iLipidome: enhancing statistical power and interpretability using hidden biosynthetic interdependencies in the lipidome.

Numerous biological processes and diseases are influenced by lipid composition. Advances in lipidomics are elucidating their roles, but analyzing and interpreting lipidomics data at the systems level remain challenging. To address this, we present iLipidome, a method for analyzing lipidomics data in the context of the lipid biosynthetic network, thus accounting for the interdependence of measured lipids. iLipidome enhances statistical power, enables reliable clustering and lipid enrichment analysis, and links lipidomic changes to their genetic origins. We applied iLipidome to investigate mechanisms driving changes in cellular lipidomes following supplementation of docosahexaenoic acid (DHA) and successfully identified the genetic causes of alterations. We further demonstrated how iLipidome can disclose enzyme-substrate specificity and pinpoint prospective glioblastoma therapeutic targets. Finally, iLipidome enabled us to explore underlying mechanisms of cardiovascular disease and could guide the discovery of early lipid biomarkers. Thus, iLipidome can assist researchers studying the essence of lipidomic data and advance the field of lipid biology.

LipidSig 2.0: integrating lipid characteristic insights into advanced lipidomics data analysis.

In the field of lipidomics, where the complexity of lipid structures and functions presents significant analytical challenges, LipidSig stands out as the first web-based platform providing integrated, comprehensive analysis for efficient data mining of lipidomic datasets. The upgraded LipidSig 2.0 (https://lipidsig.bioinfomics.org/) simplifies the process and empowers researchers to decipher the complex nature of lipids and link lipidomic data to specific characteristics and biological contexts. This tool markedly enhances the efficiency and depth of lipidomic research by autonomously identifying lipid species and assigning 29 comprehensive characteristics upon data entry. LipidSig 2.0 accommodates 24 data processing methods, streamlining diverse lipidomic datasets. The tool's expertise in automating intricate analytical processes, including data preprocessing, lipid ID annotation, differential expression, enrichment analysis, and network analysis, allows researchers to profoundly investigate lipid properties and their biological implications. Additional innovative features, such as the 'Network' function, offer a system biology perspective on lipid interactions, and the 'Multiple Group' analysis aids in examining complex experimental designs. With its comprehensive suite of features for analyzing and visualizing lipid properties, LipidSig 2.0 positions itself as an indispensable tool for advanced lipidomics research, paving the way for new insights into the role of lipids in cellular processes and disease development.

DriverDBv4: a multi-omics integration database for cancer driver gene research.

Advancements in high-throughput technology offer researchers an extensive range of multi-omics data that provide deep insights into the complex landscape of cancer biology. However, traditional statistical models and databases are inadequate to interpret these high-dimensional data within a multi-omics framework. To address this limitation, we introduce DriverDBv4, an updated iteration of the DriverDB cancer driver gene database (http://driverdb.bioinfomics.org/). This updated version offers several significant enhancements: (i) an increase in the number of cohorts from 33 to 70, encompassing approximately 24 000 samples; (ii) inclusion of proteomics data, augmenting the existing types of omics data and thus expanding the analytical scope; (iii) implementation of multiple multi-omics algorithms for identification of cancer drivers; (iv) new visualization features designed to succinctly summarize high-context data and redesigned existing sections to accommodate the increased volume of datasets and (v) two new functions in Customized Analysis, specifically designed for multi-omics driver identification and subgroup expression analysis. DriverDBv4 facilitates comprehensive interpretation of multi-omics data across diverse cancer types, thereby enriching the understanding of cancer heterogeneity and aiding in the development of personalized clinical approaches. The database is designed to foster a more nuanced understanding of the multi-faceted nature of cancer.

Transcriptomics Meta-Analysis Reveals Phagosome and Innate Immune System Dysfunction as Potential Mechanisms in the Cortex of Alzheimer's Disease Mouse Strains.

