Reactome: a database of reactions, pathways and biological processes

Towards unravelling biological mechanisms behind radiation-induced oral mucositis via mass spectrometry-based proteomics

Objective

Head and neck cancer (HNC) accounts for almost 890,000 new cases per year. Radiotherapy (RT) is used to treat the majority of these patients. A common side-effect of RT is the onset of oral mucositis, which decreases the quality of life and represents the major dose-limiting factor in RT. To understand the origin of oral mucositis, the biological mechanisms post-ionizing radiation (IR) need to be clarified. Such knowledge is valuable to develop new treatment targets for oral mucositis and markers for the early identification of "at-risk" patients.

Methods

Primary keratinocytes from healthy volunteers were biopsied, irradiated in vitro (0 and 6 Gy), and subjected to mass spectrometry-based analyses 96 h after irradiation. Web-based tools were used to predict triggered biological pathways. The results were validated in the OKF6 cell culture model. Immunoblotting and mRNA validation was performed and cytokines present in cell culture media post-IR were quantified.

Results

Mass spectrometry-based proteomics identified 5879 proteins in primary keratinocytes and 4597 proteins in OKF6 cells. Amongst them, 212 proteins in primary keratinocytes and 169 proteins in OKF6 cells were differentially abundant 96 h after 6 Gy irradiation compared to sham-irradiated controls. In silico pathway enrichment analysis predicted interferon (IFN) response and DNA strand elongation pathways as mostly affected pathways in both cell systems. Immunoblot validations showed a decrease in minichromosome maintenance (MCM) complex proteins 2-7 and an increase in IFN-associated proteins STAT1 and ISG15. In line with affected IFN signalling, mRNA levels of IFNβ and interleukin 6 (IL-6) increased significantly following irradiation and also levels of secreted IL-1β, IL-6, IP-10, and ISG15 were elevated.

Conclusion

This study has investigated biological mechanisms in keratinocytes post-in vitro ionizing radiation. A common radiation signature in keratinocytes was identified. The role of IFN response in keratinocytes along with increased levels of pro-inflammatory cytokines and proteins could hint towards a possible mechanism for oral mucositis.

Myeloid cell influx into the colonic epithelium is associated with disease severity and non-response to anti-Tumor Necrosis Factor Therapy in patients with Ulcerative Colitis

Ulcerative colitis (UC) is an idiopathic chronic inflammatory disease of the colon with sharply rising global prevalence. Dysfunctional epithelial compartment (EC) dynamics are implicated in UC pathogenesis although EC-specific studies are sparse. Applying orthogonal high-dimensional EC profiling to a Primary Cohort (PC; n=222), we detail major epithelial and immune cell perturbations in active UC. Prominently, reduced frequencies of mature BEST4+OTOP2+ absorptive and BEST2+WFDC2+ secretory epithelial enterocytes were associated with the replacement of homeostatic, resident TRDC+KLRD1+HOPX+ γδ+ T cells with RORA+CCL20+S100A4+ TH17 cells and the influx of inflammatory myeloid cells. The EC transcriptome (exemplified by S100A8, HIF1A, TREM1, CXCR1) correlated with clinical, endoscopic, and histological severity of UC in an independent validation cohort (n=649). Furthermore, therapeutic relevance of the observed cellular and transcriptomic changes was investigated in 3 additional published UC cohorts (n=23, 48 and 204 respectively) to reveal that non-response to anti-Tumor Necrosis Factor (anti-TNF) therapy was associated with EC related myeloid cell perturbations. Altogether, these data provide high resolution mapping of the EC to facilitate therapeutic decision-making and personalization of therapy in patients with UC.

Interferon-gamma ameliorates experimental autoimmune encephalomyelitis by inducing homeostatic adaptation of microglia

Compelling evidence has shown that interferon (IFN)-γ has dual effects in multiple sclerosis and in its animal model of experimental autoimmune encephalomyelitis (EAE), with results supporting both a pathogenic and beneficial function. However, the mechanisms whereby IFN-γ may promote neuroprotection in EAE and its effects on central nervous system (CNS)-resident cells have remained an enigma for more than 30 years. In this study, the impact of IFN-γ at the peak of EAE, its effects on CNS infiltrating myeloid cells (MC) and microglia (MG), and the underlying cellular and molecular mechanisms were investigated. IFN-γ administration resulted in disease amelioration and attenuation of neuroinflammation associated with significantly lower frequencies of CNS CD11b⁺ myeloid cells and less infiltration of inflammatory cells and demyelination. A significant reduction in activated MG and enhanced resting MG was determined by flow cytometry and immunohistrochemistry. Primary MC/MG cultures obtained from the spinal cord of IFN-γ-treated EAE mice that were ex vivo re-stimulated with a low dose (1 ng/ml) of IFN-γ and neuroantigen, promoted a significantly higher induction of CD4⁺ regulatory T (Treg) cells associated with increased transforming growth factor (TGF)-β secretion. Additionally, IFN-γ-treated primary MC/MG cultures produced significantly lower nitrite in response to LPS challenge than control MC/MG. IFN-γ-treated EAE mice had a significantly higher frequency of CX3CR1^high MC/MG and expressed lower levels of program death ligand 1 (PD-L1) than PBS-treated mice. Most CX3CR1^highPD-L1^lowCD11b⁺Ly6G^- cells expressed MG markers (Tmem119, Sall2, and P2ry12), indicating that they represented an enriched MG subset (CX3CR1^highPD-L1^low MG). Amelioration of clinical symptoms and induction of CX3CR1^highPD-L1^low MG by IFN-γ were dependent on STAT-1. RNA-seq analyses revealed that in vivo treatment with IFN-γ promoted the induction of homeostatic CX3CR1^highPD-L1^low MG, upregulating the expression of genes associated with tolerogenic and anti-inflammatory roles and down-regulating pro-inflammatory genes. These analyses highlight the master role that IFN-γ plays in regulating microglial activity and provide new insights into the cellular and molecular mechanisms involved in the therapeutic activity of IFN-γ in EAE.

Reversal of Lactate and PD-1-mediated Macrophage Immunosuppression Controls Growth of PTEN/p53-deficient Prostate Cancer

PURPOSE

Phosphatase and tensin homolog (PTEN) loss of function occurs in approximately 50% of patients with metastatic castrate-resistant prostate cancer (mCRPC), and is associated with poor prognosis and responsiveness to standard-of-care therapies and immune checkpoint inhibitors. While PTEN loss of function hyperactivates PI3K signaling, combinatorial PI3K/AKT pathway and androgen deprivation therapy (ADT) has demonstrated limited anticancer efficacy in clinical trials. Here, we aimed to elucidate mechanism(s) of resistance to ADT/PI3K-AKT axis blockade, and to develop rational combinatorial strategies to effectively treat this molecular subset of mCRPC.

EXPERIMENTAL DESIGN

Prostate-specific PTEN/p53-deficient genetically engineered mice (GEM) with established 150-200 mm3 tumors, as assessed by ultrasound, were treated with either ADT (degarelix), PI3K inhibitor (copanlisib), or anti-PD-1 antibody (aPD-1), as single agents or their combinations, and tumors were monitored by MRI and harvested for immune, transcriptomic, and proteomic profiling, or ex vivo co-culture studies. Single-cell RNA sequencing on human mCRPC samples was performed using 10X Genomics platform.

RESULTS

Coclinical trials in PTEN/p53-deficient GEM revealed that recruitment of PD-1-expressing tumor-associated macrophages (TAM) thwarts ADT/PI3Ki combination-induced tumor control. The addition of aPD-1 to ADT/PI3Ki combination led to TAM-dependent approximately 3-fold increase in anticancer responses. Mechanistically, decreased lactate production from PI3Ki-treated tumor cells suppressed histone lactylation within TAM, resulting in their anticancer phagocytic activation, which was augmented by ADT/aPD-1 treatment and abrogated by feedback activation of Wnt/β-catenin pathway. Single-cell RNA-sequencing analysis in mCRPC patient biopsy samples revealed a direct correlation between high glycolytic activity and TAM phagocytosis suppression.

CONCLUSIONS

Immunometabolic strategies that reverse lactate and PD-1-mediated TAM immunosuppression, in combination with ADT, warrant further investigation in patients with PTEN-deficient mCRPC.

Identifying cancer driver genes using a two-stage random walk with restart on a gene interaction network

Cancer development and progression are significantly influenced by cancer driver genes. Understanding cancer driver genes and their mechanisms of action is essential for developing effective cancer treatments. As a result, identifying driver genes is important for drug development, cancer diagnosis, and treatment. Here, we present an algorithm to discover driver genes based on the two-stage random walk with restart (RWR), and the modified method for calculating the transition probability matrix in random walk algorithm. First, we performed the first stage of RWR on the whole gene interaction network, in which we employ a new method for calculating the transition probability matrix and extracted the subnetwork based on nodes that had a high correlation with the seed nodes. The subnetwork was then applied to the second stage of RWR and the nodes were re-ranked in the subnetwork. Our approach outperformed existing methods in identifying driver genes. The outcome of the effect of three gene interaction networks, two rounds of random walk, and the seed nodes' sensitivity were all compared at the same time. In addition, we identified several potential driver genes, some of which are involved in driving cancer development. Overall, our method is efficient in various cancer types, significantly outperforms existing methods, and can identify possible driver genes.

