Prediction of High-Risk Gastrointestinal Stromal Tumor Recurrence Based on Delta-CT Radiomics Modeling: A 3-Year Follow-up Study After Surgery.

Background: Medium- to high-risk classification-gastrointestinal stromal tumors (MH-GIST) have a high recurrence rate and are difficult to treat. This study aims to predict the recurrence of MH-GIST within 3 years after surgery based on clinical data and preoperative Delta-CT Radiomics modeling. Methods: A retrospective analysis was conducted on clinical imaging data of 242 cases confirmed to have MH-GIST after surgery, including 92 cases of recurrence and 150 cases of normal. The training set and test set were established using a 7:3 ratio and time cutoff point. In the training set, multiple prediction models were established based on clinical data of MH-GIST and the changes in radiomics texture of enhanced computed tomography (CT) at different time periods (Delta-CT radiomics). The area under curve (AUC) values of each model were compared using the Delong test, and the clinical net benefit of the model was tested using decision curve analysis (DCA). Then, the model was externally validated in the test set, and a novel nomogram predicting the recurrence of MH-GIST was finally created. Results: Univariate analysis confirmed that tumor volume, tumor location, neutrophil-lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), diabetes, spicy hot pot, CT enhancement mode, and Radscore 1/2 were predictive factors for MH-GIST recurrence (P < .05). The combined model based on these above factors had significantly higher predictive performance (AUC = 0.895, 95% confidence interval [CI] = [0.839-0.937]) than the clinical data model (AUC = 0.735, 95% CI = [0.6 62-0.800]) and radiomics model (AUC = 0.842, 95% CI = [0.779-0.894]). Decision curve analysis also confirmed the higher clinical net benefit of the combined model, and the same results were validated in the test set. The novel nomogram developed based on the combined model helps predict the recurrence of MH-GIST. Conclusions: The nomogram of clinical and Delta-CT radiomics has important clinical value in predicting the recurrence of MH-GIST, providing reliable data reference for its diagnosis, treatment, and clinical decision-making.

Introducing the f0% method: a reliable and accurate approach for qPCR analysis.

BACKGROUND: qPCR is a widely used technique in scientific research as a basic tool in gene expression analysis. Classically, the quantitative endpoint of qPCR is the threshold cycle (CT) that ignores differences in amplification efficiency among many other drawbacks. While other methods have been developed to analyze qPCR results, none has statistically proven to perform better than the CT method. Therefore, we aimed to develop a new qPCR analysis method that overcomes the limitations of the CT method. Our f0% [eff naught percent] method depends on a modified flexible sigmoid function to fit the amplification curve with a linear part to subtract the background noise. Then, the initial fluorescence is estimated and reported as a percentage of the predicted maximum fluorescence (f0%). RESULTS: The performance of the new f0% method was compared against the CT method along with another two outstanding methods-LinRegPCR and Cy0. The comparison regarded absolute and relative quantifications and used 20 dilution curves obtained from 7 different datasets that utilize different DNA-binding dyes. In the case of absolute quantification, f0% reduced CV%, variance, and absolute relative error by 1.66, 2.78, and 1.8 folds relative to CT; and by 1.65, 2.61, and 1.71 folds relative to LinRegPCR, respectively. While, regarding relative quantification, f0% reduced CV% by 1.76, 1.55, and 1.25 folds and variance by 3.13, 2.31, and 1.57 folds regarding CT, LinRegPCR, and Cy0, respectively. Finally, f0% reduced the absolute relative error caused by LinRegPCR by 1.83 folds. CONCLUSIONS: We recommend using the f0% method to analyze and report qPCR results based on its reported advantages. Finally, to simplify the usage of the f0% method, it was implemented in a macro-enabled Excel file with a user manual located on https://github.com/Mahmoud0Gamal/F0-perc/releases .

Selection of Novel Reference Genes by RNA-Seq and Their Evaluation for Normalising Real-Time qPCR Expression Data of Anthocyanin-Related Genes in Lettuce and Wild Relatives.

