Transcript isoforms regulated by alternative splicing can substantially impact carcinogenesis, leading to a need to obtain clues for both gene differential expression and malfunctions of isoform distributions in cancer studies. The Cancer Genome Atlas (TCGA) project was launched in 2008 to collect cancer-related genome mutation raw data from the population. While many repositories tried to add insights into the raw data in TCGA, no existing database provides both comprehensive gene-level and isoform-level cancer stage marker investigation and survival analysis. We constructed Cancer DEIso to facilitate in-depth analyses for both gene-level and isoform-level human cancer studies. Patient RNA-seq data, sample sheets, patient clinical data, and human genome datasets were collected and processed in Cancer DEIso. And four functions to search differentially expressed genes/isoforms between cancer stages were implemented: (i) Search potential gene/isoform markers for a specified cancer type and its two stages; (ii) Search potentially induced cancer types and stages for a gene/isoform; (iii) Expression survival analysis on a given gene/isoform for some cancer; (iv) Gene/isoform stage expression comparison visualization. As an example, we demonstrate that Cancer DEIso can indicate potential colorectal cancer isoform diagnostic markers that are not easily detected when only gene-level expressions are considered. Cancer DEIso is available at http://cosbi4.ee.ncku.edu.tw/DEIso/ .

Objectives To explore the risk factors for fragility fractures in rheumatoid arthritis (RA) patients using a 3-year longitudinal, observational cohort study. Methods This RA registry study included consecutive RA patients in the outpatient clinic of Chang Gung Memorial Hospital since September 1, 2014. The demographics, clinical characteristics, lifestyle, evidence of previous fracture, risk factors according to the Fracture Risk Assessment Tool (FRAX®), and the FRAX score of each participant were recorded. The participants were categorized into the new incident fracture (group A) and no incident fracture (group B) groups based on evidence or absence of new incident fractures and propensity score matching (age and gender, 1:2). Results Overall, 477 participants completed the 3-year observation period. After matching, 103 and 206 participants were allocated to groups A and B, respectively. The non-adjusted model revealed, presented as hazard ratio (HR) (95% confidence interval [CI]), that the presence of co-morbidity (1.80 [1.17–2.78], p = 0.008), Health Assessment Questionnaire Disability Index (1.35 [1.07–1.69], p = 0.010), lower baseline hip bone mineral density (0.11 [0.02–0.48], p = 0.004), longer disease duration (1.02 [1.00–1.04], p = 0.026), higher FRAX score of major fracture (1.03 [1.02–1.04], p<0.001) or hip fracture (1.03 [1.02–1.04], p<0.001), and previous fracture history (2.65 [1.79–3.94], p<0.001) were associated with new incident fracture. After adjustment, it was disclosed that a previous fracture is an independent risk factor for fragility fractures in RA patients (2.17 [1.20–3.90], p = 0.010). Conclusions In addition to aging and disease-related factors, previous fracture history is the most important risk factor for fragility fractures in RA patients.