BRD9 Degradation Disrupts Ribosome Biogenesis in Multiple Myeloma

PURPOSE

BRD9 is a defining component of the noncanonical SWI/SNF complex, which regulates gene expression by controlling chromatin dynamics. Although recent studies have found an oncogenic role for BRD9 in multiple cancer types including multiple myeloma, its clinical significance and oncogenic mechanism have not yet been elucidated. Here, we sought to identify the clinical and biological impact of BRD9 in multiple myeloma, which may contribute to the development of novel therapeutic strategies.

EXPERIMENTAL DESIGN

We performed integrated analyses of BRD9 in vitro and in vivo using multiple myeloma cell lines and primary multiple myeloma cells in established preclinical models, which identified the molecular functions of BRD9 contributing to multiple myeloma cell survival.

RESULTS

We found that high BRD9 expression was a poor prognostic factor in multiple myeloma. Depleting BRD9 by genetic (shRNA) and pharmacologic (dBRD9-A; proteolysis-targeting chimera; BRD9 degrader) approaches downregulated ribosome biogenesis genes, decreased the expression of the master regulator MYC, and disrupted the protein-synthesis maintenance machinery, thereby inhibiting multiple myeloma cell growth in vitro and in vivo in preclinical models. Importantly, we identified that the expression of ribosome biogenesis genes was associated with the disease progression and prognosis of patients with multiple myeloma. Our results suggest that BRD9 promotes gene expression by predominantly occupying the promoter regions of ribosome biogenesis genes and cooperating with BRD4 to enhance the transcriptional function of MYC.

CONCLUSIONS

Our study identifies and validates BRD9 as a novel therapeutic target in preclinical models of multiple myeloma, which provides the framework for the clinical evaluation of BRD9 degraders to improve patient outcome.

Proteostasis networks in aging: novel insights from text-mining approaches

Aging is a topic of paramount importance in an increasingly elderly society and has been the focus of extensive research. Protein homeostasis (proteostasis) decline is a hallmark in aging and several age-related diseases, but which specific proteins and mechanisms are involved in proteostasis (de)regulation during the aging process remain largely unknown. Here, we used different text-mining tools complemented with protein-protein interaction data to address this complex topic. Analysis of the integrated protein interaction networks identified novel proteins and pathways associated to proteostasis mechanisms and aging or age-related disorders, indicating that this approach is useful to identify previously unknown links and for retrieving information of potential novel biomarkers or therapeutic targets.

Prognostic biomarkers and molecular pathways mediating Helicobacter pylori–induced gastric cancer: a network-biology approach

Cancer of the stomach is the second most frequent cancer-related death worldwide. The survival rate of patients with gastric cancer (GC) remains fragile. There is a requirement to discover biomarkers for prognosis approaches. Helicobacter pylori in the stomach is closely associated with the progression of GC. We identified the genes associated with poor/favorable prognosis in H. pylori–induced GC. Multivariate statistical analysis was applied on the Gene Expression Omnibus (GEO) dataset GSE54397 to identify differentially expressed miRNAs (DEMs) in gastric tissues with H. pylori–induced cancer compared with the H. pylori–positive with non-cancerous tissue. A protein interaction map (PIM) was built and subjected to DEMs targets. The enriched pathways and biological processes within the PIM were identified based on substantial clusters. Thereafter, the most critical genes in the PIM were illustrated, and their prognostic impact in GC was investigated. Considering p-value less than 0.01 and |Log2 fold change| as >1, five microRNAs demonstrated significant changes among the two groups. Gene functional analysis revealed that the ubiquitination system, neddylation pathway, and ciliary process are primarily involved in H. pylori–induced GC. Survival analysis illustrated that the overexpression of DOCK4, GNAS, CTGF, TGF-b1, ESR1, SELE, TIMP3, SMARCE1, and TXNIP was associated with poor prognosis, while increased MRPS5 expression was related to a favorable prognosis in GC patients. DOCK4, GNAS, CTGF, TGF-b1, ESR1, SELE, TIMP3, SMARCE1, TXNIP, and MRPS5 may be considered prognostic biomarkers for H. pylori–induced GC. However, experimental validation is necessary in the future.

Accurate Prediction of Cancer Prognosis by Exploiting Patient-Specific Cancer Driver Genes

Accurate prediction of the prognoses of cancer patients and identification of prognostic biomarkers are both important for the improved treatment of cancer patients, in addition to enhanced anticancer drugs. Many previous bioinformatic studies have been carried out to achieve this goal; however, there remains room for improvement in terms of accuracy. In this study, we demonstrated that patient-specific cancer driver genes could be used to predict cancer prognoses more accurately. To identify patient-specific cancer driver genes, we first generated patient-specific gene networks before using modified PageRank to generate feature vectors that represented the impacts genes had on the patient-specific gene network. Subsequently, the feature vectors of the good and poor prognosis groups were used to train the deep feedforward network. For the 11 cancer types in the TCGA data, the proposed method showed a significantly better prediction performance than the existing state-of-the-art methods for three cancer types (BRCA, CESC and PAAD), better performance for five cancer types (COAD, ESCA, HNSC, KIRC and STAD), and a similar or slightly worse performance for the remaining three cancer types (BLCA, LIHC and LUAD). Furthermore, the case study for the identified breast cancer and cervical squamous cell carcinoma prognostic genes and their subnetworks included several pathways associated with the progression of breast cancer and cervical squamous cell carcinoma. These results suggested that heterogeneous cancer driver information may be associated with cancer prognosis.

Ethnological validation of Ashwagandha (Withania somnifera L. Dunal) ghrita as 'Vajikarana Rasayana': In-silico, in-vitro and in-vivoapproach

ETHNOPHARMACOLOGICAL RELEVANCE

Processing cow ghee (clarified butterfat) with therapeutic herbs, i.e. ghrita, is recognized for augmenting the therapeutic efficacy of plant materials. Ashwagandha ghrita (AG) is an effective Ayurvedic formulation consisting of Indian ginseng, i.e., Withania somnifera (L.) Dunal, the main constituent used to treat infertility, weakness, gynaecological disorders, and general debility.

OBJECTIVES

The present investigation was undertaken to corroborate the ethnopharmacological claim of AG as 'Vajikarana Rasayana' for its aphrodisiac potential using bioinformatics (in-silico) and experimental (in-vitro and in-vivo) approaches.

METHODS

AG was formulated as per the methods reported in Ayurved sarsangraha. AG was further subjected to HPLC, GCMS analysis, and biological (acute toxicity and aphrodisiac) assessment per the standard procedures. Thirty-eight bioactives of Indian ginseng were subjected to computational studies (molecular docking and network pharmacology) to confirm the plausible mechanism.

RESULTS

AG was found to be safe up to 2000 mg/kg body wt., and it showed dose-dependent upsurge (p < 0.01 and p < 0.05, wherever necessary) in mount and intromission frequency, genital grooming, and anogenital sniffing at 150 and 300 mg/kg body weight suggesting aphrodisiac activity. In-vitro studies demonstrated significant relaxation of the Corpus Cavernosal Smooth Muscle at all concentrations in a dose-dependent manner. Furthermore, the results of molecular modelling studies were in agreement with the biological activity and showed interaction with phosphodiesterase-5 as a possible target.

CONCLUSION

AG exhibited an aphrodisiac effect and substantiated the traditional claim of Indian ginseng-based ghrita formulation as 'Vajikarana Rasayana'.

DIAPH1 mediates progression of atherosclerosis and regulates hepatic lipid metabolism in mice

Atherosclerosis evolves through dysregulated lipid metabolism interwoven with exaggerated inflammation. Previous work implicating the receptor for advanced glycation end products (RAGE) in atherosclerosis prompted us to explore if Diaphanous 1 (DIAPH1), which binds to the RAGE cytoplasmic domain and is important for RAGE signaling, contributes to these processes. We intercrossed atherosclerosis-prone Ldlr-/- mice with mice devoid of Diaph1 and fed them Western diet for 16 weeks. Compared to male Ldlr-/- mice, male Ldlr-/- Diaph1-/- mice displayed significantly less atherosclerosis, in parallel with lower plasma concentrations of cholesterol and triglycerides. Female Ldlr-/- Diaph1-/- mice displayed significantly less atherosclerosis compared to Ldlr-/- mice and demonstrated lower plasma concentrations of cholesterol, but not plasma triglycerides. Deletion of Diaph1 attenuated expression of genes regulating hepatic lipid metabolism, Acaca, Acacb, Gpat2, Lpin1, Lpin2 and Fasn, without effect on mRNA expression of upstream transcription factors Srebf1, Srebf2 or Mxlipl in male mice. We traced DIAPH1-dependent mechanisms to nuclear translocation of SREBP1 in a manner independent of carbohydrate- or insulin-regulated cues but, at least in part, through the actin cytoskeleton. This work unveils new regulators of atherosclerosis and lipid metabolism through DIAPH1.

Preterm labor with and without chorioamnionitis is associated with activation of myometrial inflammatory networks: a comprehensive transcriptomic analysis

BACKGROUND

The onset of preterm labor is associated with inflammation. Previous studies suggested that this is distinct from the inflammation observed during term labor. Our previous work on 44 genes differentially expressed in myometria in term labor demonstrated a different pattern of gene expression from that observed in preterm laboring and nonlaboring myometria. We found increased expression of inflammatory genes in preterm labor associated with chorioamnionitis, but in the absence of chorioamnionitis observed no difference in gene expression in preterm myometria regardless of laboring status, suggesting that preterm labor is associated with different myometrial genes or signals originating from outside the myometrium. Given that a small subset of genes were assessed, this study aimed to use RNA sequencing and bioinformatics to assess the myometrial transcriptome during preterm labor in the presence and absence of chorioamnionitis.

