ABSTRACT
BACKGROUND: The most prevalent mesenchymal-derived gastrointestinal cancers are gastric stromal tumors (GSTs), which have the highest incidence (60-70%) of all gastrointestinal stromal tumors (GISTs). However, simple and effective diagnostic and screening methods for GST remain a great challenge at home and abroad. This study aimed to build a GST early warning system based on a combination of machine learning algorithms and routine blood, biochemical and tumour marker indicators. METHODS: In total, 697 complete samples were collected from four hospitals in Gansu Province, including 42 blood indicators from 318 pretreatment GST patients, 180 samples of gastric polyps and 199 healthy individuals. In this study, three algorithms, gradient boosting machine (GBM), random forest (RF), and logistic regression (LR), were chosen to build GST prediction models for comparison. The performance and stability of the models were evaluated using two different validation techniques: 5-fold cross-validation and external validation. The DeLong test assesses significant differences in AUC values by comparing different ROC curves, the variance and covariance of the AUC value. RESULTS: The AUC values of both the GBM and RF models were higher than those of the LR model, and this difference was statistically significant (P < 0.05). The GBM model was considered to be the optimal model, as a larger area was enclosed by the ROC curve, and the axes indicated robust model classification performance according to the accepted model discriminant. Finally, the integration of 8 top-ranked blood indices was proven to be able to distinguish GST from gastric polyps and healthy people with sensitivity, specificity and area under the curve of 0.941, 0.807 and 0.951 for the cross-validation set, respectively. CONCLUSION: The GBM demonstrated powerful classification performance and was able to rapidly distinguish GST patients from gastric polyps and healthy individuals. This identification system not only provides an innovative strategy for the diagnosis of GST but also enables the exploration of hidden associations between blood parameters and GST for subsequent studies on the prevention and disease surveillance management of GST. The GST discrimination system is available online for free testing of doctors and high-risk groups at https://jzlyc.gsyy.cn/bear/mobile/index.html .
Subject(s)
Algorithms , Neoplasms , Humans , Biopsy , Biomarkers, Tumor , Disease ManagementABSTRACT
Objective: We conducted a meta-analysis to evaluate the relationship between circulating tumor cells (CTC) and the prognosis of patients with gastric cancer. Materials and methods: The cohort studies reporting on the relationship between CTC and prognosis of gastric cancer were collected from Pubmed, Cochrane, Embase, CNKI, WanFang Data, and VIP databases. The two researchers independently screened the literature, extracted the data, and evaluated the bias risk of the included literature. The data were analyzed by Revman software (Review Manager version 5.4). Result: A total of 14 retrospective cohort studies with 1053 patients were included. The results showed that the overall survival time (OS) and progression-free survival time (PFS) of CTC-positive patients were shorter compared to CTC-negative patients. Taking into consideration the critical value of CTC positive patients, country of origin, sample size, treatment mode, and study time, the subgroup analysis showed that CTC-positive was related to the shortening of OS in patients with gastric cancer. Based on the subgroup analysis of the factors such as CTC positive critical value < 2.8, sample size ≥ 75, mixed therapy, longer study duration, country, and immunofluorescence detection of CTC, it was found that OS in CTC positive group was shorter than that in CTC-negative group (all P<0.05), while the critical value of positive CTC ≥ 2.8, sample size ≥ 75, choice of treatment only for operation or non-operation, short study time and molecular detection of CTC were not associated with OS (all P>0.05). In addition, CTC-positive patients had a more advanced TNM staging, poorer tumor differentiation, and earlier distant metastasis. Conclusion: CTC can be used as a prognostic indicator of gastric cancer. Gastric cancer patients with positive CTC may have a poorer prognosis compared to those with CTC-negative tumors. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022323155.
ABSTRACT
Acer miaotaiense P. C. Tsoong is a rare and endangered tree endemic to the Qinling Mountains of China and is listed as a national third-class protected plant. In this study, we sequenced the complete mitochondrial genome of Acer miaotaiense using the Illumina Novaseq 6000 and Nanopore platforms. The total mitochondrial genome length is 819,227 bp and has 69 genes, including 41 protein-coding, 25 tRNA, and 3 rRNA genes. The genome nucleotide composition was asymmetric, with an overall G + C content of 45.7%. Phylogenetic analysis indicated that Acer miaotaiense is closely related to the congeneric Acer yangbiense.
ABSTRACT
Quercus acutissima Carruth. is a Chinese important energy plant with high ecological and economic values. While the species chloroplast genome has been reported, its mitochondrial genome (mitogenome) is still unexplored. Here, we assembled and annotated the Q. acutissima mitogenome, and we compared its characteristic differences with several closely related species. The Q. acutissima mitogenome's main structure is branched with three distinguished contigs (linear molecule 1, circular molecule 2, and circular molecule 3) with 448,982 bp total length and 45.72% GC content. The mitogenome contained 51 genes, including 32 protein-coding, 16 tRNA and 3 rRNA genes. We examined codon usage, repeated sequences, genome recombination, chloroplast to mitochondrion DNA transformation, RNA editing, and synteny in the Q. acutissima mitogenome. Phylogenetic trees based on 29 species mitogenomes clarified the species classification. Our results provided comprehensive information of Q. acutissima mitogenome, and they are expected to provide valuable information for Fagaceae evolutionary biology and to promote the species germplasm utilization.
