Augmented Lipocalin-2 Is Associated with Chronic Obstructive Pulmonary Disease and Counteracts Lung Adenocarcinoma Development.

Rationale: Early pathogenesis of lung adenocarcinoma (LUAD) remains largely unknown. We found that, relative to wild-type littermates, the innate immunomodulator Lcn2 (lipocalin-2) was increased in normal airways from mice with knockout of the airway lineage gene Gprc5a (Gprc5a-/-) and that are prone to developing inflammation and LUAD. Yet, the role of LCN2 in lung inflammation and LUAD is poorly understood.Objectives: Delineate the role of Lcn2 induction in LUAD pathogenesis.Methods: Normal airway brushings, uninvolved lung tissues, and tumors from Gprc5a-/- mice before and after tobacco carcinogen exposure were analyzed by RNA sequencing. LCN2 mRNA was analyzed in public and in-house data sets of LUAD, lung squamous cancer (LUSC), chronic obstructive pulmonary disease (COPD), and LUAD/LUSC with COPD. LCN2 protein was immunohistochemically analyzed in a tissue microarray of 510 tumors. Temporal lung tumor development, gene expression programs, and host immune responses were compared between Gprc5a-/- and Gprc5a-/-/Lcn2-/- littermates.Measurements and Main Results:Lcn2 was progressively elevated during LUAD development and positively correlated with proinflammatory cytokines and inflammation gene sets. LCN2 was distinctively elevated in human LUADs, but not in LUSCs, relative to normal lungs and was associated with COPD among smokers and patients with LUAD. Relative to Gprc5a-/- mice, Gprc5a-/-/Lcn2-/- littermates exhibited significantly increased lung tumor development concomitant with reduced T-cell abundance (CD4+) and richness, attenuated antitumor immune gene programs, and increased immune cell expression of protumor inflammatory cytokines.Conclusions: Augmented LCN2 expression is a molecular feature of COPD-associated LUAD and counteracts LUAD development in vivo by maintaining antitumor immunity.

[Effects of Xiangqin Jiere Granules on lipid metabolism and chronic inflammation in different obesity model mice].

This paper aims to study the effect of Xiangqin Jiere Granules(XQ) on lipid metabolism and chronic inflammation in different obesity model mice. The monosodium glutamate(MSG) obese mouse model was established by subcutaneous injection of MSG in newborn mice, and the high fat diet(HFD) obese mouse model was established by feeding adult mice with HFD. The normal mice were assigned into the control group; the MSG obese mice were assigned into MSG model group, XQ4.5 group(Xiangqin Jiere Granu-les, 4.5 g·kg~(-1)), XQ22.5 group(Xiangqin Jiere Granules, 22.5 g·kg~(-1)); the HFD obese mice were assigned into HFD model group, XQ4.5 group, and XQ22.5 group. The mice were intragastrically administrated with saline or XQ for 5 weeks. After that, the body weight, visceral fat mass, liver and thymus weight, and the organ indexes in each group were measured. The levels of triglyceride(TG), total cholesterol(TC), and low-density lipoprotein cholesterol(LDL-c) in serum and liver tissue were detected by the kits. The mRNA expression levels of acetyl CoA carboxylase 1(ACC1), fatty acid synthetase(FAS), diacylgycerol acyltransferase 1(DGAT1) and hepatic lipase(HTGL) involved in lipid metabolism in mouse liver tissue were detected by quantitative real-time PCR(qPCR). The protein levels of tumor necrosis factor-α(TNF-α) and interleukin-6(IL-6) in serum were detected by ELISA, and the mRNA levels of TNF-α and IL-6 in liver tissue were detected by qPCR. Compared with the control group, MSG and HFD mice showed increased body weight, abdominal circumference, Lee index and visceral fat mass as well as elevated levels of TG, TC, and LDL-c in serum. The model mice had up-regulated gene levels of ACC1, FAS and DGAT1 while down-regulated gene level of HTGL in the liver. Furthermore, the mRNA and protein levels of IL-6 increased in the model mice. Compared with the model mice, XQ treatment decreased the body weight, abdominal circumference, Lee index, and visceral fat mass, lowered the levels of TG, TC, and LDL-c in se-rum, down-regulated the gene levels of ACC1, FAS, and DGAT1 in liver tissue, up-regulated the gene level of HTGL, and down-regulated the mRNA and protein levels of IL-6. To sum up, XQ has good therapeutic effect on different obesity model mice. It can improve lipid metabolism and reduce fat accumulation in obese mice by regulating the enzymes involved in lipid metabolism, and alleviate obesity-related chronic low-grade inflammation.

