CCDC12 gene methylation in peripheral blood as a potential biomarker for breast cancer detection.

BACKGROUND: Aberrant DNA methylation has been identified as biomarkers for breast cancer detection. Coiled-coil domain containing 12 gene (CCDC12) implicated in tumorigenesis. This study aims to investigate the potential of blood-based CCDC12 methylation for breast cancer detection. METHODS: DNA methylation level of CpG sites (Cytosine-phosphate Guanine dinucleotides) in CCDC12 gene was measured by mass spectrometry in 255 breast cancer patients, 155 patients with benign breast nodules and 302 healthy controls. The association between CCDC12 methylation and breast cancer risk was evaluated by logistic regression and receiver operating characteristic curve analysis. RESULTS: A total of eleven CpG sites were analyzed. The CCDC12 methylation levels were higher in breast cancer patients. Compared to the lowest tertile of methylation level in CpG_6,7, CpG_10 and CpG_11, the highest quartile was associated with 82%, 91%, and 95% increased breast cancer risk, respectively. The CCDC12 methylation levels were associated with estrogen receptor (ER) and human epidermal growth factor 2 (HER2) status. In ER-negative and HER2-positive (ER-/HER2+) breast cancer subtype, the combination of four sites CpG_2, CpG_5, CpG_6,7 and CpG_11 methylation levels could distinguish ER-/HER2+ breast cancer from the controls (AUC = 0.727). CONCLUSION: The hypermethylation levels of CCDC12 in peripheral blood could be used for breast cancer detection.

Breast cancer detection could be facilitated by novel blood-based DNA methylation biomarkers.The methylation levels of CpG sites in CCDC12 were higher in breast cancer than those in controls.The combination of four sites CpG_2, CpG_5, CpG_6,7 and CpG_11 methylation levels could distinguish ER-/HER2+ breast cancer subtype from the controls.

Blood FOLR3 methylation dysregulations and heterogeneity in non-small lung cancer highlight its strong associations with lung squamous carcinoma.

BACKGROUND: Non-small cell lung cancer (NSCLC) accounts for the vast majority of lung cancers. Early detection is crucial to reduce lung cancer-related mortality. Aberrant DNA methylation occurs early during carcinogenesis and can be detected in blood. It is essential to investigate the dysregulated blood methylation markers for early diagnosis of NSCLC. METHODS: NSCLC-associated methylation gene folate receptor gamma (FOLR3) was selected from an Illumina 850K array analysis of peripheral blood samples. Mass spectrometry was used for validation in two independent case-control studies (validation I: n = 2548; validation II: n = 3866). Patients with lung squamous carcinoma (LUSC) or lung adenocarcinoma (LUAD), normal controls (NCs) and benign pulmonary nodule (BPN) cases were included. FOLR3 methylations were compared among different populations. Their associations with NSCLC clinical features were investigated. Receiver operating characteristic analyses, Kruskal-Wallis test, Wilcoxon test, logistics regression analysis and nomogram analysis were performed. RESULTS: Two CpG sites (CpG_1 and CpG_2) of FOLR3 was significantly lower methylated in NSCLC patients than NCs in the discovery round. In the two validations, both LUSC and LUAD patients presented significant FOLR3 hypomethylations. LUSC patients were highlighted to have significantly lower methylation levels of CpG_1 and CpG_2 than BPN cases and LUAD patients. Both in the two validations, CpG_1 methylation and CpG_2 methylation could discriminate LUSC from NCs well, with areas under the curve (AUCs) of 0.818 and 0.832 in validation I, and 0.789 and 0.780 in validation II. They could also differentiate LUAD from NCs, but with lower efficiency. CpG_1 and CpG_2 methylations could also discriminate LUSC from BPNs well individually in the two validations. With the combined dataset of two validations, the independent associations of age, gender, and FOLR3 methylation with LUSC and LUAD risk were shown and the age-gender-CpG_1 signature could discriminate LUSC and LUAD from NCs and BPNs, with higher efficiency for LUSC. CONCLUSIONS: Blood-based FOLR3 hypomethylation was shown in LUSC and LUAD. FOLR3 methylation heterogeneity between LUSC and LUAD highlighted its stronger associations with LUSC. FOLR3 methylation and the age-gender-CpG_1 signature might be novel diagnostic markers for the early detection of NSCLC, especially for LUSC.

