[Short-term efficacy and safety of cardiac contractility modulation in patients with heart failure]

Objective: To investigate the short-term efficacy and safety of cardiac contractility modulation (CCM) in patients with heart failure. Methods: This was a cross-sectional study of patients with heart failure who underwent CCM placement at the First Affiliated Hospital of Xinjiang Medical University from February to June 2022. With a follow-up of 3 months, CCM sensation, impedance, percent output, and work time were monitored, and patients were compared with pre-and 3-month postoperative left ventricular ejection fraction (LVEF) values, and 6-minute walk test distance and New York Heart Association (NYHA) cardiac function classification, and the occurrence of complications was recorded. Results: CCM was successfully implanted in all 9 patients. Seven(7/9) of them were male, aged (56±14) years, 3 patients had ischaemic cardiomyopathy and 6 patients had dilated cardiomyopathy. At 3-month postoperative follow-up, threshold was stable, sense was significantly lower at follow-up than before (right ventricle: (16.3±7.0) mV vs. (8.2±1.1) mV, P<0.05; local sense: (15.7±4.9) mV vs. (6.7±2.5) mV, P<0.05), and impedance was significantly lower at follow-up than before (right ventricle (846±179) Ω vs. (470±65) Ω, P<0.05, local sense: (832±246) Ω vs. (464±63) Ω, P<0.05). The CCM output percentage was (86.9±10.7) %, the output amplitude was (6.7±0.4) V, and the daily operating time was (8.6±1.0) h. LVEF was elevated compared to preoperative ((29.4±5.2) % vs. (38.3±4.3) %, P<0.05), the 6-minute walk test was significantly longer than before ((96.8±66.7)m vs. (289.3±121.7)m, P<0.05). No significant increase in the number of NYHA Class Ⅲ-Ⅳ patients was seen (7/9 vs. 2/9, P>0.05). The patient was not re-hospitalised for worsening heart failure symptoms, had no malignant arrhythmic events and experienced significant relief of symptoms such as chest tightness and shortness of breath. No postoperative complications related to pocket hematoma, pocket infection and rupture, electrode detachment, valve function impairment, pericardial effusion, or cardiac perforation were found. Conclusions: CCM has better short-term safety and efficacy in patients with heart failure.

The global landscape of immune-derived lncRNA signature in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a highly heterogeneous cancer. This heterogeneity has an impact on the efficacy of immunotherapy. Long noncoding RNAs (lncRNAs) have been found to play regulatory functions in cancer immunity. However, the global landscape of immune-derived lncRNA signatures has not yet been explored in colorectal cancer.

METHODS

In this study, we applied DESeq2 to identify differentially expressed lncRNAs in colon cancer. Next, we performed an integrative analysis to globally identify immune-driven lncRNA markers in CRC, including immune-associated pathways, tumor immunogenomic features, tumor-infiltrating immune cells, immune checkpoints, microsatellite instability (MSI) and tumor mutation burden (TMB).

RESULTS

We also identified dysregulated lncRNAs, such as LINC01354 and LINC02257, and their clinical relevance in CRC. Our findings revealed that the differentially expressed lncRNAs were closely associated with immune pathways. In addition, we found that RP11-354P11.3 and RP11-545G3.1 had the highest association with the immunogenomic signature. As a result, these signatures could serve as markers to assess immunogenomic activity in CRC. Among the immune cells, resting mast cells and M0 macrophages had the highest association with lncRNAs in CRC. The AC006129.2 gene was significantly associated with several immune checkpoints, for example, programmed cell death protein 1 (PD-1) and B and T lymphocyte attenuator (BTLA). Therefore, the AC006129.2 gene could be targeted to regulate the condition of immune cells or immune checkpoints to enhance the efficacy of immunotherapy in CRC patients. Finally, we identified 15 immune-related lncRNA-generated open reading frames (ORFs) corresponding to 15 cancer immune epitopes.

CONCLUSION

In conclusion, we provided a genome-wide immune-driven lncRNA signature for CRC that might provide new insights into clinical applications and immunotherapy.

Identification and Validation of a Ferroptosis Prognostic Model for Prostate Cancer Patients through Screening the TCGA and scRNA-seq Datasets

PURPOSE/OBJECTIVE(S)

Ferroptosis is currently a common mode of programmed cell death, and the induction of ferroptosis is a new strategy and idea for current tumor therapy. Therefore, the signaling pathways and genes regulated by ferroptosis are significant markers for current malignant tumor therapy. To construct a prognostic model for predicting the survival prognosis of prostate cancer (PCa) based on the molecules and markers related to ferroptosis, we combined with differentially expressed genes (DEGs) in PCa patients, and further analyze the correlation between this risk score and immune cell infiltration. Finally, to validate the expression of risk genes and analyze the expression and localization of risk genes in using the datasets of single cell RNA-sequencing (scRNA-seq).

MATERIALS/METHODS

Firstly, we screened the DEGs in PCa patients by the expression profiles of TCGA database. Meanwhile, we collected the information of ferroptosis regulatory genes from FerrDb, and these two parts were intersected. Then the impact of genes on the survival and prognosis of PCa patients was confirmed and selected by LASSO regression, further screening of molecules and fitting the risk format. And the efficacy of the model was evaluated by ROC curves. The immune cell infiltration of PCa tissues was predicted using TIMER. Last, the scRNA-seq of PCa (GSM5155455, GSM3735993) were carried to reveal the expression of risk molecules in different cell types. Besides, the expression of risk molecules was validated using PCa cell lines.

RESULTS

We found a total of 259 DEGs associated with ferroptosis in PCa tissues. After LASSO regression, we screened DRD5, LINC00336, ACSF2, RRM2, NOX1, GDF15, ALB, MIOX, and NOX4 as variables to establish a prognostic model, and the specific risk scores was calculated following this format: Risk score = (-1.9465)*DRD5+(-1.6806)*LINC00336+(0.3045)*ACSF2+(0.4747)*RRM2+(-0.2815)*NOX1+(-0.1871)* GDF15+(0.1846)*ALB+(0.2676)*MIOX+(0.1648)*NOX4 (lambda.min = 0.0032), with a 10-yr AUC value of 0.751 (95% CI, 0.549-0.953). Furthermore, we discovered the higher the scores, the fewer CD8+ T cells infiltrated as predicting, showing a negative relationship. By testing the gene sets of scRNA-seq forPCa, we discovered that RRM2, GDF15, ALB, and MIOX were mainly expressed in tumor cells, T cells, B cells and neutrophils of PCa tissues, and not in endothelial cells. Finally, we detected differences in protein expression of RRM2, GDF15, and MIOX in PCa cell lines compared to normal prostate cancer epithelium by WB.

CONCLUSION

We constructed a novel prognostic model for PCa based on ferroptosis-related genes, which showed better predictive validity. And we analyzed the cellular expression of risk genes by scRNA-seq, which will be explored future in relation to prostate cancer radiotherapy.

HPK1 Inhibition Enhancing HFRT Anti-Tumor Immune Response

PURPOSE/OBJECTIVE(S)

Radiation therapy, as one of the canonical treatments for classic tumors, results in impressive clinical responses. Stereotactic body radiotherapy (SBRT) has been increasingly used as one main therapy in early-stage non-small-cell lung cancer (NSCLC). SBRT affords good local tumor control, however, recurrence and metastasis are still the main causes of treatment failure. With the continuous deepening of the relationship between radiotherapy (RT) and immunity, reversing RT induced immunosuppression is considered to be a promising strategy to improve radiotherapy efficacy. Hematopoietic progenitor kinase 1 (HPK1) is mainly expressed in immune cells while rarely expressed in tumor cells. It has been proven to play a negative regulatory role in T cell receptor (TCR) signal. Therefore, we hypothesized that the combination of HPK1 inhibitor with SBRT would boost local and systemic anti-tumor immune responses by potentiating the anti-tumor effects of SBRT.

MATERIALS/METHODS

Using Digital Spatial Profiler (DSP), we analyzed HPK1 expression in the tumor specimens of 39 NSCLC patients treated with SBRT. By establishing mice subcutaneous tumor models, we assessed the combination of a HPK1 inhibitor and local hyper-fractionated radiotherapy (HFRT) on local and systemic tumor control and mouse survival. Using Single-cell RNA sequencing, Flow cytometry and pharmacological treatment, we analyzed and verified Tumor-infiltrating lymphocytes (TILs), and excavated the specific mechanism of the HPK1 inhibitor enhancing HFRT -induced anti -tumor immune response.

