Nationwide Big Data Analysis of Statin Use and Intracerebral Hemorrhage Risk in Acute Ischemic Stroke Patients in Taiwan.

Background and Objectives: Although statins are recommended for secondary prevention of acute ischemic stroke, some population-based studies and clinical evidence suggest that they might be used with an increased risk of intracranial hemorrhage. In this nested case-control study, we used Taiwan's nationwide universal health insurance database to investigate the possible association between statin therapy prescribed to acute ischemic stroke patients and their risk of subsequent intracerebral hemorrhage and all-cause mortality in Taiwan. Materials and Methods: All data were retrospectively obtained from Taiwan's National Health Insurance Research Database. Acute ischemic stroke patients were divided into a cohort receiving statin pharmacotherapy and a control cohort not receiving statin pharmacotherapy. A 1:1 matching for age, gender, and index day, and propensity score matching was conducted, producing 39,366 cases and 39,366 controls. The primary outcomes were long-term subsequent intracerebral hemorrhage and all-cause mortality. The competing risk between subsequent intracerebral hemorrhage and all-cause mortality was estimated using the Fine and Gray regression hazards model. Results: Patients receiving statin pharmacotherapy after an acute ischemic stroke had a significantly lower risk of subsequent intracerebral hemorrhage (p < 0.0001) and lower all-cause mortality rates (p < 0.0001). Low, moderate, and high dosages of statin were associated with significantly decreased risks for subsequent intracerebral hemorrhage (adjusted sHRs 0.82, 0.74, 0.53) and all-cause mortality (adjusted sHRs 0.75, 0.74, 0.74), respectively. Conclusions: Statin pharmacotherapy was found to safely and effectively reduce the risk of subsequent intracerebral hemorrhage and all-cause mortality in acute ischemic stroke patients in Taiwan.

A preoperative model to predict overall survival in patients with hepatoma undergoing resection.

BACKGROUND: We aimed to develop a preoperative model to predict overall survival (OS) in patients with hepatoma undergoing liver resection (LR). METHODS: Patients who underwent LR for Barcelona Clinic Liver Cancer (BCLC) stage 0, A, or B hepatoma were enrolled. Tumor burden score (TBS) scores were determined using the following equation: TBS (Pinna et al., 2018) 2 = (largest tumor size [in cm])(Pinna et al., 2018) 2 â€‹+ â€‹(tumor number) (Pinna et al., 2018) 22. The cutoff values for radiographic TBS were based on our recently published paper: low, <2.6; medium, 2.6-7.9; high, >7.9. RESULTS: Multivariate analysis showed that radiographic TBS (low: referent; medium: HR â€‹= â€‹2.89; 95 â€‹% CI: 1.60-5.21; p â€‹< â€‹0.001; high, HR â€‹= â€‹7.60; 95 â€‹% CI: 3.80-15.2; p â€‹< â€‹0.001), AFP (<400 â€‹ng/mL: referent; ≧400 â€‹ng/mL: HR â€‹= â€‹1.67, 95 â€‹% CI: 1.11-2.52, p â€‹= â€‹0.014), and cirrhosis (absence: referent; presence: HR â€‹= â€‹1.88, 95 â€‹% CI: 1.30-2.72, p â€‹< â€‹0.001) were associated with OS. A simplified risk score was superior to BCLC system in concordance index (0.688 vs. 0.623). CONCLUSIONS: We have developed a preoperative model that performs better in predicting OS than the BCLC system.

Evaluating Recurrence Risk in Patients Undergoing Breast-conserving Surgery Using E-cadherin Staining as a Biomarker.