Integrative Multianalytical Model Based on Novel Plasma Protein Biomarkers for Distinguishing Lung Adenocarcinoma and Benign Pulmonary Nodules.

Given the pressing clinical problem of making a decision in diagnosis for subjects with pulmonary nodules, we aimed to discover novel plasma protein biomarkers for lung adenocarcinoma (LUAD) and benign pulmonary nodules (BPNs) and then develop an integrative multianalytical model to guide the clinical management of LUAD and BPN patients. Through label-free quantitative plasma proteomic analysis (data are available via ProteomeXchange with identifier PXD046731), 12 differentially expressed proteins (DEPs) in LUAD and BPN were screened. The diagnostic abilities of DEPs were validated in two independent validation cohorts. The results showed that the levels of three candidate proteins (PRDX2, PON1, and APOC3) were lower in the plasma of LUAD than in BPN. The three candidate proteins were combined with three promising computed tomography indicators (spiculation, vascular notch sign, and lobulation) and three traditional markers (CEA, CA125, and CYFRA21-1) to construct an integrative multianalytical model, which was effective in distinguishing LUAD from BPN, with an AUC of 0.904, a sensitivity of 81.44%, and a specificity of 90.14%. Moreover, the model possessed impressive diagnostic performance between early LUADs and BPNs, with the AUC, sensitivity, specificity, and accuracy of 0.868, 65.63%, 90.14%, and 82.52%, respectively. This model may be a useful auxiliary diagnostic tool for LUAD and BPN by achieving a better balance of sensitivity and specificity.

Novel Biomarker miRNA-625-3p Promotes Cell Proliferation and Metastasis of Lung Adenocarcinoma by Targeting KLF9.

BACKGROUND: MicroRNAs (miRNAs) are emerging as potential blood-based biomarkers involved in various types of carcinogenesis, including lung adenocarcinoma (LUAD). MATERIALS AND METHODS: In the present study, microarray was used to screen 2,549 miRNAs in serum samples from seven patients with LUAD and seven from healthy controls. Quantitative real-time polymerase chain reaction was used to validate the expression of miRNA in serum samples from 30 patients with LUAD and 30 heathy individuals. The area under the receiver operating characteristic curve was determined to evaluate the diagnostic capability of miR-625-3p. Cell counting kit-8 assay and Transwell assays were used to explore cell proliferation, migration and invasion. Bioinformatics prediction was applied in the search for the target genes of miR-625-3p. Quantitative real-time polymerase chain reaction, western blot and dual luciferase assay were used to validate target genes of miR-625-3p. A xenograft tumor model was established to evaluate cell proliferation in vivo. RESULTS: miR-625-3p was the miRNA most highly expressed in serum samples from patients with LUAD according to microarray analysis, this finding was verified in sera from an independent cohort, as well as in tissues based on The Cancer Genome Atlas database. Serum miR-625-3p provided a high diagnostic accuracy for LUAD (area under the curve=0.790, 95% confidence interval=0.6640-0.9152). Functionally, miR-625-3p promoted LUAD cell proliferation, migration and invasion both in vivo and in vitro. Mechanistically, we found miR-625-3p promoted cell proliferation and metastasis of LUAD by directly targeting KLF transcription factor 9 (Kruppel-like factor 9, KLF9). CONCLUSION: Our study identified that miR-625-3p plays an oncogenic role in LUAD, targeting KLF9. miR-625-3p might be a potential novel diagnostic biomarker and target for LUAD therapy.

The association between CTSZ methylation in peripheral blood and breast cancer in Chinese women.

