scholarly journals A four-DNA methylation biomarker is a superior predictor of survival of patients with cutaneous melanoma

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Wenna Guo ◽  
Liucun Zhu ◽  
Rui Zhu ◽  
Qihan Chen ◽  
Qiang Wang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Cutaneous Melanoma ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Immune Checkpoint Blockade ◽  
Melanoma Diagnosis ◽  
Kaplan Meier ◽  
Genome Wide ◽  
Life Threatening ◽  
Distinct Separation

Cutaneous melanoma (CM) is a life-threatening form of skin cancer. Prognostic biomarkers can reliably stratify patients at initial melanoma diagnosis according to risk, and may inform clinical decisions. Here, we performed a retrospective, cohort-based study analyzing genome-wide DNA methylation of 461 patients with CM from the TCGA database. Cox regression analyses were conducted to establish a four-DNA methylation signature that was significantly associated with the overall survival (OS) of patients with CM, and that was validated in an independent cohort. Corresponding Kaplan–Meier analysis displayed a distinct separation in OS. The ROC analysis confirmed that the predictive signature performed well. Notably, this signature exhibited much higher predictive accuracy in comparison with known biomarkers. This signature was significantly correlated with immune checkpoint blockade (ICB) immunotherapy-related signatures, and may have potential as a guide for measures of responsiveness to ICB immunotherapy.

scholarly journals Favorable 90-Day Mortality in Obese Caucasian Patients with Septic Shock According to the Sepsis-3 Definition

2019 ◽  
Vol 9 (1) ◽  
pp. 46 ◽  
Author(s):  
Caspar Mewes ◽  
Carolin Böhnke ◽  
Tessa Alexander ◽  
Benedikt Büttner ◽  
José Hinz ◽  
...  
Keyword(s):  
Septic Shock ◽  
Protective Effect ◽  
Cox Regression ◽  
Obese Patients ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Threatening Condition ◽  
Life Threatening ◽  
Caucasian Patients ◽  
Patient Prognosis

Septic shock is a frequent life-threatening condition and a leading cause of mortality in intensive care units (ICUs). Previous investigations have reported a potentially protective effect of obesity in septic shock patients. However, prior results have been inconsistent, focused on short-term in-hospital mortality and inadequately adjusted for confounders, and they have rarely applied the currently valid Sepsis-3 definition criteria for septic shock. This investigation examined the effect of obesity on 90-day mortality in patients with septic shock selected from a prospectively enrolled cohort of septic patients. A total of 352 patients who met the Sepsis-3 criteria for septic shock were enrolled in this study. Body-mass index (BMI) was used to divide the cohort into 24% obese (BMI ≥ 30 kg/m2) and 76% non-obese (BMI < 30 kg/m2) patients. Kaplan-Meier survival analysis revealed a significantly lower 90-day mortality (31% vs. 43%; p = 0.0436) in obese patients compared to non-obese patients. Additional analyses of baseline characteristics, disease severity, and microbiological findings outlined further statistically significant differences among the groups. Multivariate Cox regression analysis estimated a significant protective effect of obesity on 90-day mortality after adjustment for confounders. An understanding of the underlying physiologic mechanisms may improve therapeutic strategies and patient prognosis.

Prognostic Significance of Nuclear Receptor Coactivator-3 Overexpression in Primary Cutaneous Melanoma

2006 ◽  
Vol 24 (28) ◽  
pp. 4565-4569 ◽  
Author(s):  
Javier Rangel ◽  
Sima Torabian ◽  
Ladan Shaikh ◽  
Mehdi Nosrati ◽  
Frederick L. Baehner ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Nuclear Receptor ◽  
Cutaneous Melanoma ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Primary Cutaneous Melanoma ◽  
Nuclear Receptor Coactivator ◽  
Kaplan Meier ◽  
The Impact

