History, molecular features, and clinical importance of conventional serum biomarkers in lung cancer

Analysis of influencing factors of serum SCCA elevation in 309 CAP patients with normal CEA,NSE and CYFRA21-1

Introduction

Squamous cell carcinoma antigen (SCCA) is one of the auxiliary diagnostic indicators of lung squamous cell carcinoma, and an increase in serum SCCA can predict the occurrence of lung squamous cell carcinoma. However, whether SCCA is also elevated in pneumonia patients without malignancy is still not clear. Therefore, we studied influencing factors of elevated serum SCCA in patients with community-acquired pneumonia.

Methods

We retrospectively enrolled 309 patients who were admitted to the Respiratory department with normal serum Carcinoembryonic antigen (CEA), Neuron specific enolase (NSE), and Cytokeratin 19 fragment (CYFRA21-1) level and were diagnosed with community-acquired pneumonia (CAP). The patients' serum SCCA level, body temperature, age, sex, white blood cell (WBC) count, hypersensitive C-reactive protein (Hs-CRP) level, and serum amyloid A (SAA) were recorded. Logistic regression models were used to analyze the risk factors of SCCA elevation. The dose-response relationship between temperature and risk of SCCA increase was analyzed using Restricted cubic splines (RCS).

Results

Of the 309 patients, 143(46.3%) showed elevated SCCA levels. The logistic regression analysis revealed a significant influence of age and body temperature on elevated SCCA (P<0.05) levels. For every one-year increase in age, the probability of elevated SCCA decreased by 3% [OR=0.97,95%CI:0.95,0.99].For every 1°C increase in body temperature, the risk of elevated SCCA increased by 2.75 times [OR=3.75,95%CI:2.55,5.49].The patients were sorted into quartiles based on body temperature. Compared with patients in the Q1 of body temperature group, patients in the Q3 group were at 7.92 times higher risk [OR=7.92, 95%CI:3.27,19.16].and the risk of elevated SCCA was increased by 22.85 times in the Q4 group [OR=23.85,95%CI:8.38,67.89] after adjusting for age, gender, Hs-CRP, SAA, and WBC. RCS analysis showed there was a linear relationship between temperature index and risk of elevated SCCA.

Conclusion

In summary, for CAP patients with normal CEA,NSE and CYFRA21-1 level, age and body temperature are influencing factors of SCCA elevation. Higher body temperature has a strong association with the occurrence of SCCA elevation.

A combination of radiomic features, clinic characteristics, and serum tumor biomarkers to predict the possibility of the micropapillary/solid component of lung adenocarcinoma

BACKGROUND

Invasive lung adenocarcinoma with MPP/SOL components has a poor prognosis and often shows a tendency to recurrence and metastasis. This poor prognosis may require adjustment of treatment strategies. Preoperative identification is essential for decision-making for subsequent treatment.

OBJECTIVE

This study aimed to preoperatively predict the probability of MPP/SOL components in lung adenocarcinomas by a comprehensive model that includes radiomics features, clinical characteristics, and serum tumor biomarkers.

DESIGN

A retrospective case control, diagnostic accuracy study.

METHODS

This study retrospectively recruited 273 patients (males: females, 130: 143; mean age ± standard deviation, 63.29 ± 10.03 years; range 21-83 years) who underwent resection of invasive lung adenocarcinoma. Sixty-one patients (22.3%) were diagnosed with lung adenocarcinoma with MPP/SOL components. Radiomic features were extracted from CT before surgery. Clinical, radiomic, and combined models were developed using the logistic regression algorithm. The clinical and radiomic signatures were integrated into a nomogram. The diagnostic performance of the models was evaluated using the area under the curve (AUC). Studies were scored according to the Radiomics Quality Score and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines.

RESULTS

The radiomics model achieved the best AUC values of 0.858 and 0.822 in the training and test cohort, respectively. Tumor size (T_size), solid tumor size (ST_size), consolidation-to-tumor ratio (CTR), years of smoking, CYFRA 21-1, and squamous cell carcinoma antigen were used to construct the clinical model. The clinical model achieved AUC values of 0.741 and 0.705 in the training and test cohort, respectively. The nomogram showed higher AUCs of 0.894 and 0.843 in the training and test cohort, respectively.

CONCLUSION

This study has developed and validated a combined nomogram, a visual tool that integrates CT radiomics features with clinical indicators and serum tumor biomarkers. This innovative model facilitates the differentiation of micropapillary or solid components within lung adenocarcinoma and achieves a higher AUC, indicating superior predictive accuracy.

A prognostic baseline blood biomarker and tumor growth kinetics integrated model in paclitaxel/platinum treated advanced non-small cell lung cancer patients

Paclitaxel/platinum chemotherapy, the backbone of standard first-line treatment of advanced non-small cell lung cancer (NSCLC), exhibits high interpatient variability in treatment response and high toxicity burden. Baseline blood biomarker concentrations and tumor size (sum of diameters) at week 8 relative to baseline (RS8) are widely investigated prognostic factors. However, joint analysis of data on demographic/clinical characteristics, blood biomarker levels, and chemotherapy exposure-driven early tumor response for improved prediction of overall survival (OS) is clinically not established. We developed a Weibull time-to-event model to predict OS, leveraging data from 365 patients receiving paclitaxel/platinum combination chemotherapy once every three weeks for ≤six cycles. A developed tumor growth inhibition model, combining linear tumor growth and first-order paclitaxel area under the concentration-time curve-induced tumor decay, was used to derive individual RS8. The median model-derived RS8 in all patients was a 20.0% tumor size reduction (range from -78% to +15%). Whereas baseline carcinoembryonic antigen, cytokeratin fragments, and thyroid stimulating hormone levels were not significantly associated with OS in a subset of 221 patients, and lactate dehydrogenase, interleukin-6 and neutrophil-to-lymphocyte ratio levels were significant only in univariate analyses (p value < 0.05); C-reactive protein (CRP) in combination with RS8 most significantly affected OS (p value < 0.01). Compared to the median population OS of 11.3 months, OS was 128% longer at the 5th percentile levels of both covariates and 60% shorter at their 95th percentiles levels. The combined paclitaxel exposure-driven RS8 and baseline blood CRP concentrations enables early individual prognostic predictions for different paclitaxel dosing regimens, forming the basis for treatment decision and optimizing paclitaxel/platinum-based advanced NSCLC chemotherapy.

Clinical Efficacy and Safety of First- or Second-Generation EGFR-TKIs after Osimertinib Resistance for EGFR Mutated Lung Cancer: A Prospective Exploratory Study

BACKGROUND

Osimertinib monotherapy is a common treatment for epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC); however, standard treatment strategies for acquired resistance to this drug have not been established. In addition, the clinical significance of first-generation (1G) or second-generation (2G) EGFR-tyrosine kinase inhibitors (TKI) in patients with EGFR-mutant NSCLC and osimertinib resistance has not yet been fully evaluated.

OBJECTIVE

We aimed to conduct a prospective multicenter observational study to evaluate the efficacy and safety of 1G and 2G EGFR-TKIs after the development of osimertinib resistance.

METHODS

Patients with EGFR-mutant NSCLC who received 1G or 2G EGFR-TKIs after developing resistance to osimertinib monotherapy were prospectively assessed at eight institutions in Japan. The primary endpoint was progression-free survival (PFS).

RESULTS

A total of 29 patients with advanced or recurrent EGFR-mutant NSCLC were analyzed. The objective response and disease control rates were 6.9% (2/29) and 58.6% (17/29), respectively. The median PFS was 1.9 months [95% confidence interval (CI): 1.3-5.3]. There was no significant difference in PFS between the 1G and 2G EGFR-TKI groups (3.7 versus 1.5 months, log-rank test p = 0.20). However, patients with normal cytokeratin 19 fragment (CYFRA 21-1) and pro-gastrin-releasing peptide (ProGRP) levels experienced longer PFS than those with elevated CYFRA 21-1 and/or ProGRP (5.5 versus 1.3 months, log-rank test p < 0.001).

CONCLUSION

Administration of 1G or 2G EGFR-TKIs after the development of osimertinib resistance has limited efficacy in patients with EGFR-mutant NSCLC. Moreover, normal CYFRA 21-1 and ProGRP levels could be promising indicators for 1G and 2G EGFR-TKI administration after osimertinib resistance development.

TRIAL REGISTRATION NUMBER

UMIN000044049.

Update value and clinical application of MUC16 (cancer antigen 125)

INTRODUCTION

The largest transmembrane mucin, mucin 16 (MUC16), contains abundant glycosylation sites on the molecular surface, allowing it to participate in various molecular pathways. When cells lose polarity and become cancerous, MUC16 is overexpressed, and more of the extracellular region (cancer antigen [CA]125) is released into serum and possibly, promote the development of diseases. Thus, MUC16 plays an indispensable role in clinical research and application.

AREAS COVERED

This review summarizes the update proposed role of MUC16 in carcinogenesis and metastasis. Most importantly, we prospect its potential value in targeted therapy after screening 1226 articles published within the last 10 years from PubMed. Two reviewers screened each record and each report retrieved independently. We have summarized the progress of MUC16/CA125 in basic research and clinical application, and predicted its possible future development directions.

EXPERT OPINION

As an important noninvasive co-factor in the diagnosis of gynecological diseases, MUC16 has been used for a long time, especially in the diagnosis and treatment of ovarian cancer. The overexpression of MUC16 plays a very obvious role in regulating inflammatory response, supporting immune suppression, and promoting the proliferation, division, and metastasis of cancer cells. In the next 20 years, there will be a luxuriant clinical application of MUC16 as a target for immune monitoring and immunotherapy.