Purpose: Previous studies have shown that DNA methylation in peripheral blood may be associated with breast cancer (BC). To explore the association between the methylation level of the Cathepsin Z (CTSZ) gene in peripheral blood and BC, we conducted a case-control study in the Chinese population. Methods: Peripheral blood samples were collected from 567 BC cases, 635 healthy controls, and 303 benign breast disease (BBD) cases. DNA extraction and bisulfite-specific PCR amplification were performed for all samples. The methylation levels of seven sites of the CTSZ gene were quantitatively determined by Mass spectrometry. The odds ratios (ORs) of CpG sites were evaluated for BC risk using per 10% reduction and quartiles analyses by logistic regression. Results: Our analysis showed that five out of the seven CpG sites exhibited significant associations with hypomethylation of CTSZ and BC, compared to healthy controls. The highest OR was for Q2 of CTSZ_CpG_1 (OR: 1.62, P=0.006), particularly for early-stage breast cancer in the case of per 10% reduction of CTSZ_CpG_1 (OR: 1.20, P=0.003). We also found that per 10% reduction of CTSZ_CpG_5 (OR: 1.39, P=0.004) and CTSZ_CpG_7,8 (OR: 1.35, P=0.005) were associated with increased BC risk. Our study also revealed that four out of seven CpG sites were linked to increased BC risk in women under 50 years of age, compared to healthy controls. The highest OR was for per 10% reduction of CTSZ_CpG_1 (OR: 1.47, P<0.001). Additionally, we found that BC exhibited lower methylation levels than BBD at CTSZ_CpG_4 (OR for Q1: 2.18, P<0.001) and CTSZ_CpG_7,8 (OR for Q1: 2.01, P=0.001). Furthermore, we observed a correlation between methylation levels and tumor stage, ER, and HER2 status in BC patients. Conclusion: Overall, our findings suggest that altered CTSZ methylation levels in peripheral blood may be associated with breast cancer, particularly in young women, and may serve as a potential biomarker for early-stage BC.

Autoantibodies of inflammatory cytokines as serum biomarkers in OSA patients.

As many as 90% of patients with obstructive sleep apnea (OSA) may be undiagnosed. It is necessary to explore the potential value of autoantibodies against CRP, IL-6, IL-8 and TNF-α in the diagnosis of OSA. ELISA was performed to detect the level of autoantibodies against CRP, IL-6, IL-8 and TNF-α in sera from 264 OSA patients and 231 normal controls (NCs). The expression level of autoantibodies against CRP, IL-6 and IL-8 in OSA were significantly higher than that in NC while the level of anti-TNF-α was lower in OSA than that in NC. The per SD increment of anti-CRP, anti-IL-6 and anti-IL-8 autoantibodies were significantly associated with a 430%, 100% and 31% higher risk for OSA, respectively. The AUC of anti-CRP was 0.808 (95% CI: 0.771-0.845) when comparing OSA with NC, while the AUC increased to 0.876 (95% CI: 0.846-0.906) combining four autoantibodies. For discrimination of severe OSA versus NC and non-severe OSA versus NC, the AUC for four autoantibodies combination was 0.885 (95% CI: 0.851-0.918) and 0.876 (95% CI: 0.842-0.913). This study revealed the association between autoantibodies against inflammatory factors and OSA, and the combination of autoantibodies against CRP, IL-6, IL-8 and TNF-α may function as novel biomarker for monitoring the presence of OSA.

Autoantibody signatures discovered by HuProt protein microarray to enhance the diagnosis of lung cancer.

This study aims to discover novel autoantibodies against tumor-associated antigens (TAAs) and establish diagnostic models for assisting in the diagnosis of lung cancer and discrimination of pulmonary nodules (PNs). Ten autoantibodies to TAAbs (TAAbs) were discovered by means of protein microarray and their serum level was also higher in 212 LC patients than that in 212 NC of validation cohort 1 (P < 0.05). The model 1 comprising 4 TAAbs and CEA reached an AUC of 0.813 (95%CI: 0.762-0.864) for diagnosing LC from normal individuals. Five TAAbs existed a significant difference between 105 malignant pulmonary nodules (MPNs) and 105 benign pulmonary nodules (BPNs) patients in validation cohort 2 (P < 0.05). Model 2 could distinguish MPNs from BPNs with an AUC of 0.845. High-throughput protein microarray is an efficient approach in discovering novel TAAbs which could be used as biomarkers in lung cancer diagnosis.