BACKGROUND/AIM: Following the National Comprehensive Cancer Network guidelines, radiotherapy is administered after breast-conserving surgery (BCS) in patients with more than four positive lymph nodes. Four positive lymph nodes are typically considered an indicator to assess disease spread and patient prognosis. However, the subjective counting of positive axillary lymph nodes underscores the need for biomarkers to improve diagnostic precision and reduce the risk of unnecessary treatments. Loss of E-cadherin expression is associated with cancer metastasis, but its potential as a predictive marker for cancer treatment remains uncertain. This study aimed to investigate the validity of E-cadherin as a reference for adjuvant radiotherapy in breast cancer patients with positive lymph nodes post-mastectomy. MATERIALS AND METHODS: Immunohistochemistry was performed on 60 clinical tissue specimens to assess these implications. RESULTS: Although no significant result was found in a single E-cadherin subgroup (low, medium, and high subgroups according to the X-tile algorithm), the proposed multivariate model, including the E-cadherin category, breast cancer subtype, and tumor size, yielded satisfactory recurrence risk estimation results for patients undergoing BCS. Patients with a low E-cadherin category, triple-negative breast cancers, and tumor size over 5 cm could have an increased risk of recurrence. CONCLUSION: Our study proposed a multivariate model that serves as a candidate prognostic factor for recurrence-free survival in patients undergoing BCS and radiotherapy. Utilizing this model for patient stratification in high-risk diseases and as a standard for assessing postoperative intensified therapy can potentially improve patient outcomes.

Prognostic mutation signature would serve as a potential prognostic predictor in patients with diffuse large B-cell lymphoma.

The present study aimed to elucidate the prognostic mutation signature (PMS) associated with long-term survival in a diffuse large B-cell lymphoma (DLBCL) cohort. All data including derivation and validation cohorts were retrospectively retrieved from The Cancer Genome Atlas (TCGA) database and whole-exome sequencing (WES) data. The Lasso Cox regression analysis was used to construct the PMS based on WES data, and the PMS was determined using the area under the receiver operating curve (AUC). The predictive performance of eligible PMS was analyzed by time-dependent receiver operating curve (ROC) analyses. After the initial evaluation, a PMS composed of 94 PFS-related genes was constructed. Notably, this constructed PMS accurately predicted the 12-, 36-, and 60-month PFS, with AUC values of 0.982, 0.983, and 0.987, respectively. A higher level of PMS was closely linked to a significantly worse PFS, regardless of the molecular subtype. Further evaluation by forest plot revealed incorporation of international prognostic index or tumor mutational burden into PMS increased the prediction capability for PFS. The drug-gene interaction and pathway exploration revealed the PFS-related genes were associated with DNA damage, TP53, apoptosis, and immune cell functions. In conclusion, this study utilizing a high throughput genetic approach demonstrated that the PMS could serve as a prognostic predictor in DLBCL patients. Furthermore, the identification of the key signaling pathways for disease progression also provides information for further investigation to gain more insight into novel drug-resistant mechanisms.

Polygenic risk score-based prediction of breast cancer risk in Taiwanese women with dense breast using a retrospective cohort study.

Mammographic screening has contributed to a significant reduction in breast cancer mortality. Several studies have highlighted the correlation between breast density, as detected through mammography, and a higher likelihood of developing breast cancer. A polygenic risk score (PRS) is a numerical score that is calculated based on an individual's genetic information. This study aims to explore the potential roles of PRS as candidate markers for breast cancer development and investigate the genetic profiles associated with clinical characteristics in Asian females with dense breasts. This is a retrospective cohort study integrated breast cancer screening, population genotyping, and cancer registry database. The PRSs of the study cohort were estimated using genotyping data of 77 single nucleotide polymorphisms based on the PGS000001 Catalog. A subgroup analysis was conducted for females without breast symptoms. Breast cancer patients constituted a higher proportion of individuals in PRS Q4 (37.8% vs. 24.8% in controls). Among dense breast patients with no symptoms, the high PRS group (Q4) consistently showed a significantly elevated breast cancer risk compared to the low PRS group (Q1-Q3) in both univariate (OR = 2.25, 95% CI 1.43-3.50, P < 0.001) and multivariate analyses (OR: 2.23; 95% CI 1.41-3.48, P < 0.001). The study was extended to predict breast cancer risk using common low-penetrance risk variants in a PRS model, which could be integrated into personalized screening strategies for Taiwanese females with dense breasts without prominent symptoms.

