CXCL9 expression in breast cancer and its correlation with the characteristics of tumor immunoinfiltration

Objective·To explore the effect of C-X-C motif chemokine ligand 9 (CXCL9) expression on the prognosis of breast cancer patients and its correlation with tumor-infiltrating immune cells (TIICs).Methods·Transcriptome data of 1 100 breast tumor tissues and 112 adjacent tissues were obtained from The Cancer Genome Atlas (TCGA) database. CIBERSORT deconvolution algorithm was used to analyze the proportion of TIIC subgroups in breast cancer immune microenvironment and its effect on the prognosis of patients. Differentially expressed genes, immune-related genes and breast cancer prognostic-related genes were downloaded from TCGA database, ImmPort database and GEPIA2 data platform, respectively. The intersection relationships of the three gene sets were analyzed by using R language, and the target genes were screened. Based on the downloaded transcriptome data, CXCL9 positive-related genes, the difference of CXCL9 mRNA expression in breast cancer tissues and adjacent tissues and its effect on the prognosis of patients were analyzed. STRING data platform was used to analyze the protein-protein interaction (PPI) network of CXCL9. Gene Ontology (GO) function analysis and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis were performed on CXCL9 positive correlation genes and the genes corresponding to the interacting proteins obtained from the PPI network by using R language. Spearman correlation coefficient was used to analyze the correlation between CXCL9 mRNA expression and TIIC subgroups and immune checkpoint-related genes. Paraffin tissue samples of 60 clinical breast cancer patients were collected and made into tissue chips. The correlation between CXCL9 expression and CD8+ T cells infiltration in the tissue chips was detected by immunohistochemical staining (IHC). The types of CXCL9+ cells in breast cancer interstitium were analyzed by multiplex immunohistochemistry staining (mIHC). Kaplan-Meier (KM) survival curve was used to analyze the effect of CXCL9 mRNA expression and CD8+ T cell infiltration on the prognosis of breast cancer patients.Results·CIBERSORT algorithm analysis showed that the distribution proportion of TIIC subgroups in breast cancer immune microenvironment varied greatly, and their effect on patients′ prognosis was also different. The Venn diagram of three types of gene sets was drawn, and CXCL9 was screened out. The top 150 positive correlation genes with CXCL9 were obtained. CXCL9 mRNA expression levels in four molecular types of breast cancer were higher than those in adjacent tissues (all P=0.000), and their high expressions were significantly associated with good prognosis of patients (P=0.013). A total of 41 interacting proteins were obtained through PPI network analysis. GO and KEGG analysis showed that CXCL9 and its related genes were mainly enriched in biological functions and pathways related to immune regulation. Spearman correlation coefficient analysis showed that the expression level of CXCL9 mRNA was positively correlated with CD8+ T cells infiltration ratio, negatively correlated with M2-type macrophages infiltration ratio, and positively correlated with most immune checkpoint genes expression (all P<0.05). IHC experiments showed that CXCL9 was highly expressed in breast cancer tissues compared with adjacent tissues, accompanied by an increased percentage of CD8+ T cells infiltration (P=0.000). mIHC results showed that CXCL9 was expressed in some CD68+ tumor-associated macrophages (TAMs) and CD11c+ dendritic cells (DCs) in the stroma of breast cancer. KM survival curve showed that when CXCL9 was highly expressed, CD8+ T cells high infiltration could prolong the survival of breast cancer patients.Conclusion·CXCL9 can be used as a biomarker for good prognosis of breast cancer patients. The high expression of CXCL9 in the microenvironment of breast cancer is positively correlated with the infiltration ratio of CD8+ T cells and may activate its anti-tumor effect. The expression of CXCL9 may be closely related to the recruitment of lymphocytes into the tumor microenvironment for anti-tumor immune response

The joint effect of cumulative doses for outdoor air pollutants exposure in early life on asthma and wheezing among young children