Artificial neural network-based diagnostic models for lung cancer combining conventional indicators with tumor markers

This study set out to establish a lung cancer diagnosis and prediction model uses conventional laboratory indicators combined with tumor markers, so as to help early screening and auxiliary diagnosis of lung cancer through a convenient, fast, and cheap way, and improve the early diagnosis rate of lung cancer. A total of 221 patients with lung cancer, 100 patients with benign pulmonary diseases, and 184 healthy subjects were retrospectively studied. General clinical data, the results of conventional laboratory indicators, and tumor markers were collected. Statistical Product and Service Solutions 26.0 was used for data analysis. The diagnosis and prediction model of lung cancer was established by artificial neural network - multilayer perceptron. After correlation and difference analysis, five comparison groups (lung cancer-benign lung disease group, lung cancer-health group, benign lung disease-health group, early-stage lung cancer-benign lung disease group, and early-stage lung cancer-health group) obtained 5, 28, 25, 16, and 25 valuable indicators for predicting lung cancer or benign lung disease, and then established five diagnostic prediction models, respectively. The area under the curve (AUC) of each combined diagnostic prediction model (0.848, 0.989, 0.949, 0.841, and 0.976) was higher than that of the diagnostic prediction model established only using tumor markers (0.799, 0.941, 0.830, 0.661, and 0.850), and the difference in the lung cancer-health group, the benign lung disease-health group, the early-stage lung cancer-benign lung disease group, and early-stage lung cancer-health group was statistically significant (P < 0.05). The artificial neural network-based diagnostic models for lung cancer combining conventional indicators with tumor markers have high performance and clinical significance in assisting the diagnosis of early lung cancer.

Early detection of lung cancer in a real-world cohort via tumor-associated immune autoantibody and imaging combination

Background

Efficient early detection methods for lung cancer can significantly decrease patient mortality. One promising approach is the use of tumor-associated autoantibodies (TAABs) as a diagnostic tool. In this study, the researchers aimed to evaluate the potential of seven TAABs in detecting lung cancer within a population undergoing routine health examinations. The results of this study could provide valuable insights into the utility of TAABs for lung cancer screening and diagnosis.

Methods

In this study, the serum concentrations of specific antibodies were measured using enzyme-linked immunosorbent assay (ELISA) in a cohort of 15,430 subjects. The efficacy of both a 7-TAAB panel and LDCT for lung cancer detection were evaluated through receiver operating characteristic (ROC) analyses, with sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) being assessed and compared. These results could have significant implications for the development of improved screening methods for lung cancer.

Results

Over the 12-month observation period, 26 individuals were diagnosed with lung cancer. The 7-TAAB panel demonstrated promising sensitivity (61.5%) and a high degree of specificity (88.5%). The panel’s area under the receiver operating characteristic (ROC) curve was 0.8062, which was superior to that of any individual TAAB. In stage I patients, the sensitivity of the panel was 50%. In our cohort, there was no gender or age bias observed. This 7-TAAB panel showed a sensitivity of approximately 60% in detecting lung cancer, regardless of histological subtype or lesion size. Notably, ground-glass nodules had a higher diagnostic rate than solid nodules (83.3% vs. 36.4%, P = 0.021). The ROC analyses further revealed that the combination of LDCT with the 7-TAAB assay exhibited a significantly superior diagnostic efficacy than LDCT alone.

Conclusion

In the context of the study, it was demonstrated that the 7-TAAB panel showed improved detective efficacy of LDCT, thus serving as an effective aid for the detection of lung cancer in real-world scenarios.

Relationships between squamous cell carcinoma antigen and cytokeratin 19 fragment values and renal function in oral cancer patients

Squamous cell carcinoma antigen (SCC-Ag) and cytokeratin 19 fragment (CYFRA) are used to screen and monitor oral cancer patients. However, recent studies have reported that tumour markers become elevated as renal function decreases, regardless of tumour progression. A retrospective study was performed of 423 oral cancer patients who underwent blood testing for these tumour markers and other blood analytes during a 10-year period. The values of SCC-Ag and CYFRA increased significantly with decreasing renal function (P < 0.01), and the values were abnormal at a median 2.6 ng/ml for SCC-Ag and 4.7 ng/ml for CYFRA in the group with estimated glomerular filtration rate (eGFR) values of< 30 ml/min/1.73 m². The factors that were related to the variation in tumour markers were albumin and creatinine. The cut-off values of eGFR were 59.7 ml/min/1.73 m² for SCC-Ag and 63.6 ml/min/1.73 m² for CYFRA, and the cut-off age when the tumour markers might rise due to the effect of renal function were 72 years for SCC-Ag and 73 years for CYFRA. In conclusion, decreased renal function should be taken into account when evaluating tumour markers in oral cancer. In addition, tumour markers are likely to be overestimated in patients over the age of 72-73 years.

The rational application of liquid biopsy based on next-generation sequencing in advanced non-small cell lung cancer

BACKGROUND

Plasma and tissue biopsy have both used for targeting actionable driver gene mutations in lung cancer, whose concordance is imperfect. A reliable method to predict the concordance is urgently needed to ease clinical application.

METHODS

A total of 1012 plasma samples, including 519 with paired-tissue biopsy samples, derived from lung adenocarcinoma patients were retrospectively enrolled. We assessed the associations of several clinicopathological characteristics and serum tumor markers with the concordance between plasma and tissue biopsies.

RESULTS

When carcinoembryonic antigen (CEA) levels were higher than thresholds of 15.01 ng/ml and 51.15 ng/ml, the positive predictive value of concordance reached 90% and 95%, respectively. When CEA levels were lower than thresholds of 5.19 ng/ml and 3.26 ng/mL, the negative predictive value of concordance reached 45% and 50%. The performance of CYFRA21-1 in predicting concordance was similar but inferior to CEA (AUC: 0.727 vs. 0.741, p = 0.633). The performance of CEA combined with CYFRA21-1 in predicting the concordance was similar to that of the combination of independent factors derived from the LASSO regression model (AUC: 0.796 vs. 0.818, p = 0.067). CEA (r = 0.47, p < 0.01) and CYFRA21-1 levels (r = 0.45, p < 0.05) were significantly correlated with the maximum variant allele frequency, respectively.

CONCLUSIONS

CEA combined with CYFRA21-1 could effectively predict the concordance between plasma and tissue biopsies, which could be used for evaluating the priority of plasma and tissue biopsies for gene testing to timely guide clinical applications in advanced lung adenocarcinoma patients.

A Combination of Radiomic Features, Imaging Characteristics, and Serum Tumor Biomarkers to Predict the Possibility of the High-Grade Subtypes of Lung Adenocarcinoma

RATIONALE AND OBJECTIVES

Lung adenocarcinomas (LADC) containing high-grade subtypes have a poorer prognosis. And some studies have shown that high-grade subtypes have been identified as an independent predictor of local recurrence in patients treated with limited resection. The aim of this study was to construct a combined model based on radiomic features, imaging characteristics and serum tumor biomarkers to predict the possibility of preoperative high-grade subtypes.

MATERIALS AND METHODS

156 patients with LADC were retrospectively recruited in this study. These patients were randomly divided into training and validation cohorts. Radiomics features and imaging characteristics were extracted from plain CT images. A nomogram was developed in a training cohort by univariate and multivariate logistic analysis, and its performance was evaluated by receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) in the training and validation cohorts.

RESULTS

A total of 1316 radiomic features were extracted from the lesions in plain chest CT images. After applying the mRMR algorithm and the LASSO regression, 4 features were retained. Based on these radiomic features, Radiomic score (Radscore) was calculated for each patient. Spiculation, air bronchogram sign, CYFRA 21-1 and Radscore had been used in the construction of the combined model. The AUC of the combined model was respectively 0.88 (95% CI, 0.82-0.95) and 0.94 (95% CI, 0.86-1.00) in the training and validation cohorts.

CONCLUSION

The combined model based on CT images and serum tumor biomarkers, can predict the high-grade subtypes of LADC in a non-invasive manner, which may influence individual treatment planning, such as the choice of surgical approach and postoperative adjuvant therapy.

Non-Targeted Serum Lipidomics Analysis and Potential Biomarkers of Laryngeal Cancer Based on UHPLC-QTOF-MS

Laryngeal cancer is a common head and neck malignant cancer type. However, effective biomarkers for diagnosis are lacking and pathogenesis is unclear. Lipidomics is a powerful tool for identifying biomarkers and explaining disease mechanisms. Hence, in this study, non-targeted lipidomics based on ultra-performance liquid chromatography-quadrupole time of flight-mass spectrometry (UHPLC-QTOF-MS) were applied to screen the differential lipid metabolites in serum and allowed for exploration of the remodeled lipid metabolism of laryngeal cancer, laryngeal benign tumor patients, and healthy crowds. Multivariate analysis and univariate analysis were combined to screen for differential lipid metabolites among the three groups. The results showed that, across a total of 57 lipid metabolic markers that were screened, the regulation of the lipid metabolism network occurred mainly in phosphatidylcholine (PC), lysophosphatidylcholine (LPC), and sphingomyelin (SM) metabolism. Of note, the concentration levels of sphingolipids 42:2 (SM 42:2) and sphingolipids 42:3 (SM 42:3) correlated with laryngeal cancer progression and were both significantly different among the three groups. Both of them could be considered as potential biomarkers for diagnosis and indicators for monitoring the progression of laryngeal cancer. From the perspective of lipidomics, this study not only revealed the regulatory changes in the lipid metabolism network, but also provided a new possibility for screening biomarkers in laryngeal cancer.

Association of CEA, NSE, CYFRA 21-1, SCC-Ag, and ProGRP with Clinicopathological Characteristics and Chemotherapeutic Outcomes of Lung Cancer

Objective

The aim of this study was to investigate the association of serum carcinoembryonic antigen (CEA), nerve-specific enolase (NSE), cytokeratin 19 fragment (CYFRA21-1), squamous cell carcinoma antigen (SCC-Ag), and pro-gastrin-releasing peptide (ProGRP) with the clinicopathological characteristics and chemotherapeutic outcomes of patients with lung cancer.

Methods

A total of 189 patients with lung cancer (lung cancer group) diagnosed at the Fourth Affiliated Hospital of Anhui Medical University from January 2020 to December 2021 were included. During the same period, 199 patients with benign lung disorders were included as the benign lung disease group and 75 healthy people were selected as the control group. The serum concentrations of CEA, NSE, CYFRA21-1, SCC-Ag, and ProGRP in all the 3 groups were analyzed and compared in patients with different lung cancer tumor-node-metastasis (TNM) stages and pathological classifications. A total of 11 patients with small cell lung cancer (SCLC) and 18 patients with lung adenocarcinoma (LAC) were further evaluated for the dynamic changes of CEA, NSE, CYFRA21-1, SCC-Ag, and ProGRP before chemotherapy and during the 6 courses of chemotherapy, and the outcome of chemotherapy was evaluated every 2 courses.