Purpose To assess the prognostic significance of nuclear receptor coactivator-3 (NCOA3) overexpression in primary cutaneous melanoma. Patients and Methods NCOA3 expression was assessed using immunohistochemical analysis of a melanoma tissue microarray (TMA) containing primary melanomas from 343 patients with defined histology and follow-up. The impact of the presence or absence of various prognostic factors on relapse-free survival (RFS) and disease-specific survival (DSS) of melanoma patients was assessed using Cox regression and Kaplan-Meier analysis. The impact of presence or absence of various factors on sentinel lymph node (SLN) metastasis was assessed using logistic regression analysis. Results Increasing degree of NCOA3 expression was significantly predictive of SLN metastasis (P = .013) and the mean number of SLN metastases (P = .031). Kaplan-Meier analysis demonstrated a significant association between NCOA3 overexpression and reduced RFS (P = .021) and DSS (P = .030). Logistic regression analysis revealed increasing degree of NCOA3 expression to be an independent predictor of SLN status (P = .017). Multivariate Cox regression analysis showed the independent impact of NCOA3 expression on RFS (P = .0095) and DSS (P = .021). NCOA3 was the most powerful factor predicting DSS, outperforming tumor thickness and ulceration. Conclusion These results identify NCOA3 as a novel, independent marker of melanoma outcome, with a significant impact on SLN metastasis, RFS, and DSS.

scholarly journals A genomic signature for accurate classification and prediction of clinical outcomes in cancer patients treated with immune checkpoint blockade immunotherapy

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Mei Lu ◽  
Kuan-Han Hank Wu ◽  
Sheri Trudeau ◽  
Margaret Jiang ◽  
Joe Zhao ◽  
...  
Keyword(s):  
Machine Learning ◽  
Overall Survival ◽  
Cancer Patients ◽  
Predictive Accuracy ◽  
Immune Checkpoint Blockade ◽  
Training Data ◽  
Genomic Signature ◽  
Validation Data ◽  
Kaplan Meier ◽  
Clinical Benefits

AbstractTumor mutational burden (TMB) is associated with clinical response to immunotherapy, but application has been limited to a subset of cancer patients. We hypothesized that advanced machine-learning and proper modeling could identify mutations that classify patients most likely to derive clinical benefits. Training data: Two sets of public whole-exome sequencing (WES) data for metastatic melanoma. Validation data: One set of public non-small cell lung cancer (NSCLC) data. Least Absolute Shrinkage and Selection Operator (LASSO) machine-learning and proper modeling were used to identify a set of mutations (biomarker) with maximum predictive accuracy (measured by AUROC). Kaplan–Meier and log-rank methods were used to test prediction of overall survival. The initial model considered 2139 mutations. After pruning, 161 mutations (11%) were retained. An optimal threshold of 0.41 divided patients into high-weight (HW) or low-weight (LW) TMB groups. Classification for HW-TMB was 100% (AUROC = 1.0) on melanoma learning/testing data; HW-TMB was a prognostic marker for longer overall survival. In validation data, HW-TMB was associated with survival (p = 0.0057) and predicted 6-month clinical benefit (AUROC = 0.83) in NSCLC. In conclusion, we developed and validated a 161-mutation genomic signature with “outstanding” 100% accuracy to classify melanoma patients by likelihood of response to immunotherapy. This biomarker can be adapted for clinical practice to improve cancer treatment and care.

scholarly journals Methylation Markers in Cutaneous Melanoma: Unravelling the Potential Utility of Their Tracking by Liquid Biopsy

Cancers ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 6217
Author(s):  
Valentina Aleotti ◽  
Cristina Catoni ◽  
Cristina Poggiana ◽  
Antonio Rosato ◽  
Antonella Facchinetti ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Cancer Progression ◽  
Liquid Biopsy ◽  
Circulating Tumor Dna ◽  
Response To Therapy ◽  
Recent Advances ◽  
Genome Wide ◽  
Potential Biomarker ◽  
Life Threatening ◽  
And Migration

Malignant melanoma is the most serious, life-threatening form of all dermatologic diseases, with a poor prognosis in the presence of metastases and advanced disease. Despite recent advances in targeted therapy and immunotherapy, there is still a critical need for a better understanding of the fundamental mechanisms behind melanoma progression and resistance onset. Recent advances in genome-wide methylation methods have revealed that aberrant changes in the pattern of DNA methylation play an important role in many aspects of cancer progression, including cell proliferation and migration, evasion of cell death, invasion, and metastasization. The purpose of the current review was to gather evidence regarding the usefulness of DNA methylation tracking in liquid biopsy as a potential biomarker in melanoma. We investigated the key genes and signal transduction pathways that have been found to be altered epigenetically in melanoma. We then highlighted the circulating tumor components present in blood, including circulating melanoma cells (CMC), circulating tumor DNA (ctDNA), and tumor-derived extracellular vesicles (EVs), as a valuable source for identifying relevant aberrations in DNA methylation. Finally, we focused on DNA methylation signatures as a marker for tracking response to therapy and resistance, thus facilitating personalized medicine and decision-making in the treatment of melanoma patients.

