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BackgroundImmunotherapy, frequently combined with conventional chemotherapy, is crucial for treating NSCLC. Kirsten rat sarcoma virus (KRAS) is a poor prognostic factor in patients with NSCLC, particularly lung adenocarcinoma, where binding of conventional inhibitors to mutated KRAS proteins is challenging. Field profiles, research hotspots, and prospects for immunotherapy for patients with NSCLC-carrying KRAS mutations were uncovered in this study.MethodsMicrosoft Excel 2019, Bibliometrix, VOSviewer software, and Citespace were utilized to conduct a comprehensive scientometric analysis and understand a specific research field's knowledge base and frontiers aided by bibliometrics.ResultsBetween 2014 and 2023, 398 eligible documents in the English language were acquired using the WoSCC database, of which 113 and 285 were reviews and articles, respectively. The growth rate per year was 34.25 %. The most cited articles were from the United States, and China published the highest number of articles. Cancers was the journal, with increased publications in recent years. The keywords with the strongest citation bursts were analyzed using Citespace. "Immune checkpoint inhibitors," "co-occurring genomic alterations," and "KRAS" are among the research hotspots in this field.ConclusionUsing bibliometric and visual analyses, we examined immunotherapy for patients with KRAS-mutant NSCLC over the previous decade. The whole analysis showed a steady, quick increase in yearly publications in this area. Our findings will provide a roadmap for future research on the mechanisms of immunotherapy and immune checkpoint inhibitor action in treating KRAS-mutant NSCLC.

A prepared FeZnNa@SiO2-C catalyst with graphitized carbon (C)-modified mesoporous SiO2 supports metal nanoparticles with the sol–gel method. The effect of adding metal Na and Zn promoters as a dispersion on the CO2 hydrogenation to low olefins was systematically studied. The results showed that Zn–Na, as a combination, could promote the absorption of CO2 and improved the conversion rate of CO2. Na as an alkaline substance can improve the absorption of more acidic CO2, which could increase the conversion rate of CO2 to 59.03%. Meanwhile, the addition of secondary metal Zn to Fe-based catalysts to form a surface alloy could alter the adsorption of CO2 and the activation of C-O bonds, inhibit the subsequent hydrogenation of olefins to paraffins, and facilitate the reduction of Fe2O3 and the formation of active Fe5C2 species. The formation of active Fe5C2 species was found in TEM and XRD, and the selectivity of the target product was 41.07%. The deep hydrogenation of olefins was inhibited, and the space–time yield (STY) of low olefins was raised again by inhibiting their deep hydrogenations, up to 0.0436. However, the corresponding STY did not increase infinitely with the increase of Na doping, and higher catalytic performance for CO2 hydrogenation could be exhibited when the Na doping reached 6.4%. Compared with Fe@SiO2-C catalyst, Na- and Zn-promoted Fe-based catalysts, prepared by the modified sol-gel method, can be used directly for highly efficient CO2 hydrogenation to low olefins and thus has a more promising application prospect in the future.

Given the complexity and highly heterogeneous nature of the microenvironment and its effects on antitumor immunity and cancer immune evasion, the prognostic value of a single immune marker is limited. Here, we show how the integration of immune checkpoint molecule expression and tumor-associated immune cell distribution patterns can influence prognosis prediction in non-small-cell lung cancer (NSCLC) patients. We analyzed tissue microarray (TMA) data derived from multiplex immunohistochemistry results and measured the densities of tumor-infiltrating CD8+ and FOXP3+ immune cells and tumor cells (PanCK+), as well as the densities of programmed cell death 1 (PD-1)+ and programmed cell death ligand 1 (PD-L1)+ cells in the peritumor and intratumor subregions. We found a higher density of infiltrating CD8+ and FOXP3+ immune cells in the peritumoral compartment than in the intratumoral compartment. In addition, unsupervised hierarchical clustering analysis of these markers revealed that the combination of high CD8/FOXP3 expression, low PD-1 and PD-L1 immune checkpoint expression, and lack of epidermal growth factor receptor (EGFR) mutation could be a favorable predictive marker. On the other hand, based on the clustering analysis, low CD8/FOXP3 and immune checkpoint (PD-1 and PD-L1) expression might be a marker for patients who are likely to respond to strategies targeting regulatory T (Treg) cells. Furthermore, an immune risk score model was established based on multivariate Cox regression, and the risk score was determined to be an independent prognostic factor for NSCLC patients. These results indicate that the immune context is heterogeneous because of the complex interactions of different components and that using multiple factors in combination might be promising for predicting the prognosis of and stratifying NSCLC patients.