RESULTS

In the tumor specimens of NSCLC patients treated with SBRT, we found that high expression HPK1 in TILs predicted poor progression-free survival (PFS). Among the C57BL/6 mice model, HFRT combined with a HPK1 inhibitor promoted local response, and improved the survival rate of mice, showing better anti-tumor curative effects. We further showed that HFRT promoted CD8+ T cell cytotoxic activity, and also aggravated CD8+ T cell exhaustion. After the intervention of HPK1 small molecular inhibitors, the proportion of exhaustion CD8+T cells was significantly reduced, while CD8+T cell cytotoxic activity was further enhanced in the later period. Single-cell RNA sequencing and pharmacological inhibition of HPK1 revealed that HPK1 mediated the exhaustion of CD8+T cells by regulating RGS16. In abscopal effects preclinical models, BGB-15025 induced obvious abscopal effect.

CONCLUSION

Thus, we demonstrate that HPK1 mediates HFRT-induced CD8+T cell exhaustion by regulating RGS16, and HPK1 is an attractive drug target for enhancing local and systemic radiotherapy.

Radiotherapy Resistance in Prostate Cancer Cells: AKR1C3 Inhibition of Ubiquitinated Degradation of Nrf2 through Interaction with KEAP1

PURPOSE/OBJECTIVE(S)

Radiotherapy is the most fundamental treatment for prostate cancer (PCa), and although radiotherapy for overall PCa patients is effective, poor prognosis and resistance to multiple treatments regimes in some highly malignant PCa, such as those with high Gleason Scores (GS) (≥9), are important bottlenecks limiting the improvement of treatment outcomes for clinical. AKR1C3 is a key PCa resistance gene that our team identified previously, but the induction of the specific mechanism of radiotherapy resistance has not been fully revealed and understand.

MATERIALS/METHODS

To analyze the correlation between its expression level and clinical radiotherapy, we used the gene expression profiles data of PCa patients in TCGA database. We generated a stepwise increase of radiotherapy dose to established PCa radiotherapy resistant cell lines and detect the AKR1C3 expression level. In addition, to explore the molecular mechanism of AKR1C3 induced prostate cancer radiation tolerance through functional enrichment analysis. Then, to treat cells with cycloheximide and the protein stability of the Nrf2 was detected. Last, the protein ubiquitination level was assayed by co-immunoprecipitation (co-IP) after treatment with MG132. Finally, protein-protein interactions were identified using co-IP to mine possible binding molecules.

RESULTS

By analyzing the expression profiles data of PCa patients in the TCGA database, we found that in the population of PCa patients treated with radiotherapy, all patients with high AKR1C3 expression died after radiotherapy, suggesting that high AKR1C3 expression may be a biomarker of resistance to radiation. Accordingly, AKR1C3 expression levels showed a positive correlation with GS score, which may be a symbol for patients with highly malignant PCa. A PCa radiotherapy resistant cell line was constructed by a stepwise increase of ionizing radiation (IR) dose, and the total IR dose of radiotherapy was 84Gy, which reached the dose of radical radiotherapy for prostate cancer. The expression of AKR1C3 was further detected by RT-qPCR and WB, and it was found that the expression of AKR1C3 was significantly up-regulated in the resistant cell line, accompanied by milder DNA damage. What's more, by GSEA functional enrichment analysis, we discovered that AKR1C3 overexpression might be related with intracellular oxidative stress damage. After CHX treatment, the protein stability of Nrf2 was significantly enhanced in AKR1C3 overexpression groups than control groups. And the administration of MG132 showed the same results, indicating that the ubiquitinated degradation of Nrf2 was inhibited in AKR1C3 overexpression groups. Further by co-IP, we found that Nrf2 was less ubiquitinated in the cytoplasm after AKR1C3 overexpression, and AKR1C3 could bind Keap1.

CONCLUSION

In sum, we found that AKR1C3 can bind with Keap1 leading to reduced ubiquitination level of Nrf2, causing upregulation of Nrf2 expression and providing new insights into PCa radiotherapy resistance.

The Baseline Serum Lipid Levels and Outcomes of NSCLC Patients Receiving Immunotherapy Combined or Non-Combined with Radiotherapy: A Single Center Retrospective Study

PURPOSE/OBJECTIVE(S)

In recent years, many studies have shown that lipids and lipid-like substances are key regulatory factors in tumor development and play an important role in immune regulation. However, it remains unclear whether serum lipids influence the outcome of immunotherapy. Therefore, determining the serum lipid levels of the immune treatment-beneficiary population may be valuable. The aim of this study is to evaluate the prognostic value of baseline serum lipid levels in non-small cell lung cancer (NSCLC) patients receiving immunotherapy.

MATERIALS/METHODS

We retrospectively included 294 patients with stage III-IV NSCLC who received immunotherapy continuously from December 2018 to November 2021 at our hospital, collecting their pre-treatment lipid levels, such as total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). Of these, 160 receiving immunotherapy without combined radiotherapy (ICIs-nRT) and 134 combined with radiotherapy (iRT). The endpoint was the correlation between pre-treatment serum lipid levels and overall survival (OS), as well as progression-free survival (PFS). The X-tile tool was used to determine the optimal cut-off value of the indicators. The Kaplan-Meier survival curves were used to calculate OS and PFS and log rank tests were used for comparison. And the Cox proportional hazard model were used for univariate and multivariate analysis.

RESULTS

In all 294 patients, low TG, low TC, and low HDL-C predicted poor OS (P<0.001) and poor PFS (P<0.05). Low LDL-C was associated with poor OS (P = 0.0001). Among 160 patients receiving ICIs-nRT and 134 iRT patients, low levels of TG (P = 0.0134, 0.0024), TC (P = 0.0003, 0.0023), HDL-C (P = 0.0004, 0.0043), and LDL-C (P = 0.0003, 0.0419) were associated with worse OS compared to high levels of them. In the ICIs-nRT patients, low HDL-C predicted poor PFS (P = 0.0011). In 134 iRT patients, low levels of TG (P = 0.0017), TC (P = 0.0028), and LDL-C (P = 0.0330) were poor prognostic factors for PFS. In the univariate and multivariate analysis with OS in all patients, TG and HDL-C were independent risk factors, while TG was an independent risk factor in the analysis with PFS. In ICIs-nRT patients, HDL-C was an independent prognostic factor for patients' OS and PFS. In iRT patients, both TG and HDL-C were prognostic risk factors for OS.

CONCLUSION

These data confirm that higher serum lipid levels are associated with better outcomes in patients with NSCLC undergoing immunotherapy. Serum lipids may identify tumors that are more likely to respond to immunotherapy. Radiation therapy may affect lipid metabolism within the body to enhance the efficacy of immunotherapy.

A Dosimetric Study Indicates the Spinal Cord Irradiation Contributes to Acute Hematologic Toxicities in Non-Small Cell Lung Cancer Patients Receiving Radiotherapy Combined with Immunotherapy

PURPOSE/OBJECTIVE(S)

To assess the radiation therapy (RT) dose to radiation-associated hematologic toxicities (HTs) in patients with non-small cell lung cancer (NSCLC) after RT combined with immunotherapy.

MATERIALS/METHODS

Cases of NSCLC treated with RT combined with immunotherapy at Shandong Cancer Hospital in China were identified. The mean dose and the volume of the spinal cord receiving at least 5 to 40 Gy (V5-V40) were retrospectively recorded. Logistic regression was used to estimate associations between grade ≥3 HT (HT3+) and dosimetric/clinical parameters. Receiver operating characteristic analysis was used to determine dosimetric cut-points.

RESULTS

Ninety-nine patients were analyzed. The majority were male (n = 78, 78.8%) and received chemotherapy (n = 83, 83.9%). All patients received either anti-PD-1 immune checkpoint (n = 89, 89.9%) or anti-PD-L1 immune checkpoint (n = 10, 10.1%) therapy. The rate of HT3+ was 24.2% (n = 24). Spinal cord mean dose, V5 to V40 and BMI parameters associated with HT3+ were included in the multivariate analysis. On multivariate analysis, increasing mean spinal cord dose (per Gy) was associated with higher odds of developing HT3+ (odds ratio 1.053, 95% confidence interval 1.002-1.105, P = .041), as were increasing spinal cord V5 to V20 (As show in the Table below). The optimal cut-points identified were V5 = 52.5%, V10 = 47.5%, V20 = 39.4%, and mean dose = 23.3 Gy. Patients with values above these cut-points had an approximately 2-fold increased risk of HT3+.

