Biomarkers For Early-stage Lung Cancer Research Articles

Epigenetic imprinting alterations as effective diagnostic biomarkers for early-stage lung cancer and small pulmonary nodules

BackgroundEarly lung cancer detection remains a clinical challenge for standard diagnostic biopsies due to insufficient tumor morphological evidence. As epigenetic alterations precede morphological changes, expression alterations of certain imprinted genes could serve as actionable diagnostic biomarkers for malignant lung lesions.ResultsUsing the previously established quantitative chromogenic imprinted gene in situ hybridization (QCIGISH) method, elevated aberrant allelic expression of imprinted genes GNAS, GRB10, SNRPN and HM13 was observed in lung cancers over benign lesions and normal controls, which were pathologically confirmed among histologically stained normal, paracancerous and malignant tissue sections. Based on the differential imprinting signatures, a diagnostic grading model was built on 246 formalin-fixed and paraffin-embedded (FFPE) surgically resected lung tissue specimens, tested against 30 lung cytology and small biopsy specimens, and blindly validated in an independent cohort of 155 patients. The QCIGISH diagnostic model demonstrated 99.1% sensitivity (95% CI 97.5–100.0%) and 92.1% specificity (95% CI 83.5–100.0%) in the blinded validation set. Of particular importance, QCIGISH achieved 97.1% sensitivity (95% CI 91.6–100.0%) for carcinoma in situ to stage IB cancers with 100% sensitivity and 91.7% specificity (95% CI 76.0–100.0%) noted for pulmonary nodules with diameters ≤ 2 cm.ConclusionsOur findings demonstrated the diagnostic value of epigenetic imprinting alterations as highly accurate translational biomarkers for a more definitive diagnosis of suspicious lung lesions.

Abstract 5784: Integration of multiple omics underlying extreme phenotype strategy identify non-invasive prognostic biomarkers specific to early-stage lung cancer

Abstract Background Emerging studies have reported that approximately 30% of patients in stage I/II die within 5 years due to the progression and recurrence. There is a great need to identify sensitive and specific non-invasive biomarkers for the prognosis and survival prediction in early-stage lung cancer. Methods The strategy of extreme phenotype was applied for the quick identification of biomarkers associated with early-stage lung cancer survival in Boston Lung Cancer Study (BLCS) cohort. Multiple omics platforms, including SOMAscan and Infinium MethylationEPIC Array, were carried out to recognize biomarkers from the circulating (blood or serum) and solid (tissue) in different molecular levels. Public databases (e.g., TCGA, HPA and GEO) were used to be external validations. Differential analysis was performed by t-test with normalization data. Kaplan-Meier curves with the log-rank test were used to plot and compare the survival between candidate groups. Results Among the lung cancer patients in stage I registered in BLCS, we selected randomly 77 samples for omics detection, of which 37 had long time survival (mean = 157.36 mos) and 40 had short survival (mean = 19.79 mos). At the protein level, we found 120 circulating differentially expressed proteins (C-DEPs) between two extreme groups (P < 0.05), and six of them were beyond the fold change (FC) > 2 [i.e., ApoB (APOB), CK-MB (CKB CKM) and CK-MM (CKM) are up in the long; GAPDH (GAPDH), RAN (RAN) and SPHK1 (SPHK1) are up in the short]. As for their lung cancer tissues, both ApoB (APOB) and CK-MM (CKM) rarely expressed at the RNA and protein levels. Thus, we considered both ApoB and CK-MM as serum-specific proteins and the others as widespread biomarkers. At the DNA methylation level, 19,084 CpGs were identified in circulating differentially methylated positions (C-DMPs) and 80,342 in tumor DMPs (T-DMPs) with P < 0.05. Next, we integrated C-DEPs, C-DMPs and T-DMPs to interpret the origin and expression pattern of specific biomarkers. Intriguingly, several T-DMPs and C-DMPs existed only in genes of serum-specific proteins (ApoB and CK-MM) along with high correlation, but not in the widespread biomarkers. These findings indicate two separate origins where the proteins specific to serum skipped the products of RNA and protein and were directly released from the solid tissue into the circulatory system, while the widespread proteins left RNA and protein behind in situ. Furthermore, among four widespread biomarkers, we observed that the RNA of SPHK1 highly expressed in lung cancer tumors and this higher expression was associated with worse survival (Plog-rank = 1.20 × 10−6), especially in stage I (Plog-rank = 1.20 × 10−5). Similar results were found with the SPHK1 protein in tumors. These findings reveal that the prognostic effect of SPHK1 at both RNA and protein levels was particularly limited to the patients in stage I, but not in advanced stages. Conclusion This is the first study to our knowledge using extreme a phenotype strategy to identify non-invasive prognostic biomarkers for early-stage lung cancer. Utilizing integration of multiple omic platform, it is plausible to recognize and evaluate the circulating biomarkers for prognosis assessment of lung cancer. Citation Format: Mulong Du, Qianyu Yuan, Li Su, Feng Chen, David C. Christiani. Integration of multiple omics underlying extreme phenotype strategy identify non-invasive prognostic biomarkers specific to early-stage lung cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5784.