OBJECTIVE

This study aimed to comprehensively determine protein-coding transcriptomic differences between preterm nonlaboring and preterm laboring myometria with and without chorioamnionitis.

STUDY DESIGN

Myometria were collected at cesarean delivery from preterm patients not in labor (n=16) and preterm patients in labor with chorioamnionitis (n=8) or without chorioamnionitis (n=6). Extracted RNA from myometrial tissue was prepared and sequenced using Illumina NovaSeq. Gene expression was quantified by mapping the sequence reads to the human reference genome (hg38). Differential gene expression analysis, gene set enrichment analysis, and weighted gene coexpression network analysis were used to comprehensively interrogate transcriptomic differences and their associated biology.

RESULTS

Differential gene expression analysis comparing preterm patients in labor with chorioamnionitis with preterm patients not in labor identified 931 differentially expressed genes, whereas comparing preterm patients in labor without chorioamnionitis with preterm patients not in labor identified no statistically significant gene expression changes. In contrast, gene set enrichment analysis and weighted gene coexpression network analysis demonstrated that preterm labor with and without chorioamnionitis was associated with enrichment of pathways involved in activation of the innate immune system and inflammation, and activation of G protein-coupled receptors. Key genes identified included chemotactic CYP4F3, CXCL8, DOCK2, and IRF1 in preterm labor with chorioamnionitis and CYP4F3, FCAR, CHUK, and IL13RA2 in preterm labor without chorioamnionitis. There was marked overlap in the pathways enriched in both preterm labor subtypes.

CONCLUSION

Differential gene expression analysis demonstrated that myometria from preterm patients in labor without chorioamnionitis and preterm patients not in labor were transcriptionally similar, whereas the presence of chorioamnionitis was associated with marked gene changes. In contrast, comprehensive bioinformatic analysis indicated that preterm labor with or without chorioamnionitis was associated with innate immune activation. All causes of preterm labor were associated with activation of the innate immune system, but this was more marked in the presence of chorioamnionitis. These data suggest that anti-inflammatory therapy may be relevant in managing preterm labor of all etiologies.

Identification of a physiologic vasculogenic fibroblast state to achieve tissue repair

Tissue injury to skin diminishes miR-200b in dermal fibroblasts. Fibroblasts are widely reported to directly reprogram into endothelial-like cells and we hypothesized that miR-200b inhibition may cause such changes. We transfected human dermal fibroblasts with anti-miR-200b oligonucleotide, then using single cell RNA sequencing, identified emergence of a vasculogenic subset with a distinct fibroblast transcriptome and demonstrated blood vessel forming function in vivo. Anti-miR-200b delivery to murine injury sites likewise enhanced tissue perfusion, wound closure, and vasculogenic fibroblast contribution to perfused vessels in a FLI1 dependent manner. Vasculogenic fibroblast subset emergence was blunted in delayed healing wounds of diabetic animals but, topical tissue nanotransfection of a single anti-miR-200b oligonucleotide was sufficient to restore FLI1 expression, vasculogenic fibroblast emergence, tissue perfusion, and wound healing. Augmenting a physiologic tissue injury adaptive response mechanism that produces a vasculogenic fibroblast state change opens new avenues for therapeutic tissue vascularization of ischemic wounds.

Potential Early Markers for Breast Cancer: A Proteomic Approach Comparing Saliva and Serum Samples in a Pilot Study

Breast cancer is the second leading cause of death for women in the United States, and early detection could offer patients the opportunity to receive early intervention. The current methods of diagnosis rely on mammograms and have relatively high rates of false positivity, causing anxiety in patients. We sought to identify protein markers in saliva and serum for early detection of breast cancer. A rigorous analysis was performed for individual saliva and serum samples from women without breast disease, and women diagnosed with benign or malignant breast disease, using isobaric tags for relative and absolute quantitation (iTRAQ) technique, and employing a random effects model. A total of 591 and 371 proteins were identified in saliva and serum samples from the same individuals, respectively. The differentially expressed proteins were mainly involved in exocytosis, secretion, immune response, neutrophil-mediated immunity and cytokine-mediated signaling pathway. Using a network biology approach, significantly expressed proteins in both biological fluids were evaluated for protein-protein interaction networks and further analyzed for these being potential biomarkers in breast cancer diagnosis and prognosis. Our systems approach illustrates a feasible platform for investigating the responsive proteomic profile in benign and malignant breast disease using saliva and serum from the same women.

New Biomarkers Based on Dendritic Cells for Breast Cancer Treatment and Prognosis Diagnosis

Dendritic cells(DCs) play a protective role in the antitumor immunity of most cancers, which can be divided into conventional dendritic cells (cDCs) and plasmacytoid dendritic cells (pDCs). Most current studies are only based on either cDCs or pDCs for the study of the relationship between DCs and breast cancer prognosis, without combining the two together. We aimed to select new biomarkers from pDCs and cDCs. In this paper, the xCell algorithm was first used to calculate the cellular abundance of 64 types of immune cells and stromal cells in tumor samples from the TCGA database, and the high-abundance pDC group and cDC group were divided according to the results of a survival analysis. Then, we looked for the co-expressed gene module of highly infiltrating pDC and cDC patients with a weighted correlation network analysis (WGCNA) and screened out the hub genes, including RBBP5, HNRNPU, PEX19, TPR, and BCL9. Finally, we analyzed the biological functions of the hub genes, and the results showed that RBBP5, TPR, and BCL9 were significantly related to the immune cells and prognosis of patients, and RBBP5 and BCL9 were involved in responding to TCF-related instructions of the Wnt pathway. In addition, we also evaluated the response of pDCs and cDCs with different abundances to chemotherapy, and the results showed that the higher the abundance of pDCs and cDCs, the higher their sensitivity to drugs. This paper revealed new biomarkers related to DCs-among them, BCL9, TPR, and RBBP5 were proven to be closely related to dendritic cells in cancer. For the first time, this paper puts forward that HNRNPU and PEX19 are related to the prognosis of dendritic cells in cancer, which also provides new possibilities for finding new targets for breast cancer immunotherapy.

Association study to evaluate Foxo1 and Foxo3 gene polymorphisms in polycystic ovary syndrome: a preliminary case-control study and in silico analysis

BACKGROUND

Polycystic ovary syndrome (PCOS) is known as a multifactorial and multi-gene-mediated endocrine disorder among women of reproductive age. FoxO1 and FoxO3 are members of the forkhead transcriptional factors family that play a pivotal role in the function of ovaries. The current work is aimed at investigating the association between gene variants of FoxO1 and FoxO3 and the risk of PCOS in a sample of the Iranian population.

METHODS AND RESULTS

We recruited 200 women diagnosed with PCOS and 200 healthy women. Both polymerase PCR-RFLP and ARMS-PCR methods were used for genotyping. Sanger sequencing was recruited to confirm the genotyping results. The T allele of rs17592236 and the C allele of rs12585277 decreased PCOS risk by 29 and 28%, respectively. In contrast, the C allele of rs2253310 and G allele of rs2802292 increased the risk of PCOS by 1.39 and 1.63 folds, correspondingly. Bioinformatics results showed that some genes, including matrix metallopeptidase 9 (MMP-9), phosphoinositide-3-Kinase Regulatory Subunit 224 1 (PIK3R1), peroxisome proliferator-activated receptor Gamma (PPARG), and glycogen synthase 225 kinase-3 beta (GSK-3 beta) have significant interactions with FoxO1, suggesting that FoxO1 might have crucial roles in regulating different signaling pathways in ovarian cells.

CONCLUSION

We found that FoxO1 rs17592236C > T and rs12585277C > T had a protective role against PCOS, while FoxO3 rs2253310C > G and rs2802292G > T  enhanced the risk of this metabolic disorder in our population. Additional studies on larger populations with varying races are needed to confirm these findings.

WMDS.net: a network control framework for identifying key players in transcriptome programs

MOTIVATION

Mammalian cells can be transcriptionally reprogramed to other cellular phenotypes. Controllability of such complex transitions in transcriptional networks underlying cellular phenotypes is an inherent biological characteristic. This network controllability can be interpreted by operating a few key regulators to guide the transcriptional program from one state to another. Finding the key regulators in the transcriptional program can provide key insights into the network state transition underlying cellular phenotypes.

RESULTS

To address this challenge, here, we proposed to identify the key regulators in the transcriptional co-expression network as a minimum dominating set (MDS) of driver nodes that can fully control the network state transition. Based on the theory of structural controllability, we developed a weighted MDS network model (WMDS.net) to find the driver nodes of differential gene co-expression networks. The weight of WMDS.net integrates the degree of nodes in the network and the significance of gene co-expression difference between two physiological states into the measurement of node controllability of the transcriptional network. To confirm its validity, we applied WMDS.net to the discovery of cancer driver genes in RNA-seq datasets from The Cancer Genome Atlas. WMDS.net is powerful among various cancer datasets and outperformed the other top-tier tools with a better balance between precision and recall.

