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Alternative polyadenylation (APA) is an important posttranscriptional modification commonly involved in tumor development. However, the functional roles of APA in tumor immunity remain largely unknown. Here, we performed an in-depth analysis of the 3′UTR usage of protein-coding genes and tumor immune response in 10,303 tumor samples across 31 cancer types to develop the immune-related APA event (ImmAPA) score pipeline, an integrated algorithm to characterize the regulatory landscape of APA events in cancer immunity–related pathways. Tumor-specific ImmAPAs that strongly correlate with immune cell infiltration and immune checkpoint blockade (ICB) treatment–related biomarkers were identified. Among these ImmAPAs, the top-ranking COL1A1 3′UTR usage was strongly associated with worse prognosis and tumor immune evasion. Furthermore, a machine learning approach to construct an ICB-related ImmAPA score model predicted immunotherapy efficacy. Overall, the characterization of immune-related APA that corresponds to tumor progression and tumor immunity highlights the clinical utility of APA events as potential biomarkers in cancer immunotherapy. Significance: Elucidation of the landscape of immune-related alternative polyadenylation in cancer identifies alternative polyadenylation events that may play a role in immune modulation and immunotherapy efficacy.

Supplementary tables 1-3 and figures 1-15.

Supplementary Data from Characterization of Immune-Related Alternative Polyadenylation Events in Cancer Immunotherapy

Supplementary Table from Characterization of Immune-Related Alternative Polyadenylation Events in Cancer Immunotherapy

Alternative polyadenylation (APA) is an important posttranscriptional modification commonly involved in tumor development. However, the functional roles of APA in tumor immunity remain largely unknown. Here, we performed an in-depth analysis of the 3′UTR usage of protein-coding genes and tumor immune response in 10,303 tumor samples across 31 cancer types to develop the immune-related APA event (ImmAPA) score pipeline, an integrated algorithm to characterize the regulatory landscape of APA events in cancer immunity–related pathways. Tumor-specific ImmAPAs that strongly correlate with immune cell infiltration and immune checkpoint blockade (ICB) treatment–related biomarkers were identified. Among these ImmAPAs, the top-ranking COL1A1 3′UTR usage was strongly associated with worse prognosis and tumor immune evasion. Furthermore, a machine learning approach to construct an ICB-related ImmAPA score model predicted immunotherapy efficacy. Overall, the characterization of immune-related APA that corresponds to tumor progression and tumor immunity highlights the clinical utility of APA events as potential biomarkers in cancer immunotherapy.Significance:Elucidation of the landscape of immune-related alternative polyadenylation in cancer identifies alternative polyadenylation events that may play a role in immune modulation and immunotherapy efficacy.

In this paper, we demonstrate dynamic optical beam-steering of a band-edge chiral nematic liquid crystal (LC) laser that does not involve any change in the configuration of the helical structure. This beam-steering is achieved by exploiting the circular polarisation of the LC laser in combination with tuneable nematic LC phase shifters and fixed polarisation gratings. Experimental results are presented, showing the optical steering of the LC laser emission to four separate discrete spatial positions and, using simulations based on Jones calculus, we explain the appearance and relative intensities of other minor spots that appear around the primary beam. Compared with other approaches of beam-steering an LC laser, this method does not result in an alteration of the laser wavelength, does not change the internal cavity structure of the laser, and has a minimal impact on the intensity of the laser emission. In addition, the whole system (except for the solid-state pump source) is comprised of thin films that are either liquid crystalline or polymers, which provides a tangible route towards a more compact and integrated optically steerable LC laser.

A number of staging systems have been developed to predict clinical outcomes in hepatocellular carcinoma (HCC). However, no general consensus has been reached regarding the optimal model. New approaches such as machine learning (ML) strategies are powerful tools for incorporating risk factors from multiple platforms. We retrospectively reviewed the baseline information, including clinicopathologic characteristics, laboratory parameters, and peripheral immune features reflecting T-cell function, from three HCC cohorts. A gradient-boosting survival (GBS) classifier was trained with prognosis-related variables in the training dataset and validated in two independent cohorts. We constructed a 20-feature GBS model classifier incorporating one clinical feature, 14 laboratory parameters, and five T-cell function parameters obtained from peripheral blood mononuclear cells. The GBS model–derived risk scores demonstrated high concordance indexes (C-indexes): 0.844, 0.827, and 0.806 in the training set and validation sets 1 and 2, respectively. The GBS classifier could separate patients into high-, medium- and low-risk subgroups with respect to death in all datasets (P < 0.05 for all comparisons). A higher risk score was positively correlated with a higher clinical stage and the presence of portal vein tumor thrombus (PVTT). Subgroup analyses with respect to Child–Pugh class, Barcelona Clinic Liver Cancer stage, and PVTT status supported the prognostic relevance of the GBS-derived risk algorithm independent of the conventional tumor staging system. In summary, a multiparameter ML algorithm incorporating clinical characteristics, laboratory parameters, and peripheral immune signatures offers a different approach to identify patients with the greatest risk of HCC-related death.