Discovering novel lung cancer associated antigens and the utilization of their autoantibodies in detection of lung cancer.

The identification of tumor-associated antigens (TAAs) and their corresponding autoantibodies in lung cancer (LC) may expand our vision of cancer immunity. This study aims to screen novel TAAs to distinguish LC from the healthy population. In our previous study, 35 genes encoding LC-associated TAAs were identified from the serological analysis of recombinant cDNA expression libraries (SEREX), and Oncomine database was further used to identify potential genes in cancer progression. Autoantibody to TAAs were tested by enzyme-linked immunosorbent assay (ELISA) in sera from 1379 participants in validation set and verification set. Based on analysis of three independent microarrays in Oncomine, ten genes were consistently dysregulated in LC. The sera level and positive frequency of the anti-TOP2A, anti-ACTR3, anti-RPS6KA5 and anti-PSIP1 from LC patients were higher than normal control in validation set. The area under curve (AUC) of anti-TOP2A, anti-ACTR3, anti-RPS6KA5 and anti-PSIP1 was respectively 0.758, 0.787, 0.707, 0.668. The sensitivity of these four autoantibodies for LC detection ranged from 26.63 % to 32.07 % with the specificity over 90 %. Data from the verification set confirmed the results. Except that, the frequency of serum autoantibody against TOP2A (43.3 %) and ACTR3 (50.0 %) was significantly higher in early stage LC than late stage (23.6 % and 22.3 %, respectively). TOP2A, ACTR3, RPS6KA5 and PSIP1 can elicit humoral immune response in LC and their autoantibodies have relationship with the tumorigenesis of LC. Anti-TOP2A and anti-ACTR3 have the potential to serve as a serological biomarkers in early stage LC.

A Plasma Long Noncoding RNA Signature for Early Detection of Lung Cancer

The early detection of lung cancer is a major clinical challenge. Long noncoding RNAs (lncRNAs) have important functions in tumorigenesis. Plasma lncRNAs directly released from primary tumors or the circulating cancer cells might provide cell-free cancer biomarkers. The objective of this study was to investigate whether the lncRNAs could be used as plasma biomarkers for early-stage lung cancer. By using droplet digital polymerase chain reaction, we determined the diagnostic performance of 26 lung cancer–associated lncRNAs in plasma of a development cohort of 63 lung cancer patients and 33 cancer-free individuals, and a validation cohort of 39 lung cancer patients and 28 controls. In the development cohort, 7 of the 26 lncRNAs were reliably measured in plasma. Two (SNHG1 and RMRP) displayed a considerably high plasma level in lung cancer patients vs. cancer-free controls (all P < .001). Combined use of the plasma lncRNAs as a biomarker signature produced 84.13% sensitivity and 87.88% specificity for diagnosis of lung cancer, independent of stage and histological type of lung tumor, and patients' age and sex (all P > .05). The diagnostic value of the plasma lncRNA signature for lung cancer early detection was confirmed in the validation cohort. The plasma lncRNA signature may provide a potential blood-based assay for diagnosing lung cancer at the early stage. Nevertheless, a prospective study is warranted to validate its clinical value.

