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Marc Andre Schneider



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    EP1.03 - Biology (ID 193)

    • Event: WCLC 2019
    • Type: E-Poster Viewing in the Exhibit Hall
    • Track: Biology
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/08/2019, 08:00 - 18:00, Exhibit Hall
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      EP1.03-30 - FAM83A and FAM83B as Prognostic Biomarkers and Potential New Therapeutic Targets in NSCLC (Now Available) (ID 587)

      08:00 - 18:00  |  Author(s): Marc Andre Schneider

      • Abstract
      • Slides

      Background

      Although targeted therapy improved survival rates in the last decade, non-small cell lung cancer (NSCLC) is still the most common cause of cancer related death. As most precision medicines lead to resistance, the challenge of identifying new targets for further effective therapies still remains. The FAMily with sequence similarity 83 (FAM83) members have recently been described as novel oncogenes in numerous human cancer specimens and shown to be involved in EGFR signaling. However, their function in cancer cells is largely unknown and especially their role in lung cancer remains unclear.

      Method

      Here, we investigated the expression and function of FAM83A and B in NSCLC. First, gene expression of the two FAM83 members was analyzed in a set of 362 NSCLC patients using qPCR. We further investigated relations in expression and their prognostic value using correlation and multivariate COX regression analyses. Functional assays in NSCLC cell lines were performed to analyze their involvement in proliferation, anchorage-independent growth, migration and the epidermal growth factor receptor (EGFR) pathway.

      Result

      We observed a highly increased gene expression level of FAM83A (ø = 68-fold) and FAM83B (ø = 20-fold) which resulted in poor survival prognosis (p < 0.0001 and p = 0.002). Correlation analysis showed poor relation between FAM83A and B in the two sub-histologies adenocarcinoma (ADC) and squamous cell carcinoma (SQCC) but confirmed correlation between FAM83A and B and EGFR expression levels in patients and cell lines. Their expression was further influenced by EGFR pathway signaling and mutation status. Both genes affected cell proliferation and FAM83A depletion resulted in reduced migration and AIG.

      Conclusion

      The results support the hypothesis that FAM83A and B have different specific functions in the histological subtypes of NSCLC and might be new therapeutic targets.

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    EP1.11 - Screening and Early Detection (ID 201)

    • Event: WCLC 2019
    • Type: E-Poster Viewing in the Exhibit Hall
    • Track: Screening and Early Detection
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/08/2019, 08:00 - 18:00, Exhibit Hall
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      EP1.11-20 - A Panel of Liquid Biomarkers for Early Response Capturing of NSCLC Therapies in Advanced Stages (Now Available) (ID 632)

      08:00 - 18:00  |  Presenting Author(s): Marc Andre Schneider

      • Abstract
      • Slides

      Background

      CT scans are the gold standard to measure treatment success of Non-Small Cell Lung Cancer (NSCLC) therapies. In recent years, liquid biopsies became an adequate diagnostic tool especially in advanced disease stages.

      Method

      Here, we investigated very early tumor response of patients receiving chemotherapy or targeted therapies using a panel of already established and explorative liquid biomarkers. Blood samples from patients were taken at baseline and day + 1 for the chemotherapy cohort (n = 25) and at baseline, day +7 and +14 for the targeted therapy cohort (n = 25). DNA mutational load, a panel of 17 microRNAs, glycodelin, glutathione disulfide, glutathione, soluble caspase-cleaved keratin 18 (M30 antigen) and soluble keratin 18 (M65 antigen) were measured using serum and plasma from patients. Baseline and first follow-up CT scan were evaluated by an experienced radiologist and correlated with biomarker data.

      Result

      In the majority of patients a decrease in glycodelin abundance as well as mutational load coincided with clinical response as assessed by CT scan. Consequently, an increase of these biomarkers implicated progressive disease. Among the measured miRNAs, miR-103, miR-628-3p, and let-7e showed largely similar behavior within individual patients upon treatment initiation. The abundance of these miRNAs increased in responding patients and in a subset of patients experiencing tumor progression. Similar observations were seen for the apoptosis markers while the best results were obtained with the detection of M65.

      Conclusion

      Taken together, several investigated biomarkers showed high potential for an early response capturing in defined NSCLC cohorts.

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    P1.01 - Advanced NSCLC (ID 158)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Advanced NSCLC
    • Presentations: 2
    • Moderators:
    • Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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      P1.01-34 - Early Assessment of Therapy Response in Non-Small Cell Lung Cancer (NSCLC) via Longitudinal ctDNA Analysis (ID 2795)

      09:45 - 18:00  |  Author(s): Marc Andre Schneider

      • Abstract

      Background

      Quantifying circulating tumor DNA (ctDNA) is an emerging method to non-invasively assess treatment effect for solid tumors. Despite disease heterogeneity in NSCLC, we set out to identify a broadly applicable ctDNA-based method for disease monitoring. By employing plasma taken during early treatment cycles, we tested whether early response assessed by ctDNA level could predict treatment effect.

      Method

      Using a 197-gene NGS assay, the AVENIO ctDNA Surveillance Kit (For Research Use Only, not for use in diagnostic procedures), we measured ctDNA levels in post-treatment plasma samples based on variants identified at baseline.

      We used samples from an observational German Lung Cancer Multi-Marker Study. In a cohort of 83 stage IV lung adenocarcinoma treated with first-line chemo or chemoradiation therapies, we evaluated the association between survival and ctDNA levels in the first available post-treatment plasma sample (median number of days after start of treatment = 23). We used a ctDNA-based monitoring algorithm, and applied it to an independent set of 22 late stage lung squamous cell carcinoma that also underwent chemo or chemoradiation therapies to further evaluate the algorithm in different histology subtypes.

