Network modeling links breast cancer susceptibility and centrosome dysfunction

Luteinizing Hormone Receptor Mutation (LHRN316S) Causes Abnormal Follicular Development Revealed by Follicle Single-Cell Analysis and CRISPR/Cas9

Abnormal interaction between granulosa cells and oocytes causes disordered development of ovarian follicles. However, the interactions between oocytes and cumulus granulosa cells (CGs), oocytes and mural granulosa cells (MGs), and CGs and MGs remain to be fully explored. Using single-cell RNA-sequencing (scRNA-seq), we determined the transcriptional profiles of oocytes, CGs and MGs in antral follicles. Analysis of scRNA-seq data revealed that CGs may regulate follicular development through the BMP15-KITL-KIT-PI3K-ARF6 pathway with elevated expression of luteinizing hormone receptor (LHR). Because internalization of the LHR is regulated by Arf6, we constructed LHRN316S mice by CRISPR/Cas9 to further explore mechanisms of follicular development and novel treatment strategies for female infertility. Ovaries of LHRN316S mice exhibited reduced numbers of corpora lutea and ovulation. The LHRN316S mice had a reduced rate of oocyte maturation in vitro and decreased serum progesterone levels. Mating LHRN316S female mice with ICR wild type male mice revealed that the infertility rate of LHRN316S mice was 21.4% (3/14). Litter sizes from LHRN316S mice were smaller than those from control wild type female mice. The oocytes from LHRN316S mice had an increased rate of maturation in vitro after progesterone administration in vitro. Furthermore, progesterone treated LHRN316S mice produced offspring numbers per litter equivalent to WT mice. These findings provide key insights into cellular interactions in ovarian follicles and provide important clues for infertility treatment.

Molecular Mechanisms Linking Genes and Vitamins of the Complex B Related to One-Carbon Metabolism in Breast Cancer: An In Silico Functional Database Study

Carcinogenesis is closely related to the expression, maintenance, and stability of DNA. These processes are regulated by one-carbon metabolism (1CM), which involves several vitamins of the complex B (folate, B2, B6, and B12), whereas alcohol disrupts the cycle due to the inhibition of folate activity. The relationship between nutrients related to 1CM (all aforementioned vitamins and alcohol) in breast cancer has been reviewed. The interplay of genes related to 1CM was also analyzed. Single nucleotide polymorphisms located in those genes were selected by considering the minor allele frequency in the Caucasian population and the linkage disequilibrium. These genes were used to perform several in silico functional analyses (considering corrected p-values < 0.05 as statistically significant) using various tools (FUMA, ShinyGO, and REVIGO) and databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) and GeneOntology (GO). The results of this study showed that intake of 1CM-related B-complex vitamins is key to preventing breast cancer development and survival. Also, the genes involved in 1CM are overexpressed in mammary breast tissue and participate in a wide variety of biological phenomena related to cancer. Moreover, these genes are involved in alterations that give rise to several types of neoplasms, including breast cancer. Thus, this study supports the role of one-carbon metabolism B-complex vitamins and genes in breast cancer; the interaction between both should be addressed in future studies.

Antileukemic potential of methylated indolequinone MAC681 through immunogenic necroptosis and PARP1 degradation

BACKGROUND

Despite advancements in chronic myeloid leukemia (CML) therapy with tyrosine kinase inhibitors (TKIs), resistance and intolerance remain significant challenges. Leukemia stem cells (LSCs) and TKI-resistant cells rely on altered mitochondrial metabolism and oxidative phosphorylation. Targeting rewired energy metabolism and inducing non-apoptotic cell death, along with the release of damage-associated molecular patterns (DAMPs), can enhance therapeutic strategies and immunogenic therapies against CML and prevent the emergence of TKI-resistant cells and LSC persistence.

METHODS

Transcriptomic analysis was conducted using datasets of CML patients' stem cells and healthy cells. DNA damage was evaluated by fluorescent microscopy and flow cytometry. Cell death was assessed by trypan blue exclusion test, fluorescent microscopy, flow cytometry, colony formation assay, and in vivo Zebrafish xenografts. Energy metabolism was determined by measuring NAD+ and NADH levels, ATP production rate by Seahorse analyzer, and intracellular ATP content. Mitochondrial fitness was estimated by measurements of mitochondrial membrane potential, ROS, and calcium accumulation by flow cytometry, and morphology was visualized by TEM. Bioinformatic analysis, real-time qPCR, western blotting, chemical reaction prediction, and molecular docking were utilized to identify the drug target. The immunogenic potential was assessed by high mobility group box (HMGB)1 ELISA assay, luciferase-based extracellular ATP assay, ectopic calreticulin expression by flow cytometry, and validated by phagocytosis assay, and in vivo vaccination assay using syngeneic C57BL/6 mice.

RESULTS

Transcriptomic analysis identified metabolic alterations and DNA repair deficiency signatures in CML patients. CML patients exhibited enrichment in immune system, DNA repair, and metabolic pathways. The gene signature associated with BRCA mutated tumors was enriched in CML datasets, suggesting a deficiency in double-strand break repair pathways. Additionally, poly(ADP-ribose) polymerase (PARP)1 was significantly upregulated in CML patients' stem cells compared to healthy counterparts. Consistent with the CML patient DNA repair signature, treatment with the methylated indolequinone MAC681 induced DNA damage, mitochondrial dysfunction, calcium homeostasis disruption, metabolic catastrophe, and necroptotic-like cell death. In parallel, MAC681 led to PARP1 degradation that was prevented by 3-aminobenzamide. MAC681-treated myeloid leukemia cells released DAMPs and demonstrated the potential to generate an immunogenic vaccine in C57BL/6 mice. MAC681 and asciminib exhibited synergistic effects in killing both imatinib-sensitive and -resistant CML, opening new therapeutic opportunities.

CONCLUSIONS

Overall, increasing the tumor mutational burden by PARP1 degradation and mitochondrial deregulation makes CML suitable for immunotherapy.

Single-cell multi-omics profiling of human preimplantation embryos identifies cytoskeletal defects during embryonic arrest

Human in vitro fertilized embryos exhibit low developmental capabilities, and the mechanisms that underlie embryonic arrest remain unclear. Here using a single-cell multi-omics sequencing approach, we simultaneously analysed alterations in the transcriptome, chromatin accessibility and the DNA methylome in human embryonic arrest due to unexplained reasons. Arrested embryos displayed transcriptome disorders, including a distorted microtubule cytoskeleton, increased genomic instability and impaired glycolysis, which were coordinated with multiple epigenetic reprogramming defects. We identified Aurora A kinase (AURKA) repression as a cause of embryonic arrest. Mechanistically, arrested embryos induced through AURKA inhibition resembled the reprogramming abnormalities of natural embryonic arrest in terms of the transcriptome, the DNA methylome, chromatin accessibility and H3K4me3 modifications. Mitosis-independent sequential activation of the zygotic genome in arrested embryos showed that YY1 contributed to human major zygotic genome activation. Collectively, our study decodes the reprogramming abnormalities and mechanisms of human embryonic arrest and the key regulators of zygotic genome activation.

Homo cerevisiae-Leveraging Yeast for Investigating Protein-Protein Interactions and Their Role in Human Disease

Understanding how genetic variation affects phenotypes represents a major challenge, particularly in the context of human disease. Although numerous disease-associated genes have been identified, the clinical significance of most human variants remains unknown. Despite unparalleled advances in genomics, functional assays often lack sufficient throughput, hindering efficient variant functionalization. There is a critical need for the development of more potent, high-throughput methods for characterizing human genetic variants. Here, we review how yeast helps tackle this challenge, both as a valuable model organism and as an experimental tool for investigating the molecular basis of phenotypic perturbation upon genetic variation. In systems biology, yeast has played a pivotal role as a highly scalable platform which has allowed us to gain extensive genetic and molecular knowledge, including the construction of comprehensive interactome maps at the proteome scale for various organisms. By leveraging interactome networks, one can view biology from a systems perspective, unravel the molecular mechanisms underlying genetic diseases, and identify therapeutic targets. The use of yeast to assess the molecular impacts of genetic variants, including those associated with viral interactions, cancer, and rare and complex diseases, has the potential to bridge the gap between genotype and phenotype, opening the door for precision medicine approaches and therapeutic development.

GPR19 Coordinates Multiple Molecular Aspects of Stress Responses Associated with the Aging Process

G protein-coupled receptors (GPCRs) play a significant role in controlling biological paradigms such as aging and aging-related disease. We have previously identified receptor signaling systems that are specifically associated with controlling molecular pathologies associated with the aging process. Here, we have identified a pseudo-orphan GPCR, G protein-coupled receptor 19 (GPR19), that is sensitive to many molecular aspects of the aging process. Through an in-depth molecular investigation process that involved proteomic, molecular biological, and advanced informatic experimentation, this study found that the functionality of GPR19 is specifically linked to sensory, protective, and remedial signaling systems associated with aging-related pathology. This study suggests that the activity of this receptor may play a role in mitigating the effects of aging-related pathology by promoting protective and remedial signaling systems. GPR19 expression variation demonstrates variability in the molecular activity in this larger process. At low expression levels in HEK293 cells, GPR19 expression regulates signaling paradigms linked with stress responses and metabolic responses to these. At higher expression levels, GPR19 expression co-regulates systems involved in sensing and repairing DNA damage, while at the highest levels of GPR19 expression, a functional link to processes of cellular senescence is seen. In this manner, GPR19 may function as a coordinator of aging-associated metabolic dysfunction, stress response, DNA integrity management, and eventual senescence.

