Predicting drug response through tumor deconvolution by cancer cell lines.

Large-scale cancer drug sensitivity data have become available for a collection of cancer cell lines, but only limited drug response data from patients are available. Bridging the gap in pharmacogenomics knowledge between in vitro and in vivo datasets remains challenging. In this study, we trained a deep learning model, Scaden-CA, for deconvoluting tumor data into proportions of cancer-type-specific cell lines. Then, we developed a drug response prediction method using the deconvoluted proportions and the drug sensitivity data from cell lines. The Scaden-CA model showed excellent performance in terms of concordance correlation coefficients (>0.9 for model testing) and the correctly deconvoluted rate (>70% across most cancers) for model validation using Cancer Cell Line Encyclopedia (CCLE) bulk RNA data. We applied the model to tumors in The Cancer Genome Atlas (TCGA) dataset and examined associations between predicted cell viability and mutation status or gene expression levels to understand underlying mechanisms of potential value for drug repurposing.

Conductive and Enhanced Mechanical Strength of Mo2Ti2C3 MXene-Based Hydrogel Promotes Neurogenesis and Bone Regeneration in Bone Defect Repair.

Bone defects are common with increasing high-energy fractures, tumor bone invasion, and implantation revision surgery. Bone is an electroactive tissue that has electromechanical interaction with collogen, osteoblasts, and osteoclasts. Hydrogel provides morphological plasticity and extracellular matrix (ECM) 3D structures for cell survival, and is widely used as a bone engineering material. However, the hydrogels have poor mechanical intensity and lack of cell adhesion, slow gelation time, and limited conductivity. MXenes are novel nanomaterials with hydrophilic groups that sense cell electrophysiology and improve hydrogel electric conductivity. Herein, gelatin had multiple active groups (NH2, OH, and COOH) and an accelerated gelation time. Acrylamide has Schiff base bonds to cross-link with gelatin and absorb metal ions. Deacetylated chitosan improved cell adhesion and active groups to connect MXene and acrylamide. We constructed Mo2Ti2C3 MXene hydrogel with improved elastic modulus and viscosity, chemical cross-linking structure, electric conductivity, and good compatibility. Mo2Ti2C3 MXene hydrogel exhibits outstanding osteogenesis in vitro. Mo2Ti2C3 MXene hydrogel promotes osteogenesis via alkaline phosphatase (ALP) and alizarin red S (ARS) staining, improving osteogenic marker genes and protein expressions in vitro. Mo2Ti2C3 MXene hydrogel aids new bone formation in the in vivo calvarial bone defect model via micro-CT and histology. Mo2Ti2C3 MXene hydrogel facilitates neurogenesis factors nerve growth factor (NGF) and brain-derived neurotrophic factor (BDNF) expression, and aids newly born neuron marker Tuj-1 and sensory neuron marker serotonin (5-HT) and osteogenesis pathway proteins, runt-related transcription factor 2 (Runx2), osteocalcin (OCN), SMAD family member 4 (SMAD4), and bone morphogenetic protein-2 (BMP2) in the bone defect repair process. Mo2Ti2C3 MXene hydrogel promotes osteogenesis and neurogenesis, which extends its biomedical application in bone defect reconstruction.

The largest genome-wide association study for breast cancer in Taiwanese Han population.

PURPOSE: Breast cancer is a molecularly heterogeneous disease, and multiple genetic variants contribute to its development and prognosis. Most of previous genome-wide association studies (GWASs) and polygenic risk scores (PRSs) analyses focused on studying breast cancers of Caucasian populations, which may not be applicable to other population. Therefore, we conducted the largest breast cancer cohort of Taiwanese population to fill in the knowledge gap. METHODS: A total of 152,534 Participants recruited by China Medical University Hospital between 2003 and 2019 were filtered by several patient selection criteria and GWAS quality control steps, resulting in the inclusion of 2496 cases and 9984 controls for this study. We then conducted GWAS for all breast cancers and PRS analyses for all breast cancers and the four breast cancer subtypes, including luminal A, luminal B, basal-like, and HER2-enriched. RESULTS: The GWAS analyses identified 113 SNPs, 50 of which were novel. The PRS models for all breast cancers and the luminal A subtype showed positively correlated trends between the PRS and the risk of developing breast cancer. The odds ratios (95% confidence intervals) for the groups with the highest PRS in all breast cancers and the luminal A subtype were 5.33 (3.79-7.66) and 3.55 (2.13-6.14), respectively. CONCLUSION: In summary, we explored the association of genetic variants with breast cancer in the largest Taiwanese cohort and developed two PRS models that can predict the risk of developing any breast cancer and the luminal A subtype in Taiwanese women.

