < median (5 months; p < 0.001; log rank test). A Cox regression model revealed that the risk of death was increased by 27.9% with every millimeter reduction in TMT. In the multivariate analysis, TMT (HR 0.724; 95% 0.642-0.816; < 0.001) and DS-GPA (HR 1.214; 95% CI 1.023-1.439; p = 0.026) showed a statistically significant correlation with overall survival. CONCLUSION: TMT is an independent predictor of survival in melanoma patients with brain metastases. This parameter may aid in patient selection for clinical trials or to the choice of different treatment options based on the determination of frail patient populations

High correlation of temporal muscle thickness with lumbar skeletal muscle cross-sectional area in patients with brain metastases.

OBJECTIVES: This study aimed to assess the correlation of temporal muscle thickness (TMT), measured on routine cranial magnetic resonance (MR) images, with lumbar skeletal muscles obtained on computed tomography (CT) images in brain metastasis patients to establish a new parameter estimating skeletal muscle mass on brain MR images. METHODS: We retrospectively analyzed the cross-sectional area (CSA) of skeletal muscles at the level of the third lumbar vertebra on computed tomography scans and correlated these values with TMT on MR images of the brain in two independent cohorts of 93 lung cancer and 61 melanoma patients (overall: 154 patients) with brain metastases. RESULTS: Pearson correlation revealed a strong association between mean TMT and CSA in lung cancer and melanoma patients with brain metastases (0.733; p<0.001). The two study cohorts did not differ significantly in patient characteristics, including age (p = 0.661), weight (p = 0.787), and height (p = 0.123). However, TMT and CSA measures differed significantly between male and female patients in both lung cancer and melanoma patients with brain metastases (p<0.001). CONCLUSION: Our data indicate that TMT, measured on routine cranial MR images, is a useful surrogate parameter for the estimation of skeletal muscle mass in patients with brain metastases. Thus, TMT may be useful for prognostic assessment, treatment considerations, and stratification or a selection factor for clinical trials in patients with brain metastases. Further studies are needed to assess the association between TMT and clinical frailty parameters, and the usefulness of TMT in patients with primary brain tumors

Survival prediction using temporal muscle thickness measurements on cranial magnetic resonance images in patients with newly diagnosed brain metastases.

OBJECTIVES: To evaluate the prognostic relevance of temporal muscle thickness (TMT) in brain metastasis patients. METHODS: We retrospectively analysed TMT on magnetic resonance (MR) images at diagnosis of brain metastasis in two independent cohorts of 188 breast cancer (BC) and 247 non-small cell lung cancer (NSCLC) patients (overall: 435 patients). RESULTS: Survival analysis using a Cox regression model showed a reduced risk of death by 19% with every additional millimetre of baseline TMT in the BC cohort and by 24% in the NSCLC cohort. Multivariate analysis included TMT and diagnosis-specific graded prognostic assessment (DS-GPA) as covariates in the BC cohort (TMT: HR 0.791/CI [0.703-0.889]/p < 0.001; DS-GPA: HR 1.433/CI [1.160-1.771]/p = 0.001), and TMT, gender and DS-GPA in the NSCLC cohort (TMT: HR 0.710/CI [0.646-0.780]/p < 0.001; gender: HR 0.516/CI [0.387-0.687]/p < 0.001; DS-GPA: HR 1.205/CI [1.018-1.426]/p = 0.030). CONCLUSION: TMT is easily and reproducibly assessable on routine MR images and is an independent predictor of survival in patients with newly diagnosed brain metastasis from BC and NSCLC. TMT may help to better define frail patient populations and thus facilitate patient selection for therapeutic measures or clinical trials. Further prospective studies are needed to correlate TMT with other clinical frailty parameters of patients. KEY POINTS: • TMT has an independent prognostic relevance in brain metastasis patients. • It is an easily and reproducibly parameter assessable on routine cranial MRI. • This parameter may aid in patient selection and stratification in clinical trials. • TMT may serve as surrogate marker for sarcopenia

Hypothyroidism correlates with favourable survival prognosis in patients with brain metastatic cancer

BACKGROUND Several preclinical and epidemiologic studies have indicated tumour-promoting effects of thyroid hormones (THs). However, very limited knowledge exists on the prognostic impact of thyroid function in metastatic cancer. METHODS We compiled a discovery cohort of 1692 patients with newly diagnosed brain metastases (BMs) of solid cancers treated at the Medical University of Vienna and an independent validation cohort of 191 patients with newly diagnosed BMs treated at the University Hospital Zurich. RESULTS Hypothyroidism before diagnosis of cancer was evident in 133 of 1692 (7.9%) patients of the discovery, and in 18 of 191 (9.4%) patients of the validation cohort. In the discovery cohort, hypothyroidism was statistically significantly associated with favourable survival prognosis from diagnosis of cancer (31 vs. 21 months; p = 0.0026) and with survival prognosis from diagnosis of BMs (12 vs. 7 months; p = 0.0079). In multivariate analysis including the diagnosis-specific graded prognostic assessment score, primary tumour type and sex, hypothyroidism was an independent factor associated with survival after diagnosis of BMs (hazard ratio: 0.76; 95% confidence interval [CI]: (0.63; 0.91; p = 0.0034). In the validation cohort, the association of hypothyroidism and favourable survival prognosis from diagnosis of cancer (55 vs. 11 months; p = 0.00058), as well as from diagnosis of BMs (40 vs. 10 months; p = 0.0036) was confirmed. CONCLUSION Pre-existing hypothyroidism was strongly and independently associated with prognosis in patients with newly diagnosed BMs, supporting the evidence from preclinical data that THs may indeed have a tumour-promoting effect. Further investigation of the underlying pathobiological mechanism and potential therapeutic implications are required

High correlation of temporal muscle thickness with lumbar skeletal muscle cross-sectional area in patients with brain metastases.

ObjectivesThis study aimed to assess the correlation of temporal muscle thickness (TMT), measured on routine cranial magnetic resonance (MR) images, with lumbar skeletal muscles obtained on computed tomography (CT) images in brain metastasis patients to establish a new parameter estimating skeletal muscle mass on brain MR images.MethodsWe retrospectively analyzed the cross-sectional area (CSA) of skeletal muscles at the level of the third lumbar vertebra on computed tomography scans and correlated these values with TMT on MR images of the brain in two independent cohorts of 93 lung cancer and 61 melanoma patients (overall: 154 patients) with brain metastases.ResultsPearson correlation revealed a strong association between mean TMT and CSA in lung cancer and melanoma patients with brain metastases (0.733; pConclusionOur data indicate that TMT, measured on routine cranial MR images, is a useful surrogate parameter for the estimation of skeletal muscle mass in patients with brain metastases. Thus, TMT may be useful for prognostic assessment, treatment considerations, and stratification or a selection factor for clinical trials in patients with brain metastases. Further studies are needed to assess the association between TMT and clinical frailty parameters, and the usefulness of TMT in patients with primary brain tumors