Polyglutamine Binding Protein 1 regulates neurite outgrowth through recruiting N-WASP.

Neurite outgrowth is a critical step in neural development, leading to the generation of neurite branches that allow individual neurons to make contacts with multiple neurons within the target region. Polyglutamine-binding protein 1 (PQBP1) is a highly conserved protein with a key role in neural development. Our recent mass spectrometric analysis showed that PQBP1 associates with neural Wiskott-Aldrich syndrome protein (N-WASP), an important actin polymerization-promoting factor involved in neurite outgrowth. Here, we report that the WW domain of PQBP1 directly interacts with the proline-rich domain of N-WASP. The disruption of this interaction leads to impaired neurite outgrowth and growth cone size. Furthermore, we demonstrate that PQBP1/N-WASP interaction is critical for the recruitment of N-WASP to the growth cone, but does not affect N-WASP protein levels or N-WASP-induced actin polymerization. Our results indicated that PQBP1 regulates neurite outgrowth by recruiting N-WASP to the growth cone, thus representing an alternative molecular mechanism via which PQBP1-mediates neurite outgrowth.

Defect Engineering in Ce-Based Metal-Organic Frameworks toward Enhanced Catalytic Performance for Hydrogenation of Dicyclopentadiene.

Defective metal-organic frameworks (MOFs) have shown great potential for catalysis due to abundant active sites and adjustable physical and chemical properties. A series of Ce-based MOFs with different defect contents were synthesized via a modulator-induced defect engineering strategy with the aid of the cell pulverization technique. The effects of modulators on the pore structure, morphology, valence distribution of Ce, and Lewis acidity of Ce-MOF-801 were systematically investigated. Among the different samples studied, the optimal Ce-MOF-801-50eq sample exhibited remarkable catalytic activity for DCPD hydrogenation, achieving a conversion rate of 100%, which is significantly higher compared to other Ce-MOF-801-neq samples as well as the Zr-MOF-801-50eq and Hf-MOF-801-50eq samples. The enhanced catalytic performance of Ce-MOF-801-50eq can be attributed to advantages provided by defect engineering, such as the high specific surface area, proper pore size distribution, abundant unsaturated metal sites, and Ce3+/Ce4+ atom ratio, which have been supported by various characterizations. This study provides important insights into the rational design of Ce-MOFs in the field of catalytic DCPD hydrogenation.

Identification of biomarkers and potential therapeutic targets for pancreatic cancer by proteomic analysis in two prospective cohorts.

Pancreatic cancer (PC) is the deadliest malignancy due to late diagnosis. Aberrant alterations in the blood proteome might serve as biomarkers to facilitate early detection of PC. We designed a nested case-control study of incident PC based on a prospective cohort of 38,295 elderly Chinese participants with ∼5.7 years' follow-up. Forty matched case-control pairs passed the quality controls for the proximity extension assay of 1,463 serum proteins. With a lenient threshold of p < 0.005, we discovered regenerating family member 1A (REG1A), REG1B, tumor necrosis factor (TNF), and phospholipase A2 group IB (PLA2G1B) in association with incident PC, among which the two REG1 proteins were replicated using the UK Biobank Pharma Proteomics Project, with effect sizes increasing steadily as diagnosis time approaches the baseline. Mendelian randomization analysis further supported the potential causal effects of REG1 proteins on PC. Taken together, circulating REG1A and REG1B are promising biomarkers and potential therapeutic targets for the early detection and prevention of PC.

Subtype-Specific Association of Mitochondrial DNA Copy Number With Poststroke/TIA Outcomes in 10†241 Patients in China.

