Clinical Usefulness of Human Epididymis Protein 4 in Lung Cancer

HE4-based nomogram for predicting overall survival in patients with idiopathic pulmonary fibrosis: construction and validation

Idiopathic pulmonary fibrosis (IPF) is a life-threatening interstitial lung disease. Identifying biomarkers for early diagnosis is of great clinical importance. The epididymis protein 4 (HE4) is important in the process of inflammation and fibrosis in the epididymis. Its prognostic value in IPF, however, has not been studied. The mRNA and protein levels of HE4 were used to determine the prognostic value in different patient cohorts. In this study, prognostic nomograms were generated based on the results of the cox regression analysis. We identified the HE4 protein level increased in IPF patients, but not the HE4 gene expression. The increased expression of HE4 correlated positively with a poor prognosis for patients with IPF. The HR and 95% CI were 2.62 (1.61-4.24) (p < 0.001) in the training set. We constructed a model based on the risk-score = 0.16222182 * HE4 + 0/0.37580659/1.05003609 (for GAP index 0-3/4-5/6-8) + (- 1.1183375). In both training and validation sets, high-risk patients had poor prognoses (HR: 3.49, 95%CI 2.10-5.80, p = 0.001) and higher likelihood of dying (HR: 6.00, 95%CI 2.04-17.67, p = 0.001). Analyses of calibration curves and decision curves suggest that the method is effective in predicting outcomes. Furthermore, a similar formulation was used in a protein-based model based on HE4 that also showed prognostic value when applied to IPF patients. Accordingly, HE4 is an independent poor prognosis factor, and it has the potential to predict IPF patient survival.

Bibliometric and visualized analysis of applying tumor markers in lung cancer diagnosis from 2000 to 2022

Background

Lung cancer (LC) is the leading cause of cancer-related deaths worldwide. Tumor marker (TM) detection can indicate the existence and growth of a tumor and has therefore been used extensively for diagnosing LC. Here, we conducted a bibliometric analysis to examine TM-related publications for LC diagnosis to illustrate the current state and future trends of this field, as well as to identify additional promising TMs with high sensitivity.

Methods

Publications regarding TMs in LC diagnosis were downloaded from the Web of Science Core Collection. CiteSpace was applied to perform a bibliometric analysis of journals, cocitation authors, keywords, and references related to this field. VOSviewer was used to generate concise diagrams about countries, institutions, authors, and keywords. Changes in the TM research frontier were analyzed through citation burst detection.

Results

A total of 990 studies were analyzed in this work. The collaboration network analysis revealed that the People's Republic of China, Yonsei University, and Molina R were the most productive country, institution, and scholar, respectively. Additionally, Molina R was the author with the most citations. The National Natural Science Foundation of China was the largest funding source. "Carcinoembryonic antigen (CEA) as tumor marker in lung cancer" was the top reference with the most citations, Lung Cancer was the core journal, and "serum tumor marker" experienced a citation burst over the past 5 years.

Conclusion

This bibliometric analysis of TMs in LC diagnosis presents the current trends and frontiers in this field. We summarized the research status of this field and the methods to improve the diagnostic efficacy of traditional serum TMs, as well as provided new directions and ideas for improving the LC clinical detection rate. Priority should be given to the transformation of computer-assisted diagnostic technology for clinical applications. In addition, circulating tumor cells, exosomes, and microRNAs were the current most cutting-edge TMs.

The investigation of levels of endothelial cell-specific molecule, progranuline, clusterin, and human epididymis protein 4 in the differential diagnosis of malignant pleural effusions

BACKGROUND

Progranulin (PGRN), endothelial cell-specific molecule-1, clusterin (CLU), and human epididymis protein 4 (HE-4) are novel proteins reported to have diagnostic and prognostic potential in lung cancer. Here, we aimed to identify the markers with high sensitivity and specificity in distinguishing malignant pleural fluids from other pleural fluids.

METHODS

This prospective, descriptive study was conducted at a medical faculty hospital between 2016 and 2019. The study population consisted of 90 patients <18 years of age with pleural effusion (PE). Levels of pleural fluids of PGRN, endothelial cell-specific molecule-1, CLU, and HE-4 were measured with enzyme-linked immunosorbent assay kits under the manufacturer's manual.