scholarly journals Elevated TG/HDL-C and Non-HDL-C/HDL-C Ratios Predict Mortality in Peritoneal Dialysis Patients

2020 ◽  
Author(s):  
Wenkai Xia ◽  
Xiajuan Yao ◽  
Yan Chen ◽  
Jie Lin ◽  
Volker Vielhauer ◽  
...  
Keyword(s):  
Peritoneal Dialysis ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Serum Triglyceride ◽  
Hdl Cholesterol ◽  
Atherogenic Dyslipidemia ◽  
Dialysis Patients ◽  
Cox Regression Analysis ◽  
Kaplan Meier

Abstract Background and Aims: Dyslipidemia is common in patients with chronic kidney disease and particular prevalent in patients receiving peritoneal dialysis. However, whether markers of atherogenic dyslipidemia correlate with outcomes in dialysis patients as in the general population is uncertain. Here, we investigated the prognostic value of the serum triglyceride/HDL cholesterol (TG/HDL-C) ratio and non-HDL-C/HDL-C ratio in peritoneal dialysis patients to predict all-cause mortality. Methods 214 PD patients were retrospectively analyzed from January 2011 to December 2015, with a median follow-up of 59 months. We used receiver operating curves (ROC) to determine the optimal threshold for TG/HDL-C and non-HDL/HDL-C ratios at baseline to predict OS during follow-up. Prognostic values were accessed by univariate and multivariate COX regression analysis and Kaplan-Meier curve. A predictive nomogram was developed to predict prognosis for overall survival, and the predictive accuracy was evaluated by concordance index (c-index). Results The optimal cut-off values for TG/HDL-C ratio and non-HDL-C/HDL-C ratio were 1.94 and 2.86, respectively. A high TG/HDL-C ratio and a high non-HDL-C/HDL-C ratio strongly correlated with worse OS in PD patients. Multivariate analysis demonstrated that elevated TG/HDL-C ratio as well as non-HDL/HDL-C ratios were independent markers to predict reduced OS. The TG/HDL-C ratio (HR 2.60, 95% CI 1.40–4.83, P = 0.002) was superior to non-HDL-C/HDL-C ratio based on hazard ratio (HR 2.43, 95% CI 1.09–5.40, P = 0.029). Conclusion TG/HDL-C ratio and non-HDL-C/HDL-C were identified as potential prognostic biomarkers in PD patients. The proposed nomograms can be utilized for prediction of OS in PD patients.

scholarly journals Establishment of a 5 DNA Methylation Site Prognostic Signature Associated with N6-Methyladenosine in Lung Adenocarcinoma

2021 ◽  
Author(s):  
Liqiang Yuan ◽  
Wei Jiang ◽  
Zhanyu Xu ◽  
Kung Deng ◽  
Yu Sun ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Lung Adenocarcinoma ◽  
Cox Regression ◽  
Clinicopathological Parameters ◽  
Main Body ◽  
Methylation Site ◽  
Cox Regression Analysis ◽  
Site Model ◽  
Kaplan Meier ◽  
Cox Analysis