A non-socially-sensitive predictive model of prostate cancer for Asian males with benign prostatic hyperplasia: A multi-site cross-sectional case-control study.

BACKGROUND: Benign prostatic hyperplasia (BPH) is common in aging Asian males and is associated with an excess risk of developing prostate cancer (PCa). However, discussions about socially-sensitive experiences such as sexual activity, which can significantly predict PCa risk, may be considered stigmatized in Asian culture. This study aimed to develop a predictive model for PCa risk in Asian males with BPH using non-socially-sensitive information. METHODS: A cross-sectional case-control study, with PCa patients as the cases and remaining as the controls, was conducted on a cohort of Taiwanese males with BPH from four medical institutions. Patients who met the inclusion criteria were enrolled, excluding those aged over 86 years or who had received human papillomavirus (HPV) vaccination. Non-socially-sensitive variables such as obesity, occupational exposure, HPV infection, and PCa family history score (FH score) were included in a fully adjusted logistic regression model, and depicted using a nomogram. RESULTS: Among 236 BPH patients, 45.3% had PCa. Obesity, occupational exposure, HPV infection, and family history of PCa were significantly associated with PCa risk. The FH score (OR = 1.89, 95% CI = 1.03-3.47, P = 0.041) had the highest impact, followed by HPV infection (OR = 1.47, 95% CI = 1.03-2.11, P = 0.034), occupational exposure (OR = 1.32, 95% CI = 1.15-1.51, P <0.001), and obesity (OR = 1.22, 95% CI = 1.07-1.41, P = 0.005). The nomogram accurately depicted the predictive risk, and the model demonstrated robust performance compared to individual factors. In addition, the subgroup analysis results showed elderly age group could obtain more favorable predictive performance in our proposed model (AUC = 0.712). CONCLUSION: This non-socially-sensitive predictive model for PCa risk in Taiwanese males with BPH integrates multiple factors that could provide acceptable PCa risk-predictive performance, especially for elderly BPH patients over 70 years, aiding clinical decision-making and early cancer detection.

An Information Fusion System-Driven Deep Neural Networks With Application to Cancer Mortality Risk Estimate.

Next-generation sequencing (NGS) genomic data offer valuable high-throughput genomic information for computational applications in medicine. Using genomic data to identify disease-associated genes to estimate cancer mortality risk remains challenging regarding to computational efficiency and risk integration. For determining mortality-related genes, we propose an information fusion system based on a fuzzy system to fuse the numerous deep-learning-based risk scores, consider the significance of features related to time-varying effects and risk stratifications, and interpret the directional relationship and interaction between outcome and predictors. Fuzzy rules were implemented to integrate the considerations mentioned above by merging all the risk score models to achieve advanced risk estimation. The genomic data of head and neck squamous cell carcinoma (HNSCC) were used to evaluate the performance of the proposed computational approach. The results indicated that the proposed computational approach exhibited optimal ability to identify mortality risk-related genes in HNSCC patients. The results also suggest that HNSCC mortality is associated with cancer inflammatory response, the interleukin-17A signaling pathway, stellate cell activation, and the extracellular-regulated protein kinase five signaling pathway, which might offer new therapeutic targets HNSCC through immunologic or antiangiogenic mechanisms. The proposed information fusion system can promote the determination of high-risk genes related to cancer mortality. This study contributes a valid cancer mortality risk estimate that can identify mortality-related genes.

The Prognosis Performance of a Neutrophil- and Lymphocyte-Associated Gene Mutation Score in a Head and Neck Cancer Cohort.