RESULTS

Of 90 patients, 54 were men, and 36 were women (mean age 65 ± 16 years). Of pleural fluids investigated, 23 (25%) and 67 (74%) were transudates and exudates, respectively. Of exudates, while 27 (40%) and 19 (28%) were parapneumonic PE and tuberculous PE, respectively, 20 (29%) were malignant pleural effusion (MPE). Levels of all biomarkers in exudate fluids were found significantly higher than those of transudate fluids. CLU, HE-4, and PGRN levels in MPE were also found significantly higher than benign fluids (P < .05). Cutoff values were achieved by receiver operating characteristics analysis for CLU, HE-4, and PGRN to distinguish between malignant and benign groups. For diagnosis of MPE, the sensitivity and specificity values were found as 0.66 and 0.67 for a cutoff value of CLU of 18.29 mg/L (P = .00), as 0.76 and 0.76 for a cutoff value of HE-4 of 9.33 mg/L (P = .00), and as 0.66 and 0.67 for a cutoff value of PGRN of 105.91 mg/L (P = .001).

CONCLUSION

HE-4 having high sensitivity and specificity can be a potential diagnostic marker in distinguishing between malignant and benign effusions, and these findings can constitute a basis for future research.

Serum CA125 and HE4 as Biomarkers for the Detection of Endometrial Cancer and Associated High-Risk Features

Early detection of endometrial cancer improves survival. Non-invasive diagnostic biomarkers would improve triage of symptomatic women for investigations. This study aimed to determine the diagnostic accuracy of serum Cancer Antigen 125 (CA125) and Human Epididymis 4 (HE4) for endometrial cancer and associated high-risk features. Serum samples from women investigated for gynaecological symptoms or diagnosed with endometrial cancer were analysed for CA125 and HE4. Conventional diagnostic metrics were calculated. In total, 755 women were included; 397 had endometrial cancer. Serum CA125 and HE4 were significantly elevated in cases compared with controls (both p < 0.001), and with pathological markers of disease severity (p < 0.05). A combination of CA125 and HE4 detected endometrial cancer with an area under the curve (AUC) of 0.77 (95% CI: 0.74−0.81). In a model with body mass index (BMI) and parity, HE4 predicted endometrial cancer in pre-menopausal women with an AUC of 0.91 [sensitivity = 84.5%, specificity = 80.9% (p < 0.001)]. In women with abnormal ultrasound, HE4 ≥ 77 pmol/L improved specificity compared with imaging alone [68.6% (95% CI: 75.0−83.6) vs. 34.4% (95% CI: 27.1−42.3), respectively], but at a cost to sensitivity. HE4 ≥ 77 pmol/L improved the detection of myometrial invasion ≥50% in women with stage I disease compared with magnetic resonance imaging (MRI) alone [sensitivity = 100% (95% CI: 54.1−100)]. CA125 ≥ 35 U/mL did not add to imaging. HE4 is a good predictor of poor prognostic features which could assist staging investigations.

Prognostic Modeling of Lung Adenocarcinoma Based on Hypoxia and Ferroptosis-Related Genes