Results

The serum concentrations of CEA, NSE, CYFRA21-1, SCC-Ag, and ProGRP in the lung cancer group were significantly higher than those in the control group (P &lt; .05). We found statistically significant differences in serum CEA, NSE, CYFRA 21-1, SCC-Ag, and ProGRP among patients with different pathological types (LAC, squamous cell carcinoma, or SCLC) and different stages (I–IV). The ProGRP and NSE had the highest expression in SCLC, CEA showed the highest expression in LAC, whereas CYFRA21-1 and SCC-Ag showed the highest expression in lung squamous cell carcinoma (LSCC). The concentrations of all the markers were elevated in the advanced pathological stages. The receiver operating characteristic curve analysis showed that the diagnostic value of the combined detection of CEA, NSE, CYFRA 21-1, SCC-Ag, and ProGRP for lung cancer was significantly higher than using a single biomarker (P &lt; .05). Our dynamic monitoring results show that ProGRP progressively decreased in remission cases of SCLC and CEA progressively decreased in LAC remission cases.

Conclusion

CEA, NSE, CYFRA 21-1, SCC-Ag, and ProGRP have good clinical value in the early diagnosis, differential diagnosis, and progression monitoring of lung cancer. The ProGRP and CEA concentrations are beneficial for evaluating the outcome of chemotherapy in SCLC and LAC. The combined detection of multiple biomarkers shows improved clinical value in the early diagnosis of lung cancer.

HEG1 as a novel potential biomarker for the prognosis of lung adenocarcinoma

BACKGROUND

Heart development protein with EGF-like domains 1 (HEG1), generally related to angiogenesis and embryonic development, was reported to participate in the occurrence and progression of some tumors recently. However, the role of HEG1 in lung adenocarcinoma (LUAD) is unclear.

PATIENTS AND METHODS

To explore the effect of HEG1 on LUAD, GEPIA platform and UALCAN database, as well as Kaplan-Meier plotter were adopted to analyze the association of HEG1 with clinicopathological characteristics and survival outcomes for LUAD firstly. And then the HEG1 in LUAD tissues, blood and cell lines were detected by qRT-PCR, western blot, immunofluorescence, immunohistochemistry, and ELISA. Gene set enrichment analysis (GSEA) was conducted to identify pathways that might be affected by HEG1 in LUAD.

RESULTS

In this study, HEG1 in lung tissues and cell lines of LUAD were significantly downregulated compared to benign pulmonary disease tissues and alveolar epithelial cells (p < 0.05). Moreover, compared with other groups, patients with advanced tumor stage had lower HEG1 mRNA expression levels (p = 0.025), which were negatively correlated with Ki67 index in tumor tissues (r = -0.427, p = 0.033). On the other hand, the LUAD patients with lower HEG1 had shorter overall survival (OS) (HR = 0.51, 95% CI: 0.40-0.65, p < 0.001) according to Kaplan-Meier plotter. In addition, HEG1 in serum of LUAD patients was negatively associated with CEA (r = -0.636, p < 0.001). GSEA showed that HEG1 was enriched in various metabolic-related pathways, including glucose metabolism, lipid metabolism, and nucleotide metabolism signaling.

CONCLUSIONS

HEG1 was downregulated in LUAD patients and associated with poor prognosis, which indicating HEG1 may serve as a potential biomarker for diagnosis and prognosis of LUAD.

Application Value Analysis of Seven-Autoantibody Panel in the Lung Cancer Screening in Yunnan

Objective

To study the application value of seven-autoantibody (anti-CAGE, anti-GAGE7, anti-GBU4-5, anti-MAGE A1, anti-P53, and anti-PGP9.5, anti-SOX2) in lung cancer (LC) screening in Yunnan.

Methods

The clinical data of 329 lung cancer patients and 202 nonlung cancer controls in the First People's Hospital of Yunnan Province from November 2018 to April 2022 were retrospectively analyzed. The detection results of anti-CAGE, anti-GAGE7, anti-GBU4-5, anti-MAGE A1, anti-P53, anti-PGP9.5, and anti-SOX2 were collected. The receiver operating curve (ROC) was used to analyze the value of these seven-autoantibody in the detection of LC alone and in combination, and the area under the curve (AUC), sensitivity, specificity, and cut-off values were calculated.

Results

The levels of anti-CAGE, anti-GAGE7, anti-GBU4-5, anti-MAGE A1, anti-P53, anti-PGP9.5 and anti-SOX2 in LC patients were significantly higher than those in the controls, and the differences were statistically significant (P < 0.001). The AUC of anti-CAGE, anti-GAGE7, anti-GBU4-5, anti-MAGE A1, anti-P53, anti-PGP9.5, and anti-SOX2 for the diagnosis of LC were 0.586 (95% CI: 0.537-0.634, P < 0.001), 0.620 (95% CI: 0.572-0.667, P < 0.001), 0.570 (95% CI: 0.521-0.619, P=0.007), 0.612 (95% CI: 0.563-0.660, P < 0.007) 0.001), 0.561 (95% CI: 0.510-0.611, P=0.019), 0.667 (95% CI: 0.619-0.715, P < 0.001), 0.587 (95% CI: 0.538-0.636, P < 0.001), respectively. The AUC of combined detection of LC was 0.719 (95% CI: 0.676-0.761, P < 0.001). The positive rate of the combined detection of seven-autoantibody in the LC group was 48.02% (158/329), which was significantly higher than that of the control group (13.86% (28/202)), the difference was statistically significant (χ 2 = 64.183, P < 0.001).

Conclusion

The individual detection and combined detection of the seven-autoantibody have a certain value in the diagnosis of LC in Yunnan, and it can provide a certain reference for clinical LC screening.

Assessing the Prognostic Value of the Neutrophil-to-Lymphocyte Ratio in Stage I Non-Small-Cell Lung Cancer with Complete Resection

Purpose. To explore the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) in stage I non-small-cell lung cancer (NSCLC) undergoing surgery. Patients and Methods. Between 2014 and 2016, a total of 190 patients with postoperative pathology of stage I NSCLC who underwent radical surgery at Nanjing Chest Hospital were studied. Clinical data were analyzed and classified into low-risk, moderate-risk, and high-risk groups based on independent risk factors to assess the prognosis. Results. NLR was associated with histological type and gender, and patients with an elevated NLR have poor overall survival (OS). Lymphovascular invasion, red blood cell distribution width-standard deviation (RDW-SD), and carcinoembryonic antigen (CEA) were independent prognostic factors for progression-free survival (PFS) in postoperative patients with stage I NSCLC, while NLR, RDW-SD, and CEA were independent risk factors for OS. Both PFS and OS were shorter in the low-risk group than in the medium-risk and high-risk groups. Conclusions. NLR, RDW-SD, CEA, and lymphovascular invasion are independent risk factors for postoperative prognosis in patients with stage I NSCLC, and the combination has a predictive value.

Neuron-Specific Enolase and Hemoglobin as Risk Factors of Intraocular Metastasis in Patients with Renal Cell Carcinoma

Renal cell carcinoma (RCC) appears to be a high risk of spread. This research investigated the correlation between a different range of clinical features and intraocular metastasis (IOM) in RCC patients and attempted to determine potential risk factors of RCC patients with IOM. In the study, there are a total of 351 patients with RCC that were recruited between May 1994 and May 2016. The differences between RCC patients with IOM and RCC patients with non-IOM (NIOM) were evaluated by the chi-squared test and Student t test. Binary logistic regression analysis was applied to determine risk factors. Finally, the value of diagnosis for RCC patients with IOM was assessed by receiver operating characteristic (ROC) curve analysis. Eighteen individuals were identified with IOM. There were no significant differences that were detected in alkaline phosphatase (AFP), carcinoembryonic antigen (CEA), alkaline phosphatase (ALP), cancer antigen 125 (CA-125), cancer antigen 153 (CA-153), cancer antigen 199 (CA-199), calcium, age, primary tumor site, and histopathological subtypes between the two groups. But there was a difference in terms of gender ( $P<0.05$ ). The IOM group exhibited significantly higher neuron-specific enolase (NSE) and lower hemoglobin (Hb) values compared to the NIOM group ( $P<0.05$ , respectively). Binary logistic regression identified NSE and Hb as significant risk factors of IOM for RCC patient ( $P<0.05$ and $P<0.001$ , respectively). The ROC curve analysis indicated that the area under the curve (AUC) values of NSE and Hb were 0.694 and 0.749, while cut-off values were 49.5 ng/mL and 102.5 g/L, respectively. The sensitivity and specificity of NSE were 72.2% and 66.4%, respectively, while those of Hb were 72.2% and 74.2%, respectively. The result reveals that NSE and Hb represent promising significant risk factors of IOM for RCC patients. Notably, Hb is more reliable than NSE in distinguishing case of IOM from NIOM in patients with RCC.

High-Sensitivity Fluorescence Detection for lung cancer CYFRA21-1 DNA based on Accumulative Hybridization of Quantum Dots

Sensitive detection of circulating tumor DNA (ctDNA) in vitro has attracted growing attention owing to its potential application in diagnostics of cancer. In this study, we synthesized hydrophilic AgInS2@ZnS core-shell...

Recent advances and challenges of bispecific antibodies in solid tumors

Cancer immunotherapy has made remarkable progress in the past decade. Bispecific antibodies (BsAbs) have acquired much attention as the next generation strategy of antibody-target cancer immunotherapy, which overwhelmingly focus on T cell recruitment and dual receptors blockade. So far, BsAb drugs have been proved clinically effective and approved for the treatment of hematologic malignancies, but no BsAb have been approved in solid tumors. Numerous designed BsAb drugs for solid tumors are now undergoing evaluation in clinical trials. In this review, we will introduce the formats of bispecific antibodies, and then update the latest preclinical studies and clinical trials in solid tumors of BsAbs targeting EpCAM, CEA, PMSA, ErbB family, and so on. Finally, we discuss the BsAb-related adverse effects and the alternative strategy for future study.