The treatment of head and neck squamous cell carcinomas (HNSCCs) is multimodal, and chemoradiotherapy (CRT) is a critical component. However, the availability of predictive or prognostic markers in patients with HNSCC is limited. Inflammation is a well-documented factor in cancer, and several parameters have been studied, with the neutrophil-to-lymphocyte ratio (NLR) being the most promising. The NLR is the most extensively researched clinical biomarker in various solid tumors, including HNSCC. In our study, we collected clinical and next-generation sequencing (NGS) data with targeted sequencing information from 107 patients with HNSCC who underwent CRT. The difference in the NLR between the good response group and the poor response group was significant, with more patients having a high NLR in the poor response group. We also examined the genetic alterations linked to the NLR and found a total of 41 associated genes across eight common pathways searched from the KEGG database. The overall mutation rate was low, and there was no significant mutation difference between the low- and high-NLR groups. Using a multivariate binomial generalized linear model, we identified three candidate genes (MAP2K2, MAP2K4, and ABL1) that showed significant results and were used to create a gene mutation score (GMS). Using the NLR-GMS category, we noticed that the high-NLR-GMS group had significantly shorter relapse-free survival compared to the intermediate- or low-NLR-GMS groups.

SUV39H1 Expression as a Guideline for Omitting Radiotherapy in Lymph Node-positive Triple-negative Breast Cancer Patients.

BACKGROUND/AIM: The role of postoperative radiotherapy (RT) combined with chemotherapy (CT) for lymph node-positive (LN+) triple-negative breast cancer (TNBC) remains controversial. SUV39H1-mediated epigenetic regulation is associated with cancer cell migration, invasion, metastasis, and treatment resistance. This study aims to identify the role of SUV39H1 in TNBCs. MATERIALS AND METHODS: Overall, 498 TNBCs with SUV39H1 RNA-seq profiles were retrieved from TCGA-BRCA and analyzed; the X-tile algorithm was used to stratify the population into low, intermediate, and high SUV39H1. Furthermore, we performed an in vitro clonogenic cell survival assay using the MDA-MB-231 cell line to assess the effects of SUV39H1 on cellular responses. RESULTS: The results showed that SUV39H1 was significantly higher in TNBC than normal tissue and luminal subtype breast cancer. Notably, SUV39H1 is significantly expressed in the basal-like 1 (BL1) and immunomodulatory (IM) subgroups, compared to other subtypes. Compared to patients with a low or medium expression of SUV39H1, omitting RT only worsens disease-free survival (DFS) in those with high SUV39H1 expression. The experimental results showed SUV39H1 was suppressed by si-SUV39H1, and SUV39H1 knockdown in MDA-MB-231-IV2-1 cells enhanced the cellular toxicity of doxorubicin and paclitaxel. CONCLUSION: Targeting SUV39H1 may provide a potential guiding indication of omitting RT to avoid over-treatment and chemosensitivity for TNBC.

Using the hazard function to evaluate hepatocellular carcinoma recurrence risk after curative resection.

Predicting recurrence patterns of hepatocellular carcinoma (HCC) can be helpful in developing surveillance strategies. This study aimed to use the hazard function to investigate recurrence hazard and peak recurrence time transitions in patients with HCC undergoing liver resection (LR). We enrolled 1204 patients with HCC undergoing LR between 2007 and 2018 at our institution. Recurrence hazard, patterns, and peak rates were analyzed. The overall recurrence hazard peaked at 7.2 months (peak hazard rate [pHR]: 0.0197), but varied markedly. In subgroups analysis based on recurrence risk factors, patients with a high radiographic tumor burden score (pHR: 0.0521), alpha-fetoprotein level ≥ 400 ng/ml (pHR: 0.0427), and pT3-4 (pHR: 0.0656) showed a pronounced peak within the first year after LR. Patients with cirrhosis showed a pronounced peak within three years after LR (pHR: 0.0248), whereas those with Barcelona Clinic Liver Cancer stage B (pHR: 0.0609) and poor tumor differentiation (pHR: 0.0451) showed multiple peaks during the 5-year follow-up period. In contrast, patients without these recurrence risk factors had a relatively flat hazard function curve. HCC recurrence hazard, patterns, and peak rates varied substantially depending on different risk factors of HCC recurrence.