Integrating domain knowledge with machine learning to detect obstructive sleep apnea: Snore as a significant bio-feature.

Our study's main purpose is to emphasise the significance of medical knowledge of pathophysiology before machine learning. We investigated whether combining domain knowledge with machine learning results might increase accuracy and minimise the number of bio-features used to detect obstructive sleep apnea (OSA). The present study analysed data on 36 self-reported symptoms and 24 clinical features obtained from 3,495 patients receiving polysomnography at a regional hospital and a medical centre. The area under the receiver operating characteristic (AUC) curve was used to evaluate patients with and without moderate or severe OSA using three prediction models on the basis of various estimation methods: the multiple logistic regression (MLR), support vector machine (SVM), and neural network (NN) methods. Odds ratios stratified by gender and age were also measured to account for clinicians' common sense. We discovered that adding the self-reported snoring item improved the AUC by 0.01-0.10 and helped us to rapidly achieve the optimum level. The performance of four items (gender, age, body mass index [BMI], and snoring) was comparable with that of adding two or more items (neck and waist circumference) for predicting moderate to severe OSA (Apnea-Hypopnea Index ≥15 events/hr) in all three prediction models, demonstrating the medical knowledge value of pathophysiology. The four-item test sample AUCs were 0.83, 0.84, and 0.83 for MLR, SVM, and NN, respectively. Participants with regular snoring and a BMI of ≥25 kg/m2 had a greater chance of moderate to severe OSA according to the stratified adjusted odds ratios. Combining domain knowledge into machine learning could increase efficiency and enable primary care physicians to refer for an OSA diagnosis earlier.

Sleep disturbance and psychological distress in adult patients with tinnitus.

BACKGROUND/PURPOSE: Sleep disturbance and psychological distress are among the most prevalent comorbidities of tinnitus. We aimed to clarify the dose-response effects of these phenomena with tinnitus severity. METHODS: This study enrolled adult patients with subjective tinnitus for more than 6 months was conducted from January 2017 to December 2018 in one tertiary medical center and one local hospital. Data collected included demographic data and questionnaires, namely Tinnitus Handicap Inventory (THI), Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), and Hospital Anxiety and Depression Scale (HADS). RESULTS: In total, 1610 patients with tinnitus (1105 male, 68.6%) with mean age of 48.3 ± 14.3 years completed all questionnaires. The average THI score was 9.2 ± 19.4, and 82.4% of patients reported to have slight tinnitus (THI ranged 0-16). The mean PSQI score was 8.4 ± 4.3, and 70.8% of participants had sleep difficulty (PSQI > 5). Compared with patients with slight tinnitus, those with catastrophic tinnitus were mostly old women with lower body mass index, and had higher scores in ESS, PSQI, and HADS (all P < 0.05). In 1140 patients with sleep difficulty, independent factors influencing THI were age, ESS, and HADS, and positive correlations were observed between age-adjusted THI and ESS, HADS-A, and HADS-D (all P < 0.001). CONCLUSION: Old age, daytime sleepiness, and psychological distress are highly associated with tinnitus severity among patients with sleep difficulty. Management of sleep disturbance and psychological distress is necessary to control tinnitus.

Trading amino acids at the aphid-Buchnera symbiotic interface.

Plant sap-feeding insects are widespread, having evolved to occupy diverse environmental niches despite exclusive feeding on an impoverished diet lacking in essential amino acids and vitamins. Success depends exquisitely on their symbiotic relationships with microbial symbionts housed within specialized eukaryotic bacteriocyte cells. Each bacteriocyte is packed with symbionts that are individually surrounded by a host-derived symbiosomal membrane representing the absolute host-symbiont interface. The symbiosomal membrane must be a dynamic and selectively permeable structure to enable bidirectional and differential movement of essential nutrients, metabolites, and biosynthetic intermediates, vital for growth and survival of host and symbiont. However, despite this crucial role, the molecular basis of membrane transport across the symbiosomal membrane remains unresolved in all bacteriocyte-containing insects. A transport protein was immunolocalized to the symbiosomal membrane separating the pea aphid Acyrthosiphon pisum from its intracellular symbiont Buchnera aphidicola The transporter, A. pisum nonessential amino acid transporter 1, or ApNEAAT1 (gene: ACYPI008971), was characterized functionally following heterologous expression in Xenopus oocytes, and mediates both inward and outward transport of small dipolar amino acids (serine, proline, cysteine, alanine, glycine). Electroneutral ApNEAAT1 transport is driven by amino acid concentration gradients and is not coupled to transmembrane ion gradients. Previous metabolite profiling of hemolymph and bacteriocyte, alongside metabolic pathway analysis in host and symbiont, enable prediction of a physiological role for ApNEAAT1 in bidirectional host-symbiont amino acid transfer, supplying both host and symbiont with indispensable nutrients and biosynthetic precursors to facilitate metabolic complementarity.

