Deep Probabilistic Principal Component Analysis for Process Monitoring.

Probabilistic latent variable models (PLVMs), such as probabilistic principal component analysis (PPCA), are widely employed in process monitoring and fault detection of industrial processes. This article proposes a novel deep PPCA (DePPCA) model, which has the advantages of both probabilistic modeling and deep learning. The construction of DePPCA includes a greedy layer-wise pretraining phase and a unified end-to-end fine-tuning phase. The former establishes a hierarchical deep structure based on cascading multiple layers of the PPCA module to extract high-level features. The latter builds an end-to-end connection between the raw inputs and the final outputs to further improve the representation of the model to high-level features. After constructing the model structure of DePPCA, we first present the detailed training processes of the pretraining and fine-tuning stages, then clarify the theoretical merits of the proposed model from the perspective of variational inference. For process monitoring purposes, we develop two statistics based on the established DePPCA. The monitoring performance of these two statistics can remain superior even if the features extracted by DePPCA are significantly compressed to univariate. This makes the feature extraction process and online monitoring procedure of DePPCA quite fast. In other words, the proposed DePPCA can achieve accurate and efficient process monitoring by only extracting one feature for each sample. Finally, the effectiveness of DePPCA is evaluated on the Tennessee Eastman (TE) process and the multiphase flow (MPF) facility.

Global analysis of T-cell groups reveals immunological features and common antigen targets of digestive tract tumors.

BACKGROUND: T cells are key players in the tumor immune microenvironment (TIME), as they can recognize and eliminate cancer cells that express neoantigens derived from somatic mutations. However, the diversity and specificity of T-cell receptors (TCRs) that recognize neoantigens are largely unknown, due to the high variability of TCR sequences among individuals. METHODS: To address this challenge, we applied GLIPH2, a novel algorithm that groups TCRs based on their predicted antigen specificity and HLA restriction, to cluster the TCR repertoire of 1,702 patients with digestive tract cancer. The patients were divided into five groups based on whether they carried tumor-infiltrating or clonal-expanded TCRs and calculated their TCR diversity. The prognosis, tumor subtype, gene mutation, gene expression, and immune microenvironment of these groups were compared. Viral specificity inference and immunotherapy relevance analysis performed for the TCR groups. RESULTS: This approach reduced the complexity of TCR sequences to 249 clonally expanded and 150 tumor-infiltrating TCR groups, which revealed distinct patterns of TRBV usage, HLA association, and TCR diversity. In gastric adenocarcinoma (STAD), patients with tumor-infiltrating TCRs (Patients-TI) had significantly worse prognosis than other patients (Patients-nonTI). Patients-TI had richer CD8+ T cells in the immune microenvironment, and their gene expression features were positively correlated with immunotherapy response. We also found that tumor-infiltrating TCR groups were associated with four distinct tumor subtypes, 26 common gene mutations, and 39 gene expression signatures. We discovered that tumor-infiltrating TCRs had cross-reactivity with viral antigens, indicating a possible link between viral infections and tumor immunity. CONCLUSION: By applying GLIPH2 to TCR sequences from digestive tract tumors, we uncovered novel insights into the tumor immune landscape and identified potential candidates for shared TCRs and neoantigens.

Oleic acid availability impacts thymocyte preprogramming and subsequent peripheral Treg cell differentiation.

The nature of activation signals is essential in determining T cell subset differentiation; however, the features that determine T cell subset preference acquired during intrathymic development remain elusive. Here we show that naive CD4+ T cells generated in the mouse thymic microenvironment lacking Scd1, encoding the enzyme catalyzing oleic acid (OA) production, exhibit enhanced regulatory T (Treg) cell differentiation and attenuated development of experimental autoimmune encephalomyelitis. Scd1 deletion in K14+ thymic epithelia recapitulated the enhanced Treg cell differentiation phenotype of Scd1-deficient mice. The dearth of OA permitted DOT1L to increase H3K79me2 levels at the Atp2a2 locus of thymocytes at the DN2-DN3 transition stage. Such epigenetic modification persisted in naive CD4+ T cells and facilitated Atp2a2 expression. Upon T cell receptor activation, ATP2A2 enhanced the activity of the calcium-NFAT1-Foxp3 axis to promote naive CD4+ T cells to differentiate into Treg cells. Therefore, OA availability is critical for preprogramming thymocytes with Treg cell differentiation propensities in the periphery.