Increased circulating cytokeratin 19 fragment levels in preterm neonates receiving mechanical ventilation are associated with poor outcome

Invasive mechanical ventilation and oxygen toxicity are postnatal contributors to chronic lung disease of prematurity, also known as bronchopulmonary dysplasia (BPD). Cyfra 21-1 is a soluble fragment of cytokeratin 19, which belongs to the cytoskeleton stabilizing epithelial intermediate filaments. As a biomarker of structural integrity, Cyfra 21-1 might be associated with airway injury and lung hypoplasia in neonates. Serum Cyfra 21-1 concentrations for 80 preterm and 80 healthy term newborns were measured within 48 h after birth. Preterm infants with the combined endpoint BPD/mortality had significantly higher Cyfra 21-1 levels compared with those without fulfilling BPD/mortality criteria (P = 0.01). Also, severe RDS (>grade III) was associated with higher Cyfra levels (P = 0.01). Total duration of oxygen therapy was more than five times longer in neonates with high Cyfra 21-1 levels (P = 0.01). Infants with higher Cyfra 21-1 values were more likely to receive mechanical ventilation (50% vs. 17.5%). However, the duration of mechanical ventilation was similar between groups. The median Cyfra value was 1.93 ng/mL (IQR: 1.68-2.53 ng/mL) in healthy term neonates and 8.5 ng/mL (IQR: 3.6-16.0 ng/mL) in preterm infants. Using ROC analysis, we calculated a Cyfra cutoff > 8.5 ng/mL to predict BPD/death with an AUC of 0.795 (P = 0.004), a sensitivity of 88.9%, and a specificity of 55%. Mortality was predicted with a cutoff > 17.4 ng/mL (AUC: 0.94; P = 0.001), a sensitivity of 100%, and a specificity of 84%. These findings suggest that Cyfra 21-1 concentration might be useful to predict poor outcome in premature infants.

[Predicting the risk of tumor progression in patients with early stages of adenocarcinoma and squamous cell lung carcinoma based on laboratory parameters]

Non-small cell carcinoma (NSCLC) prevails in the structure of the incidence of lung cancer. In patients with I stage NSCLC, only 60-70% overcome the 5-year survival barrier, and at II stage it decreases to 35-40%. The reason for such a high mortality rate is almost always a relapse of the disease. The main histological forms of NSCLC - adenocarcinoma (AC) and squamous cell carcinoma (SCLC) - differ in the course, protocols and effectiveness of the treatment. Comparative survival data for AK and PCLC are controversial, and reliable biomarkers for determining the risk of tumor progression are lacking. In thus study we have investigated the possibility of using laboratory parameters characterizing the level of some blood proteins involved in carcinogenesis in patients with early stages of AC and SCLC to determine the risk of disease progression. We retrospectively analyzed the duration of the relapse-free period after surgical treatment for one year in 1250 patients (816 with stages I and II of adenocarcinoma, G1-3 and 434 with early stages of SCLC, G1-3). In 81 patients with AC and 36 - with SCLC (stages I-II, G1-3) the level of CYFRA 21-1 and SCC by electrochemiluminescent method, chemokines CXCL5, CXCL8, TPA, pyruvate kinase M2, HIF-1α and hyaluronic acid by enzyme immunoassay, receptors CXCR1, CXCR2, CD44v6 by flow cytometry were determined. Using the Kaplan-Meier graphical analysis, groups of low (stage I G1-2 + stage II G1) and high (stage I G3 + stage II G2-3) risk of tumor progression were identified. In the case of the one-year survival rate of patients with AC was higher than with SCLC. In patients with AC and a high risk of tumor recurrence, compared with a low one, the level of CYFRA 21-1, the mean intensity of fluorescence (MFI) of the CXCR1 receptor in granulocytes, and the relative content of the CXCR2 receptor in lymphocytes were higher. In the case of rapid progression of SCLC in patients, the relative content of the CXCR2 receptor in lymphocytes, the proportion of monocytes equipped with the CD44v6 receptor, and the SCC level were higher than with slow progression. Regression equations, including combinations of the above parameters (threshold value for AC - 0,512, for SCLC - 0,409, sensitivity - 91,9% and 90,0%, specificity - 90,0% and 87,5%, respectively), allow to predict the probability of tumor recurrence.

The diagnostic value of the combination of carcinoembryonic antigen, squamous cell carcinoma-related antigen, CYFRA 21-1, neuron-specific enolase, tissue polypeptide antigen, and progastrin-releasing peptide in small cell lung cancer discrimination

BACKGROUND

The diagnostic value of six tumor markers was investigated and the appropriate combinations of those tumor markers to discriminate small cell lung cancer was explored.

METHODS

Patients suspected with lung cancer (1938) were retrospectively analyzed. Candidate tumor markers from carcinoembryonic antigen (CEA), squamous cell carcinoma-related antigen (SCC), cytokeratin 19 fragment 21-1 (CYFRA 21-1), neuron-specific enolase (NSE), tissue polypeptide antigen (TPA), and progastrin releasing peptide (ProGRP) were selected to construct a logistic regression model. The receiver operating characteristic curve was used for evaluating the diagnostic value of the tumor markers and the predictive model.

RESULTS

ProGRP had the highest positive rate (72.3%) in diagnosed small cell lung cancer, followed by neuron-specific enolase (68.3%), CYFRA21-1 (50.5%), carcinoembryonic antigen (45.5%), tissue polypeptide antigen (30.7%), and squamous cell carcinoma-related antigen (5.9%). The predictive model for small cell lung cancer discrimination was established, which yielded the highest area under the curve (0.888; 95% confidence interval: 0.846-0.929), with a sensitivity of 71.3%, a specificity of 95.0%, a positive predictive value of 49.0%, and a negative predictive value of 98.0%.

CONCLUSIONS

Combining tumor markers can improve the efficacy for small cell lung cancer discrimination. A predictive model has been established in small cell lung cancer differential diagnosis with preferable efficacy.

Clinical Significance of CYFRA21-1, AFP, CA-153, CEA, and CA-199 in the Diagnosis of Lung Cancer Ocular Metastasis in Hypertension Population

Purpose: To detect lung metastases, we conducted a retrospective study to improve patient prognosis.

Methods: Hypertension patients with ocular metastases (OM group; n = 58) and without metastases (NM group; n = 1,217) were selected from individuals with lung cancer admitted to our hospital from April 2005 to October 2019. The clinical characteristics were compared by Student's t-test and chi-square test. Independent risk factors were identified by binary logistic regression, and their diagnostic value evaluated by receiver operating characteristic curve analysis.

Results: Age and sex did not differ significantly between OM and NM groups; There were significant differences in pathological type and treatment. Adenocarcinoma was the main pathological type in the OM group (67.24%), while squamous cell carcinoma was the largest proportion (46.43%) in the NM group, followed by adenocarcinoma (34.10%). The OM group were treated with chemotherapy (55.17%), while the NM group received both chemotherapy (39.93%) and surgical treatment (37.06%). Significant differences were detected in the concentrations of cancer antigen (CA)−125, CA-199, CA-153, alpha fetoprotein (AFP), carcinoembryonic antigen (CEA), cytokeratin fraction 21-1 (CYFRA21-1), total prostate-specific antigen, alkaline phosphatase, and hemoglobin (Student's t-test). Binary logistic regression analysis indicated that CA-199, CA-153, AFP, CEA, and CYRFA21-1 were independent risk factors for lung cancer metastasis. AFP (98.3%) and CEA (89.3%) exhibited the highest sensitivity and specificity, respectively, while CYRFA21-1 had the highest area under the ROC curve value (0.875), with sensitivity and specificity values of 77.6 and 87.0%, respectively. Hence, CYFRA21-1 had the best diagnostic value.

Diagnostic value of conventional tumor markers in young patients with pulmonary nodules

Background

Lung cancer is one of the most common malignancies, and there is a trend of increasing incidence in young patients. The preoperative diagnosis of pulmonary nodules is mainly based on the combination of imaging and tumor markers. There is no relevant report on the diagnostic value of tumor markers in young pulmonary nodules. Our study was designed to explore the value of five tumor markers in young patients with pulmonary nodules.

Methods

We reviewed the medical records of 390 young patients (age ≤45 years) with pulmonary nodules treated at two separate centers from January 1, 2015, to January 1, 2021. Malignant pulmonary nodules were confirmed in 318 patients, and the other 72 patients were diagnosed with benign pulmonary nodules. The gold standard for diagnosis of pulmonary nodules was surgical biopsy. The conventional serum biomarkers included cytokeratin 19 (CYFRA21‐1), pro‐gastrin‐releasing‐peptide (ProGRP), carcinoembryonic antigen (CEA), neuron‐specific enolase (NSE), and squamous cell carcinoma‐associated antigen (SCCA). The diagnostic values of five tumor markers were analyzed by receiver operating characteristic (ROC) curves.

Results

There were no significant differences in the expression of five tumor markers between the groups (p > 0.05). Single tumor marker (CYFRA21‐1, ProGRP, CEA, NSE, and SCCA) showed a limited value in the diagnosis of malignant pulmonary nodules, with the AUC of 0.506, 0.503 0.532, 0.548, and 0.562, respectively. The AUC of the combined examination was only 0.502~0.596, which did not improve the diagnostic value.

Conclusions

Five conventional tumor markers had a limited diagnostic value in young patients with pulmonary nodules.

Prevalence of serum galectin-1 autoantibodies in seven types of cancer: A potential biomarker

Although serum galectin-1 antibodies (s-GAL-1-Abs) have been evaluated in a small number of patients with cancer, a large series of patients with different cancer types have not been reported. The current study evaluated 1,833 patients with esophageal cancer (n=172), gastric cancer (n=317), colorectal cancer (n=262), hepatocellular carcinoma (n=91), prostate cancer (n=358), breast cancer (n=364), lung cancer (n=269) and 72 healthy individuals. s-GAL-1-Abs levels were analyzed using an originally developed ELISA system. A cut-off optical density value was determined as the mean (0.053) + 3 standard deviations (0.105) of sera from healthy controls. The results revealed that the positive rate of s-GAL-1-Abs in patients with hepatocellular carcinoma (16.7%) and lung cancer (13.8%) were significantly higher compared with the other groups: Esophageal cancer (11.6%), colorectal cancer (11.5%), prostate cancer (7.3%), gastric cancer (6.9%), breast cancer (6.9%) and healthy controls (4.2%). Although the positive rates of s-GAL-1-Abs in different cancer types were relatively low, s-GAL-1-Abs may be useful for patients with hepatocellular carcinoma and lung cancer.