Estimating Life Expectancy From Chinese Medicine Could Improve End-of-Life Care in Terminally Ill Cancer Patients.

Preparing for a good death is an important and meaningful concept in Chinese culture because people hope to know residual life to make effort for their unfinished business. However, the family of terminally ill patients with cancer may be annoyed and frustrated about unexpected bereavement if they have unresolved conflicts with the loved one, missing a chance for declaring love, untimely apologizing and saying goodbye. The study aimed to explore this difficult issue. The medical records of 121 deceased terminally ill patients with cancer at National Cheng Kung University Hospital between December 2010 and February 2012 were reviewed. The signs and awareness of dying among these patients were collected using palliative routine instruments in the hospice ward. The top 3 most prevalent dying signs were coolness and cyanosis (prevalence 98.3%, median period from the first documented dying sign to death 2 days, P = .028), mirror-like tongue (prevalence 94.2%, median period 5 days, P = .007), and earlobe crease (prevalence 93.4%, median period 4 days, P = .052). In addition, the prevalence of dying awareness was 71.1% (median period 4 days, P = .001). Furthermore, terminal agitation was identified more frequently in terminally ill patients with hepatoma and colon cancer (adjusted odds ratio = 3.240, P = .043), but turbid sclera with edema was noted more often in terminally ill patients with head and neck cancer (adjusted odds ratio = 5.698, P = .042). The results provide evidence to support clinical practice, offering knowledge and techniques to health care providers, and increasing quality of life for terminally ill patients with cancer.

Correction to: Depressive symptom trajectories in the first 10 years of diabetes diagnosis: antecedent factors and link with future disability in Taiwan.

The original article can be found online at.

Utilizing Cancer - Functional Gene Set - Compound Networks to Identify Putative Drugs for Breast Cancer.

AIM AND OBJECTIVE: The number of anticancer drugs available currently is limited, and some of them have low treatment response rates. Moreover, developing a new drug for cancer therapy is labor intensive and sometimes cost prohibitive. Therefore, "repositioning" of known cancer treatment compounds can speed up the development time and potentially increase the response rate of cancer therapy. This study proposes a systems biology method for identifying new compound candidates for cancer treatment in two separate procedures. MATERIALS AND METHODS: First, a "gene set-compound" network was constructed by conducting gene set enrichment analysis on the expression profile of responses to a compound. Second, survival analyses were applied to gene expression profiles derived from four breast cancer patient cohorts to identify gene sets that are associated with cancer survival. A "cancer-functional gene set- compound" network was constructed, and candidate anticancer compounds were identified. Through the use of breast cancer as an example, 162 breast cancer survival-associated gene sets and 172 putative compounds were obtained. RESULTS: We demonstrated how to utilize the clinical relevance of previous studies through gene sets and then connect it to candidate compounds by using gene expression data from the Connectivity Map. Specifically, we chose a gene set derived from a stem cell study to demonstrate its association with breast cancer prognosis and discussed six new compounds that can increase the expression of the gene set after the treatment. CONCLUSION: Our method can effectively identify compounds with a potential to be "repositioned" for cancer treatment according to their active mechanisms and their association with patients' survival time.

A Population-Based Cohort Study on the Ability of Acupuncture to Reduce Post-Stroke Depression.