CONCLUSION

We found that mean spinal cord dose and low-dose parameters (V5-V20) were associated with HT3+ in NSCLC patients after RT and immunotherapy. The mean dose of the spinal cord should be kept lower than 23.3 Gy for these patients. These data suggested that efforts to spare doses to the spinal cord might reduce rates of severe HT.

Molecular cloning, expression analysis and functional characterization of chicken cytochrome P450 27A1: A novel mitochondrial vitamin D3 25-hydroxylase

Vitamin D₃ is hydroxylated by cytochrome P450 (CYP) before exerting biological effects. The chicken CYP involved in vitamin D₃ 25-hydroxylation has yet to be cloned, and little is known about its functional characteristics, tissue distribution, and cellular expression. We identified a novel, full-length CYP27A1 gene cloned from chicken hepatocyte cDNA that encodes a putative protein of 518 amino acids. Swiss modeling revealed that chicken CYP27A1 has a classic open-fold form. Multisequence homology alignment determined that CYP27A1 contains conserved motifs for substrate recognition and binding. Quantitative real-time PCR analysis in 2-mo-old Partridge Shank broilers demonstrated that CYP27A1 mRNA levels were highest in the liver, followed by the thigh muscles, the breast muscles, and kidneys. The transcripts of CYP27A1 in breast muscles were significantly higher in males than in females. A subcellular localization analysis demonstrated that CYP27A1 was mainly expressed in the mitochondria. In vitro enzyme assays suggested that recombinant CYP27A1 hydroxylates vitamin D₃ at the C-25 position to form 25-hydroxyvitamin D₃ (25(OH)D₃). The K_m and V_max values for CYP27A1-dependent vitamin D₃ 25-hydroxylation were estimated to be 4.929 μM and 0.389 mol min^-1 mg^-1 protein, respectively. In summary, these results suggest that CYP27A1 encodes a mitochondrial CYP that plays an important physiologic role in the 25-hydroxylation of vitamin D₃ in chickens, providing novel insights into vitamin D₃ metabolism in this species.

EdeepSADPr: an extensive deep-learning architecture for prediction of the in situ crosstalks of serine phosphorylation and ADP-ribosylation

The in situ post-translational modification (PTM) crosstalk refers to the interactions between different types of PTMs that occur on the same residue site of a protein. The crosstalk sites generally have different characteristics from those with the single PTM type. Studies targeting the latter's features have been widely conducted, while studies on the former's characteristics are rare. For example, the characteristics of serine phosphorylation (pS) and serine ADP-ribosylation (SADPr) have been investigated, whereas those of their in situ crosstalks (pSADPr) are unknown. In this study, we collected 3,250 human pSADPr, 7,520 SADPr, 151,227 pS and 80,096 unmodified serine sites and explored the features of the pSADPr sites. We found that the characteristics of pSADPr sites are more similar to those of SADPr compared to pS or unmodified serine sites. Moreover, the crosstalk sites are likely to be phosphorylated by some kinase families (e.g., AGC, CAMK, STE and TKL) rather than others (e.g., CK1 and CMGC). Additionally, we constructed three classifiers to predict pSADPr sites from the pS dataset, the SADPr dataset and the protein sequences separately. We built and evaluated five deep-learning classifiers in ten-fold cross-validation and independent test datasets. We also used the classifiers as base classifiers to develop a few stacking-based ensemble classifiers to improve performance. The best classifiers had the AUC values of 0.700, 0.914 and 0.954 for recognizing pSADPr sites from the SADPr, pS and unmodified serine sites, respectively. The lowest prediction accuracy was achieved by separating pSADPr and SADPr sites, which is consistent with the observation that pSADPr's characteristics are more similar to those of SADPr than the rest. Finally, we developed an online tool for extensively predicting human pSADPr sites based on the CNN_OH classifier, dubbed EdeepSADPr. It is freely available through http://edeepsadpr.bioinfogo.org/. We expect our investigation will promote a comprehensive understanding of crosstalks.

Lactate regulators contribute to tumor microenvironment and predict prognosis in lung adenocarcinoma

Background

Lactic acid, as a product of glycolysis, increases tumor cell migration and the invasion of tumor cells in the tumor microenvironment. Besides this, lactic acid promotes the expression of programmed death-1 expression (PD-1) in regulatory T cells, which could cause the failure of PD-1 blockade therapy. However, the implications of lactic acid in the tumor microenvironment of lung adenocarcinoma (LUAD) remain largely unclear.

Methods

We performed unsupervised consensus clustering to identify lactic-associated subtypes using expression profile of lactate regulators in LUAD. Differentially expressed genes (DEGs) associated with lactic-associated subtypes was used to construct lactate signature (LaSig) using LASSO regression algorithm. Immune infiltration analysis was conducted by ESTIMATER and drug sensitivity was estimated by R package called "pRRophetic". The difference between two groups was calculated using Wilcox rank sum test and correlation analysis was calculated using Pearson correlation coefficient.

Results

In this study, we evaluated DNA methylation and the mutation frequency of lactate regulators and found lactate regulators showed low mutation frequency in the TCGA-LUAD cohort, except TP53. At the RNA level, the expression level of lactate regulators was significantly associated with the immune cell component. In particular, expression of LDHA was positively correlated with CD4 T cell, CD8 T cell, M1 macrophages, and the enrichment score of multiple immune pathways. Two clusters were defined using the gene expression level of lactate regulators, and LDHA was significantly upregulated in cluster 1 with poor overall survival. A lactate signature (LaSig) had a robust performance in predicting the survival rate and immunotherapy response of LUAD patients. Moreover, patients in the high LaSig group may be more likely to benefit from these drugs (Cisplatin, Erlotinib, Gemcitabine, and Vinblastine) than those in the low LaSig group.

Conclusion

In summary, our study explores the role of lactate regulators in guiding the clinical treatment of lung adenocarcinoma and provides additional help to supplement traditional molecular subtypes.

AgingBank: a manually curated knowledgebase and high-throughput analysis platform that provides experimentally supported multi-omics data relevant to aging in multiple species

Discovering the biological basis of aging is one of the greatest remaining challenges for biomedical field. Work on the biology of aging has discovered a range of interventions and pathways that control aging rate. Thus, we developed AgingBank (http://bio-bigdata.hrbmu.edu.cn/AgingBank) which was a manually curated comprehensive database and high-throughput analysis platform that provided experimentally supported multi-omics data relevant to aging in multiple species. AgingBank contained 3771 experimentally verified aging-related multi-omics entries from studies across more than 50 model organisms, including human, mice, worms, flies and yeast. The records included genome (single nucleotide polymorphism, copy number variation and somatic mutation), transcriptome [mRNA, long non-coding RNA (lncRNA), microRNA (miRNA) and circular RNA (circRNA)], epigenome (DNA methylation and histone modification), other modification and regulation elements (transcription factor, enhancer, promoter, gene silence, alternative splicing and RNA editing). In addition, AgingBank was also an online computational analysis platform containing five useful tools (Aging Landscape, Differential Expression Analyzer, Data Heat Mapper, Co-Expression Network and Functional Annotation Analyzer), nearly 112 high-throughput experiments of genes, miRNAs, lncRNAs, circRNAs and methylation sites related with aging. Cancer & Aging module was developed to explore the relationships between aging and cancer. Submit & Analysis module allows users upload and analyze their experiments data. AginBank is a valuable resource for elucidating aging-related biomarkers and relationships with other diseases.

CysModDB: a comprehensive platform with the integration of manually curated resources and analysis tools for cysteine posttranslational modifications

The unique chemical reactivity of cysteine residues results in various posttranslational modifications (PTMs), which are implicated in regulating a range of fundamental biological processes. With the advent of chemical proteomics technology, thousands of cysteine PTM (CysPTM) sites have been identified from multiple species. A few CysPTM-based databases have been developed, but they mainly focus on data collection rather than various annotations and analytical integration. Here, we present a platform-dubbed CysModDB, integrated with the comprehensive CysPTM resources and analysis tools. CysModDB contains five parts: (1) 70 536 experimentally verified CysPTM sites with annotations of sample origin and enrichment techniques, (2) 21 654 modified proteins annotated with functional regions and structure information, (3) cross-references to external databases such as the protein-protein interactions database, (4) online computational tools for predicting CysPTM sites and (5) integrated analysis tools such as gene enrichment and investigation of sequence features. These parts are integrated using a customized graphic browser and a Basket. The browser uses graphs to represent the distribution of modified sites with different CysPTM types on protein sequences and mapping these sites to the protein structures and functional regions, which assists in exploring cross-talks between the modified sites and their potential effect on protein functions. The Basket connects proteins and CysPTM sites to the analysis tools. In summary, CysModDB is an integrated platform to facilitate the CysPTM research, freely accessible via https://cysmoddb.bioinfogo.org/.