Immune-related pathways can affect the immune system directly, such as the chemokine signaling pathway, or indirectly, such as the phagosome pathway. Alzheimer's disease (AD) is reportedly associated with several immune-related pathways. However, exploring its underlying mechanism is challenging in animal studies because AD mouse strains differentially express immune-related pathway characteristics. To overcome this problem, we performed a meta-analysis to identify significant and consistent immune-related AD pathways that are expressed in different AD mouse strains. Next-generation RNA sequencing (RNA-seq) and microarray datasets for the cortex of AD mice from different strains such as APP/PSEN1, APP/PS2, 3xTg, TREM, and 5xFAD were collected from the NCBI GEO database. Each dataset's quality control and normalization were already processed from each original study source using various methods depending on the high-throughput analysis platform (FastQC, median of ratios, RMA, between array normalization). Datasets were analyzed using DESeq2 for RNA-seq and GEO2R for microarray to identify differentially expressed (DE) genes. Significantly DE genes were meta-analyzed using Stouffer's method, with significant genes further analyzed for functional enrichment. Ten datasets representing 20 conditions were obtained from the NCBI GEO database, comprising 116 control and 120 AD samples. The DE analysis identified 284 significant DE genes. The meta-analysis identified three significantly enriched immune-related AD pathways: phagosome, the complement and coagulation cascade, and chemokine signaling. Phagosomes-related genes correlated with complement and immune system. Meanwhile, phagosomes and chemokine signaling genes overlapped with B cells receptors pathway genes indicating potential correlation between phagosome, chemokines, and adaptive immune system as well. The transcriptomic meta-analysis showed that AD is associated with immune-related pathways in the brain's cortex through the phagosome, complement and coagulation cascade, and chemokine signaling pathways. Interestingly, phagosome and chemokine signaling pathways had potential correlation with B cells receptors pathway.

Upregulation of APAF1 and CSF1R in Peripheral Blood Mononuclear Cells of Parkinson's Disease.

Increased oxidative stress and neuroinflammation play a crucial role in the pathogenesis of Parkinson's disease (PD). In this study, the expression levels of 52 genes related to oxidative stress and inflammation were measured in peripheral blood mononuclear cells of the discovery cohort including 48 PD patients and 25 healthy controls. Four genes, including ALDH1A, APAF1, CR1, and CSF1R, were found to be upregulated in PD patients. The expression patterns of these genes were validated in a second cohort of 101 PD patients and 61 healthy controls. The results confirmed the upregulation of APAF1 (PD: 0.34 ± 0.18, control: 0.26 ± 0.11, p < 0.001) and CSF1R (PD: 0.38 ± 0.12, control: 0.33 ± 0.10, p = 0.005) in PD patients. The expression level of APAF1 was correlated with the scores of the Unified Parkinson's Disease Rating Scale (UPDRS, r = 0.235, p = 0.018) and 39-item PD questionnaire (PDQ-39, r = 0.250, p = 0.012). The expression level of CSF1R was negatively correlated with the scores of the mini-mental status examination (MMSE, r = -0.200, p = 0.047) and Montréal Cognitive Assessment (MoCA, r = -0.226, p = 0.023). These results highly suggest that oxidative stress biomarkers in peripheral blood may be useful in monitoring the progression of motor disabilities and cognitive decline in PD patients.

Transcriptomic Analyses of Exercise Training in Alzheimer's Disease Cerebral Cortex.