Objective: Post-stroke depression (PSD) is common and has a negative impact on recovery. Although many stroke patients in Taiwan have used acupuncture as a supplementary treatment for reducing stroke comorbidities, little research has been done on the use of acupuncture to prevent PSD. Accordingly, our goal is to investigate whether using acupuncture after a stroke can reduce the risk of PSD. Method: This population-based cohort study examined medical claims data from a random sample of 1 million insured people registered in Taiwan. Newly diagnosed stroke patients in the period 2000-2005 were recruited in our study. All patients were followed through to the end of 2007 to determine whether they had developed symptoms of depression. A Cox proportional hazard model was used to estimate the relative risk of depression in patients after being diagnosed as having had a stroke, with a focus on the differences in those with and without acupuncture treatment. Results: A total of 8487 newly-diagnosed stroke patients were included in our study; of these, 1036 patients received acupuncture more than five times following their stroke, 1053 patients received acupuncture 1-5 times following their stroke and 6398 did not receive acupuncture. After we controlled for potential confounders (e.g., age, sex, insurance premium, residential area, type of stroke, length of hospital stay, stroke severity index, rehabilitation and major illness-related depression), we found that acupuncture after stroke significantly reduced the risk of depression, with a hazard ratio (HR) of 0.475 (95% CI, 0.389-0.580) in frequent acupuncture users and 0.718 (95% CI, 0.612-0.842) in infrequent acupuncture users, indicating that acupuncture may lower the risk of PSD by an estimated 52.5% in frequent users and 28.2% in infrequent users. Conclusions: After we controlled for potential confounders, it appears that using acupuncture after a stroke lowers the risk of depression. Additional strictly-designed randomized controlled trials are needed to better understand the specific mechanisms relating acupuncture to health outcomes.

Depressive symptom trajectories in the first 10 years of diabetes diagnosis: antecedent factors and link with future disability in Taiwan.

PURPOSE: This study identified depressive symptom trajectories in the years after diabetes diagnosis, examined factors that predict the probability for people following a specific trajectory, and investigated how the trajectories are associated with subsequent disability. METHODS: We drew data from a nationally representative survey in Taiwan to identify adults aged 50 and older diagnosed with diabetes; 487 patients newly diagnosed with diabetes during 1996-2007 were included. Time axis was set to zero when diabetes was first reported in any given wave in the survey, and data related to depressive symptoms after that were recorded. We used group-based semi-parametric mixture models to identify trajectories of depressive symptoms and multinomial logistic regressions to examine factors associated with the trajectories. RESULTS: Older adults with newly diagnosis of diabetes in Taiwan follow different trajectories of depressive symptoms over time. Being female, lower educated, not married/partnered, with lower self-rated health, hospitalizations, more limitations in physical function, less regular exercise before diagnosis, and not regularly using anti-diabetic medication at the beginning of their diagnosis were factors associated with increasing or high stable depressive symptom trajectories. Those who experienced high depressive symptoms were more likely than individuals with stable depressive symptoms to have physical limitations in the last follow-up interview. CONCLUSIONS: Depressive symptom trajectories after diabetes diagnosis were associated with select sociodemographic, health, and lifestyle factors before diagnosis, and also predicted subsequent disability. Risk groups identified in the present study may be used for personalized diabetes care that prevents diabetes-related distress and future disability.

Psychological prognosis after newly diagnosed chronic conditions: socio-demographic and clinical correlates.

BACKGROUND: This study was aimed toward discerning depressive symptom trajectories associated with different chronic conditions and toward finding modifiable factors associated with those trajectories. METHODS: Data were drawn from the 1996-2007 Taiwan Longitudinal Study on Aging. Nine chronic conditions were selected, and mood trajectories were measured with the Center of Epidemiological Studies-Depression scale. RESULTS: Among the nine chronic conditions we examined, four patterns of depressive symptom trajectories were identified: (1) elevated depressive symptoms and worsened over time after diagnosed with heart disease (n = 681), arthritis (n = 850), or hypertension (n = 1,207); (2) elevated depressive symptoms without worsening over time after diagnosed with stroke (n = 160), lung diseases (n = 432), gastric conditions (n = 691), or liver diseases (n = 234); (3) no elevated depressive symptoms after diagnosis but an increase in depressive symptoms over time for participants with diabetes (n = 499); and (4) no significant patterns after diagnosed with cancer (n = 57). Cumulative psychological burden over time was significant for participants with hypertension, diabetes, heart diseases, or arthritis. However, these effects disappeared after controlling for comorbidities and physical limitations. Moreover, psychiatric condition was found to play an important role in baseline depressive symptoms among participants diagnosed with lung diseases, arthritis, or liver diseases. CONCLUSIONS: Findings from this study provide information in addressing psychological burden at different times for different conditions. In addition, minimizing the incidence of comorbidities, physical limitations, or psychiatric conditions may have the prospective effect of avoiding the trend of increased depressive symptoms, especially when adults diagnosed with hypertension, diabetes, heart diseases, arthritis, lung diseases, arthritis, or liver diseases.

