Virtual Library

 x 
My Library Virtual Library FAQ

Start Your Search

C. Behrens



Author of

  • +

    MO19 - Lung Cancer Immunobiology (ID 91)

    • Event: WCLC 2013
    • Type: Mini Oral Abstract Session
    • Track: Biology
    • Presentations: 1
    • +

      MO19.10 - Prevalence and prognostic association of PD-L1 protein and immune gene expression in NSCLC (ID 2437)

      11:25 - 11:30  |  Author(s): C. Behrens

      • Abstract
      • Presentation
      • Slides

      Background
      Programmed Death Ligand 1 (PD-L1, CD274, B7-H1) is an immune checkpoint molecule that binds to the receptors PD-1 and B7.1 on activated T cells. Binding negatively regulates T-cell function in both physiological and pathological conditions. Recent clinical studies have suggested that numerous cancers, including NSCLC, may utilize PD-L1 expression to escape T-cell mediated cytotoxic activity. Inhibition of PD-L1 can restore anti-tumor immunity, leading to clinical responses. A better understanding of PD-L1 expression patterns, co-expression with other immune markers and actionable disease associated biomarkers may provide insight into the future design of cancer immunotherapy trials in NSCLC.

      Methods
      Expression of PD-L1 was measured by immunohistochemistry (IHC) in archival tumors and, in some cases, in paired metastases in 2 FFPE NSCLC tumor tissue collections. Set 1 (N=561) was collected from patients who were eligible for surgery with curative intent from 2003 to 2005 at MD Anderson Cancer Center. The samples from Set 2 (N=300) contained surgically resected NSCLC tissue collected between 2006 and 2011 (UCCC and Norwegian Radium Hospital). PD-L1 expression was analyzed in both malignant and non-malignant cells (e.g., infiltrating immune cells). In addition, a multiplex qPCR assay that measures ≈90 immune-related genes was used to characterize the tumor immune microenvironment in the NSCLC tumor samples. Disease associated biomarkers, including the mutation status of EGFR and KRAS, as well as expression of MET (by IHC) were also evaluated.

      Results
      Prevalence of PD-L1 was comparable between adenocarcinoma and squamous cell carcinoma (≈30% in tumor cells; ≈45% and ≈50%, respectively, in immune cells). PD-L1 prevalence varied depending on the pathological stage, and was higher in Stages I-IIIA than in Stages IIIB-IV. Similarly, the prognostic value of PD-L1 varied by both stage and histology. In adenocarcinoma, tumors with PD-L1–positive tumor cells had a higher frequency of KRAS mutation and high Met expression, and a lower frequency of EGFR mutation compared with PD-L1–negative tumors. In contrast, tumors with PD-L1–positive and PD-L1–negative immune cells had a comparable frequency of high Met expression. Expression of PD-L1 was frequently co-localized with CD8+ T-cell infiltrates. Gene expression profiling revealed differences in the tumor immune environment, including genes associated with cytotoxic T-cells, between adenocarcinomas and squamous cell carcinomas. PD-L1 protein and immune gene expression associations with patient characteristics will be described in further detail.

      Conclusion
      These data provide a comprehensive description of PD-L1 expression in the context of disease biology utilizing large independent cohorts of well-characterized lung cancer tissues. The results highlight the complexity of the tumor immune environment in NSCLC with particular emphasis on the association with factors such as pathological stage, histology and oncogenic mutational status. These analyses may help guide future development of immunotherapy trials in NSCLC.

      Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.

      Only Active Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login or select "Add to Cart" and proceed to checkout.

  • +

    P1.06 - Poster Session 1 - Prognostic and Predictive Biomarkers (ID 161)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Biology
    • Presentations: 1
    • +

      P1.06-049 - Analysis of Tn antigen and its relationship with clinic, histologic and biomarkers profile in patients with non-small-cell lung cancer (NSCLC). (ID 2897)

      09:30 - 09:30  |  Author(s): C. Behrens

      • Abstract

      Background
      The Tn antigen (GalNAc alpha-O-Ser/Thr), a product of incomplete O-glycosylation, is expressed in about 90% of human carcinomas, but not in normal human tissues, being associated with poor prognosis in breast cancer. There is no information about the relationship between Tn antigen expression and clinical outcome of patients with lung cancer. Aim: To study the frequency of expression of the Tn antigen in a large set of surgically resected NSCLC tumor tissues, and its association with clinical, pathological and molecular characteristics including patient’s recurrence-free survival (RFS) and overall survival (OS).