Immune checkpoint blockade (ICB) of the programmed cell death 1/programmed cell death ligand 1 (PD-1/PD-L1) immune checkpoint pathway has led to unprecedented advances in cancer therapy. However, the overall response rate of anti-PD-1/PD-L1 monotherapy is still unpromising, underscoring the need for predictive biomarkers. In this retrospective study, we collected pretreatment plasma samples from two independent cohorts of patients receiving ICB. To determine whether a signature of plasma cytokines could be associated with therapeutic efficacy, we systemically profiled cytokine clusters and functional groups in the discovery and validation datasets by using 59 multiplexed bead immunoassays and bioinformatics analysis. We first attempted to functionally classify the 59 immunological factors according to their biological classification or functional roles in the cancer-immunity cycle. Surprisingly, we observed that two signatures, the "checkpoint signature" and "trafficking of T-cell signature", were higher in the response subgroup than in the nonresponse subgroup in both the discovery and validation cohorts. Moreover, enrichment of the "checkpoint signature" was correlated with improved overall survival and progression-free survival in both datasets. In addition, we demonstrated that increased baseline levels of three checkpoint molecules (PD-L1, T-cell immunoglobulin mucin receptor 3 and T-cell-specific surface glycoprotein CD28) were common peripheral responsive correlates in both cohorts, thus rendering this "refined checkpoint signature" an ideal candidate for future verification. In the peripheral blood system, the "refined checkpoint signature" may function as a potential biomarker for anti-PD-1/PD-L1 monotherapy in gastrointestinal (GI) cancers.

BackgroundImmune checkpoint inhibitors (ICIs) have been increasingly used in patients with various cancers and have shown efficient therapeutic outcomes. However, fewer than 40% of cases across multiple cancer types show a response to ICIs. Therefore, developing more efficient combinational approaches with ICIs and revealing the underlying mechanisms are important goals for achieving rapid clinical transformation and application.MethodsThe effects on antitumor immunity activity of albendazole (ABZ) and the synergistic effects of ABZ with CD73 blockade were investigated in the melanoma B16F10 and the Lewis lung cancer tumor-bearing immune-competent mice models. The mechanism of ABZ reducing PD-L1 protein level through suppressing UBQLN4 was identified and validated through immunoprecipitation-mass spectrometry and molecular methods. Bioinformatics and anti-PD-1 therapy melanoma patients samples analysis were used to assess the level of UBQLN4/PD-L1 in the therapeutic efficacy of anti-PD-1 therapy.ResultsABZ induces CD8+ T cell activity and subsequent immunotherapy response associated with suppression of PD-L1 protein level. Mechanistically, we revealed that ABZ promotes ubiquitin-mediated degradation of PD-L1 via suppressing UBQLN4, which was bound to PD-L1 and stabilized PD-L1 protein. Preclinically, genetic deletion or target inhibition of CD73 showed synergistic effects with ABZ treatment in the immune-competent mice models. Significantly, UBQLN4 and PD-L1 levels were higher in the tumor region of responders versus non-responders and correlated with better progression-free survival and overall survival in anti-PD-1 therapy melanoma patients.ConclusionsOur findings revealed a previously unappreciated role of ABZ in antitumor immunity by inducing ubiquitin-mediated PD-L1 protein degradation, identified predictors for assessing the therapeutic efficacy of anti-PD-1 therapy, and provided novel therapeutic possibility by combination treatment of ABZ and CD73 blockade in cancers.

