Background: We designed the study to investigate whether methotrexate, doxorubicin, and cisplatinum (MAP) chemotherapy strategy was still the preferred option for the survival of osteosarcoma patients. Method: We collected some trials of osteosarcoma to make a meta-analysis first. Then, we retrospectively collected data from 115 patients with osteosarcoma and performed further analysis to verify the impact of MAP regimen on the survival of patients. Results: Seven studies including 3433 participants met the preliminary inclusion criteria. Meta-analysis of the 3-year disease-free survival (odds ratio [OR] = 1.06, 95% confidence interval [CI]: 0.88–1.28; P = .52) and overall survival (OR = 1.21, 95% CI: 0.70–2.11; P = .54), 5-year disease-free survival (OR = 1.07, 95% CI: 0.87–1.30; P = .54) and overall survival (OR = 0.86, 95% CI: 0.65–1.12; P = .26), and mortality rate (OR = 0.90, 95% CI: 0.70–1.17; P = .44), showed no statistically significant differences. The most common grade 3/4 adverse events were neutropenia (498 [85.9%] patients in MAP vs 533 [93.3%] in MAP plus ifosfamide and etoposide, or other adjuvant therapy drugs [MAP⁺]). MAP was associated with less frequent toxicities than MAP⁺ group with statistical significance in thrombocytopenia, febrile neutropenia, anemia, and hypophosphatemia. The same phenomenon could also be seen in the analysis of clinical data. Conclusion: MAP regimen remains the preferred option for osteosarcoma chemotherapy.

Background: This study was designed to explore the implications of ferroptosis-related alterations in glioblastoma patients.Method: After obtaining the data sets CGGA325, CGGA623, TCGA-GBM, and GSE83300 online, extensive analysis and mutual verification were performed using R language-based analytic technology, followed by further immunohistochemistry staining verification utilizing clinical pathological tissues.Results: The analysis revealed a substantial difference in the expression of ferroptosis-related genes between malignant and paracancerous samples, which was compatible with immunohistochemistry staining results from clinicopathological samples. Three distinct clustering studies were run sequentially on these data. All of the findings were consistent and had a high prediction value for glioblastoma. Then, the risk score predicting model containing 23 genes (CP, EMP1, AKR1C1, FMOD, MYBPH, IFI30, SRPX2, PDLIM1, MMP19, SPOCD1, FCGBP, NAMPT, SLC11A1, S100A10, TNC, CSMD3, ATP1A2, CUX2, GALNT9, TNFAIP6, C15orf48, WSCD2, and CBLN1) on the basis of “Ferroptosis.gene.cluster” was constructed. In the subsequent correlation analysis of clinical characteristics, tumor mutation burden, HRD, neoantigen burden and chromosomal instability, mRNAsi, TIDE, and GDSC, all the results indicated that the risk score model might have a better predictive efficiency.Conclusion: In glioblastoma, there were a large number of abnormal ferroptosis-related alterations, which were significant for the prognosis of patients. The risk score-predicting model integrating 23 genes would have a higher predictive value.

Lung adenocarcinoma (LUAD) is a very common and lethal kind of lung malignancy. An increasing number of studies indicated that tissue-resident memory T (T_RM) cells played significant roles in anti-cancer immunity. In our previous study, EXO1 was found to be a core gene for T_RM cells in the prognosis of LUAD. However, the roles of EXO1 in the tumor microenvironment, and its application in the diagnosis and prognosis prediction of LUAD are still inadequately explored. In this study, the RNA expression, DNA methylation, CNV, somatic mutation data of EXO1, and the corresponding patients’ clinical information from publicly available databases were analyzed using bioinformatic methods. The results were validated through immunohistochemical staining of EXO1 in LUAD samples. The results showed EXO1 was aberrantly highly expressed in LUAD tissues. High expression of EXO1 was a risky factor for LUAD patients. The expression level of EXO1 was associated with many clinical features such as TNM stages. It can also distinguish normal tissues and LUAD tumor tissues accurately. EXO1 expression was correlated with the infiltration of immune cells, and high expression of EXO1 was an adverse effect on LUAD patients receiving anti-PD-1/PD-L1 immunotherapy. Moreover, patients with EXO1 mutation had worse DSS, DFI and PFI.

