Author of

• 10583

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

  • Event: WCLC 2013
  • Type: Poster Session
  • Track: Biology
  • Presentations: 1
  • Moderators:
  • Coordinates: 10/28/2013, 09:30 - 16:30, Exhibit Hall, Ground Level

  • 10609

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    P1.06-026 - Validation of a Proliferation-based Expression Signature as Prognostic Marker in Early Stage Lung Adenocarcinoma (ID 1954)

    09:30 - 16:30  |  Author(s): E. Hughes
    • Abstract

    Background
    Use of adjuvant chemotherapy in non-small cell lung carcinoma (NSCLC) is based upon pathological stage and is not generally recommended for patients with Stage I disease despite a five-year overall mortality of 30% in Stage IA and 50% in Stage IB. Molecular biomarkers have the potential to guide treatment by identifying patients at highest risk for recurrent cancer. An evaluation of prognostic breast RNA profiles revealed a common component of cell cycle regulated mRNAs which contains the major prognostic power of each expression profile. The expression levels of cell cycle progression (CCP) genes measure tumor growth irrespective of the underlying genetic aberrations. CCP has been shown to be a highly significant predictor of cancer specific mortality at five years in three individual datasets. From these data a prognostic model was generated incorporating the CCP expression signature with pathological stage. The study herein will assess the validity of this combined clinical and gene expression score to predict five-year risk of lung cancer death in patients with early stage lung adenocarcinoma. A high combined prognostic score will identify patients with an increased risk for relapse whom may benefit significantly from adjuvant chemotherapy.

    Methods
    A cohort of patients with NSCLC adenocarcinoma was assembled with the following clinical covariates: age at diagnosis, gender, smoking status, tumor size and grade, pleural invasion, TNM Stage, adjuvant treatment status, and EGFR mutation status (if known). Outcome variables include cause of death and time to recurrence and death. An event is defined as death due to lung cancer within five years of surgery. If cause of death is unknown, death following recurrence will be used as a surrogate. A cohort with 150 events will have 99% statistical power at the 5% significance level to demonstrate an association between CCP and death from lung cancer outcome. A CCP score will be calculated from the mRNA expression levels of 31 proliferation genes in this cohort and combined with stage in a final prognostic score.

    Results
    To date, 631 Stage I and Stage II adenocarcinomas have been assembled. Two hundred and fifty-five deaths have occurred in the cohort with more than 100 deaths caused by lung cancer. Also, there have been over 150 instances of lung cancer recurrence documented. Two hundred and thirty-four samples have been processed with CCP scores ranging from -3.20 to 2.20. The distribution of CCP scores is consistent with those observed in previous cohorts of early stage lung adenocarcinoma. Complete analysis will be presented.

    Conclusion
    This validation cohort will provide adequate events to significantly demonstrate whether the prospectively defined prognostic score can define a high–risk group of early stage NSCLC patients with a high risk of death from lung cancer. This information may help guide adjuvant treatment decisions.

• 12441

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

  • Event: WCLC 2013
  • Type: Poster Session
  • Track: Biology
  • Presentations: 1
  • Moderators:
  • Coordinates: 10/30/2013, 09:30 - 16:30, Exhibit Hall, Ground Level

  • 12455

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

    09:30 - 16:30  |  Author(s): E. Hughes
    • 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.