Immune checkpoint blockade (ICB) exhibits considerable benefits in malignancies, but its overall response rate is limited. Previous studies have shown that sphingosine kinases (SPHKs) are critical in the tumor microenvironment (TME), but their role in immunotherapy is unclear. We performed integrative analyses including bioinformatics analysis, functional study, and clinical validation to investigate the role of SPHK1 in tumor immunity. Functionally, we demonstrated that the inhibition of SPHK1 significantly suppressed tumor growth by promoting antitumor immunity in immunocompetent melanoma mouse models and tumor T-cell cocultures. A mechanistic analysis revealed that MTA3 functions as the downstream target of SPHK1 in transcriptionally regulating tumor PD-L1. Preclinically, we found that anti-PD-1 monoclonal antibody (mAb) treatment significantly rescued tumor SPHK1 overexpression or tumor MTA3 overexpression-mediated immune evasion. Significantly, we identified SPHK1 and MTA3 as biological markers for predicting the efficacy of anti-PD-1 mAb therapy in melanoma patients. Our findings revealed a novel role for SPHK1 in tumor evasion mediated by regulating the MTA3-PD-L1 axis, identified SPHK1 and MTA3 as predictors for assessing the efficacy of PD-1 mAb treatment, and provided a therapeutic possibility for the treatment of melanoma patients.

Whether the lifestyle is associated with the risk of psoriasis in the presence of different genetic risk levels remains unknown.To examine the gene-behavior interaction in association with incident psoriasis.This study is based on the data from the UK Biobank, which recruited 500,000 participants. Genetic risk was categorized into low, intermediate, and high groups. The lifestyle score comprised the body mass index, smoking, physical activity, and diet and was also categorized into the ideal, intermediate, and poor groups. Within each genetic risk group, the risks of incident psoriasis associated with each lifestyle level were investigated and compared with the low genetic risk and ideal lifestyle group.Compared with the low genetic risk and ideal lifestyle group, the poor lifestyle and high genetic risk group was associated with a hazard ratio of up to 4.625 (95% confidence interval [CI], 2.920-7.348) for psoriasis. There was no interaction between genetic risk and lifestyle. The population attributable fractions of lifestyle and genetic risk were 32.2% (95% CI, 25.1%-38.6%) and 13.0% (95% CI, 3.2%-21.8%), respectively.No verification in other independently ascertained populations.Lifestyle factors are predictive of the risk of incident psoriasis independent of genetic risk, and the relative impact of lifestyle factors was greater than that of genetic risk.

The ecological model we developed can simulate the state of wetlands and predict ecosystem development by varying both parameter settings and forcing functions. The newly created wetland resulting from large-scale coal mining is a distinct type of wetland, but existing ecological models for this wetland type are limited in number and scope. The Yanzhou coalfield, located in Shandong Province in China, contains a typical newly created wetland that came into being after coal mining subsidence. We developed an ecological model for this wetland that estimates values for four state variables: phytoplankton biomass (A), zooplankton biomass (Z), sediment biomass (D), and hydrophyte biomass (H). Analysis of the results showed that the model was sensitive to changes in nutrient loading. As nutrient loads increased, plankton biomass increased, and the ratio of zooplankton biomass to phytoplankton biomass (Z/A) decreased. We defined three prediction scenarios for the wetland and calculated their eco-exergies to compare the ecological effects for each scenario. The most effective measures to improve the state of the ecosystem are to reduce the subsidence depth and to decrease nutrient loading.

Over the past decade, thousands of long noncoding RNAs (lncRNAs) have been identified, many of which play crucial roles in normal physiology and human disease. LncRNAs can interact with chromatin and then recruit protein complexes to remodel chromatin states, thus regulating gene expression. However, how lncRNA-chromatin interactions contribute to their biological functions is largely unknown. Here, we collected and constructed an atlas of 188,647 lncRNA-chromatin interactions in human and mouse. All lncRNAs showed diverse epigenetic modification patterns at their binding sites, especially the marks of enhancer activity. Functional analysis of lncRNA target genes further revealed that lncRNAs could exert their functions by binding to both promoter and distal regulatory elements, especially the distal regulatory elements. Intriguingly, many important pathways were observed to be widely regulated by lncRNAs through distal binding. For example, NEAT1, a cancer lncRNA, controls 13.3% of genes in the PI3K-AKT signaling pathway by interacting with distal regulatory elements. In addition, “two-gene” signatures composed of a lncRNA and its distal target genes, such as HOTAIR-CRIM1, provided significant clinical benefits relative to the lncRNA alone. In summary, our findings underscored that lncRNA-distal interactions were essential for lncRNA functions, which would provide new clues to understand the molecular mechanisms of lncRNAs in complex disease.