Purpose: To investigate the significance of macrophage infiltration to the prognosis of lung adenocarcinoma.Methods: R language bioinformatics analysis technology, was used to obtain macrophage infiltration-related module genes through WGCNA (Weighted Gene Co-Expression Network Analysis). Marker genes of macrophage subtypes were identified using single-cell sequencing of lung adenocarcinoma tissue. Risk score models were constructed and validated using external data cohorts and clinical samples.Results: Analysis of cohorts TCGA-LUAD, GSE11969, GSE31210, GSE50081, GSE72094 and GSE8894, revealed a negative correlation between macrophage infiltration and survival. Immunohistochemical analyses of clinical samples were consistent with these data. Based on cell-cluster-markers and TAMs-related-genes, TOP8 genes were obtained (C1QTNF6, CCNB1, FSCN1, HMMR, KPNA2, PRC1, RRM2, and TK1) with a significant association to prognosis. Risk score models including 9 factors (C1QTNF6, FSCN1, KPNA2, GLI2, TYMS, BIRC3, RBBP7, KRT8, GPR65) for prognosis were constructed. The efficacy, stability and generalizability of the risk score models were validated using multiple data cohorts (GSE19188, GSE26939, GSE31210, GSE50081, GSE42127, and GSE72094).Conclusions: Macrophage infiltration negatively correlates with prognosis in patients with lung adenocarcinoma. Based on cell-cluster-markers and TAMs-related-genes, both TOP8 genes (C1QTNF6, CCNB1, FSCN1, HMMR, KPNA2, PRC1, RRM2, TK1) and risk score models using C1QTNF6, FSCN1, KPNA2, GLI2, TYMS, BIRC3, RBBP7, KRT8, GPR65 could predict disease prognosis.

In order to obtain adequate information for the treatment of methicillin resistant Staphylococcus aureus (MRSA) infections, it is crucial to identify trends in epidemiological and antimicrobial resistance patterns of local S. aureus strains. Community and hospital acquired S. aureus isolates (n=202) were characterized using staphylococcal cassette chromosome mec (SCCmec) typing, pulse field gel electrophoresis (PFGE) analysis, spa typing and minimal inhibitory concentration (MIC) determination. The prevalence of the Panton-Valentine leukocidine (pvl) and several antibiotic resistance genes among the isolates were also detected by PCR. All of the S. aureus isolates were susceptible to vancomycin, daptomycin and linezolid. Three hospital isolates were resistant to teicoplanin while 14 showed intermediate resistance to teicoplanin. The resistance patterns of community-acquired MRSA (CA-MRSA) isolates to other antimicrobials were similar to those of hospital-acquired MRSA (HA-MRSA) isolates except for clindamycin and gentamicin. There was excellent correlation between phenotypes and genotypes in the determination of S. aureus resistance to erythromycin, gentamicin, and tetracycline. The SCCmec type II and SCCmec type IV were the predominant types detected in hospital and community isolates, respectively. The most frequently encountered spa types were t002 and t030 both in HA- and CA-MRSA isolates. Pulsotype A was the most predominant pulsotype identified among the isolates tested, followed by pulsotype B. Seventy-two hospital isolates (19 HA-MRSA and 53 HA-MSSA) and 10 CA-MRSA were positive for the pvl gene. This study shows that the combination of susceptibility testing and various molecular methods has provided useful information on the antibiotic resistance and molecular diversity of S. aureus in a specific region of China. The high proportion of pvl positive MSSA and MRSA isolates observed in this study indicates that adequate measures are needed to curtail the spread of those MRSA and MSSA clones prevailing both in hospital and the community.

Purpose: This study aims to explore novel biomarkers related to the coagulation process and tumor-associated macrophage (TAM) infiltration in lung adenocarcinoma (LUAD).Methods: The macrophage M2-related genes were obtained by Weighted Gene Co-expression Network Analysis (WGCNA) in bulk RNA-seq data, while the TAM marker genes were identified by analyzing the scRNA-seq data, and the coagulation-associated genes were obtained from MSigDB and KEGG databases. Survival analysis was performed for the intersectional genes. A risk score model was subsequently constructed based on the survival-related genes for prognosis prediction and validated in external datasets.Results: In total, 33 coagulation and macrophage-related (COMAR) genes were obtained, 19 of which were selected for the risk score model construction. Finally, 10 survival-associated genes (APOE, ARRB2, C1QB, F13A1, FCGR2A, FYN, ITGB2, MMP9, OLR1, and VSIG4) were involved in the COMAR risk score model. According to the risk score, patients were equally divided into low- and high-risk groups, and the prognosis of patients in the high-risk group was significantly worse than that in the low-risk group. The ROC curve indicated that the risk score model had high sensitivity and specificity, which was validated in multiple external datasets. Moreover, the model also had high efficacy in predicting the clinical outcomes of LUAD patients who received anti-PD-1/PD-L1 immunotherapy.Conclusion: The COMAR risk score model constructed in this study has excellent predictive value for the prognosis and immunotherapeutic clinical outcomes of patients with LUAD, which provides potential biomarkers for the treatment and prognostic prediction.