Identification and exploration of pharmacological pyroptosis-related biomarkers of ulcerative colitis

Ulcerative colitis (UC) is a chronic inflammatory bowel disease (IBD). Its etiology is unclear. Much evidence suggests that the death of abnormal intestinal epithelial cells (IECs) leads to intestinal barrier disruption, and the subsequent inflammatory response plays a vital role in UC. Pyroptosis is a form of programmed inflammatory cell death, and the role of pyroptosis in UC etiology remains to be explored. This study identified 10 hub genes in pyroptosis by gene expression profiles obtained from the GSE87466 dataset. Meanwhile, the biomarkers were screened based on gene significance (GS) and module membership (MM) through the Weighted Gene Co-Expression Network Analysis (WGCNA). The following analysis indicated that hub genes were closely associated with the UC progression and therapeutic drug response. The single-cell RNA (scRNA) sequencing data from UC patients within the GSE162335 dataset indicated that macrophages were most related to pyroptosis. Finally, the expression of hub genes and response to the therapeutic drug [5-aminosalicylic acid (5-ASA)] were verified in dextran sulfate sodium (DSS)-induced colitis mice. Our study identified IL1B as the critical pyroptosis-related biomarker in UC. The crosstalk between macrophage pyroptosis and IEC pyroptosis may play an essential role in UC, deserving further exploration.

[The Physician of the Shao Xing School in the Late Qing Dynasty -- Zhao Qingchu]

Zhao Qingchu, a Confucian physician from the Kuaiji area at the end of the Qing Dynasty, learned from famous physicians of the Shao Xing School on exogenous febirle disease (Shang Han) and the You's of the Shi Cai School, drawing from the knowledge of the both medical schools. He quickly became popular for being a physician after giving up his research of Confucianism. He had a wide physician-patient network because of his art of healing as many politicians and celebrities such like Shao Youlian, Zeng Guoquan, Ren Daorong, Xu Yingkui and Ren Fuchang,were his patients. He was taken as a typical example of being good at the medical communication among doctors and doctors-patients in the Yangtze River area in the late Qing Dynasty. For instance, he once had a variety of medical communication with famous physicians, such as Wang Yuezhen, Ma Peizhi, He Lianchen, Zhang Wanxiang, Ling Jialiu and Zhou Bodu. He investigated medical theories in terms of exogenous febirle disease (Shang Han) and integrated his thinking with various medical schools, even attempting to involving western medicine. He was also skilled in teaching his medical thinking to his disciples, such as Zhao Shuan, Yang Zhian, Lu Dongchuan and He Jiren. Zhao Qingchu compiled his medical understanding based on his practice and experiences throughout his life and published this knowledge in Cun Cun Zhai Yi Hua Gao. He had it published many times, leading to a profound influence in Shaoxing and the Jiangnan area at that time.

Prioritizing cancer lncRNA modulators via integrated lncRNA-mRNA network and somatic mutation data

Abstract:

Background: Long noncoding RNAs (LncRNAs) represent a large category of functional RNA molecules that play a significant role in human cancers. lncRNAs can be genes modulators to affect the biological process of multiple cancers.

Methods:

Here, we developed a computational framework that uses lncRNA-mRNA network and mutations in individual genes of 9 cancers from TCGA to prioritize cancer lncRNA modulators. Our method screened risky cancer lncRNA regulators based on integrated multiple lncRNA functional networks and 3 calculation methods in network.

Results:

Validation analyses revealed that our method was more effective than prioritization based on a single lncRNA network. This method showed high predictive performance and the highest ROC score was 0.836 in breast cancer. It’s worth noting that we found that 5 lncRNAs scores were abnormally high and these lncRNAs appeared in 9 cancers. By consulting the literatures, these 5 lncRNAs were experimentally supported lncRNAs. Analyses of prioritizing lncRNAs reveal that these lncRNAs are enriched in various cancer-related biological processes and pathways.

Conclusions:

Together, these results demonstrated the ability of this method identifying candidate lncRNA molecules and improved insights into the pathogenesis of cancer.

Identifying and characterizing lincRNA genomic clusters reveals its cooperative functions in human cancer

Background

Emerging evidence has revealed that some long intergenic non-coding RNAs (lincRNAs) are likely to form clusters on the same chromosome, and lincRNA genomic clusters might play critical roles in the pathophysiological mechanism. However, the comprehensive investigation of lincRNA clustering is rarely studied, particularly the characterization of their functional significance across different cancer types.

Methods

In this study, we firstly constructed a computational method basing a sliding window approach for systematically identifying lincRNA genomic clusters. We then dissected these lincRNA genomic clusters to identify common characteristics in cooperative expression, conservation among divergent species, targeted miRNAs, and CNV frequency. Next, we performed comprehensive analyses in differentially-expressed patterns and overall survival outcomes for patients from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) across multiple cancer types. Finally, we explored the underlying mechanisms of lincRNA genomic clusters by functional enrichment analysis, pathway analysis, and drug-target interaction.

Results

We identified lincRNA genomic clusters according to the algorithm. Clustering lincRNAs tended to be co-expressed, highly conserved, targeted by more miRNAs, and with similar deletion and duplication frequency, suggesting that lincRNA genomic clusters may exert their effects by acting in combination. We further systematically explored conserved and cancer-specific lincRNA genomic clusters, indicating they were involved in some important mechanisms of disease occurrence through diverse approaches. Furthermore, lincRNA genomic clusters can serve as biomarkers with potential clinical significance and involve in specific pathological processes in the development of cancer. Moreover, a lincRNA genomic cluster named Cluster127 in DLK1-DIO3 imprinted locus was discovered, which contained MEG3, MEG8, MEG9, MIR381HG, LINC02285, AL132709.5, and AL132709.1. Further analysis indicated that Cluster127 may have the potential for predicting prognosis in cancer and could play their roles by participating in the regulation of PI3K-AKT signaling pathway.

Conclusions

Clarification of the lincRNA genomic clusters specific roles in human cancers could be beneficial for understanding the molecular pathogenesis of different cancer types.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03179-5.

Epigenome signature as an immunophenotype indicator prompts durable clinical immunotherapy benefits in lung adenocarcinoma

Intertumoral immune heterogeneity is a critical reason for distinct clinical benefits of immunotherapy in lung adenocarcinoma (LUAD). Tumor immunophenotype (immune 'Hot' or 'Cold') suggests immunological individual differences and potential clinical treatment guidelines. However, employing epigenome signatures to determine tumor immunophenotypes and responsive treatment is not well understood. To delineate the tumor immunophenotype and immune heterogeneity, we first distinguished the immune 'Hot' and 'Cold' tumors of LUAD based on five immune expression signatures. In terms of clinical presentation, the immune 'Hot' tumors usually had higher immunoactivity, lower disease stages and better survival outcomes than 'Cold' tumors. At the epigenome levels, we observed that distinct DNA methylation patterns between immunophenotypes were closely associated with LUAD development. Hence, we identified a set of five CpG sites as the immunophenotype-related methylation signature (iPMS) for tumor immunophenotyping and further confirmed its efficiency based on a machine learning framework. Furthermore, we found iPMS and immunophenotype-related immune checkpoints (IPCPs) could contribute to the risk of tumor progression, implying IPCP has the potential to be a novel immunotherapy blockade target. After further parsing of the role of iPMS-predicted immunophenotypes, we found immune 'Hot' was a protective factor leading to better survival outcomes when patients received the anti-PD-1/PD-L1 immunotherapy. And iPMS was also a well-performed signature (AUC = 0.752) for predicting the durable/nondurable clinical benefits. In summary, our study explored the role of epigenome signature in clinical tumor immunophenotyping. Utilizing iPMS to characterize tumor immunophenotypes will facilitate developing personalized epigenetic anticancer approaches.

