Systematic profiling of diagnostic and prognostic value of autophagy-related genes for sarcoma patients.

BACKGROUND: Autophagy-related genes (ARGs) have been confirmed to have an important role in tumorigenesis and tumor microenvironment formation. Nevertheless, a systematic analysis of ARGs and their clinical significance in sarcoma patients is lacking. METHODS: Gene expression files from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx) were used to select differentially expressed genes (DEGs). Differentially expressed ARGs (DEARGs) were determined by matching the DEG and HADb gene sets, which were evaluated by functional enrichment analysis. Unsupervised clustering of the identified DEARGs was conducted, and associations with tumor microenvironment (TME), immune checkpoints, and immune cells were analyzed simultaneously. Two prognostic signatures, one for overall survival (OS) and one for disease-free survival (DFS), were established and validated in an independent set. RESULTS: In total, 84 DEARGs and two clusters were identified. TME scores, five immune checkpoints, and several types of immune cells were found to be significantly different between two clusters. Two prognostic signatures incorporating DEARGs showed favorable discrimination and were successfully validated. Two nomograms combining signature and clinical variables were generated. The C-indexes were 0.818 and 0.747 for the OS and DFS nomograms, respectively. CONCLUSION: This comprehensive analyses of the ARG landscape in sarcoma showed novel ARGs related to carcinogenesis and the immune microenvironment. These findings have implications for prognosis and therapeutic responses, which reveal novel potential prognostic biomarkers, promote precision medicine, and provide potential novel targets for immunotherapy.

Establishment of an Autophagy-Related Clinical Prognosis Model for Predicting the Overall Survival of Osteosarcoma.

PURPOSE: Osteosarcoma is the most common primary and highly invasive bone tumor in children and adolescents. The purpose of this study is to construct a multi-gene expression feature related to autophagy, which can be used to predict the prognosis of patients with osteosarcoma. Materials and methods. The clinical and gene expression data of patients with osteosarcoma were obtained from the target database. Enrichment analysis of autophagy-related genes related to overall survival (OS-related ARGs) screened by univariate Cox regression was used to determine OS-related ARGs function and signal pathway. In addition, the selected OS-related ARGs were incorporated into multivariate Cox regression to construct prognostic signature for the overall survival (OS) of osteosarcoma. Use the dataset obtained from the GEO database to verify the signature. Besides, gene set enrichment analysis (GSEA) were applied to further elucidate the molecular mechanisms. Finally, the nomogram is established by combining the risk signature with the clinical characteristics. RESULTS: Our study eventually included 85 patients. Survival analysis showed that patients with low riskScore had better OS. In addition, 16 genes were included in OS-related ARGs. We also generate a prognosis signature based on two OS-related ARGs. The signature can significantly divide patients into low-risk groups and high-risk groups, and has been verified in the data set of GEO. Subsequently, the riskScore, primary tumor site and metastasis status were identified as independent prognostic factors for OS and a nomogram were generated. The C-index of nomogram is 0.789 (95% CI: 0.703~0.875), ROC curve and calibration chart shows that nomogram has a good consistency between prediction and observation of patients. CONCLUSIONS: ARGs was related to the prognosis of osteosarcoma and can be used as a biomarker of prognosis in patients with osteosarcoma. Nomogram can be used to predict OS of patients and improve treatment strategies.

Identification of Iron Metabolism-Related Gene Signatures for Predicting the Prognosis of Patients With Sarcomas.

Iron is one of the essential trace elements in the human body. An increasing amount of evidence indicates that the imbalance of iron metabolism is related to the occurrence and development of cancer. Here, we obtained the gene expression and clinical data of sarcoma patients from TCGA and the GEO database. The prognostic value of iron metabolism-related genes (IMRGs) in patients with sarcoma and the relationship between these genes and the immune microenvironment were studied by comprehensive bioinformatics analyses. Two signatures based on IMRGs were generated for the overall survival (OS) and disease-free survival (DFS) of sarcoma patients. At 3, 5, and 7 years, the areas under the curve (AUCs) of the OS signature were 0.708, 0.713, and 0.688, respectively. The AUCs of the DFS signature at 3, 5, and 7 years were 0.717, 0.689, and 0.702, respectively. Kaplan-Meier survival analysis indicated that the prognosis of high-risk patients was worse than that of low-risk patients. In addition, immunological analysis showed that there were different patterns of immune cell infiltration among patients in different clusters. Finally, we constructed two nomograms that can be used to predict the OS and DFS of sarcoma patients. The C-index was 0.766 (95% CI: 0.697-0.835) and 0.763 (95% CI: 0.706-0.820) for the OS and DFS nomograms, respectively. Both the ROC curves and the calibration plots showed that the two nomograms have good predictive performance. In summary, we constructed two IMRG-based prognostic models that can effectively predict the OS and DFS of sarcoma patients.

Three newly recorded genera from China (Hymenoptera, Braconidae, Opiinae), with the notes on the genus Neopius and descriptions of three new species.

The genera Bitomoides van Achterberg, 2004, Neopius Gahan, 1917 and Sternaulopius Fischer, 1965 of the subfamily Opiinae are newly discovered in China and one new species of each genus are described and illustrated, viz. Bitomoides platyaulicis Sheng Chen sp. n., Neopius citrinus Sheng Chen, sp. n. and Sternaulopius macrophthalmos Sheng Chen sp. n. The status of the genus Neopius Gahan is discussed.