A cost‐effective approach to factor assay calibration using a truncated live calibration curve

Guy, Susan; Sermon-Cadd, Anne M; Shepherd, Fiona; Kitchen, Steve; Bowyer, Annette

doi:10.1111/ijlh.13087

Cited by 5 publications

(6 citation statements)

References 8 publications

(17 reference statements)

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“…WGCNA was conducted using the WGCNA package ( Guy et al, 2019 ). It is a systematic way for effectively acquiring the expression patterns of multiple genes in different samples, which can obtain a gene cluster with the same clinical phenotype.…”

Section: Methodsmentioning

confidence: 99%

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Identification of Ferroptosis-Related Genes Signature Predicting the Efficiency of Invasion and Metastasis Ability in Colon Adenocarcinoma

Shi

Xie

et al. 2022

Front. Cell Dev. Biol.

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Background: Colon adenocarcinoma (COAD) is one of the most prevalent cancers worldwide and has become a leading cause of cancer death. Although many potential biomarkers of COAD have been screened with the bioinformatics method, it is necessary to explore novel markers for the diagnosis and appropriate individual treatments for COAD patients due to the high heterogeneity of this disease. Epithelial-to-mesenchymal transition (EMT)-mediated tumor metastasis suggests poor prognosis of cancers. Ferroptosis is involved in tumor development. EMT signaling can increase the cellular sensitivity to ferroptosis in tumors. The aim of our study is finding novel prognostic biomarkers to determine COAD patients for predicting efficiency of metastasis status and targeting precise ferroptosis-related therapy.Methods: A novel gene signature related to metastasis and ferroptosis was identified combing with risk model and WGCNA analysis with R software. The biological functions and predictive ability of the signature in COAD were explored through bioinformatics analysis.Results: We established a four-gene prognostic signature (MMP7, YAP1, PCOLCE, and HOXC11) based on EMT and ferroptosis related genes and validated the reliability and effectiveness of this model in COAD. This four-gene prognostic signature was closely connected with metastasis and ferroptosis sensitivity of COAD. Moreover, WGCNA analysis further confirmed the correlation between PCOLCE, HOXC11, and liver and lymphatic invasion of COAD.Conclusion: The four genes may become potential prognostic biomarkers to identify COAD patients with metastasis. Moreover, this four-gene signature may be able to determine the COAD suitable with ferroptosis induction therapy. Finally, PCOLCE2 and HOXC11 were selected individually because of their novelties and precise prediction ability. Overall, this signature provided novel possibilities for better prognostic evaluation of COAD patients and may be of great guiding significance for individualized treatment and clinical decision.

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Section: Methodsmentioning

confidence: 99%

“…The R software package rms ( Zhang et al, 2019 ) was used to achieve the establishment and application of the nomogram. The calibration analysis ( Guy et al, 2019 ) was performed aligned with nomogram. Decision curve analysis (DCA) ( Van Calster et al, 2018 ) was conducted to verify the risk model.…”

Section: Methodsmentioning

confidence: 99%

Identification of Ferroptosis-Related Genes Signature Predicting the Efficiency of Invasion and Metastasis Ability in Colon Adenocarcinoma

Shi

Xie

et al. 2022

Front. Cell Dev. Biol.

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“…The clinical features and risk scores were used to establish a nomogram model. The calibration analysis ( Guy et al, 2019 ) was performed aligned with nomogram. Decision curve analysis (DCA) ( Van Calster et al, 2018 ) was conducted to verify the risk model.…”

Section: Methodsmentioning

confidence: 99%

“…WGCNA ( Guy et al, 2019 ) was conducted using the WGCNA package. It is a systematic way for effectively acquiring the expression patterns of multiple genes in different samples, which can obtain a gene cluster with the same expression pattern.…”

Section: Methodsmentioning

confidence: 99%

Identification of DDX31 as a Potential Oncogene of Invasive Metastasis and Proliferation in PDAC

Xie

Liu

Ding

et al. 2022

Front. Cell Dev. Biol.

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Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignant tumors worldwide and has poor prognosis. DEAD box proteins31 (DDX31) participate in cellular processes involving RNA secondary structure changes. However, the functions of DDX31 in PDAC remain to be elucidated.Methods: The key gene DDX31 was identified using a combination of a risk model and weighted gene co-expression network analysis (WGCNA) with R software. The biological functions of DDX31 in PDAC were investigated through bioinformatics analysis and in vitro experiments.Results: Combining with WGCNA and risk model, DDX31 was identified as a potential factor of the invasive metastasis properties of PDAC, and its expression was closely related to the malignant differentiation of PDAC. The results of gene set enrichment analysis (GSEA) showed that DDX31 was correlated with cell invasive metastasis and proliferation by activating MAPK signaling pathway. The inhibition of DDX31 inhibited the invasion and migration of PDAC cells. Survival analysis showed that DDX31 expression was negatively associated with the poor prognosis in patients with PDAC.Interpretation:DDX31 may be a potential factor for PDAC. The inhibition of DDX31 may be a potential way to treat PDAC.

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“…Calibration curves were drawn for evaluating the accurate prediction of the two models in the validation cohort. The Brier Scores were compared between two models, and a small Brier Score ( 23 ) indicates high prediction accuracy and is well-calibrated.…”

Section: Methodsmentioning

confidence: 99%

RGB Three-Channel SWE-Based Ultrasomics Model: Improving the Efficiency in Differentiating Focal Liver Lesions

et al. 2021

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ObjectiveTo explore a new method for color image analysis of ultrasomics and investigate the efficiency in differentiating focal liver lesions (FLLs) by Red, Green, and Blue (RGB) three-channel SWE-based ultrasomics model.MethodsOne hundred thirty FLLs were randomly divided into training set (n = 65) and validation set (n = 65). The RGB three-channel and direct conversion methods were applied to the same color SWE images. Ultrasomics features were extracted from the preprocessing images establishing two feature data sets. The least absolute shrinkage and selection operator (LASSO) logistic regression model was applied for feature selection and model construction. Two models, named RGB model (based on RGB three-channel conversion) and direct model (based on direct conversion), were used to differentiate FLLs. The diagnosis performance of the two models was evaluated by area under the curve (AUC), calibration curves, decision curves, and net reclassification index (NRI).ResultsIn the validation cohort, the AUC of the direct model and RGB model in characterization on FLLs were 0.813 and 0.926, respectively (p = 0.038). Calibration curves and decision curves indicated that the RGB model had better calibration efficiency and provided greater clinical benefits. NRI revealed that the RGB model correctly reclassified 7% of malignant cases and 25% of benign cases compared to the direct model (p = 0.01).ConclusionThe RGB model generated by RGB three-channel method yielded better diagnostic efficiency than the direct model established by direct conversion method. The RGB three-channel method may be promising on ultrasomics analysis of color images in clinical application.

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A cost‐effective approach to factor assay calibration using a truncated live calibration curve

Cited by 5 publications

References 8 publications

Identification of Ferroptosis-Related Genes Signature Predicting the Efficiency of Invasion and Metastasis Ability in Colon Adenocarcinoma

Identification of Ferroptosis-Related Genes Signature Predicting the Efficiency of Invasion and Metastasis Ability in Colon Adenocarcinoma

Identification of DDX31 as a Potential Oncogene of Invasive Metastasis and Proliferation in PDAC

RGB Three-Channel SWE-Based Ultrasomics Model: Improving the Efficiency in Differentiating Focal Liver Lesions

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