AVAILABILITY AND IMPLEMENTATION

https://github.com/chaofen123/WMDS.net.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Associations of peripheral blood DNA methylation and estimated monocyte proportion differences during infancy with toddler attachment style

Attachment is a motivational system promoting felt security to a caregiver resulting in a persistent internal working model of interpersonal behavior. Attachment styles are developed in early social environments and predict future health and development outcomes with potential biological signatures, such as epigenetic modifications like DNA methylation (DNAm). Thus, we hypothesized infant DNAm would associate with toddler attachment styles. An epigenome-wide association study (EWAS) of blood DNAm from 3-month-old infants was regressed onto children's attachment style from the Strange Situation Procedure at 22-months at multiple DNAm Cytosine-phosphate-Guanine (CpG) sites. The 26 identified CpGs associated with proinflammatory immune phenotypes and cognitive development. In post-hoc analyses, only maternal cognitive-growth fostering, encouraging intellectual exploration, contributed. For disorganized children, DNAm-derived cell-type proportions estimated higher monocytes -cells in immune responses hypothesized to increase with early adversity. Collectively, these findings suggested the potential biological embedding of both adverse and advantageous social environments as early as 3-months-old.

An integrated investigation of structural and pathway alteration caused by PIK3CA and TP53 mutations identified in cfDNA of metastatic breast cancer

In peripheral blood, cell-free DNA (cfDNA) contains circulating tumor DNA (ctDNA), which indicates molecular abnormalities in metastatic breast tumor tissue. The sequencing of cfDNA of Metastatic Breast Cancer (MBC) patients allows assessment of therapy response and noninvasive treatment. In the proposed study, clinically significant alterations in PIK3CA and TP53 genes associated with MBC resulting in a missense substitution of His1047Arg and Arg282Trp from an next-generation sequencing-based multi-gene panel were reported in a cfDNA of a patient with MBC. To investigate the impact of the reported mutation, we used molecular docking, molecular dynamics simulation, network analysis, and pathway analysis. Molecular Docking analysis determined the distinct binding pattern revealing H1047R-ATP complex has a higher number of Hydrogen bonds (H-bonds) and binding affinity with a slight difference compared to the PIK3CA-ATP complex. Following, molecular dynamics simulation for 200 ns, of which H1047R-ATP complex resulted in the instability of PIK3CA. Similarly, for TP53 mutant R282W, the zinc-free state (apo) and zinc-bounded (holo) complexes were investigated for conformational change between apo and holo complexes, of which the holo complex mutant R282W was unstable. To validate the conformational change of PIK3CA and TP53, 80% mutation of H1047R in the kinase domain of p110α expressed ubiquitously in PIK3CA protein that alters PI3K pathway, while R282W mutation in DNA binding helix (H2) region of P53 protein inhibits the transcription factor in P53 pathway causing MBC. According to our findings, the extrinsic (hypoxia, oxidative stress, and acidosis); intrinsic factors (MYC amplification) in PIK3CA and TP53 mutations will provide potential insights for developing novel therapeutic methods for MBC therapy.

Time-resolved RNA signatures of CD4+ T cells in Parkinson's disease

Parkinson's disease (PD) emerges as a complex, multifactorial disease. While there is increasing evidence that dysregulated T cells play a central role in PD pathogenesis, elucidation of the pathomechanical changes in related signaling is still in its beginnings. We employed time-resolved RNA expression upon the activation of peripheral CD4+ T cells to track and functionally relate changes on cellular signaling in representative cases of patients at different stages of PD. While only few miRNAs showed time-course related expression changes in PD, we identified groups of genes with significantly altered expression for each different time window. Towards a further understanding of the functional consequences, we highlighted pathways with decreased or increased activity in PD, including the most prominent altered IL-17 pathway. Flow cytometric analyses showed not only an increased prevalence of Th17 cells but also a specific subtype of IL-17 producing γδ-T cells, indicating a previously unknown role in PD pathogenesis.

Identification of Comorbidities, Genomic Associations, and Molecular Mechanisms for COVID-19 Using Bioinformatics Approaches

Several studies have been done to identify comorbidities of COVID-19. In this work, we developed an analytical bioinformatics framework to reveal COVID-19 comorbidities, their genomic associations, and molecular mechanisms accomplishing transcriptomic analyses of the RNA-seq datasets provided by the Gene Expression Omnibus (GEO) database, where normal and infected tissues were evaluated. Using the framework, we identified 27 COVID-19 correlated diseases out of 7,092 collected diseases. Analyzing clinical and epidemiological research, we noticed that our identified 27 diseases are associated with COVID-19, where hypertension, diabetes, obesity, and lung cancer are observed several times in COVID-19 patients. Therefore, we selected the above four diseases and performed assorted analyses to demonstrate the association between COVID-19 and hypertension, diabetes, obesity, and lung cancer as comorbidities. We investigated genomic associations with the cross-comparative analysis and Jaccard's similarity index, identifying shared differentially expressed genes (DEGs) and linking DEGs of COVID-19 and the comorbidities, in which we identified hypertension as the most associated illness. We also revealed molecular mechanisms by identifying statistically significant ten pathways and ten ontologies. Moreover, to understand cellular physiology, we did protein-protein interaction (PPI) analyses among the comorbidities and COVID-19. We also used the degree centrality method and identified ten biomarker hub proteins (IL1B, CXCL8, FN1, MMP9, CXCL10, IL1A, IRF7, VWF, CXCL9, and ISG15) that associate COVID-19 with the comorbidities. Finally, we validated our findings by searching the published literature. Thus, our analytical approach elicited interconnections between COVID-19 and the aforementioned comorbidities in terms of remarkable DEGs, pathways, ontologies, PPI, and biomarker hub proteins.

Bioinformatic identification of potential biomarkers and therapeutic targets in carotid atherosclerosis and vascular dementia

Background

Vascular disease is the second most common cause of dementia. The prevalence of vascular dementia (VaD) has increased over the past decade. However, there are no licensed treatments for this disease. Carotid atherosclerosis (CAS) is highly prevalent and is the main cause of ischemic stroke and VaD. We studied co-expressed genes to understand the relationships between CAS and VaD and further reveal the potential biomarkers and therapeutic targets of CAS and VaD.

Methods

CAS and VaD differentially expressed genes (DEGs) were identified through bioinformatic analysis Gene Expression Omnibus (GEO) datasets GSE43292 and GSE122063, respectively. Furthermore, a variety of target prediction methods and network analysis approaches were used to assess the protein-protein interaction (PPI) networks, the Gene Ontology (GO) terms, and the pathway enrichment for DEGs, and the top 7 hub genes, coupled with corresponding predicted miRNAs involved in CAS and VaD, were assessed as well.

Result

A total of 60 upregulated DEGs and 159 downregulated DEGs were identified, of which the top 7 hub genes with a high degree of connectivity were selected. Overexpression of these hub genes was associated with CAS and VaD. Finally, the top 7 hub genes were coupled with corresponding predicted miRNAs. hsa-miR-567 and hsa-miR-4652-5p may be significantly associated with CAS and VaD.

Mass Spectrometry-Based Vitreous Proteomics: Validated Methods and Analysis Pipeline

Retinal diseases like diabetic retinopathy and age-related macular degeneration affect millions of individuals worldwide and often lead to vision loss. Vitreous fluid abuts the retina, is accessible for sampling, and contains many proteins related to retinal disease. Therefore, analysis of vitreous is an important tool for studying retinal disease. Because it is rich in proteins and extracellular vesicles, mass spectrometry-based proteomics is an excellent method for vitreous analysis. Here, we discuss important variables to consider when performing vitreous proteomics via mass spectrometry.

MicroRNA-Based Markers of Oral Tongue Squamous Cell Carcinoma and Buccal Squamous Cell Carcinoma: A Systems Biology Approach

Objective

Oral tongue squamous cell carcinoma (OTSCC) and buccal squamous cell carcinoma (BSCC) are the first and second leading causes of oral cancer, respectively. OTSCC and BSCC are associated with poor prognosis in patients with oral cancer. Thus, we aimed to indicate signaling pathways, Gene Ontology terms, and prognostic markers mediating the malignant transformation of the normal oral tissue to OTSCC and BSCC.

Methods

The dataset GSE168227 was downloaded and reanalyzed from the GEO database. Orthogonal partial least square (OPLS) analysis identified common differentially expressed miRNAs (DEMs) in OTSCC and BSCC compared to their adjacent normal mucosa. Next, validated targets of DEMs were identified using the TarBase web server. With the use of the STRING database, a protein interaction map (PIM) was created. Using the Cytoscape program, hub genes and clusters within the PIM were shown. Next, gene-set enrichment analysis was carried out using the g:Profiler tool. Using the GEPIA2 web tool, analyses of gene expression and survival analysis were also performed.

Results

Two DEMs, including has-miR-136 and has-miR-377, were common in OTSCC and BSCC (p value <0.01; |Log2 FC| > 1). A total of 976 targets were indicated for common DEMs. PIM included 96 hubs, and the upregulation of EIF2S1, CAV1, RAN, ANXA5, CYCS, CFL1, MYC, HSP90AA1, PKM, and HSPA5 was significantly associated with a poor prognosis in the head and neck squamous cell carcinoma (HNSCC), while NTRK2, HNRNPH1, DDX17, and WDR82 overexpression was significantly linked to favorable prognosis in the patients with HNSCC. "Clathrin-mediated endocytosis" was considerably dysregulated in OTSCC and BSCC.

Conclusion

The present study suggests that has-miR-136 and has-miR-377 are underexpressed in OTSCC and BSCC than in normal oral mucosa. Moreover, EIF2S1, CAV1, RAN, ANXA5, CYCS, CFL1, MYC, HSP90AA1, PKM, HSPA5, NTRK2, HNRNPH1, DDX17, and WDR82 demonstrated prognostic markers in HNSCC. These findings may benefit the prognosis and management of individuals with OTSCC/BSCC. However, additional experimental verification is required.