      Methods
      We used tumor tissue microarrays containing 426 NSCLCs, including 281 adenocarcinomas (ADC) and 145 squamous cell carcinomas (SCC). We performed immunohistochemistry using the murine monoclonal antibody 83D4. The expression of the Tn antigen was quantified using a four-value intensity score (0, 1+, 2+, and 3+) and the percentage (0-100%) of tumor stained cells. The final score obtained was in the range 0-300. The patients were divided into 2 groups: those who received neoadjuvant chemotherapy (WNA) (n=67), and those without this treatment (WONA) (n=359).

      Results
      We found frequent Tn antigen expression in NSCLC. ADCs expressed high levels of the Tn antigen in 72.7% of cases while in SCCs Tn antigen was found in 27.3% of cases (p<0,004). In relation to smoking, patients with positive smoking history (smokers and former smokers) presented statistically higher expression of Tn than nonsmokers, (p = 0.001). We observed a trend of the Tn antigen expression in favor of male, Caucasian, under 70 years, adjuvant treatment and stage higher than I, not statistically significant. In patients with ADC but without neoadyuvant treatment, we found a statistically significant correlation of Tn antigen expression with positive smoking history too (p = 0.001) and its expression is different according the histology pattern, showing higher value in solid histology pattern and lower in lepidic, papilar and acinar histology pattern. Using Spearman Correlation test, Tn antigen correlated significantly with EpCAM-N (n = 393, r = 0.20, p = 0.001), EpCAM-C (n = 391, r = 0.12, p = 0.01), TTF-1 (n = 250, r = -0.29 p = 0.001), mutated EGFR status (p = 0.001) and KRAS (p = 0.01) and not with EML4-ALK fusion gene (p = NS). Interestingly, in the ADC-WONA subset, the high level of Tn antigen, are significantly associated with poor prognosis in RFS (p <0.04, HR = 1.45) and strong tendency in OS (p = 0.06, HR = 1.47). In the group ADC-WNA, high level of Tn antigen was significantly associated with poor prognosis in OS (p <0.02, HR = 2.84) and no difference in RFS. Patients with SCC in both groups, with or without neoadjuvant, showed no difference in prognosis regarding Tn antigen expression.

      Conclusion
      Tn antigen is frequently expressed in NSCLC and associates with worse prognosis in patients with ADC. Our data showed a significant correlation between the Tn antigen expression and other useful molecular markers in lung cancer (EPCAM, TTF-1, EGFR and KRAS), opening a new possible candidate for targeted therapy.

  • +

    P2.06 - Poster Session 2 - Prognostic and Predictive Biomarkers (ID 165)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Biology
    • Presentations: 1
    • +

      P2.06-005 - The High Incidence of Overlap between Actionable Biomarkers in NSCLC: Potential Impact on Future Clinical Trial Design (ID 360)

      09:30 - 09:30  |  Author(s): C. Behrens

      • Abstract

      Background
      Recent advances in molecular profiling of non-small cell lung cancer (NSCLC) have led to the replacement of platinum-based chemotherapy with targeted therapies for certain genetic subsets of NSCLC (ALK rearrangements, some EGFR activating mutations). It is also known that myriad pathways can drive resistance, the unfortunate norm for most patients. A greater understanding of the overlap across multiple biomarker subsets, including activating mutations, signal transduction pathways, and immune system markers, might aid in prognostic assessment, predictive biomarker development and the design of combination or sequential treatment regimens.