Diagnostic potential of extracellular vesicle-associated microRNA-10b and tumor markers for lung adenocarcinoma

MicroRNAs (miRNAs/miRs) in extracellular vesicles (EVs) are potential diagnostic markers. The purpose of the present study was to investigate potential EV miRNA biomarkers for lung adenocarcinoma (LUAD). Potential miRNAs were identified by searching public databases and verified by examining clinical samples. The diagnostic value of EV-associated miR-10b, plasma miR-10b and tumor markers (TMs), including α-fetoprotein (AFP), neuron-specific enolase, carcinoembryonic antigen (CEA), cytokeratin 19 fragment 21-1 (CYFRA211), pro-gastrin-releasing-peptide, carbohydrate antigen (CA)125, CA153, CA199 and CA724, was evaluated via receiver operating characteristic curve analysis. By searching the Gene Expression Omnibus and The Cancer Genome Atlas databases, miR-10b was identified as a potential biomarker. The analysis of clinical samples suggested that EV-associated miR-10b from plasma was significantly differentially expressed between LUAD and control samples. EV-associated miR-10b could function as a diagnostic marker for LUAD, with an AUC of 0.998, which was higher than the AUCs for TMs such as AFP, CEA, CYFRA211, CA125, CA153, CA199, CA724, pro-gastrin-releasing-peptide and neuron-specific enolase. In conclusion, EV-associated miR-10b may be a potential diagnostic biomarker for LUAD that is superior to plasma miR-10b and TMs.

Screening and identification of key biomarkers in alimentary tract cancers: A bioinformatic analysis

BACKGROUND

Alimentary tract cancers (ATCs) are the most malignant cancers in the world. Numerous studies have revealed the tumorigenesis, diagnosis and treatment of ATCs, but many mechanisms remain to be explored.

METHODS

To identify the key genes of ATCs, microarray datasets of oesophageal cancer, gastric cancer and colorectal cancer were obtained from the Gene Expression Omnibus (GEO) database. In total, 207 differentially expressed genes (DEGs) were screened. KEGG and GO function enrichment analyses were conducted, and a protein-protein interaction (PPI) network was generated and gene modules analysis was performed using STRING and Cytoscape.

RESULTS

Five hub genes were screened, and the associated biological processes indicated that these genes were mainly enriched in cellular processes, protein binding and metabolic processes. Clinical survival analysis showed that COL10A1 and KIF14 may be significantly associated with the tumorigenesis or pathology grade of ATCs. In addition, relative human ATC cell lines along with blood samples and tumour tissues of ATC patients were obtained. The data proved that high expression of COL10A1 and KIF14 was associated with tumorigenesis and could be detected in blood.

CONCLUSION

In conclusion, the identification of hub genes in the present study helped us to elucidate the molecular mechanisms of tumorigenesis and identify potential diagnostic indicators and targeted treatment for ATCs.

Clinical value of tumor-associated antigens and autoantibody panel combination detection in the early diagnostic of lung cancer

BACKGROUND

This study aimed to investigate the efficiency of combining tumor-associated antigens (TAAs) and autoantibodies in the diagnosis of lung cancer.

METHODS

The serum levels of TAAs and seven autoantibodies (7-AABs) were detected from patients with lung cancer, benign lung disease and healthy controls. The performance of a new panel by combing TAAs and 7-AABs was evaluated for the early diagnosis of lung cancer.

RESULTS

The positive rate of 7-AABs was higher than the single detection of antibody. The positive rate of the combined detection of 7-AABs in lung cancer group (30.2%) was significantly higher than that of healthy controls (16.8%), but had no statistical difference compared with that of benign lung disease group (20.8%). The positive rate of 7-AABs showed a tendency to increase in lung cancer patients with higher tumor-node-metastasis (TNM) stages. For the pathological subtype analysis, the positive rate of 7-AABs was higher in patients with squamous cell carcinoma and small cell lung cancer than that of adenocarcinoma. The levels of carcinoembryonic antigen (CEA) and cytokeratin 19 fragment 211 (CYFRA 211) were significantly higher than that of benign lung disease and healthy control groups. An optimal model was established (including 7-AABs, CEA and CYFRA21-1) to distinguish lung cancer from control groups. The performance of this model was superior than that of single markers, with a sensitivity of 52.26% and specificity of 77.46% in the training group. Further assessment was studied in another validation group, with a sensitivity of 44.02% and specificity of 83%.

CONCLUSIONS

The diagnostic performance was enhanced by combining 7-AABs, CEA and CYFRA21-1, which has critical value for the screening and early detection of lung cancer.

Upregulation of Long Non-Coding RNA GCC2-AS1 Facilitates Malignant Phenotypes and Correlated With Unfavorable Prognosis for Lung Adenocarcinoma

Background

The role played by long noncoding RNA GCC2-AS1 in primary malignant tumors remains poorly understood. This study aimed to determine the expression levels and evaluate the clinical significance and biological effects of GCC2-AS1 in lung adenocarcinoma (LUAD).

Methods

We used data obtained from tissue samples and the TCGA database to determine the levels of GCC2-AS1 expression LUAD patients, and the prognostic value of those levels. Functional experiments were performed to investigate the effect of GCC2-AS1 on LUAD cells. Genes that were differentially expressed in GCC2-AS1-low and -high groups were analyzed by an enrichment analysis. Additionally, a nomogram model was created and subgroup analyses were performed to further determine the prognostic value of GCC2-AS1 in LUAD.

Results

GCC2-AS1 expression was significantly upregulated in lung adenocarcinoma tissues as compared with normal tissues. Depletion of GCC2-AS1 inhibited the proliferation and invasion of LUAD cells in vitro. An elevated level of GCC2-AS1 was strongly correlated with shorter overall survival time and was identified as an independent prognostic marker for LUAD patients. Enrichment analyses conducted using GO, KEGG, and GSEA databases were performed to identify biological pathways that might involve GCC2-AS1. Several subgroups were found to have a significant prognostic value for patients in the GCC2-AS1-low and -high groups.

Conclusions

Our findings suggest that GCC2-AS1 can serve as a diagnostic and prognostic biomarker for LUAD patients.

Progastrin-Releasing Peptide Precursor and Neuron-Specific Enolase Predict the Efficacy of First-Line Treatment with Epidermal Growth Factor Receptor (EGFR) Tyrosine Kinase Inhibitors Among Non-Small-Cell Lung Cancer Patients Harboring EGFR Mutations

Purpose

Lung cancer is the leading cause of cancer-related mortality and non-small-cell lung cancer (NSCLC) accounts for 80–90% of all lung cancers. However, biomarkers to predict the prognosis of NSCLC patients upon treatment with tyrosine kinase inhibitors remain unreliable. Different types of EGFR mutations can help predict the efficacy of tyrosine kinase inhibitor (TKI) treatment among advanced NSCLC patients harboring them. However, survival varies among individuals harboring the same mutation after targeted therapy. This study aimed to investigate the value of serum tumor markers (STMs) and EGFR mutations in the prognostic assessment of progression-free survival (PFS) in advanced-stage EGFR-mutated NSCLC.

Patients and Methods

A retrospective clinical review was performed on 81 NSCLC patients harboring EGFR mutations and for whom STM data, measured before commencement of first‐line treatment with tyrosine kinase inhibitors, were available. Associations among EGFR mutations, STMs, baseline clinical features, and PFS were analyzed. Kaplan−Meier method was used to plot survival curves, and Cox logistic regression models were used to identify independent prognostic factors.

Results

Exon 19 deletion (19-del) in EGFR, negative neuron-specific enolase (NSE), negative pro-gastrin-releasing peptide precursor (ProGRP) value, and “never smoking” status were significantly associated with improved PFS (P=0.007, P=0.001, P<0.001, and P<0.001, respectively). Multivariate Cox analysis revealed that 19-del in EGFR, never smoking, negative ProGRP value, and negative NSE were independent predictors of PFS.

Conclusion

This study demonstrated that 19-del in EGFR may predict longer PFS in advanced-stage EGFR-mutated NSCLC treated with TKIs. Additionally, longer PFS can be predicted by serum tumor markers with negative ProGRP value, negative NSE value before initial treatment, and “never smoking.” Therefore, in addition to the EGFR mutation type and smoking status, physicians can also prognosticate the PFS of tyrosine kinase inhibitors treatment according to the values of ProGRP and NSE before treatment.

Effects of Docetaxel Combined with Icotinib on Serum Tumor Markers and Quality of Life of Patients with Advanced Non-Small Cell Lung Cancer

Background

To investigate the effects of docetaxel combined with icotinib on tumor markers in serum and quality of life of patients with advanced non-small cell lung cancer (NSCLC).

Methods

Overall, 121 patients with advanced NSCLC, admitted to the Third Affiliated Hospital of Shandong First Medical University, China from 2017-2018 were selected as subjects. Among them, 58 patients treated with docetaxel combined with icotinib for chemotherapy were considered as study group, and 63 patients treated with paclitaxel combined with carboplatin as control group. The clinical efficacy, adverse reactions, and ECOG scores of the two groups were observed. CEA, CA125, and SCC (Tumor markers) levels of the two groups before and after treatment were detected by chemiluminescence immunoassay (CLIA).

Results

The leukopenia, oral mucosa ulcer and mild numbness in the control group were significantly higher than those in the study group (P<0.05). After treatment, ECOG scores of both groups decreased (P<0.05), and the ECOG score of the study group was significantly higher than that of the control group (P<0.05). The serum CEA, CA125 and SCC levels of the study group and the control group after treatment decreased significantly compared with that before treatment (P<0.05).

Conclusion

Application of docetaxel combined with icotinib for chemotherapy of patients with advanced NSCLC can effectively reduce the serum levels of CEA, SCC, and the CA125. Docetaxel combined with icotinib can significantly reduce adverse reactions and better improve the quality of life of patients compared with paclitaxel combined with carboplatin, which is worthy of clinical promotion.