Pathway-Specific Polygenic Risk Scores Correlate with Clinical Status and Alzheimer's Disease-Related Biomarkers

BACKGROUND

APOE is the largest genetic risk factor for Alzheimer's disease (AD), but there is a substantial polygenic component. Polygenic risk scores (PRS) can summarize small effects across the genome but may obscure differential risk across molecular processes and pathways that contribute to heterogeneity of disease presentation.

OBJECTIVE

We examined polygenic risk impacting specific AD-associated pathways and its relationship with clinical status and biomarkers of amyloid, tau, and neurodegeneration (A/T/N).

METHODS

We analyzed data from 1,411 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We applied pathway analysis and clustering to identify AD-associated "pathway clusters" and construct pathway-specific PRSs (excluding the APOE region). We tested associations with diagnostic status, abnormal levels of amyloid and ptau, and hippocampal volume.

RESULTS

Thirteen pathway clusters were identified, and eight pathway-specific PRSs were significantly associated with AD diagnosis. Amyloid-positivity was associated with endocytosis and fibril formation, response misfolded protein, and regulation protein tyrosine PRSs. Ptau positivity and hippocampal volume were both related to protein localization and mitophagy PRS, and ptau-positivity was also associated with an immune signaling PRS. A global AD PRS showed stronger associations with diagnosis and all biomarkers compared to pathway PRSs.

CONCLUSIONS

Pathway PRS may contribute to understanding separable disease processes, but do not add significant power for predictive purposes. These findings demonstrate that AD-phenotypes may be preferentially associated with risk in specific pathways, and defining genetic risk along multiple dimensions may clarify etiological heterogeneity in AD. This approach to delineate pathway-specific PRS can be used to study other complex diseases.

Deep learning-derived cardiovascular age shares a genetic basis with other cardiac phenotypes

Artificial intelligence (AI)-based approaches can now use electrocardiograms (ECGs) to provide expert-level performance in detecting heart abnormalities and diagnosing disease. Additionally, patient age predicted from ECGs by AI models has shown great potential as a biomarker for cardiovascular age, where recent work has found its deviation from chronological age ("delta age") to be associated with mortality and co-morbidities. However, despite being crucial for understanding underlying individual risk, the genetic underpinning of delta age is unknown. In this work we performed a genome-wide association study using UK Biobank data (n=34,432) and identified eight loci associated with delta age ([Formula: see text]), including genes linked to cardiovascular disease (CVD) (e.g. SCN5A) and (heart) muscle development (e.g. TTN). Our results indicate that the genetic basis of cardiovascular ageing is predominantly determined by genes directly involved with the cardiovascular system rather than those connected to more general mechanisms of ageing. Our insights inform the epidemiology of CVD, with implications for preventative and precision medicine.

Dynamic regulation and key roles of ribonucleic acid methylation

Ribonucleic acid (RNA) methylation is the most abundant modification in biological systems, accounting for 60% of all RNA modifications, and affects multiple aspects of RNA (including mRNAs, tRNAs, rRNAs, microRNAs, and long non-coding RNAs). Dysregulation of RNA methylation causes many developmental diseases through various mechanisms mediated by N ⁶-methyladenosine (m⁶A), 5-methylcytosine (m⁵C), N ¹-methyladenosine (m¹A), 5-hydroxymethylcytosine (hm⁵C), and pseudouridine (Ψ). The emerging tools of RNA methylation can be used as diagnostic, preventive, and therapeutic markers. Here, we review the accumulated discoveries to date regarding the biological function and dynamic regulation of RNA methylation/modification, as well as the most popularly used techniques applied for profiling RNA epitranscriptome, to provide new ideas for growth and development.

Characterization of circular RNAs in dorsal root ganglia after central and peripheral axon injuries

In central nervous system, axons fail to regenerate after injury while in peripheral nervous system, axons retain certain regenerative ability. Dorsal root ganglion (DRG) neuron has an ascending central axon branch and a descending peripheral axon branch stemming from one single axon and serves as a suitable model for the comparison of growth competence following central and peripheral axon injuries. Molecular alterations underpin different injury responses of DRG branches have been investigated from many aspects, such as coding gene expression, chromatin accessibility, and histone acetylation. However, changes of circular RNAs are poorly characterized. In the present study, we comprehensively investigate circular RNA expressions in DRGs after rat central and peripheral axon injuries using sequencing analysis and identify a total of 33 differentially expressed circular RNAs after central branch injury as well as 55 differentially expressed circular RNAs after peripheral branch injury. Functional enrichment of host genes of differentially expressed circular RNAs demonstrate the participation of Hippo signaling pathway and Notch signaling pathway after both central and peripheral axon injuries. Circular RNA changes after central axon injury are also linked with apoptosis and cellular junction while changes after peripheral axon injury are associated with metabolism and PTEN-related pathways. Altogether, the present study offers a systematic evaluation of alterations of circular RNAs in rat DRGs following injuries to the central and peripheral axon branches and contributes to the deciphering of essential biological activities and mechanisms behind successful nerve regeneration.

Inactivation of Notch4 Attenuated Pancreatic Tumorigenesis in Mice

Expression of the Notch family of receptors is often upregulated in pancreatic ductal adenocarcinoma (PDAC). In this study, we focused on Notch4, which had not been investigated in PDAC. We generated KC (LSL-KrasG12D;p48-Cre), N4 - / - KC (Notch4- / -;LSL-KrasG12D;p48-Cre), PKC (p16fl/fl;LSL-KrasG12D;p48-Cre), and N4 - / - PKC (Notch4-/ -; p16fl/f l;LSL-KrasG12D;p48-Cre) genetically engineered mouse models (GEMM). We performed caerulein treatment in both KC and N4 - / - KC mice, and the development of acinar-to-ductal metaplasia (ADM) and pancreatic intraepithelial neoplasia (PanIN) lesions were significantly diminished in the N4 - / - KC than in the KC GEMM (P = 0.01). This in vivo result was validated by in vitro ADM induction of the explant cultures of pancreatic acinar cells from the N4 - / - KC and KC mice (P < 0.001), confirming that Notch4 is an important contributor to early pancreatic tumorigenesis. To evaluate the role of Notch4 in the later stage of pancreatic tumorigenesis, we compared the PKC and N4 - / - PKC mice. The N4 - / - PKC mice had better overall survival (P = 0.012) and significantly reduced tumor burden (PanIN: P = 0.018 at 2 months, PDAC: P = 0.039 at 5 months) compared with the PKC GEMM. RNA-sequencing analysis of pancreatic tumor cell lines derived from the PKC and N4 - / - PKC GEMMs revealed that 408 genes were differentially expressed (FDR < 0.05) and Pcsk5 is a potential downstream effector of the Notch4 signaling pathway (P < 0.001). Low expression of Pcsk5 positively correlates with good survival in patients with PDAC (P = 0.028). We have identified a novel role for Notch4 signaling with tumor-promoting function in pancreatic tumorigenesis. Our study also uncovered a novel association between Pcsk5 and Notch4 signaling in PDAC.

Significance

We demonstrated that global inactivation of Notch4 significantly improved the survival of an aggressive mouse model for PDAC and provided preclinical evidence that Notch4 and Pcsk5 are novel targets for PDAC therapies.

Identification of characteristic markers correlated with Th2 cell infiltration and metabolism molecular subtype in pancreatic adenocarcinoma

Background

Pancreatic adenocarcinoma, the deadliest malignant cancer, has gradually become the third leading cause of cancer-related death. Multidisciplinary therapy has been difficult to implement because of the particularity of pancreatic adenocarcinoma. Research has increasingly indicated the significance of metabolic adaption in pancreatic adenocarcinoma. The difference in metabolism may influence immune cell infiltration in pancreatic adenocarcinoma. Novel immune-related metabolism biomarkers are needed to improve the therapeutic outcomes of existing targeted therapies.

Methods

We enrolled whole-genome sequencing data and clinical information about 168 pancreatic adenocarcinoma samples from The Cancer Genome Atlas (TCGA) database, other pancreatic adenocarcinoma samples, and clinical information from other cohorts. We used the gene set variation analysis (GSVA) package to calculate feature score, the weighted gene co-expression network analysis (WGCNA) and randomSurvivalForest package to screen hub genes, the ConsenClusterPlus package to classify subtypes, the pRRopthetic package to evaluate drug sensibility, the maftools package to analyze mutation information and the Seurat package to analyze single cell sequencing data.

Results

We revealed the prognosis significance of Th2 cell infiltration, classified two subtypes based on hub genes, compared immune cell infiltration, substance metabolism, cellular processes, gene mutation, and copy number variation (CNV) between subtypes and explored the clinical and biological features of Th2 cell infiltration.

Conclusions

We displayed the poor prognosis significance of Th2 cell infiltration and the significant difference of simple nucleotide polymorphism, CNV, natural killer (NK) CD56 bright cell infiltration, substance metabolism, autophagy and necroptosis between subtypes. Additionally, we discovered the sensitivity difference of chemotherapy drug and the Th2 cell infiltration changes after chimeric antigen receptor T cells (CAR-T) cell therapy and radiotherapy and explored the differences between normal liver and metastatic liver tissues of pancreatic adenocarcinoma patients.

