A Genomic Strategy to Refine Prognosis in Early-Stage Non–Small-Cell Lung Cancer

Potti, Anil; Mukherjee, Sayan; Petersen, Rebecca P.; Dressman, Holly K.; Bild, Andrea; Koontz, Jason I.; Kratzke, Robert A.; Watson, Mark A.; Kelley, Michael J.; Ginsburg, Geoffrey S.; West, Mike; Harpole, David H.; Nevins, Joseph R.

doi:10.1056/nejmoa060467

Cited by 552 publications

(364 citation statements)

References 30 publications

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“…49 Recent studies have shown that gene-expression profiles can distinguish lung cancer patients at particularly high risk of disease recurrence. 50,51 These genomic signatures have not, however, been evaluated for their ability to predict patterns of failure.…”

Section: Biological Predictorsmentioning

confidence: 99%

Factors associated with the development of brain metastases

Hubbs

Boyd

Hollis

et al. 2010

Cancer

114

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BACKGROUND The risk of developing brain metastases after definitive treatment of locally advanced nonsmall cell lung cancer (NSCLC) is approximately 30%-50%. The risk for patients with early stage disease is less defined. The authors sought to investigate this further and to study potential risk factors. METHODS The records of all patients who underwent surgery for T1-T2 N0-N1 NSCLC at Duke University between the years 1995 and 2005 were reviewed. The cumulative incidence of brain metastases and distant metastases was estimated by using the Kaplan-Meier method. A multivariate analysis assessed factors associated with the development of brain metastases. RESULTS Of 975 consecutive patients, 85% were stage I, and 15% were stage II. Adjuvant chemotherapy was given to 7%. The 5-year actuarial risk of developing brain metastases and distant metastases was 10%(95% confidence interval [CI], 8-13) and 34%(95% CI, 30-39), respectively. Of patients developing brain metastases, the brain was the sole site of failure in 43%. On multivariate analysis, younger age (hazard ratio [HR], 1.03 per year), larger tumor size (HR, 1.26 per cm), lymphovascular space invasion (HR, 1.87), and hilar lymph node involvement (HR, 1.18) were associated with an increased risk of developing brain metastases. CONCLUSIONS In this large series of patients treated surgically for early stage NSCLC, the 5-year actuarial risk of developing brain metastases was 10%. A better understanding of predictive factors and biological susceptibility is needed to identify the subset of patients with early stage NSCLC who are at particularly high risk. Cancer 2010;116:5038-46.

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Section: Biological Predictorsmentioning

confidence: 99%

Factors associated with the development of brain metastases

Hubbs

Boyd

Hollis

et al. 2010

Cancer

114

View full text Add to dashboard Cite

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“…13). Recent reports suggest a similar approach is feasible using lung cancer tissue to identify high-and low-risk groups for recurrence and survival (14)(15)(16), although these approaches do not address early detection methodologies.…”

Section: Introductionmentioning

confidence: 99%

A Macrophage Gene Expression Signature Defines a Field Effect in the Lung Tumor Microenvironment

et al. 2008

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One area of intensive investigation is to understand complex cellular and signaling interactions in the tumor microenvironment. Using a novel, although straightforward, microarray approach, we defined a gene expression signature from the lung tumor microenvironment in the murine A/J-urethane model of human lung adenocarcinoma. The tumor microenvironment is reflected by the composition of the cell types present and alterations in mRNA levels, resulting in a ''Field Effect'' around the tumor. The genes composing the Field Effect expression signature include proteases and their inhibitors, inflammation markers, and immune signaling molecules. By several criteria, the Field Effect expression signature can be attributed to the macrophage lineage, suggesting a qualitative change in the expression pattern of tumor-associated macrophages (TAM) observed in lung tumors. The protein expression levels for a number of Field Effect genes were verified by Western blot analysis of lung homogenates, and for their expression in macrophages and parenchymal cells outside of the tumors by immunohistochemistry. In addition, the Field Effect expression signature was used to classify bronchoalveolar lavage (BAL) cells from tumor-bearing or age-matched control mice. Using a variety of statistical measures, the Field Effect expression signature correctly classified the BAL cells >94% of the time. Finally, the protein levels for several Field Effect genes were higher in cellfree BAL fluid, indicating they may be secreted by the TAMs. This work suggests that TAMs generate a unique gene expression signature within the tumor microenvironment, and this signature could potentially be used for identifying lung cancer from BAL cells and/or fluid. [Cancer Res 2008;68(1):34-43]

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“…A clinical test that could identify patients likely to recur would be useful in guiding individual treatment strategies. Two groups have developed prediction methods that are promising on this front [46,47].…”

Section: To Optimize Therapy For a Given Patientmentioning

confidence: 99%

“…Potti et al identified gene-expression profiles that predicted the risk of recurrence following surgery from a cohort of 89 patients with early-stage NSCLC [47]. They tested their predictor model in 109 patients.…”

Section: To Optimize Therapy For a Given Patientmentioning

confidence: 99%

Gene expression profiling of Non-small cell lung cancer

et al. 2008

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Functional genomics has emerged over the past ten years as a novel technology to study genetic alterations. Gene expression arrays are one genomic technique employed to discover changes in the DNA expression that occur in neoplastic transformation. Microarrays have been applied to investigating lung cancer. Specific applications include discovering novel genetic changes that occur in lung tumors. Microarrays can also be applied to improve diagnosis, staging, and discover prognostic markers. The eventual goal of this technology is to discover new markers for therapy and to customize therapy based on an individual tumor genetic composition. In this review, we present the current state of gene expression array technology in its application to lung cancer.

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A Genomic Strategy to Refine Prognosis in Early-Stage Non–Small-Cell Lung Cancer

Abstract: The lung metagene model provides a potential mechanism to refine the estimation of a patient's risk of disease recurrence and, in principle, to alter decisions regarding the use of adjuvant chemotherapy in early-stage NSCLC.

Cited by 552 publications

References 30 publications

Factors associated with the development of brain metastases

Factors associated with the development of brain metastases

A Macrophage Gene Expression Signature Defines a Field Effect in the Lung Tumor Microenvironment

Gene expression profiling of Non-small cell lung cancer

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