Construction of lncRNA TYMSOS/hsa-miR-101-3p/CEP55 and TYMSOS/hsa-miR-195-5p/CHEK1 Axis in Non-small Cell Lung Cancer.

As novel master regulators of initiation and progression, long non-coding RNAs (lncRNAs) can response to therapy in a wide variety of malignances. This study aimed to explore the regulatory mechanisms in non-small cell lung cancer (NSCLC) by constructing lncRNA-miRNA-mRNA networks. The whole transcriptome sequence was performed in five NSCLC tissues and their corresponding paired adjacent normal tissues. MicroRNAs (miRNAs) and mRNAs expression profiles were obtained from TCGA database. "EdgeR" R package was used for gene expression comparisons and the genes with | log2FC |> 2 and false discovery rate (FDR) adjusted P<0.05 were considered significant. Totally, 559 differentially expressed lncRNAs (DELs) (235 up-regulated, 324 down-regulated) were identified via whole transcriptome sequence analysis. Subsequently, 14 up-regulated lncRNAs were obtained in the intersection of our RNA-seq data and TCGA dataset. The dysregulations of the selected lncRNAs were evaluated through GEPIA. Three candidate lncRNAs (LINC01426, TYMSOS, VPS9D1-AS1) were finally selected for further study. Through bioinformatics prediction, with the three lnRNAs and their associated miRNAs (n=14) and mRNAs (n=218), a lncRNA-miRNA-mRNA network was constructed. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway associated with the targeted genes were proceeded. In addition, the protein-protein interaction (PPI) network construction was performed by STRING and lncRNA-miRNA-mRNA regulatory network was visualized via Cytoscape. The top ten significant hub-genes in the PPI network are identified based on their node degrees. Moreover, the lncRNA-miRNA and miRNA-mRNA interactions were predicted using the StarBase and survival analyses were performed in Kaplan-Meier plotter website. We concluded that TYMSOS/hsa-miR-101-3p/CEP55 and TYMSOS/hsa-miR-195-5p/CHEK1 ceRNA regulatory aixs may play vital roles in the occurrence and development of NSCLC, and may provide novel therapeutic targets in the future.

Plasma autoantibodies IgG and IgM to PD1/PDL1 as potential biomarkers and risk factors of lung cancer.

Antibodies targeting programmed cell death-1 (PD1) and its ligand (PDL1) have transformed current cancer therapy while little is known about the expression of anti-PD1/PDL1 autoantibodies between lung cancer (LC) patients and normal controls (NC). The expression level of anti-PD1/PDL1 IgG and IgM was detected in plasma of 325 LC and 324 NC by indirect enzyme-linked immune sorbent assay (ELISA). Western blot and indirect immunofluorescence (IIF) were used to verify the ELISA results. The association analysis was used to evaluate the odds ratio (OR) of LC. The expression of anti-PD1/PDL1 IgG in LC samples was significantly higher than NC (P < 0.001 and P < 0.05, respectively). The positive rate of anti-PD1/PDL1 IgG in LC was significantly higher than NC and significant difference was also shown in LC samples of different clinical characteristics, such as clinical stage, nodules diameter, lymph node metastasis and distant metastasis (P < 0.001). Moreover, PD1/PDL1 expression in tissues showed no significant relation with that in plasma (P > 0.05). Anti-PD1/PDL1 IgG were the risk factors related to LC (OR (95% CI): 22.433 (5.426-92.745) and 5.051 (1.316-19.386)), while anti-PD1/PDL1 IgM were the risk factors for LC with ≤ 60 years (OR (95% CI): 6.122 (1.365-27.455) and 7.664 (1.715-34.251)) and anti-PD1 IgM was also the risk factor for male LC cases(OR (95% CI): 6.948 (1.076-44.868)). Plasma anti-PD1/PDL1 IgG and IgM might serve as potential biomarkers and risk predictors for LC.