BACKGROUND: Mitochondrial DNA copy number (mtDNA-CN) is associated with the severity and mortality in patients with stroke, but the associations in different stroke subtypes remain unexplored. METHODS: We conducted an observational prospective cohort analysis on patients with ischemic stroke or transient ischemic attack enrolled in the Third China National Stroke Registry. We applied logistic models to assess the association of mtDNA-CN with functional outcome (modified Rankin Scale score, 3-6 versus 0-2) and Cox proportional hazard models to assess the association with stroke recurrence (treating mortality as a competing risk) and mortality during a 12-month follow-up, adjusting for sex, age, physical activity, National Institutes of Health Stroke Scale at admission, history of stroke and peripheral artery disease, small artery occlusion, and interleukin-6. Subgroup analyses stratified by age and stroke subtypes were conducted. RESULTS: The Third China National Stroke Registry enrolled 15 166 patients, of which 10 241 with whole-genome sequencing data were retained (mean age, 62.2 [SD, 11.2] years; 68.8% men). The associations between mtDNA-CN and poststroke/transient ischemic attack outcomes were specific to patients aged ≤65 years, with lower mtDNA-CN significantly associated with stroke recurrence in 12 months (subdistribution hazard ratio, 1.15 per SD lower mtDNA-CN [95% CI, 1.04-1.27]; P=5.2×10-3) and higher all-cause mortality in 3 months (hazard ratio, 2.19 [95% CI, 1.41-3.39]; P=5.0×10-4). Across subtypes, the associations of mtDNA-CN with stroke recurrence were specific to stroke of undetermined cause (subdistribution hazard ratio, 1.28 [95% CI, 1.11-1.48]; P=6.6×10-4). In particular, lower mtDNA-CN was associated with poorer functional outcomes in stroke of undetermined cause patients diagnosed with embolic stroke of undetermined source (odds ratio, 1.53 [95% CI, 1.20-1.94]; P=5.4×10-4), which remained significant after excluding patients with recurrent stroke (odds ratio, 1.49 [95% CI, 1.14-1.94]; P=3.0×10-3). CONCLUSIONS: Lower mtDNA-CN is associated with higher stroke recurrence rate and all-cause mortality, as well as poorer functional outcome at follow-up, among stroke of undetermined cause, embolic stroke of undetermined source, and younger patients.

Enhancing the Flame Retardancy of Polyester/Cotton Blend Fabrics Using Biobased Urea-Phytate Salt.

The use of biobased flame-retardant (FR) agents for reducing the flammability of polyester/cotton (T/C) blend fabrics is highly desirable. In this study, a novel and sustainable phosphorus/nitrogen-containing FR, namely, phytic acid-urea (PA-UR) salt, was synthesized. The PA-UR salt was further used to enhance the FR performance of T/C fabric through surface modification. We further explored the potential chemical structure of PA-UR and the surface morphology, thermal stability, heat release capacity, FR properties, and mode of action of the coated fabric. The coated fabric achieved self-extinguishing and exhibited an increased limiting oxygen index of 31.8%. Moreover, the coated T/C blend fabric demonstrated a significantly reduced heat release capacity, indicating a decreased fire hazard. Thermogravimetric analysis revealed the anticipated decomposition of the coated T/C blend fabric and a subsequent increase in thermal stability. The burned char residues also maintained their fiber shape structures, suggesting the presence of condensed FR actions in the PA-UR-coated T/C blend fabric.

Dual-task turn velocity - a novel digital biomarker for mild cognitive impairment and dementia.

Background: Disorders associated with cognitive impairment impose a significant burden on both families and society. Previous studies have indicated that gait characteristics under dual-task as reliable markers of early cognitive impairment. Therefore, digital gait detection has great potential for future cognitive screening. However, research on digital biomarkers based on smart devices to identify cognitive impairment remains limited. The aim of this study is to explore digital gait biomarkers by utilizing intelligent wearable devices for discriminating mild cognitive impairment and dementia. Methods: This study included 122 subjects (age: 74.7 ± 7.7 years) diagnosed with normal cognition (NC, n = 38), mild cognitive impairment (MCI, n = 42), or dementia (n = 42). All subjects underwent comprehensive neuropsychological assessments and cranial Magnetic Resonance Imaging (MRI). Gait parameters were collected using validated wearable devices in both single-task and dual-task (DT). We analyzed the ability of gait variables to predict MCI and dementia, and examined the correlations between specific DT-gait parameters and sub-cognitive functions as well as hippocampal atrophy. Results: Our results demonstrated that dual-task could significantly improve the ability to predict cognitive impairment based on gait parameters such as gait speed (GS) and stride length (SL). Additionally, we discovered that turn velocity (TV and DT-TV) can be a valuable novel digital marker for predicting MCI and dementia, for identifying MCI (DT-TV: AUC = 0.801, sensitivity 0.738, specificity 0.842), and dementia (DT-TV: AUC = 0.923, sensitivity 0.857, specificity 0.842). The correlation analysis and linear regression analysis revealed a robust association between DT-TV and memory function, as well as the hippocampus atrophy. Conclusion: This study presents a novel finding that DT-TV could accurately identify varying degrees of cognitive impairment. DT-TV is strongly correlated with memory function and hippocampus shrinkage, suggests that it can accurately reflect changes in cognitive function. Therefore, DT-TV could serve as a novel and effective digital biomarker for discriminating cognitive impairment.