BACKGROUND: Research reported exercise could reduce Alzheimer's disease (AD) symptoms in human and animals. However, the molecular mechanism of exercise training via transcriptomic analysis was unclear especially in AD in the cortex area. OBJECTIVE: Investigate potential significant pathways in the cortex area that were affected by exercise during AD. METHODS: RNA-seq analysis, differential expressed genes, functional enrichment analysis, and GSOAP clustering analysis were performed in the isolated cerebral cortex from eight 3xTg AD mice (12 weeks old) randomly and equally divided into control (AD) and exercise training (AD-EX) group. Swimming exercise training in AD-EX group was conducted 30 min/day for 1 month. RESULTS: There were 412 genes significant differentially expressed in AD-EX group compared to AD group. Top 10 upregulated genes in AD-EX group against AD group mostly correlated with neuroinflammation, while top 10 downregulated genes mostly had connection with vascularization, membrane transport, learning memory, and chemokine signal. Pathway analysis revealed the upregulated interferon alpha beta signaling in AD-EX had association with cytokines delivery in microglia cells compared to AD and top 10 upregulated genes involved in interferon alpha beta were Usp18, Isg15, Mx1, Mx2, Stat1, Oas1a, and Irf9; The downregulated extracellular matrix organization in AD-EX had correlation with Aß and neuron cells interaction and Vtn was one of the top 10 downregulated genes involved in this pathway. CONCLUSION: Exercise training influenced 3xTg mice cortex through interferon alpha beta signaling upregulation and extracellular matrix organization downregulation based on transcriptomics analysis.

Matrix Metallopeptidase-Gene Signature Predicts Stage I Lung Adenocarcinoma Survival Outcomes.

Tumor recurrence poses a significant challenge to the clinical management of stage I lung adenocarcinoma after curative surgical resection. Matrix metalloproteinases (MMPs) increase expression and correlate with recurrence and metastasis in surgically resected non-small cell lung cancer. However, the impact of MMPs on survival outcome varies, and their roles in patients with stage I lung adenocarcinoma remain unclear. In two discovery cohorts, we first analyzed 226 stage I-II lung adenocarcinoma cases in the GSE31210 cohort using a clustering-based method and identified a 150-gene MMP cluster with increased expression in tumors associated with worse survival outcomes. A similar analysis was performed on 517 lung adenocarcinoma cases in the Cancer Genome Atlas cohort. A 185-gene MMP cluster was identified, which also showed increased expression in tumors and correlated with poor survival outcomes. We further streamlined from the discovery cohorts a 36-gene MMP signature significantly associated with recurrence and worse overall survival in patients with stage I lung adenocarcinoma after surgical resection. After adjusting for covariates, the high MMP-gene signature expression remained an independent risk factor. In addition, the MMP-gene signature showed enrichment in epidermal growth factor receptor wild-type lung tumors, especially for those with Kirsten rat sarcoma virus mutations. Using an independent validation cohort, we further validated the MMP-gene signature in 70 stage I lung adenocarcinoma cases. In conclusion, MMP-gene signature is a potential predictive and prognostic biomarker to stratify patients with stage I lung adenocarcinoma into subgroups based on their risk of recurrence for aiding physicians in deciding the personalized adjuvant therapeutics.

Non-Insulin-Based Insulin Resistance Indices and Localized Periodontitis in Physically Active Young Male Adults: CHIEF Oral Health Study.

AIMS: This study aims to examine the association between non-insulin-based insulin resistance indices and periodontitis severity in young males. BACKGROUND: Periodontitis has been reported with an association with insulin resistance in middle- and old-aged adults. OBJECTIVE: The association between insulin resistance and localized periodontitis in young adults is unclear. METHODS: A total of non-diabetic 1,111 military males in Taiwan were included in this study. Localized periodontitis was classified as healthy (N =665), stage I (N =130), stage II (N =161), and stage III (N =155) based on the world workshop in 2017. Insulin resistance was assessed by serum triglycerides concentrations, the triglycerides glucose (TyG) index, the product of serum triglycerides and fasting glucose, and the ratio of serum triglycerides to high-density lipoprotein cholesterol (TG/HDL-C). Multiple logistic regression analysis with adjustment for age, tobacco smoking, alcohol intake, abdominal obesity, and hypertension was used to determine the associations. RESULTS: Serum TG concentrations, TyG index, and TG/HDL-C ratio were dose-dependently associated with a greater risk of localized periodontitis severity (from stage I to stage III) [odds ratios and 95% confidence intervals: 1.001 (0.999-1.004), 1.003 (1.001-1.004) and 1.003 (1.002- 1.005) for TG; 1.45 (1.03-2.03), 1.65 (1.22-2.22) and 1.66 (1.22-2.26) for TyG index; 1.06 (0.99- 1.14), 1.09 (1.03-1.15) and 1.10 (1.04-1.16) for TG/HDL-C ratio]. However, the association was only found in obese individuals and those free of impaired fasting glucose. CONCLUSION: The present study confirmed that periodontitis may lead to insulin resistance in young male adults, particularly for those with obesity and without hyperglycemia. The TyG index is suggestive as the strongest indicator for the association between insulin resistance and periodontitis in young adults.