Cell-type Deconvolution and Age Estimation Using DNA Methylation Reveals NK Cell Deficiency in the Hepatocellular Carcinoma Microenvironment

Hepatocellular carcinoma (HCC) has been an approved indication for the administration of immunotherapy since 2017, but biomarkers that predict therapeutic response have remained limited. Understanding and characterizing the tumor immune microenvironment enables better classification of these tumors and may reveal biomarkers that predict immunotherapeutic efficacy. In this paper, we applied a cell-type deconvolution algorithm using DNA methylation array data to investigate the composition of the tumor microenvironment in HCC. Using two publicly available datasets with a total cohort size of 57 patients, each with tumor and matched normal tissue samples, we identified key differences in immune cell composition. We found that NK cell abundance was significantly decreased in HCC tumors compared to adjacent normal tissue. We also applied DNA methylation "clocks" which estimate phenotypic aging and compared these findings to expression-based determinations of cellular senescence. Senescence and epigenetic aging was significantly increased in HCC tumors, and the degree of age acceleration and senescence was strongly associated with decreased NK cell abundance. In summary, we found that NK cell infiltration in the tumor microenvironment is significantly diminished, and that this loss of NK abundance is strongly associated with increased senescence and age-related phenotype. These findings point to key interactions between NK cells and the senescent tumor microenvironment and offer insights into the pathogenesis of HCC as well as potential biomarkers of therapeutic efficacy.

Exosomes Released by Influenza-Virus-Infected Cells Carry Factors Capable of Suppressing Immune Defense Genes in Naïve Cells

Background: Exosomes are involved in intercellular communication and can transfer regulatory molecules between cells. Consequently, they can participate in host immune response regulation. For the influenza A virus (IAV), there is very limited information on changes in exosome composition during cell infection shedding light on the potential role of these extracellular membrane vesicles. Thus, the aim of our work was to study changes in exosomal composition following IAV infection of cells, as well as to evaluate their effect on uninfected cells. Methods: To characterize changes in the composition of cellular miRNAs and mRNAs of exosomes during IAV infection of A549 cells, NGS was used, as well as PCR to identify viral genes. Naïve A549 cells were stimulated with infected-cell-secreted exosomes for studying their activity. Changes in the expression of genes associated with the cell's immune response were shown using PCR. The effect of exosomes on IAV replication was shown in MDCK cells using In-Cell ELISA and PCR of the supernatants. Results: A change in the miRNA composition (miR-21-3p, miR-26a-5p, miR-23a-5p, miR-548c-5p) and mRNA composition (RPL13A, MKNK2, TRIB3) of exosomes under the influence of the IAV was shown. Many RNAs were involved in the regulation of the immune response of the cell, mainly by suppressing it. After exosome stimulation of naïve cells, a significant decrease in the expression of genes involved in the immune response was shown (RIG1, IFIT1, MDA5, COX2, NFκB, AnxA1, PKR, IL6, IL18). When infecting MDCK cells, a significant decrease in nucleoprotein levels was observed in the presence of exosomes secreted by mock-infected cells. Viral levels in supernatants also decreased. Conclusions: Exosomes secreted by IAV-infected cells could reduce the immune response of neighboring intact cells, leading to more effective IAV replication. This may be associated both with regulatory functions of cellular miRNAs and mRNAs carried by exosomes, or with the presence of viral mRNAs encoding proteins with an immunosuppressive function.

Transcriptomic profiling implicates PAF1 in both active and repressive immune regulatory networks

BACKGROUND

Sitting at the interface of gene expression and host-pathogen interaction, polymerase associated factor 1 complex (PAF1C) is a rising player in the innate immune response. The complex localizes to the nucleus and associates with chromatin to modulate RNA polymerase II (RNAPII) elongation of gene transcripts. Performing this function at both proximal and distal regulatory elements, PAF1C interacts with many host factors across such sites, along with several microbial proteins during infection. Therefore, translating the ubiquity of PAF1C into specific impacts on immune gene expression remains especially relevant.

RESULTS

Advancing past work, we treat PAF1 knockout cells with a slate of immune stimuli to identify key trends in PAF1-dependent gene expression with broad analytical depth. From our transcriptomic data, we confirm PAF1 is an activator of traditional immune response pathways as well as other cellular pathways correlated with pathogen defense. With this model, we employ computational approaches to refine how PAF1 may contribute to both gene activation and suppression. Specifically focusing on transcriptional motifs and regulons, we predict gene regulatory elements strongly associated with PAF1, including those implicated in an immune response. Overall, our results suggest PAF1 is involved in innate immunity at several distinct axes of regulation.

CONCLUSIONS

By identifying PAF1-dependent gene expression across several pathogenic contexts, we confirm PAF1C to be a key mediator of innate immunity. Combining these transcriptomic profiles with potential regulatory networks corroborates the previously identified functions of PAF1C. With this, we foster new avenues for its study as a regulator of innate immunity, and our results will serve as a basis for targeted study of PAF1C in future validation studies.

Chronic stress causes striatal disinhibition mediated by SOM-interneurons in male mice

Chronic stress (CS) is associated with a number of neuropsychiatric disorders, and it may also contribute to or exacerbate motor function. However, the mechanisms by which stress triggers motor symptoms are not fully understood. Here, we report that CS functionally alters dorsomedial striatum (DMS) circuits in male mice, by affecting GABAergic interneuron populations and somatostatin positive (SOM) interneurons in particular. Specifically, we show that CS impairs communication between SOM interneurons and medium spiny neurons, promoting striatal overactivation/disinhibition and increased motor output. Using probabilistic machine learning to analyze animal behavior, we demonstrate that in vivo chemogenetic manipulation of SOM interneurons in DMS modulates motor phenotypes in stressed mice. Altogether, we propose a causal link between dysfunction of striatal SOM interneurons and motor symptoms in models of chronic stress.

Optimal construction of a functional interaction network from pooled library CRISPR fitness screens

BACKGROUND

Functional interaction networks, where edges connect genes likely to operate in the same biological process or pathway, can be inferred from CRISPR knockout screens in cancer cell lines. Genes with similar knockout fitness profiles across a sufficiently diverse set of cell line screens are likely to be co-functional, and these "coessentiality" networks are increasingly powerful predictors of gene function and biological modularity. While several such networks have been published, most use different algorithms for each step of the network construction process.

RESULTS

In this study, we identify an optimal measure of functional interaction and test all combinations of options at each step-essentiality scoring, sample variance and covariance normalization, and similarity measurement-to identify best practices for generating a functional interaction network from CRISPR knockout data. We show that Bayes Factor and Ceres scores give the best results, that Ceres outperforms the newer Chronos scoring scheme, and that covariance normalization is a critical step in network construction. We further show that Pearson correlation, mathematically identical to ordinary least squares after covariance normalization, can be extended by using partial correlation to detect and amplify signals from "moonlighting" proteins which show context-dependent interaction with different partners.

CONCLUSIONS

We describe a systematic survey of methods for generating coessentiality networks from the Cancer Dependency Map data and provide a partial correlation-based approach for exploring context-dependent interactions.

Data-driven analysis and druggability assessment methods to accelerate the identification of novel cancer targets

Over the past few decades, drug discovery has greatly improved the outcomes for patients, but several challenges continue to hinder the rapid development of novel drugs. Addressing unmet clinical needs requires the pursuit of drug targets that have a higher likelihood to lead to the development of successful drugs. Here we describe a bioinformatic approach for identifying novel cancer drug targets by performing statistical analysis to ascertain quantitative changes in expression levels between protein-coding genes, as well as co-expression networks to classify these genes into groups. Subsequently, we provide an overview of druggability assessment methodologies to prioritize and select the best targets to pursue.

Genome-wide analyses identify novel risk loci for cluster headache in Han Chinese residing in Taiwan

BACKGROUND

Cluster headache is a highly debilitating neurological disorder with considerable inter-ethnic differences. Genome-wide association studies (GWAS) recently identified replicable genomic loci for cluster headache in Europeans, but the genetic underpinnings for cluster headache in Asians remain unclear. The objective of this study is to investigate the genetic architecture and susceptibility loci of cluster headache in Han Chinese resided in Taiwan.

METHODS

We conducted a two-stage genome-wide association study in a Taiwanese cohort enrolled from 2007 through 2022 to identify the genetic variants associated with cluster headache. Diagnosis of cluster headache was retrospectively ascertained with the criteria of International Classification of Headache Disorders, third edition. Control subjects were enrolled from the Taiwan Biobank. Genotyping was conducted with the Axiom Genome-Wide Array TWB chip, followed by whole genome imputation. A polygenic risk score was developed to differentiate patients from controls. Downstream analyses including gene-set and tissue enrichment, linkage disequilibrium score regression, and pathway analyses were performed.

RESULTS

We enrolled 734 patients with cluster headache and 9,846 population-based controls. We identified three replicable loci, with the lead SNPs being rs1556780 in CAPN2 (odds ratio = 1.59, 95% CI 1.42‒1.78, p = 7.61 × 10^-16), rs10188640 in MERTK (odds ratio = 1.52, 95% CI 1.33‒1.73, p = 8.58 × 10^-13), and rs13028839 in STAB2 (odds ratio = 0.63, 95% CI 0.52‒0.78, p = 2.81 × 10^-8), with the latter two replicating the findings in European populations. Several previously reported genes also showed significant associations with cluster headache in our samples. Polygenic risk score differentiated patients from controls with an area under the receiver operating characteristic curve of 0.77. Downstream analyses implicated circadian regulation and immunological processes in the pathogenesis of cluster headache.

CONCLUSIONS

This study revealed the genetic architecture and novel susceptible loci of cluster headache in Han Chinese residing in Taiwan. Our findings support the common genetic contributions of cluster headache across ethnicities and provide novel mechanistic insights into the pathogenesis of cluster headache.

