ABSTRACT
BACKGROUND: This study aimed to identify a series of prognostically relevant immune features by immunophenoscore. Immune features were explored using MRI radiomics features to prediction the overall survival (OS) of lower-grade glioma (LGG) patients and their response to immune checkpoints. METHOD: LGG data were retrieved from TCGA and categorized into training and internal validation datasets. Patients attending the First Affiliated Hospital of Harbin Medical University were included in an external validation cohort. An immunophenoscore-based signature was built to predict malignant potential and response to immune checkpoint inhibitors in LGG patients. In addition, a deep learning neural network prediction model was built for validation of the immunophenoscore-based signature. RESULTS: Immunophenotype-associated mRNA signatures (IMriskScore) for outcome prediction and ICB therapeutic effects in LGG patients were constructed. Deep learning of neural networks based on radiomics showed that MRI radiomic features determined IMriskScore. Enrichment analysis and ssGSEA correlation analysis were performed. Mutations in CIC significantly improved the prognosis of patients in the high IMriskScore group. Therefore, CIC is a potential therapeutic target for patients in the high IMriskScore group. Moreover, IMriskScore is an independent risk factor that can be used clinically to predict LGG patient outcomes. CONCLUSIONS: The IMriskScore model consisting of a sets of biomarkers, can independently predict the prognosis of LGG patients and provides a basis for the development of personalized immunotherapy strategies. In addition, IMriskScore features were predicted by MRI radiomics using a deep learning approach using neural networks. Therefore, they can be used for the prognosis of LGG patients.
ABSTRACT
Soil pollution has become a constraint for the Guangdong-Hong Kong-Macao Greater Bay Area to move toward becoming an international first-class bay area. Learning from the three major bay areas of New York, San Francisco, and Tokyo can provide guidance for alleviating the soil environmental pressure in the Greater Bay Area. Based on the relevant literature in the core database of the Web of Science, the current research status of soil pollution in the three major bay areas was analyzed by using co-citation analysis, keywords co-occurrence analysis, and keyword emergence detection. The results showed that the main research topics of soil pollution in the three major bay areas are focused mainly on the source, spatial distribution of and remediation of soil pollutants, bioavailability of soil pollution and its adverse effects on marine organisms, and the role of the marine biotic index in soil pollution assessment. Hotspots in the study of soil pollutants are concentrated in the areas of organic pollution and heavy metal pollution. Toxicity, imposex, and biomarkers are the hot topics in the related marine biological research. By comparing the research status of soil pollution in bay areas at home and abroad, it was found that the study of soil pollution in China's bay areas started relatively late compared with that in the three major bay areas and that the distributions of research area and subject are unbalanced. The intensity of research on the related marine biological research is relatively low. Therefore, carrying out research on the land-sea integration of Guangdong-Hong Kong-Macao Greater Bay Area is an urgent priority. The research field needs to be extended to the related marine biological research. In this way, the study of soil pollution in the Guangdong-Hong Kong-Macao Greater Bay Area can be improved and the problems of soil pollution can be addressed.
ABSTRACT
AIMS: We aimed to analyze the phenotype of tumor-infiltrating lymphocytes (TILs) and non-tumor infiltrating lymphocytes (NILs) in HCC and non-tumor tissues, and evaluate relationships between changes in these cells and the prognosis of HCC. METHODS: Lymphocytes were isolated from HCC and corresponding non-tumor tissues and tested by flow cytometry. For comparison, clinical parameters were analyzed. RESULTS: Compared with the non-tumor tissue, tumor tissue had a lower intensity of NK, NKT and CD8+T cell infiltration. TILs had higher intensity of CD4+CD25+Foxp3+regulatory T cell (Treg cells) infiltration compared with that in NILs. The prevalence of Treg cells was associated with fewer CD8 + T lymphocytes in the HCC immune microenvironment. The frequencies of NK cells and CD8+T cells in TILs of HCC patients with metastasis less than 12 months were lower than those without metastasis. However, the frequency of Treg cells was higher than those without metastasis. CONCLUSION: These results suggest that the frequencies of CD8+T, NK and NKT cells as well as Treg cells in the tumor tissue of HCC are significantly associated with patient survival, and could be applied as predictive indicators for HCC prognosis.