Identification and validation of novel prognostic biomarkers and therapeutic targets for non-small cell lung cancer

Background: Despite the significant survival benefits of anti-PD-1/PD-L1 immunotherapy, non-small cell lung cancer (NSCLC) remains one of the most common tumors and major causes of cancer-related deaths worldwide. Thus, there is an urgent need to identify new therapeutic targets for this refractory disease.

Methods: In this study, microarray datasets GSE27262, GSE75037, GSE102287, and GSE21933 were integrated by Venn diagram. We performed functional clustering and pathway enrichment analyses using R. Through the STRING database and Cytoscape, we conducted protein-protein interaction (PPI) network analysis and identified the key genes, which were verified by the GEPIA2 and UALCAN portal. Validation of actin-binding protein anillin (ANLN) was performed by quantitative real-time polymerase chain reaction and Western blotting. Additionally, Kaplan-Meier methods were used to compute the survival analyses.

Results: In total, 126 differentially expressed genes were identified, which were enriched in mitotic nuclear division, mitotic cell cycle G2/M transition, vasculogenesis, spindle, and peroxisome proliferator-activated receptor signaling pathway. 12 central node genes were identified in the PPI network complex. The survival analysis revealed that high transcriptional levels were associated with inferior survival in NSCLC patients. The clinical implication of ANLN was further explored; its protein expression showed a gradually increasing trend from grade I to III.

Conclusion: These Key genes may be involved in the carcinogenesis and progression of NSCLC, which may serve as useful targets for NSCLC diagnosis and treatment.

Integrative Analysis of Metabolome and Transcriptome Reveals the Mechanism of Color Formation in Yellow-Fleshed Kiwifruit

During the development of yellow-fleshed kiwifruit (Actinidia chinensis), the flesh appeared light pink at the initial stage, the pink faded at the fastest growth stage, and gradually changed into green. At the maturity stage, it showed bright yellow. In order to analyze the mechanism of flesh color change at the metabolic and gene transcription level, the relationship between color and changes of metabolites and key enzyme genes was studied. In this study, five time points (20 d, 58 d, 97 d, 136 d, and 175 d) of yellow-fleshed kiwifruit were used for flavonoid metabolites detection and transcriptome, and four time points (20 d, 97 d, 136 d, and 175 d) were used for targeted detection of carotenoids. Through the analysis of the content changes of flavonoid metabolites, it was found that the accumulation of pelargonidin and cyanidin and their respective anthocyanin derivatives was related to the pink flesh of young fruit, but not to delphinidin and its derivative anthocyanins. A total of 140 flavonoid compounds were detected in the flesh, among which anthocyanin and 76% of the flavonoid compounds had the highest content at 20 d, and began to decrease significantly at 58 d until 175 d, resulting in the pale-pink fading of the flesh. At the mature stage of fruit development (175 d), the degradation of chlorophyll and the increase of carotenoids jointly led to the change of flesh color from green to yellow, in addition to chlorophyll degradation. In kiwifruit flesh, 10 carotenoids were detected, with none of them being linear carotenoids. During the whole development process of kiwifruit, the content of β-carotene was always higher than that of α-carotene. In addition, β-cryptoxanthin was the most-accumulated pigment in the kiwifruit at 175 d. Through transcriptome analysis of kiwifruit flesh, seven key transcription factors for flavonoid biosynthesis and ten key transcription factors for carotenoid synthesis were screened. This study was the first to analyze the effect of flavonoid accumulation on the pink color of yellow-fleshed kiwifruit. The high proportion of β-cryptoxanthin in yellow-fleshed kiwifruit was preliminarily found. This provides information on metabolite accumulation for further revealing the pink color of yellow-fleshed kiwifruit, and also provides a new direction for the study of carotenoid biosynthesis and regulation in yellow-fleshed kiwifruit.

NetSHy: network summarization via a hybrid approach leveraging topological properties

MOTIVATION

Biological networks can provide a system-level understanding of underlying processes. In many contexts, networks have a high degree of modularity, i.e. they consist of subsets of nodes, often known as subnetworks or modules, which are highly interconnected and may perform separate functions. In order to perform subsequent analyses to investigate the association between the identified module and a variable of interest, a module summarization, that best explains the module's information and reduces dimensionality is often needed. Conventional approaches for obtaining network representation typically rely only on the profiles of the nodes within the network while disregarding the inherent network topological information.

RESULTS

In this article, we propose NetSHy, a hybrid approach which is capable of reducing the dimension of a network while incorporating topological properties to aid the interpretation of the downstream analyses. In particular, NetSHy applies principal component analysis (PCA) on a combination of the node profiles and the well-known Laplacian matrix derived directly from the network similarity matrix to extract a summarization at a subject level. Simulation scenarios based on random and empirical networks at varying network sizes and sparsity levels show that NetSHy outperforms the conventional PCA approach applied directly on node profiles, in terms of recovering the true correlation with a phenotype of interest and maintaining a higher amount of explained variation in the data when networks are relatively sparse. The robustness of NetSHy is also demonstrated by a more consistent correlation with the observed phenotype as the sample size decreases. Lastly, a genome-wide association study is performed as an application of a downstream analysis, where NetSHy summarization scores on the biological networks identify more significant single nucleotide polymorphisms than the conventional network representation.

AVAILABILITY AND IMPLEMENTATION

R code implementation of NetSHy is available at https://github.com/thaovu1/NetSHy.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The importance of RHAMM in the normal brain and gliomas: physiological and pathological roles

Although the literature about the functions of hyaluronan and the CD44 receptor in the brain and brain tumours is extensive, the role of the receptor for hyaluronan-mediated motility (RHAMM) in neural stem cells and gliomas remain poorly explored. RHAMM is considered a multifunctional receptor which performs various biological functions in several normal tissues and plays a significant role in cancer development and progression. RHAMM was first identified for its ability to bind to hyaluronate, the extracellular matrix component associated with cell motility control. Nevertheless, additional functions of this protein imply the interaction with different partners or cell structures to regulate other biological processes, such as mitotic-spindle assembly, gene expression regulation, cell-cycle control and proliferation. In this review, we summarise the role of RHAMM in normal brain development and the adult brain, focusing on the neural stem and progenitor cells, and discuss the current knowledge on RHAMM involvement in glioblastoma progression, the most aggressive glioma of the central nervous system. Understanding the implications of RHAMM in the brain could be useful to design new therapeutic approaches to improve the prognosis and quality of life of glioblastoma patients.

Gene Differential Co-Expression Networks Based on RNA-Seq: Construction and Its Applications

Gene co-expression network (GCN) becomes an increasingly important tool in omics data analysis. A great challenge for GCN construction is that the sample size is far lower than the number of genes. Traditional methods rely on considerable samples. Moreover, association signals are likely weak, nonlinear and stochastic, which are difficult to be identified among thousands of candidates. In this paper, the gray correlation coefficient (GCC) is introduced, and a novel method to construct gene differential co-expression networks (GDCNs) is proposed. Based on the GDCNs, three measures are proposed to explore informative genes. The proposed method can make full use of the information provided by a handful of samples and overcome the shortages of GCNs, which can evaluate the changes of co-expression relationships that are possibly triggered by treatments. Based on RNA-seq data of Brassica napus, GDCNs under multiple experimental conditions are constructed and investigated. It is found that the GCC-based method is very robust to data processing. The GDCNs facilitate the inference of gene functions and the identification of informative genes that are responsible for stress responsiveness. The GDCN-based approaches integrate the 'guilt by association' and the 'guilt by rewiring' rules, which provide alternative tools for omics data analysis.

The role of RHAMM in cancer: Exposing novel therapeutic vulnerabilities

Receptor for hyaluronic acid-mediated motility (RHAMM) is a cell surface receptor for hyaluronic acid that is critical for cell migration and a cell cycle protein involved in microtubule assembly and stability. These functions of RHAMM are required for cellular stress responses and cell cycle progression but are also exploited by tumor cells for malignant progression and metastasis. RHAMM is often overexpressed in tumors and is an independent adverse prognostic factor for a number of cancers such as breast and prostate. Interestingly, pharmacological or genetic inhibition of RHAMM in vitro and in vivo ablates tumor invasiveness and metastatic spread, implicating RHAMM as a potential therapeutic target to restrict tumor growth and improve patient survival. However, RHAMM’s pro-tumor activity is dependent on its subcellular distribution, which complicates the design of RHAMM-directed therapies. An alternative approach is to identify downstream signaling pathways that mediate RHAMM-promoted tumor aggressiveness. Herein, we discuss the pro-tumoral roles of RHAMM and elucidate the corresponding regulators and signaling pathways mediating RHAMM downstream events, with a specific focus on strategies to target the RHAMM signaling network in cancer cells.

Gene amplification-driven RNA methyltransferase KIAA1429 promotes tumorigenesis by regulating BTG2 via m6A-YTHDF2-dependent in lung adenocarcinoma

Background

Epigenetic alterations have been shown to contribute immensely to human carcinogenesis. Dynamic and reversible N6‐methyladenosine (m6A) RNA modification regulates gene expression and cell fate. However, the reasons for activation of KIAA1429 (also known as VIRMA, an RNA methyltransferase) and its underlying mechanism in lung adenocarcinoma (LUAD) remain largely unexplored. In this study, we aimed to clarify the oncogenic role of KIAA1429 in the tumorigenesis of LUAD.