Targeting eIF4A triggers an interferon response to synergize with chemotherapy and suppress triple-negative breast cancer.

Protein synthesis is frequently dysregulated in cancer and selective inhibition of mRNA translation represents an attractive cancer therapy. Here, we show that therapeutically targeting the RNA helicase eIF4A with zotatifin, the first-in-class eIF4A inhibitor, exerts pleiotropic effects on both tumor cells and the tumor immune microenvironment in a diverse cohort of syngeneic triple-negative breast cancer (TNBC) mouse models. Zotatifin not only suppresses tumor cell proliferation but also directly repolarizes macrophages toward an M1-like phenotype and inhibits neutrophil infiltration, which sensitizes tumors to immune checkpoint blockade. Mechanistic studies revealed that zotatifin reprograms the tumor translational landscape, inhibits the translation of Sox4 and Fgfr1, and induces an interferon (IFN) response uniformly across models. The induction of an IFN response is partially due to the inhibition of Sox4 translation by zotatifin. A similar induction of IFN-stimulated genes was observed in breast cancer patient biopsies following zotatifin treatment. Surprisingly, zotatifin significantly synergizes with carboplatin to trigger DNA damage and an even heightened IFN response, resulting in T cell-dependent tumor suppression. These studies identified a vulnerability of eIF4A in TNBC, potential pharmacodynamic biomarkers for zotatifin, and provide a rationale for new combination regimens consisting of zotatifin and chemotherapy or immunotherapy as treatments for TNBC.

Targeting EIF4A triggers an interferon response to synergize with chemotherapy and suppress triple-negative breast cancer.

Protein synthesis is frequently dysregulated in cancer and selective inhibition of mRNA translation represents an attractive cancer therapy. Here, we show that therapeutically targeting the RNA helicase eIF4A by Zotatifin, the first-in-class eIF4A inhibitor, exerts pleiotropic effects on both tumor cells and the tumor immune microenvironment in a diverse cohort of syngeneic triple-negative breast cancer (TNBC) mouse models. Zotatifin not only suppresses tumor cell proliferation but also directly repolarizes macrophages towards an M1-like phenotype and inhibits neutrophil infiltration, which sensitizes tumors to immune checkpoint blockade. Mechanistic studies revealed that Zotatifin reprograms the tumor translational landscape, inhibits the translation of Sox4 and Fgfr1, and induces an interferon response uniformly across models. The induction of an interferon response is partially due to the inhibition of Sox4 translation by Zotatifin. A similar induction of interferon-stimulated genes was observed in breast cancer patient biopsies following Zotatifin treatment. Surprisingly, Zotatifin significantly synergizes with carboplatin to trigger DNA damage and an even heightened interferon response resulting in T cell-dependent tumor suppression. These studies identified a vulnerability of eIF4A in TNBC, potential pharmacodynamic biomarkers for Zotatifin, and provide a rationale for new combination regimens comprising Zotatifin and chemotherapy or immunotherapy as treatments for TNBC.

The immune landscape of undifferentiated pleomorphic sarcoma.

Introduction: Undifferentiated pleomorphic sarcoma (UPS) can be associated with a relatively dense immune infiltration. Immune checkpoint inhibitors (anti-PD1, anti-PDL1, and anti-CTLA4) are effective in 20% of UPS patients. We characterize the immune microenvironment of UPS and its association with oncologic outcomes. Material and methods: Surgically resected UPS samples were stained by immunohistochemistry (IHC) for the following: tumor-associated immune cells (CD3, CD8, CD163, CD20), immune checkpoints (stimulatory: OX40, ICOS; inhibitory: PD-L1, LAG3, IDO1, PD1), and the adenosine pathway (CD73, CD39). Sections were reviewed for the presence of lymphoid aggregates (LA). Clinical data were retrospectively obtained for all samples. The Wilcoxon rank-sum and Kruskal-Wallis tests were used to compare distributions. Correlations between biomarkers were measured by Spearman correlation. Univariate and multivariate Cox models were used to identify biomarkers associated with overall survival (OS) and disease-free survival (DFS). Unsupervised clustering was performed, and Kaplan-Meier curves and log-rank tests used for comparison of OS and DFS between immune clusters. Results: Samples analyzed (n=105) included 46 primary tumors, 34 local recurrences, and 25 metastases. LA were found in 23% (n=10/43), 17% (n=4/24), and 30% (n=7/23) of primary, recurrent, and metastatic samples, respectively. In primary UPS, CD73 expression was significantly higher after preoperative radiation therapy (p=0.009). CD39 expression was significantly correlated with PD1 expression (primary: p=0.002, recurrent: p=0.004, metastatic: p=0.001), PD-L1 expression (primary: p=0.009), and CD3+ cell densities (primary: p=0.016, recurrent: p=0.043, metastatic: p=0.028). In recurrent tumors, there was a strong correlation between CD39 and CD73 (p=0.015), and both were also correlated with CD163+ cell densities (CD39 p=0.013; CD73 p<0.001). In multivariate analyses, higher densities of CD3+ and CD8+ cells (Cox Hazard Ratio [HR]=0.33; p=0.010) were independently associated with OS (CD3+, HR=0.19, p<0.001; CD8+, HR= 0.33, p=0.010) and DFS (CD3+, HR=0.34, p=0.018; CD8+, HR=0.34, p= 0.014). Unsupervised clustering of IHC values revealed three immunologically distinct clusters: immune high, intermediate, and low. In primary tumors, these clusters were significantly associated with OS (log-rank p<0.0001) and DFS (p<0.001). Conclusion: We identified three immunologically distinct clusters of UPS Associated with OS and DFS. Our data support further investigations of combination anti-PD-1/PD-L1 and adenosine pathway inhibitors in UPS.