This paper is a preliminary attempt to quantify the impact of coal mining subsidence on surface ecology. The Yanzhou coalfield of Shandong Province has a long history of longwall coal extraction and the resulting subsidence depressions has created new wetlands. To assess the ecosystem processes of these new wetlands, we determined their eco-exergy based on a structural dynamic method. We used Stella, a software that facilitates construction of structurally dynamic models, including the nutrient cycle, hydrological processes, and large aquatic plant factors. Following calibration and validation, the model was applied to two scenarios to show different trends. The ratio of zooplankton biomass to phytoplankton biomass, transparency in Secchi depth, eco-exergy, and structural eco-exergy were selected as indicators. Understanding eco-exergy can help protect an area’s ecological balance and achieve a sustainable use of water and soil resources.

Background : Currently, only a small subset of cancer patients can benefit from anti-PD-1/PD-L1 monotherapy, indicating that further predictive biomarkers are needed. Methods: In the retrospective study, plasma samples were collected before anti-PD-L1/PD-L1 treatment in two subset of patients. A total of 59 immunological factors, including cytokines, chemokines, and soluble immune checkpoints, were measured by using a multiplex immunoassay kit. Moreover, multiplex immunohistochemistry (mIHC) was performed in a subgroup of patients. Findings: In the discovery cohort, multiplex immunoassay profiling data revealed that both soluble PD-L1 and C-C motif chemokine 5 (CCL5/RANTES) showed rising trends across the three subgroups PD, SD and CR/PR. Further investigation demonstrated the predictive and prognostic value of the pre-treatment levels of PD-L1, CCL5/RANTES, and their combinatorial signature the “2-cytokine signature”. As expected, the signature-high patients displayed a remarkably increased disease control rate (DCR) and prolonged survival versus that of the lower subgroup. More importantly, the relevance between the three signatures and the efficiency of immunotherapy was confirmed in the pan-cancer validation cohort. Notably, the significant association between the “2-cytokine signature” and longer survival was validated. Further quantitative analyses of the tumor microenvironment composition suggested a link between the “2-cytokine signature” and NK cell infiltration. Interpretation: A combined peripheral signature comprising CCL5/RANTES and soluble PD-L1 appears to be an effective biomarker to predict benefit from anti-PD-1/PD-L1 monotherapy. Our study underscores that peripheral immunological features may play an essential role in guiding patient selection and are worthy of future prospective investigations. Funding: This work was supported by The National Key Sci-Tech Special Project of China (No. 2018ZX10302207). Declaration of Interests: HZ has received research funding from The National Key Sci-Tech Special Project of China. The remaining authors declare no competing financial interests. Ethics Approval Statement: This study was approved by the Internal Review and the Ethics Boards of the Fifth Medical Center, General Hospital of the PLA and were performed in accordance with the Declaration of Helsinki. Written informed consent was obtained from each patient.

Immune checkpoint blockade (ICB) of the programmed cell death 1/programmed cell death ligand 1 (PD-1/PD-L1) immune checkpoint pathway has led to unprecedented advances in cancer therapy. However, the overall response rate of anti-PD-1/PD-L1 monotherapy is still unpromising, underscoring the need for predictive biomarkers. In this retrospective study, we collected pretreatment plasma samples from two independent cohorts of patients receiving ICB. To determine whether a signature of plasma cytokines could be associated with therapeutic efficacy, we systemically profiled cytokine clusters and functional groups in the discovery and validation datasets by using 59 multiplexed bead immunoassays and bioinformatics analysis. We first attempted to functionally classify the 59 immunological factors according to their biological classification or functional roles in the cancer-immunity cycle. Surprisingly, we observed that two signatures, the "checkpoint signature" and "trafficking of T-cell signature", were higher in the response subgroup than in the nonresponse subgroup in both the discovery and validation cohorts. Moreover, enrichment of the "checkpoint signature" was correlated with improved overall survival and progression-free survival in both datasets. In addition, we demonstrated that increased baseline levels of three checkpoint molecules (PD-L1, T-cell immunoglobulin mucin receptor 3 and T-cell-specific surface glycoprotein CD28) were common peripheral responsive correlates in both cohorts, thus rendering this "refined checkpoint signature" an ideal candidate for future verification. In the peripheral blood system, the "refined checkpoint signature" may function as a potential biomarker for anti-PD-1/PD-L1 monotherapy in gastrointestinal (GI) cancers.