Methods

Whole‐genome sequencing and transcriptome sequencing of LUAD data were used to analyze the gene amplification of RNA methyltransferase. The in vitro and in vivo functions of KIAA1429 were investigated. Transcriptome sequencing, methylated RNA immunoprecipitation sequencing (MeRIP‐seq), m6A dot blot assays and RNA immunoprecipitation (RIP) were performed to confirm the modified gene mediated by KIAA1429. RNA stability assays were used to detect the half‐life of the target gene.

Results

Copy number amplification drove higher expression of KIAA1429 in LUAD, which was correlated with poor overall survival. Manipulating the expression of KIAA1429 could regulate the proliferation and metastasis of LUAD. Mechanistically, the target genes of KIAA1429‐mediated m6A modification were confirmed by transcriptome sequencing and MeRIP‐seq assays. We also revealed that KIAA1429 could regulate BTG2 expression in an m6A‐dependent manner. Knockdown of KIAA1429 significantly decreased the m6A levels of BTG2 mRNA, leading to enhanced YTH m6A RNA binding protein 2 (YTHDF2, the m6A “reader”)‐dependent BTG2 mRNA stability and promoted the expression of BTG2; thus, participating in the tumorigenesis of LUAD.

Conclusions

Our data revealed the activation mechanism and important role of KIAA1429 in LUAD tumorigenesis, which may provide a novel view on the targeted molecular therapy of LUAD.

CircXPO5 Plays a Neuroprotective Function in the Lateral Geniculate Nucleus of Glaucoma by Regulating GRIN2A

PURPOSE

Previous studies have found the neurodegeneration and atrophy of glaucomatous lateral geniculate nucleus (LGN), but the mechanism is still unknown. Circular RNA (circRNA) plays some important roles in physiological and pathological progression of the disease. In this study, we focused on the differentially expressed circRNAs and the mechanism for circXPO5 in LGN degeneration in a macaque glaucoma model.

METHODS

Using RNA-seq, we analyzed the differentially expressed circRNAs in a macaque glaucoma model. An RT-QPCR was used to check the expression of selected differentially expressed circRNAs, candidate miRNAs and mRNAs. A competing endogenous RNA (ceRNA) network analysis was performed to examine the mechanism of circXPO5 action.

RESULTS

circXPO5 significantly decreased in the glaucoma model and a ceRNA network analysis revealed that circXPO5 can bind to miR-330-5p, which also binds to GRIN2A (ionotropic receptor NMDA type subunit 2A). QPCR detection showed a decrease in GRIN2A and an increase in miR-330-5p.

CONCLUSIONS

Our earlier studies revealed that the GRIN2A gene regulates the calcium signal pathway. Decreasing of GRIN2A related with neuron apoptosis and neurodegeneration. These findings indicate that the reduction in circXPO5 may have a protective effect on neuronal apoptosis in the visual central system of glaucoma.

Pathogenic BRCA1 variants disrupt PLK1-regulation of mitotic spindle orientation

Preneoplastic mammary tissues from human female BRCA1 mutation carriers, or Brca1-mutant mice, display unexplained abnormalities in luminal differentiation. We now study the division characteristics of human mammary cells purified from female BRCA1 mutation carriers or non-carrier donors. We show primary BRCA1 mutant/+ cells exhibit defective BRCA1 localization, high radiosensitivity and an accelerated entry into cell division, but fail to orient their cell division axis. We also analyse 15 genetically-edited BRCA1 mutant/+ human mammary cell-lines and find that cells carrying pathogenic BRCA1 mutations acquire an analogous defect in their division axis accompanied by deficient expression of features of mature luminal cells. Importantly, these alterations are independent of accumulated DNA damage, and specifically dependent on elevated PLK1 activity induced by reduced BRCA1 function. This essential PLK1-mediated role of BRCA1 in controlling the cell division axis provides insight into the phenotypes expressed during BRCA1 tumorigenesis.

Modification of BRCA1-associated breast cancer risk by HMMR overexpression

Breast cancer risk for carriers of BRCA1 pathological variants is modified by genetic factors. Genetic variation in HMMR may contribute to this effect. However, the impact of risk modifiers on cancer biology remains undetermined and the biological basis of increased risk is poorly understood. Here, we depict an interplay of molecular, cellular, and tissue microenvironment alterations that increase BRCA1-associated breast cancer risk. Analysis of genome-wide association results suggests that diverse biological processes, including links to BRCA1-HMMR profiles, influence risk. HMMR overexpression in mouse mammary epithelium increases Brca1-mutant tumorigenesis by modulating the cancer cell phenotype and tumor microenvironment. Elevated HMMR activates AURKA and reduces ARPC2 localization in the mitotic cell cortex, which is correlated with micronucleation and activation of cGAS-STING and non-canonical NF-κB signaling. The initial tumorigenic events are genomic instability, epithelial-to-mesenchymal transition, and tissue infiltration of tumor-associated macrophages. The findings reveal a biological foundation for increased risk of BRCA1-associated breast cancer.

Molecular characterization of chronic liver disease dynamics: from liver fibrosis to acute-on-chronic liver failure

Background & Aims

The molecular mechanisms driving the progression from early-chronic liver disease (CLD) to cirrhosis and, finally, acute-on-chronic liver failure (ACLF) are largely unknown. Our aim was to develop a protein network-based approach to investigate molecular pathways driving progression from early-CLD to ACLF.

Methods

Transcriptome analysis was performed on liver biopsies from patients at different liver disease stages, including fibrosis, compensated cirrhosis, decompensated cirrhosis and ACLF, and control healthy livers. We created 9 liver-specific disease-related protein-protein interaction networks capturing key pathophysiological processes potentially related to CLD. We used these networks as a framework and performed gene set-enrichment analysis (GSEA) to identify dynamic gene profiles of disease progression.

Results

Principal component analyses revealed that samples clustered according to the disease stage. GSEA of the defined processes showed an upregulation of inflammation, fibrosis and apoptosis networks throughout disease progression. Interestingly, we did not find significant gene expression differences between compensated and decompensated cirrhosis, while ACLF showed acute expression changes in all the defined liver disease-related networks. The analyses of disease progression patterns identified ascending and descending expression profiles associated with ACLF onset. Functional analyses showed that ascending profiles were associated with inflammation, fibrosis, apoptosis, senescence and carcinogenesis networks, while descending profiles were mainly related to oxidative stress and genetic factors. We confirmed by qPCR the upregulation of genes of the ascending profile and validated our findings in an independent patient cohort.

Conclusion

ACLF is characterized by a specific hepatic gene expression pattern related to inflammation, fibrosis, apoptosis, senescence and carcinogenesis. Moreover, the observed profile is significantly different from that of compensated and decompensated cirrhosis, supporting the hypothesis that ACLF should be considered a distinct entity.

Lay summary

By using transjugular biopsies obtained from patients at different stages of chronic liver disease, we unveil the molecular pathogenic mechanisms implicated in the progression of chronic liver disease to cirrhosis and acute-on-chronic liver failure. The most relevant finding in this study is that patients with acute-on-chronic liver failure present a specific hepatic gene expression pattern distinct from that of patients at earlier disease stages. This gene expression pattern is mostly related to inflammation, fibrosis, angiogenesis, and senescence and apoptosis pathways in the liver.

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We unveiled the molecular pathogenic mechanisms implicated in the progression of chronic liver disease to cirrhosis and ACLF.

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ACLF presents a specific hepatic gene expression pattern distinct from that of patients at earlier disease stages.

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Gene expression pattern of ACLF is mostly related to inflammation, fibrosis, angiogenesis, senescence and apoptosis pathways in the liver.

BRCA1 and Metastasis: Outcome of Defective DNA Repair

Simple Summary

BRCA1 has critical functions in accurately repairing double stand breaks in the DNA through a process known as homologous recombination. BRCA1 also has various functions in other cellular processes that safeguard the genome. Thus, mutations or silencing of this tumor suppressor significantly increases the risk of developing breast, ovarian, and other cancers. Metastasis refers to the spread of cancer to other parts of the body and is the leading cause of cancer-related deaths. In this review, we discuss the mechanisms by which BRCA1 mutations contribute to the metastatic and aggressive nature of the tumor cells.

Abstract

Heritable mutations in BRCA1 and BRCA2 genes are a major risk factor for breast and ovarian cancer. Inherited mutations in BRCA1 increase the risk of developing breast cancers by up to 72% and ovarian cancers by up to 69%, when compared to individuals with wild-type BRCA1. BRCA1 and BRCA2 (BRCA1/2) are both important for homologous recombination-mediated DNA repair. The link between BRCA1/2 mutations and high susceptibility to breast cancer is well established. However, the potential impact of BRCA1 mutation on the individual cell populations within a tumor microenvironment, and its relation to increased aggressiveness of cancer is not well understood. The objective of this review is to provide significant insights into the mechanisms by which BRCA1 mutations contribute to the metastatic and aggressive nature of the tumor cells.