Lettuce is a popular vegetable source of bioactive compounds, like anthocyanins, powerful antioxidants present in red and semi-red varieties. Selection of reliable reference genes (RGs) for the normalization of real-time quantitative PCR (qPCR) data is crucial to obtain accurate gene expression results. Among the genes with totally unrelated biological functions, six candidate RGs (ADF2, CYB5, iPGAM, SCL13, TRXL3-3, and VHA-H) with low variation in expression according to RNA-seq analyses, were selected for future expression studies of anthocyanin-related genes in three different experiments: leaf colour comparison (green vs. red) in commercial varieties; tissue comparison (leaf vs. stem) in a wild relative; and drought stress experiment in commercial and traditional varieties, and a wild relative. Expression profiles of the candidate RGs were obtained by qPCR and their stability was assessed by four different analytical tools, geNorm, NormFinder, BestKeeper, and Delta Ct method, all integrated in RefFinder. All results considered, we recommend CYB5 to be used as RG for the leaf colour experiment and TRXL3-3 for the tissue and drought stress ones, as they were the most stable genes in each case. RNA-seq is useful to preselect novel RGs although validation by qPCR is still advisable. These results provide helpful information for gene expression studies in Lactuca spp. under the described conditions.

Co-detection of the measles vaccine and wild-type virus by real-time PCR: public health laboratory protocol.

In rare cases vaccination with the measles virus vaccine genotype A (MeVA) may cause a vaccine reaction with clinical signs similar to infection with wild-type measles virus (MeVwt). Rapid differentiation between MeVA and MeVwt infection is important for taking adequate public health measures. Recently, a few MeVA real-time reverse-transcription quantitative PCR methods (RT-qPCRs) were described that can distinguish between MeVA and MeVwt. However, detection of MeVA does in theory not exclude infection with MeVwt. In the present study, we established a protocol for determination of co-infections with MeVA and MeVwt. To this end, MeVA RT-qPCRs were used in combination with the routine measles virus (MeV) RT-qPCR, and the results suggested that the differences between the RT-qPCR Ct values (delta Ct, ∆Ct) could be used as criteria. Subsequently, we tested samples from vaccine-associated measles cases that were confirmed by genotyping. In addition, experimental mixtures of MeVA and MeVwt were tested in different concentrations. All tested MeVA clinical samples had ∆Ct ≤3.6. The results of experimental mixtures showed a mean ∆Ct ≤2.8 for genotype A alone and >3.2 when combined with either genotype B3 or D8. The results of a receiver operator characteristic analysis indicated that the optimum ∆Ct for use as a cut-off value was 3.5, while with ∆Ct values of 2.9 and 3.7 sensitivity and specificity were respectively 1.00. Thus, ∆Ct could be used to exclude the presence of MeVwt if MeVA is detected and ∆Ct is <2.9, while ∆Ct >3.7 were highly suggestive of co-infection and ≥2.9 ∆Ct <3.7 warranted additional confirmation, such as next-generation sequencing. This RT-qPCR-based protocol could be used for the exclusion of infection with MeVwt in cases with vaccine-associated measles reaction, crucial for the timely implementation of public health prevention and control measures.

Identification and validation of reference genes for qRT-PCR based studies in horse gram (Macrotyloma uniflorum).

The quantitative real-time polymerase chain reaction (qRT-PCR) is the most sensitive and commonly used technique for gene expression studies in biological systems. However, the reliability of qRT-PCR results depends on the selection of reference gene(s) for data normalization. Horse gram (Macrotyloma uniflorum) is an important legume crop on which several molecular studies have been reported. However, the stability of reference genes has not been evaluated. In the present study, nine candidate reference genes were identified from horse gram RNA-seq data and evaluated in two horse gram genotypes, HPK4 and HPKM317 under six abiotic stresses viz. cold, drought, salinity, heat, abscisic acid and methyl viologen-induced oxidative stress. The results were evaluated using geNorm, Bestkeeper, Normfinder and delta-delta Ct methods and comprehensive ranking was assigned using RefFinder and RankAggreg software. The overall result showed that TCTP was one of the most stable genes in all samples and in genotype HPK4, while in HPKM317 profilin was most stably expressed. However, PSMA5 was identified as least stable in all the experimental conditions. Expression of target genes dehydrin and early response to dehydration 6 under drought stress was also validated using TCTP and profilin for data normalization, either alone or in combination, which confirmed their suitability for qRT-PCR data normalization. Thus, TCTP and profilin genes may be used for qRT-PCR data normalization for molecular and genomic studies in horse gram. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-021-01104-0.

