Chromatin accessibility complex subunit 1 enhances tumor growth by regulating the oncogenic transcription of YAP in breast and cervical cancer.

Background: As a component of chromatin remodeling complex, chromatin accessibility complex subunit 1 (CHRAC1) is critical in transcription and DNA replication. However, the significance of CHRAC1 in cancer progression has not been investigated extensively. This research aimed to determine the function of CHRAC1 in breast and cervical cancer and elucidate the molecular mechanism. Methods: The Bio-ID method was used to identify the interactome of transcriptional activator Yes-associated protein (YAP) and the binding between YAP and CHRAC1 was verified by immunofluorescence. CCK8, colony formation and subcutaneous xenograft assays were conducted to explore the function of CHRAC1 in cancer cell proliferation. RNA-seq analysis and RT-PCR were used to analyze the transcription program change after CHRAC1 ablation. The diagnostic value of CHRAC1 was analyzed by TCGA database and further validated by immunohistochemistry staining. Results: In the current study, we found that the chromatin remodeler CHRAC1 was a potential YAP interactor. CHRAC1 depletion suppressed breast and cervical cancer cell proliferation and tumor growth. The potential mechanism may be that CHRAC1 interacts with YAP to facilitate oncogenic transcription of YAP target genes in Hippo pathway, thereby promoting tumorigenesis. CHRAC1 was elevated in cervical and breast cancer biopsies and the upregulation correlated with shorter survival, poor pathological stages and metastasis of cancer patients. Moreover, CHRAC1 expression was statistically associated with YAP in breast and cervical cancer biopsies. Conclusions: These findings highlight that CHRAC1 contributes to cancer progression through regulating the oncogenic transcription of YAP, which makes it a potential therapeutic target for cancer treatment.

CB[8]- and triarylboron-based supramolecular organic framework for microRNA detection, tumor-targeted drug delivery, and photodynamic therapy.

Supramolecular organic frameworks (SOFs) are widely used for biological detection and drug delivery. In this study, a SOF system was fabricated through the self-assembly of photosensitive triarylboron (TAB), TAB-6-methyl, and CB[8]. The maximum fluorescence emission of TAB-6-methyl was greatly enhanced and red-shifted from 560 nm to 610 nm after SOF formation. The SOF can specifically respond to a microRNA by dissembling and then combining with microRNA, which is accompanied by a fluorescence shift from 610 nm to 560 nm, thus providing a ratiometric readout for microRNA detection. The photosensitivity of TAB-6-methyl can be further improved by forming a SOF, which can be used in photodynamic therapy. By constructing another guest molecule, TAB-5-1-cRGD, we successfully embedded cRGD in the SOF system to improve its tumor-targeting ability. Moreover, we used this SOF system as a fluorescence imaging probe for targeted tumor imaging and as a drug carrier system for loading DOX to achieve combined photodynamic and chemotherapy treatment of tumors.

Lysophosphatidic acid responsive photosensitive supramolecular organic frameworks for tumor imaging, drug loading, and photodynamic therapy.

Supramolecular organic frameworks have been widely applied for biological detection and drug delivery. In this study, a supramolecular organic framework (SOF) is constructed through the self-assembly of a highly photosensitive triarylphosphine oxide guest molecule, OTPP-6-Methyl, with cucurbit [8] uril (CB [8]). The formation of the SOF gradually enhances the weak fluorescence of OTPP-6-Methyl owing to the restriction of the molecular folding motion. Although the high positive charge of OTPP-6-Methyl facilitates binding to various negatively charged substances, the SOF system only demonstrated an obvious fluorescence response to LPA, a biomarker of ovarian cancer, via the disassembly of SOF and subsequent binding of OTPP-6-Methyl with LPA. The fluorescence changes during the entire process are insufficient to allow the sensitive detection of LPA; thus, we further designed a FRET system by introducing Cy5, which can act as an energy receptor to achieve a ratiometric readout for LPA. The tumor-targeting cRGD group was introduced into the SOF system as part of another guest molecule, OTPP-5-M-1-cRGD, to improve the tumor-targeting ability of the SOF system. The SOF system further improves the photosensitivity of guest molecules, and is therefore used in the in vivo imaging of ovarian cancer subcutaneous tumors and as a DDS for loading DOX for the combined in vivo chemotherapy and photodynamic treatment of tumors.

