The Prospect of Biologic Staging of Non–Small-Cell Lung Cancer

Different growth patterns of non-small cell lung cancer represent distinct biologic subtypes

BACKGROUND

We have recently shown the prognostic value of growth pattern classification in non-small cell lung cancer. The aim of this study is to validate the hypothesis that these growth patterns have a distinct angiogenic and proliferative profile.

METHODS

Hematoxylin-eosin stained tissue sections of 239 patients with non-small cell lung cancer were classified into growth patterns. One representative tissue section per patient was double immunostained with CD34 and Ki-67 antibodies. Endothelial cell proliferation fraction, tumor cell proliferation fraction, microvessel density, and Chalkley count were assessed at the invading front and the center of the selected tumor section.

RESULTS

According to the growth pattern classification, 161 patients (67.4%) had a destructive, 33 (13.8%) a papillary, and 45 (18.8%) an alveolar growth pattern. There were significant differences in endothelial cell proliferation fraction (p < 0.001), tumor cell proliferation fraction (p < 0.001), microvessel density (p < 0.001), and Chalkley count (p < 0.001) between the growth patterns. Multiple Cox regression analysis showed that a low endothelial cell proliferation fraction was consistently an independent prognostic factor for overall poor (hazard ratio = 0.93; confidence interval: 0.88 to 0.97, p = 0.002) and disease-free survival (hazard ratio = 0.94; confidence interval: 0.89 to 0.98, p = 0.007).

CONCLUSIONS

Growth patterns have a distinct angiogenic and proliferative profile. In non-small cell lung cancer, a low degree of angiogenesis (a low endothelial cell proliferation fraction) is associated with poor prognosis.

Distinct angiogenic and non-angiogenic growth patterns of lung metastases from renal cell carcinoma

AIMS

We have recently evaluated a classification of non-small-cell lung cancer based upon the presence of an angiogenic or a non-angiogenic growth pattern. The aim of the present study was to test the hypothesis that lung metastases of clear cell renal cell carcinoma (RCC) can grow without eliciting angiogenesis and give rise to the same set of growth patterns.

METHODS AND RESULTS

Tissue sections of 24 patients with lung metastases from clear cell RCC were analysed. Haematoxylin and eosin and reticulin staining were performed to evaluate growth pattern. Double-labelling with antibodies to CD34 and proliferating cell nuclear antigen (PCNA) was performed to determine the endothelial cell proliferation fraction (ECPF) and the microvessel density (MVD). Three growth patterns were observed. In the destructive growth pattern (54%), the architecture of the lung was not preserved. In the alveolar (33%) and interstitial growth patterns (13%), the normal lung parenchyma was preserved within the metastases. MVD was higher in the destructive than in the alveolar growth pattern (P = 0.009). ECPF was higher in the destructive (mean 31.1 +/- 22.7%, median 30.0) than in the alveolar growth pattern (mean 3.6 +/- 2.8%, median 3.2; P = 0.005).

CONCLUSIONS

The present study demonstrates that highly angiogenic primary tumours can give rise to non-angiogenic metastases. This type of metastasis may be resistant to antiangiogenic therapy.

A critical appraisal of prognostic and predictive factors for common lung cancers

The outlook for patients with lung cancer remains poor despite advances in the understanding of the pathology and biology of this disease. To optimize treatment protocols prognostic data are essential. The current era with molecular research on mRNA expression analysis and proteomics will lead to a plethora of new molecular markers, which are likely to be correlated, at least in part, with each other and with disease activity, progression and survival. However, although the number of prognostic factors analysed in published systematic reviews on lung cancer is large, the scope of these factors in individual studies is often narrow. In daily practice prognostic factors other than general TNM staging are not implemented. To assess the efficacy of new prognostic factors for the management of individual patients with non-small cell lung cancer, studies with clinically relevant modelling are required. In this review arguments are provided to use a model combining radiological and histopathological growth rate, histopathological diagnosis and molecular characteristics as markers for metastatic capacity, tumour volume doubling time and expected response to targeted therapy. This may reveal time-related predictive information useful for treatment guidance of the individual patient.