Evaluation of serum autoantibodies against tumor-associated antigens as biomarkers in lung cancer.

We evaluated autoantibodies against nine tumor-associated antigens, including p62, p16, Koc, p53, Cyclin B1, Cyclin E, Survivin, HCC1, and RalA as serological markers in lung cancer. Enzyme-linked immunosorbent assay (ELISA) was used to detect autoantibodies in sera from 50 lung cancer patients and 42 normal controls. Then, four tumor-associated antigens of higher values were selected and validated in sera from validation group. Western blot and serum absorption test were used to confirm positive findings from ELISA. When cutoff values were set as mean optical density values plus 3 standard deviation of normal controls, the positive rate of autoantibodies against four tumor-associated antigens (Survivin, Cyclin B1, HCC1, and p53) reached 32%, 20%, 22%, and 18%, with area under the curve values of 0.653, 0.767, 0.622, and 0.623 in sera from 50 lung cancer, respectively (all p < 0.05). Results from the validation group confirmed the results. When lung cancer patients were divided by their clinicopathological characteristics into different subgroups, we have found that serum anti-Cyclin B1 and anti-HCC1 autoantibodies increased in stages 1, 2, and 3 lung cancer; anti-Survivin autoantibodies increased in stages 2 and 3 lung cancer; and anti-p53 autoantibody only increased in stage 1 when compared with their corresponding levels in controls (all p < 0.05). Serum anti-Cyclin B1 and anti-Survivin autoantibodies increased with disease histological grade 2 and 3 (both p < 0.05). And higher serum level of anti-p53 autoantibodies is positively associated with tumor size. Parallel utilization of these four anti-tumor-associated antigens (any positive) can increase sensitivity to 65.0% at 100% specificity with area under the curve of 0.908 ( p < 0.001) in lung cancer detection in validation group. Our results suggest that autoantibodies against these four tumor-associated antigens have higher values in lung cancer detection, and serum anti-Cyclin-B1 has the potential to serve as novel non-invasive biomarkers in early-stage lung cancer.

Molecular biomarkers in early-stage lung cancer.

e23082Background: Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related death worldwide; early diagnosis represents the main approach to reduce disease mortality. Molecular biom...

Identification of ENO1 As a Potential Sputum Biomarker for Early-Stage Lung Cancer by Shotgun Proteomics

BackgroundLung cancer is the leading cancer killer. Early detection will reduce the related deaths. The objective of this study was to identify potential biomarkers for early-stage lung cancer in sputum supernatant. Materials and MethodsUsing shotgun proteomics, we detected changes in protein profiles that were associated with lung cancer by analyzing sputum supernatants from 6 patients with early-stage lung cancer and 5 cancer-free controls. Using western blotting, we validated the proteomic results in 22 lung cancer cases and 22 controls. Using enzyme-linked immunosorbent assay (ELISA), we evaluated the diagnostic performance of the biomarker candidates in an independent set of 35 cases and 36 controls. ResultsProteomics identified 8 biomarker candidates for lung cancer. Western blotting validation of the candidates showed that enolase 1 (ENO1) displayed a higher expression level in patients with cancer than in cancer-free individuals (P = .015). ELISA revealed that the assessment of ENO1 expression in sputum supernatant had 58.33% sensitivity and 80.00% specificity in distinguishing patients with stage I lung cancer from cancer-free individuals. ConclusionThe analysis of protein biomarkers in sputum may provide a potential approach for the early detection of lung cancer. Future validation of all the candidates defined by shotgun proteomics in a large cohort study may help develop additional biomarkers that can be added to ENO1 to provide more diagnostic efficacy for lung cancer.