Background: Conventional strategies for assessing clinical and pathological risk factors have been adopted to predict clinical outcomes in patients with hepatocellular carcinoma (HCC). We hypothesized that an ensemble learning approach that incorporates multidimensional features would enable the construction of an effective prediction model for patient-specific risk profiles. Methods: We analyzed data from 222 stage II-III HCC patients who underwent surgical resection at Eastern Hepatobiliary Surgery Hospital (Shanghai, China). We developed five machine learning-based estimation models for patient overall survival. The models were trained on 155 patients with 48 features (included clinical and pathological risk factors, laboratory tests and in situ immunological profiles), and validated on the remaining 67 patients. Findings: A risk scoring system incorporating multiple machine learning methods was developed for survival prediction. For all models tested, immune features such as CD68+ and CD8+ immune cell infiltration played a crucial role in predicting patient overall survival. The risk scoring system stratified patients into high-risk and low-risk subgroups (validation cohort: HR, 6.5; 95% CI, 2.4-18; p = 3.4e-05). In the validation set, the scoring system predicted the half-year mortality of patients with an AUC of 0.9 (95% CI, 0.771-1.029) and 1-year mortality with an AUC of 0.897 (95% CI, 0.816-0.978). The system was also predictive of the time to recurrence (p

High functional heterogeneity of cancer cells poses a major challenge for cancer research. Single-cell sequencing technology provides an unprecedented opportunity to decipher diverse functional states of cancer cells at single-cell resolution, and cancer scRNA-seq datasets have been largely accumulated. This emphasizes the urgent need to build a dedicated resource to decode the functional states of cancer single cells. Here, we developed CancerSEA (http://biocc.hrbmu.edu.cn/CancerSEA/ or http://202.97.205.69/CancerSEA/), the first dedicated database that aims to comprehensively explore distinct functional states of cancer cells at the single-cell level. CancerSEA portrays a cancer single-cell functional state atlas, involving 14 functional states (including stemness, invasion, metastasis, proliferation, EMT, angiogenesis, apoptosis, cell cycle, differentiation, DNA damage, DNA repair, hypoxia, inflammation and quiescence) of 41 900 cancer single cells from 25 cancer types. It allows querying which functional states are associated with the gene (or gene list) of interest in different cancers. CancerSEA also provides functional state-associated PCG/lncRNA repertoires across all cancers, in specific cancers, and in individual cancer single-cell datasets. In summary, CancerSEA provides a user-friendly interface for comprehensively searching, browsing, visualizing and downloading functional state activity profiles of tens of thousands of cancer single cells and the corresponding PCGs/lncRNAs expression profiles.

Large-scale sequencing studies discovered substantial genetic variants occurring in enhancers which regulate genes via long range chromatin interactions. Importantly, such variants could affect enhancer regulation by changing transcription factor bindings or enhancer hijacking, and in turn, make an essential contribution to disease progression. To facilitate better usage of published data and exploring enhancer deregulation in various human diseases, we created DiseaseEnhancer (http://biocc.hrbmu.edu.cn/DiseaseEnhancer/), a manually curated database for disease-associated enhancers. As of July 2017, DiseaseEnhancer includes 847 disease-associated enhancers in 143 human diseases. Database features include basic enhancer information (i.e. genomic location and target genes); disease types; associated variants on the enhancer and their mediated phenotypes (i.e. gain/loss of enhancer and the alterations of transcription factor bindings). We also include a feature on our website to export any query results into a file and download the full database. DiseaseEnhancer provides a promising avenue for researchers to facilitate the understanding of enhancer deregulation in disease pathogenesis, and identify new biomarkers for disease diagnosis and therapy.

Background Enhancer has been recognized as an important driver whose genetic alterations contribute to disease progression. However, there is still no easy-to-use tools to identify pathogenic enhancers, allowing for deciphering functional influence of genetic variants on enhancer. Results We developed a user-friendly one-stop shop platform, named inferring pathogenic enhancer with variant (IPEV), only requiring variants as input, to quickly infer the pathogenic enhancers that harbor variants affecting their activities. Results of IPEV are explored in an interactive, user-friendly web environment, which is designed to highlight the most probable pathogenic enhancers and their target genes. Furthermore, IPEV provides intuitive visualizations of how a variant affects the corresponding enhancer activity by mediating TF binding changes. Conclusions IPEV is specially designed to prioritize the potentially pathogenic enhancers with genetic variants, and provides intuitive visualizations how a variant affects the corresponding enhancer activity by mediating which transcription factor binding changes. The use of IPEV does not require any specialized computer skills. We believe that IPEV will be useful in interpreting non-coding variants by the inferring pathogenic enhancers. It is freely available at http://biocc.hrbmu.edu.cn/IPEV/ or http://210.46.80.168/IPEV and supports recent versions of all major browsers.