Comprehensive characterization genetic regulation and chromatin landscape of enhancer-associated long non-coding RNAs and their implication in human cancer

Long non-coding RNAs (lncRNAs) that emanate from enhancer regions (defined as enhancer-associated lncRNAs, or elncRNAs) are emerging as critical regulators in disease progression. However, their biological characteristics and clinical relevance have not been fully portrayed. Here, based on the traditional expression quantitative loci (eQTL) and our optimized residual eQTL method, we comprehensively described the genetic effect on elncRNA expression in more than 300 lymphoblastoid cell lines. Meanwhile, a chromatin atlas of elncRNAs relative to the genetic regulation state was depicted. By applying the maximum likelihood estimate method, we successfully identified causal elncRNAs for protein-coding gene expression reprogramming and showed their associated single nucleotide polymorphisms (SNPs) favor binding of transcription factors. Further epigenome analysis revealed two immune-associated elncRNAs AL662844.4 and LINC01215 possess high levels of H3K27ac and H3K4me1 in human cancer. Besides, pan-cancer analysis of 3D genome, transcriptome, and regulatome data showed they potentially regulate tumor-immune cell interaction through affecting MHC class I genes and CD47, respectively. Moreover, our study showed there exist associations between elncRNA and patient survival. Finally, we made a user-friendly web interface available for exploring the regulatory relationship of SNP-elncRNA-protein-coding gene triplets (http://bio-bigdata.hrbmu.edu.cn/elncVarReg). Our study provides critical mechanistic insights for elncRNA function and illustrates their implications in human cancer.

DNA methylation dynamics of long noncoding RNA during human fetal development

Aim: To determine whether the promoters of long noncoding RNAs (lncRNAs) undergo dynamic changes in DNA methylation during fetal development. Methods: ANOVA and the tissue specificity index were used to identify and validate tissue-specific methylation sites. Age-associated DNA methylation signatures were identified by applying the elastic net method. Results: The lncRNA methylome landscape was characterized in four types of fetal tissue and at three gestational time points, and specific characteristics relative to the tissue of origin and developmental age were identified. Higher levels of lncRNA methylation might be involved in tissue differentiation. LncRNAs harboring age-associated methylation signatures may participate in the fetal developmental process. Conclusion: This study provides novel insights into the role of lncRNA methylomes in fetal tissue specification and development.

Development of a 19-plex short tandem repeat typing system for individual identification and parentage testing of horses (Equus caballus)

Individual identification of horses for pedigree verification and registration is important for the sustainable development of the horse industry. Horse individual identification and parentage tests commonly use the 17 short tandem repeats (STRs) recommended by the International Society for Animal Genetics (ISAG) and the locus LEX33. While many multiplex STR typing systems have been established for the horse, a sex determining marker is usually absent, and none of them can simultaneously detect all 17 ISAG recommended loci and the locus LEX33. Here, we present a 19-plex STR typing system that contains the 17 ISAG recommend loci, the locus LEX33 and amelogenin as sex determining loci. The results of our sensitivity, species specificity, stutter analysis and population data analysis, indicate that this system is a specific, sensitive, and robust tool for the identification of individuals, parentage testing and genetic research in the horse.

MeImmS: Predict Clinical Benefit of Anti-PD-1/PD-L1 Treatments Based on DNA Methylation in Non-small Cell Lung Cancer

Immunotherapy has become an effective therapy for cancer treatment. However, the development of biomarkers to predict immunotherapy response still remains a challenge. We have developed the DNA Methylation Immune Score, named “MeImmS,” which can predict clinical benefits of non-small cell lung cancer (NSCLC) patients based on DNA methylation of 8 CpG sites. The 8 CpG sites regulate the expression of immune-related genes and MeImmS was related to immune-associated pathways, exhausted T cell markers and immune cells. Copy-number loss in 1p36.33 may affect the response of cancer patients to immunotherapy. In addition, SAA1, CXCL10, CCR5, CCL19, CXCL11, CXCL13, and CCL5 were found to be key immune regulatory genes in immunotherapy. Together, MeImmS discovered the heterogeneous of NSCLC patients and guided the immunotherapy of cancer patients in the future.

LincSNP 3.0: an updated database for linking functional variants to human long non-coding RNAs, circular RNAs and their regulatory elements

We describe an updated comprehensive database, LincSNP 3.0 (http://bioinfo.hrbmu.edu.cn/LincSNP), which aims to document and annotate disease or phenotype-associated variants in human long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) or their regulatory elements. LincSNP 3.0 has updated with several novel features, including (i) more types of variants including single nucleotide polymorphisms (SNPs), linkage disequilibrium SNPs (LD SNPs), somatic mutations and RNA editing sites have been expanded; (ii) more regulatory elements including transcription factor binding sites (TFBSs), enhancers, DNase I hypersensitive sites (DHSs), topologically associated domains (TADs), footprintss, methylations and open chromatin regions have been added; (iii) the associations among circRNAs, regulatory elements and variants have been identified; (iv) more experimentally supported variant-lncRNA/circRNA-disease/phenotype associations have been manually collected; (v) the sources of lncRNAs, circRNAs, SNPs, somatic mutations and RNA editing sites have been updated. Moreover, four flexible online tools including Genome Browser, Variant Mapper, Circos Plotter and Functional Annotation have been developed to retrieve, visualize and analyze the data. Collectively, LincSNP 3.0 provides associations among functional variants, regulatory elements, lncRNAs and circRNAs in diseases. It will serve as an important and continually updated resource for investigating functions and mechanisms of lncRNAs and circRNAs in diseases.

Lnc2Cancer 3.0: an updated resource for experimentally supported lncRNA/circRNA cancer associations and web tools based on RNA-seq and scRNA-seq data

An updated Lnc2Cancer 3.0 (http://www.bio-bigdata.net/lnc2cancer or http://bio-bigdata.hrbmu.edu.cn/lnc2cancer) database, which includes comprehensive data on experimentally supported long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) associated with human cancers. In addition, web tools for analyzing lncRNA expression by high-throughput RNA sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) are described. Lnc2Cancer 3.0 was updated with several new features, including (i) Increased cancer-associated lncRNA entries over the previous version. The current release includes 9254 lncRNA-cancer associations, with 2659 lncRNAs and 216 cancer subtypes. (ii) Newly adding 1049 experimentally supported circRNA-cancer associations, with 743 circRNAs and 70 cancer subtypes. (iii) Experimentally supported regulatory mechanisms of cancer-related lncRNAs and circRNAs, involving microRNAs, transcription factors (TF), genetic variants, methylation and enhancers were included. (iv) Appending experimentally supported biological functions of cancer-related lncRNAs and circRNAs including cell growth, apoptosis, autophagy, epithelial mesenchymal transformation (EMT), immunity and coding ability. (v) Experimentally supported clinical relevance of cancer-related lncRNAs and circRNAs in metastasis, recurrence, circulation, drug resistance, and prognosis was included. Additionally, two flexible online tools, including RNA-seq and scRNA-seq web tools, were developed to enable fast and customizable analysis and visualization of lncRNAs in cancers. Lnc2Cancer 3.0 is a valuable resource for elucidating the associations between lncRNA, circRNA and cancer.

LnCeCell: a comprehensive database of predicted lncRNA-associated ceRNA networks at single-cell resolution

Within the tumour microenvironment, cells exhibit different behaviours driven by fine-tuning of gene regulation. Identification of cellular-specific gene regulatory networks will deepen the understanding of disease pathology at single-cell resolution and contribute to the development of precision medicine. Here, we describe a database, LnCeCell (http://www.bio-bigdata.net/LnCeCell/ or http://bio-bigdata.hrbmu.edu.cn/LnCeCell/), which aims to document cellular-specific long non-coding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) networks for personalised characterisation of diseases based on the ‘One Cell, One World’ theory. LnCeCell is curated with cellular-specific ceRNA regulations from >94 000 cells across 25 types of cancers and provides >9000 experimentally supported lncRNA biomarkers, associated with tumour metastasis, recurrence, prognosis, circulation, drug resistance, etc. For each cell, LnCeCell illustrates a global map of ceRNA sub-cellular locations, which have been manually curated from the literature and related data sources, and portrays a functional state atlas for a single cancer cell. LnCeCell also provides several flexible tools to infer ceRNA functions based on a specific cellular background. LnCeCell serves as an important resource for investigating the gene regulatory networks within a single cell and can help researchers understand the regulatory mechanisms underlying complex microbial ecosystems and individual phenotypes.