Protocol for PPP1R15A-inhibited mouse model establishment with subcutaneous B16F1 tumor and single-cell analysis.

Here, we present a protocol for exploring the effects of PPP1R15A inhibitor, Sephin1, on antitumor immunity of B16F1 subcutaneous tumor in mice. We describe steps for constructing single-cell transcriptome and TCR libraries, sequencing, and using sequencing data for the integration of expression and TCR data. We then detail procedures for gene differentiation, regulon and cell-cell communication analysis, and validation of single-cell analysis results. For complete details on the use and execution of this protocol, please refer to Wang et al.1.

GRAPE: A multi-modal dataset of longitudinal follow-up visual field and fundus images for glaucoma management.

As one of the leading causes of irreversible blindness worldwide, glaucoma is characterized by structural damage and functional loss. Glaucoma patients often have a long follow-up and prognosis prediction is an important part in treatment. However, existing public glaucoma datasets are almost cross-sectional, concentrating on segmentation on optic disc (OD) and glaucoma diagnosis. With the development of artificial intelligence (AI), the deep learning model can already provide accurate prediction of future visual field (VF) and its progression with the support of longitudinal datasets. Here, we proposed a public longitudinal glaucoma real-world appraisal progression ensemble (GRAPE) dataset. The GRAPE dataset contains 1115 follow-up records from 263 eyes, with VFs, fundus images, OCT measurements and clinical information, and OD segmentation and VF progression are annotated. Two baseline models demonstrated the feasibility in prediction of VF and its progression. This dataset will advance AI research in glaucoma management.

Escaping but not the inactive X-linked protein complex coding genes may achieve X-chromosome dosage compensation and underlie X chromosome inactivation-related diseases.

X chromosome dosage compensation (XDC) refers to the process by which X-linked genes acquire expression equivalence between two sexes. Ohno proposed that XDC is achieved by two-fold upregulations of X-linked genes in both sexes and by silencing one X chromosome (X chromosome inactivation, XCI) in females. However, genes subject to two-fold upregulations as well as the underlying mechanism remain unclear. It's reported that gene dosage changes may only affect X-linked dosage-sensitive genes, such as protein complex coding genes (PCGs). Our results showed that in human PCGs are more likely to escape XCI and escaping PCGs (EsP) show two-fold higher expression than inactivated PCGs (InP) or other X-linked genes at RNA and protein levels in both sexes, which suggest that EsP may achieve upregulations and XDC. The higher expressions of EsP possibly result from the upregulations of the single active X chromosome (Xa), rather than escaping expressions from the inactive X chromosome (Xi). EsP genes have relatively high expression levels in humans and lower dN/dS ratios, suggesting that they are likely under stronger selection pressure over evolutionary time. Our study also suggests that SP1 transcription factor is significantly enriched in EsP and may be involved in the up-regulations of EsP on the active X. Finally, human EsP genes in this study are enriched in the toll-like receptor pathway, NF-kB pathway, apoptotic pathway, and abnormal mental, developmental and reproductive phenotypes. These findings suggest misregulations of EsP may be involved in autoimmune, reproductive, and neurological diseases, providing insight for the diagnosis and treatment of these diseases.

Intact regulation of G1/S transition renders esophageal squamous cell carcinoma sensitive to PI3Kα inhibitors.