A simple gene set-based method accurately predicts the synergy of drug pairs.

BACKGROUND: The advance in targeted therapy has greatly increased the effectiveness of clinical cancer therapy and reduced the cytotoxicity of treatments to normal cells. However, patients still suffer from cancer relapse due to the occurrence of drug resistance. It is of great need to explore potential combinatorial drug therapy since individual drug alone may not be sufficient to inhibit continuous activation of cancer-addicted genes or pathways. The DREAM challenge has confirmed the potentiality of computational methods for predicting synergistic drug combinations, while the prediction accuracy can be further improved. METHODS: Based on previous reports, we hypothesized the similarity in biological functions or genes perturbed by two drugs can determine their synergistic effects. To test the feasibility of the hypothesis, we proposed three scoring systems: co-gene score, co-GS score, and co-gene/GS score, measuring the similarities in genes with significant expressional changes, enriched gene sets, and significantly changed genes within an enriched gene sets between a pair of drugs, respectively. Performances of these scoring systems were evaluated by the probabilistic c-index (PC-index) devised by the DREAM consortium. We also applied the proposed method to the Connectivity Map dataset to explore more potential synergistic drug combinations. RESULTS: Using a gold standard derived by the DREAM consortium, we confirmed the prediction power of the three scoring systems (all P-values < 0.05). The co-gene/GS score achieved the best prediction of drug synergy (PC-index = 0.663, P-value < 0.0001), outperforming all methods proposed during DREAM challenge. Furthermore, a binary classification test showed that co-gene/GS scoring was highly accurate and specific. Since our method is constructed on a gene set-based analysis, in addition to synergy prediction, it provides insights into the functional relevance of drug combinations and the underlying mechanisms by which drugs achieve synergy. CONCLUSIONS: Here we proposed a novel and simple method to predict and investigate drug synergy, and validated its efficacy to accurately predict synergistic drug combinations and to comprehensively explore their underlying mechanisms. The method is widely applicable to expression profiles of other drug treatments and is expected to accelerate the realization of precision cancer treatment.

Impact of traditional Chinese medicine on age trajectories of health: evidence from the Taiwan Longitudinal Study on Aging.

Although traditional Chinese medicine (TCM) is widely used, its effect on health outcomes is not well understood. This study employed a cohort sequential design to investigate levels and rates of change in health from midlife to older adulthood in TCM users and nonusers. A sample of 1,302 community-dwelling adults aged 53 to 80 was selected from individuals interviewed in the 1999 Taiwan Longitudinal Study on Aging (TLSA) and reinterviewed in 2003 and 2007. TCM users were identified as participants who reported visiting a Chinese medicine clinic in the year before each of the three interviews. Health outcomes included physical function, self-rated health, cognitive function, and depressive symptoms. Approximately one in five adults reported that they used TCM in at least one wave of the 3 interview years, but less than one in twenty across all waves. Controlling for time-varying sociodemographic and health conditions, levels and rates of change in physical and cognitive function did not differ according to TCM use. Although adults who reported using TCM had higher depressive symptoms (ßTCM = 0.979, 95% confidence interval (CI) = 0.200-1.758) and poorer self-rated health (ßTCM = -0.267, 95% CI = -0.267 to -0.081) at baseline, their rates of change in these outcomes did not differ from those who did not use TCM. Subgroup analyses revealed that TCM use benefited adults with higher depressive symptoms by attenuating worsening depressive symptoms (ßTCM ×Age = -0.221, 95% CI = -0.434 to -0.007). Further research aimed at understanding the specific mechanisms by which TCM affects health outcomes is warranted.

Resolution enhancement of imaging small-scale portions in a compactly supported function.

The ambiguity involved in reconstructing an image from limited Fourier data is removed using a new technique that incorporates prior knowledge of the location of regions containing small-scale features of interest. The prior discrete Fourier transform (PDFT) method for image reconstruction incorporates prior knowledge of the support, and perhaps general shape, of the object function being reconstructed through the use of a weight function. The new approach extends the PDFT by allowing different weight functions to modulate the different spatial frequency components of the reconstructed image. The effectiveness of the new method is tested on one- and two-dimensional simulations.