LncRNA HOTAIR impairs the prognosis of papillary thyroid cancer via regulating cellular malignancy and epigenetically suppressing DLX1.

PURPOSE: Papillary thyroid cancer (PTC) is the most common endocrine malignancy with a fast-growing incidence in recent decades. HOTAIR as a long non-coding RNA has been shown to be highly expressed in papillary thyroid cancer tissues with only a limited understanding of its functional roles and downstream regulatory mechanisms in papillary thyroid cancer cells. METHODS: We applied three thyroid cancer cell lines (MDA-T32, MDA-T41 and K1) to investigate the phenotypic influence after gain or loss of HOTAIR. The Cancer Genome Atlas (TCGA) database were utilised to select candidate genes possibly regulated by HOTAIR with validation in the cellular system and immunohistochemical (IHC) staining of PTC tissues. RESULTS: We observed HOTAIR was highly expressed in MDA-T32 cells but presents significantly decreased levels in MDA-T41 and K1 cells. HOTAIR knockdown in MDA-T32 cells significantly suppressed proliferation, colony formation, migration with cell cycle retardation at G1 phase. On the contrary, HOTAIR overexpression in MDA-T41 cells dramatically enhanced proliferation, colony formation, migration with cell cycle driven toward S and G2/M phases. Similar phenotypic effects were also observed as overexpressing HOTAIR in K1 cells. To explore novel HOTAIR downstream mechanisms, we analyzed TCGA transcriptome in PTC tissues and found DLX1 negatively correlated to HOTAIR, and its lower expression associated with reduced progression free survival. We further validated DLX1 gene was epigenetically suppressed by HOTAIR via performing chromatin immunoprecipitation. Moreover, IHC staining shows a significantly stepwise decrease of DLX1 protein from normal thyroid tissues to stage III PTC tissues. CONCLUSIONS: Our study pointed out that HOTAIR is a key regulator of cellular malignancy and its epigenetic suppression on DLX1 serves as a novel biomarker to evaluate the PTC disease progression.

Risk Role of Breast Cancer in Association with Human Papilloma Virus among Female Population in Taiwan: A Nationwide Population-Based Cohort Study.

PURPOSE: We analyzed data from the National Health Insurance Research Database (NHIRD) in Taiwan, collected information regarding human papillomavirus (HPV) and breast cancer prevalence, and explored the association between HPV infection and the risk of breast carcinoma. METHODS: We included the NHIRD data of 30,936 insured patients aged 20 years an older without breast cancer prior to the index date (date of HPV diagnosis) and matched each patient with a reference subject according to age, comorbidities, and index year (1:1 ratio). We calculated the incidence rates of breast cancer in the cohorts, age groups, and comorbidity groups, as well as the relative risk of breast cancer stratified by age and comorbidity in the HPV and non-HPV groups. RESULTS: The patients with and without HPV had incidence rates of 12.5 and 9.81 per 10,000 person years, respectively. The risk of breast cancer for the 50-64 and ≥65 age groups was 1.67 and 1.36 times higher than that in patients younger than 49 years, respectively, and hypertension, chronic obstructive pulmonary disease, and diabetes mellitus were significant risk factors for breast cancer. The HPV group had a higher risk of developing breast cancer than the non-HPV group, regardless of age group and the presence or absence of comorbidities. Patients with HPV in the 50-64 age group were 1.39 times more likely to develop breast cancer than patients of the same age without HPV. CONCLUSION: Patients older than 49 were more likely to develop breast cancer, and patients with HPV had a higher likelihood of developing breast cancer, regardless of age and the presence or absence of comorbidities. HPV likely plays a causal role in breast cancer.