Riparian zones are interesting habitats as they are important transitional zones between terrestrial and aquatic ecosystems, but highly threatened by human disturbances. They support a high arthropod diversity as they experience periodic flooding disturbance and sharp environmental gradients. Their associated arthropod fauna are of high conservation value. Nevertheless, their arthropod diversity remains largely unknown, and its distribution pattern along elevational gradients is poorly understood. Few data are available on the effects of flood regimes and other factors in determining riparian arthropod communities. In this study, we investigated the diversity and distribution of riparian arthropods along an elevational gradient and determined the major factors structuring the arthropod communities in the drawdown zone of the Three Gorges Reservoir, China. Significant compositional and structural changes of riparian arthropod communities were observed along the test elevational gradient. The abundance and richness of riparian arthropods increased with elevation. The relative abundance of predators decreased with elevation, whereas the saprovores and omnivores showed an upward trend along the elevational gradient. Redundancy analysis showed that there were significant interactions between the flood regimes, plant communities, and soil conditions. Among these environmental factors studied, flood duration was the main factor in structuring the riparian arthropod communities. Conservation and restoration strategies should consider flood duration in the operation of large reservoirs because riparian arthropods are particularly sensitive to flood regimes.

Mixed-species vegetation, such as that in semi-natural meadows, is increasingly adopted in urban green infrastructure to enhance habitat quality and aesthetic value; however, little is known regarding the consequences of using meadow mixes in river revetments. In the present study, 20 herbaceous species that naturally occur in habitats with infrequent and periodic inundation were mix-planted in hydrology-induced and disturbed revetments along the mainstream of the Yangtze River in the typical mountain city of Chongqing, China. The experimental meadow communities exhibited persistence under the constraints imposed by the prevailing hydrological conditions and disturbances, such as the extremely high soil wetness variability between periodical inundation on seedlings, the drought during the summer, and the transition between runoff washout and quick drainage. All planted species survived under the changing hydrological conditions, while the semi-natural meadow maintained good growth and visual landscape quality. Meadow mixes were significantly superior in species richness, abundance and structural diversity over the existing homogeneous community dominated by invasive liana Humulus scandens. Community data suggest that species richness has increased by more than 60% in the meadow mix over the existing vegetation. The meadow communities resisted invasion by indigenous weeds and colonising species that spread through wind-dispersal and hydrochorous transport from the upstream catchment. We therefore recommend prioritising taxonomically diverse meadows for river revetments wherever possible. This study provides a valid framework that can be used to inform future vegetation restoration schemes in river revetments affected by complex hydrological variation and disturbances. The methodology is applicable to a broad range of vegetative revetment structures.

Long intergenic non-coding RNAs (lincRNAs) are emerging as important regulatory molecules involved in diseases including heart failure. However, little is known about how the lincRNAs work together with protein-coding genes (PCGs) contributing to the pathogenesis of heart failure. In this study, we constructed a comprehensive transcriptome profile of lincRNAs, PCGs and miRNAs using RNA-seq and miRNA-seq data of 16 heart failure patients (HFs) and 8 non-failing individuals (NFs). Through integrating lincRNA and PCG expression profiles, we identified HF-associated lincRNA modules. We identified a heart-specific lincRNA module which was significantly enriched for differentially expressed lincRNAs and PCGs. This module was associated with heart failure rather than with other clinical traits such as sex, age, smoking and diabetes mellitus. Moreover, the module was significantly correlated with certain indicators of left ventricular function like ejection fraction and left ventricular end-diastolic diameter, implying the potential of its components as crucial biomarkers. Apart from enhancer-like function, lincRNAs in this module could act as competing endogenous RNAs (ceRNAs) to regulate genes which were associated with left-ventricular systolic function. Our work provided deep insights into the critical roles of lincRNAs in the pathology of heart failure and suggested that they could be valuable biomarkers and therapeutic targets.