Background. It is well known that hypoxia and ferroptosis are intimately connected with tumor development. The purpose of this investigation was to identify whether they have a prognostic signature. To this end, genes related to hypoxia and ferroptosis scores were investigated using bioinformatics analysis to stratify the risk of lung adenocarcinoma. Methods. Hypoxia and ferroptosis scores were estimated using The Cancer Genome Atlas (TCGA) database-derived cohort transcriptome profiles via the single sample gene set enrichment analysis (ssGSEA) algorithm. The candidate genes associated with hypoxia and ferroptosis scores were identified using weighted correlation network analysis (WGCNA) and differential expression analysis. The prognostic genes in this study were discovered using the Cox regression (CR) model in conjunction with the LASSO method, which was then utilized to create a prognostic signature. The efficacy, accuracy, and clinical value of the prognostic model were evaluated using an independent validation cohort, Receiver Operator Characteristic (ROC) curve, and nomogram. The analysis of function and immune cell infiltration was also carried out. Results. Here, we appraised 152 candidate genes expressed not the same, which were related to hypoxia and ferroptosis for prognostic modeling in The Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) cohort, and these genes were further validated in the GSE31210 cohort. We found that the 14-gene-based prognostic model, utilizing MAPK4, TNS4, WFDC2, FSTL3, ITGA2, KLK11, PHLDB2, VGLL3, SNX30, KCNQ3, SMAD9, ANGPTL4, LAMA3, and STK32A, performed well in predicting the prognosis in lung adenocarcinoma. ROC and nomogram analyses showed that risk scores based on prognostic signatures provided desirable predictive accuracy and clinical utility. Moreover, gene set variance analysis showed differential enrichment of 33 hallmark gene sets between different risk groups. Additionally, our results indicated that a higher risk score will lead to more fibroblasts and activated CD4 T  cells but fewer myeloid dendritic cells, endothelial cells, eosinophils, immature dendritic cells, and neutrophils. Conclusion. Our research found a 14-gene signature and established a nomogram that accurately predicted the prognosis in patients with lung adenocarcinoma. Clinical decision-making and therapeutic customization may benefit from these results, which may serve as a valuable reference in the future.

The Role of Human Epididymis Protein 4 in the Diagnosis and Prognosis of Diseases: An Umbrella Review of Systematic Reviews and Meta-Analyses of Observational Studies

Background

The application of human epididymis protein 4 (HE4) in diverse health diseases, especially in cancers, has been extensively studied in recent decades. To summarize the existing evidence of the aforementioned topic, we conducted an umbrella review to systematically evaluate the reliability and strength of evidence regarding the role of HE4 in the diagnostic and prognostic estimate of diverse diseases.

Methods

Electronic searches in PubMed, Web of Science, and Embase databases were conducted from inception to September 16, 2021, for meta-analyses, which focus on the role of HE4 in the diagnosis and prognosis of diseases. This study protocol has been registered at PROSPERO (CRD42021284737). We collected the meta-analysis effect size of sensitivity, specificity, positive predictive value, and negative predictive value from diagnostic studies and gathered the hazard ratio (HR) of disease-free survival, overall survival, and progression-free survival from prognostic studies. For each systematic review and meta-analysis, we used a measurable tool for evaluating systematic reviews and meta-analysis (AMSTAR) to evaluate the methodological quality. Additionally, we assessed the quality of evidence on estimating the ability of HE4 in the diagnosis and prognosis of diverse diseases by the Grading of Recommendations Assessment, Development and Evaluation (GRADE) guideline.

Results

Overall, 20 meta-analyses including a total of 331 primary studies of different diseases were examined, mainly including ovarian cancer (OC) (n = 9), endometrial cancer (EC) (n = 6), and lung cancer (LC) (n = 4). The methodological qualities of all studies were rated as moderate (45%) or high (55%) by the AMSTAR. According to the GRADE, the certainties of 18 diagnostic pieces of evidence (9 for sensitivity and 9 for specificity) were rated as moderate (34%), low (33%), and very low (33%). Moreover, outcomes from prognosis studies showed evidence (1 for disease-free survival) with high certainty in regard to cancers (such as EC, OC, and LC) with the remaining three being moderate.

Conclusion

This umbrella review suggested that HE4 was a favored biomarker in the prognosis of cancers, which was supported by high certainty of evidence. Additionally, HE4 could provide a suitable method for the diagnosis of EC, OC, and LC with moderate certainty evidence. Further large prospective cohort studies are needed to better elucidate the diagnostic and prognostic role of HE4 in diseases.

Human epididymis protein 4 is a new biomarker to predict the prognosis of progressive fibrosing interstitial lung disease

BACKGROUND

The clinical course and prognosis of progressive fibrosing interstitial lung diseases (PF-ILDs) vary between individuals. Notably, predictive serum biomarkers for disease management are needed. Serum human epididymis protein 4 (HE4) is reportedly elevated in patients with idiopathic pulmonary fibrosis (IPF); however, its clinical utility remains unknown. We evaluated the potential of serum HE4 as a biomarker for patients with PF-ILD.