Aggregation-induced type I&II photosensitivity and photodegradability-based molecular backbones for synergistic antibacterial and cancer phototherapy via photodynamic and photothermal therapies.

The clinical applications of phototherapy nanomaterials are still limited due to concerns regarding their phototoxicity and efficacy. Herein, we report a novel type of D-π-A molecular backbone that induces type I/II photosensitivity and photodegradability by forming J-aggregates. The photodegradation rate can be regulated by changing the donor groups to regulate the photosensitivity of their aggregates because the photodegradability performance results from their oxidation by 1O2 generated by their type II photosensitivity. AID4 NPs possess faster photodegradation because of their better type I&II photosensitivity, which can also self-regulate by inhibiting type II and improving type I under hypoxic conditions. Moreover, they exhibited good photothermal and photoacoustic performance for improving their therapeutic effect by a synergistic effect and achieving photoacoustic imaging in vivo. The experimental result also showed that they can be effective for antibacterial and anti-tumor treatment and the photodegradation products of AID4 NPs possess low biological toxicity in the dark or under light. This study could provide a novel strategy for improving the safety and treatment effects of phototherapy.

Machine learning algorithms for predicting the risk of fracture in patients with diabetes in China.

Background: Patients with diabetes are more likely to be predisposed to fractures compared to those without diabetes. In clinical practice, predicting fracture risk in diabetics is still difficult because of the limited availability and accessibility of existing fracture prediction tools in the diabetic population. The purpose of this study was to develop and validate models using machine learning (ML) algorithms to achieve high predictive power for fracture in patients with diabetes in China. Methods: In this study, the clinical data of 775 hospitalized patients with diabetes was analyzed by using Decision Tree (DT), Gradient Boosting Decision Tree (GBDT), Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost) and Probabilistic Classification Vector Machines (PCVM) algorithms to construct risk prediction models for fractures. Moreover, the risk factors for diabetes-related fracture were identified by the feature selection algorithms. Results: The ML algorithms extracted 17 most relevant factors from raw clinical data to maximize the accuracy of the prediction results, including bone mineral density, age, sex, weight, high-density lipoprotein cholesterol, height, duration of diabetes, total cholesterol, osteocalcin, N-terminal propeptide of type I, diastolic blood pressure, and body mass index. The 7 ML models including LR, SVM, RF, DT, GBDT, XGBoost, and PCVM had f1 scores of 0.75, 0.83, 0.84, 0.85, 0.87, 0.88, and 0.97, respectively. Conclusions: This study identified 17 most relevant risk factors for diabetes-related fracture using ML algorithms. And the PCVM model proved to perform best in predicting the fracture risk in the diabetic population. This work proposes a cheap, safe, and extensible ML algorithm for the precise assessment of risk factors for diabetes-related fracture.

Leveraging epigenomes and three-dimensional genome organization for interpreting regulatory variation.

Understanding the impact of regulatory variants on complex phenotypes is a significant challenge because the genes and pathways that are targeted by such variants and the cell type context in which regulatory variants operate are typically unknown. Cell-type-specific long-range regulatory interactions that occur between a distal regulatory sequence and a gene offer a powerful framework for examining the impact of regulatory variants on complex phenotypes. However, high-resolution maps of such long-range interactions are available only for a handful of cell types. Furthermore, identifying specific gene subnetworks or pathways that are targeted by a set of variants is a significant challenge. We have developed L-HiC-Reg, a Random Forests regression method to predict high-resolution contact counts in new cell types, and a network-based framework to identify candidate cell-type-specific gene networks targeted by a set of variants from a genome-wide association study (GWAS). We applied our approach to predict interactions in 55 Roadmap Epigenomics Mapping Consortium cell types, which we used to interpret regulatory single nucleotide polymorphisms (SNPs) in the NHGRI-EBI GWAS catalogue. Using our approach, we performed an in-depth characterization of fifteen different phenotypes including schizophrenia, coronary artery disease (CAD) and Crohn's disease. We found differentially wired subnetworks consisting of known as well as novel gene targets of regulatory SNPs. Taken together, our compendium of interactions and the associated network-based analysis pipeline leverages long-range regulatory interactions to examine the context-specific impact of regulatory variation in complex phenotypes.