Background Epigenetic marks can cooperatively regulate chromatin accessibility and in turn facilitate or impede the binding of regulatory factors to various elements, suggesting their important roles in regulatory circuits. However, it remains elusive as to how epigenetic marks cooperate in the operations of regulatory network. Methods Here, we systematically characterized chromatin states of 26 epigenetic marks on different elements of protein-coding genes and miRNAs. We comprehensively analyzed, by using an integrative regulatory network, how cooperation among epigenetic, transcriptional, and post-transcriptional regulations came about. Results We observed extensive cooperation of epigenetic marks on local functional elements and complex epigenetic patterns corresponding to different biological functions. By identifying the significantly epigenetic state-modified motifs, we found that multiple combinations of epigenetic states were associated with a specific type of motif. Interestingly, miRNA-mediated motifs were linked to stable epigenetic states of downstream targets. Changes in epigenetic states of downstream targets in miRNA-mediated motifs can buffer the effects of upstream regulator on target genes, suggesting that miRNA-mediated motifs require the cooperation of epigenetic marks. Conclusions Overall, epigenetic marks are involved in the running of regulatory motifs in the way traffic lights control traffic flows and hence should be part of the architecture of complex regulatory circuits. General significance We demonstrated a detailed analysis of the cooperation of multiple epigenetic marks and how epigenetic regulation was organized into a human regulatory network. The findings form a basis for further understanding of the complicated roles of epigenetic marks on regulatory circuits.

e16635 Background: Surgical resection is a common curative treatment for patients with primary hepatocellular carcinoma (HCC), and conventional strategies of assessing clinical and pathologic risk factors have been adopted to predict clinic outcomes in patients after curative surgery. We hypothesized that an ensemble learning approach which incorporates multidimensional features would enable effective prediction of patient survival. Methods: We analyzed data from 222 stage II-III HCC patients who underwent surgical resection at Eastern Hepatobiliary Surgery Hospital (Shanghai, China). Baseline information for each patient includes clinical and pathologic risk factors, laboratory tests and in situ immunological profiles. Using machine learning, we developed CoxPH, GBS, CGBS, FSVM and NSVM models for patient overall survival (OS). Models were trained on 155 cases with 48 features. Thirteen-fold cross-validation (CV) was used to measure performance with area under the ROC curve (AUC) and C-Index (CI). The ensemble model was used to predict patient OS and validated on the subsequent 67 cases. Results: For all models tested, immune features, including the fraction of CD68+ and CD8+ cells in tumor, and CD8+ cells in stroma, play a crucial role in predicting patient OS. Using the ensemble CoxPH model (with superior value of AUC and CI), a risk scoring system for patient OS was developed. The scoring system could stratify patients into high-risk or low-risk groups, revealing different prognosis (validation cohort: HR, 6.5, 95% CI, 2.4-18, P = 3.4e-05). The CoxPH model was also predictive of the time to-recurrence (p < 0.0001). In validation set, the scoring system predicted half-year mortality of patients with AUC of 0.9, and 1-year mortality of patients with AUC of 0.897. The scoring system could also predict half-year recurrence and 1-year recurrence with AUC more than 0.83. Conclusions: The machine learning-based risk scoring system offers a novel strategy for incorporating multidimensional risk factors to predict clinic outcome and may help medical practitioners to optimize clinical follow-up or therapeutic interventions. [Table: see text]

4080 Background: Microsatellite instability high (MSI-H)/mismatch-repair-deficient (dMMR) has been proved as a validated biomarker in solid tumors receiving immune checkpoint inhibitors (ICIs). Recently, mutational status of the DNA damage repair (DDR) genes has been linked to anti-tumor immune response in bladder cancer. Therefore, it would be of great interest to unravel the implications of DDR in shaping the immune responsiveness in CRC. Methods: The genomic correlates were examined in a publicly available cohort from Memorial Sloan Kettering Cancer Center (MSK ICI cohort). To explore the associations between DDR mutation and immune features, the genomic data of The Cancer Genome Atlas (TCGA) colorectal adenocarcinoma (COADREAD) dataset was analyzed. Further, we determined DDR mutation and MSI status in a Chinese CRC cohort via a 543-gene panel sequencing. Results: First, we observed that DDR pathway was commonly mutated (21.79%) in the multi-cancer MSK ICI cohort, with the highest frequency of 36.36% in CRCs. Second, survival analysis revealed that the median overall survival (mOS) in patients with DDR mutations was significantly longer than that in the DDR wild-type subgroup, in both pan-cancer (P = 0.0008; mOS 31 vs 16 months) and CRC patients (P = 0.016; mOS 34 vs 13 months) in the MSK ICI cohort. However, in the TCGA COADREAD dataset, there was no significant difference in OS or progression free survival (PFS) between DDR mutant and DDR wild-type subgroups. These observation indicated a specific prognostic value for DDR mutation in patients with ICI treatment while not conventional treatment. Third, in the TCGA COADREAD dataset, DDR mutations were associated with increased TMB, enrichment of immune cell infiltration and immune checkpoint molecule expression, suggesting an improvement of various steps of the cancer immunity cycles in DDR mutant CRCs. Lastly, we investigated the DDR mutational pattern, and its associations with MSI-H and other genomic features in a Chinese CRC cohort. Notably, MSI-H and DDR mutation account for 5.7% and 13.4% respectively, suggesting that DDR may identify a higher proportion of potential responders than MSI-H. Conclusions: Our data suggest that DDR mutation is a potential prognostic biomarker for ICI-treated CRCs. Functional analysis in TCGA dataset revealed that DDR mutation might be an indication of enhanced cancer immunity. The higher incidence of DDR mutation in Chinese CRCs emphasized the future utility of panel-based DDR evaluation in guiding ICI treatment.