Lnc2Cancer v2.0: updated database of experimentally supported long non-coding RNAs in human cancers

Lnc2Cancer 2.0 (http://www.bio-bigdata.net/lnc2cancer) is an updated database that provides comprehensive experimentally supported associations between lncRNAs and human cancers. In Lnc2Cancer 2.0, we have updated the database with more data and several new features, including (i) exceeding a 4-fold increase over the previous version, recruiting 4989 lncRNA-cancer associations between 1614 lncRNAs and 165 cancer subtypes. (ii) newly adding about 800 experimentally supported circulating, drug-resistant and prognostic-related lncRNAs in various cancers. (iii) appending the regulatory mechanism of lncRNA in cancer, including microRNA (miRNA), transcription factor (TF), variant and methylation regulation. (iv) increasing more than 70 high-throughput experiments (microarray and next-generation sequencing) of lncRNAs in cancers. (v) Scoring the associations between lncRNA and cancer to evaluate the correlations. (vi) updating the annotation information of lncRNAs (version 28) and containing more detailed descriptions for lncRNAs and cancers. Moreover, a newly designed, user-friendly interface was also developed to provide a convenient platform for users. In particular, the functions of browsing data by cancer primary organ, biomarker type and regulatory mechanism, advanced search following several features and filtering the data by LncRNA-Cancer score were enhanced. Lnc2Cancer 2.0 will be a useful resource platform for further understanding the associations between lncRNA and human cancer.

LnCeVar: a comprehensive database of genomic variations that disturb ceRNA network regulation

LnCeVar (http://www.bio-bigdata.net/LnCeVar/) is a comprehensive database that aims to provide genomic variations that disturb lncRNA-associated competing endogenous RNA (ceRNA) network regulation curated from the published literature and high-throughput data sets. LnCeVar curated 119 501 variation–ceRNA events from thousands of samples and cell lines, including: (i) more than 2000 experimentally supported circulating, drug-resistant and prognosis-related lncRNA biomarkers; (ii) 11 418 somatic mutation–ceRNA events from TCGA and COSMIC; (iii) 112 674 CNV–ceRNA events from TCGA; (iv) 67 066 SNP–ceRNA events from the 1000 Genomes Project. LnCeVar provides a user-friendly searching and browsing interface. In addition, as an important supplement of the database, several flexible tools have been developed to aid retrieval and analysis of the data. The LnCeVar–BLAST interface is a convenient way for users to search ceRNAs by interesting sequences. LnCeVar–Function is a tool for performing functional enrichment analysis. LnCeVar–Hallmark identifies dysregulated cancer hallmarks of variation–ceRNA events. LnCeVar–Survival performs COX regression analyses and produces survival curves for variation–ceRNA events. LnCeVar–Network identifies and creates a visualization of dysregulated variation–ceRNA networks. Collectively, LnCeVar will serve as an important resource for investigating the functions and mechanisms of personalized genomic variations that disturb ceRNA network regulation in human diseases.

CancerClock: A DNA Methylation Age Predictor to Identify and Characterize Aging Clock in Pan-Cancer

Many biological indicators related to chronological age have been proposed. Recent studies found that epigenetic clock or DNA methylation age is highly correlated with chronological age. In particular, a significant difference between DNA methylation age (m-age) and chronological age was observed in cancers. However, the prediction and characterization of m-age in pan-cancer remains an explored area. In this study, 1,631 age-related methylation sites in normal tissues were discovered and analyzed. A comprehensive computational model named CancerClock was constructed to predict the m-age for normal samples based on methylation levels of the extracted methylation sites. LASSO linear regression model was used to screen and train the CancerClock model in normal tissues. The accuracy of CancerClock has proved to be 81%, and the correlation value between chronological age and m-age was 0.939 (P < 0.01). Next, CancerClock was used to evaluate the difference between m-age and chronological age for 33 cancer types from TCGA. There were significant differences between predicted m-age and chronological age in large number of cancer samples. These cancer samples were defined as “age-related cancer samples” and they have some differential methylation sites. The differences between predicted m-age and chronological age may contribute to cancer development. Some of these differential methylation sites were associated with cancer survival. CancerClock provided assistance in estimating the m-age in normal and cancer samples. The changes between m-age and chronological age may improve the diagnosis and prognosis of cancers.

A novel 13-plex STR typing system for individual identification and parentage testing of donkeys (Equus asinus)

BACKGROUND

Previous studies investigating donkey parentage and genetic diversity used horse-specific multiplex systems. However, several mis-allele and null-allele issues were found with some of the horse primers when used in donkeys. In 2017, the International Society for Animal Genetics (ISAG) recommended 13 dinucleotide short tandem repeats (STRs) (AHT4, ASB23, HMS2, HMS3, HMS6, HMS7, HMS18, HTG7, HTG10, TKY297, TKY312, TKY337 and TKY343) as a core panel that should be used to identify individuals and to test for parentage in donkeys. To date, no single multiplex STR typing system containing all 13 donkey STRs recommended by the ISAG has been reported.

OBJECTIVES

To establish a novel and donkey-specific multiplex STR typing system containing all 13 recommended STRs.

STUDY DESIGN

Assay development and validation in field population.

METHODS

Primers for seven of the STRs were redesigned and conditions for polymerase chain reaction (PCR) were optimised. We analysed the allele sequences, sensitivity, species-specificity and stutter ratios of this new system.

RESULTS

A 13-plex STR typing system for donkey was established. A full profile could be generated from a single PCR reaction using as little as 5 ng of DNA template with the 13 pairs of primers labelled with fluorescent dyes. An allele ladder, containing 101 alleles from the 13 STRs, was generated. No full genotype profile was generated with these primers if DNA from humans, or 11 other commonly encountered animals, was used. Genotypes could be generated for the horse and horse-donkey hybrids (mule and hinny). Stutter ratios and population genetic parameters were calculated based on samples from 150 donkeys. The combined probabilities of paternity exclusion for this system were 0.988907326 (CPEduo) and 0.999665018 (CPEtrio).

MAIN LIMITATIONS

This system cannot detect sex.

CONCLUSIONS

Our results indicate that our donkey-specific 13-plex STR typing system is sensitive, species-specific and robust for individual identification, paternity testing and population genetic analysis in donkeys, and has potential forensic applications.

Validation of Zero TE-MRA in the Characterization of Cerebrovascular Diseases: A Feasibility Study

BACKGROUND AND PURPOSE

Zero TE-MRA is less sensitive to field heterogeneity, complex flow, and acquisition noise. This study aimed to prospectively validate the feasibility of zero TE-MRA for cerebrovascular diseases assessment, compared with TOF-MRA.

MATERIALS AND METHODS

Seventy patients suspected of having cerebrovascular disorders were recruited. Sound levels were estimated for each MRA subjectively and objectively in different modes. MRA image quality was estimated by 2 neuroradiologists. The degree of stenosis (grades 0-4) and the z-diameter of aneurysms (tiny group ≤3 mm and large group >3 mm) were measured for further quantitative analysis. CTA was used as the criterion standard.

RESULTS

Zero TE-MRA achieved significantly lower subjective perception and objective noise reduction (37.53%). Zero TE-MRA images showed higher signal homogeneity (3.29 ± 0.59 versus 3.04 ± 0.43) and quality of venous signal suppression (3.67 ± 0.47 versus 2.75 ± 0.46). The intermodality agreement was higher for zero TE-MRA than for TOF-MRA (zero TE, 0.90; TOF, 0.81) in the grading of stenosis. Zero TE-MRA had a higher correlation than TOF-MRA (zero TE, 0.84; TOF, 0.74) in the tiny group and a higher consistency with CTA (intraclass correlation coefficient, 0.83; intercept, -0.5084-1.1794; slope -0.4952 to -0.2093) than TOF-MRA (intraclass correlation coefficient, 0.64; intercept, 0.7000-2.6133; slope -1.0344 to -0.1923). Zero TE-MRA and TOF-MRA were comparable in the large group. Zero TE-MRA had more accurate details than TOF-MRA of AVM and Moyamoya lesions.

CONCLUSIONS

Compared with TOF-MRA, zero TE-MRA achieved more robust performance in depicting cerebrovascular diseases. Therefore, zero TE-MRA was shown to be a promising MRA technique for further routine application in the clinic in patients with cerebrovascular diseases.

