Publisher Correction: MethCORR modelling of methylomes from formalin-fixed paraffin-embedded tissue enables characterization and prognostication of colorectal cancer

Mattesen, Trine B.; Rasmussen, Mads Heilskov; Sandoval, Juan; Ongen, Halit; Árnadóttir, Sigrid S.; Gladov, Josephine; Martínez-Cardús, Anna; Moura, Manuel Castro de; Madsen, Anders Husted; Laurberg, Søren; Dermitzakis, Emmanouil T.; Esteller, Manel; Andersen, Claus L.; Bramsen, Jesper B.

doi:10.1038/s41467-020-16538-5

Cited by 2 publications

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“…If the expression of gene A > the expression of gene B, then the feature "A|B" is marked as 1, otherwise, it is marked as 0, as shown in Eq. (1).…”

Section: Prognostic Model Buildingmentioning

confidence: 99%

“…Despite a continuous refinement to the UICC tumor, node, metastasis (TNM) staging system to measure disease extent and define prognosis, disease outcome still varies considerably even among patients with the same tumor stage. Therefore, new factors that can more precisely stratify patients into different risk categories are clearly warranted ( 1 , 2 ).…”

Section: Introductionmentioning

confidence: 99%

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Identification of immunotherapy and chemotherapy-related molecular subtypes in colon cancer by integrated multi-omics data analysis

et al. 2023

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BackgroundColon cancer is a highly heterogeneous disease, and identifying molecular subtypes can provide insights into deregulated pathways within tumor subsets, which may lead to personalized treatment options. However, most prognostic models are based on single-pathway genes.MethodsIn this study, we aimed to identify three clinically relevant subtypes of colon cancer based on multiple signaling pathways-related genes. Integrative multi-omics analysis was used to explain the biological processes contributing to colon cancer aggressiveness, recurrence, and progression. Machine learning methods were employed to identify the subtypes and provide medication guidance for distinct subtypes using the L1000 platform. We developed a robust prognostic model (MKPC score) based on gene pairs and validated it in one internal test set and three external test sets. Risk-related genes were extracted and verified by qPCR.ResultsThree clinically relevant subtypes of colon cancer were identified based on multiple signaling pathways-related genes, which had significantly different survival state (Log-Rank test, p<0.05). Integrative multi-omics analysis revealed biological processes contributing to colon cancer aggressiveness, recurrence, and progression. The developed MKPC score, based on gene pairs, was robust in predicting prognosis state (Log-Rank test, p<0.05), and risk-related genes were successfully verified by qPCR (t test, p<0.05). An easy-to-use web tool was created for risk scoring and therapy stratification in colon cancer patients, and the practical nomogram can be extended to other cancer types.ConclusionIn conclusion, our study identified three clinically relevant subtypes of colon cancer and developed a robust prognostic model based on gene pairs. The developed web tool is a valuable resource for researchers and clinicians in risk scoring and therapy stratification in colon cancer patients, and the practical nomogram can be extended to other cancer types.

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“…If the expression of gene A > the expression of gene B, then the feature "A|B" is marked as 1, otherwise, it is marked as 0, as shown in Eq. (1).…”

Section: Prognostic Model Buildingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identification of immunotherapy and chemotherapy-related molecular subtypes in colon cancer by integrated multi-omics data analysis

et al. 2023

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“…Over the past decades, despite considerable advances in early detection and surgical techniques, and medical therapies (e.g., chemotherapy, radiotherapy, targeted therapy, and immunotherapy) used in urinary system cancers, the 5-year survival outcome of patients diagnosed with urinary tumors remains poor; and the risk of recurrence and progression of these tumors is high ( 4 ). Numerous clinical studies have evaluated the prognosis of patients with urological cancers and have assisted clinicians in making follow-up treatment protocols using TNM stage, grade, tumor size, symptoms, and paraneoplastic syndromes ( 5 – 7 ). However, using the above clinical prognostic indicators alone can not accurately assess the extent of disease extent or define prognosis ( 7 , 8 ).…”

Section: Introductionmentioning

confidence: 99%

Serum albumin to globulin ratio prior to treatment as a potential non-invasive prognostic indicator for urological cancers

Xia

Yuan

et al. 2022

Front. Nutr.

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BackgroundNumerous clinical studies have reported an association between the pretreatment albumin to globulin ratio (AGR) and survival outcomes of urological cancers. However, these conclusions remain controversial. Therefore, we performed a meta-analysis to explore the prognostic value of the AGR in urinary system tumors.MethodsWe retrieved eligible studies published up to June 2022 through a comprehensive search of multiple databases. Pooled hazard ratios (HRs) with 95% confidence intervals (CI) for overall survival (OS), cancer-specific survival (CSS), recurrence-free survival (RFS), progression-free survival (PFS), and biochemical recurrence-free survival (BRFS) were used to evaluated the predictive effect of the AGR before treatment in urinary system tumors. Heterogeneity test, random-effects models, fixed-effects models and sensitivity tests were used for analyses.ResultsA total of 21 studies with 18,269 patients were enrolled in our meta-analysis. We found that patients with urinary system cancer with low AGR prior to treatment had poor OS [HR = 1.93, 95% CI (1.56–2.39), p < 0.001], CSS [HR = 2.22, 95% CI (1.67–2.96), p < 0.001], RFS [HR = 1.69, 95% CI (1.29–2.22), p < 0.001], and PFS [HR = 1.29, 95% CI (0.54–3.07), p < 0.001]. For prostate cancer (PCa), a low pretreatment AGR was associated with poor BRFS [HR = 1.46, 95% CI (1.28–1.67), p < 0.001]. Also, a subgroup analysis, stratified by ethnicity, cancer type, cutoff value, sample size and publication year, was conducted. The results showed that worse OS and CSS were significantly associated with these factors.ConclusionOur meta-analysis revealed that the AGR before treatment could be used as a non-invasive predictive biomarker to evaluate the prognosis of urological cancer patients in clinical practice.

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Publisher Correction: MethCORR modelling of methylomes from formalin-fixed paraffin-embedded tissue enables characterization and prognostication of colorectal cancer

Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Cited by 2 publications

References 0 publications

Identification of immunotherapy and chemotherapy-related molecular subtypes in colon cancer by integrated multi-omics data analysis

Identification of immunotherapy and chemotherapy-related molecular subtypes in colon cancer by integrated multi-omics data analysis

Serum albumin to globulin ratio prior to treatment as a potential non-invasive prognostic indicator for urological cancers

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