Prevalence of Carbapenem Resistance Genes among Acinetobacter baumannii Isolated from a Teaching Hospital in Taiwan.

The problem of antibiotic-resistant strains has become a global public issue; antibiotic resistance not only limits the choice of treatments but also increases morbidity, mortality and treatment costs. The multi-drug resistant Acinetobacter baumannii is occurring simultaneously in hospitals and has become a major public health issue worldwide. Although many medical units have begun to control the use of antibiotics and paid attention to the issue of drug resistance, understanding the transmission pathways of clinical drug-resistant bacteria and drug-resistant mechanisms can be effective in real-time control and prevent the outbreak of antibiotic-resistant pathogens. In this study, a total of 154 isolates of Acinetobacter baumannii obtained from Chia-Yi Christian Hospital in Taiwan were collected for specific resistance genotyping analysis. Ten genes related to drug resistance, including blaOXA-51-like, blaOXA-23-like, blaOXA-58-like, blaOXA-24-like, blaOXA-143-like, tnpA, ISAba1, blaPER-1, blaNDM and blaADC, and the repetitive element (ERIC2) were selected for genotyping analysis. The results revealed that 135 A. baumannii isolates (87.6%) carried the blaOXA-51-like gene, 4.5% of the isolates harbored the blaOXA-23-like gene, and 3.2% of the isolates carried the blaOXA-58-like gene. However, neither the blaOXA-24-like nor blaOXA-143-like genes were detected in the isolates. Analysis of ESBL-producing strains revealed that blaNDM was not found in the test strains, but 38.3% of the test isolates carried blaPER-1. In addition, blaADC, tnpA and ISAba1genes were found in 64.9%, 74% and 93% of the isolates, respectively. Among the carbapenem-resistant strains of A. baumannii, 68% of the isolates presenting a higher antibiotic resistance carried both tnpA and ISAba1 genes. Analysis of the relationship between their phenotypes (antibiotic resistant and biofilm formation) and genotypes (antibiotic-resistant genes and biofilm-related genes) studied indicated that the bap, ompA, ISAba1and blaOXA-51 genes influenced biofilm formation and antibiotic resistance patterns based on the statistical results of a hierarchical clustering dendrogram. The analysis of the antibiotic-resistant mechanism provides valuable information for the screening, identification, diagnosis, treatment and control of clinical antibiotic-resistant pathogens, and is an important reference pointer to prevent strains from producing resistance.

Shared decision-making for renal replacement treatment and illness perception in patients with advanced chronic kidney disease.

BACKGROUND: Current healthcare trends emphasize the use of shared decision-making (SDM) for renal replacement treatment (RRT) in patients with chronic kidney disease (CKD). This is crucial to understand the relationship between SDM and illness perception of CKD patients. Few studies have focused on SDM and illness perception status of CKD patients and the impact of illness perception on RRT after SDM. METHODS: In this cross-sectional study, we used a questionnaire with purposive sampling from March 2019 to February 2020 at the nephrology outpatient department of a medical center in southern Taiwan. The nephrology medical team in this study used the SHARE five-step model of SDM to communicate with the patients about RRT and Brief Illness Perception Questionnaire (BIPQ) was applied to evaluate illness perception of these patients at the beginning of SDM. According to the SDM decision time, the study participants were classified general and delayed SDM groups. The distribution between SDM groups was estimated using independent two sample t-test, chi-squared test or Fisher's exact test. The correlation between illness perception and SDM decision time were illustrated and evaluated using Spearman's correlation test. A p-value less than 0.05 is statistically significant. RESULTS: A total of 75 patients were enrolled in this study. The average time to make a dialysis decision after initiating SDM was 166.2 ± 178.1 days. 51 patients were classified as general group, and 24 patients were classified as delayed group. The median SDM decision time of delayed group were significantly longer than general group (56 vs. 361 days, P < 0.001). Our findings revealed that delayed group was significantly characterized with not created early surgical assess (delayed vs. general: 66.7% vs. 27.5%, p = 0.001) compared to general group. The average BIPQ score was 54.0 ± 8.1 in our study. We classified the patients into high and low illness perception group according to the median score of BIPQ. The total score of BIPQ in overall participants might increase by the SDM decision time (rho = 0.83, p = 0.830) and the linear regression line also showed consistent trends between BIPQ and SDM decision time in correspond cohorts. However, no statistically significant findings were found. CONCLUSIONS: The patients with advanced chronic kidney disease took an average of five and a half months to make a RRT decision after undergoing SDM. Although there is no statistical significance, the trend of illness perception seems correlated with decision-making time. The stronger the illness perception, the longer the decision-making time. Furthermore, shorter decision times may be associated with earlier establishment of surgical access. We need more research exploring the relationship between illness perception and SDM for RRT in CKD patients.