Comprehensive Characterization of Somatic Mutations Impacting lncRNA Expression for Pan-Cancer

Somatic mutations have long been recognized as an important feature of cancer. However, analysis of somatic mutations, to date, has focused almost entirely on the protein coding regions of the genome. The potential roles of somatic mutations in human long noncoding RNAs (lncRNAs) are therefore largely unknown, particularly their functional significance across different cancer types. In this study, we characterized some lncRNAs whose expression was affected by somatic mutations (defined as MutLncs) and constructed global MutLnc landscapes across 17 cancer types by systematically integrating multiple levels of data. MutLncs were commonly downregulated and carried low mutation frequencies and non-silent mutations in most cancer types. Co-occurrence analysis in pan-cancer highlighted combined patterns of specific MutLncs, suggesting that a number of MutLncs influence diverse cancer types through combination effects. Several conserved and cancer-specific functions of MutLncs were determined. We further explored the somatic mutations affecting lncRNA expression via mixed and unmixed effects, which led to specific functions in pan-cancer. Survival analysis indicated that MutLncs and co-occurrence pairs can potentially serve as cancer biomarkers. Clarification of the specific roles of MutLncs in human cancers could be beneficial for understanding the molecular pathogenesis of different cancer types and developing the appropriate treatments.

[Clinical significance of exosomal miR-1231 in pancreatic cancer]

Objective: To investigate the expression and clinical significance of exosomal miR-1231 in plasma of pancreatic cancer (PC) patients and pancreatic cancer cells. Methods: A total of 16 patients who were diagnosed with pancreatic cancer in Hunan Cancer Hospital were collected from April 2016 to August 2017. Meanwhile, 16 healthy volunteers were recruited as the healthy control group at the same period. The plasma exosomes were extracted, and the levels of miR-1231 were detected by qRT-PCR in PC and healthy control groups. Moreover, the clinicopathological significance of exosomal miR-1231 expression was analyzed. Furthermore, the expression of exosomal miR-1231 was detected in several pancreatic cancer cells (MIA PaCa-2, PANC-1, SW1990, AsPC-1 and BxPc-3) and two normal pancreatic epithelial cells (HPDE and human primary pancreatic epithelial cell). Results: qRT-PCR results showed that the expression level of miR-1231 in plasma exosomes of pancreatic cancer patients (1.06±0.46) was significantly lower than that in healthy controls (2.30±0.99; P<0.05). The levels of exosomal miR-1231 in patients with stage Ⅰ-Ⅱ (1.515±0.531), no distant metastasis (1.236±0.461) and no lymph node metastasis (1.337±0.522) were significantly higher than those with stage Ⅲ-Ⅳ (0.848±0.224), distant metastasis (0.757±0.278) and lymph node metastasis (0.838±0.261), respectively (P<0.05 for all). In addition, there were no correlation between exosomal miR-1231 expression and age, sex, smoking history, CA19-9 levels and tumor sites (P>0.05). Furthermore, the expression level of exosomal miR-1231 in pancreatic cancer cell lines (0.142±0.135) was significantly lower than that in normal epithelial cells (1.127±0.179; P<0.05). Conclusions: The downregulation of exosomal miR-1231 in plasma of pancreatic cancer patients and pancreatic cancer cells suggests that it is related to the initiation and development of PC. It may be a new diagnostic and prognostic marker for PC.

Short communication: Genotyping and single nucleotide polymorphism analysis of bovine leukemia virus in Chinese dairy cattle

Bovine leukemia virus (BLV) causes enzootic leucosis in cattle and is classified into 10 genotypes with a worldwide distribution, except for several European countries, Australia, and New Zealand. Although BLV is widespread in Chinese cows with the positive rate of 49.1% at the individual level, very little is known about the BLV genotype in dairy cattle in China. To determine BLV genetic variability in cows in China, 112 BLV-positive samples from 5 cities in China were used for BLV molecular characterization in this study. Phylogenetic analysis using the neighbor-joining method on partial env sequence encoding gp51 obtained from 5 Chinese cities and those available in GenBank (n = 53, representing BLV genotype 1-10) revealed the Chinese strains belonged to genotype 6. Seven unique SNP were identified among Yancheng, Shanghai, and Bengbu strains out of the total 12 SNP identified in Chinese strains. The genotyping coupled with SNP analysis of BLV can serve as a useful molecular epidemiological tool for tracing the source of pathogens. This study highlights the importance of genetic analysis of geographically diverse BLV strains to understand BLV global genetic diversity.

Integrated analysis of the prognostic role of the lymph node ratio in node-positive gastric cancer: A meta-analysis

BACKGROUND

The lymph node ratio (LNR) as a prognostic parameter for gastric cancer has yet to be fully validated in the current tumor node metastasis staging system. We assessed the prognostic role of LNR in lymph node-positive gastric cancer through a meta-analysis.

MATERIALS AND METHODS

PubMed and EMBASE were searched for relevant studies up until December 2016. The effect measure for meta-analysis of primary outcomes was the hazard ratio (HR) for overall survival. Pooled HRs and 95% confidence intervals were calculated using random effects models. The I² statistic was used to measure heterogeneity. Subgroup analysis and meta-regression were chosen to illustrate the potential heterogeneity of the risk factors of outcomes. Publication bias was assessed using Egger's test and Begg's funnel plots. Sensitivity analysis was applied to evaluate the origin of the heterogeneity.

RESULTS

We included 27 studies in this meta-analysis. Higher LNRs were significantly associated with a shorter overall survival (OS). High heterogeneity among the studies was identified (I² = 85.6), and the publication bias was moderate. Subgroup analysis showed similar results, and elevated LNR was associated with late-stage gastric cancer and indicative of a worse prognosis. Univariate meta-regression analysis of OS indicated that both treatment type and ethnicity may be causes of heterogeneity in patients with gastric cancer (p values were 0.005 and 0.008, respectively).

CONCLUSION

LNR was associated with a significantly poorer OS and LNR was an independent predictor of survival in patients with gastric cancer. LNR should be added as one of the parameters to be used in future tumor staging classification systems.

Exploration of drug-response mechanism by integrating genetics and epigenetics across cancers

Aim: To discover CpG island methylator phenotype (CIMP) as a predictor for cancer drug-response mechanism. Materials & methods: CIMP classification of 966 cancer cell lines was determined according to identified copy number alteration and differential methylation by DNA methylation profiles. CIMP-related drugs were analyzed by analysis of variance. Tissue–cell–drug networks were developed to predict drug response of individual samples. Results & conclusion: One hundred and thirty-six copy number gain and 142 copy number loss cell lines were classified into CIMP-high and CIMP-low groups, meanwhile 9 and 24 CIMP-associated drugs were identified, respectively. Specially, breast invasive carcinoma samples primarily composed by HCC1419 were predicted to be sensitive to GSK690693. The study provides guidance for drug response in cancer therapy through genome-wide DNA methylation.

Expressions and clinical significance of factors related to acute coronary syndrome

Acute coronary syndrome (ACS) is the acute stage of coronary artery disease, which remains a major cause of mortality and morbidity. It is essential to explore the role of matrix metalloproteinase -2 (MMP-2) and interleukin (IL)-18 and their association with disease in patients with severe ACS. Circulating MMP-2 and IL-18 levels were measured using enzyme linked immunosorbent assay (ELISA) in 94 subjects with acute coronary syndrome (ACS, n=38), stable angina pectoris (SAP, n=27) and healthy individuals (control group, n=29). We examined the correlations between the levels of MMP-2 and IL-18 and cardiac risk factors in ACS. Logistic regression analysis was performed to screen for factors that predict ACS. Both MMP-2 and IL-18 concentrations were increased in the ACS group compared to the SAP group or control group (P less than 0.01). Especially, MMP-2 and IL-18 were highly expressed in the patients with ST elevated myocardial infarction (STEMI). Both serum levels of MMP-2 and IL-18 in the single-, double- and triple-vessel lesion group were higher compared to the control group (P less than 0.01). MMP-2 levels were positively correlated with IL-18 (r=0.639, P less than 0.01), CK-MB (r=0.47, P=0.003) and hs-CRP levels (r=0.583, P less than 0.01). The logistic regression analysis showed that increases in MMP-2 levels may be a powerful predictor of ACS. Thus, the changes in levels of serum MMP-2 and IL-18 may be useful in the diagnosis of ACS and prediction of its prognosis.