Caused by schistosomes, the human schistosomiasis is a tropical zoonotic parasitic disease. Pathologically, it occurs most often in the intestines and the liver, the sites of Schistosoma japonicum egg accumulation. The parasites’ produced eggs cause the main pathology in patients. Deposited parasite eggs in the liver induce the production of multiple cytokines that mediate the immune response, which in turn leads to granulomatous responses and liver fibrosis. These impact the hosts’ quality of life and health status, resulting in severe morbidity and even mortality. In this study, differentially expressed genes (DEGs) between ordinary samples and three 6- week infected mice were mined from microarray analysis based on the limma package. In total, we excavated the differential expression LCN2 was exhibited high expressions profile in GSE59276, GSE61376 demonstrated the result. Furthermore, CIBERSORT suggested detailed analysis of the immune subtype distribution pattern. In vivo experiments like real-time quantitative PCR, immunohistochemical (IHC) staining, and immunofluorescence (IF) demonstrated the expressions of LCN2 was significantly upregulated in S. japonicum–infected mice liver tissues and located in macrophages. Previous studies have shown that macrophages act as the first line of defense during schistosome infection and are an important part of liver granuloma. We used S. japonicum soluble worm antigens (SWA) to induce RAW264.7 cells to construct an in vitro inflammatory model. The current study aimed to investigate whether the NF-κB signaling network is involved in LCN2 upregulation induced by SWA and whether LCN2 can promote M1 polarization of macrophages under SWA treatment. Our research work suggests that LCN2 is significant in the development of early infection caused by S. japonicum and is of great value for further exploration. Collectively, the findings indicated that SWA promoted the expression of LCN2 and promoted M1 polarization of macrophages via the upregulation of NF-κB signaling pathway. Our findings demonstrate that NF-κB/LCN2 is necessary for migration and phagocytosis of M1 macrophages in response to SWA infection. Our study highlights the essential role of NF-κB/LCN2 in early innate immune response to infection.

Ovarian cancer (OV) has become the most lethal gynecological cancer. However, its treatment methods and staging system are far from ideal. In the present study, taking the advantage of large-scale public cohorts, we extracted a list of immune-related prognostic genes that differentially expressed in tumor and normal ovarian tissues. Importantly, an individualized immune-related gene based prognostic model (IPM) for OV patients were developed. Furthermore, we validated our IPM in Gene Expression Omnibus (GEO) repository and compared the immune landscape and pathways between high-risk and low-risk groups. The results of our study can serve as an important model to identify the immune subset of patients and has potential for use in immune therapeutic selection and patient management.

Background: Clear cell renal cell carcinoma (ccRCC) is the most frequent and terminal subtype of RCC. Reliable markers associated with the immune response are not available to predict the prognosis of patients with ccRCC. We exploited the extensive number of ccRCC samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repository to perform a comprehensive analysis of immune-related genes (IRGs).Methods: Based on TCGA data, we incorporated IRGs and their expression profiles of 72 normal and 539 ccRCC samples. Univariate Cox analysis was used to evaluate the relationship between overall survival (OS) and IRGs expression. The Lasso Cox regression model identified prognostic genes used to establish a clinical immune prognostic model. The TF–IRG network was used to study the potential molecular mechanisms of action and properties of ccRCC-specific IRGs. Multivariate Cox analysis established a clinical prognostic model of IRGs.Results: We found a significant correlation among 15 differentially expressed IRGs with the OS of patients with ccRCC. Gene function enrichment analysis showed that these IRGs are significantly associated with response to receptor ligand activity. Lasso Cox regression analysis identified 10 genes with the greatest prognostic value. A clinical prognostic model based on six IRGs, which performed well for predicting prognosis, revealed significant associations of patients' survival with age, sex, stage, tumor, node, and metastasis. Moreover, these findings reflect the infiltration of tumors by various immune cells.Conclusion: We identified six clinically significant IRGs and incorporated them into a clinical prognostic model with great significance for monitoring and predicting prognosis of ccRCC.

There has been an increase in the mortality rate and morbidity of kidney cancer (KC) with kidney renal clear cell carcinoma (KIRC) being the most common subtype of KC. GRAMD1C (GRAM Domain Containing 1C) has not been reported to relate to prognosis and immunotherapy in any cancers. Using bioinformatics methods, we judged the prognostic value of GRAMD1C expression in KIRC and investigated the underlying mechanisms of GRAMD1C affecting the overall survival of KIRC based on data downloaded from The Cancer Genome Atlas (TCGA). The outcome revealed that reduced GRAMD1C expression could be a promising predicting factor of poor prognosis in kidney renal clear cell carcinoma. Meanwhile, GRAMDIC expression was significantly correlated to several tumor-infiltrating immune cells (TIICs), particularly the regulatory T cells (Tregs). Furthermore, GRAMD1C was most significantly associated with the mTOR signaling pathway, RNA degradation, WNT signaling pathway, toll pathway and AKT pathway in KIRC. Thus, GRAMD1C has the potential to become a novel predictor to evaluate prognosis and immune infiltration for KIRC patients.