A Novel Synthetic Oleanolic Acid Derivative Inhibits Glioma Cell Proliferation by Regulating Cell Cycle G2/M Arrest.

2-Cyano-3,12-dioxooleana-1,9(11)-dien-28-oic acid-9,11-dihydro-trifluoroethyl amide (CDDO-dhTFEA) has antioxidant and anti-inflammatory activities; however, whether CDDO-dhTFEA has anticancer effects is unclear. The objective of this research was to investigate the possibility of CDDO-dhTFEA as a potential cancer-fighting treatment in glioblastoma cells. Our experiments were performed on U87MG and GBM8401 cells, and we found that CDDO-dhTFEA was effective in reducing cell proliferation in both cell lines, in a manner that was dependent on both time and concentration. Additionally, we observed that CDDO-dhTFEA had a significant impact on the regulation of cell proliferation, which was evident in the increase in DNA synthesis that was observed in both cell types. CDDO-dhTFEA induced G2/M cell cycle arrest and mitotic delay, which may be associated with the inhibition of proliferation. Treatment with CDDO-dhTFEA led to cell cycle G2/M arrest and inhibited proliferation of U87MG and GBM8401 cells by regulating G2/M cell cycle proteins and gene expression in GBM cells in vitro.

The role of the genomic mutation signature and tumor mutation burden on relapse risk prediction in head and neck squamous cell carcinoma after concurrent chemoradiotherapy.

Personalized genetic profiling has focused on improving treatment efficacy and predicting risk stratification by identifying mutated genes and selecting targeted agents according to genetic testing. Therefore, we evaluated the role of genetic profiling and tumor mutation burden (TMB) using next-generation sequencing in patients with head and neck squamous cell carcinoma (HNSC). The relapse mutation signature (RMS) and chromatin remodeling mutation signature (CRMS) were explored to predict the risk of relapse in patients with HNSC treated with concurrent chemoradiotherapy (CCRT) with platinum-based chemotherapy. Patients in the high RMS and CRMS groups showed significantly shorter relapse-free survival than those in the low RMS and CRMS groups, respectively (p < 0.001 and p = 0.006). Multivariate Cox regression analysis showed that extranodal extension, CCRT response, and three somatic mutation profiles (TMB, RMS, and CRMS) were independent risk predictors for HNSC relapse. The predictive nomogram showed satisfactory performance in predicting relapse-free survival in patients with HNSC treated with CCRT.

Chromatin Remodeling Enzyme Cluster Predicts Prognosis and Clinical Benefit of Therapeutic Strategy in Breast Cancer.