Novel blood-based FUT7 DNA methylation is associated with lung cancer: especially for lung squamous cell carcinoma.

BACKGROUND: The death rate of lung cancer (LC) ranks first in the world. Changes of DNA methylation in peripheral blood may be related to malignant tumors. It is necessary to explore blood-based biomarkers of methylation to detect LC. METHODS: Mass spectrometry assays were conducted to measure DNA methylation levels of seven CpG sites within FUT7 gene in the peripheral blood of 428 patients with LC, 233 patients with benign pulmonary nodule (BPN) and 862 normal controls (NC). The odds ratios (ORs) of all CpG sites were evaluated for their risk to LC using per SD change and tertiles analyses by logistic regression. The predictive ability of the seven FUT7 CpG sites and risk factors were evaluated by receiver operating characteristic curve (ROC). RESULTS: The methylation levels of seven CpG sites of FUT7 in LC were significantly lower than that in NC (P < 0.05). The per SD decrement of methylation level in CpG_1-7 was significantly associated with 65%, 38%, 59%, 46%, 23%, 20% and 68% higher risk for LC versus NC, respectively, and the adjusted ORs (95% CI) were 2.92 (2.17-3.96), 1.76 (1.29-2.38), 2.83 (2.09-3.82), 3.00 (2.17-4.16), 1.81 (1.35-2.43), 1.48 (1.11-1.97) and 3.04 (2.23-4.16) for the lowest tertiles of methylation level in CpG_1-7 compared with the top tertiles, respectively. The area under the curve (AUC) of FUT7_CpG_1-7 was 0.659 (CI 0.626-0.693), 0.792 (CI 0.736-0.848) and 0.729 (CI 0.665-0.792) in distinguishing LC versus NC, LUSC versus NC and LUSC versus BPN. CONCLUSIONS: Our study revealed an association between FUT7 hypomethylation and LC, especially for LUSC, which provides novel support for the blood-based methylation signatures as potential marker for assessing lung cancer risk.

CT and CEA-based machine learning model for predicting malignant pulmonary nodules.

Computed tomography (CT), an efficient radiological technology, is used to detect lung cancer in the clinic. Carcinoembryonic antigen (CEA), a common tumor biomarker, is applied in the detection of various tumors. To highlight the advantages of two-dimensional techniques and assist clinicians in optimizing lung cancer diagnostic schemes, we established a favorable model combining CT and CEA. In the study, univariate analysis was performed to screen independent predictors in a training cohort of 271 patients with malignant pulmonary nodules (MPNs) and 92 with benign pulmonary nodules (BPNs). Six machine learning-based models involving five CT predictors (mediastinal lymph node enlargement, lobulation, vascular notch sign, spiculation, and nodule number) and lnCEA were constructed and validated in an independent cohort of 129 participants (92 MPNs and 37 BPNs) by SPSS Modeler. A nomogram and the Delong test were generated by R software. Finally, the model established by logistic regression had highest diagnostic efficiency (area under the curve [AUC] = 0.912). Moreover, the diagnostic ability of the logistic model in the validation cohort (AUC = 0.882, 80.4% sensitivity, 75.7% specificity) was higher than that of the Peking University model (AUC = 0.712, 68.5% sensitivity, 70.3% specificity) and the Mayo model (AUC = 0.745, 62.0% sensitivity, 75.7% specificity). Interestingly, for the participants with intermediate (10-30 mm) and CEA-negative nodule, the model reached an AUC of 0.835 (72.3% sensitivity, 83.3% specificity). The AUC for the early lung cancer was as high as 0.822 with 67.3% sensitivity and 78.9% specificity. As a conclusion, this promising model presents a new diagnostic strategy for the clinic to distinguish MPNs from BPNs.