SyBLaRS: A web service for laying out, rendering and mining biological maps in SBGN, SBML and more

Visualization is a key recurring requirement for effective analysis of relational data. Biology is no exception. It is imperative to annotate and render biological models in standard, widely accepted formats. Finding graph-theoretical properties of pathways as well as identifying certain paths or subgraphs of interest in a pathway are also essential for effective analysis of pathway data. Given the size of available biological pathway data nowadays, automatic layout is crucial in understanding the graphical representations of such data. Even though there are many available software tools that support graphical display of biological pathways in various formats, there is none available as a service for on-demand or batch processing of biological pathways for automatic layout, customized rendering and mining paths or subgraphs of interest. In addition, there are many tools with fine rendering capabilities lacking decent automatic layout support.

To fill this void, we developed a web service named SyBLaRS (Systems Biology Layout and Rendering Service) for automatic layout of biological data in various standard formats as well as construction of customized images in both raster image and scalable vector formats of these maps. Some of the supported standards are more generic such as GraphML and JSON, whereas others are specialized to biology such as SBGNML (The Systems Biology Graphical Notation Markup Language) and SBML (The Systems Biology Markup Language). In addition, SyBLaRS supports calculation and highlighting of a number of well-known graph-theoretical properties as well as some novel graph algorithms turning a specified set of objects of interest to a minimal pathway of interest.

We demonstrate that SyBLaRS can be used both as an offline layout and rendering service to construct customized and annotated pictures of pathway models and as an online service to provide layout and rendering capabilities for systems biology software tools.

SyBLaRS is open source and publicly available on GitHub and freely distributed under the MIT license. In addition, a sample deployment is available here for public consumption.

Maternal plasma proteome profiling of biomarkers and pathogenic mechanisms of early-onset and late-onset preeclampsia

Preeclampsia is still the leading cause of morbidity and mortality in pregnancy without a cure. There are two phenotypes of preeclampsia, early-onset (EOPE) and late-onset (LOPE) with poorly defined pathogenic differences. This study aimed to facilitate better understanding of the mechanisms of pathophysiology of EOPE and LOPE, and identify specific biomarkers or therapeutic targets. In this study, we conducted an untargeted, label-free quantitative proteomic analyses of plasma samples from pregnant women with EOPE (n = 17) and LOPE (n = 11), and age, BMI-matched normotensive controls (n = 18). Targeted proteomics approach was also employed to validate a subset of proteins (n = 17). In total, there were 26 and 20 differentially abundant proteins between EOPE or LOPE, and normotensive controls, respectively. A series of angiogenic and inflammatory proteins, including insulin-like growth factor-binding protein 4 (IGFBP4; EOPE: FDR = 0.0030 and LOPE: FDR = 0.00396) and inter-alpha-trypsin inhibitor heavy chain H2-4 (ITIH2-4), were significantly altered in abundance in both phenotypes. Through validation we confirmed that ITIH2 was perturbed only in LOPE (p = 0.005) whereas ITIH3 and ITIH4 were perturbed in both phenotypes (p < 0.05). Overall, lipid metabolism/transport proteins associated with atherosclerosis were highly abundant in LOPE, however, ECM proteins had a more pronounced role in EOPE. The complement cascade and binding and uptake of ligands by scavenger receptors, pathways, were associated with both EOPE and LOPE.

Modulation of Monocyte Response by Microrna-15b/106a/374a During Antibody-mediated Rejection in Kidney Transplantation

BACKGROUND

Increasing evidence suggest that microRNAs are involved in the physiopathology of acute or chronic renal disease. In kidney transplantation, as key regulators of cellular homeostasis, microRNAs may be involved in the regulation of immune cell function and the allograft response. Here, we investigated the change in circulating microRNA expression profile and their involvement in the profound transcriptional changes associated with antibody-mediated rejection (ABMR).

METHODS

Blood samples were collected at the time of the 710 kidney allograft biopsies at 4 European transplant centers. Messenger RNA and microRNA profiling analyses were performed in a discovery-to-validation study within 3 independent cohorts encompassing N = 126, N = 135, and N = 416 patients, respectively.

RESULTS

Compared with samples with no ABMR, 14 microRNAs were significantly decreased in ABMR samples. Among them, expression levels of microRNA-15b, microRNA-106a, and microRNA-374a gradually decreased with the severity of ABMR lesions. From their in silico-predicted target genes, a high proportion proved to be significantly upregulated in the paired transcriptomic analysis. Gene ontology analyses of microRNA-15b/-106a/-374a suggested enrichment in myeloid-related pathways, which was further refined by in silico and ex vivo transcriptomic analyses, showing a specific origin from classical CD14 + monocytes. Finally, human CD14 + monocytes were subjected to transduction by antago-microRNAs to mimic ABMR pathology. MicroRNA-15b/-106a/-374a impairment resulted in cellular activation with an increased expression of CD69, CRIM1, IPO7, and CAAP1, direct and common targets of the 3 microRNAs.

CONCLUSIONS

Together, our data provide new insights into circulating microRNAs as markers and key players in ABMR, and they suggest monocyte involvement in this process.

The RPL/RPS gene signature of melanoma CTCs associates with brain metastasis

Melanoma brain metastasis (MBM) is linked to poor prognosis and low overall survival. We hypothesized that melanoma circulating tumor cells (CTCs) possess a gene signature significantly expressed and associated with MBM. Employing a multi-pronged approach, we provide first-time evidence identifying a common CTC gene signature for ribosomal protein large/small subunits (RPL/RPS) which associate with MBM onset and progression. Experimental strategies involved capturing, transcriptional profiling and interrogating CTCs, either directly isolated from blood of melanoma patients at distinct stages of MBM progression or from CTC-driven MBM in experimental animals. Second, we developed the first Magnetic Resonance Imaging (MRI) CTC-derived MBM xenograft model (MRI-MBM CDX) to discriminate MBM spatial and temporal growth, recreating MBM clinical presentation and progression. Third, we performed the comprehensive transcriptional profiling of MRI-MBM CDXs, along with longitudinal monitoring of CTCs from CDXs possessing/not possessing MBM. Our findings suggest that enhanced ribosomal protein content/ribogenesis may contribute to MBM onset. Since ribosome modifications drive tumor progression and metastatic development by remodeling CTC translational events, overexpression of the CTC RPL/RPS gene signature could be implicated in MBM development. Collectively, this study provides important insights for relevance of the CTC RPL/RPS gene signature in MBM, and identify potential targets for therapeutic intervention to improve patient care for melanoma patients diagnosed with or at high-risk of developing MBM.

Endotype reversal as a novel strategy for screening drugs targeting familial Alzheimer's disease

While amyloid-β (Aβ) plaques are considered a hallmark of Alzheimer's disease, clinical trials focused on targeting gamma secretase, an enzyme involved in aberrant Aβ peptide production, have not led to amelioration of AD symptoms or synaptic dysregulation. Screening strategies based on mechanistic, multi-omics approaches that go beyond pathological readouts can aid in the evaluation of therapeutics. Using early-onset Alzheimer's (EOFAD) disease patient lineage PSEN1^A246E iPSC-derived neurons, we performed RNA-seq to characterize AD-associated endotypes, which are in turn used as a screening evaluation metric for two gamma secretase drugs, the inhibitor Semagacestat and the modulator BPN-15606. We demonstrate that drug treatment partially restores the neuronal state while concomitantly inhibiting cell cycle re-entry and dedifferentiation endotypes to different degrees depending on the mechanism of gamma secretase engagement. Our endotype-centric screening approach offers a new paradigm by which candidate AD therapeutics can be evaluated for their overall ability to reverse disease endotypes.

Applying differential network analysis to longitudinal gene expression in response to perturbations

Differential Network (DN) analysis is a method that has long been used to interpret changes in gene expression data and provide biological insights. The method identifies the rewiring of gene networks in response to external perturbations. Our study applies the DN method to the analysis of RNA-sequencing (RNA-seq) time series datasets. We focus on expression changes: (i) in saliva of a human subject after pneumococcal vaccination (PPSV23) and (ii) in primary B cells treated ex vivo with a monoclonal antibody drug (Rituximab). The DN method enabled us to identify the activation of biological pathways consistent with the mechanisms of action of the PPSV23 vaccine and target pathways of Rituximab. The community detection algorithm on the DN revealed clusters of genes characterized by collective temporal behavior. All saliva and some B cell DN communities showed characteristic time signatures, outlining a chronological order in pathway activation in response to the perturbation. Moreover, we identified early and delayed responses within network modules in the saliva dataset and three temporal patterns in the B cell data.

Cellular shape reinforces niche to stem cell signaling in the small intestine

Niche-derived factors regulate tissue stem cells, but apart from the mechanosensory pathways, the effect of niche geometry is not well understood. We used organoids and bioengineered tissue culture platforms to demonstrate that the conical shape of Lgr5+ small intestinal stem cells (ISCs) facilitate their self-renewal and function. Inhibition of non-muscle myosin II (NM II)-driven apical constriction altered ISC shape and reduced niche curvature and stem cell capacity. Niche curvature is decreased in aged mice, suggesting that suboptimal interactions between old ISCs and their niche develop with age. We show that activation of NM IIC or physical restriction to young topology improves in vitro regeneration by old epithelium. We propose that the increase in lateral surface area of ISCs induced by apical constriction promotes interactions between neighboring cells, and the curved topology of the intestinal niche has evolved to maximize signaling between ISCs and neighboring cells.