Identification of the prognostic value of LACTB2 and its correlation with immune infiltrates in ovarian cancer by integrated bioinformatics analyses.

Ovarian cancer (OC) is one of the most common reproductive tumors in women, whereas current treatment options are limited. ß-lactamase-like-protein 2 (LACTB2) has been observed to be associated with various cancers, but its function in OC is unknown. Therefore, we evaluate the prognostic value and the underlying function of LACTB2 in OC. In this study, high expression of LACTB2 was observed in OC compared with normal controls. Kaplan-Meier Plotter analysis revealed that overexpressed LACTB2 is strongly correlated with poor prognosis. We conducted GO/KEGG analysis to investigate the potential biological function of LACTB2 in OC. GESA analysis showed that LACTB2 was closely related to immune-related pathways. Subsequently, we explored the relationship between LACTB2 and 24 types of immune cells in OC. The results suggested that LACTB2 was positively associated with multiple tumor-infiltrating immune cells. Importantly, LACTB2 may modulate immune cell infiltration in OC to influence prognosis. In conclusion, LACTB2 can be used as a promising prognostic biomarker and immunotherapy target for OC.

Comprehensive machine learning-based preoperative blood features predict the prognosis for ovarian cancer.

PURPOSE: Significant advancements in improving ovarian cancer (OC) outcomes have been limited over the past decade. To predict prognosis and improve outcomes of OC, we plan to develop and validate a robust prognosis signature based on blood features. METHODS: We screened age and 33 blood features from 331 OC patients. Using ten machine learning algorithms, 88 combinations were generated, from which one was selected to construct a blood risk score (BRS) according to the highest C-index in the test dataset. RESULTS: Stepcox (both) and Enet (alpha = 0.7) performed the best in the test dataset with a C-index of 0.711. Meanwhile, the low RBS group possessed observably prolonged survival in this model. Compared to traditional prognostic-related features such as age, stage, grade, and CA125, our combined model had the highest AUC values at 3, 5, and 7 years. According to the results of the model, BRS can provide accurate predictions of OC prognosis. BRS was also capable of identifying various prognostic stratifications in different stages and grades. Importantly, developing the nomogram may improve performance by combining BRS and stage. CONCLUSION: This study provides a valuable combined machine-learning model that can be used for predicting the individualized prognosis of OC patients.

Anoikis-related signature predicts prognosis and characterizes immune landscape of ovarian cancer.

Ovarian cancer (OV) is the most lethal gynecological malignancy worldwide, with high recurrence rates. Anoikis, a newly-acknowledged form of programmed cell death, plays an essential role in cancer progression, though studies focused on prognostic patterns of anoikis in OV are still lacking. We filtered 32 potential anoikis-related genes (ARGs) among the 6406 differentially expressed genes (DEGs) between the 180 normal controls and 376 TCGA-OV samples. Through the LASSO-Cox analysis, a 2-gene prognostic signature, namely AKT2, and DAPK1, was finally distinguished. We then demonstrated the promising prognostic value of the signature through the K-M survival analysis and time-dependent ROC curves (p-value < 0.05). Moreover, based on the signature and clinical features, we constructed and validated a nomogram model for 1-year, 3-year, and 5-year overall survival, with reliable prognostic values in both TCGA-OV training cohort (p-value < 0.001) and ICGC-OV validation cohort (p-value = 0.030). We evaluated the tumor immune landscape through the CIBERSORT algorithm, which indicated the upregulation of resting Myeloid Dendritic Cells (DCs), memory B cells, and naïve B cells and high expression of key immune checkpoint molecules (CD274 and PDCD1LG2) in the high-risk group. Interestingly, the high-risk group exhibited better sensitivity toward immunotherapy and less sensitivity toward chemotherapies, including Cisplatin and Bleomycin. Especially, based on the IHC of tissue microarrays among 125 OV patients at our institution, we reported that aberrant upregulation of DAPK1 was related to poor prognosis. Conclusively, the anoikis-related signature was a promising tool to evaluate prognosis and predict therapy responses, thus assisting decision-making in the realm of OV precision medicine.

CSGALNACT2 restricts ovarian cancer migration and invasion by modulating MAPK/ERK pathway through DUSP1.