Statins downregulate YAP and TAZ and exert anti-cancer effects in canine mammary tumour cells

Canine mammary tumours (CMTs) are the most common neoplasms in intact bitches, and few chemotherapeutic options are available for highly invasive and metastatic tumours. Recent studies have shown the potential involvement of dysregulated Hippo signalling in CMT development and progression. Statins can activate the Hippo pathway by blocking protein geranylgeranylation (GGylation), resulting in decreased expression and activity of the transcriptional co-activators YAP and TAZ. In this study, we therefore sought to determine if statins could exert anti-cancer effects in CMT cells. Our results demonstrate that Atorvastatin and Fluvastatin are cytotoxic to two CMT cell lines (CMT9 and CMT47), with ED50 values ranging from 0.95 to 23.5 μM. Both statins acted to increase apoptosis and promote cell cycle arrest. Both statins also decreased YAP and TAZ expression and reduced the mRNA levels of key Hippo transcriptional target genes known to be involved in breast cancer progression and chemoresistance (CYR61, CTGF and RHAMM). Moreover, both statins effectively inhibited cell migration and anchorage independent growth, but did not influence matrix invasion. Taken together, our results demonstrate for the first time that statins act upon the Hippo pathway in CMT cells to counteract several molecular and cellular hallmarks of cancer. These findings suggest that targeting the Hippo pathway with statins represents a novel and promising approach for the treatment canine mammary gland cancers.

The fellowship of the RING: BRCA1, its partner BARD1 and their liaison in DNA repair and cancer

The breast cancer type 1 susceptibility protein (BRCA1) and its partner - the BRCA1-associated RING domain protein 1 (BARD1) - are key players in a plethora of fundamental biological functions including, among others, DNA repair, replication fork protection, cell cycle progression, telomere maintenance, chromatin remodeling, apoptosis and tumor suppression. However, mutations in their encoding genes transform them into dangerous threats, and substantially increase the risk of developing cancer and other malignancies during the lifetime of the affected individuals. Understanding how BRCA1 and BARD1 perform their biological activities therefore not only provides a powerful mean to prevent such fatal occurrences but can also pave the way to the development of new targeted therapeutics. Thus, through this review work we aim at presenting the major efforts focused on the functional characterization and structural insights of BRCA1 and BARD1, per se and in combination with all their principal mediators and regulators, and on the multifaceted roles these proteins play in the maintenance of human genome integrity.

Interpretation of cancer mutations using a multiscale map of protein systems

A major goal of cancer research is to understand how mutations distributed across diverse genes affect common cellular systems, including multiprotein complexes and assemblies. Two challenges—how to comprehensively map such systems and how to identify which are under mutational selection—have hindered this understanding. Accordingly, we created a comprehensive map of cancer protein systems integrating both new and published multi-omic interaction data at multiple scales of analysis. We then developed a unified statistical model that pinpoints 395 specific systems under mutational selection across 13 cancer types. This map, called NeST (Nested Systems in Tumors), incorporates canonical processes and notable discoveries, including a PIK3CA-actomyosin complex that inhibits phosphatidylinositol 3-kinase signaling and recurrent mutations in collagen complexes that promote tumor proliferation. These systems can be used as clinical biomarkers and implicate a total of 548 genes in cancer evolution and progression. This work shows how disparate tumor mutations converge on protein assemblies at different scales.

Validating HMMR Expression and Its Prognostic Significance in Lung Adenocarcinoma Based on Data Mining and Bioinformatics Methods

Hyaluronic acid-mediated motility receptor (HMMR), a tumor-related gene, plays a vital role in the occurrence and progression of various cancers. This research is aimed to reveal the effect of HMMR in lung adenocarcinoma (LUAD). We first obtained the gene expression profiles and clinical data of patients with LUAD from The Cancer Genome Atlas (TCGA) database. Then, based on the TCGA cohort, the HMMR expression difference between LUAD tissues and nontumor tissues was detected and verified with public tissue microarrays (TMAs), clinical LUAD specimen cohort, and Gene Expression Omnibus (GEO) cohort. Logistic regression analysis and chi-square test were adopted to study the correlation between HMMR expression and clinicopathological parameters. The effect of HMMR expression on survival was evaluated by Kaplan–Meier survival analysis and using the Cox regression model. Furthermore, Gene Set Enrichment Analysis (GSEA) was utilized to screen out signaling pathways related to LUAD and the co-expression analysis was employed to build the protein–protein interaction (PPI) network. The HMMR expression level in LUAD tissues was dramatically higher than that in nontumor tissues. Logistic regression analysis and chi-square test demonstrated that the high HMMR expression in LUAD has relation with gender, pathological stage, T classification, lymph node metastasis, and distant metastasis. The Kaplan–Meier curve suggested a poor prognosis for LUAD patients with high HMMR expression. Multivariate analysis implied that the high HMMR expression was a vital independent predictor of poor overall survival (OS). GSEA indicated that a total of 15 signaling pathways were enriched in samples with the high HMMR expression phenotype. The PPI network gave 10 genes co-expressed with HMMR. HMMR may be an oncogene in LUAD and is expected to become a potential prognostic indicator and therapeutic target for LUAD.

High levels of truncated RHAMM cooperate with dysfunctional p53 to accelerate the progression of pancreatic cancer

Pancreatic cancer has the lowest survival rate out of all types of cancer. Pancreatic cancer patients are often diagnosed at advanced stages, hence an urgent need for a better therapeutic development of this devastating disease. Receptor for hyaluronan-mediated motility (RHAMM), not expressed in adult normal pancreas, has been suggested as a prognostic factor and a potential therapeutic target for pancreatic ductal adenocarcinoma (PDAC) and pancreatic neuroendocrine tumor (PNET). In this study, we initially sought to determine whether genetic deletion of RHAMM would slow down pancreatic cancer progression using Rhamm^-/- mice. However, we found that Rhamm^-/- mice expressed a truncated HMMR^Δexon8-16 protein at higher abundance levels than wild-type RHAMM. While HMMR^Δexon8-16 did not enable malignant progression of pancreatic intraepithelial neoplasia in p48-Cre; LSL-KRAS^G12D mice, it accelerated the formation of invasive PDAC and shortened the survival of p48-Cre; LSL-KRAS^G12D mice with heterozygous p53 knockout. Kras^G12D PDAC mice with homozygous p53 knockout mice died around 10 weeks, and the effect of HMMR^Δexon8-16 was not apparent in these short lifespan mice. In addition, HMMR^Δexon8-16 shortened the survival of PNET-bearing RIP-Tag mice, which had inactivated p53. In our analysis of TCGA dataset, pancreatic cancer patients with mutant TP53 or loss of one copy of TP53 had higher RHAMM expression, which, combined, predicted worse outcomes. Taken together, by collaborating with dysfunctional p53, high levels of HMMR^Δexon8-16 , which lacks the centrosome targeting domain and degrons for interaction with the Anaphase-Promoting Complex (APC), accelerated pancreatic cancer progression.

Cerebellar Long Noncoding RNA Expression Profile in a Niemann-Pick C Disease Mouse Model

Niemann-Pick type C (NP-C) disease is a neurodegenerative lysosomal storage disorder primarily caused by mutations in NPC1. However, its pathogenesis remains poorly understood. While mounting evidence has demonstrated the involvement of long noncoding RNAs (lncRNAs) in the pathogenesis of neurodegenerative disorders, the lncRNA expression profile in NP-C has not been determined. Here, we used RNA-seq analysis to determine lncRNA and mRNA expression profiles of the cerebella of NPC1^−/− mice. We found that 272 lncRNAs and 856 mRNAs were significantly dysregulated in NPC1^−/− mice relative to controls (≥ 2.0-fold, p < 0.05). Quantitative real-time PCR (qRT‐PCR) was utilized to validate the expression of selected lncRNAs and mRNAs. Next, a lncRNA-mRNA coexpression network was employed to examine the potential roles of the differentially expressed (DE) lncRNAs. Functional analysis revealed that mRNAs coexpressed with lncRNAs are mainly linked to immune system–related processes and neuroinflammation. Moreover, knockdown of the lncRNA H19 ameliorated changes in ROS levels and cell viability and suppressed the lipopolysaccharide (LPS)–induced inflammatory response in vitro. Our findings indicate that dysregulated lncRNA expression patterns are associated with NP-C pathogenesis and offer insight into the development of novel therapeutics based on lncRNAs.

Strict network analysis of evolutionary conserved and brain-expressed genes reveals new putative candidates implicated in Intellectual Disability and in Global Development Delay

OBJECTIVES

Intellectual Disability (ID) and Global Development Delay (GDD) are frequent reasons for referral to genetic services and although they present overlapping phenotypes concerning cognitive, motor, language, or social skills, they are not exactly synonymous. Aiming to better understand independent or shared mechanisms related to these conditions and to identify new candidate genes, we performed a highly stringent protein-protein interaction network based on genes previously related to ID/GDD in the Human Phenotype Ontology portal.

METHODS

ID/GDD genes were searched for reliable interactions through STRING and clustering analysis was applied to detect biological complexes through the MCL algorithm. Six coding hub genes (TP53, CDC42, RAC1, GNB1, APP, and EP300) were recognised by the Cytoscape NetworkAnalyzer plugin, interacting with 1625 proteins not yet associated with ID or GDD. Genes encoding these proteins were explored by gene ontology, associated diseases, evolutionary conservation, and brain expression.