Phosphatidylinositol 3-kinase alpha (PI3Kα) inhibitors are currently evaluated for the therapy of esophageal squamous cell carcinoma (ESCC). It is of great importance to identify potential biomarkers to predict or monitor the efficacy of PI3Kα inhibitors in an aim to improve the clinical responsive rate in ESCC. Here, ESCC PDXs with CCND1 amplification were found to be more sensitive to CYH33, a novel PI3Kα-selective inhibitor currently in clinical trials for the treatment of advanced solid tumors including ESCC. Elevated level of cyclin D1, p21 and Rb was found in CYH33-sensitive ESCC cells compared to those in resistant cells. CYH33 significantly arrested sensitive cells but not resistant cells at G1 phase, which was associated with accumulation of p21 and suppression of Rb phosphorylation by CDK4/6 and CDK2. Hypo-phosphorylation of Rb attenuated the transcriptional activation of SKP2 by E2F1, which in turn hindered SKP2-mediated degradation of p21 and reinforced accumulation of p21. Moreover, CDK4/6 inhibitors sensitized resistant ESCC cells and PDXs to CYH33. These findings provided mechanistic rationale to evaluate PI3Kα inhibitors in ESCC patients harboring amplified CCND1 and the combined regimen with CDK4/6 inhibitors in ESCC with proficient Rb.

Targeting KRAS-mutant stomach/colorectal tumors by disrupting the ERK2-p53 complex.

KRAS is widely mutated in human cancers, resulting in unchecked tumor proliferation and metastasis, which makes identifying KRAS-targeting therapies a priority. Herein, we observe that mutant KRAS specifically promotes the formation of the ERK2-p53 complex in stomach/colorectal tumor cells. Disruption of this complex by applying MEK1/2 and ERK2 inhibitors elicits strong apoptotic responses in a p53-dependent manner, validated by genome-wide knockout screening. Mechanistically, p53 physically associates with phosphorylated ERK2 through a hydrophobic interaction in the presence of mutant KRAS, which suppresses p53 activation by preventing the recruitment of p300/CBP; trametinib disrupts the ERK2-p53 complex by reducing ERK2 phosphorylation, allowing the acetylation of p53 protein by recruiting p300/CBP; acetylated p53 activates PUMA transcription and thereby kills KRAS-mutant tumors. Our study shows an important role for the ERK2-p53 complex and provides a potential therapeutic strategy for treating KRAS-mutant cancer.

Single-cell RNA sequencing reveals the suppressive effect of PPP1R15A inhibitor Sephin1 in antitumor immunity.

Protein phosphatase 1 regulatory subunit 15A (PPP1R15A) is an important factor in the integrated stress response (ISR) in mammals and may play a crucial role in tumorigenesis. In our studies, we found an inhibitor of PPP1R15A, Sephin1, plays a protumorigenic role in mouse tumor models. By analyzing the single-cell transcriptome data of the mouse tumor models, we found that in C57BL/6 mice, Sephin1 treatment could lead to higher levels of ISR activity and lower levels of antitumor immune activities. Specifically, Sephin1 treatment caused reductions in antitumor immune cell types and lower expression levels of cytotoxicity-related genes. In addition, T cell receptor (TCR) repertoire analysis demonstrated that the clonal expansion of tumor-specific T cells was inhibited by Sephin1. A special TCR + macrophage subtype in tumor was identified to be significantly depleted upon Sephin1 treatment, implying its key antitumor role. These results suggest that PPP1R15A has the potential to be an effective target for tumor therapy.

Remodeling of H3K9me3 during the pluripotent to totipotent-like state transition.

Multiple chromatin modifiers associated with H3K9me3 play important roles in the transition from embryonic stem cells to 2-cell (2C)-like cells. However, it remains elusive how H3K9me3 is remodeled and its association with totipotency. Here, we integrated transcriptome and H3K9me3 profiles to conduct a detailed comparison of 2C embryos and 2C-like cells. Globally, H3K9me3 is highly preserved and H3K9me3 dynamics within the gene locus is not associated with gene expression change during 2C-like transition. Promoter-deposited H3K9me3 plays non-repressive roles in the activation of genes during 2C-like transition. In contrast, transposable elements, residing in the nearby regions of up-regulated genes, undergo extensive elimination of H3K9me3 and are tended to be induced in 2C-like transitions. Furthermore, a large fraction of trophoblast stem cell-specific enhancers undergo loss of H3K9me3 exclusively in MERVL+/Zscan4+ cells. Our study therefore reveals the unique H3K9me3 profiles of 2C-like cells, facilitating the further exploration of totipotency.

