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Approximately 50% of colorectal cancer (CRC) patients would develop metastasis with poor prognosis, therefore, it is necessary to effectively predict metastasis in clinical treatment. In this study, we aimed to establish a machine-learning model for predicting metastasis in CRC patients by considering radiomics and transcriptomics simultaneously. Here, 1023 patients with CRC from three centers were collected and divided into five queues (Dazhou Central Hospital n  = 517, Nanchong Central Hospital n  = 120 and the Cancer Genome Atlas (TCGA) n  = 386). A total of 854 radiomics features were extracted from tumor lesions on CT images, and 217 differentially expressed genes were obtained from non-metastasis and metastasis tumor tissues using RNA sequencing. Based on radiotranscriptomic (RT) analysis, a novel RT model was developed and verified through genetic algorithms (GA). Interleukin (IL)-26, a biomarker in RT model, was verified for its biological function in CRC metastasis. Furthermore, 15 radiomics variables were screened through stepwise regression, which was highly correlated with the IL26 expression level. Finally, a radiomics model (RA) was established by combining GA and stepwise regression analysis with radiomics features. The RA model exhibited favorable discriminatory ability and accuracy for metastasis prediction in two independent verification cohorts. We designed multicenter, multi-scale cohorts to construct and verify novel combined radiomics and genomics models for predicting metastasis in CRC. Overall, RT model and RA model might help clinicians in directing personalized diagnosis and therapeutic regimen selection for patients with CRC. [ABSTRACT FROM AUTHOR]

In traditional Chinese medicine, Angelica dahurica is a valuable herb with numerous therapeutic applications for a range of ailments. There have not yet been any articles on the methodical assessment and choice of the best reference genes for A. dahurica gene expression studies. Real-time quantitative PCR (RT-qPCR) is widely employed as the predominant method for investigating gene expression. In order to ensure the precise determination of target gene expression outcomes in RT-qPCR analysis, it is imperative to employ stable reference genes. In this study, a total of 11 candidate reference genes including SAND family protein (SAND), polypyrimidine tract-binding protein (PTBP), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), actin (ACT), TIP41-like protein (TIP41), cyclophilin 2 (CYP2), elongation factor 1 α (EF1α), ubiquitin-protein ligase 9 (UBC9), tubulin β-6 (TUB6), thioredoxin-like protein YLS8 (YLS8), and tubulin-α (TUBA) were selected from the transcriptome of A. dahurica. Subsequently, three statistical algorithms (geNorm, NormFinder, and BestKeeper) were employed to assess the stability of their expression patterns across seven distinct stimulus treatments. The outcomes obtained from these analyses were subsequently amalgamated into a comprehensive ranking using RefFinder. Additionally, one target gene, phenylalanine ammonia-lyase (PAL), was used to confirm the effectiveness of the selected reference genes. According to the findings of this study, the two most stable reference genes for normalizing the expression of genes in A. dahurica are TIP41 and UBC9. Overall, our research has determined the appropriate reference genes for RT-qPCR in A. dahurica and provides a crucial foundation for gene screening and identifying genes associated with the biosynthesis of active ingredients in A. dahurica. [ABSTRACT FROM AUTHOR]

Background: It is well-established that biochemical recurrence is detrimental to prostate cancer (PCa). In the present study, we explored the mechanisms underlying PCa progression. Methods: Five cohorts from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases were used to perform gene set variation analysis (GSVA) between nonrecurrent and recurrent PCa patients. We obtained the intersection of pathway enrichment results and extracted the corresponding gene list. LASSO Cox regression analysis was used to identify recurrence-free survival (RFS)-related significant genes and establish an RFS prediction gene signature and nomogram. MTT and colony formation assays were conducted to validate our findings. Results: The E2F signaling pathway was activated in recurrent PCa patients compared to nonrecurrent patients. We established an E2F-related gene signature for RFS prediction based on the four identified E2F-related genes (CDKN2C, CDKN3, RACGAP1, and RRM2) using LASSO Cox regression in the Memorial Sloan Kettering Cancer Center (MSKCC) cohort. The risk score of each patient in MSKCC was calculated based on the expression levels of CDKN2C, CDKN3, RACGAP1, and RRM2. PCa patients with low-risk scores exhibited higher RFS than those with high-risk scores. Receiver operating characteristic (ROC) curve analysis validated the good performance and prognostic accuracy of the E2F-related gene signature, which was validated in the TCGA-prostate adenocarcinoma (TCGA-PRAD) cohort. Compared to patients with low Gleason scores and early T stages, PCa patients with high Gleason scores and advanced T stages had high-risk scores. Moreover, the E2F-related gene signature-based nomogram yielded good performance in RFS prediction. Functional experiments further confirmed these results. Conclusions: The E2F signaling pathway is associated with biochemical recurrence in PCa. Our established E2F-related gene signature and nomogram yielded good accuracy in predicting the biochemical recurrence in PCa. [ABSTRACT FROM AUTHOR]

