Prognostic Values of Preoperative Inflammatory and Nutritional Markers for Colorectal Cancer

Zhang, Nannan; Ning, Fei‐Long; Guo, Rui; Pei, Jun‐Peng; Qiao, Yun; Fan, Jie; Jiang, Bo; Liu, Yanlong; Chi, Zhaocheng; Mei, Zubing; Abe, Masanobu; Zhu, Ji; Zhang, Rui; Zhang, Chun‐Dong

doi:10.3389/fonc.2020.585083

Cited by 12 publications

(17 citation statements)

References 62 publications

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“…Tumor-associated neutrophils (TANs) can recruit immune T cells, which may promote tumor growth, progression, and resistance to chemotherapy [ 36 ]. Zhang et al [ 37 ] demonstrated that TANs can independently influence OS and DFS in colorectal cancer. Tregs reduce immunotherapy effectiveness due to their antitumor immune effects [ 38 ].…”

Section: Discussionmentioning

confidence: 99%

[Retracted] DNM1: A Prognostic Biomarker Associated with Immune Infiltration in Colon Cancer—A Study Based on TCGA Database

et al. 2021

BioMed Research International

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Aim. The aim of our work was to determine the utility of DNM1 as a biomarker for the diagnosis and prognosis of colon cancer (CC). Methods. DNM1 expression variations in CC vs. normal tissues were investigated using The Cancer Genome Atlas (TCGA) database. The association of DNM1 expression levels with the clinicopathological variables in CC prognosis was investigated using logistic regression analyses. Independent prognostic factors for CC were evaluated using univariate and multivariate Cox regression analyses. The correlation between DNM1 expression and immune cell infiltration was estimated using single-sample Gene Set Enrichment Analysis (ssGSEA). Results. DNM1 expression in CC tissues was significantly higher than that in normal tissues. High DNM1 expression was significantly correlated with M stage, N stage, perineural invasion and lymphatic invasion and predicted poor prognosis. The univariate analysis highlighted that DNM1 was an independent CC risk factor. Results of ssGSEA showed that DNM1 was linked to several cancer-related pathways, including the neuroactive ligand-receptor interaction, hypertrophic cardiomyopathy, ECM-receptor interaction, dilated cardiomyopathy, and calcium signaling pathway. Moreover, DNM1 expression was positively correlated with the level of infiltration by Neutrophils, Tregs, NK cells, and Macrophages. Conclusion. DNM1 has a significant function and has diagnostic and prognostic potential for CC.

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Section: Discussionmentioning

confidence: 99%

[Retracted] DNM1: A Prognostic Biomarker Associated with Immune Infiltration in Colon Cancer—A Study Based on TCGA Database

et al. 2021

BioMed Research International

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“…Daniel Boakye et al constructed a clinical nomogram incorporating comorbidities and functional status, which could substantially enhance prediction of CRC prognosis (37). Likewise, a novel nomogram i n c o r p o r a t i n g p r e o p e r a t i v e i n fl a m m a t o r y a n d nutritional markers, built by Zhang Nannan et al (5), could individually predict both OS and disease-free survival (DFS) of patients with CRC. Here, the aim of our study was to construct a convenient and clinically available prognostic model to better predict outcomes of CRC patients.…”

Section: Discussionmentioning

confidence: 99%

“…To calculate the LODDS value, negative LNs (nLNs) representing non-metastatic lymph nodes should be derived by subtracting pLNs from the harvested LNs. Afterwards, LODDS was determined as the following formula: LODDS = In ([pLNs + 0.5]/[nLNs + 0.5]) (5,15).…”

Section: Crc Patients and Study Designmentioning

confidence: 99%

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A Novel Prognostic Model and Practical Nomogram for Predicting the Outcomes of Colorectal Cancer: Based on Tumor Biomarkers and Log Odds of Positive Lymph Node Scheme

Jun

Hao

et al. 2021

Front. Oncol.