Association Between Pretransplant Serum Carcinoembryonic Antigen Levels and Immunohistochemical Staining of Explanted Native Lungs in Patients Who Underwent Lung Transplantation

Some patients show high serum carcinoembryonic antigen (CEA) levels in the evaluation of candidate patients for lung transplantation, which might be a challenge because high serum CEA potentially implies an existence of malignancy. For further understanding of the true meaning of high serum CEA levels in lung transplantation, we retrospectively investigated the relationship between serum CEA and clinical data. We also performed immunohistochemical analysis of explanted native lungs and evaluated its relationship with serum CEA levels. Retrospective chart review was performed in consecutive patients who underwent lung transplantation with measurement of serum CEA before and after transplantation at our institution between August 2008 and June 2017. Histopathological analysis was also performed in the same cohort of patients. Survival outcomes and pathohistological findings were compared between the high serum CEA and the normal CEA group, adjusting for potential confounding factors. One hundred and fifteen patients were eligible for analysis. High serum CEA levels before lung transplantation in most cases were decreased after the transplantation (35/39, 90%, P < 0.001). Preoperative serum CEA levels were not associated with postoperative survival. The percentage of CEA-positive alveolar cells was significantly higher in the high serum CEA group (P < 0.0001). After adjusting for potential confounding factors, there was a significant difference between the high serum CEA group and normal serum CEA group (CEA-positive alveolar cells; P = 0.002). High serum CEA levels before lung transplantation might derive from native lungs in the recipients and that they were not associated with overall survival after lung transplantation.

Stem signatures associated antibodies yield early diagnosis and precise prognosis predication of patients with non-small cell lung cancer

BACKGROUND

This study was designed to detect patients with early NSCLC with tentatively using the stem signatures associated autoantibodies (AAbs), and to evaluate its latent values in the early diagnosis and precise prognosis prediction.

METHODS

The serum concentrations of selective antibodies were quantitated by enzyme-linked immunosorbent assay (ELISA), and a total of 458 cases were enrolled (training set = 401; validation set = 57). TCGA databases were used to analyze the distinct expressions and prognostic values of related genes. The optimal cut-off values were 11.60 U/ml for P53, 4.90 U/ml for MAGEA1, 3.85 U/ml for SOX2, and 7.05U/ml for PGP9.5.

RESULTS

We found that the stem signatures associated antibodies of MAGEA1, PGP9.5, SOX2, and TP53 exhibited high expressions in NSCLC, negatively correlating with the overall survival (OS) (P < 0.05). In the test groups, the diagnosis sensitivity of P53, PGP9.5, SOX2, and MAGEA1 reached to 21.5%, 39.0%, 50.3%, and 35.0%, respectively, and the specificity reached to 98.7%, 99.4%, 92.2%, and 97.4%. The four candidates' panel gave a sensitivity of 71.8% with a specificity of 89%. In the validation group, the detection of the four antibodies in early diagnosis of NSCLC also exhibited high specificity and sensitivity, further consolidating their potential application.

CONCLUSIONS

The detection regarding stem signatures associated antibodies could be used as effective tools in early NSCLC diagnosis, but not for localized screening of cancers, and their abnormal expression was in accordance with poorer survival.

Selective application of neuroendocrine markers in the diagnosis and treatment of small cell lung cancer

AIMS

Here, we explored the potential application and selection of neuroendocrine biomarkers in the diagnosis and treatment of small cell lung cancer.

METHODS

We retrospectively analyzed 118 patients with small cell lung cancer (SCLC), 166 patients with non-small cell lung cancer (NSCLC), 33 patients with benign lung disease (BLD), and 200 healthy individuals admitted to Zhejiang Provincial People's Hospital between January 1, 2015 and May 31, 2019. All the patients were newly diagnosed with either SCLC, NSCLC, or BLD and previously untreated. Peripheral blood levels of ProGRP, NSE, CEA, and CYFRA21-1 were analyzed during the follow-up treatment, and 2-fold upper limit of reference intervals were defined as effective elevation. We used paired results to analyze the diagnostic efficiency of proGRP and NSE on SCLC.

RESULTS

In the 118 SCLC patients, proGRP levels were significantly higher compared with NSE levels. The diagnostic efficiencies of NSE and ProGRP for SCLC were 0.8554 and 0.9053, respectively. The combined diagnostic efficiency (0.9426) was higher relative to NSE, but there was no significant difference compared with proGRP. The effective elevation rate of proGRP was 45.3% higher than that of NSE in the limited stage of SCLC. In the extensive disease of SCLC patients, 70.7% cases had more than 10-fold increase in proGRP value, whereas 56.9% cases had less than 5-fold increase in NSE value. Compared with pre-treatment, the median concentrations of proGRP increased by 204.0% higher than that of NSE (71.3%) in the progressive group. Besides, the dynamic change in imaging characteristics and tumor size had a strong correlation with the levels of proGRP.

SIGNIFICANCE

ProGRP is a reliable neuroendocrine biomarker in SCLC. The effective elevation of proGRP has a potential diagnostic and efficacy value in the evaluation of SCLC. However, the combined detection of proGRP and NSE does not significantly improve the diagnosis of lung cancer.

YRDC is upregulated in non-small cell lung cancer and promotes cell proliferation by decreasing cell apoptosis

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-associated mortality worldwide. yrdC N6-threonylcarbamoltransferase domain containing protein (YRDC) has been demonstrated to be involved in the formation of threonylcarbamoyladenosine in transfer ribonucleic acid. However, the molecular mechanisms underlying NSCLC progression remain largely unclear. The present study revealed that YRDC was upregulated in NSCLC samples compared with adjacent non-cancerous tissues by analyzing datasets obtained from the Gene Expression Omnibus and The Cancer Genome Atlas. Higher expression of YRDC was associated with overall survival time and disease-free survival time in patients with NSCLC, particularly in lung adenocarcinoma. Furthermore, knockdown of YRDC in NSCLS cell lines significantly suppressed cell growth and cell colony formation in vitro. Additionally, the results demonstrated that silencing of YRDC induced apoptosis of A549 cells. Then, the protein-protein interaction networks associated with yrdC N6-threonylcarbamoltransferase domain containing protein (YRDC) in NSCLC were subsequently constructed to investigate the potential molecular mechanism underlying the role of YRDC in NSCLC. The results revealed that YRDC was involved in the regulation of spliceosomes, ribosomes, the p53 signaling pathway, proteasomes, the cell cycle and DNA replication. The present study demonstrated that YRDC may serve as a novel biomarker for the prognosis prediction and treatment of NSCLC.

Integration of platelet features in blood and platelet rich plasma for detection of lung cancer

OBJECTIVES

To determine whether the integration platelet features in blood and platelet rich plasma can establish a model to diagnose lung cancer and colon cancer, even differentiate lung malignancy from lung benign diseases.

METHODS

245 individuals including 159 lung cancer and 86 normal participants were divided into the training cohort and testing cohort randomly. Then, 32 colon cancers, 37 lung cancers, and 21 benign patients were enrolled into validate cohort. The whole blood and corresponding platelet rich plasma (PRP) samples from all participants were prospectively collected, and the platelet features were determined. The features which are statistically significant at the univariate analysis in the training cohort and reported significant features were entered the diagnostic model. A receiver operator characteristic (ROC) curve was drawn to evaluate the accuracy of the model in each cohort.

RESULTS

In the training cohort, multiple platelet features were significantly different in lung cancer patients, including MPV in whole blood, MPV, and platelet count in PRP and platelet recovery rate (PRR). For the training cohort, the diagnostic model for lung cancer performed well (AUC = 0.92). The probability distribution of lung cancers and controls in testing cohort were also separated well by the diagnostic model (AUC = 0.79). The diagnostic model for colon cancer also performed well (AUC = 0.79). The model also has a potential value in differentiating the lung malignancy from the benign (AUC = 0.69).

CONCLUSION

The PRR was first raised and used in the detection of lung cancer. This study identified a diagnostic model based on PRR and other platelet features in whole blood and PRP samples with the potential to distinguish patients with lung cancer or colon cancer from healthy controls. The model could also be used to distinguish between lung cancer from the benign disease.

Development of a machine learning-based multimode diagnosis system for lung cancer

As an emerging technology, artificial intelligence has been applied to identify various physical disorders. Here, we developed a three-layer diagnosis system for lung cancer, in which three machine learning approaches including decision tree C5.0, artificial neural network (ANN) and support vector machine (SVM) were involved. The area under the curve (AUC) was employed to evaluate their decision powers. In the first layer, the AUCs of C5.0, ANN and SVM were 0.676, 0.736 and 0.640, ANN was better than C5.0 and SVM. In the second layer, ANN was similar with SVM but superior to C5.0 supported by the AUCs of 0.804, 0.889 and 0.825. Much higher AUCs of 0.908, 0.910 and 0.849 were identified in the third layer, where the highest sensitivity of 94.12% was found in C5.0. These data proposed a three-layer diagnosis system for lung cancer: ANN was used as a broad-spectrum screening subsystem basing on 14 epidemiological data and clinical symptoms, which was firstly adopted to screen high-risk groups; then, combining with additional 5 tumor biomarkers, ANN was used as an auxiliary diagnosis subsystem to determine the suspected lung cancer patients; C5.0 was finally employed to confirm lung cancer patients basing on 22 CT nodule-based radiomic features.

Clinical value of seven autoantibodies combined detection in the diagnosis of lung cancer

Background

To analyze the clinical value of seven autoantibodies (p53, PGP9.5, SOX2, GAGE7, GBU4‐5, MAGE A1 and CAGE) in lung cancer patients.

Methods

ELISA was used to determine serum levels of seven autoantibodies in 177 patients with lung cancer, 201 healthy persons, and 210 patients with benign pulmonary diseases. Positive rates of 7 autoantibodies were analyzed; receiver operating characteristic (ROC) curves were drawn to analyze their diagnostic efficiency in lung cancer and to compare the positive rate of seven kinds of autoantibody combined detection of lung cancer patients with different clinicopathological features.

Results

The positive rate of seven autoantibodies in all subjects was 13.44%. The positive rate of seven autoantibodies in lung cancer was 25.42%. The positive rate of the combined detection of seven autoantibodies in the lung cancer group was significantly higher than that in healthy control group (χ² = 19.76, P < .001) and benign lung disease group (χ² = 21.44, P < .001). Sensitivity, specificity, and AUC^ROC of the seven autoantibodies were 25.42%, 91.75%, and 0.683, respectively. Sensitivity and AUC^ROC were higher than those of the single autoantibody detection. Positive rates of seven autoantibodies in different pathological types and clinical stages of lung cancer patients were significantly different (P < .05).

Conclusions

The combined detection of 7 autoantibodies in lung cancer has some clinical value for the auxiliary diagnosis of lung cancer.