Abstract Background: There is a high incidence of lung adenocarcinoma (LUAD). Even with surgery, targeted therapy and immunotherapy, the survival rate of LUAD patients is still low. N6-methyladenosine (m6A) and DNA methylation markers can help with the diagnosis and treatment of LUAD patients. Therefore, it is necessary to identify a novel m6A-related DNA methylation sites signature to predict the survival of patients with LUAD. Methods: In this study, we screened 15 m6A-related genes and their 217 methylation sites. RNA sequencing data of 15 genes and the clinicopathological parameters of TCGA-LUAD were obtained from the TCGA database (http://cancergenome.nih.gov/). The LUAD-DNA CpG site information was obtained from the Illumina Human Methylation 450 BeadChip (Illumina, San Diego, CA, United States). The methylation sites related to prognosis were screened using univariate COX analysis, and the independent predictors of LUAD patients were identified using multivariate COX analysis of least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Finally, a model with 5 methylation sites as the main body to predict the prognosis of OS in patients with LUAD was obtained. According to the risk grouping of the prediction model, Kaplan-Meier curve and the receiver operating characteristic (ROC) curve were performed in the test and training sets to assess the predicted capacity of the model. In addition, a nomogram constructed by combining the risk score of methylation group and other related clinicopathological factors to verify the reliability of our model.Results: We constructed a m6A-related 5-DNA methylation site model to predict OS in LUAD patients. According to the results of the Kaplan-Meier curve, both the test set and the training set, the high-risk group showed a worse prognosis. The AUCs of the 5 DNA methylation signature at 1, 5 and 10 years in test datasets were 0.730, 0.649 and 0.726, respectively, and 0.679, 0.656 and 0.732 in training datasets. Finally, we constructed a nomogram to further verify the reliability of the model.Conclusion: In this study, we analyzed the methylation sites of m6A-related genes and established a m6A-related 5-DNA methylation site model to predict OS in LUAD patients.

Clinical Significance of Prognostic Alternative Splicing Signature in Tumor Immune Environment and Immune Therapy of Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Qianhui Xu ◽  
Hao Xu ◽  
Rongshan Deng ◽  
Nanjun Li ◽  
Ruiqi Mu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Alternative Splicing ◽  
Clinical Decision Making ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Immune Therapy ◽  
Immune Checkpoint Blockade ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Prognostic Prediction

Abstract Background: Hepatocellular carcinoma (HCC) ranks the sixth prevalent tumors with high mortality globally. Alternative splicing (AS) drives protein diversity, the imbalance of which might act an important factor in tumorigenesis. We aimed to construct of AS-based prognostic signature and elucidate the role in tumor immune microenvironment (TIME) and immunotherapy in HCC.Methods: To determine the prognosis-related AS events, univariate Cox regression analysis was performed, followed by the development of prognostic signatures. The prognosis predictive ability of risk signature was validated and a predictive nomogram was constructed. To uncover the context of TIME in HCC, ESTIMATE R package, ssGSEA algorithm and CIBERSORT method and TIMER database exploration were performed. And the correlation of AS events with immune checkpoint blockade (ICB)-related genes was analyzed.Results: A total of 3294 AS events associated with survival of HCC patients were screened. Based on splicing subtypes, we then constructed eight AS prognostic signature with robust prognostic predictive accuracy. Furthermore, a quantitative nomogram exhibited robust validity in prognostic prediction of HCC. Besides, the consolidated signature was significantly correlated with TIME diversity and ICB-related genes. Finally, the splicing regulatory network uncovered the potential functions of splicing factors (SFs) in HCC.Conclusion: Herein, the AS events may contribute novel and robust indicators for the prognostic prediction of HCC. The AS-SF networks could open up new approach for investigation of potential regulatory mechanisms. And we revealed the pivotal player of AS events in context of TIME and immunotherapy, contributing to clinical decision-making and personalized prognosis monitoring of HCC.

scholarly journals Cellular Mechanisms of Oxidative Stress and Action in Melanoma

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Mario Venza ◽  
Maria Visalli ◽  
Concetta Beninati ◽  
Giuseppe Valerio De Gaetano ◽  
Diana Teti ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Dna Methylation ◽  
Methylation Pattern ◽  
The Body ◽  
Current Evidence ◽  
Cellular Mechanisms ◽  
Melanoma Diagnosis ◽  
Life Threatening ◽  
Induced Changes ◽  
The Impact

