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Ning Zhou
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P37 - Pathology - Biomarker Testing (ID 107)
- Event: WCLC 2020
- Type: Posters
- Track: Pathology, Molecular Pathology and Diagnostic Biomarkers
- Presentations: 1
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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P37.32 - Epigenetic Imprinted Genes as Biomarkers for the Proactive Detection and Accurate Presurgical Diagnosis of Small Lung Nodules (ID 1658)
00:00 - 00:00 | Presenting Author(s): Ning Zhou
- Abstract
Introduction
The current pulmonary nodule guidelines from The Fleischner Society recommends that lung nodules smaller than 2 cm only require clinical follow-up. However, such small-sized nodules can aggressively progress into severe conditions for certain cases. From current presurgical examination methods, it is still challenging to distinguish early-stage lung cancers from small benign nodules because of insufficient morphological evidences. Epigenetic alterations occurring at the earliest stages of tumorigenesis can be used as novel biomarkers to enhance the accurate diagnosis of small lung nodules. Quantitative Chromogenic Imprinting Gene In-Situ Hybridization (QCIGISH) technology was implemented to directly visualize and quantitatively assess the biallelic and multiallelic alterations of imprinted gene expressions during carcinogenesis and lung cancer progression. In this study, we used the QCIGISH method to analyze the expression status of an imprinted gene panel and applied a lung cancer diagnostic grading model to effectively improve the diagnostic accuracy of small lung nodules as compared to standard presurgical biopsies.
Methods
91 patients with 92 lung nodules were recruited under clinical trial NCT03882684 involving three medical centers between 2015 and 2019. One presurgical sample was taken from each nodule by minimally invasive approaches (transbronchial brushing, transbronchial brushing, or transthoracic needle aspiration), and subjected to QCIGISH detection to analyze the allelic expression status of the GNAS, GRB10, SNRPN and HM13 imprinted gene panel. These samples were blindly scored using a diagnostic grading model previously developed from 225 retrospective surgical tissues, and then compared with final diagnosis (75 lung cancers confirmed by postsurgical or small tissue histopathology, 17 benign lung lesions confirmed by >24 months follow-up).
Results
The QCIGISH method achieved high sensitivities (>90%) across all nodule sizes, while standard presurgical diagnostic procedures were only sensitive for large nodules (>2cm). For small nodules (≤2cm), QCIGISH attained 100% sensitivity which was significantly higher than transbronchial brushing (17%), transbronchial biopsy (50%), transthoracic needle aspiration (50%) and the combination of all three methods (50%) (Table 1). In addition, QCIGISH also obtained very high specificity (100%) in benign lesions. These results implied how epigenetic imprinted gene biomarkers could effectively improve the diagnostic accuracy for small lung nodules.
Conclusion
The improved accuracy demonstrated by QCIGISH over standard presurgical biopsies makes it an effective and powerful clinical tool for small lung nodule diagnosis. QCIGISH-enhanced early lung cancer diagnosis from small nodules can help minimize lung resection procedures and prevent potential further metastasis which will ultimately prolong lung cancer patients’ survival and improve their quality of life.
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P38 - Pathology - Pathology/Staging (ID 108)
- Event: WCLC 2020
- Type: Posters
- Track: Pathology, Molecular Pathology and Diagnostic Biomarkers
- Presentations: 1
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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P38.06 - Evaluation of Non-invasive Transcutaneous Bioconductance Measurement - a Risk-Stratification Biomarker for Suspicious Pulmonary Lesions (ID 2263)
00:00 - 00:00 | Author(s): Ning Zhou
- Abstract
Introduction
By conducting low dose CT screening program in the high-risk population, a large number of pulmonary nodules have been discovered by the radiology image. There is an urgent need for risk stratification biomarkers for pre-interventional assessment of growing numbers of Indeterminate Pulmonary Lesions (IPL). In the previous study, we found the bioconductance through normal lung parenchyma differs from pathologic lesions, including inflammation and malignant tumors. Using non-invasive multi-point and multiparametric measurements of transcutaneous bioconductance, the previous single-center open-labeled feasibility trial (JTO 2012;7:681) developed an algorithm with high-performance AUC/accuracy 90%. Subsequent prospective multi-center trials in US (NCT01566682) and China had lower performances (60% accuracy) attributed to data overfitting and inconsistent human performances. In this abstract, we presented the latest multi-center prospective trial (NCT0156668; China reg20170226) evaluating revised Prolung test protocol.
Methods
Institutions IRB approved the recruitment of subjects undergoing multidisciplinary evaluation of IPLs, undergo single Prolung Test measurement before biopsies. Protocol modified from previous studies; briefly only 20 surface points interrogated instead of 62, 3X measurement plus within-patient calibration improved measurement consistency. Operator training and criteria for subjects’ enrollment also modified. Collected bioconductance data is analyzed on a modified algorithm, and binary malignancy prediction score (increased/decreased) generated and locked prior to follow-up interventions. In this non-interventional study, the result of prediction is withheld from clinical investigators prior to the final diagnosis.