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BackgroundEmerging evidence shows that serum tumor biomarkers (TBs) and log odds of positive lymph node scheme (LODDS) are closely associated with the prognosis of colorectal cancer (CRC) patients. The aim of our study is to validate the predictive value of TBs and LODDS clinically and to develop a robust prognostic model to predict the overall survival (OS) of patients with CRC.MethodsCRC patients who underwent radical resection and with no preoperative chemotherapy were enrolled in the study. The eligible population were randomized into training (70%) and test (30%) cohorts for the comprehensive evaluation of the prognostic model. Clinical implications of serum biomarkers and LODDS were identified by univariate and multivariate Cox proportion regression analysis. The predictive ability and discriminative performance were evaluated by Kaplan–Meier (K–M) curves and receiver operating characteristic (ROC) curves. Clinical applicability of the prognostic model was assessed by decision curve analysis (DCA), and the corresponding nomogram was constructed based on the above factors.ResultsA total of 1,202 eligible CRC patients were incorporated into our study. Multivariable COX analysis demonstrated that CA199 (HR = 1.304), CA125 (HR = 1.429), CEA (HR = 1.307), and LODDS (HR = 1.488) were independent risk factors for OS (all P < 0.0001). K–M curves showed that the high-risk group possessed a shorter OS than the low-risk counterparts. The area under curves (AUCs) of the model for 1-, 3- and 5-year OS were 86.04, 78.70, and 76.66% respectively for the train cohort (80.35, 77.59, and 74.26% for test cohort). Logistic DCA and survival DCA confirmed that the prognostic model displayed more clinical benefits than the conventional AJCC 8th TNM stage and CEA model. The nomograms were built accordingly, and the calibration plot for the probability of survival at 3- or 5-years after surgery showed an optimal agreement between prediction and actual observation.ConclusionsPreoperative serum TBs and LODDS have significant clinical implications for CRC patients. A novel prognostic model incorporating common TBs (CA199, CA125, and CEA) and LODDS displayed better predictive performance than both single factor and the TNM classification. A novel nomogram incorporating TBs and LODDS could individually predict OS in patients with CRC.

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“…The calibration was calculated by the “calibrate” function with the parameter “cmethod = KM, method = boot, m = 80.” Discrimination was evaluated by Harrell’s concordance index (C-index) and ROC curve. A higher area under curve (AUC) value revealed superior model discriminative ability, and a higher C-index value demonstrated better model-fitting performance ( Zhang et al, 2020 ). Decision curve analysis (DCA) was further performed to measure and compare the clinical utilities of the different prognostic models.…”

Section: Methodsmentioning

confidence: 99%

Novel Molecular Subtypes and Related Score Based on Histone Acetylation Modification in Renal Clear Cell Carcinoma

Wang

Xiang

et al. 2021

Front. Cell Dev. Biol.

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Background: Histone acetylation modification has been found to be correlated the development of renal carcinoma; however, its role in clear cell renal carcinoma (ccRCC) remains to be investigated. Thus, this study aimed to identify the molecular subtypes and establish a relevant score based on histone acetylation modification in ccRCC.Methods: Gene expression and mutation data were retrieved from The Cancer Genome Atlas database. Molecular subtypes were identified by unsupervised clustering based on histone acetylation regulators expression, and the molecular and clinical characteristics including survival, tumor microenvironment, gene set variation, immune cell infiltration, and immune checkpoints in each subtype were investigated. Next, we employed univariate Cox analysis to analyze these genes and established acetylation-related score by lasso regression analysis. Furthermore, we investigated the differences including survival, signaling pathways, mutational landscape, and tumor mutation burden (TMB) between high-risk and low-risk groups. The established score was validated by receiver operating curve and univariate and multivariate Cox regression analyses. We also established a nomogram including acetylation score, age, gender, grade, and stage and verified it by decision curve analysis and calibration plot. The E-MTAB-1980 cohort from the ArrayExpress database was employed as a reference to validate the established score.Results: Thirty-three types of histone acetylation regulators were employed in this study, and two clusters were identified. The two clusters presented significant differences in survival, tumor microenvironment, immune cell infiltration, immune checkpoints, and signaling pathways. Furthermore, an acetylation-related score, composed of six genes (BRD9, HDAC10, KAT2A, KAT5, BRDT, SIRT1, KAT6A, HDAC5), was verified to be significantly associated with prognosis and TMB. Thus, the established scores were successfully verified by the validated cohort, and the nomogram was constructed and successfully validated.Conclusion: The identification of the histone acetylation-related subtypes and score in our study may help reveal the potential relation between histone acetylation and immunity and provide novel insights for the development of individualized therapy for ccRCC.

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Prognostic Values of Preoperative Inflammatory and Nutritional Markers for Colorectal Cancer

Cited by 12 publications

References 62 publications

[Retracted] DNM1: A Prognostic Biomarker Associated with Immune Infiltration in Colon Cancer—A Study Based on TCGA Database

[Retracted] DNM1: A Prognostic Biomarker Associated with Immune Infiltration in Colon Cancer—A Study Based on TCGA Database

A Novel Prognostic Model and Practical Nomogram for Predicting the Outcomes of Colorectal Cancer: Based on Tumor Biomarkers and Log Odds of Positive Lymph Node Scheme

Novel Molecular Subtypes and Related Score Based on Histone Acetylation Modification in Renal Clear Cell Carcinoma

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