Inference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets.

Cell type-specific gene expression patterns are outputs of transcriptional gene regulatory networks (GRNs) that connect transcription factors and signaling proteins to target genes. Single-cell technologies such as single cell RNA-sequencing (scRNA-seq) and single cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq), can examine cell-type specific gene regulation at unprecedented detail. However, current approaches to infer cell type-specific GRNs are limited in their ability to integrate scRNA-seq and scATAC-seq measurements and to model network dynamics on a cell lineage. To address this challenge, we have developed single-cell Multi-Task Network Inference (scMTNI), a multi-task learning framework to infer the GRN for each cell type on a lineage from scRNA-seq and scATAC-seq data. Using simulated and real datasets, we show that scMTNI is a broadly applicable framework for linear and branching lineages that accurately infers GRN dynamics and identifies key regulators of fate transitions for diverse processes such as cellular reprogramming and differentiation.

Isothermal amplification based on specific signal extraction and output for fluorescence and colorimetric detection of nucleic acids.

Due to the complexity of compositions and low abundance of target in clinical sample, nucleic acids detection often suffers from false positives caused by nonspecific amplification. In in vitro diagnosis (IVD), PCR usually employ TaqMan probe to report specific signals and block false positive signals. However, nucleic acid isothermal amplifications, such as loop-mediated isothermal amplification (LAMP), lack of mature specific signal output mechanism, which prevents them from being used for IVD and point-of-care testing (POCT). In this work, we constructed a specific signal extract-to-output isothermal detection system (SSEI). SSEI contains a well-designed DNA probe for specific signal extraction and output in LAMP. This probe is a double-stranded DNA with an overhang sequence and named as extract-to-output probe (ETO probe). ETO probe can recognize the target-specific intermediate products in LAMP and release another signal-output probe (OP) to report the target-specific signals. With these unique properties, SSEI can detect as low as 10 copies of target DNA per reaction either by fluorescence detector or naked eyes. Moreover, due to the excellent performance against background nucleic acids interference, this biosensing platform had been successfully used for hepatitis B virus (HBV) clinical samples detection.

Molecular-engineered highly photosensitive triarylphosphine oxide compounds for apoptosis imaging and selectively inducing apoptosis of tumor cells by photodynamic therapy.

Although photodynamic therapy (PDT) has wide applications, tumor-targeting probes with high photosensitivity or apoptosis-monitoring capability, which possess low phototoxicity and can be used for evaluating therapeutic efficacy, are still scarce. In this study, we constructed a series of highly photosensitive probes by introducing multivalent positive charges around propeller-like triarylphosphine oxide compounds. Some of them can be used to detect apoptosis by selectively entering apoptotic cells in the presence of living or necrotic cells. Among them, OTPP-6-Amyl can target SKOV-3 cells by binding to their membrane in a short time and move to mitochondria with prolonging time and can be further applied for imaging SKOV-3 tumors in vivo, whereas for various apoptotic cells, it mainly enters the nucleus. Its high photosensitivity can be used to induce apoptosis in SKOV-3 cells without affecting the survival of other cells. By functionalizing with cRGD, another probe was constructed to target U87MG cells and induce their apoptosis by PDT, and it can also pass through the blood-brain barrier.

Triarylboron-Based High Photosensitive Probes for Apoptosis Detection, Tumor-Targeted Imaging, and Selectively Inducing Apoptosis of Tumor Cells by Photodynamics.

Herein, a series of triarylboron-based fluorescent probes were developed for distinguishing apoptosis from living cells and even necrosis. They also demonstrate high photosensitivity because they can produce detectable reactive oxygen species (ROS) under an ultra-low light power density (1.5 mW/cm2). By changing the peripheral groups to regulate the performance, we identified a multifunctional probe, TAB-6-amyl, which can be used not only for selectively imaging apoptosis but also for the targeted imaging of SKOV-3 cells in vitro and in vivo. It could further specifically induce the apoptosis of SKOV-3 cells under light irradiation. During the study, we also found that TAB-6-amyl can cross the blood-brain barrier (BBB). Therefore, another probe based on this kind of structure, TAB-5-M-1-cRGD, was constructed for the targeted imaging of brain glioma cells and inducing their apoptosis. This study offers some promising tools for apoptosis detection and tumor photodynamic therapy (PDT).