Transcriptomic profiling of sporadic Alzheimer's disease patients

Alzheimer's disease (AD) manifested before age 65 is commonly referred to as early-onset AD (EOAD) (Reitz et al. Neurol Genet. 2020;6:e512). While the majority (> 90%) of EOAD cases are not caused by autosomal-dominant mutations in PSEN1, PSEN2, and APP, they do have a higher heritability (92-100%) than sporadic late-onset AD (LOAD, 70%) (Wingo et al. Arch Neurol. 2012;69:59-64, Fulton-Howard et al. Neurobiol Aging. 2021;99:101.e1-101.e9). Although the endpoint clinicopathological changes, i.e., Aβ plaques, tau tangles, and cognitive decline, are common across EOAD and LOAD, the disease progression is highly heterogeneous (Neff et al. Sci Adv Am Assoc Adv Sci. 2021;7:eabb5398). This heterogeneity, leading to temporally distinct age at onset (AAO) and stages of cognitive decline, may be caused by myriad combinations of distinct disease-associated molecular mechanisms. We and others have used transcriptome profiling in AD patient-derived neuron models of autosomal-dominant EOAD and sporadic LOAD to identify disease endotypes (Caldwell et al. Sci Adv Am Assoc Adv Sci. 2020;6:eaba5933, Mertens et al. Cell Stem Cell. 2021;28:1533-1548.e6, Caldwell et al. Alzheimers Demen. 2022). Further, analyses of large postmortem brain cohorts demonstrate that only one-third of AD patients show hallmark disease endotypes like increased inflammation and decreased synaptic signaling (Neff et al. Sci Adv Am Assoc Adv Sci. 2021;7:eabb5398). Areas of the brain less affected by AD pathology at early disease stages-such as the primary visual cortex-exhibit similar transcriptomic dysregulation as those regions traditionally affected and, therefore, may offer a view into the molecular mechanisms of AD without the associated inflammatory changes and gliosis induced by pathology (Haroutunian et al. Neurobiol Aging. 2009;30:561-73). To this end, we analyzed AD patient samples from the primary visual cortex (19 EOAD, 20 LOAD) using transcriptomic signatures to identify patient clusters and disease endotypes. Interestingly, although the clusters showed distinct combinations and severity of endotypes, each patient cluster contained both EOAD and LOAD cases, suggesting that AAO may not directly correlate with the identity and severity of AD endotypes.

CellCallEXT: Analysis of Ligand-Receptor and Transcription Factor Activities in Cell-Cell Communication of Tumor Immune Microenvironment

Simple Summary

CellCall is an R package tool that is used to analyze cell–cell communication based on transcription factor (TF) activities calculated by cell-type specificity of target genes and thus cannot directly handle two-condition comparisons. We developed CellCallEXT to complement CellCall. CellCallEXT can directly identify ligand–receptor (L–R) interactions that alter the expression profiles of downstream genes between two conditions, such as tumor and healthy tissue. Scoring in CellCallEXT quantitatively integrates expression of ligands, receptors, TFs, and target genes (TGs). The pathway enrichment analysis and visualization modules allow biologists to investigate how disease alters cell–cell communication. Furthermore, Reactome pathways were added into CellCallEXT to expand the L–R–TF database.

Abstract

(1) Background: Single-cell RNA sequencing (scRNA-seq) data are useful for decoding cell–cell communication. CellCall is a tool that is used to infer inter- and intracellular communication pathways by integrating paired ligand–receptor (L–R) and transcription factor (TF) activities from steady-state data and thus cannot directly handle two-condition comparisons. For tumor and healthy status, it can only individually analyze cells from tumor or healthy tissue and examine L–R pairs only identified in either tumor or healthy controls, but not both together. Furthermore, CellCall is highly affected by gene expression specificity in tissues. (2) Methods: CellCallEXT is an extension of CellCall that deconvolutes intercellular communication and related internal regulatory signals based on scRNA-seq. Information on Reactome was retrieved and integrated with prior knowledge of L–R–TF signaling and gene regulation datasets of CellCall. (3) Results: CellCallEXT was successfully applied to examine tumors and immune cell microenvironments and to identify the altered L–R pairs and downstream gene regulatory networks among immune cells. Application of CellCallEXT to scRNA-seq data from patients with deficiency of adenosine deaminase 2 demonstrated its ability to impute dysfunctional intercellular communication and related transcriptional factor activities. (4) Conclusions: CellCallEXT provides a practical tool to examine intercellular communication in disease based on scRNA-seq data.

Systemic Biomarkers and Unique Pathways in Different Phenotypes of Heart Failure with Preserved Ejection Fraction

Heart failure with preserved ejection fraction (HFpEF) accounts for around 50% of all heart failure cases. It is a heterogeneous condition with poorly understood pathogenesis. Here, we aimed to identify unique pathogenic mechanisms in acute and chronic HFpEF and hypertrophic cardiomyopathy (HCM). We performed unbiased, comprehensive proteomic analyses of plasma samples from gender- and BMI-matched patients with acute HFpEF (n = 8), chronic HFpEF (n = 9) and HCM (n = 14) using liquid chromatography–mass spectrometry. Distinct molecular signatures were observed in different HFpEF forms. Clusters of biomarkers differentially abundant between HFpEF forms were predominantly associated with microvascular inflammation. New candidate protein markers were also identified, including leucine-rich alpha-2-glycoprotein 1 (LRG1), serum amyloid A1 (SAA1) and inter-alpha-trypsin inhibitor heavy chain 3 (ITIH3). Our study is the first to apply systematic, quantitative proteomic screening of plasma samples from patients with different subtypes of HFpEF and identify candidate biomarkers for improved management of acute and chronic HFpEF and HCM.

Transcriptomic Signatures of Hypomethylating Agent Failure in Myelodysplastic Syndromes and Chronic Myelomonocytic Leukemia

Hypomethylating agents (HMAs) are the standard of care for myelodysplastic syndromes (MDS) and chronic myelomonocytic leukemia (CMML). HMA treatment failure is a major clinical problem and its mechanisms are poorly characterized. We performed RNA sequencing in CD34⁺ bone marrow stem hematopoietic stem and progenitor cells (BM-HSPCs) from 51 patients with CMML and MDS before HMA treatment and compared transcriptomic signatures between responders and nonresponders. We observed very few genes with significant differential expression in HMA non-responders versus responders, and the commonly altered genes in non-responders to both azacitidine (AZA) and decitabine (DAC) treatments were immunoglobulin genes. Gene set analysis identified 78 biological pathways commonly altered in non-responders to both treatments. Among these, we determined that the γ-aminobutyric acid (GABA) receptor signaling significantly affected hematopoiesis in both human BM-HSPCs and mice, indicating that the transcriptomic signatures identified here could serve as candidate biomarkers and therapeutic targets for HMA failure in MDS and CMML.

Potential Biomarkers and Signaling Pathways Associated with the Pathogenesis of Primary Ameloblastoma: A Systems Biology Approach

Objective

Ameloblastoma is a benign odontogenic tumor that may lead to ameloblastic carcinoma. This study aimed to determine potential signaling pathways and biological processes, critical genes and their regulating transcription factors (TFs), and miRNAs, as well as protein kinases involved in the etiology of primary ameloblastoma.

Methods

The dataset GSE132472 was obtained from the GEO database, and multivariate statistical analyses were applied to identify differentially expressed genes (DEGs) in primary ameloblastoma tissues compared to the corresponding normal gingiva samples. A protein-protein interaction (PPI) map was built using the STRING database. The Cytoscape software identified significant modules and the hub genes within the PPI network. Gene Ontology annotation and signaling pathway analyses were executed by employing the DAVID and Reactome databases, respectively. Significant TFs and miRNAs acting on the hub genes were identified using the iRegulon plugin and MiRWalk 2.0 database, respectively. A protein kinase enrichment analysis was conducted using the online Kinase Enrichment Analysis 2 (KEA2) web server. The approved drugs acting on the hub genes were also found.

Results

A total of 1,629 genes were differentially expressed in primary ameloblastoma (P value <0.01 and |Log2FC| > 1). HRAS, CDK1, MAPK3, ERBB2, COL1A1, CYCS, and BRCA1 demonstrated high degree and betweenness centralities in the PPI network. E2F4 was the most significant TF acting on the hub genes. BTK was the protein kinase significantly enriched by the TFs. Cholesterol biosynthesis was considerably involved in primary ameloblastoma.

Conclusions

This study provides an intuition into the potential mechanisms involved in the etiology of ameloblastoma.

KIF17 maintains the epithelial phenotype of breast cancer cells and curbs tumour metastasis

Kinesin superfamily motor protein 17 (KIF17) was previously identified downregulated in breast cancer and correlated with patient prognosis. However, its pathophysiological role in tumours remains unknown. Here, we confirmed that KIF17 was significantly under-expressed in breast cancer tissues and low KIF17 expression correlated with poor outcomes in patients with breast cancer. In vitro and in vivo experiments demonstrated that KIF17 overexpression in breast cancer cell lines significantly inhibited breast cancer invasion and metastasis. By establishing the lung metastatic MDA-MB-231 cell lines, we found a transient silence of KIF17 during the initiation of breast cancer metastasis. Further experiments revealed that KIF17 might suppress metastasis by regulating the level of acetylated tubulin to maintain cytoskeleton stability. Eventually, we found that the low expression of KIF17 in breast cancer is regulated by DNMT1-mediated 5-mC DNA methylation and epigenetic silencing. Decitabine can effectively improve the expression level of KIF17 in breast cancer cells. Our study demonstrates that KIF17 mediates microtubule acetylation to maintain the stability of microtubules, thereby inhibiting tumour invasion and metastasis.