PURPOSE: Ovarian cancer is one of the leading causes of cancer-related death among women. CSGALNACT2 is a vital Golgi transferase and is related to a variety of human diseases. However, its expression pattern and function in ovarian cancer remain uncertain. METHODS: The Cancer Genome Atlas and GEPIA databases were used to assess the expression of CSGALNACT2 in ovarian cancer patients. RNA-seq, qRT-PCR, and IHC were used to verify the expression of CSGALNACT2 in ovarian cancer tissues. Then, in vivo and in vitro experiments were conducted to evaluate the role of CSGALNACT2 in the progression of ovarian cancer. RNA-seq and GSEA were used to reveal the potential biological function and oncogenic pathways of CSGALNACT2. RESULTS: We demonstrated that the mRNA expression and protein level of CSGALNACT2 were significantly downregulated in ovarian cancer and ovarian cancer metastatic tissues. CSGALNACT2 can significantly inhibit the migration, invasion, and clonogenic growth of ovarian cancer in vitro and is progressively lost during ovarian cancer progression in vivo. CSGALNACT2 suppresses ovarian cancer migration and invasion via DUSP1 modulation of the MAPK/ERK pathway through RNA-seq, KEGG analysis, and Western blotting. Moreover, CSGALNACT2 expression was correlated with immune cell infiltration and had prognostic value in different immune cell-enriched or decreased ovarian cancer. In addition, patients with CSGALNACT2 downregulation are less likely to benefit from immunotherapy. CONCLUSION: As an ovarian cancer suppressor gene, CSGALNACT2 inhibits the development of ovarian cancer, and it might be used as a prognostic biomarker in patients with ovarian cancer.

Genetic and observational associations of lung function with gastrointestinal tract diseases: pleiotropic and mendelian randomization analysis.

BACKGROUND: The two-way communications along the gut-lung axis influence the immune function in both gut and lung. However, the shared genetic characteristics of lung function with gastrointestinal tract (GIT) diseases remain to be investigated. METHODS: We first investigated the genetic correlations between three lung function traits and four GIT diseases. Second, we illustrated the genetic overlap by genome-wide pleiotropic analysis (PLACO) and further pinpointed the relevant tissue and cell types by partitioning heritability. Furthermore, we proposed pleiotropic genes as potential drug targets by drug database mining. Finally, we evaluated the causal relationships by epidemiologic observational study and Mendelian randomization (MR) analysis. RESULTS: We found lung function and GIT diseases were genetically correlated. We identified 258 pleiotropic loci, which were enriched in gut- and lung-specific regions marked by H3K4me1. Among these, 16 pleiotropic genes were targets of drugs, such as tofacitinib and baricitinib targeting TYK2 for the treatment of ulcer colitis and COVID-19, respectively. We identified a missense variant in TYK2, exhibiting a shared causal effect on FEV1/FVC and inflammatory bowel disease (rs12720356, PPLACO=1.38 × 10- 8). These findings suggested TYK2 as a promising drug target. Although the epidemiologic observational study suggested the protective role of lung function in the development of GIT diseases, no causalities were found by MR analysis. CONCLUSIONS: Our study suggested the shared genetic characteristics between lung function and GIT diseases. The pleiotropic variants could exert their effects by modulating gene expression marked by histone modifications. Finally, we highlighted the potential of pleiotropic analyses in drug repurposing.

Carbon dots-functionalized extended gate organic field effect transistor-based biosensors for low abundance proteins.

Organic field effect transistors have emerged as promising platforms for biosensing applications. However, the challenge lies in optimizing functionalization strategies for the sensing interface, enabling the simultaneous detection of low abundance proteins while maintaining device performance. Here, we designed a carbon dots-functionalized extended gate organic field effect transistor. Leveraging the advantages of facile synthesis, tunable modification, small particle size, and cost-effectiveness of carbon dots, we implemented their integration onto the electrode surface. Through harnessing the covalent interactions of functional groups on the surface of carbon dots, we achieved effective immobilization of low abundance proteins without compromising device performance. Consequently, this biosensor exhibits a remarkably low limit of detection of 2.7 pg mL-1 and demonstrates high selectivity for the carcinoembryonic antigen. These findings highlight the superior capabilities of carbon dots in enhancing biosensor performance and emphasize their potential for early cancer detection.

Clinical significance and immune infiltration analyses of a novel coagulation-related signature in ovarian cancer.