METHODS

Serum HE4 was measured in a retrospective study consisting of 34 patients with PF-ILD and 40 healthy volunteers. The relationship between serum HE4 levels and clinical parameters or prognosis was investigated. To validate the significance of results obtained, a prospective observational study was performed in 37 patients presenting PF-ILD and 40 control patients without PF-ILD.

RESULTS

Serum HE4 levels were higher in patients with PF-ILD than in healthy volunteers (P < 0.01). Moreover, serum HE4 levels correlated with the extent of honeycombing on chest high-resolution computed tomography (r = 0.41, P = 0.015). In multivariate analysis using the Cox proportional hazard model, higher HE4 levels (>238 pmol/L) were associated with an elevated mortality risk; hazard ratio (HR) 7.27, 95% CI 1.56-34.0, P = 0.01 in the derivation cohort; HR 44.3, 95% CI 4.19-468, P < 0.01 in validation cohort.

CONCLUSIONS

Serum HE4 levels may serve as a new diagnostic and prognostic biomarker for patients with PF-ILD.

A Prognostic Nomogram Combining Immune-Related Gene Signature and Clinical Factors Predicts Survival in Patients With Lung Adenocarcinoma

The existence of tumor heterogeneity and complex carcinogenic mechanisms in lung adenocarcinoma (LUAD) make the most commonly used TNM staging system unable to well-interpret the prognosis of patients. Using transcriptome profiling and clinical data from The Cancer Genome Atlas (TCGA) database, we constructed an immune signature based on a multivariate Cox analysis (stepwise model). We estimated the half-maximal inhibitory concentration (IC50) of chemotherapeutic drugs in patients according to the pRRophetic algorithm. Gene-set variation analysis (GSVA) was used to reveal pathway enrichment between groups. Moreover, immune microenvironment landscape was described by single-sample gene-set enrichment analysis (ssGSEA) and CIBERSORT and systematically correlated with genomic of these patients. A prognostic nomogram combining the immune signature and TNM stage to predict the prognosis was developed by multivariate Cox regression. The novel signature with four immune-related genes (MAL, MS4A1, OAS1, and WFDC2) had good robustness, which can accurately distinguish between high- and low-risk patients. Compared with low-risk patients, high-risk patients with a worse prognosis (5-year OS: 46.5 vs. 59.4%, p = 0.002) could benefit more from immunotherapy and the application of common chemotherapeutic agents such as cisplatin and paclitaxel (Wilcoxon test, all p < 0.05). There were significant differences in tumor immune microenvironment and metabolic pathways between the two groups. Additionally, the constructed nomogram had reliable predictive performance with the C-index of 0.725 (95% CI = 0.668–0.781) in the development set (n = 500), 0.793 (95% CI = 0.728–0.858) in the internal validation set (n = 250) and 0.679 (95% CI = 0.644–0.714) in the external validation set (n = 442). The corresponding calibration curves also showed good consistency. To sum up, we developed an immune-related gene signature and comprehensively evaluated LUAD immune landscape and metabolic pathways. Effective differentiation of high- and low-risk patients and accurate construction of nomogram would be helpful to the development of individualized treatment strategies.

Diagnostic accuracy of human epididymis secretory protein 4 for lung cancer: a systematic review and meta-analysis

Background

Several studies have assessed the diagnostic accuracy of serum human epididymis secretory protein 4 (HE4) for lung cancer, but their results were heterogeneous. The aim of this study was to systematically review the available studies and pool their results using meta-analysis.

Methods

PubMed, EMBASE and Web of Science databases were searched up to January 1, 2019 to identify studies investigating the diagnostic accuracy of HE4 for lung cancer. We assessed the quality of eligible studies with the revised Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. The overall diagnostic sensitivity, specificity, positive and negative likelihood ratios were pooled using a bivariate model. Deeks's test was applied to detect the degree of publication bias.