Deep PLS: A Lightweight Deep Learning Model for Interpretable and Efficient Data Analytics.

The salient progress of deep learning is accompanied by nonnegligible deficiencies, such as: 1) interpretability problem; 2) requirement for large data amounts; 3) hard to design and tune parameters; and 4) heavy computation complexity. Despite the remarkable achievements of neural networks-based deep models in many fields, the practical applications of deep learning are still limited by these shortcomings. This article proposes a new concept called the lightweight deep model (LDM). LDM absorbs the useful ideas of deep learning and overcomes their shortcomings to a certain extent. We explore the idea of LDM from the perspective of partial least squares (PLS) by constructing a deep PLS (DPLS) model. The feasibility and merits of DPLS are proved theoretically, after that, DPLS is further generalized to a more common form (GDPLS) by adding a nonlinear mapping layer between two cascaded PLS layers in the model structure. The superiority of DPLS and GDPLS is demonstrated through four practical cases involving two regression problems and two classification tasks, in which our model not only achieves competitive performance compared with existing neural networks-based deep models but also is proven to be a more interpretable and efficient method, and we know exactly how it improves performance, how it gives correct results. Note that our proposed model can only be regarded as an alternative to fully connected neural networks at present and cannot completely replace the mature deep vision or language models.

A novel long noncoding RNA SP100-AS1 induces radioresistance of colorectal cancer via sponging miR-622 and stabilizing ATG3.

Although radiotherapy is an essential modality in the treatment of colorectal cancer (CRC), the incidence of radioresistance remains high clinically. Long noncoding RNAs (lncRNAs) reportedly play critical roles in CRC radioresistance by regulating genes or proteins at the transcriptional or post-translational levels. This study aimed to identify novel lncRNAs involved in radioresistance. We found that SP100-AS1 (lncRNA targeting antisense sequence of SP100 gene) was upregulated in radioresistant CRC patient tissues using RNA-seq analysis. Importantly, knockdown of SP100-AS1 significantly reduced radioresistance, cell proliferation, and tumor formation in vitro and in vivo. Mechanistically, mass spectrometry and bioinformatics analyses were used to identify the interacting proteins and microRNAs of SP100-AS1, respectively. Moreover, SP100-AS1 was found to interact with and stabilize ATG3 protein through the ubiquitination-dependent proteasome pathway. In addition, it could serve as a sponge for miR-622, which targeted ATG3 mRNA and affected autophagic activity. Thus, lncRNA SP100-AS1 could act as a radioresistance factor in CRC patients via RNA sponging and protein stabilizing mechanisms. In conclusion, the present study indicates that SP100-AS1/miR-622/ATG3 axis contributes to radioresistance and autophagic activity in CRC patients, suggesting it has huge prospects as a therapeutic target for improving CRC response to radiation therapy.

SCD1 Sustains Homeostasis of Bulge Niche via Maintaining Hemidesmosomes in Basal Keratinocytes.