Utility of isocitrate dehydrogenase 1 as a serum protein biomarker for the early detection of non-small-cell lung cancer: A multicenter in vitro diagnostic clinical trial

We aimed to verify the expression status and diagnostic significance of isocitrate dehydrogenase 1 (IDH1) in non-small-cell lung cancer (NSCLC), especially during early stages. Serum IDH1 levels were measured by ELISA. A total of 1223 participants (660 patients with NSCLC, 276 healthy controls [HCs], 95 patients with benign pulmonary conditions [BPCs], 135 patients with other cancers [OCs], and 57 samples with interfering factors) were divided into a training cohort and a validation cohort according to 3 testing centers. The IDH1 concentrations in the NSCLC group were obviously higher than those in the control groups (P < .001). Area under the receiver operating characteristic curves (AUCs) for discriminating NSCLC patients from controls (HC, BPC, and OC) were 0.870 and 0.745 (sensitivity, 63.3% and 55.0%; specificity, 86.8% and 86.3%) in the training cohort and validation cohort, respectively. The AUCs for discriminating stage 0-IA lung cancer patients from HCs were 0.907 and 0.788 (sensitivity, 58.6% and 59.1%; specificity, 92.9% and 89.3%) in 2 cohorts, respectively. Isocitrate dehydrogenase 1 showed specificity for NSCLC and had no diagnostic value for other common cancers. Furthermore, IDH1 was significantly reduced in postoperative serum. Isocitrate dehydrogenase 1 shows clinical utility as a serum protein biomarker for the early diagnosis of NSCLC.

Long noncoding RNA MALAT1 as a candidate serological biomarker for the diagnosis of non-small cell lung cancer: A meta-analysis

Background

To investigate the diagnostic efficacy of long noncoding RNA metastasis‐associated in lung adenocarcinoma transcript l (MALAT1) as a candidate serological biomarker for non‐small cell lung cancer (NSCLC).

Methods

Diagnostic studies relevant to circulation long noncoding RNA MALAT1 as a candidate serological biomarker for NSCLC were electronically systematically searched in PubMed, EMBASE, EBSCO and CNKI databases. Suitable studies were included in the meta‐analysis by pooling the diagnostic sensitivity, specificity, positive likelihood ratio (+LR), negative likelihood ratio (−LR), diagnostic odds ratio (DOR) and area under the symmetric ROC curve (AUC) through a random or fixed effects model. Deeks' funnel plot was applied for publication bias evaluation.

Results

Six studies with eight datasets were finally included in the meta‐analysis after a systematic search of the databases was performed. The pooled diagnostic sensitivity, specificity, +LR, −LR and DOR were 0.81 (95% CI:0.78–0.84), 0.67 (95% CI:0.63–0.71), 2.61 (95% CI:1.81–3.71), 0.28 (95% CI:0.19–0.43) and 13.73 (95% CI:6.19–30.44), respectively. The pooled area under the ROC curve (AUC) were 0.8663 and 0.8658, respectively by symmetric and asymmetric methods.

Conclusion

Based on the results of our study, serum long noncoding RNA MALAT1 is a promising biomarker for NSCLC screening. However, due to its low specificity, MALAT1 positive cases need further validation for NSCLC by other diagnostic methods such as radiology, cytology, etc.

Nanotechnology based therapeutic application in cancer diagnosis and therapy

Due to the lack of early diagnosis, cancer remains as one of the leading cause of human mortality. Inability to translate research into clinical trials and also inability of chemotherapeutics delivery to targeted tumor sites are major drawbacks in cancer therapeutics. With the emergence of nanomedicine, several nanoprobes (conjugated with targeting ligands and chemotherapeutic drugs) are developed. It can interact with biological system and thus sense and monitor the biological events with high efficiency and accuracy along with therapy application. Nanoparticles like gold and iron oxide are frequently used in the computed tomography and magnetic resonance imaging applications, respectively. Moreover, enzymatic activity of gold and iron oxide nanoparticles enables the visible colorimetric diagnostic of cancer cells, whereas, fluorescence property of quantum dots and upconversion nanoparticles helps in in vivo imaging application. Other than this, drug conjugation with nanoparticles also reduces the systemic toxic effect of chemotherapeutic drugs. Due to their several unique intrinsic properties, nanoparticles itself can also be employed as therapeutics in cancer treatment by photothermal therapy (PTT) and photodynamic therapy (PDT). Thus, the main focus of this review is to emphasize on current progress in diagnostic and therapeutic application of nanoprobes in cancer.

HE4 as a biomarker for diagnosis of lung cancer: A meta-analysis

BACKGROUND

The aim of our study was to assess the value of serum human epididymis protein 4 (HE4) to diagnose lung cancer and provide reliable scientific conclusions to guide clinical practice.

METHODS

A systematic search of the PubMed, EMBASE, Cochrane Library, Chinese National Knowledge Infrastructure, Chinese Biomedical Literature, and WANFANG databases was conducted to identify all studies examining serum HE4 in the diagnosis of lung cancer published up to June, 2017. The Quality Assessment of Diagnostic Accuracy Studies tool was used to evaluate the methodological quality of each trial. The meta-analysis was performed using STATA software and Review Manager 5.3.

RESULTS

There were 21 studies involving 1883 cases and 1696 controls included in our meta-analysis. The pooled sensitivity and specificity of HE4 for diagnosing lung cancer were 0.73 (95% confidence interval [CI] 0.68-0.78) and 0.86 (95% CI 0.81-0.91), respectively. The positive likelihood ratio and negative likelihood ratio were 5.4 (95% CI 3.8-7.5) and 0.31 (95% CI 0.26-0.37), respectively. The diagnostic odds ratio was 17 (95% CI 12-26). The area under the curve of the summary receiver-operating characteristic curve was 0.86 (95% CI 0.83-0.89). Race, assay method, type of cancer, sample size, and publication date might be sources of heterogeneity in our meta-analysis. Subgroup analyses showed that the sensitivity in Caucasians was higher than that in Asians (0.81, 95% CI 0.71-0.91; and 0.71, 95% CI 0.66-0.77, respectively), but the specificity in Asians was better than that in Caucasians (0.87, 95% CI 0.81-0.92; and 0.85, 95% CI 0.73-0.97, respectively). The chemiluminescent microparticle immunoassay had the highest sensitivity, with 0.79 (95% CI 0.73-0.97), and the enzyme-linked immunosorbent assay had the highest specificity, with 0.87 (95% CI 0.79-0.94). HE4 had high diagnostic efficacy when screening for small cell lung cancer with the highest specificity (0.90, 95% CI 0.77-1.00).

CONCLUSIONS

HE4 is a relatively promising and effective biomarker for the diagnosis of lung cancer. Furthermore, given the limitations of our study, additional large-scale and well-designed studies are needed in the future.

Immunotherapy a New Hope for Cancer Treatment: A Review

Cancer is a major burden of disease worldwide with considerable impact on society. The tide of immunotherapy has finally changed after decades of disappointing results and has become a clinically validated treatment for many cancers. Immunotherapy takes many forms in cancer treatment, including the adoptive transfer of ex vivo activated T cells, oncolytic viruses, natural killer cells, cancer vaccines and administration of antibodies or recombinant proteins that either costimulate cells or block the so-called immune checkpoint pathways. Recently, cancer immunotherapy has received a high degree of attention, which mainly contains the treatments for programmed death ligand 1 (PD-L1), programmed death 1 (PD-1), chimeric antigen receptors (CARs) and cytotoxic T lymphocyte-associated antigen 4 (CTLA-4). Here, this paper reviewed the current understandings of the main strategies in cancer immunotherapy (adoptive cellular immunotherapy, immune checkpoint blockade, oncolytic viruses and cancer vaccines) and discuss the progress in the synergistic design of immune-targeting combination therapies.

Pre-operative plasma cell-free circulating tumor DNA and serum protein tumor markers as predictors of lung adenocarcinoma recurrence

Background: Lung cancer patients have a risk of recurrence even after curatively intended surgery. Cell-free circulating tumor DNA (ctDNA) and circulating tumor marker measurements are easily accessible through peripheral blood and could potentially identify patients with worse prognosis. The aim of this study was to examine ctDNA in pre-operative plasma and the role of tumor markers in pre-operative serum for their predictive potential on risk of tumor recurrence. Methods: Mutation analysis by 26-gene targeted sequencing was performed on 157 lung adenocarcinomas (ACs) from patients surgically treated at the Lund University Hospital 2005-2014. Of these, 58 tumors from patients in stages I-IIIA (34 stage I, 14 stage II and 10 stage III) with mutation(s) in EGFR, BRAF or KRAS were included. ctDNA from corresponding plasma (median 1.5 ml, range 1-1.6) was analyzed for one tumor-specific mutation in either of these three oncogenes using ultrasensitive IBSAFE droplet digital PCR (ddPCR). The tumor markers cancer antigen 125 (CA 125) and carbohydrate antigen 19-9 (CA 19-9) were analyzed in corresponding serum with electrochemiluminiscence immunoassay. Results: 6/7 patients with ctDNA and 19/51 without detected ctDNA were diagnosed with recurrence (log-rank test p = .001). 8/10 patients with positive serum tumor markers and 17/47 without tumor markers were diagnosed with recurrence (log-rank test, p = .0002). Fifteen patients had positive ctDNA and/or tumor markers, 12 of these had recurrence (log-rank test, p < .0001). Conclusion: A combination of tumor markers and ctDNA single mutation detection in low-volume pre-operative blood samples is a promising prognostic test. Prediction of recurrent disease in surgically treated early stage lung cancer can likely be further improved by using larger volumes of blood.

Multiplex plasma protein profiling identifies novel markers to discriminate patients with adenocarcinoma of the lung

Background

The overall prognosis of non-small cell lung cancer (NSCLC) is poor, and currently only patients with localized disease are potentially curable. Therefore, preferably non-invasively determined biomarkers that detect NSCLC patients at early stages of the disease are of high clinical relevance. The aim of this study was to identify and validate novel protein markers in plasma using the highly sensitive DNA-assisted multiplex proximity extension assay (PEA) to discriminate NSCLC from other lung diseases.

Methods

Plasma samples were collected from a total of 343 patients who underwent surgical resection for different lung diseases, including 144 patients with lung adenocarcinoma (LAC), 68 patients with non-malignant lung disease, 83 patients with lung metastasis of colorectal cancers and 48 patients with typical carcinoid. One microliter of plasma was analyzed using PEA, allowing detection and quantification of 92 established cancer related proteins. The concentrations of the plasma proteins were compared between disease groups.

