A molecular genetic and statistical approach for the diagnosis of dual-site cancers.
BACKGROUND
Concurrent tumors can be synchronous, independently derived, non-metastatic tumors or metastatic tumors. The prognosis and clinical management of patients with these different concurrent tumor types are different.


METHODS
DNA from normal and tumor tissues of 62 patients with synchronous endometrial and ovarian, bilateral ovarian, or endometrial and bilateral ovarian tumors was analyzed for loss of heterozygosity and microsatellite instability using eight polymorphic microsatellite markers at loci frequently deleted in ovarian and/or endometrial cancers. A statistical algorithm was designed to assess the clonal relationship between the tumors.


RESULTS
The original histopathology reports classified 26 (42%) case patients with single primary tumors and related metastatic lesions and 21 (34%) with independent primary tumors; 15 (24%) were unclassified. Genetic data identified 35 (56%) case patients with single primary tumors and related metastatic lesions, 18 (29%) with independent primary tumors, and nine (15%) that could not be typed. Excluding case patients with histopathology reports for which a clonal relationship was uncertain or was not reported, there was 53% concordance between genetic and histopathology diagnoses. Increasing the stringency of the statistical analysis increased the number of uncertain diagnoses but did not affect the proportion of discordant genetic and histologic diagnoses.


CONCLUSIONS
We have developed a rapid and robust combined genetic and statistical method to establish whether multiple tumors from the same patient represent distinct primary tumors or whether they are clonally related and therefore metastatic. For the majority of case patients, histopathology reports and genetic analyses were in agreement and diagnostic confidence was improved. Importantly, in approximately one-fourth of all case patients, genetic and histopathologic analyses suggested alternative diagnoses. The results suggest that genetic analysis has implications for clinical management and can be performed rapidly as a diagnostic test with paraffin-embedded tissues.
Brinkmann
Dirk
D
Gynaecology Cancer Research Unit, St. Bartholomew's and The London, Queen Mary's School of Medicine and Dentistry, University of London, London, UK.
Ryan
Andy
A
Ayhan
Ayse
A
McCluggage
W Glen
WG
Feakins
Roger
R
Santibanez-Koref
Mauro F
MF
Mein
Charles A
CA
Gayther
Simon A
SA
Jacobs
Ian J
IJ
D014408:Biomarkers, Tumor / Q000235:genetics*; D002277:Carcinoma / Q000175:diagnosis / Q000235:genetics; D043171:Chromosomal Instability; D002999:Clone Cells / Q000473:pathology; D016172:DNA Fingerprinting; D004273:DNA, Neoplasm / Q000032:analysis; D016889:Endometrial Neoplasms / Q000175:diagnosis* / Q000235:genetics*; D005260:Female; D017353:Gene Deletion; D005819:Genetic Markers; D006801:Humans; D019656:Loss of Heterozygosity; D018895:Microsatellite Repeats; D015233:Models, Statistical; D008967:Molecular Biology; D009378:Neoplasms, Multiple Primary / Q000175:diagnosis* / Q000235:genetics* / Q000473:pathology / Q000628:therapy; D016609:Neoplasms, Second Primary / Q000175:diagnosis / Q000235:genetics / Q000473:pathology / Q000628:therapy; D010051:Ovarian Neoplasms / Q000175:diagnosis* / Q000235:genetics*; D011379:Prognosis
D014408:Biomarkers, Tumor; D004273:DNA, Neoplasm; D005819:Genetic Markers