Enabling Studies of Genome-Scale Regulatory Network Evolution in Large Phylogenies with MRTLE.

Transcriptional regulatory networks specify context-specific patterns of genes and play a central role in how species evolve and adapt. Inferring genome-scale regulatory networks in non-model species is the first step for examining patterns of conservation and divergence of regulatory networks. Transcriptomic data obtained under varying environmental stimuli in multiple species are becoming increasingly available, which can be used to infer regulatory networks. However, inference and analysis of multiple gene regulatory networks in a phylogenetic setting remains challenging. We developed an algorithm, Multi-species Regulatory neTwork LEarning (MRTLE), to facilitate such studies of regulatory network evolution. MRTLE is a probabilistic graphical model-based algorithm that uses phylogenetic structure, transcriptomic data for multiple species, and sequence-specific motifs in each species to simultaneously infer genome-scale regulatory networks across multiple species. We applied MRTLE to study regulatory network evolution across six ascomycete yeasts using transcriptomic measurements collected across different stress conditions. MRTLE networks recapitulated experimentally derived interactions in the model organism S. cerevisiae as well as non-model species, and it was more beneficial for network inference than methods that do not use phylogenetic information. We examined the regulatory networks across species and found that regulators associated with significant expression and network changes are involved in stress-related processes. MTRLE and its associated downstream analysis provide a scalable and principled framework to examine evolutionary dynamics of transcriptional regulatory networks across multiple species in a large phylogeny.

Response of surface water quality characteristics to socio-economic factors in Eastern-Central China.

Following the implementation of the strictest water resource management system in China, it has become increasingly important to understand and improve the surface water quality and the rate at which water function zones reach the water quality standard. Based on the monthly monitoring data from 450 monitoring sites at the provincial borders of 27 provinces in China in 2019, the overall surface water quality at provincial boundaries in China was evaluated. The Canadian Council of Ministers of the Environment-water quality index (CCME-WQI) showed that the provincial boundary water quality exceeded the fair level, and F1 was the most influential factor. Then, 27 factors that directly or indirectly affect the surface water quality were identified, and the indirect influencing factors were integrated into the ecological environmental quality index and human activities quantitative index. Finally, the 27 factors were integrated into six factors, and the relationship between these indicators and CCME-WQI as well as the concentration of influencing elements with respect to regulatory standard limits were analyzed. The proportion of building land was the most significant factor affecting the quality of the aquatic environment in provincial boundaries. In addition, the economic development level, proportion of farmland, and degree of social development were identified as significant influencing factors. The six factors have different degrees of impact on the concentrations of major elements with respect to standard limits. This study basically explores water resource management and offers significant reference and guidelines for the improvement of the quality of surface water at provincial boundaries in China.

Health and ecotoxicological risk assessment for human and aquatic organism exposure to polycyclic aromatic hydrocarbons in the Baiyangdian Lake.

Seasonal and regional distributions of 17 polycyclic aromatic hydrocarbons (PAHs) in surface waters from four different main water functional regions of the Baiyangdian Lake were analyzed through GC/MS/MS during spring and summer season. The aim was to identify their possible pollution sources and evaluate their health risk for human and ecotoxicological risk for aquatic organisms. Results showed that the range of total PAH concentration is 35.38-88.06 ng/L (average 46.57 ng/L) in spring and 25.64-301.41 ng/L (average 76.23 ng/L) in summer. PAH contamination was observed slightly lower in the summer season from the pollution characteristics of water bodies in most areas of the Baiyangdian Lake, and the levels of PAH pollution in the water body of urban residential regions and rural residential regions were relatively higher than those in tourist regions and low human disturbance regions. Source analysis based on diagnostic ratios confirmed that combustion sources and petroleum sources were two main sources for PAHs entering into the waters of the Baiyangdian Lake. Human health risk assessment showed that PAHs in surface waters from the Baiyangdian Lake will not cause a potential non-carcinogenic risk to local residents and the carcinogenic risk could mostly be accepted, but the potential lifetime carcinogenic risk for infants in rural residential regions should be concerned about. Urban residential regions and rural residential regions were subject to higher cumulative non-carcinogenic and carcinogenic risk when compared to the other functional regions. Ecotoxicological risk assessment found a moderate risk to aquatic organisms presented by individual PAH and a low risk by total PAHs, and PAHs in the water body of urban residential regions and rural residential regions also have relatively higher harm effects to aquatic organisms compared with the other two functional regions. This study revealed the pollution characteristics of PAHs and their possible sources in waters of the Baiyangdian Lake, clarified its correlation to regional anthropogenic activities, and provided corresponding risk management strategies for human and aquatic organisms.