Results
418 of 486(86%) enrolled subjects evaluable for the outcome. Demographic distribution: male:female 44%/56%. Age range 3rd-9th decades with significant clustering around the 5th-6th decades (64%). Tissue diagnostic modalities are by surgery (193=46%) and bronchoscopy (84=20%), non-diagnostic biopsies followed by radiology(141=34%). Based on the pathological diagnosis, it includes 221(52.9%) cancers and 197(47.1%) benign. Cancer cell type predominantly adenocarcinoma (84.7%), squamous ca (9.1%), other cell types (6.2%). Test performance (Figure 1) demonstrates Sensitivity 84.2%, Specificity 73.6%, overall accuracy 79.2%, PPV 78.2%, NPV 80.6%. Focusing on the 153/193(79.3%) surgical group with pathologic staging, 128 stage I patients had a test sensitivity of 83.6%. Accuracy of test stable across size ranges 82%(4-8mm), 77.2%(8-30mm), 80%(30-50mm).
Conclusion
In this blinded prospective validation trial, the current iteration of the Prolung Test(v2.0) has significantly improved sensitivity (84.2% vs 70-75%) and specificity (73.6% vs 47-50%) over the previous version, based on the streamlined protocol of human operations and minor algorithm development. Overall performance achieved without subgroup selection based on risk score and without degradation in smaller stage I cancers. Efficacy as a follow-up tool and further benefits from hardware modifications await studies.
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P46 - Screening and Early Detection - Gene-Based Risk Stratification (ID 183)
- Event: WCLC 2020
- Type: Posters
- Track: Screening and Early Detection
- Presentations: 1
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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P46.01 - Intronic Noncoding RNA Expression of DCN is Related to Cancer-Associated Fibroblasts and NSCLC Patients’ Prognosis (ID 1545)
00:00 - 00:00 | Author(s): Ning Zhou
- Abstract
Introduction
Lung cancer has been the primary cause of cancer mortality. Prognostic evaluation by way of traditional clinical and pathological features may not be sufficient enough to support appropriate treatment. Cancer-related epigenetic biomarkers have been identified for both cancer diagnosis and prognosis. In our previous studies, we discovered an epigenetic panel of imprinted genes including DCN for prognosis of NSCLC. Here we explored the mechanism underlying the high expression of intronic DCN and NSCLC patients’ prognosis
Methods
Tissue samples of 123 NSCLC cases were retrospectively collected from Zhongshan Hospital, Fudan University and the Affiliated Yantai Yuhuangding Hospital, Qingdao University between 2010-2014 with known 5-year survival status. Quantitative chromogenic imprinted gene in-situ hybridization (QCIGISH) targeting non-coding regions was conducted to evaluate the expression status of DCN. Total allelic expression (TE), biallelic expression (BAE) and multiallelic expression (MAE) were counted manually in tissue samples as well as human lung fibroblast (HLF) cell line and mesenchymal stem cell lines including human chorionic villi-derived mesenchymal stem cells (hMSC), human bone marrow derived mesenchymal stem cells (bMSC) and human umbilical cord derived mesenchymal stem cells (qMSC) and lung cancer cell lines (A549, PC9, SKMES-1, 95D, and H460). Immunohistochemistry (IHC) of cancer-associated fibroblast (CAF)-specific marker proteins α-smooth muscle actin (α-SMA) and fibroblast activation protein (FAP) was carried out immediately after QCIGISH on the same tissue section.
Results
NSCLC cases with high expression of DCN, 91.2% (31/34) had poor prognosis (survived less than 5 years), including 8 stage I, 6 stage II, 9 stage III and 8 stage IV. High MAE level of DCN was expressed in both the stromal and epithelial areas of some samples, as well as solely expressed in the stroma for the other samples. In human cell lines, MAE was only expressed in HLF, hMSC, bMSC and qMSC, but not expressed in lung cancer cell lines (A549, PC9, SKMES-1, 95D, and H460). CAFs are the main component of tumor stroma and play a very important role in cancer aggression and prognosis. We therefore investigated whether there was a link between MAE of DCN and CAF-specific marker proteins (α-SMA and FAP). Using the RNA QCIGISH and protein IHC double staining on the same tissue, we noted higher CAF-specific biomarkers a-SMA and FAP in DCN high-expression samples than DCN low-expression samples. Furthermore, most MAE of DCN was observed in the CAF marker protein positive stromal cells. In contrast, CAF negative marker CD31 was only expressed in vascular endothelial cells but not in stromal areas.
Conclusion
Our result suggested that the relationship between MAE of DCN and poor prognosis is linked to CAFs. This method can be easily adopted for clinical presurgical samples to effectively predict NSCLC patients’ survival and guide proper treatment.