RESULTS

One hundred and seventy-two new putative genes playing a role in enriched processes/pathways previously related to ID and GDD were revealed, some of which were already postulated to be linked to ID/GDD in additional databases.

CONCLUSIONS

Our findings expanded the aetiological genetic landscape of ID/GDD and showed evidence that both conditions are closely related at the molecular and functional levels.

AR-mTOR-SRF Axis Regulates HMMR Expression in Human Prostate Cancer Cells

The elevated expression of the hyaluronan-mediated motility receptor (HMMR) is known to be highly associated with tumor progression in prostate cancer, but the molecular mechanisms underlying the regulation of HMMR expression remain unclear. Here, we report that mammalian target of rapamycin (mTOR) is a key regulator of HMMR expression, for which its kinase activity is required. Pharmacological inhibitors of mTOR, such as rapamycin and Torin2, markedly suppressed the mRNA level as well as the protein level of HMMR in LNCaP and PC-3 cells. Our data demonstrate that such regulation occurs at the transcription level. HMMR promoter reporter assays revealed that the transcription factor SRF is responsible for the mTOR-mediated transcriptional regulation of HMMR gene. Consistently, the suppression of HMMR expression by Torin2 was noticeably reversed by the overexpression of SRF. Moreover, our findings suggest that the SRF binding sites responsible for the transcriptional regulation of HMMR through the mTOR-SRF axis are located in HMMR promoter sequences carrying the first intron, downstream of the translational start site. Furthermore, the upregulation of HMMR by DHT was abolished by stimulation with rapamycin, prior to DHT treatment, suggesting that mTOR activity is required for the induction of HMMR expression by androgen. Collectively, our study provides new mechanistic insights into the role of mTOR/SRF/AR signaling in HMMR regulation in prostate cancer cells.

A tipping point in cancer-immune dynamics leads to divergent immunotherapy responses and hampers biomarker discovery

BACKGROUND

Predicting treatment response or survival of cancer patients remains challenging in immuno-oncology. Efforts to overcome these challenges focus, among others, on the discovery of new biomarkers. Despite advances in cellular and molecular approaches, only a limited number of candidate biomarkers eventually enter clinical practice.

METHODS

A computational modeling approach based on ordinary differential equations was used to simulate the fundamental mechanisms that dictate tumor-immune dynamics and to investigate its implications on responses to immune checkpoint inhibition (ICI) and patient survival. Using in silico biomarker discovery trials, we revealed fundamental principles that explain the diverging success rates of biomarker discovery programs.

RESULTS

Our model shows that a tipping point-a sharp state transition between immune control and immune evasion-induces a strongly non-linear relationship between patient survival and both immunological and tumor-related parameters. In patients close to the tipping point, ICI therapy may lead to long-lasting survival benefits, whereas patients far from the tipping point may fail to benefit from these potent treatments.

CONCLUSION

These findings have two important implications for clinical oncology. First, the apparent conundrum that ICI induces substantial benefits in some patients yet completely fails in others could be, to a large extent, explained by the presence of a tipping point. Second, predictive biomarkers for immunotherapy should ideally combine both immunological and tumor-related markers, as a patient's distance from the tipping point can typically not be reliably determined from solely one of these. The notion of a tipping point in cancer-immune dynamics helps to devise more accurate strategies to select appropriate treatments for patients with cancer.

Long Noncoding RNA Expression Profiles of Periodontal Ligament Stem Cells from the Periodontitis Microenvironment in Response to Static Mechanical Strain

During the period of orthodontic tooth movement, periodontal ligament stem cells (PDLSCs) play an important role in transducing mechanical stimulation and tissue remodeling. However, our previous studies verified that the periodontitis microenvironment causes damage to the biological functions of PDLSCs and abnormal mechanical sensitivity. Long noncoding RNAs (lncRNAs) participate in the inflammatory pathogenesis and development of many diseases. Whether lncRNAs are abnormally expressed in PDLSCs obtained from periodontal tissues of periodontitis patients (PPDLSCs) and whether putative lncRNAs participate in the mechanotransductive process in PDLSCs remain poorly understood. First, we subjected PDLSCs obtained from healthy periodontal tissues (HPDLSCs) and PPDLSCs to static mechanical strain (SMS) with 12% elongation at 0.1 Hz frequency using an FX-4000T system and screened overall lncRNA profiles in both cell types by microarray. Among lncRNAs with a fold change (FC) > 20.0, 27 lncRNAs were upregulated in strained HPDLSCs, and 16 lncRNAs (9 upregulated and 7 downregulated) were detected in strained PPDLSCs. For mRNAs with FC > 20.0, we detected 25 upregulated mRNAs and one downregulated mRNA in strained HPDLSCs and 7 upregulated and 5 downregulated mRNAs in strained PPDLSCs. Further enrichment analysis showed that, unlike HPDLSCs with annotations principally involving transduction-associated signaling pathways, dysregulated mRNAs in PPDLSCs are mainly responsible for pathological conditions. Moreover, coexpressed lncRNA-mRNA networks confirmed the pathological state and exacerbated inflammatory conditions in strained PPDLSCs. Taken together, when compared with strained HPDLSCs, various lncRNAs and mRNAs were dysregulated in PPDLSCs under mechanical forces, implicating the response of lncRNAs in PPDLSCs to mechanical stress. Moreover, we provide potential lncRNA targets, which may contribute to future intervention strategies for orthodontic treatment in periodontitis patients.

Six genes involved in prognosis of hepatocellular carcinoma identified by Cox hazard regression

BACKGROUND

Hepatocellular carcinoma (HCC), derived from hepatocytes, is the main histological subtype of primary liver cancer and poses a serious threat to human health due to the high incidence and poor prognosis. This study aimed to establish a multigene prognostic model to predict the prognosis of patients with HCC.

RESULTS

Gene expression datasets (GSE121248, GSE40873, GSE62232) were used to identify differentially expressed genes (DEGs) between tumor and adjacent or normal tissues, and then hub genes were screened by protein-protein interaction (PPI) network and Cytoscape software. Seventeen genes among hub genes were significantly associated with prognosis and used to construct a prognostic model through COX hazard regression analysis. The predictive performance of this model was evaluated with TCGA data and was further validated with independent dataset GSE14520. Six genes (CDKN3, ZWINT, KIF20A, NUSAP1, HMMR, DLGAP5) were involved in the prognostic model, which separated HCC patients from TCGA dataset into high- and low-risk groups. Kaplan-Meier (KM) survival analysis and risk score analysis demonstrated that low-risk group represented a survival advantage. Univariate and multivariate regression analysis showed risk score could be an independent prognostic factor. The receiver operating characteristic (ROC) curve showed there was a better predictive power of the risk score than that of other clinical indicators. At last, the results from GSE14520 demonstrated the reliability of this prognostic model in some extent.

CONCLUSION

This prognostic model represented significance for prognosis of HCC, and the risk score according to this model may be a better prognostic factor than other traditional clinical indicators.

Identification of novel hub genes and lncRNAs related to the prognosis and progression of pancreatic cancer by microarray and integrated bioinformatics analysis

BACKGROUND

Pancreatic cancer (PC) is one of the most invasive and metastatic neoplasms among the fatal malignancies of the digestive system. Abnormal expression of genes and long non-coding RNAs (lncRNAs) are reportedly linked to multiple cancers. However, the lncRNA-mRNA expression profiles and their molecular mechanisms in PC progression are poorly known. This study aimed to map the hub genes and lncRNAs which might play core roles in the development of PC.

METHODS

This study used microarray expression analysis to screen for both differentially expressed genes (DEGs) and differentially expressed lncRNAs (DElncRNAs) between PC and matched adjacent non-tumor (AN) tissues. In order to clarify the functional classification of DEGs, we conducted GO and KEGG pathway enrichment analyses via the Enrichr database. LncRNA-mRNA co-expressed networks were also constructed to explore the probable core regulating DEGs and DElncRNAs. Subsequently, the hub genes and lncRNAs were validated via the ONCOMINE and GEPIA databases and the co-expressed networks.

RESULTS

By analyzing an mRNA-lncRNA microarray, we identified 943 mRNAs and 1,138 lncRNAs differentially expressed in PC tumors compared with the matched AN tissues. GO analysis confirmed that both up-regulated and down-regulated DEGs were enriched in multiple terms. The KEGG pathways enrichment analyses revealed that DEGs were mostly enriched in the focal adhesion and glutathione metabolism pathways, amongst others. Co-expressed networks were established to reveal the differential interactions between DEGs and DElncRNAs, and to indicate the core regulatory factors located at the core nodes of the co-expressed networks. The expression levels of potential core-regulating DEGs were validated by the GEPIA and ONCOMINE databases, and the relationship between overall survival and tumor stage and the potential core-regulating DEGs was analyzed using the GEPIA database. As a result, five genes and sixteen lncRNAs were finally considered as the hub transcripts in PC.

CONCLUSIONS

This study identified DEGs and DElncRNAs between PC tumors and matched AN tissues, and these transcripts were connected with malignant phenotypes in PC through different BPs and signaling pathways. Furthermore, five hub genes and sixteen lncRNAs were identified, which are expected to represent candidate diagnostic biomarkers or potential therapeutic targets for PC.