Background: Constrained by no proper way to assess cumulative exposure, the joint effect of air pollution cumulative exposure doses on childhood asthma and wheezing (AW) was not understood. Objective: To assess the association between cumulative exposure to multiple air pollutants in early life and childhood AW. Methods: We designed a nested case-control study based on the birth cohort in Jinan City. Children with AW followed up within 2 years after birth were treated as cases, and non-cases in this cohort were treated as the control source population, and the propensity score matching method was used to match each case to 5 controls. We calculated the individual cumulative outdoor exposure doses for each period using an inverse distance weighted model, alongside the complex Simpson's formula, accounting for outdoor time and respiratory volume. The Least absolute shrinkage and selection operator (Lasso) regression was performed to screen for covariates. To analyze the joint effects of pollutants, we employed the weighted quantile sum (WQS) regression model in conjunction with conditional logistic regression. Results: 84 cases and 420 controls were included in this study. The odds ratio (OR) with 95% confidence interval (CI) of the impact of cumulative exposure (mg/m3) after birth on childhood AW was 1.78 (1.15–2.74) for SO2, 1.69 (1.11–2.57) for NO2, and 1.65 (1.09–2.52) for PM2.5, respectively. Furthermore, with each 25th percentile increase in the WQS index, the overall risk of cumulative doses for six pollutants exposure after birth on AW increased by an adjusted OR of 1.10 (1.03, 1.18), and SO2, PM2.5, and NO2 contributed the most to the WQS index. However, no statistically significant association was found between cumulative exposure to all pollutants before birth and childhood AW. Conclusions: There was a joint effect of the cumulative exposure dose of outdoor air pollutants after birth on AW in children aged 0–2 years. And traffic-related pollutants (SO2, PM2.5, and NO2) make a greater contribution to the joint effect

Unveiling the origin of anomalous low-frequency Raman mode in CVD-grown monolayer WS₂

Substrates provide the necessary support for scientific explorations of numerous promising features and exciting potential applications in two-dimensional (2D) transition metal dichalcogenides (TMDs). To utilize substrate engineering to alter the properties of 2D TMDs and avoid introducing unwanted adverse effects, various experimental techniques, such as high-frequency Raman spectroscopy, have been used to understand the interactions between 2D TMDs and substrates. However, sample-substrate interaction in 2D TMDs is not yet fully understood due to the lack of systematic studies by techniques that are sensitive to 2D TMD-substrate interaction. This work systematically investigates the interaction between tungsten disulfide (WS2) monolayers and substrates by low-frequency Raman spectroscopy, which is very sensitive to WS2-substrate interaction. Strong coupling with substrates is clearly revealed in chemical vapor deposition (CVD)-grown monolayer WS2 by its low-wavenumber interface mode. It is demonstrated that the enhanced sample-substrate interaction leads to tensile strain on monolayer WS2, which is induced during the cooling process of CVD growth and could be released for monolayer WS2 sample after transfer or fabricated by an annealing-free method such as mechanical exfoliation. These results not only suggest the effectiveness of low-frequency Raman spectroscopy for probing sample-substrate interactions in 2D TMDs, but also provide guidance for the design of high-performance devices with the desired sample-substrate coupling strength based on 2D TMDs.Ministry of Education (MOE)National Research Foundation (NRF)This work is supported by the National Natural Science Foundation of China (Nos. 62004197 and 61774040), the Ministry of Education of Singapore (No. MOE2019-T2-1-004), the Singapore National Research Foundation under the Competitive Research Programs (No. NRF-CRP-21-2018-0007), the National Key R&D Program of China (No. 2018YFA0703700), the National Young 1000 Talent Plan of China, the Shanghai Municipal Natural Science Foundation (No. 20ZR1403200), the Shanghai Municipal Science and Technology Commission (No. 18JC1410300), the Fudan University-CIOMP Joint Fund (No. FC2018-002), and the Natural Science Foundation of Liaoning Province, China (Nos. 2019-BS-243 and 2019-MS-320)