Ovarian cancer (OV) is the most lethal gynecological malignancies worldwide. The coagulation cascade could induce tumor cell infiltration and contribute to OV progression. However, coagulation-related gene (CRG) signature for OV prognosis hasn't been determined yet. In this study, we evaluated the prognostic value of coagulation scores through receiver operating characteristics (ROC) analysis and K-M curves, among OV patients at our institution. Based on the transcriptome data of TCGA-OV cohort, we stratified two coagulation-related subtypes with distinct differences in prognosis and tumor immune microenvironment (p < 0.05). Moreover, from the 6406 differentially-expressed genes (DEGs) between the GTEx (n = 180) and TCGA-OV cohorts (n = 376), we identified 138 potential CRGs. Through LASSO-Cox algorithm, we finally distinguished a 3-gene signature (SERPINA10, CD38, and ZBTB16), with promising prognostic ability in both TCGA (p < 0.001) and ICGC cohorts (p = 0.040). Stepwise, we constructed a nomogram based on the clinical features and coagulation-related signature for overall survival prediction, with the C-index of 0.6761, which was evaluated by calibration curves. Especially, based on tissue microarrays analysis, Quantitative real-time fluorescence PCR (qRT-PCR), and Western Blot, we found that aberrant upregulation of CRGs was related to poor prognosis in OV at both mRNA and protein level (p < 0.05). Collectively, the coagulation-related signature was a robust prognostic biomarker, which could provide therapeutic benefits for chemotherapy/immunotherapy and assist clinical decision in OV patients.

A Novel pyroptosis-related signature for predicting prognosis and evaluating tumor immune microenvironment in ovarian cancer.

Ovarian cancer (OV) is the most fatal gynecological malignant tumor worldwide, with high recurrence rates and great heterogeneity. Pyroptosis is a newly-acknowledged inflammatory form of cell death with an essential role in cancer progression, though studies focusing on prognostic patterns of pyroptosis in OV are still lacking. Our research filtered 106 potential pyroptosis-related genes (PRGs) among the 6406 differentially expressed genes (DEGs) between the 376 TCGA-OV samples and 180 normal controls. Through the LASSO-Cox analysis, the 6-gene prognostic signature, namely CITED2, EXOC6B, MIA2, NRAS, SETBP1, and TRPV46, was finally distinguished. Then, the K-M survival analysis and time-dependent ROC curves demonstrated the promising prognostic value of the 6-gene signature (p-value < 0.0001). Furthermore, based on the signature and corresponding clinical features, we constructed and validated a nomogram model for 1-year, 2-year, and 3-year OV survival, with reliable prognostic values in TCGA-OV (p-value < 0.001) and ICGC-OV cohort (p-value = 0.040). Pathway analysis enriched several critical pathways in cancer, refer to the pyroptosis-related signature, while the m6A analysis indicated greater m6A level in high-risk group. We assessed tumor immune microenvironment through the CIBERSORT algorithm, which demonstrated the upregulation of M1 Macrophages and activated DCs and high expression of key immune checkpoint molecules (CTLA4, PDCD1LG2, and HAVCR2) in high-risk group. Interestingly, the high-risk group exhibited poor sensitivity towards immunotherapy and better sensitivity towards chemotherapies, including Vinblastine, Docetaxel, and Sorafenib. Briefly, the pyroptosis-related signature was a promising tool to predict prognosis and evaluate immune responses, in order to assist decision-making for OV patients in the realm of precision medicine.

Regulating Exciton De-Trapping of Te4+ -Doped Zero-Dimensional Scandium-Halide Perovskite for Fluorescence Thermometry with Record High Time-Resolved Thermal Sensitivity.

Fluorescence thermometry has been propelled to the forefront of scientific attention due to its high spatial resolution and remote non-invasive detection. However, recent generations of thermometers still suffer from limited thermal sensitivity (Sr ) below 10% change per Kelvin. Herein, this work presents an ideal temperature-responsive fluorescence material through Te4+ -doped 0D Cs2 ScCl5 ·H2 O, in which isolated polyhedrons endow highly localized electronic structures, and the strong electron-phonon coupling facilitates the formation of self-trapped excitons (STEs). With rising temperature, the dramatic asymmetric expansion of the soft lattice induces increased defects, strong exciton-phonon coupling, and low thermal activation energy, which evokes a rapid de-trapping process of STEs, enabling several orders of magnitude changes in the fluorescence lifetime over a narrow temperature range. After regulating the de-trapping process with different Te4+ doping, a record-high Sr (27.36% K-1 ) of fluorescence lifetime-based detection is achieved at 325 K. The robust stability against multiple heating/cooling cycles and long-term measurements enables a low temperature uncertainty of 0.067 K. Further, the developed thermometers are demonstrated for the remote local monitoring of operating temperature on internal electronic components. It is believed that this work constitutes a solid step towards building the next generation of ultrasensitive thermometers based on low-dimensional metal halides.

