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Flow cytometric dna content analysis in neuroendocrine carcinoma of the lung. Correlation with survival and histologic subtype
Author(s) -
JacksonYork Gary L.,
Davis Bruce H.,
Memoli Vincent A.,
Warren William H.,
Gould Victor E.
Publication year - 1991
Publication title -
cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.052
H-Index - 304
eISSN - 1097-0142
pISSN - 0008-543X
DOI - 10.1002/1097-0142(19910715)68:2<374::aid-cncr2820680227>3.0.co;2-2
Subject(s) - pathology , carcinoma , medicine , stage (stratigraphy) , aneuploidy , lung , neuroendocrine tumors , small cell carcinoma , survival analysis , ploidy , oncology , biology , chromosome , paleontology , biochemistry , gene
The DNA content of 53 primary and locally metastatic pulmonary neuroendocrine carcinomas was retrospectively determined by flow cytometric analysis of nuclei released from paraffin‐embedded tissues and compared with histologic subtypes and clinical survival. Forty‐one percent (9 of 22) of tumors classified as well‐differentiated neuroendocrine carcinoma (WDNC) were aneuploid. In contrast, 85% (17 of 20) of small cell neuroendocrine carcinoma (SCNC), and 73% (8 of 11) of intermediate cell neuroendocrine carcinoma (ICNC) were aneuploid. DNA content was not a significant independent predictor of patient survival within each histologic subtype ( P > 0.05 for all subtypes). Yet, when all cases were examined as a single group, diploid cases showed better clinical survival than cases with DNA aneuploidy ( P < 0.02). However, the survival advantage for diploid DNA content did not quite achieve statistical significance when only cases of limited stage disease were analyzed (0.10 > P > 0.05). Histologic subtype was also a prognostic indicator, with WDNC cases showing a significantly longer survival than either SCNC ( P < 0.05) or ICNC ( P < 0.02), for those cases with limited‐stage disease. These results indicate information on clinical staging and the histologic subtype are important parameters to compare with DNA content analysis in determining independent prognostic factors in neuroendocrine or small cell carcinoma of the lung.