Identification and validation of novel biomarkers associated with immune infiltration for the diagnosis of osteosarcoma based on machine learning

Objectives: Osteosarcoma is the most common primary malignant tumor in children and adolescents, and the 5-year survival of osteosarcoma patients gained no substantial improvement over the past decades. Effective biomarkers in diagnosing osteosarcoma are warranted to be developed. This study aims to explore novel biomarkers correlated with immune cell infiltration in the development and diagnosis of osteosarcoma.Methods: Three datasets (GSE19276, GSE36001, GSE126209) comprising osteosarcoma samples were extracted from Gene Expression Omnibus (GEO) database and merged to obtain the gene expression. Then, differentially expressed genes (DEGs) were identified by limma and potential biological functions and downstream pathways enrichment analysis of DEGs was performed. The machine learning algorithms LASSO regression model and SVM-RFE (support vector machine-recursive feature elimination) analysis were employed to identify candidate hub genes for diagnosing patients with osteosarcoma. Receiver operating characteristic (ROC) curves were developed to evaluate the discriminatory abilities of these candidates in both training and test sets. Furthermore, the characteristics of immune cell infiltration in osteosarcoma, and the correlations between these potential genes and immune cell abundance were illustrated using CIBERSORT. qRT-PCR and western blots were conducted to validate the expression of diagnostic candidates.Results: GEO datasets were divided into the training (merged GSE19276, GSE36001) and test (GSE126209) groups. A total of 71 DEGs were screened out in the training set, including 10 upregulated genes and 61 downregulated genes. These DEGs were primarily enriched in immune-related biological functions and signaling pathways. After machine learning by SVM-RFE and LASSO regression model, four biomarkers were chosen for the diagnostic nomogram for osteosarcoma, including ASNS, CD70, SRGN, and TRIB3. These diagnostic biomarkers all possessed high diagnostic values (AUC ranging from 0.900 to 0.955). Furthermore, these genes were significantly correlated with the infiltration of several immune cells, such as monocytes, macrophages M0, and neutrophils.Conclusion: Four immune-related candidate hub genes (ASNS, CD70, SRGN, TRIB3) with high diagnostic value were confirmed for osteosarcoma patients. These diagnostic genes were significantly connected with the immune cell abundance, suggesting their critical roles in the osteosarcoma tumor immune microenvironment. Our study provides highlights on novel diagnostic candidate genes with high accuracy for diagnosing osteosarcoma patients

Pulmonary infection associated with immune dysfunction is associated with poor prognosis in patients with myelodysplastic syndrome accompanied by TP53 abnormalities

The aim of this study was to examine the characteristics and prognosis of patients with myelodysplastic syndrome (MDS) accompanied by TP53 abnormalities and explore potential prognostic factors and treatment responses. This retrospective analysis included 95 patients with MDS and TP53 abnormalities and 173 patients with MDS without TP53 abnormalities at the Fujian Medical University Union Hospital between January 2016 and June 2023. Among patients with TP53 abnormalities, 26 (27.4%) developed AML during the disease course, with a median transformation time of 5.7 months. Complex karyotypes were observed in 73.1% of patients, and the proportions of -5 or del(5q), -7 or del(7q), +8, and -20 or del(20q) were 81.8%, 54.5%, 30.7%, and 25.0%, respectively. These patients exhibited poor survival, with a median overall survival (OS) of 7.3 months, and had 1- and 2-year OS rates of 42.2% and 21.5%, respectively. The complete response rates for azacitidine monotherapy, venetoclax combined with azacitidine, decitabine monotherapy, and decitabine combined with low-dose chemotherapy were 9.1%, 41.7%, 37.5%, and 33.3%, respectively. Long-term survival was similar among the four treatment groups. Patients who underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT) had a median OS of 21.3 months, which trended to be longer than that of patients who did not undergo allo-HSCT (5.6 months; P = 0.1449). Patients with pulmonary infection at diagnosis experienced worse OS than those without pulmonary infection (2.3 months vs. 15.4 months; P < 0.0001). Moreover, 61.9% of patients with pulmonary infection had immune dysfunction, with a ratio of CD4+ to CD8+ T lymphocytes below two. Pulmonary infections and complex karyotypes were independent adverse prognostic factors for OS. In conclusion, TP53 abnormalities in patients with MDS were frequently accompanied by complex karyotypes, and treatments based on hypomethylating agents or venetoclax have limited efficacy. Pulmonary infections associated with immune dysfunction is associated with poor prognosis

Combining Multiple Algorithms for Road Network Tracking from Multiple Source Remotely Sensed Imagery: a Practical System and Performance Evaluation