Using bioinformatics approaches to identify survival-related oncomiRs as potential targets of miRNA-based treatments for lung adenocarcinoma.

Lung cancer is a major cause of cancer-associated deaths worldwide, and lung adenocarcinoma (LUAD) is the most common lung cancer subtype. Micro RNAs (miRNAs) regulate the pattern of gene expression in multiple cancer types and have been explored as potential drug development targets. To develop an oncomiR-based panel, we identified miRNA candidates that show differential expression patterns and are relevant to the worse 5-year overall survival outcomes in LUAD patient samples. We further evaluated various combinations of miRNA candidates for association with 5-year overall survival and identified a four-miRNA panel: miR-9-5p, miR-1246, miR-31-3p, and miR-3136-5p. The combination of these four miRNAs outperformed any single miRNA for predicting 5-year overall survival (hazard ratio [HR]: 3.47, log-rank p-value = 0.000271). Experiments were performed on lung cancer cell lines and animal models to validate the effects of these miRNAs. The results showed that singly transfected antagomiRs largely inhibited cell growth, migration, and invasion, and the combination of all four antagomiRs considerably reduced cell numbers, which is twice as effective as any single miRNA-targeted transfected. The in vivo studies revealed that antagomiR-mediated knockdown of all four miRNAs significantly reduced tumor growth and metastatic ability of lung cancer cells compared to the negative control group. The success of these in vivo and in vitro experiments suggested that these four identified oncomiRs may have therapeutic potential.

Identification of a Steroid Hormone-Associated Gene Signature Predicting the Prognosis of Prostate Cancer through an Integrative Bioinformatics Analysis.

The importance of anti-androgen therapy for prostate cancer (PC) has been well recognized. However, the mechanisms underlying prostate cancer resistance to anti-androgens are not completely understood. Therefore, identifying pharmacological targets in driving the development of castration-resistant PC is necessary. In the present study, we sought to identify core genes in regulating steroid hormone pathways and associating them with the disease progression of PC. The selection of steroid hormone-associated genes was identified from functional databases, including gene ontology, KEGG, and Reactome. The gene expression profiles and relevant clinical information of patients with PC were obtained from TCGA and used to examine the genes associated with steroid hormone. The machine-learning algorithm was performed for key feature selection and signature construction. With the integrative bioinformatics analysis, an eight-gene signature, including CA2, CYP2E1, HSD17B, SSTR3, SULT1E1, TUBB3, UCN, and UGT2B7 was established. Patients with higher expression of this gene signature had worse progression-free interval in both univariate and multivariate cox models adjusted for clinical variables. The expression of the gene signatures also showed the aggressiveness consistently in two external cohorts, PCS and PAM50. Our findings demonstrated a validated eight-gene signature could successfully predict PC prognosis and regulate the steroid hormone pathway.

Identification of DNA Damage Repair-Associated Prognostic Biomarkers for Prostate Cancer Using Transcriptomic Data Analysis.

In the recent decade, the importance of DNA damage repair (DDR) and its clinical application have been firmly recognized in prostate cancer (PC). For example, olaparib was just approved in May 2020 to treat metastatic castration-resistant PC with homologous recombination repair-mutated genes; however, not all patients can benefit from olaparib, and the treatment response depends on patient-specific mutations. This highlights the need to understand the detailed DDR biology further and develop DDR-based biomarkers. In this study, we establish a four-gene panel of which the expression is significantly associated with overall survival (OS) and progression-free survival (PFS) in PC patients from the TCGA-PRAD database. This panel includes DNTT, EXO1, NEIL3, and EME2 genes. Patients with higher expression of the four identified genes have significantly worse OS and PFS. This significance also exists in a multivariate Cox regression model adjusting for age, PSA, TNM stages, and Gleason scores. Moreover, the expression of the four-gene panel is highly correlated with aggressiveness based on well-known PAM50 and PCS subtyping classifiers. Using publicly available databases, we successfully validate the four-gene panel as having the potential to serve as a prognostic and predictive biomarker for PC specifically based on DDR biology.