Most melanomas occur on the skin, but a small percentage of these life-threatening cancers affect other parts of the body, such as the eye and mucous membranes, including the mouth. Given that most melanomas are caused by ultraviolet radiation (UV) exposure, close attention has been paid to the impact of oxidative stress on these tumors. The possibility that key epigenetic enzymes cannot act on a DNA altered by oxidative stress has opened new perspectives. Therefore, much attention has been paid to the alteration of DNA methylation by oxidative stress. We review the current evidence about (i) the role of oxidative stress in melanoma initiation and progression; (ii) the mechanisms by which ROS influence the DNA methylation pattern of transformed melanocytes; (iii) the transformative potential of oxidative stress-induced changes in global and/or local gene methylation and expression; (iv) the employment of this epimutation as a biomarker for melanoma diagnosis, prognosis, and drug resistance evaluation; (v) the impact of this new knowledge in clinical practice for melanoma treatment.

scholarly journals Methylation and transcriptome analysis reveal lung adenocarcinoma-specific diagnostic biomarkers

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Rui Li ◽  
Yi-E Yang ◽  
Yun-Hong Yin ◽  
Meng-Yu Zhang ◽  
Hao Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Lung Adenocarcinoma ◽  
Cox Regression ◽  
R Package ◽  
Functional Enrichment ◽  
Independent Effect ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Differentially Methylated Genes

Abstract Background DNA methylation can regulate the role of long noncoding RNAs (lncRNAs) in the development of lung adenocarcinoma (LUAD). The present study aimed to identify methylation-driven lncRNAs and mRNAs as biomarkers in the prognosis of LUAD using bioinformatics analysis. Methods Differentially expressed RNAs were obtained using the edge R package from 535 LUAD tissues and 59 adjacent non-LUAD tissues. Differentially methylated genes were obtained using the limma R package from 475 LUAD tissues and 32 adjacent non-LUAD tissues. Methylation-driven mRNA and lncRNA were obtained using the MethylMix R package from 465 LUAD tissues with matched DNA methylation and RNA expression and 32 non-LUAD tissues with DNA methylation. Gene ontology and ConsensusPathDB pathway analysis were performed to identify functional enrichment of methylation-driven mRNAs. Univariate and multivariate Cox regression analyses were performed to identify the independent effect of each variable for predicting the prognosis of LUAD. Kaplan–Meier curve analysis of DNA methylation and gene expression might provide potential prognostic biomarkers for LUAD patients. Results A total of 99 methylation-driven mRNAs and 17 methylation-driven lncRNAs were obtained. Univariate and multivariate Cox regression analysis showed that 6 lncRNAs (FOXE1, HOXB13-AS1_2, VMO1, HIST1H3F, AJ003147.8, ASXL3) were retrieved to construct a predictive model associated with overall survival in LUAD patients. Combined DNA methylation and gene expression survival analysis revealed that 4 lncRNAs (AC023824.1, AF186192.1, LINC01354 and WASIR2) and 8 mRNAs (S1PR1, CCDC181, F2RL1, EFS, KLHDC9, MPV17L, GKN2, ITPRIPL1) might act as independent biomarkers for the prognosis of LUAD. Conclusions Methylation-driven lncRNA and mRNA contribute to the survival of LUAD, and 4 lncRNAs and 8 mRNAs might be potential biomarkers for the prognosis of LUAD.

scholarly journals The Development of Three-DNA Methylation Signature as a Novel Prognostic Biomarker in Patients with Colorectal Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Shu Gong ◽  
Weijian Ye ◽  
Tiankai Liu ◽  
Shaofen Jian ◽  
Wenhua Liu
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Overall Survival ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Methylation Array ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Potential Biomarker ◽  
And Gender

Aims. The prognosis of colorectal cancer (CRC) remains poor. This study aimed to develop and validate DNA methylation-based signature model to predict overall survival of CRC patients. Methods. The methylation array data of CRC patients were retrieved from The Cancer Genome Atlas (TCGA) database. These patients were divided into training and validation datasets. A risk score model was established based on Kaplan-Meier and multivariate Cox regression analysis of training cohort and tested in validation cohort. Results. Among total 14,626 DNA methylation candidate markers, we found that a three-DNA methylation signature (NR1H2, SCRIB, and UACA) was significantly associated with overall survival of CRC patients. Subgroup analysis indicated that this signature could predict overall survival of CRC patients regardless of age and gender. Conclusions. We established a prognostic model consisted of 3-DNA methylation sites, which could be used as potential biomarker to evaluate the prognosis of CRC patients.

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