The treatment provided for breast cancer depends on the expression of hormone receptors, human epidermal growth factor receptor-2 (HER2), and cancer staging. Surgical intervention, along with chemotherapy or radiation therapy, is the mainstay of treatment. Currently, precision medicine has led to personalized treatment using reliable biomarkers for the heterogeneity of breast cancer. Recent studies have shown that epigenetic modifications contribute to tumorigenesis through alterations in the expression of tumor suppressor genes. Our aim was to investigate the role of epigenetic modifications in genes involved in breast cancer. A total of 486 patients from The Cancer Genome Atlas Pan-cancer BRCA project were enrolled in our study. Hierarchical agglomerative clustering analysis further divided the 31 candidate genes into 2 clusters according to the optimal number. Kaplan-Meier plots showed worse progression-free survival (PFS) in the high-risk group of gene cluster 1 (GC1). In addition, the high-risk group showed worse PFS in GC1 with lymph node invasion, which also presented a trend of better PFS when chemotherapy was combined with radiotherapy than when chemotherapy was administered alone. In conclusion, we developed a novel panel using hierarchical clustering that high-risk groups of GC1 may be promising predictive biomarkers in the clinical treatment of patients with breast cancer.

Deciphering the Functions of Telomerase Reverse Transcriptase in Head and Neck Cancer.

Head and neck cancers (HNCs) are among the ten leading malignancies worldwide. Despite significant progress in all therapeutic modalities, predictive biomarkers, and targeted therapies for HNCs are limited and the survival rate is unsatisfactory. The importance of telomere maintenance via telomerase reactivation in carcinogenesis has been demonstrated in recent decades. Several mechanisms could activate telomerase reverse transcriptase (TERT), the most common of which is promoter alternation. Two major hotspot TERT promoter mutations (C228T and C250T) have been reported in different malignancies such as melanoma, genitourinary cancers, CNS tumors, hepatocellular carcinoma, thyroid cancers, sarcomas, and HNCs. The frequencies of TERT promoter mutations vary widely across tumors and is quite high in HNCs (11.9-64.7%). These mutations have been reported to be more enriched in oral cavity SCCs and HPV-negative tumors. The association between TERT promoter mutations and poor survival has also been demonstrated. Till now, several therapeutic strategies targeting telomerase have been developed although only a few drugs have been used in clinical trials. Here, we briefly review and summarize our current understanding and evidence of TERT promoter mutations in HNC patients.

A preoperative model for predicting early recurrence in patients undergoing resection for single hepatocellular carcinoma.

BACKGROUND AND AIM: The updated Barcelona Clinic Liver Cancer guidelines recommend liver resection (LR) for patients with single hepatocellular carcinoma (HCC) of any size. This study developed a preoperative model for predicting early recurrence in patients undergoing LR for single HCC. MATERIALS AND METHODS: We identified 773 patients undergoing LR for single HCC between 2011 and 2017 from the cancer registry database of our institution. Multivariate Cox regression analyses were performed to construct a preoperative model for predicting early recurrence, i.e., recurrence within 2 years of LR. RESULTS: Early recurrence was identified in 219 patients (28.3%). The final model of early recurrence included four predictive factors-alpha-fetoprotein level of ≥20 ng/mL, tumor size of >30 mm, Model for End-Stage Liver Disease score of >8, and cirrhosis. Preoperative application of this model provided three risk strata for recurrence-free survival (RFS): low risk, with 2-year RFS of 79.8% (95% confidence interval [CI]: 75.7-84.2%); intermediate risk, with 2-year RFS of 66.6% (95% CI: 61.1-72.6%); and high risk, with 2-year RFS of 51.1% (95% CI: 43.0-60.8%). CONCLUSION: We developed a preoperative model for predicting early recurrence after LR for single HCC. This model provides useful information for clinical decision-making.

Clustering of Chromatin Remodeling Enzymes Predicts Prognosis and Clinical Benefit of Therapeutic Strategy in Pancreatic Cancer.