Subtle genetic changes enhance virulence of methicillin resistant and sensitive Staphylococcus aureus.

BACKGROUND: Community acquired (CA) methicillin-resistant Staphylococcus aureus (MRSA) increasingly causes disease worldwide. USA300 has emerged as the predominant clone causing superficial and invasive infections in children and adults in the USA. Epidemiological studies suggest that USA300 is more virulent than other CA-MRSA. The genetic determinants that render virulence and dominance to USA300 remain unclear. RESULTS: We sequenced the genomes of two pediatric USA300 isolates: one CA-MRSA and one CA-methicillin susceptible (MSSA), isolated at Texas Children's Hospital in Houston. DNA sequencing was performed by Sanger dideoxy whole genome shotgun (WGS) and 454 Life Sciences pyrosequencing strategies. The sequence of the USA300 MRSA strain was rigorously annotated. In USA300-MRSA 2658 chromosomal open reading frames were predicted and 3.1 and 27 kilobase (kb) plasmids were identified. USA300-MSSA contained a 20 kb plasmid with some homology to the 27 kb plasmid found in USA300-MRSA. Two regions found in US300-MRSA were absent in USA300-MSSA. One of these carried the arginine deiminase operon that appears to have been acquired from S. epidermidis. The USA300 sequence was aligned with other sequenced S. aureus genomes and regions unique to USA300 MRSA were identified. CONCLUSION: USA300-MRSA is highly similar to other MRSA strains based on whole genome alignments and gene content, indicating that the differences in pathogenesis are due to subtle changes rather than to large-scale acquisition of virulence factor genes. The USA300 Houston isolate differs from another sequenced USA300 strain isolate, derived from a patient in San Francisco, in plasmid content and a number of sequence polymorphisms. Such differences will provide new insights into the evolution of pathogens.

A hybrid model for PM2.5 forecasting based on ensemble empirical mode decomposition and a general regression neural network.

Exposure to high concentrations of fine particulate matter (PM2.5) can cause serious health problems because PM2.5 contains microscopic solid or liquid droplets that are sufficiently small to be ingested deep into human lungs. Thus, daily prediction of PM2.5 levels is notably important for regulatory plans that inform the public and restrict social activities in advance when harmful episodes are foreseen. A hybrid EEMD-GRNN (ensemble empirical mode decomposition-general regression neural network) model based on data preprocessing and analysis is firstly proposed in this paper for one-day-ahead prediction of PM2.5 concentrations. The EEMD part is utilized to decompose original PM2.5 data into several intrinsic mode functions (IMFs), while the GRNN part is used for the prediction of each IMF. The hybrid EEMD-GRNN model is trained using input variables obtained from principal component regression (PCR) model to remove redundancy. These input variables accurately and succinctly reflect the relationships between PM2.5 and both air quality and meteorological data. The model is trained with data from January 1 to November 1, 2013 and is validated with data from November 2 to November 21, 2013 in Xi'an Province, China. The experimental results show that the developed hybrid EEMD-GRNN model outperforms a single GRNN model without EEMD, a multiple linear regression (MLR) model, a PCR model, and a traditional autoregressive integrated moving average (ARIMA) model. The hybrid model with fast and accurate results can be used to develop rapid air quality warning systems.