Niche for stem cells profoundly influences their maintenance and fate during tissue homeostasis and pathological disorders; however, the underlying mechanisms and tissue-specific features remain poorly understood. Here, it is reported that fatty acid desaturation catabolized by stearoyl-coenzyme A desaturase 1 (SCD1) regulates hair follicle stem cells (HFSCs) and hair growth by maintaining the bulge, niche for HFSCs. Scd1 deletion in mice results in abnormal hair growth, an effect exerted directly on keratin K14+ keratinocytes rather than on HFSCs. Mechanistically, Scd1 deficiency impairs the level of integrin α6ß4 complex and thus the assembly of hemidesmosomes (HDs). The disruption of HDs allows the aberrant activation of focal adhesion kinase and PI3K in K14+ keratinocytes and subsequently their differentiation and proliferation. The overgrowth of basal keratinocytes results in downward extension of the outer root sheath and interruption of bulge formation. Then, inhibition of PI3K signaling in Scd1-/- mice normalizes the bulge, HFSCs, and hair growth. Additionally, supplementation of oleic acid to Scd1-/- mice reestablishes HDs and the homeostasis of bulge niche, and restores hair growth. Thus, SCD1 is critical in regulating hair growth through stabilizing HDs in basal keratinocytes and thus sustaining bulge for HFSC residence and periodic activity.

Genome-wide gain-of-function screening identifies EZH2 mediating resistance to PI3Kα inhibitors in oesophageal squamous cell carcinoma.

Phosphoinositide-3 kinase alpha (PI3Kα) has been confirmed to be a potential therapeutic target for esophageal squamous cell carcinoma (ESCC), while the potency of PI3Kα inhibitors is often attenuated by concurrent oncogenic signalling pathways. We performed genome-wide gain-of-function screening with a CRISPR-SAM library and identified enhancer of zeste homolog 2 (EZH2) rendering ESCC cells resistant to the PI3Kα inhibitor CYH33. Enhanced expression of EZH2 frequently occurs in ESCC and is related to poor prognosis. Overexpression of full-length EZH2 but not methyltransferase-deficient EZH2 conferred resistance to CYH33, while downregulating EZH2 expression restored sensitivity. EZH2 expression was negatively related to the activity of CYH33 against the proliferation of ESCC cell lines and patient-derived cells. Transcriptomic analysis revealed that EZH2 abrogated CYH33-mediated cell cycle regulation. EZH2 epigenetically suppressed the transcription of CDKN1A, promoting RB phosphorylation and cell cycle progression. Concurrently targeting EZH2 significantly potentiated CYH33 to inhibit the growth of ESCC cells and patient-derived xenografts accompanied by enhanced cell cycle arrest. Taken together, our study demonstrated that an EZH2-p21-RB axis remodeled cell cycle regulation and rendered resistance to PI3Kα inhibitors in ESCC. Simultaneously targeting PI3Kα and EZH2 may provide an effective strategy for ESCC therapy with high expression of EZH2.

Longitudinal immune profiling reveals dominant epitopes mediating long-term humoral immunity in COVID-19-convalescent individuals.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly pathogenic and contagious coronavirus that caused a global pandemic with 5.2 million fatalities to date. Questions concerning serologic features of long-term immunity, especially dominant epitopes mediating durable antibody responses after SARS-CoV-2 infection, remain to be elucidated. OBJECTIVE: We aimed to dissect the kinetics and longevity of immune responses in coronavirus disease 2019 (COVID-19) patients, as well as the epitopes responsible for sustained long-term humoral immunity against SARS-CoV-2. METHODS: We assessed SARS-CoV-2 immune dynamics up to 180 to 220 days after disease onset in 31 individuals who predominantly experienced moderate symptoms of COVID-19, then performed a proteome-wide profiling of dominant epitopes responsible for persistent humoral immune responses. RESULTS: Longitudinal analysis revealed sustained SARS-CoV-2 spike protein-specific antibodies and neutralizing antibodies in COVID-19 patients, along with activation of cytokine production at early stages after SARS-CoV-2 infection. Highly reactive epitopes that were capable of mediating long-term antibody responses were shown to be located at the spike and ORF1ab proteins. Key epitopes of the SARS-CoV-2 spike protein were mapped to the N-terminal domain of the S1 subunit and the S2 subunit, with varying degrees of sequence homology among endemic human coronaviruses and high sequence identity between the early SARS-CoV-2 (Wuhan-Hu-1) and current circulating variants. CONCLUSION: SARS-CoV-2 infection induces persistent humoral immunity in COVID-19-convalescent individuals by targeting dominant epitopes located at the spike and ORF1ab proteins that mediate long-term immune responses. Our findings provide a path to aid rational vaccine design and diagnostic development.