DNA methylation dynamics: identification and functional annotation

DNA methylation is an epigenetic modification of cytosines that undergoes dynamic changes in a temporal, spatial and cell-type-specific manner. Recent advances in technology have permitted the profiling of high-throughput methylomes in large numbers of biological samples. Various computational tools have been developed to identify and analyze DNA methylation dynamics in a variety of critical biological processes. As DNA methylation is becoming increasingly viewed as a dynamic process, the mechanisms governing DNA methylation dynamics and its roles in the transcriptional regulatory network are of great interest. It has been reported that DNA methylation dynamics plays essential roles in multiple biological processes, including development and cancer. As a functional event, the dynamics of DNA methylation have become increasingly relevant to many researchers. Here, we review state-of-the-art advances at three levels (genome-wide identification, regulatory mechanism investigation and the functional annotation) in the field of DNA methylation dynamics, as well as the future perspective of DNA methylation dynamics.

Systematic identification and annotation of human methylation marks based on bisulfite sequencing methylomes reveals distinct roles of cell type-specific hypomethylation in the regulation of cell identity genes

DNA methylation is a key epigenetic mark that is critical for gene regulation in multicellular eukaryotes. Although various human cell types may have the same genome, these cells have different methylomes. The systematic identification and characterization of methylation marks across cell types are crucial to understand the complex regulatory network for cell fate determination. In this study, we proposed an entropy-based framework termed SMART to integrate the whole genome bisulfite sequencing methylomes across 42 human tissues/cells and identified 757 887 genome segments. Nearly 75% of the segments showed uniform methylation across all cell types. From the remaining 25% of the segments, we identified cell type-specific hypo/hypermethylation marks that were specifically hypo/hypermethylated in a minority of cell types using a statistical approach and presented an atlas of the human methylation marks. Further analysis revealed that the cell type-specific hypomethylation marks were enriched through H3K27ac and transcription factor binding sites in cell type-specific manner. In particular, we observed that the cell type-specific hypomethylation marks are associated with the cell type-specific super-enhancers that drive the expression of cell identity genes. This framework provides a complementary, functional annotation of the human genome and helps to elucidate the critical features and functions of cell type-specific hypomethylation.

SEA: a super-enhancer archive

Super-enhancers are large clusters of transcriptional enhancers regarded as having essential roles in driving the expression of genes that control cell identity during development and tumorigenesis. The construction of a genome-wide super-enhancer database is urgently needed to better understand super-enhancer-directed gene expression regulation for a given biology process. Here, we present a specifically designed web-accessible database, Super-Enhancer Archive (SEA, http://sea.edbc.org). SEA focuses on integrating super-enhancers in multiple species and annotating their potential roles in the regulation of cell identity gene expression. The current release of SEA incorporates 83 996 super-enhancers computationally or experimentally identified in 134 cell types/tissues/diseases, including human (75 439, three of which were experimentally identified), mouse (5879, five of which were experimentally identified), Drosophila melanogaster (1774) and Caenorhabditis elegans (904). To facilitate data extraction, SEA supports multiple search options, including species, genome location, gene name, cell type/tissue and super-enhancer name. The response provides detailed (epi)genetic information, incorporating cell type specificity, nearby genes, transcriptional factor binding sites, CRISPR/Cas9 target sites, evolutionary conservation, SNPs, H3K27ac, DNA methylation, gene expression and TF ChIP-seq data. Moreover, analytical tools and a genome browser were developed for users to explore super-enhancers and their roles in defining cell identity and disease processes in depth.

Abstract P4-05-12: MultiOmyx™ screening for prognostic indicators of breast cancer

Over the last three decades, the incidence of early-stage breast cancer has doubled while the incidence of late stage breast cancer has slightly decreased; however, the standard treatment for both has not changed significantly in the last 10 years. Of those diagnosed with early-stage breast cancer, 30% will develop recurrent disease, though there is currently no diagnostic available to identify these cases. Conversely, identifying late stage patients with a low- risk for recurrence could spare them from post-surgical chemotherapy. We have developed a technology that allows in situ staining and analysis of up to 60 proteins on a single tissue slide. In this exploratory study we evaluated 25 known biomarkers on a cohort of more than 800 breast cancer cases assembled onto three tissue arrays. The cohort spans clinical grades and breast cancer subtypes, and is thus useful in novel associations of biomarker expression across a variety of clinical features. Twenty-five markers were chosen based on literature reports for marker association with disease recurrence and represent a range of biological features including signaling pathways and cell phenotypes. The slides were sequentially stained with antibodies that were directly conjugated to Cy3 and Cy5 dyes, imaged, evaluated for quality and subject inclusion, and subsequently analyzed for statistical correlations of expression values to clinical features. The images were then processed using a single cell analysis algorithm which allows for quantification of individual tumor cells and signal intensities for the markers to be extracted from sub-cellular domains (nucleus, cytoplasm, and membrane of each cell) allowing unique patterns of protein expression to be determined. Univariate Cox proportional hazards analysis was first applied to determine those features with strongest association with ‘death due to disease’. Of the 25 markers analyzed, several markers (e.g. API3, AMPH2, beta-catenin, CD44, CEACAM5, CK15, CK19, cMET, Her2, Ki67, TRIM29) were found to have strong association with poor outcome (FDR &lt; 0.05). After adjusting for clinical variables (stage, number of positive nodes, grade), a number of markers (e.g. CD44, CEACAM5, cMET, TRIM29) still show a strong association with poor clinical outcome (FDR &lt; 0.05, Cox proportional hazards model). CEACAM5 is part of the MammostratTM panel of markers used for determining prognosis in ER positive breast cancers after Tamoxifen® treatment. CD44, a cancer stem cell marker, and TRIM 29, a transcriptional regulatory factor involved in carcinogenesis, have been associated with basal-like breast cancers which have the worst prognosis of all the breast cancer subtypes. High levels of cMET have been associated with poor prognosis for all breast cancer subtypes and cMET is being explored as a therapeutic target. The MultiomyxTM methodology enabled us to verify a subset of biomarkers that are clinically relevant to breast cancer outcome. Using this technology could lead to identification of novel biosignatures that stratify patients and enable precision medicine that results in better treatment decisions and prognosis for patients.

Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P4-05-12.

Temporal expression of metalloproteinase-8 and -13 and their relationships with extracellular matrix metalloproteinase inducer in the development of ligature-induced periodontitis in rats

BACKGROUND AND OBJECTIVE

Matrix metalloproteinases (MMPs) play important roles in extracellular matrix degradation and may be regulated by extracellular matrix metalloproteinase inducer (EMMPRIN). The aim of this study was to investigate the temporal expression and localization of MMP-8 and MMP-13 during the development of ligature-induced periodontitis in rats, and to analyze the correlations of EMMPRIN with MMP-8 and MMP-13 in periodontitis.

MATERIAL AND METHODS

Periodontitis was simulated in rats by ligaturing the cervix of the lower first molars, as described in our previous method. The rats were killed 0, 3, 5, 7, 11, 15 and 21 d after ligation. Micro-computed tomography examinations were performed to detect alveolar bone loss. Semiquantitative western blotting was used to assess the temporal changes in the levels of MMP-8, MMP-13 and EMMPRIN proteins in gingival tissue. Immunohistochemistry was applied to detect the expression and locations of MMP-8 and MMP-13 in gingival tissue and alveolar bone.

RESULTS

Alveolar bone loss showed an exponential increase from days 3 to 11, followed by a slower rate of loss at subsequent study time points. MMP-8 showed a rapid increase of expression from baseline to a peak on day 3, a gradual decrease from days 5 to 7 and then stabilized thereafter. MMP-8 was predominantly located in neutrophil-like cells. Statistically, the expression of MMP-8 was not correlated with the expression of EMMPRIN. The expression of MMP-13 and of EMMRPIN increased from days 3 to 7, and showed a moderate decrease thereafter. The immunoreactivity of MMP-13 was mainly detected in monocytes/macrophages, on the alveolar bone surface, in osteoclasts and in gingival epithelial cells. Statistically, MMP-13 had a strong, positive correlation with EMMPRIN (r = 0.855, p < 0.01).

CONCLUSION

The levels of expression of MMP-8 and MMP-13 are temporally varied at different periods during the development of experimental periodontitis. The level of expression of EMMPRIN is closely associated with the expression of MMP-13, but not with the expression of MMP-8. In addition, MMP-13 might be involved in alveolar bone destruction, as well as in physiological bone remodeling.