An unusual cause of pleural effusion.

We describe a case of human herpes virus-8-associated primary effusion lymphoma (PEL) in a patient initially presented with fever, non-productive cough and exertional dyspnoea. Physical examination revealed oral thrush, diminished breath sounds and dullness on percussion over the left hemithorax. A thoracic computed tomography (CT) revealed left-sided massive pleural effusion without tumour masses or lymphadenopathy. The effusion was drained and cytology showed medium to large lymphoid cells, with prominent nucleoli and irregular nuclear contours. Meanwhile, his HIV was tested positive. Cell block immunostaining of the pleural effusion revealed these cells were CD45 (+), CD30 (+), MUM1 (melanoma-associated antigen [mutated] 1) (+), LANA (latency-associated nuclear antigen) (+) and EBER (Epstein-Barr virus-encoded small RNAs) in situ hybridization (-). This case highlights the learning point that PEL in the setting of HIV/AIDS should be added in the differential diagnosis of patients with unexplained oropharyngeal candidiasis and malignant lymphomatous pleural effusion without a clear primary site.

Genome-Wide Epigenetic Landscape of Lung Adenocarcinoma Links HOXB9 DNA Methylation to Intrinsic EGFR-TKI Resistance and Heterogeneous Responses.

PURPOSE: Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) show efficacy in treating patients with lung adenocarcinoma with EGFR-activating mutations. However, a significant subset of targeted patients fail to respond. Unlike acquired resistance (AR), intrinsic resistance (IR) remains poorly understood. We investigated whether epigenomic factors contribute to patient-to-patient heterogeneity in the EGFR-TKI response and aimed to characterize the IR subpopulation that obtains no benefit from EGFR-TKIs. PATIENTS AND METHODS: We conducted genome-wide DNA methylation profiling of 79 tumors sampled from patients with advanced lung adenocarcinoma before they received EGFR-TKI treatment and analyzed the patient responses. Pyrosequencing was performed in a validation cohort of 163 patients with EGFR-activating mutations. RESULTS: A DNA methylation landscape of 216 CpG sites with differential methylation was established to elucidate the association of DNA methylation with the characteristics and EGFR-TKI response status of the patients. Functional analysis of 37 transcription-repressive sites identified the enrichment of transcription factors, notably homeobox (HOX) genes. DNA methylation of HOXB9 (cg13643585) in the enhancer region yielded 88% sensitivity for predicting drug response (odds ratio [OR], 6.64; 95% CI, 1.98 to 25.23; P = .0009). Pyrosequencing validated that HOXB9 gained methylation in patients with a poor EGFR-TKI response (OR, 3.06; 95% CI, 1.13 to 8.19; P = .019). CONCLUSION: Our data suggest that homeobox DNA methylation could be a novel tumor cellular state that can aid the precise categorization of tumor heterogeneity in the study of IR to EGFR-TKIs. We identified, for the first time, an epigenomic factor that can potentially complement DNA mutation status in discriminating patients with lung adenocarcinoma who are less likely to benefit from EGFR-TKI treatment, thereby leading to improved patient management in precision medicine.

Lung carcinomas induced by NNK and LPS.

Cigarette smoking is the major culprit of chronic lung diseases and the most dominant risk factor for the development of both lung cancer and chronic obstructive pulmonary disease (COPD). In addition, chronic inflammation has been shown to increase the risk of lung cancer and COPD in clinical and epidemiological studies. For pulmonary disease-related research, mice are the most commonly used model system. Multiple lung cancer mouse models driven by targeted genetic alterations are used to evaluate the critical roles of oncogenes and tumor suppressor genes. These models are useful in addressing lung tumorigenesis associated with specific genetic changes, but they are not able to provide a global insight into cigarette smoke-induced carcinogenesis. To fill this knowledge gap, we developed a lung cancer model by treating mice with cigarette smoke carcinogen nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) with/without repeated lipopolysaccharides (LPS) exposure in order to determine the role of chronic inflammation in lung tumorigenesis. Notably, combined LPS/NNK treatment increased tumor number, tumor incidence, and tumor area compared to NNK treatment alone. Therefore, this model offers a feasible approach to investigate lung cancer development on a more global level, determine the role of inflammation in carcinogenesis, and provide a tool for evaluating chemoprevention and immunotherapy.

