Julian R. Molina M.D., Ph.D.

Lay Description

Surgery has been the most effective form of therapy for bronchioalveolar carcinoma (BAC). Some patients will recur after surgery in multiple areas of the lung while others will remain free of disease. This study seeks to identify molecular “biomarkers” that will help predict which patients are likely to recur. To achieve this goal, the genetic profiles of tissues taken from patients with BAC that developed recurrence will be compared with patients that did not. The Mayo Clinic has a large database of patients diagnosed with lung cancer between 1997 and 2002. Among this group of 5,628 patients, 296 patients have a diagnosis of BAC and 413 have a different type called adenocarcinoma although the cells have some BAC characteristics. Cases of BAC within the database that presented as a single nodule and then progressed to either multi-nodule disease or metastasis will be analyzed and compared to BAC cases that did not recur following treatment.

Selection of biomarkers in this study is based on the hypothesis that BAC recurrence and metastasis results from the loss of control of many regulatory pathways within the cell that affect its growth. These pathways consist of complicated sequences of enzymes that interact to produce a specific result such as programmed cell death. Failure of these normal cell mechanisms can cause cancerous transformation and are due to gene abnormalities. This study will use techniques such as DNA microarray chips and tissue microarrays that will profile the genes of the cells and allow a comparison to be made between BAC cells that recur and those that do not. Genes that are expressed differentially between the two types will be tested for the potential to be used as predictive biomarkers. This will offer the prospect of being able to screen patients to determine the best candidates for surgery.

Scientific Abstract

Background: The finding of molecular biomarkers for bronchioalveolar carcinoma (BAC) could provide additional information to that gained from traditional histopathologic analysis. The application of new molecular biology approaches could yield potential new predictor markers of recurrence in BAC.

Objective: The purpose of this grant application is to find predictive biomarkers for recurrence and metastasis in BAC

Specific Aims:

• To establish a large tissue repository from a retrospective cohort of patients with BAC to identify those who developed recurrence (cases) and those who did not (controls)
• To determine clonality between BAC cases presenting as single nodule, recurrent (metastasis) and multiple nodule BAC
• To test potential biomarkers of risk in this archival tissue set using tissue microarrays.
• To discover new, potentially relevant biomarkers of risk in fresh and frozen specimens of BAC

Study Design: We will retrospectively search for cases of BAC or adenocarcinoma with BAC features at the Mayo Clinic between 1977 and 1997. We anticipate identifying approximately 300 cases and we will match appropriate controls to those cases. The large number of cases provides adequate sample size for us to set aside a subset of 20 cases as a marker testing set (to preserve this valuable tissue resource) with validation of promising markers on the much larger set of >250 cases.

Our approach to marker selection is straightforward and driven by a single hypothesis—that the process of BAC progression and recurrence depends upon the acquisition of multiple genetic changes in key regulatory genes, that these multiple changes can be detectable in BAC. The biomarkers we have selected assess various pathways involved in lung cancer.

Realizing that the genes and markers currently known and available not only for BAC but also for lung cancer may not capture key phenomena underlying BAC recurrence and metastasis, a major aim of this application is discovery. The discovery work includes the use of gene expression profiles to find gene markers predictors of recurrence in BAC. The results from these studies will allow us to continue to build our knowledge base so that better markers of risk can be identified and then studied in our archival tissue set.

Relevance: With improved identification of patients at increased risk for progression we can target better surveillance, risk reduction strategies and therapies accordingly. Moreover, our plan to identify new biomarkers in BAC may help to identify causative pathways in lung carcinogenesis that could then be targeted for specific therapies