The swamp dike-pond complex (SDPC) is a mode of ecological restoration in coal-mining subsidence areas in China that consists of an engineered swamp and an engineered dike-pond. The aim of this study is to compare conventional reclamation and ecological restoration systems by performing emergy analysis. The analysed systems included an SDPC and contrasting fish ponds (CFP) in a stabilized subsidence area and an SDPC in a submergence area that can be used as a transition system during the course of the succession of coal-mining subsidence areas. Indices, ratios and ternary diagrams based on emergy can be used to assess the behaviours of the three systems. Emergy analysis was well suited for this task because it was capable of converting all energies, materials and information to a common unit of quality to allow for deep comparisons across the three systems. The results show that the SDPC was most dependent upon renewable resources, and efforts were made to maintain the natural mechanisms of energy and matter flow regulation as much as possible. Therefore, the SDPC has greater emergy efficiency in terms of biological energy use and the level of environmental loading. The CFP was more dependent on the fraction of purchased inputs and nonrenewable inputs from the outside. The sustainability index values for the three systems ranged from 0.82 for the CFP in the stabilized subsidence area to 4.31 for the SDPC in the submergence area and 9.12 for the SDPC in the stabilized subsidence area. The results confirm that the SDPC is less stressful on the environment and more sustainable than the CFP in coal-mining subsidence areas. In addition, the respective ecosystem service values for each system were 1.52E + 17 sej/yr/ha for the SDPC in the stabilized subsidence area and 2.90E + 16 sej/yr/ha for the SDPC in the submergence area, which were 10.1 and 1.9 times higher than the value for the CFP, respectively. This research suggests that vegetation, faunal communities and functional hydrology, which support the entire ecosystem via the food web, can be restored in the SDPC, and restored wetlands can provide economic and ecological benefits via the return of their ecological services and functions. Endangered and rare species, such as Baer's pochard (Aythya baeri) and reed parrotbill (Paradoxornis heudei), were found in this area, and the prospects of such species depend on future restoration policies in coal-mining subsidence areas in China. To safeguard biodiversity, SDPCs should be preferred over other reclamation methods. This work will inform environmental policy making and be used to recommend better management practices to the government.

Long non-coding RNAs (lncRNAs) constitute an important layer of chromatin regulation that contributes to various biological processes and diseases. By interacting with chromatin, many lncRNAs can regulate that state of chromatin by recruiting chromatin-modifying complexes and thus control large-scale gene expression programs. However, the available information on interactions between lncRNAs and chromatin is hidden in a large amount of dispersed literature and has not been extensively collected. We established the LnChrom database, a manually curated resource of experimentally validated lncRNA–chromatin interactions. The current release of LnChrom includes 382 743 interactions in human and mouse. We also manually collected detailed metadata for each interaction pair, including those of chromatin modifying factors, epigenetic marks and disease associations. LnChrom provides a user-friendly interface to facilitate browsing, searching and retrieving of lncRNA–chromatin interaction data. Additionally, a large amount of multi-omics data was integrated into LnChrom to aid in characterizing the effects of lncRNA–chromatin interactions on epigenetic modifications and transcriptional expression. We believe that LnChrom is a timely and valuable resource that can greatly motivate mechanistic research into lncRNAs. Database URL: http://biocc.hrbmu.edu.cn/LnChrom/