Occludin is a target of Src kinase and promotes lipid secretion by binding to BTN1a1 and XOR.

Lipid droplets (LDs) have increasingly been recognized as an essential organelle for eukaryotes. Although the biochemistry of lipid synthesis and degradation is well characterized, the regulation of LD dynamics, including its formation, maintenance, and secretion, is poorly understood. Here, we report that mice lacking Occludin (Ocln) show defective lipid metabolism. We show that LDs were larger than normal along its biogenesis and secretion pathway in Ocln null mammary cells. This defect in LD size control did not result from abnormal lipid synthesis or degradation; rather, it was because of secretion failure during the lactation stage. We found that OCLN was located on the LD membrane and was bound to essential regulators of lipid secretion, including BTN1a1 and XOR, in a C-terminus-dependent manner. Finally, OCLN was a phosphorylation target of Src kinase, whose loss causes lactation failure. Together, we demonstrate that Ocln is a downstream target of Src kinase and promotes LD secretion by binding to BTN1a1 and XOR.

CST6 protein and peptides inhibit breast cancer bone metastasis by suppressing CTSB activity and osteoclastogenesis.

Background: Bone metastasis is a frequent symptom of breast cancer and current targeted therapy has limited efficacy. Osteoclasts play critical roles to drive osteolysis and metastatic outgrowth of tumor cells in bone. Previously we identified CST6 as a secretory protein significantly downregulated in bone-metastatic breast cancer cells. Functional analysis showed that CST6 suppresses breast-to-bone metastasis in animal models. However, the functional mechanism and therapeutic potential of CST6 in bone metastasis is unknown. Methods: Using in vitro osteoclastogenesis and in vivo metastasis assays, we studied the effect and mechanism of extracellular CST6 protein in suppressing osteoclastic niches and bone metastasis of breast cancer. A number of peptides containing the functional domain of CST6 were screened to inhibit bone metastasis. The efficacy, stability and toxicity of CST6 recombinant protein and peptides were evaluated in preclinical metastasis models. Results: We show here that CST6 inhibits osteolytic bone metastasis by inhibiting osteoclastogenesis. Cancer cell-derived CST6 enters osteoclasts by endocytosis and suppresses the cysteine protease CTSB, leading to up-regulation of the CTSB hydrolytic substrate SPHK1. SPHK1 suppresses osteoclast maturation by inhibiting the RANKL-induced p38 activation. Importantly, recombinant CST6 protein effectively suppresses bone metastasis in vitro and in vivo. We further identified several peptides mimicking the function of CST6 to suppress cancer cell-induced osteoclastogenesis and bone metastasis. Pre-clinical analyses of CTS6 recombinant protein and peptides demonstrated their potentials in treatment of breast cancer bone metastasis. Conclusion: These findings reveal the CST6-CTSB-SPHK1 signaling axis in osteoclast differentiation and provide a promising approach to treat bone diseases with CST6-based peptides.

Tumor microbiome contributes to an aggressive phenotype in the basal-like subtype of pancreatic cancer.

Despite the uniform mortality in pancreatic adenocarcinoma (PDAC), clinical disease heterogeneity exists with limited genomic differences. A highly aggressive tumor subtype termed 'basal-like' was identified to show worse outcomes and higher inflammatory responses. Here, we focus on the microbial effect in PDAC progression and present a comprehensive analysis of the tumor microbiome in different PDAC subtypes with resectable tumors using metagenomic sequencing. We found distinctive microbial communities in basal-like tumors and identified an increasing abundance of Acinetobacter, Pseudomonas and Sphingopyxis to be highly associated with carcinogenesis. Functional characterization of microbial genes suggested the potential to induce pathogen-related inflammation. Host-microbiota interplay analysis provided new insights into the tumorigenic role of specific microbiome compositions and demonstrated the influence of host genetics in shaping the tumor microbiome. Taken together, these findings indicated that the tumor microbiome is closely related to PDAC oncogenesis and the induction of inflammation. Additionally, our data revealed the microbial basis of PDAC heterogeneity and proved the predictive value of the microbiome, which will contribute to the intervention and treatment of disease.