Pathway Analysis of Selected Circulating miRNAs in Plasma of Breast Cancer Patients: A Preliminary Study.

MicroRNAs in the circulation of breast cancer (BC) patients have great potential for the early diagnosis, treatment and monitoring of breast cancer. The aim of this preliminary study was to obtain the expression profile of selected miRNAs in the plasma of BC patients that could discriminate BC patients from healthy volunteers and may be useful in early detection of BC. Significantly deregulated miRNAs were evaluated by pathway analysis with the prediction of potential miRNA targets. The study enrolled plasma samples from 65 BC patients and 34 healthy volunteers. Selected miRNAs were screened in pilot testing by the real-time PCR (qPCR) method, and the most appropriate reference genes were selected for normalisation by the geNorm algorithm. In the final testing, we detected miR-99a, miR-130a, miR-484 and miR-1260a (p < 0.05) as significantly up-regulated in the plasma of BC patients. Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis revealed that all significantly deregulated miRNAs are involved in the Hippo and Transforming Growth Factor-beta (TGF-beta) signalling pathways. Our study confirmed a different profile of selected circulating miRNAs in the plasma of BC patients with an emphasis on some critical points in the analysis process.

A tissue-based approach to selection of reference genes for quantitative real-time PCR in a sheep osteoporosis model.

BACKGROUND: In order to better understand the multifactorial nature of osteoporosis, animal models are utilized and compared to healthy controls. Female sheep are well established as a model for osteoporosis induced by ovariectomy, calcium and vitamin D low diet, application of steroids, or a combination of these treatments. Transcriptional studies can be performed by applying quantitative real time PCR (RT-qPCR). RT-qPCR estimates mRNA-levels of target genes in relation to reference genes. A chosen set of reference genes should not show variation under experimental conditions. Currently, no standard reference genes are accepted for all tissue types and experimental conditions. Studies examining reference genes for sheep are rare and only one study described stable reference in mandibular bone. However, this type of bone differs from trabecular bone where most osteoporotic fractures occur. The present study aimed at identifying a set of reference genes for relative quantification of transcriptional activity of ovine spine bone and ovine in vitro differentiated mesenchymal stromal cells (MSC) for reliable comparability. METHODS: Twelve candidate reference genes belonging to different functional classes were selected and their expression was measured from cultured ovMSCs (n = 18) and ovine bone samples (n = 16), respectively. RefFinder was used to rank the candidate genes. RESULTS: We identified B2M, GAPDH, RPL19 and YWHAZ as the best combination of reference genes for normalization of RT-qPCR results for transcriptional analyses of these ovine samples. CONCLUSION: This study demonstrates the importance of applying a set of reference genes for RT-qPCR analysis in sheep. Based on our data we recommend using four identified reference genes for relative quantification of gene expression studies in ovine bone or for in vitro experiments with osteogenically differentiated ovine MSCs.

Leukocyte Dynamics Influence Reference Gene Stability in Whole Blood: Data-Driven qRT-PCR Normalization Is a Robust Alternative for Measurement of Transcriptional Biomarkers.