Results

The comparison between LAC and benign samples revealed significantly different plasma levels for four proteins; CXCL17, CEACAM5, VEGFR2 and ERBB3 (adjusted p-value < 0.05). A multi-parameter classifier was developed to discriminate between samples from LAC patients and from patients with non-malignant lung conditions. With a bootstrap aggregated decision tree algorithm (TreeBagger), a sensitivity of 93% and specificity of 64% was achieved to detect LAC in this risk population.

Conclusions

By applying the highly sensitive PEA, reliable protein profiles could be determined in microliter amounts of plasma. We further identified proteins that demonstrated different plasma concentration in defined disease groups and developed a signature that holds potential to be included in a screening assay for early lung cancer detection.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5943-3) contains supplementary material, which is available to authorized users.

Establishment and validation of a novel survival prediction scoring algorithm for patients with non-small-cell lung cancer spinal metastasis

BACKGROUND

This study was to develop an algorithm capable of predicting the survival of patients with NSCLC spinal metastasis for individualized therapy.

METHODS

We identified 176 consecutive patients with NSCLC spinal metastasis between 2006 and 2017. Twenty-four features, including age, gender, smoking, KPS, paralysis, histological subtype, tumor stage, surgery, EGFR status, CEA, CA125, CA19-9, NSE, SCC, CYFRA21-1, calcium, AKP, albumin, the number of spinal, extra-spinal bone and visceral metastasis, time to metastasis, pathological fracture, and primary or secondary metastasis, were retrospectively analyzed. Features associated with survival in the multivariate analyses were included in a scoring model, which was prospectively validated in another 63 patients (NCT03363685).

RESULTS

The median follow-up period was 12.00 months (interquartile range 6.00-23.40 months). One hundred forty-seven patients died during follow-up, with a median survival of 13.6 months being observed. Multivariate analysis revealed that the following features were associated with survival: age, smoking, CA125, SCC, KPS, and EGFR status. A scoring system based on these features was created to stratify patients into low-risk (0-3), intermediate-risk (4-6) and high-risk (7-10) groups, whose estimated median survival times 29.10, 10.40 and 3.90 months, respectively. The Harrell's c-index was 0.72. Model validation supported this model's validity and reproducibility.

CONCLUSIONS

In patients with NSCLC spinal metastasis, survival was associated with age, smoking, CA125, SCC, KPS, and EGFR status. A validated scoring system based on these features was devised that can predict the survival times of those patients. This scoring system provides a basis for applying the NOMS framework and for facilitating individual treatment.

Diagnostic value analysis of combined detection of Trx, CYFRA21-1 and SCCA in lung cancer

The expression levels of thioredoxin (Trx), cytokeratin fragment 21–1 (CYFRA21-1) and serum squamous cell carcinoma antigen (SCCA) in patients with lung cancer and the diagnostic value of combined detection were investigated. Sixty-five patients with lung cancer in Weihai Municipal Hospital from January 2014 to June 2017 were retrospectively selected as the observation group, while 60 healthy subjects receiving physical examination were selected as the control group. The expression levels of serum Trx, CYFRA21-1 and SCCA were detected. The sensitivity and specificity of single detection and combined detection of these indexes were compared. Moreover, the diagnostic values of single detection and combined detection were analyzed using the receiver operating characteristic (ROC) curve. The levels of CYFRA21-1 and SCCA were the highest in squamous carcinoma (P<0.05). The level of Trx was the highest in small cell lung cancer compared with those in squamous carcinoma and adenocarcinoma (P<0.05). The levels of serum Trx, CYFRA21-1 and SCCA in lung cancer patients in clinical stage III–IV were obviously higher than those in patients in clinical stage I–II (P<0.001). The positive rate of Trx was the highest in small cell lung cancer, and the positive rates of CYFRA21-1 and SCCA were the highest in squamous carcinoma compared with other cancers (P<0.05). The area under the ROC curve of combined detection of the three indexes was the largest. The optimal cut-off value of combined detection of the three indexes in lung cancer was 9.952 with the sensitivity of 86.2% and specificity of 75.0%. The detection of serum Trx, CYFRA21-1 and SCCA is of great significance in the diagnosis, progression and pathological type of lung cancer, and combined detection can improve both specificity and sensitivity, which is more conducive to the positive rate of diagnosis of lung cancer.

Application of serum microRNA-9-5p, 21-5p, and 223-3p combined with tumor markers in the diagnosis of non-small-cell lung cancer in Yunnan in southwestern China

Purpose

Xuanwei City is located in late Permian coal-accumulating areas of the northeastern region of Yunnan Province. In China, morbidity and mortality from lung cancer are highest in Yunnan. Identifying useful circulating markers suitable for the diagnosis of lung cancer in this region is quite meaningful. In this study, we evaluated diagnostic roles of serum miR-9-5p, 21-5p, 223-3p, 135b-5p, 339-5p, and 501-5p in patients with non-small-cell lung cancer (NSCLC) in Yunnan. Moreover, we evaluated the diagnostic performance of several tumor markers, including carcinoembryonic antigen (CEA), cytokeratin 19 fragment 21-1 (CYFRA21-1), and squamous cell carcinoma-related antigen (SCC).

Methods

Quantitative real-time polymerase chain reaction detected six miRNAs in the serum of 104 NSCLC patients and 50 cancer-free controls. Other markers, including CEA, CYFRA21-1, and SCC, in serum were also measured. The diagnostic ability of miRNAs and tumor markers was evaluated by receiver operating characteristic (ROC) curve analysis. The diagnostic performance of these serum markers was also evaluated in Xuanwei and non-Xuanwei subjects, because the etiological and the epidemiological characteristics of lung cancer in Xuanwei were quite different from those in other regions.

Results

Serum miR-9-5p, miR-21-5p, miR-223-3p, CEA, CYFRA21-1, and SCC were upregulated in NSCLC patients, compared with cancer-free controls. No significant difference was found in miR-135b-5p, miR-339-5p, and miR-501-5p expression. The area under ROC curves (AUCs) of miR-9-5p, miR-21-5p, miR-223-3p, CEA, CYFRA21-1, and SCC were 0.706, 0.765, 0.744, 0.749, 0.735, and 0.616, respectively. When combined, miRNAs and tumor markers yielded the highest diagnostic power, with AUC of 0.886, sensitivity of 82.69%, and specificity of 88.00%. In Xuanwei subjects, miR-223-3p and CEA may be suitable biomarkers to distinguish NSCLC from cancer-free states with AUCs of 0.752 and 0.791, respectively. The diagnostic power of the combination of miRNAs and tumor markers was still the highest in both subgroups (region: Xuanwei and non-Xuanwei; stages: I–II and III–IV).

Conclusion

Serum miR-9-5p, miR-21-5p, miR-223-3p, CEA, CYFRA21-1, and SCC could be potential diagnostic biomarkers for NSCLC patients in Yunnan. miRNAs and tumor markers should be combined to diagnose NSCLC, as it showed better ability for screening patients with NSCLC.

Development of a novel biomarker model for predicting preoperative lymph node metastatic extent in esophageal squamous cell carcinoma1

The number and range of lymph node metastasis (LNM) are critical prognostic factors in esophageal squamous cell carcinoma (ESCC). Preoperative serum biomarkers are reported to be associated with LNM. However, whether these markers can precisely predict the extent of LNM is not known. The aim of this study was to evaluate the predictive value of preoperative serum SCC-Ag, Cyfra21-1, CEA, CA19-9 and CA72-4 for LNM number and range by retrospectively investigating 577 ESCC patients undergone esophagectomy from 2007-2010. In this study, the positive rate of SCC-Ag and CA19-9 were associated with pN stage. Significant differences were found in CEA and CA19-9 between pN0-1 stage patients and pN2-3 stage patients. However, in subgroup analysis (patients with pN0-1), significant difference was found only in SCC-Ag between pN0 and pN1 stage patients (P=0.003). Middle thoracic ESCC patients were Chosen to analyze the correlation between the range of LNM and biomarkers. SCC-Ag was correlated with paraesophageal and paracardial lymph nodes, but not correlated with subcarinal and left gastric artery lymph nodes. Interestingly, the results of CEA were opposite to that of SCC-Ag. CA19-9 was associated with subcarinal and paracardial LNM (P=0.000, P=0.038). Based on the results, a model incorporated SCC-Ag, CEA and CA19-9 was constructed. The rate of patients with pN2-3 stage was 15.4% and 54.4% in group 1 and 4 of our model.

In summary, SCC-Ag was associated with early lymph node metastatic stage, and CEA and CA19-9 have a close relationship with advanced lymph node metastatic stage. The model combining SCC-Ag, CEA and CA19-9 might help identify the preoperative extent of LNM for a subgroup of ESCC patients that can be benefited from neoadjuvant therapy.

The clinical use of circulating microRNAs as non-invasive diagnostic biomarkers for lung cancers

Many studies have investigated the diagnostic role of circulating microRNAs (miRNAs) in patients with lung cancer; however, the results still remain inconclusive. An updated system review and meta-analysis was necessary to give a comprehensive evaluation of diagnostic role of circulating miRNAs in lung cancer. Eligible studies were searched in electronical databases. The sensitivity and specificity were used to plot the summary receiver operator characteristic (SROC) curve and calculate the area under the curve (AUC). The between-study heterogeneity was evaluated by Q test and I² statistics. Subgroup analyses and meta-regression were further performed to explore the potential sources of heterogeneity. A total of 134 studies from 65 articles (6,919 patients with lung cancer and 7,064 controls) were included for analysis. Overall analysis showed that circulating miRNAs had a good diagnostic performance in lung cancers, with a sensitivity of 0.83, a specificity of 0.84, and an AUC of 0.90. Subgroup analysis suggested that combined miRNAs and Caucasian populations may yield relatively higher diagnostic performance. In addition, we found serum might serve as an ideal material to detecting miRNA as good diagnostic performance. We also found the diagnostic role of miRNAs in early stage lung cancer was still relatively high (the sensitivity, specificity and an AUC of stage I/II was 0.81, 0.82 and 0.88; and for stage I, it was 0.80, 0.81, and 0.88). We also identified a panel of miRNAs such as miR-21-5p, miR-223-3p, miR-155-5p and miR-126-3p might serve as potential biomarkers for lung cancer. As a result, circulating miRNAs, particularly the combination of multiple miRNAs, may serve as promising biomarkers for the diagnosis of lung cancer.