Association of immune cell composition with the risk factors and incidence of acute coronary syndrome.

BACKGROUND: Although immune cells are involved in acute coronary syndrome (ACS), few studies have explored the association of incident ACS with the relative immune cell proportions. We aimed to investigate the association of immune cell proportions with the incidence and risk factors of ACS in the Dongfeng-Tongji cohort. METHODS: We conducted the analyses with 38,295 subjects from the first follow-up of the Dongfeng-Tongji cohort, including DNA methylation profiles for 1570 individuals. The proportions of immune cell types were observed from routine blood tests or estimated from DNA methylation profiles. For both observed and estimated immune cell proportions, we tested their associations with risk factors of ACS by multivariable linear regression models. In addition, the association of each immune cell proportion with incident ACS was assessed by the Cox regression model and conditional logistic regression model, respectively, adjusting for the risk factors of ACS. FINDINGS: The proportions of lymphocytes, monocytes, and neutrophils showed strong associations with sex, followed by diabetes. Moreover, sex and current smoking were the two factors with strongest association with the proportions of lymphocyte subtypes. The hazard ratio (HR) and 95% confidence interval (CI) of incident ACS per standard deviation (SD) increase in proportions of lymphocytes and neutrophils were 0.91 (0.85-0.96) and 1.10 (1.03-1.16), respectively. Furthermore, the OR (95% CI) of incident ACS per SD increase in proportions of NK cells, CD4+ T cells, and B cells were 0.88 (0.78-0.99), 1.15 (1.03-1.30), and 1.13 (1.00-1.26), respectively. INTERPRETATION: The proportions of immune cells were associated with several risk factors of ACS, including sex, diabetes, and current smoking. In addition, proportion of neutrophils had a risk effect, while proportion of lymphocytes had a protective effect on the incidence of ACS. The protective effect of lymphocytes was probably driven by NK cells.

The role of autophagy in regulating metabolism in the tumor microenvironment.

Autophagy, as a special programmed cell death, is a critical degradative process that eliminates intracellular abnormal proteins or damage organelles to balance cell energy and favor cell metabolism with autophagy-related (ATG) proteins. Autophagy activation is being increasingly recognized as an essential hallmark in tumorigenesis through influencing the metabolism of stromal cells in the tumor microenvironment (TME) which comprises of tumor cells, cancer-associated fibroblasts (CAFs), cancer-associated endothelial cells (CAEs), immune cells and adipocytes. Tumor cells can reuse autophagy-involved recycling to maintain mitochondrial function and energy supply to meet the metabolic demand of their growth and proliferation. However, the mechanism through which autophagy can promote a crosstalk between tumor and stroma cells is not clear. Reprogramed metabolism is one of the main characteristics of TME leading to higher adaptability of tumor cells with diverse mechanisms. The activation of autophagy has expanded our understanding on the interaction between tumor metabolism and TME. The aim of this review is to report recent advances on the metabolic cross-talk between stromal cells and solid tumor cells induced by autophagy in TME and revealed potential therapeutic targets.

CenhANCER: a comprehensive cancer enhancer database for primary tissues and cell lines.

Enhancers, which are key tumorigenic factors with wide applications for subtyping, diagnosis and treatment of cancer, are attracting increasing attention in the cancer research. However, systematic analysis of cancer enhancers poses a challenge due to the lack of integrative data resources, especially those from tumor primary tissues. To provide a comprehensive enhancer profile across cancer types, we developed a cancer enhancer database CenhANCER by curating public resources including all the public H3K27ac ChIP-Seq data from 805 primary tissue samples and 671 cell line samples across 41 cancer types. In total, 57 029 408 typical enhancers, 978 411 super-enhancers and 226 726 enriched transcription factors were identified. We annotated the super-enhancers with chromatin accessibility regions, cancer expression quantitative trait loci (eQTLs), genotype-tissue expression eQTLs and genome-wide association study risk single nucleotide polymorphisms (SNPs) for further functional analysis. The identified enhancers were highly consistent with accessible chromatin regions in the corresponding cancer types, and all the 10 super-enhancer regions identified from one colorectal cancer study were recapitulated in our CenhANCER, both of which testified the high quality of our data. CenhANCER with high-quality cancer enhancer candidates and transcription factors that are potential therapeutic targets across multiple cancer types provides a credible resource for single cancer analysis and for comparative studies of various cancer types. Database URL http://cenhancer.chenzxlab.cn/.