De Novo Transcriptomic Analyses Revealed Some Detoxification Genes and Related Pathways Responsive to Noposion Yihaogong® 5% EC (Lambda-Cyhalothrin 5%) Exposure in Spodoptera frugiperda Third-Instar Larvae

Simple Summary

Insect pest resistance to synthetic insecticides is a major problem that limits efficient management and thus decreases productivity for farmers and increases the use of harmful materials that pollute the environment and endanger humans and beneficial organisms. A major approach for resistance management is understanding how insect pest field populations develop resistance at molecular levels. To provide a comprehensive insight into the resistance mechanisms of Spodoptera frugiperda larvae to lambda-cyhalothrin 5%, we investigated the molecular basis of resistance mechanism in field collected population of fall armyworm (Spodoptera frugiperda) to lambda-cyhalothrin 5% insecticide, a pyrethroid insecticide by using de novo transcriptomics analysis. We found that resistance to lambda-cyhalothrin 5% can be metabolic by increasing the levels of detoxifying enzymes such as P450, GST and UGT and related genes to insecticide resistance in the field population. The obtained transcriptome information provides large gene resources available for further studying the resistance development of Spodoptera frugiperda to pesticides. The DGE data provide comprehensive insights into the gene expression profiles of fall armyworm (Spodoptera frugiperda) to lambda-cyhalothrin 5% and will facilitate the study of the role of each gene in lambda-cyhalothrin resistance development.

Abstract

The fall armyworm, Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), is a polyphagous, invasive insect pest which causes significant losses in important crops wherever it has spread. The use of pesticides in agriculture is a key tool in the management of many important crop pests, including S. frugiperda, but continued use of insecticides has selected for various types of resistance, including enzyme systems that provide enhanced mechanisms of detoxification. In the present study, we analyzed the de novo transcriptome of S. frugiperda larvae exposed to Noposion Yihaogong^® 5% emulsifiable concentrate (EC) insecticide focusing on detoxification genes and related pathways. Results showed that a total of 1819 differentially expressed genes (DEGs) were identified in larvae after being treated with Noposion Yihaogong^® 5% EC insecticide, of which 863 were up- and 956 down-regulated. Majority of these differentially expressed genes were identified in numerous Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including metabolism of xenobiotics and drug metabolism. Furthermore, many of S. frugiperda genes involved in detoxification pathways influenced by lambda-cyhalothrin stress support their predicted role by further co-expression network analysis. Our RT-qPCR results were consistent with the DEG’s data of transcriptome analysis. The comprehensive transcriptome sequence resource attained through this study enriches the genomic platform of S. frugiperda, and the identified DEGs may enable greater molecular underpinnings behind the insecticide-resistance mechanism caused by lambda-cyhalothrin.

Postzygotic Somatic Mutations in the Human Brain Expand the Threshold-Liability Model of Schizophrenia

The search for what causes schizophrenia has been onerous. This research has included extensive assessment of a variety of genetic and environmental factors using ever emerging high-resolution technologies and traditional understanding of the biology of the brain. These efforts have identified a large number of schizophrenia-associated genes, some of which are altered by mutational and epi-mutational mechanisms in a threshold liability model of schizophrenia development. The results, however, have limited predictability and the actual cause of the disease remains unknown. This current state asks for conceptualizing the problem differently in light of novel insights into the nature of mutations, the biology of the brain and the fine precision and resolution of emerging technologies. There is mounting evidence that mutations acquired during postzygotic development are more common than germline mutations. Also, the postzygotic somatic mutations including epimutations (PZMs), which often lead to somatic mosaicism, are relatively common in the mammalian brain in comparison to most other tissues and PZMs are more common in patients with neurodevelopmental mental disorders, including schizophrenia. Further, previously inaccessible, detection of PZMs is becoming feasible with the advent of novel technologies that include single-cell genomics and epigenomics and the use of exquisite experimental designs including use of monozygotic twins discordant for the disease. These developments allow us to propose a working hypothesis and expand the threshold liability model of schizophrenia that already encompasses familial genetic, epigenetic and environmental factors to include somatic de novo PZMs. Further, we offer a test for this expanded model using currently available genome sequences and methylome data on monozygotic twins discordant for schizophrenia (MZD) and their parents. The results of this analysis argue that PZMs play a significant role in the development of schizophrenia and explain extensive heterogeneity seen across patients. It also offers the potential to convincingly link PZMs to both nervous system health and disease, an area that has remained challenging to study and relatively under explored.

Genome-wide translational profiling of amygdala Crh-expressing neurons reveals role for CREB in fear extinction learning

Fear and extinction learning are adaptive processes caused by molecular changes in specific neural circuits. Neurons expressing the corticotropin-releasing hormone gene (Crh) in central amygdala (CeA) are implicated in threat regulation, yet little is known of cell type-specific gene pathways mediating adaptive learning. We translationally profiled the transcriptome of CeA Crh-expressing cells (Crh neurons) after fear conditioning or extinction in mice using translating ribosome affinity purification (TRAP) and RNAseq. Differential gene expression and co-expression network analyses identified diverse networks activated or inhibited by fear vs extinction. Upstream regulator analysis demonstrated that extinction associates with reduced CREB expression, and viral vector-induced increased CREB expression in Crh neurons increased fear expression and inhibited extinction. These findings suggest that CREB, within CeA Crh neurons, may function as a molecular switch that regulates expression of fear and its extinction. Cell-type specific translational analyses may suggest targets useful for understanding and treating stress-related psychiatric illness.

Transcriptome analysis uncovers the diagnostic value of miR-192-5p/HNF1A-AS1/VIL1 panel in cervical adenocarcinoma

Despite the fact that the incidence of cervical squamous cell carcinoma has decreased, there is an increase in the incidence of cervical adenocarcinoma. However, our knowledge on cervical adenocarcinoma is largely unclear. Transcriptome sequencing was conducted to compare 4 cervical adenocarcinoma tissue samples with 4 normal cervical tissue samples. mRNA, lncRNA, and miRNA signatures were identified to discriminate cervical adenocarcinoma from normal cervix. The expression of VIL1, HNF1A-AS1, MIR194-2HG, SSTR5-AS1, miR-192-5p, and miR-194-5p in adenocarcinoma were statistically significantly higher than that in normal control samples. The Receiver Operating Characteristic (ROC) curve analysis indicated that combination of miR-192-5p, HNF1A-AS1, and VIL1 yielded a better performance (AUC = 0.911) than any single molecule -and could serve as potential biomarkers for cervical adenocarcinoma. Of note, the combination model also gave better performance than TCT test for cervical adenocarcinoma diagnosis. However, there was no correlation between miR-192-5p or HNF1A-AS1 and HPV16/18 E6 or E7. VIL1 was weakly correlated with HPV18 E7 expression. In summary, our study has identified miR-192-5p/HNF1A-AS1/VIL1 panel that accurately discriminates adenocarcinoma from normal cervix. Detection of this panel may provide considerable clinical value in the diagnosis of cervical adenocarcinoma.

Pathway Analysis of Renal Cell Carcinoma Genome-Wide Association Studies Identifies Novel Associations

BACKGROUND

Much of the heritable risk of renal cell carcinoma (RCC) associated with common genetic variation is unexplained. New analytic approaches have been developed to increase the discovery of risk variants in genome-wide association studies (GWAS), including multi-locus testing through pathway analysis.

METHODS

We conducted a pathway analysis using GWAS summary data from six previous scans (10,784 cases and 20,406 controls) and evaluated 3,678 pathways and gene sets drawn from the Molecular Signatures Database. To replicate findings, we analyzed GWAS summary data from the UK Biobank (903 cases and 451,361 controls) and the Genetic Epidemiology Research on Adult Health and Aging cohort (317 cases and 50,511 controls).

RESULTS

We identified 14 pathways/gene sets associated with RCC in both the discovery (P < 1.36 × 10-5, the Bonferroni correction threshold) and replication (P < 0.05) sets, 10 of which include components of the PI3K/AKT pathway. In tests across 2,035 genes in these pathways, associations (Bonferroni corrected P < 2.46 × 10-5 in discovery and replication sets combined) were observed for CASP9, TIPIN, and CDKN2C. The strongest SNP signal was for rs12124078 (P Discovery = 2.6 × 10-5; P Replication = 1.5 × 10-4; P Combined = 6.9 × 10-8), a CASP9 expression quantitative trait locus.

CONCLUSIONS

Our pathway analysis implicates genetic variation within the PI3K/AKT pathway as a source of RCC heritability and identifies several promising novel susceptibility genes, including CASP9, which warrant further investigation.

IMPACT

Our findings illustrate the value of pathway analysis as a complementary approach to analyzing GWAS data.

Robust edge-based biomarker discovery improves prediction of breast cancer metastasis

Background

The abundance of molecular profiling of breast cancer tissues entailed active research on molecular marker-based early diagnosis of metastasis. Recently there is a surging interest in combining gene expression with gene networks such as protein-protein interaction (PPI) network, gene co-expression (CE) network and pathway information to identify robust and accurate biomarkers for metastasis prediction, reflecting the common belief that cancer is a systems biology disease. However, controversy exists in the literature regarding whether network markers are indeed better features than genes alone for predicting as well as understanding metastasis. We believe much of the existing results may have been biased by the overly complicated prediction algorithms, unfair evaluation, and lack of rigorous statistics. In this study, we propose a simple approach to use network edges as features, based on two types of networks respectively, and compared their prediction power using three classification algorithms and rigorous statistical procedure on one of the largest datasets available. To detect biomarkers that are significant for the prediction and to compare the robustness of different feature types, we propose an unbiased and novel procedure to measure feature importance that eliminates the potential bias from factors such as different sample size, number of features, as well as class distribution.

