Evidence map›Paper›PMID 32730361›Full record

ArticlePloS one2020

A new clinical prognostic nomogram for liver cancer based on immune score.

Qinyan Shen, Guinv Hu, JinZhong Wu, Liting Lv

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In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Qinyan ShenDepartment of Surgical Oncology, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, Zhejiang, China.ORCID 0000-0003-4869-477X
Guinv HuDepartment of Surgical Oncology, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, Zhejiang, China.
JinZhong WuDepartment of Surgical Oncology, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, Zhejiang, China.
Liting LvDepartment of Surgical Oncology, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIncreased attention is being paid to the relationship between the immune status of the tumor microenvironment and tumor prognosis. The application of immune scoring in evaluating the clinical prognosis of liver cancer patients has not yet been explored. This study sought to clarify the association between immune score and prognosis and construct a clinical nomogram to predict the survival of patients with liver cancer.

methodsA total of 346 patients were included in our analysis datasets downloaded from The Cancer Genome Atlas (TCGA) dataset. A Cox proportional-hazards regression model was used to estimate the adjusted hazard ratios (HRs). A nomogram was built based on the results of multivariate analysis and was subjected to bootstrap internal validation. The predictive accuracy and discriminative ability were measured by the concordance index (C-index) and the calibration curve. Through the functional analysis of differential expression of genes with different immune scores, the target genes were screened out.

resultsIn comparison with patients with low immune scores, those with intermediate and high immune scores had significantly improved survival time [HR and 95% confidence interval (CI): 0.54 (0.30-0.97) and 0.51 (0.27-0.97), respectively]. The C-index for survival time prediction was 0.66 (95% CI: 0.60-0.71). The calibration plot for the probability of survival at three or five years showed good agreement between prediction by the nomogram and actual observations. The top 10 hub genes were CXCL8(chemokine (C-X-C motif) ligand 8), SYK(spleen tyrosine kinase), CXCL12(chemokine (C-X-C motif) ligand 12), CXCL10 (chemokine (C-X-C motif) ligand10), CXCL1(chemokine (C-X-C motif) ligand1), CCL5(chemokine (C-C motif) ligand 5), CCL20(chemokine (C-C motif) ligand 20), LCK, CXCL11(chemokine (C-X-C motif) ligand 11), CCR5(chemokine (C-C motif) receptor 5). More importantly, we found that the high expression of CXCL8 and CXCL1 were related to the prognosis.

conclusionsHigh and/or intermediate immune scores are significantly correlated with better survival time in patients with liver cancer. Moreover, nomograms for predicting prognosis may help to estimate the survival of patients. We also propose that CXCL8 and CXCL1 may be a potential therapeutic target for liver cancer treatment.

Indexed as

NomogramsAdolescentAdultAgedAged, 80 and overChemokine CXCL12Databases, FactualFemaleHumansInterleukin-8Kaplan-Meier EstimateLiver NeoplasmsMaleMiddle AgedNeoplasm StagingProportional Hazards ModelsChemokine CXCL12Interleukin-8Syk Kinase

Identifiers

PMID32730361
PMCPMC7392298

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.