Data integration for inferring context-specific gene regulatory networks.

Transcriptional regulatory networks control context-specific gene expression patterns and play important roles in normal and disease processes. Advances in genomics are rapidly increasing our ability to measure different components of the regulation machinery at the single-cell and bulk population level. An important challenge is to combine different types of regulatory genomic measurements to construct a more complete picture of gene regulatory networks across different disease, environmental, and developmental contexts. In this review, we focus on recent computational methods that integrate regulatory genomic data sets to infer context specificity and dynamics in regulatory networks.

ABC-GWAS: Functional Annotation of Estrogen Receptor-Positive Breast Cancer Genetic Variants.

Over the past decade, hundreds of genome-wide association studies (GWAS) have implicated genetic variants in various diseases, including cancer. However, only a few of these variants have been functionally characterized to date, mainly because the majority of the variants reside in non-coding regions of the human genome with unknown function. A comprehensive functional annotation of the candidate variants is thus necessary to fill the gap between the correlative findings of GWAS and the development of therapeutic strategies. By integrating large-scale multi-omics datasets such as the Cancer Genome Atlas (TCGA) and the Encyclopedia of DNA Elements (ENCODE), we performed multivariate linear regression analysis of expression quantitative trait loci, sequence permutation test of transcription factor binding perturbation, and modeling of three-dimensional chromatin interactions to analyze the potential molecular functions of 2,813 single nucleotide variants in 93 genomic loci associated with estrogen receptor-positive breast cancer. To facilitate rapid progress in functional genomics of breast cancer, we have created "Analysis of Breast Cancer GWAS" (ABC-GWAS), an interactive database of functional annotation of estrogen receptor-positive breast cancer GWAS variants. Our resource includes expression quantitative trait loci, long-range chromatin interaction predictions, and transcription factor binding motif analyses to prioritize putative target genes, causal variants, and transcription factors. An embedded genome browser also facilitates convenient visualization of the GWAS loci in genomic and epigenomic context. ABC-GWAS provides an interactive visual summary of comprehensive functional characterization of estrogen receptor-positive breast cancer variants. The web resource will be useful to both computational and experimental biologists who wish to generate and test their hypotheses regarding the genetic susceptibility, etiology, and carcinogenesis of breast cancer. ABC-GWAS can also be used as a user-friendly educational resource for teaching functional genomics. ABC-GWAS is available at http://education.knoweng.org/abc-gwas/.

Piperazine multi-substituted triarylphosphine oxide compound as an instant "light-up" fluorescent probe for monoamine oxidase.

Monoamine oxidase (MAOs) is involved in several psychiatric and neurological disorders. The specific detection of MAOs is of great significance to elucidate their functions in various biological processes. Currently, however, fast detection of MAOs remains a great challenge. It is, therefore, important to develop novel fluorescent probes for the monitoring of intracellular MAO activity. In this study, we synthesized OTPP-3-Piperazine and OTNP-3-Piperazine by functionalizing triarylphosphine with piperazine groups for MAO detection, using the rational design ofmolecular structures. OTNP-3-Piperazine demonstrated higher sensitivity to MAOs than OTPP-3-Piperazine because MAOs induced an AIE process via oxidation to produce water-insoluble oxidation products in OTNP-3-Piperazine. Such a recognition mechanism instantly responded to MAOs. OTNP-3-Piperazine was also introduced into different cells to explore its application as a biological probe. These results showed that it differentiated MAO-overexpressing cells from other cells, which demonstrated its promise as a biological fluorescent probe.

In silico prediction of high-resolution Hi-C interaction matrices.