In light of the increasing availability of commercial high-resolution imaging sensors, automatic interpretation tools are needed to extract road features. Currently, many approaches for road extraction are available, but it is acknowledged that there is no single method that would be successful in extracting all types of roads from any remotely sensed imagery. In this paper, a novel classification of roads is proposed, based on both the roads' geometrical, radiometric properties and the characteristics of the sensors. Subsequently, a general road tracking framework is proposed, and one or more suitable road trackers are designed or combined for each type of roads. Extensive experiments are performed to extract roads from aerial/satellite imagery, and the results show that a combination strategy can automatically extract more than 60% of the total roads from very high resolution imagery such as QuickBird and DMC images, with a time-saving of approximately 20%, and acceptable spatial accuracy. It is proven that a combination of multiple algorithms is more reliable, more efficient and more robust for extracting road networks from multiple-source remotely sensed imagery than the individual algorithms

Ferroptosis-related gene HIC1 in the prediction of the prognosis and immunotherapeutic efficacy with immunological activity

BackgroundHypermethylated in Cancer 1 (HIC1) was originally confirmed as a tumor suppressor and has been found to be hypermethylated in human cancers. Although growing evidence has supported the critical roles of HIC1 in cancer initiation and development, its roles in tumor immune microenvironment and immunotherapy are still unclear, and no comprehensive pan-cancer analysis of HIC1 has been conducted.MethodsHIC1 expression in pan-cancer, and differential HIC1 expression between tumor and normal samples were investigated. Immunohistochemistry (IHC) was employed to validate HIC1 expression in different cancers by our clinical cohorts, including lung cancer, sarcoma (SARC), breast cancer, and kidney renal clear cell carcinoma (KIRC). The prognostic value of HIC1 was illustrated by Kaplan-Meier curves and univariate Cox analysis, followed by the genetic alteration analysis of HIC1 in pan-cancer. Gene Set Enrichment Analysis (GSEA) was conducted to illustrate the signaling pathways and biological functions of HIC1. The correlations between HIC1 and tumor mutation burden (TMB), microsatellite instability (MSI), and the immunotherapy efficacy of PD-1/PD-L1 inhibitors were analyzed by Spearman correlation analysis. Drug sensitivity analysis of HIC1 was performed by extracting data from the CellMiner™ database.ResultsHIC1 expression was abnormally expressed in most cancers, and remarkable associations between HIC1 expression and prognostic outcomes of patients in pan-cancer were detected. HIC1 was significantly correlated with T cells, macrophages, and mast cell infiltration in different cancers. Moreover, GSEA revealed that HIC1 was significantly involved in immune-related biological functions and signaling pathways. There was a close relationship of HIC1 with TMB and MSI in different cancers. Furthermore, the most exciting finding was that HIC1 expression was significantly correlated with the response to PD-1/PD-L1 inhibitors in cancer treatment. We also found that HIC1 was significantly correlated with the sensitivity of several anti-cancer drugs, such as axitinib, batracylin, and nelarabine. Finally, our clinical cohorts further validated the expression pattern of HIC1 in cancers.ConclusionsOur investigation provided an integrative understanding of the clinicopathological significance and functional roles of HIC1 in pan-cancer. Our findings suggested that HIC1 can function as a potential biomarker for predicting the prognosis, immunotherapy efficacy, and drug sensitivity with immunological activity in cancers

Comparative genomics and phylogenomics of the genus Glycyrrhiza (Fabaceae) based on chloroplast genomes

Glycyrrhiza (Fabaceae) species are rich in metabolites and widely used in medicine. Research on the chloroplast genome of Glycyrrhiza is important for understanding its phylogenetics, biogeography, genetic diversity, species identification, and medicinal properties. In this study, comparative genomics and phylogenomics of Glycyrrhiza were analyzed based on the chloroplast genome. The chloroplast genomes of six Glycyrrhiza species were obtained using various assembly and annotation tools. The final assembled chloroplast genome sizes for the six Glycyrrhiza species ranged from 126,380 bp to 129,115 bp, with a total of 109–110 genes annotated. Comparative genomics results showed that the chloroplast genomes of Glycyrrhiza showed typically lacking inverted repeat regions, and the genome length, structure, GC content, codon usage, and gene distribution were highly similar. Bioinformatics analysis revealed the presence of 69–96 simple sequence repeats and 61–138 long repeats in the chloroplast genomes. Combining the results of mVISTA and nucleotide diversity, four highly variable regions were screened for species identification and relationship studies. Selection pressure analysis indicated overall purifying selection in the chloroplast genomes of Glycyrrhiza, with a few positively selected genes potentially linked to environmental adaptation. Phylogenetic analyses involving all tribes of Fabaceae with published chloroplast genomes elucidated the evolutionary relationships, and divergence time estimation estimated the chronological order of species differentiations within the Fabaceae family. The results of phylogenetic analysis indicated that species from the six subfamilies formed distinct clusters, consistent with the classification scheme of the six subfamilies. In addition, the inverted repeat-lacking clade in the subfamily Papilionoideae clustered together, and it was the last to differentiate. Co-linear analysis confirmed the conserved nature of Glycyrrhiza chloroplast genomes, and instances of gene rearrangements and inversions were observed in the subfamily Papilionoideae