      Methods
      The prevalence and prognostic significance of nine biomarkers (TTF1, p63, EGFR mutation, KRAS mutation, MET immunohistochemistry [IHC], PDL1 IHC, PTEN IHC, NaPi2B IHC, ECDH IHC) across two independent sample sets (Set 1, n=561; Set 2, n=300) were tested. With the exception of ECDH, all assays were IVD or companion diagnostics. Set 1 was collected from patients who were eligible for surgery with curative intent from 2003–2005 at MD Anderson Cancer Center in the USA. Samples from Set 2 were part of a collaboration between the University of Colorado Cancer Center, USA and The Norwegian Radium Hospital, and contained surgically-resected NSCLC tissues collected from 2006–2011.

      Results
      The prevalence of each biomarker varied significantly by histology. For adenocarcinoma samples, the prevalence of each biomarker was: EGFR mutation (13%), KRAS mutation (29%), TTF1 IHC (83%), p63 IHC (7%), MET IHC (50%), PDL1 IHC (45%), PTEN loss IHC (11%), NaPi2B IHC (76%), EGFR IHC (FLEX cut-off, 11%). In squamous-cell carcinoma, the prevalence of each biomarker was: TTF1 IHC (2%), p63 IHC (87%), MET IHC (13%), PDL1 IHC (50%), PTEN loss IHC (13%), NaPi2B IHC (3%), EGFR IHC (FLEX cut-off, 40%). In addition, more than 67% of patients were positive for more than one biomarker and >33% were positive for at least three biomarkers. The diagnostic criteria for each biomarker and correlations with patient characteristics will be described in further detail. Figure 1. Biomarker Overlap in Adenocarcinoma in Set 1 (n=337) Figure 1

      Conclusion
      Collectively, these data suggest that the biomarker landscape in NSCLC is complex and will be increasingly dynamic as more experimental agents approach pivotal testing. Grant support: this study was partially funded by UT Lung Specialized Programs of Research Excellence grant (P50CA70907; IIW)

  • +

    P3.06 - Poster Session 3 - Prognostic and Predictive Biomarkers (ID 178)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Biology
    • Presentations: 1
    • +

      P3.06-015 - Integrated Prognosis in Early Stage Resectable Lung Adenocarcinoma (ID 1707)

      09:30 - 09:30  |  Author(s): C. Behrens

      • Abstract

      Background
      Treatment decisions in stage I and II resectable lung adenocarcinoma (ADC) are heterogeneous due to low efficacy of treatment and a high frequency of co-morbidities in the patient population. Currently, pathological stage is the main determinant of adjuvant treatment recommendations. The cell cycle progression (CCP) score is a proliferation based expression profile that has been shown to add significant prognostic stratification within stage I and II patients. We have developed an integrated prognostic model of pathological stage and the CCP expression score in order to maximize the prognostic utility of both markers.

      Methods
      Cox proportional hazards models with pathological stage and the CCP expression score were created from two data sets: 256 patients (190 stage I, 66 stage II) from the Director’s Consortium microarray cohort and 381 adenocarcinomas (337 stage I, 44 stage II) from a clinical study set analyzed by qPCR. Expression microarray data were scaled to adjust for differences in experimental platforms. The primary outcome measure was cancer-specific death, defined as death from lung cancer or death with recurrence within five years of surgery. Coefficients for modeling were derived from the hazard ratio in the Cox PH model.

      Results
      Both pathological stage and CCP score were independent predictors of lung cancer death in both cohorts. The coefficients for pathological stage and CCP score were consistent across both data sets and did not differ significantly between the analysis of all patients and a subset of untreated patients. A combined score (CS) of stage and CCP score (0.33 * CCP score + 0.52 * stage) was created from the subset of untreated patients. When applied to untreated patients in the clinical ADC cohort, pathological stage alone provided estimates of five-year risk of cancer-specific death of 12.6% (stage IA), 22.6% (stage IB), 38.4% (stage IIA) and 60% (stage IIB). In the same cohort, the combined score could separate stage IA patients with five-year risk estimates ranging from 6% to 24%. Similarly increased discrimination of risk estimates were observed for stage IB (10% to 42%), stage IIA (21% to 63%) and stage IIB patients (32% to 75%).

      Conclusion
      A combination of pathological stage and the CCP expression score is a more effective predictor of post-surgical risk of cancer-specific death than either marker alone. A more precise risk assessment provides better guidance in balancing treatment related risks with disease-specific survival.