Results

Experimental results reveal that edge-based feature types consistently outperformed gene-based feature type in random forest and logistic regression models under all performance evaluation metrics, while the prediction accuracy of edge-based support vector machine (SVM) model was poorer, due to the larger number of edge features compared to gene features and the lack of feature selection in SVM model. Experimental results also show that edge features are much more robust than gene features and the top biomarkers from edge feature types are statistically more significantly enriched in the biological processes that are well known to be related to breast cancer metastasis.

Conclusions

Overall, this study validates the utility of edge features as biomarkers but also highlights the importance of carefully designed experimental procedures in order to achieve statistically reliable comparison results.

Comprehensive Transcriptome Profiling of Dairy Goat Mammary Gland Identifies Genes and Networks Crucial for Lactation and Fatty Acid Metabolism

Milk fatty acids secreted by the mammary gland are one of the most important determinants of the nutritional value of goat milk. Unlike cow milk, limited data are available on the transcriptome-wide changes across stages of lactation in dairy goats. In this study, goat mammary gland tissue collected at peak lactation, cessation of milking, and involution were analyzed with digital gene expression (DGE) sequencing to generate longitudinal transcript profiles. A total of 51,299 unigenes were identified and further annotated to 12,763 genes, of which 9,131 were differentially expressed across various stages of lactation. Most abundant genes and differentially expressed genes (DEGs) were functionally classified through clusters of euKaryotic Orthologous Groups (KOG), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. A total of 16 possible expression patterns were uncovered, and 13 genes were deemed novel candidates for regulation of lactation in the goat: POLG, SPTA1, KLC, GIT2, COPS3, PDP, CD31, USP16/29/37, TLL1, NCAPH, ABI2, DNAJC4, and MAPK8IP3. In addition, PLA2, CPT1, PLD, GGA, SRPRB, and AP4S1 are proposed as novel and promising candidates regulating mammary fatty acid metabolism. “Butirosin and neomycin biosynthesis” and “Glyoxylate and dicarboxylate metabolism” were the most impacted pathways, and revealed novel metabolic alterations in lipid metabolism as lactation progressed. Overall, the present study provides new insights into the synthesis and metabolism of fatty acids and lipid species in the mammary gland along with more detailed information on molecular regulation of lactogenesis. The major findings will benefit efforts to further improve milk quality in dairy goats.

The Function of BARD1 in Centrosome Regulation in Cooperation with BRCA1/OLA1/RACK1

Breast cancer gene 1 (BRCA1)-associated RING domain protein 1 (BARD1) forms a heterodimer with BRCA1, a tumor suppressor associated with hereditary breast and ovarian cancer. BRCA1/BARD1 functions in multiple cellular processes including DNA repair and centrosome regulation. Centrosomes are the major microtubule-organizing centers in animal cells and are critical for the formation of a bipolar mitotic spindle. BRCA1 and BARD1 localize to the centrosome during the cell cycle, and the BRCA1/BARD1 dimer ubiquitinates centrosomal proteins to regulate centrosome function. We identified Obg-like ATPase 1 (OLA1) and receptor for activated C kinase (RACK1) as BRCA1/BARD1-interating proteins that bind to BARD1 and BRCA1 and localize the centrosomes during the cell cycle. Cancer-derived variants of BRCA1, BARD1, OLA1, and RACK1 failed to interact, and aberrant expression of these proteins caused centrosome amplification due to centriole overduplication only in mammary tissue-derived cells. In S-G2 phase, the number of centrioles was higher in mammary tissue-derived cells than in cells from other tissues, suggesting their involvement in tissue-specific carcinogenesis by BRCA1 and BARD1 germline mutations. We described the function of BARD1 in centrosome regulation in cooperation with BRCA1/OLA1/RACK1, as well as the effect of their dysfunction on carcinogenesis.

Identification of the association between HMMR expression and progression of hepatocellular carcinoma via construction of a co-expression network

The aim of the present study was to identify key genes involved in the progression of hepatocellular carcinoma (HCC). According to the theory of the multistep process of hepatocarcinogenesis and weighted gene co-expression network analysis, hub genes associated with the progression of HCC were identified using the gene expression profiles of patients with normal to chronic hepatitis/cirrhosis and dysplastic nodules to HCC. An independent dataset was used to verify the association between hub gene and clinical phenotype. The diagnostic and prognostic value of hub genes regarding HCC were evaluated. Gene set enrichment analysis (GSEA) was performed to explore the function of hub genes. A co-expression gene module positively associated with HCC progression was identified. Combined with a protein-protein interaction (PPI) network, a total of 10 common hub genes common to both the module of interest and the PPI network were selected as hub genes. Hyaluronan mediated motility receptor (HMMR) was selected as the candidate gene and was significantly upregulated in HCC at the mRNA and protein expression levels. HMMR is a promising diagnostic biomarker for HCC, and is also associated with its progression. The expression of HMMR was positively correlated with HCC tumor grade, pathological stage, tumor stage and Ishak score. The expression of HMMR was an independent prognostic factor compared with clinicopathological features. Patients with high expression levels of HMMR exhibited a less favorable prognosis. GSEA identified 6 representative gene sets that were associated with cancer. Overall, HMMR may serve an important role in HCC and may have potential as a biomarker of HCC diagnosis and progression.

LncRNA and mRNA expression profiles reveal the potential roles of lncRNA contributing to regulating dural penetration in clival chordoma

Chordoma is a rare bone cancer originating from embryologic notochordal remnants. Clival chordomas show different dural penetration ability, with serious dural penetration exhibiting poorer prognosis. The molecular mechanism of dural penetration is not clear. We analyzed lncRNA and mRNA profiles in 12 chordoma patients with different degrees of dural penetration using expression microarrays. The differentially expressed lncRNAs and mRNAs were used to construct a lncRNA-mRNA co-expression network. LncRNAs were classified into lincRNA, enhancer-like lncRNA, or antisense lncRNA. Biological functions for lncRNAs were predicted according to the lncRNA-mRNA network and adjacent coding genes by pathway analysis. The 2760 lncRNAs and 3988 mRNAs were differentially expressed in chordomas between two groups of patients with and without dural penetration. Possible pathway involvement of the significance among the 55 lncRNAs located in the lncRNA-mRNA network, 24 lincRNAs, 7 enhancer-like lncRNAs, and 14 antisense lncRNAs include cell adhesion, metastasis, invasion, proliferation, and apoptosis. Expression of 10 lncRNAs and mRNAs, and epidermal growth factor mRNA with two identified lncRNAs were subsequently verified by qRT-PCR in chordoma tissues. Our report predicts the biological functions of many lncRNAs which may be used as diagnostic and prognostic biomarkers as well as therapeutic targets during the process of dural penetration in chordoma.

Proteogenomic analysis of Inhibitor of Differentiation 4 (ID4) in basal-like breast cancer

BACKGROUND

Basal-like breast cancer (BLBC) is a poorly characterised, heterogeneous disease. Patients are diagnosed with aggressive, high-grade tumours and often relapse with chemotherapy resistance. Detailed understanding of the molecular underpinnings of this disease is essential to the development of personalised therapeutic strategies. Inhibitor of differentiation 4 (ID4) is a helix-loop-helix transcriptional regulator required for mammary gland development. ID4 is overexpressed in a subset of BLBC patients, associating with a stem-like poor prognosis phenotype, and is necessary for the growth of cell line models of BLBC through unknown mechanisms.

METHODS

Here, we have defined unique molecular insights into the function of ID4 in BLBC and the related disease high-grade serous ovarian cancer (HGSOC), by combining RIME proteomic analysis, ChIP-seq mapping of genomic binding sites and RNA-seq.

RESULTS

These studies reveal novel interactions with DNA damage response proteins, in particular, mediator of DNA damage checkpoint protein 1 (MDC1). Through MDC1, ID4 interacts with other DNA repair proteins (γH2AX and BRCA1) at fragile chromatin sites. ID4 does not affect transcription at these sites, instead binding to chromatin following DNA damage. Analysis of clinical samples demonstrates that ID4 is amplified and overexpressed at a higher frequency in BRCA1-mutant BLBC compared with sporadic BLBC, providing genetic evidence for an interaction between ID4 and DNA damage repair deficiency.

CONCLUSIONS

These data link the interactions of ID4 with MDC1 to DNA damage repair in the aetiology of BLBC and HGSOC.

Research Note: Circular RNA expressing in different developmental stages of the chicken bursa of Fabricius

The bursa of Fabricius plays an essential role in B lymphocyte development, which is controlled not only by proteins but by noncoding RNA. Circular RNA (circRNA) are expressed in diverse tissues in eukaryotes. To acquire a deeper perception of the molecular mechanism of bursal development, RNA sequencing was used to identify the circRNA during varied evolving stages of the chicken bursa of Fabricius. We identified 13,689 circRNA. All these circRNA were originated from 4565 chicken genes. Among them, only 1 circRNA was yielded from those 4131 parental genes, and 2 or more circular isoforms were generated from the remaining genes. There were 27 circRNA found to be differentially expressed between the embryonic day 20 and day 2 developmental stages. The 5 isoforms of immunoglobulin lambda-like polypeptide 1 circRNA were tested to validate the RNA sequencing data, and their targeted genes were also analyzed with quantitative reverse transcription PCR. These data indicate that cirRNA are abundant and essential during bursal development and may play essential roles in the development of bursa of Fabricius.