The three-dimensional (3D) organization of the genome plays an important role in gene regulation bringing distal sequence elements in 3D proximity to genes hundreds of kilobases away. Hi-C is a powerful genome-wide technique to study 3D genome organization. Owing to experimental costs, high resolution Hi-C datasets are limited to a few cell lines. Computational prediction of Hi-C counts can offer a scalable and inexpensive approach to examine 3D genome organization across multiple cellular contexts. Here we present HiC-Reg, an approach to predict contact counts from one-dimensional regulatory signals. HiC-Reg predictions identify topologically associating domains and significant interactions that are enriched for CCCTC-binding factor (CTCF) bidirectional motifs and interactions identified from complementary sources. CTCF and chromatin marks, especially repressive and elongation marks, are most important for HiC-Reg's predictive performance. Taken together, HiC-Reg provides a powerful framework to generate high-resolution profiles of contact counts that can be used to study individual locus level interactions and higher-order organizational units of the genome.

The Cancer-Associated Genetic Variant Rs3903072 Modulates Immune Cells in the Tumor Microenvironment.

Genome-wide association studies (GWAS) have hitherto identified several germline variants associated with cancer susceptibility, but the molecular functions of these risk modulators remain largely uncharacterized. Recent studies have begun to uncover the regulatory potential of noncoding GWAS SNPs using epigenetic information in corresponding cancer cell types and matched normal tissues. However, this approach does not explore the potential effect of risk germline variants on other important cell types that constitute the microenvironment of tumor or its precursor. This paper presents evidence that the breast-cancer-associated variant rs3903072 may regulate the expression of CTSW in tumor-infiltrating lymphocytes. CTSW is a candidate tumor-suppressor gene, with expression highly specific to immune cells and also positively correlated with breast cancer patient survival. Integrative analyses suggest a putative causative variant in a GWAS-linked enhancer in lymphocytes that loops to the 3' end of CTSW through three-dimensional chromatin interaction. Our work thus poses the possibility that a cancer-associated genetic variant could regulate a gene not only in the cell of cancer origin but also in immune cells in the microenvironment, thereby modulating the immune surveillance by T lymphocytes and natural killer cells and affecting the clearing of early cancer initiating cells.

A novel triarylboron based ratiometric fluorescent probe for in vivo targeting and specific imaging of cancer cells expressing abnormal concentration of GGT.

Abnormal expression of γ-glutamyltranspeptidase (GGT) in living organisms is closely associated with tumorigenesis. However, few reported fluorescence probes can specifically respond to abnormal concentration of GGT. Here, by functionalizing triarylboron moiety with three GGT-specific substrate (GSH) units, a novel fluorescence probe, TAB-3-GSH, was developed for detecting GGT. The results showed that TAB-3-GSH selectively responds to abnormally high levels of GGT (100-1000 U/L) rather than to normal GGT levels (<100 U/L) with ratiometric readout, since the amide linkage can be further hydrolyzed under high GGT levels. TAB-3-GSH was also capable of differentiating GGT-overexpressing ovarian cancer cells from normal cells, because of an improvement in the probe's cell membrane permeability upon reaction with GGT. Moreover, the probe could achieve selective imaging of SKOV-3 tumor site in xenograft mice model. Thus, TAB-3-GSH is a promising probe for tumor targeting in vivo.

A triarylboron-based binuclear Zn(II) complex as a two-photon fluorescent probe for simultaneous multicolor imaging of the cell membrane, endoplasmic reticulum, and nucleolus.

The visualization of subcellular structures is critical for understanding their intracellular function. We prepared two triarylboron-based multinuclear Zn2+ complexes, TAB-1-3Zn2+ and TAB-2-2Zn2+, which can be used as fluorescent probes for nucleoside polyphosphate (NPP) and RNA because their multi Zn2+ center can selectively combine with the phosphate side chain of NPP or RNA, accompanied by a corresponding fluorescence change. Among them, TAB-2-2Zn2+ is more suitable than TAB-1-3Zn2+ for live cell imaging because of its excellent cell membrane permeability resulting from amphiphilicity. Since the various membrane structures in cells are also composed of phosphoric acid bilayers, TAB-2-2Zn2+ may also be used to image various membrane structures. Various colocalization experiments further confirmed that TAB-2-2Zn2+ can achieve clear simultaneous imaging of the cell membrane, the endoplasmic reticulum, and the nucleolus. Graphical abstract.