In recent years, translational research and pharmacological targeting of epigenetic modifications have become the focus of personalized therapy for patients with pancreatic cancer. Preclinical and clinical trials targeting post-translational modifications have been evaluated as monotherapy or in combination with standard chemotherapy. In this study, we selected 43 genes from seven families of chromatin-modifying enzymes and investigated the influences of epigenetic modifications and their interactions on pancreatic ductal adenocarcinoma (PDAC) using hierarchical clustering analysis. Our analysis also evaluated their effects on treatment modalities and regimens of chemotherapy for PDAC. RNA-seq data for a total of 177 patients with pancreatic cancer, obtained from The Cancer Genome Atlas database, were analyzed. Our results suggested that high-risk patients of survival significant chromatin remodeling-associated gene cluster (gene cluster 2), composed of histone methyltransferases, histone acetyltransferases, histone deacetylases, histone demethylases, and 10-11 translocation family, demonstrated inferior progression-free survival and overall survival in patients with PDAC, especially in men. Our novel biomarker, survival significant chromatin remodeling-associated gene cluster, showed superior prediction performance compared with the conventional TNM system. Overall, these findings suggest that epigenetic modifications and interactions play an important role in the prognosis and therapeutic response of patients with PDAC.

Machine learning approaches for the mortality risk assessment of patients undergoing hemodialysis.

Introduction: Mortality is a major primary endpoint for long-term hemodialysis (HD) patients. The clinical status of HD patients generally relies on longitudinal clinical observations such as monthly laboratory examinations and physical examinations. Methods: A total of 829 HD patients who met the inclusion criteria were analyzed. All patients were tracked from January 2009 to December 2013. Taken together, this study performed full-adjusted-Cox proportional hazards (CoxPH), stepwise-CoxPH, random survival forest (RSF)-CoxPH, and whale optimization algorithm (WOA)-CoxPH model for the all-cause mortality risk assessment in HD patients. The model performance between proposed selections of CoxPH models were evaluated using concordance index. Results: The WOA-CoxPH model obtained the highest concordance index compared with RSF-CoxPH and typical selection CoxPH model. The eight significant parameters obtained from the WOA-CoxPH model, including age, diabetes mellitus (DM), hemoglobin (Hb), albumin, creatinine (Cr), potassium (K), Kt/V, and cardiothoracic ratio, have also showed significant survival difference between low- and high-risk characteristics in single-factor analysis. By integrating the risk characteristics of each single factor, patients who obtained seven or more risk characteristics of eight selected parameters were dichotomized as high-risk subgroup, and remaining is considered as low-risk subgroup. The integrated low- and high-risk subgroup showed greater discrepancy compared with each single risk factor selected by WOA-CoxPH model. Conclusion: The study findings revealed WOA-CoxPH model could provide better risk assessment performance compared with RSF-CoxPH and typical selection CoxPH model in the HD patients. In summary, patients who had seven or more risk characteristics of eight selected parameters were at potentially increased risk of all-cause mortality in HD population.

Comprehensive Transcriptomic and Proteomic Analyses Identify a Candidate Gene Set in Cross-Resistance for Endocrine Therapy in Breast Cancer.

Endocrine therapy (ET) of selective estrogen receptor modulators (SERMs), selective estrogen receptor downregulators (SERDs), and aromatase inhibitors (AIs) has been used as the gold standard treatment for hormone-receptor-positive (HR+) breast cancer. Despite its clinical benefits, approximately 30% of patients develop ET resistance, which remains a major clinical challenge in patients with HR+ breast cancer. The mechanisms of ET resistance mainly focus on mutations in the ER and related pathways; however, other targets still exist from ligand-independent ER reactivation. Moreover, mutations in the ER that confer resistance to SERMs or AIs seldom appear in SERDs. To date, little research has been conducted to identify a critical target that appears in both SERMs/SERDs and AIs. In this study, we conducted comprehensive transcriptomic and proteomic analyses from two cohorts of The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) to identify the critical targets for both SERMs/SERDs and AIs of ET resistance. From a treatment response cohort with treatment response for the initial ET regimen and an endocrine therapy cohort with survival outcomes, we identified candidate gene sets that appeared in both SERMs/SERDs and AIs of ET resistance. The candidate gene sets successfully differentiated progress/resistant groups (PD) from complete response groups (CR) and were significantly correlated with survival outcomes in both cohorts. In summary, this study provides valuable clinical implications for the critical roles played by candidate gene sets in the diagnosis, mechanism, and therapeutic strategy for both SERMs/SERDs and AIs of ET resistance for the future.