Results

A total of 16 studies with 18 cohorts (1,756 lung cancers and 1,446 controls) were included. HE4 had a pooled sensitivity of 0.65 (95% CI: 0.54-0.75), specificity of 0.88 (95% CI: 0.82-0.92), positive likelihood ration of 5.3 (95% CI: 3.7-7.6) and negative likelihood ratio of 0.40 (95% CI: 0.30-0.52). Patient selection bias and partial verification bias were the major design weaknesses of available studies. No publication bias was observed.

Conclusions

HE4 has moderate diagnostic accuracy for lung cancer. Its result should be interpreted in parallel with clinical findings and the results of other conventional tests. Further studies are still needed to rigorously evaluate the diagnostic accuracy of HE4 for lung cancer.

Human epididymis protein 4 (HE4) protects against cystic pulmonary fibrosis associated-inflammation through inhibition of NF-κB and MAPK singnaling

BACKGROUND

Cystic pulmonary fibrosis (CF) affects mostly the lung of the newborns. Chronic infection and inflammation become the major causes of morbidity and mortality in CF. However, the underlying molecular mechanisms causing CF still remain unclear.

METHODS

ELISA assay was used to examine the expression of HE4 and pro-inflammatory cytokines in W126VA4 cells supernatant fluid. qRT-PCR was applicable to determine the mRNA level of HE4, α-SMA, collagen 1, MMP2, MMP9 and various interleukins. Immunofluorescent assay was used to test the expression of HE4 in WI-26 VA4 cells. Major elements of MAPK and NF-κB signals pathways were examined by western blot.

RESULTS

We found higher expression of HE4 in CF patients serum and lung biopsy. Interestingly, HE4 expression was positively correlated with fibrosis markers expression. In addition,HE4 overexpression increased inflammatory cytokines secretion and fibrosis markers expression in WI-26 VA4 cells. And NF-κB pathways were responsible for elevated inflammation. In addition, HE4/MAPK/MMPs signaling cascades destroyed the normal extracellular matrix (ECM) and promoted fibrosis.

CONCLUSIONS

Overall, we first identified that HE4 promoted CF-associated inflammation. Additionally, NF-κB and MAPK signalings were further validated to be responsible for CF-associated inflammation and ECM destruction. Characterization of lumacaftor/ivacaftor in CF-associated inflammation may provide a novel insight into clinical CF treatment.

Comparison of Four Automated Carcinoembryonic Antigen Immunoassays: ADVIA Centaur XP, ARCHITECT I2000sr, Elecsys E170, and Unicel Dxi800

Background

Carcinoembryonic antigen (CEA) is one of the tumor markers available for evaluating disease progression status after initial therapy and monitoring subsequent treatment modalities in colorectal, gastrointestinal, lung, and breast carcinoma. We evaluated the correlations and differences between widely used, automated CEA immunoassays at four different medical laboratories.

Methods

In total, 393 serum samples with CEA ranging from 3.0 to 1,000 ng/mL were analyzed on ADVIA Centaur XP (Siemens Diagnostics, Tarrytown, NY, USA), ARCHITECT i2000sr (Abbott Diagnostics, Abbott Park, IL, USA), Elecsys E170 (Roche Diagnostics, Indianapolis, IN, USA), and Unicel DxI800 (Beckman Coulter, Fullerton, CA, USA), and the results were compared. Deming regression, Passing-Bablok regression, and Bland-Altman analyses were performed to evaluate the data correlation and % differences among these assays.

Results

Deming regression analysis of data from Elecsys E170 and UniCel DxI800 showed good correlation (y=3.1615+0.8970x). According to Bland-Altman plot, no statistically significant bias (−1.78 ng/mL [95% confidence interval: −4.02 to 0.46]) was observed between Elecsys E170 and UniCel DxI800. However, the relative differences of CEA concentrations between assays exceeded the acceptable limit of 30%. Regarding the agreement of positivity with cut-off value 5.0 ng/mL, ARCHITECT i2000sr and Elecsys E170 showed the highest agreement (95.2%), whereas ADVIA Centaur XP and ARCHITECT i2000sr showed the lowest agreement (70.7%).

Conclusions

Agreements between automated CEA immunoassays are variable, and individual CEA concentrations may differ significantly between assays. Standardization of serum CEA concentrations and further harmonization are needed.