Clinical M2 Macrophage-Related Genes Can Serve as a Reliable Predictor of Lung Adenocarcinoma

BackgroundNumerous studies have found that infiltrating M2 macrophages play an important role in the tumor progression of lung adenocarcinoma (LUAD). However, the roles of M2 macrophage infiltration and M2 macrophage-related genes in immunotherapy and clinical outcomes remain obscure.MethodsSample information was extracted from TCGA and GEO databases. The TIME landscape was revealed using the CIBERSORT algorithm. Weighted gene co-expression network analysis (WGCNA) was used to find M2 macrophage-related gene modules. Through univariate Cox regression, lasso regression analysis, and multivariate Cox regression, the genes strongly associated with the prognosis of LUAD were screened out. Risk score (RS) was calculated, and all samples were divided into high-risk group (HRG) and low-risk group (LRG) according to the median RS. External validation of RS was performed using GSE68571 data information. Prognostic nomogram based on risk signatures and other clinical information were constructed and validated with calibration curves. Potential associations of tumor mutational burden (TMB) and risk signatures were analyzed. Finally, the potential association of risk signatures with chemotherapy efficacy was investigated using the pRRophetic algorithm.ResultsBased on 504 samples extracted from TCGA database, 183 core genes were identified using WGCNA. Through a series of screening, two M2 macrophage-related genes (GRIA1 and CLEC3B) strongly correlated with LUAD prognosis were finally selected. RS was calculated, and prognostic risk nomogram including gender, age, T, N, M stage, clinical stage, and RS were constructed. The calibration curve shows that our constructed model has good performance. HRG patients were suitable for new ICI immunotherapy, while LRG was more suitable for CTLA4-immunosuppressive therapy alone. The half-maximal inhibitory concentrations (IC50) of the four chemotherapeutic drugs (metformin, cisplatin, paclitaxel, and gemcitabine) showed significant differences in HRG/LRG.ConclusionsIn conclusion, a comprehensive analysis of the role of M2 macrophages in tumor progression will help predict prognosis and facilitate the advancement of therapeutic techniques

Author Correction: Discovery of 42 genome-wide significant loci associated with dyslexia

Correction to: Nature Genetics https://doi.org/10.1038/s41588-022-01192-y. Published online 20 October 2022. In the version of this article originally published, a paragraph was omitted in the Methods section, reading “Genomic control. Top SNPs are reported from the more conservative GWAS results adjusted for genomic control (Fig. 1, Extended Data Figs. 1–4, and Supplementary Tables 1, 2, 9 and 10), whereas downstream analyses (including gene-set analysis, enrichment and heritability partitioning, genetic correlations, polygenic prediction, candidate gene replication) are based on GWAS results without genomic control.” The paragraph has now been included in the HTML and PDF versions of the article

Expression of key ion transporters in the gill and esophageal- gastrointestinal tract of euryhaline mozambique tilapia oreochromis mossambicus acclimated to fresh water, seawater and hypersaline water

10.1371/journal.pone.0087591PLoS ONE91-POLN

Structure and evolutionary origin of Ca2+-dependent herring type II antifreeze protein

10.1371/journal.pone.0000548PLoS ONE26

An Integrated High-density Linkage Map of Soybean with RFLP, SSR, STS, and AFLP Markers Using A Single F2 Population

Soybean [Glycine max (L.) Merrill] is the most important leguminous crop in the world due to its high contents of high-quality protein and oil for human and animal consumption as well as for industrial uses. An accurate and saturated genetic linkage map of soybean is an essential tool for studies on modern soybean genomics. In order to update the linkage map of a F2 population derived from a cross between Misuzudaizu and Moshidou Gong 503 and to make it more informative and useful to the soybean genome research community, a total of 318 AFLP, 121 SSR, 108 RFLP, and 126 STS markers were newly developed and integrated into the framework of the previously described linkage map. The updated genetic map is composed of 509 RFLP, 318 SSR, 318 AFLP, 97 AFLP-derived STS, 29 BAC-end or EST-derived STS, 1 RAPD, and five morphological markers, covering a map distance of 3080 cM (Kosambi function) in 20 linkage groups (LGs). To our knowledge, this is presently the densest linkage map developed from a single F2 population in soybean. The average intermarker distance was reduced to 2.41 from 5.78 cM in the earlier version of the linkage map. Most SSR and RFLP markers were relatively evenly distributed among different LGs in contrast to the moderately clustered AFLP markers. The number of gaps of more than 25 cM was reduced to 6 from 19 in the earlier version of the linkage map. The coverage of the linkage map was extended since 17 markers were mapped beyond the distal ends of the previous linkage map. In particular, 17 markers were tagged in a 5.7 cM interval between CE47M5a and Satt100 on LG C2, where several important QTLs were clustered. This newly updated soybean linkage map will enable to streamline positional cloning of agronomically important trait locus genes, and promote the development of physical maps, genome sequencing, and other genomic research activities