PI3Kα inhibitor CYH33 triggers antitumor immunity in murine breast cancer by activating CD8+T cells and promoting fatty acid metabolism.

BACKGROUND: The phosphatidylinositol 3-kinase (PI3K) is frequently hyperactivated in cancer and plays important roles in both malignant and immune cells. The effect of PI3Kα inhibitors on the tumor microenvironment (TME) remains largely unknown. Here, we investigated the modulation of the TME by a clinical PI3Kα-specific inhibitor CYH33. METHODS: The activity of CYH33 against a panel of murine tumors in the immune-competent context or athymic mice was detected. Single-cell RNA sequencing and multi-parameter flow cytometry were performed to determine the immune profiling of TME. The effect of CYH33 on immune cells was conducted with primary murine cells. RESULTS: CYH33 exhibited more potent antitumor activity in immune-competent context. CYH33 enhanced the infiltration and activation of CD8+T and CD4+T cells, while attenuating M2-like macrophages and regulatory CD4+T cells. Increase in memory T cells was confirmed by the induction of long-term immune memory on CYH33 treatment. Mechanistically, CYH33 relieved the suppressed expansion of CD8+T cells via preferential polarization of the macrophages to the M1 phenotype. CYH33 promoted fatty acid (FA) metabolism in the TME, while FA enhanced the activity of CD8+T cells in vitro. The combination of CYH33 with the FA synthase (FASN) inhibitor C75 synergistically inhibited tumor growth with enhanced host immunity. CONCLUSIONS: CYH33 induces immune activation and synergizes with FASN inhibitor to further promote the antitumor immunity, which gains novel insights into how PI3K inhibitors exert their activity by modulating TME and provides a rationale for the concurrent targeting of PI3K and FASN in breast cancer treatment.

Characterization of the Blood and Cerebrospinal Fluid Microbiome in Children with Bacterial Meningitis and Its Potential Correlation with Inflammation.

Bacterial meningitis shows a higher incidence in children than adults, but signs may be scarce. Although some pathogenic microorganisms of meningitis from cerebrospinal fluid (CSF) have been reported, the signature of the representative microbiota in CSF and blood samples from patients remains incompletely revealed. To extend the understanding of the microbiome in patients, we recruited 32 children with bacterial meningitis, 30 undiagnosed infectious children, and 10 matched healthy individuals, which was followed by untargeted metagenomic next-generation sequencing (mNGS) and bioinformatic analysis. Our results showed that children with bacterial meningitis exhibited different microbiome signatures in their CSF and blood compared with undiagnosed and healthy children, and patients could be divided into varied subsets according to these signatures, including Escherichia coli, Klebsiella pneumoniae, Thermothelomyces thermophila, Lactobacillus acidophilus, and Staphylococcus haemolyticus. To further explore their potential role in patients' conditions, we examined their correlation with clinical parameters. Importantly, microbiome signatures with compositional changes were correlated with the C-reactive protein (CRP) level in blood and granulocyte percentage in CSF. Moreover, the blood in subsets of patients with a predominance of Klebsiella pneumoniae could replace CSF as the main specimen for clinical monitoring. IMPORTANCE This study revealed the microbial compositions in children with bacterial meningitis who were treated with antibiotics and made a comprehensive comparison between blood and CSF specimens for the risk and prognosis assessment. We found that microbiome signatures could distinguish patient subsets in the children and were correlated with the CRP level in blood and granulocyte percentage in CSF. The compositional changes in representative microbiota constituents could provide guidance for clinical monitoring and antibiotic intervention.