Objective. The aim of the study is to explore the relationship between lymphatic metastasis genes, prognosis, and immune cell infiltration in patients with colon cancer. Methods. Based on the Cancer Genome Atlas Program (TCGA) database, differentially expressed genes and prognostic genes related to colon adenocarcinoma (COAD) lymphatic metastasis were screened and intersected. We used lasso and univariate Cox regression analysis to screen core genes and establish a preliminary prediction model. GO and KEGG enrichment analysis was used for lymphatic metastasis-related genes, and single GSEA was used for the final screening results. Finally, we evaluated the relationship between identified genes and immune cell infiltration. Results. A total of 1727 genes were differentially expressed between COAD patients with TNM stages of N0 and N1. After further screening, six core genes (RNU4-2, ZNF556, RNVU1-15, NSA2P6, RN7SL767P, and RN7SL473P) were obtained, and a preliminary prediction model was established, in which ZNF556 was a risk factor, and the rest were protective factors. Single GSEA showed that pathways such as systemic lupus erythematosus might play an important role in the initial lymphatic metastasis of COAD. GO and KEGG enrichment analysis of 1727 genes supported this result. Immune infiltration analysis showed that six genes were significantly correlated with T cell and NK cell families. Conclusion. Six core genes may affect COAD initial lymphatic metastasis through the systemic lupus erythematosus pathway and immune cell infiltration. [ABSTRACT FROM AUTHOR]

Aim: We aimed to explore a new approach and theoretical basis for the diagnosis, treatment and prognosis of pre‐eclampsia. Methods: In total, 103 pre‐eclamptic patients (study group: SG) and 100 healthy pregnant women (control group: CG) were enrolled. Reverse transcription quantitative polymerase chain reaction (RT‐qPCR) was used to detect the expression level of serum Hoxb3. Enzyme‐linked immunosorbent assay was used to detect the content of serum sFlt‐1. Pregnancy outcomes in the two groups were recorded, and the correlations of the levels of Hoxb3 and sFlt‐1 with the pregnancy outcomes were analyzed. Results: The relative expression of serum Hoxb3 mRNA in the CG was significantly higher than that in the SG, whereas the content of serum sFlt‐1 in the CG was significantly lower than that in the SG. Compared with the CG, the SG had a significantly lower number of spontaneous deliveries, higher number of cesarean deliveries and significantly higher number of uneventful perinatal births. The incidences of intrauterine growth restriction, intrauterine distress, premature infants and neonatal deaths in perinatal infants in the SG were significantly higher than those in the CG. According to the analysis of receiver operating characteristic curves, the areas under the curves of Hoxb3, sFlt‐1 and their combined detection for diagnosing pre‐eclampsia were 0.799, 0.856 and 0.930, respectively. The areas under the curves for predicting poor perinatal outcomes were 0.724, 0.828 and 0.871, respectively. Conclusion: In conclusion, Hoxb3 and sFlt‐1 have certain reference significance for the risk evaluation of pre‐eclampsia and the adverse pregnancy outcomes of pre‐eclampsia women. [ABSTRACT FROM AUTHOR]

Background: Individualized therapeutic regimen is a recently intensively pursued approach for targeting diseases, in which the search for biomarkers was considered the first and most important. Thus, the goal of this study was to investigate whether the UGT1A1, ERCC1, BRCA1, TYMS, RRM1, TUBB3, STMN1 and TOP2A genes are underlying biomarkers for gastric cancer, which, to our knowledge, has not been performed.Methods: Ninety-eight tissue specimens were collected from gastric cancer patients between May 2012 and March 2015. A multiplex branched DNA liquidchip technology was used for measuring the mRNA expressions of ERCC1, BRCA1, TYMS, RRM1, TUBB3, STMN1 and TOP2A. Direct sequencing was performed for determination of UGT1A1 polymorphisms. Furthermore, correlations between gene expressions, polymorphisms and clinicopathological characteristics were investigated.Results: The expressions of TYMS, TUBB3 and STMN1 were significantly associated with the clinicopathological characteristics of age, gender and family history of gastric cancer, but not with differentiation, growth patterns, metastasis and TNM staging in patients with gastric cancer. No clinical characteristics were correlated with the expressions of ERCC1, BRCA1, RRM1 and TOP2A. Additionally, patients carrying G allele at -211 of UGT1A1 were predisposed to developing tubular adenocarcinoma, while individuals carrying 6TAA or G allele respectively at *28 or -3156 of UGT1A1 tended to have a local invasion.Conclusions: The UGT1A1 polymorphism may be useful to screen the risk population of gastric cancer, while TYMS, TUBB3 and STMN1 may be potential biomarkers for prognosis and chemotherapy guidance. [ABSTRACT FROM AUTHOR]