Treatment with a Urinary Bladder Matrix Alters the Innate Host Response to Pneumonia Induced by Escherichia coli.

Escherichiacoli has become the prominent cause of nosocomial pneumonia in recent years. In the meantime, some strains of E. coli have developed resistance to commonly used antibacterial drugs. The urinary bladder matrix (UBM) is a biologically derived scaffold material that has been used to promote site-appropriate tissue remodeling in a variety of body systems, partially through the modulation of the innate immune response. In this study, we seek to determine UBM efficacy in preventing bacterial pneumonia in mouse lungs using the Gram-negative bacterial strain E. coli. Our results show that the UBM prevented bacterial biofilm formation in both abiotic and biotic conditions through experimentation on polystyrene plates and culture on the apical surface of differentiated airway epithelial cells. Intratracheal treatment with UBM led to host protection from E. coli-induced respiratory infection in a murine pneumonia model. Transcriptomic analysis revealed the involvement of the enhanced host immune response in UBM-treated mice. Additionally, UBM-treated macrophages had an increased iNOS expression and enhanced phagocytosis activity. Therefore, the protection against E. coli-induced infection and the antibacterial function observed by UBM is potentially through both the anti-biofilm activity and enhanced host immunity following UBM treatment. Taken together, our results support further investigation of UBM as an alternative treatment to attenuate bacterial-induced respiratory infection.

Lipopolysaccharide-Mediated Chronic Inflammation Promotes Tobacco Carcinogen-Induced Lung Cancer and Determines the Efficacy of Immunotherapy.

Chronic obstructive pulmonary disease (COPD) is an inflammatory disease that is associated with increased risk of lung cancer. Pseudomonas aeruginosa (PA) infections are frequent in patients with COPD, which increase lung inflammation and acute exacerbations. However, the influences of PA-induced inflammation on lung tumorigenesis and the efficacy of immune checkpoint blockade remain unknown. In this study, we initiated a murine model of lung cancer by treating FVB/NJ female mice with tobacco carcinogen nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) alone or in combination with PA-lipopolysaccharide (LPS). LPS-mediated chronic inflammation induced T-cell exhaustion, increased the programmed cell death-1 (PD-1)/programmed cell death ligand-1 (PD-L1) axis, and enhanced NNK-induced lung tumorigenesis through an immunosuppressive microenvironment characterized by accumulation of myeloid-derived suppressive cells (MDSC) and regulatory T cells. Anti-PD-1 antibody treatment reduced tumors in NNK/LPS-treated mice with a 10-week LPS treatment but failed to inhibit tumor growth when LPS exposure was prolonged to 16 weeks. Anti-Ly6G antibody treatment coupled with depletion of MDSC alone reduced tumor growth; when combined with anti-PD-1 antibody, this treatment further enhanced antitumor activity in 16-week NNK/LPS-treated mice. Immune gene signatures from a human lung cancer dataset of PD-1 blockade were identified, which predicted treatment responses and survival outcome and overlapped with those from the mouse model. This study demonstrated that LPS-mediated chronic inflammation creates a favorable immunosuppressive microenvironment for tumor progression and correlates with the efficacy of anti-PD-1 treatment in mice. Immune gene signatures overlap with human and mouse lung tumors, providing potentially predictive markers for patients undergoing immunotherapy. SIGNIFICANCE: This study identifies an immune gene signature that predicts treatment responses and survival in patients with tobacco carcinogen-induced lung cancer receiving immune checkpoint blockade therapy.