BACKGROUND: The use of reference genes for normalization of whole blood qRT-PCR data may be problematic in conditions such as stroke which induce alterations in white blood cell differential. In this study, we assessed the influence of stroke on the stability of commonly employed reference genes, and we evaluated data-driven normalization as an alternative. METHODS: Peripheral whole blood was sampled from 33 stroke patients and 29 controls, and qRT-PCR was used to measure the expression levels of 10 target genes whose transcripts are known stroke biomarkers. Target gene expression levels were normalized via those of 2 frequently cited reference genes (ACTB and B2M) as well as with the NORMA-Gene data-driven normalization algorithm. RESULTS: Whole blood expression levels of reference genes were significantly altered in stroke patients relative to controls. In comparison to normalization via reference genes, NORMA-Gene produced more robust target gene expression data in terms of differential expression dynamics, variance properties, and diagnostic performance. CONCLUSIONS: Our findings suggest that whole blood expression levels of commonly used reference genes may be sensitive to changes in white blood cell differential, and that data-driven qRT-PCR normalization approaches offer a powerful alternative.

Estimating marginal properties of quantitative real-time PCR data using nonlinear mixed models.

A unified modeling framework based on a set of nonlinear mixed models is proposed for flexible modeling of gene expression in real-time PCR experiments. Focus is on estimating the marginal or population-based derived parameters: cycle thresholds and ΔΔc(t), but retaining the conditional mixed model structure to adequately reflect the experimental design. Additionally, the calculation of model-average estimates allows incorporation of the model selection uncertainty. The methodology is applied for estimating the differential expression of a phosphate transporter gene OsPT6 in rice in comparison to a reference gene at several states after phosphate resupply. In a small simulation study the performance of the proposed method is evaluated and compared to a standard method.

Human apolipoprotein E4 modulates the expression of Pin1, Sirtuin 1, and Presenilin 1 in brain regions of targeted replacement apoE mice.

The apolipoprotein E4 (apoE4) allele is consistently associated with increased risk for Alzheimer's disease (AD). We investigated the molecular mechanism of this susceptibility by analyzing the levels of genes involved in AD pathogenesis in transgenic mice expressing human apoE3 or apoE4 isoforms. mRNA and protein levels of Pin1, Sirtuin 1 (Sirt1), Presenilin 1 (PS1), and pro-Brain-derived Neurotrophic Factor (BDNF) were analyzed in brain regions affected by neuropathological changes in AD. Pin1 mRNA was significantly higher in the hippocampus of apoE4 mice than in apoE3 controls, whereas lower expression was detected in the entorhinal and parietal cortices. Reduced Pin1 levels may increase neurofibrillary degeneration and amyloidogenic processes, while compensatory mechanisms may take place in the hippocampus to balance spatial memory deficits. Sirt1 levels were significantly reduced in the frontal cortex of apoE4 mice. Sirt1 reduction may hinder its protective role against the formation of plaques and tangles and diminish its anti-inflammatory actions. Sirt1 decrease may also play a role in apoE4-associated memory impairments. Moreover, in apoE4 mice PS1 mRNA levels were lower in the frontal cortex. Lower PS1 expression may hamper γ-secretase function, thus affecting amyloid precursor protein processing. Pro-BDNF mRNA levels did not differ between apoE3 and apoE4 mice in any region analyzed. This study showed dysregulated expression of Pin1, Sirt1, and PS1 genes in different cerebral areas of apoE4 mice, suggesting that these changes may play a role in the mechanism of AD vulnerability.

MicroRNAs-449a and -449b exhibit tumor suppressive effects in retinoblastoma.

Retinoblastoma is the most common pediatric cancer of the eye. Currently, the chemotherapeutic treatments for retinoblastoma are broad-based drugs such as vincristine, carboplatin, or etoposide. However, therapies targeted directly to aberrant signaling pathways may provide more effective therapy for this disease. The purpose of our study is to illustrate the relationship between the expressions of miRs-449a and -449b to retinoblastoma proliferation and apoptosis. We are the first to confirm an inhibitory effect of miR-449a and -449b in retinoblastoma by demonstrating significantly impaired proliferation and increased apoptosis of tumor cells when these miRNAs are overexpressed. This study suggests that these miRNAs could serve as viable therapeutic targets for retinoblastoma treatment.