      Result

      We divided the 83 adenocarcinoma cohort into training (n=53) and test (n=30) sets. We found that subjects with longer progression free survival (PFS) had mean allele fraction (AF) < 1% in the training set. We applied the classifier to our adenocarcinoma test set and found that subjects with mean AF < 1% had longer PFS (HR 0.35; 95% CI 0.12 - 0.93; log-rank P = 0.028) and overall survival (OS) (HR 0.29; 95% CI 0.09 - 0.89; log-rank P= 0.021).

      Using cutoffs identified in adenocarcinoma, we applied the same algorithms to the squamous cell carcinoma cohort. Subjects with mean AF < 1% had longer PFS (HR 0.26; 95% CI 0.10 - 0.71; log-rank P = 0.005) and OS (HR 0.12; 95% CI 0.05 - 0.51; log-rank P= 0.001).

      Conclusion

      Even in heterogeneous diseases such as NSCLC, changes in ctDNA levels in response to treatment may prove to be a valuable way of identifying subjects who may not benefit, before current standard of care methods like computed tomography (CT) scan. Future prospective studies to confirm these results are warranted.

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      P1.01-58 - Comprehensive Serial Biomaterial Acquisition in Advanced NSCLC: Feasibility, Challenges and Perspectives (ID 473)

      09:45 - 18:00  |  Presenting Author(s): Marc Andre Schneider

      • Abstract
      • Slides

      Background

      Availability of tumour material at baseline and disease progression is increasingly important for patient management in non-small-cell lung cancer (NSCLC), especially in tyrosine kinase and immune checkpoint inhibitor treatment. Here, we report the experience with prospective biobanking for advanced NSCLC from a pilot project in the academic setting.

      Method

      Main objective was the longitudinal collection of snap-frozen in addition to formalin-fixed paraffin-embedded (FFPE) biopsies required for routine diagnostics, along with blood samples and detailed clinical annotation using standardized questionnaires.

      Result

      Over five years, 205 patients were enrolled yielding 387 cryoconserved biopsies and 1098 serum, plasma and buffy-coat samples. The feasibility of obtaining cryoconserved in addition to FFPE biopsies was 89 % for newly diagnosed cases, but dropped down to 56 % and 47 % at first and second disease progression, respectively. Main obstacle was increased procedural risk due to patient deterioration, but no complications occurred. Biopsies had a tumour cellularity of 34 % and yielded 13.6 µg DNA and 12 µg RNA in median.

      Conclusion

      Despite the poor condition and limited prognosis of most NSCLC patients, systematic, serial biomaterial acquisition including routine collection of cryoconserved biopsies is feasible in order to facilitate individualized management and support research that will advance therapeutic options.

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    P2.03 - Biology (ID 162)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Biology
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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      P2.03-04 - The Prognostic Value of Serological Tumor Markers in Lung Cancer – Analysis of 13,373 Cases (ID 800)

      10:15 - 18:15  |  Author(s): Marc Andre Schneider

      • Abstract
      • Slides

      Background

      Serological tumor markers such as Carcinoembryonic Antigen (CEA), Cytokeratin 19 Fragments (Cyfra 21-1) and Neuron Specific Enolase (NSE) have been shown to provide prognostic information in lung cancer. We have introduced an algorithm to combine two markers (CEA, Cyfra 21-1) into a new variable the so called tumor marker index (TMI). TMI is defined as the geometric mean of normalized marker values (Muley et al, Anticancer Res 24:1953-56, 2004).

      Method

      We have uploaded available routine tumor marker data from various sources (excel sheets, extracts from laboratory IT-systems and from our clinical cancer registry) into the clinical research data warehouse based on i2b2/tranSMART using Talend Open Studio procedures. We extracted selected clinical parameters together with tumor marker data for further analyses with the statistical software package SPSS 25.0 (IBM Deutschland GmbH, Ehningen). Pretherapeutical tumor markers were measured with Roche Elecsys (Roche Diagnostics GmbH, Penzberg). A complete set of tumor marker data for the calculation of TMI1 (CEA, CYFRA21-1) and TMI2 (CEA, CYFRA21-1, NSE) was available in n=13373 and n=13174 cases, respectively.

      Result

      The median value (range) for TMI1 and TMI2 was found to be 0.94 (0.01-1311.98) and 1.01 (0.01-201.67), respectively. Besides the validation of our originally published prognostic cut off value of 0.54 for TMI1 (Muley et al, Lung Cancer 2008, 60:408-415) in 1315 p-stage I NSCLC patients (figure), we found additional cut off values for the differentiation of prognostic groups in the data set of all patients. Up to 7 groups with patient number >1800 could be significantly differentiated by both indices (table).

      muley_fig_wclc2019.png

      TMI1
      cutoff

      Patients
      (n)

      Median
      (mos)

      HR

      TMI2
      cutoff

      Patients
      (n)

      Median
      (mos)
      HR
      0.42 2,014 62.4 1 0.55 1,989 82.1 1
      0.58 1,837 35.3 1.33 0.70 1,774 40.8 1.39
      0.79 1,891 26.3 1.61 0.89 1,913 23.5 1.92
      1.11 1,913 17.2 2.12 1.15 1,868 16.5 2.49
      1.76 1,916 13.3 2.70 1.64 1,871 13.7 3.09
      3.54 1,891 10.2 3.44 2.73 1,883 9.4 4.34
      >3.54 1,910 6.7 5.00 >2.73 1,871 6.6 5.97

      Conclusion

      The usefulness of our clinical data warehouse for assembling and structuring of clinical parameters and tumor marker data is warranted. The value of TMIs for the stratification of individual risk groups could be verified in one of the world wide largest series of tumor marker data in lung cancer.

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