A novel autophagy-related gene signature associated with prognosis and immune microenvironment in ovarian cancer.

Ovarian cancer (OV), the most fatal gynecological malignance worldwide, has high recurrence rates and poor prognosis. Recently, emerging evidence supports that autophagy, a highly regulated multi-step self-digestive process, plays an essential role in OV progression. Accordingly, we filtered 52 potential autophagy-related genes (ATGs) among the 6197 differentially expressed genes (DEGs) identified in TCGA-OV samples (n = 372) and normal controls (n = 180). Based on the LASSO-Cox analysis, we distinguished a 2-gene prognostic signature, namely FOXO1 and CASP8, with promising prognostic value (p-value < 0.001). Together with corresponding clinical features, we constructed a nomogram model for 1-year, 2-year, and 3-year survival, which was validated in both in training (TCGA-OV, p-value < 0.001) and validation (ICGC-OV, p-value = 0.030) cohorts. Interestingly, we evaluated the immune infiltration landscape through the CIBERSORT algorithm, which indicated the upregulation of 5 immune cells, including CD8 + T cells, Tregs, and Macrophages M2, and high expression of critical immune checkpoints (CTLA4, HAVCR2, PDCD1LG2, and TIGIT) in high-risk group. Stepwise, high-risk group exhibited better sensitivity towards chemotherapies of Bleomycin, Sorafenib, Veliparib, and Vinblastine, though less sensitive to immunotherapy. Especially, based on the IHC of tissue microarrays among 125 patients in our institution, we demonstrated that aberrant upregulation of FOXO1 in OV was related to metastasis and poor prognosis. Moreover, FOXO1 could significantly promote tumor invasiveness, migration, and proliferation in OV cell lines, which was assessed through the Transwell, wound-healing, and CCK-8 assay, respectively. Briefly, the autophagy-related signature was a reliable tool to evaluate immune responses and predict prognosis in the realm of OV precision medicine.

Risk prediction of hepatobiliary and pancreatic cancers in elderly Chinese: The Dongfeng-Tongji cohort.

AIM: Hepatobiliary and pancreatic (HBP) cancers are among the deadliest malignancies. The objective of the study is to build cost-effective models to identify high-risk individuals for early diagnosis and substantially to reduce the burden of HBP cancers. METHODS: Based on the prospective Dongfeng-Tongji cohort with ∼6 years follow-up, we identified 162 incident cases of hepatocellular carcinoma (HCC), 53 of biliary tract cancer (BTC), and 58 of pancreatic cancer (PC). We matched three controls to each case by age, sex, and hospital. We applied conditional logistic regression to identify predictive clinical variables, from which we constructed clinical risk scores (CRSs). We evaluated the utility of CRSs in stratifying high-risk individuals by 10-fold cross-validation. RESULTS: Among 50 variables we screened, 6 were independent predictors of HCC, with the top ones being hepatitis (OR = 8.51, 95% CI (3.83, 18.9)), plateletcrit (OR = 0.57, 95% CI (0.42, 0.78)), and alanine aminotransferase (OR = 2.06, 95% CI (1.39, 3.06)). Gallstone (OR = 2.70, 95% CI (1.17, 6.24)) and direct bilirubin (OR = 1.58, 95% CI (1.08, 2.31)) were predictive of BTC, while hyperlipidemia (OR = 2.56, 95% CI (1.12, 5.82)) and fasting blood glucose (OR = 2.00, 95% CI (1.26, 3.15)) were predictive of PC. The CRSs achieved AUCs of 0.784 for HCC, 0.648 for BTC, and 0.666 for PC, respectively. When applying to the full cohort with age and sex included as predictors, the AUCs were increased to 0.818, 0.704, and 0.699, respectively. CONCLUSIONS: Disease history and routine clinical variables are predictive of incident HBP cancers in elderly Chinese.