Bptf determines oncogenic addiction in aggressive B-cell lymphomas

Chromatin remodeling factors contribute to establish aberrant gene expression programs in cancer cells and therefore represent valuable targets for therapeutic intervention. BPTF (Bromodomain PhD Transcription Factor), a core subunit of the nucleosome remodeling factor (NURF), modulates c-MYC oncogenic activity in pancreatic cancer. Here, we analyze the role of BPTF in c-MYC-driven B-cell lymphomagenesis using the Eμ-Myc transgenic mouse model of aggressive B-cell lymphoma. We find that BPTF is required for normal B-cell differentiation without evidence of haploinsufficiency. In contrast, deletion of one Bptf allele is sufficient to delay lymphomagenesis in Eμ-Myc mice. Tumors arising in a Bptf heterozygous background display decreased c-MYC levels and pathway activity, together with increased activation of the NF-κB pathway, a molecular signature characteristic of human diffuse large B-cell lymphoma (DLBCL). In human B-cell lymphoma samples, we find a strong correlation between BPTF and c-MYC mRNA and protein levels, together with an anti-correlation between BPTF and NF-κB pathway activity. Our results indicate that BPTF is a relevant therapeutic target in B-cell lymphomas and that, upon its inhibition, cells acquire distinct oncogenic dependencies.

Integrative Analysis for the Roles of lncRNAs in the Immune Responses of Mouse PBMC Exposed to Low-Dose Ionizing Radiation

It is well accepted that low-dose ionizing radiation (LDIR) modulates a variety of immune responses that have exhibited the properties of immune hormesis. Alterations in messenger RNA (mRNA) and long noncoding RNA (lncRNA) expression were to crucially underlie these LDIR responses. However, lncRNAs in LDIR-induced immune responses have been rarely reported, and its functions and molecular mechanisms have not yet been characterized. Here, we used microarray profiling to determine lncRNA in BALB/c mice exposed to single (0.5 Gy×1) and chronic (0.05 Gy×10) low-dose γ-rays radiation (Co⁶⁰). We observed that a total of 8274 lncRNAs and 7240 mRNAs were altered in single LDIR, while 2077 lncRNAs and 796 mRNAs in chronic LDIR. The biological functions of these upregulated mRNAs in both 2 groups using Gene Ontology functional and pathway enrichment analysis were significantly enriched in immune processes and immune signaling pathways. Subsequently, we screened out the lncRNAs involved in regulating these immune signaling pathways and examined their potential functions by lncRNAs-mRNAs coexpression networks. This is the first study to comprehensively identify lncRNAs in single and chronic LDIR responses and to demonstrate the involvement of different lncRNA expression patterns in LDIR-induced immune signaling pathways. Further systematic research on these lncRNAs will provide new insights into our understanding of LDIR-modulated immune hormesis responses.

Epigenetic Alterations Associated with the Overall Survival and Recurrence Free Survival among Oral Squamous Cell Carcinoma Patients

Oral squamous cell carcinoma (OSCC) is a fatal disease caused by complex interactions between environmental, genomic, and epigenetic alterations. In the current study, we aimed to identify clusters of genes whose promoter methylation status correlated with various tested clinical features. Molecular datasets of genetic and methylation analysis based on whole-genome sequencing of 159 OSCC patients were obtained from the The Cancer Genome Atlas (TCGA) data portal. Genes were clustered based on their methylation status and were tested for their association with demographic, pathological, and clinical features of the patients. Overall, seven clusters of genes were revealed that showed a significant association with the overall survival/recurrence free survival of patients. The top ranked genes within cluster 4, which showed the worst prognosis, primarily acted as paraneoplastic genes, while the genes within cluster 6 primarily acted as anti-tumor genes. A significant difference was found regarding the mean age in the different clusters. No significant correlation was found between the tumor staging and the different clusters. In conclusion, our result provided a proof-of-principle for the existence of phenotypic diversity among the epigenetic clusters of OSCC and demonstrated the utility of the use epigenetics alterations in devolving new prognostic and therapeutics tools for OSCC patients.

Comparative evaluation of network features for the prediction of breast cancer metastasis

Background

Discovering a highly accurate and robust gene signature for the prediction of breast cancer metastasis from gene expression profiling of primary tumors is one of the most challenging tasks to reduce the number of deaths in women. Due to the limited success of gene-based features in achieving satisfactory prediction accuracy, many methodologies have been proposed in recent years to develop network-based features by integrating network information with gene expression. However, evaluation results are inconsistent to confirm the effectiveness of network-based features, because of many confounding factors involved in classification model learning process, such as data normalization, dimension reduction, and feature selection. An unbiased comparative evaluation is essential for uncovering the strength of network-based features.

Methods

In this study, we compared several types of network-based features obtained using different mathematical operators (Mean, Maximum, Minimum, Median, Variance) on geneset (i.e., a gene and its’ neighbors in the network) in protein-protein interaction network and gene co-expression network for their ability in predicting breast cancer metastasis using gene expression data from more than 10 patient cohorts.

Results

While network-based features are usually statistically more significant than gene-based feature, a consistent improvement of prediction performance using network-based features requires a substantial number of patients in the dataset. In contrary to many previous reports, no evidence was found to support the robustness of network-based features and we argue some of the robustness may be due to the inherent bias associated with node degree in the network. In addition, different types of network features seem to cover different pathways and are complementary to each other. Consequently, an ensemble classifier combining different network features was proposed and was found to significantly outperform classifiers based on gene-based feature or any single type of network-based features.

Conclusions

Network-based features and their combination show promise for improving the prediction of breast cancer metastasis but may require a large amount of training data. Robustness claim of network-based features needs to be re-examined with network node degree and other confounding factors in consideration.

Long noncoding RNA-mRNA expression profiles and validation in pancreatic neuroendocrine neoplasms

BACKGROUND

Pancreatic neuroendocrine neoplasms (pNENs) are a group of endocrine tumours arising in the pancreas and deemed to be the most common neuroendocrine tumours. The pathogenesis of pNENs remains unknown. Long noncoding RNAs (lncRNAs) are aberrantly expressed in cancers. The functional roles of lncRNAs and lncRNA-mRNA expression profiles in pNENs are undefined. The aim of this study was to identify the lncRNA and mRNA expression profiles and explore the lncRNA-mRNA co-expression networks associated with the pNENs carcinogenesis.

METHOD

Differentially expressed lncRNA and mRNA in pNENs tissues from adjacent tissues were detected using human lncRNA microarray V3.0 containing 30 586 lncRNA and 26 109 coding transcripts. Probable functions for lncRNAs and mRNAs were predicted according to lncRNA-mRNA network.

RESULTS

The microarray identified 2080 lncRNAs and 1771 mRNAs in pNENs tumours differentially expressed compared with the adjacent tissues. The GO terms and KEGG pathway annotation data indicated that cell projection morphogenesis, cell adhesion molecules pathway, PI3K-AKT signalling pathway, focal adhesion pathway, neuroactive ligand-receptor interaction pathways and Ras signalling pathways were significantly associated with the pNENs tumorigenesis. Co-expression network analysis revealed the differential interactions between lncRNAs and mRNAs in pNENs tumours and adjacent tissues. The genes, situated at the important nodes of the co-expression network, include ICOSLG, ENST00000512077, FGF8 and ENST00000511918.

CONCLUSIONS

There were significant differences in lncRNA and mRNA expression between pNEN tumours and adjacent tissues, and these differences were associated with tumorigenesis through multiple biological processes and signalling pathways. These results provided important insights regarding lncRNA in pNENs pathogenesis and provide potential therapeutic targets.

Hyaluronan Mediated Motility Receptor (HMMR) Encodes an Evolutionarily Conserved Homeostasis, Mitosis, and Meiosis Regulator Rather than a Hyaluronan Receptor

Hyaluronan is an extracellular matrix component that absorbs water in tissues and engages cell surface receptors, like Cluster of Differentiation 44 (CD44), to promote cellular growth and movement. Consequently, CD44 demarks stem cells in normal tissues and tumor-initiating cells isolated from neoplastic tissues. Hyaluronan mediated motility receptor (HMMR, also known as RHAMM) is another one of few defined hyaluronan receptors. HMMR is also associated with neoplastic processes and its role in cancer progression is often attributed to hyaluronan-mediated signaling. But, HMMR is an intracellular, microtubule-associated, spindle assembly factor that localizes protein complexes to augment the activities of mitotic kinases, like polo-like kinase 1 and Aurora kinase A, and control dynein and kinesin motor activities. Expression of HMMR is elevated in cells prior to and during mitosis and tissues with detectable HMMR expression tend to be highly proliferative, including neoplastic tissues. Moreover, HMMR is a breast cancer susceptibility gene product. Here, we briefly review the associations between HMMR and tumorigenesis as well as the structure and evolution of HMMR, which identifies Hmmr-like gene products in several insect species that do not produce hyaluronan. This review supports the designation of HMMR as a homeostasis, mitosis, and meiosis regulator, and clarifies how its dysfunction may promote the tumorigenic process and cancer progression.