Gene expressions and copy numbers associated with metastatic phenotypes of uterine cervical cancer.
BACKGROUND
A better understanding of the development of metastatic disease and the identification of molecular markers for cancer spread would be useful for the design of improved treatment strategies. This study was conducted to identify gene expressions associated with metastatic phenotypes of locally advanced cervical carcinomas and investigate whether gains or losses of these genes could play a role in regulation of the transcripts. Gene expressions and copy number changes were determined in primary tumors from 29 patients with and 19 without diagnosed lymph node metastases by use of cDNA and genomic microarray techniques, respectively.


RESULTS
Thirty-one genes that differed in expression between the node positive and negative tumors were identified. Expressions of eight of these genes (MRPL11, CKS2, PDK2, MRPS23, MSN, TBX3, KLF3, LSM3) correlated with progression free survival in univariate analysis and were therefore more strongly associated with metastatic phenotypes than the others. Immunohistochemistry data of CKS2 and MSN showed similar relationships to survival. The prognostic genes clustered into two groups, suggesting two major metastatic phenotypes. One group was associated with rapid proliferation, oxidative phosphorylation, invasiveness, and tumor size (MRPS23, MRPL11, CKS2, LSM3, TBX3, MSN) and another with hypoxia tolerance, anaerobic metabolism, and high lactate content (PDK2, KLF3). Multivariate analysis identified tumor volume and PDK2 expression as independent prognostic variables. Gene copy number changes of the differentially expressed genes were not frequent, but correlated with the expression level for seven genes, including MRPS23, MSN, and LSM3.


CONCLUSIONS
Gene expressions associated with known metastatic phenotypes of cervical cancers were identified. Our findings may indicate molecular mechanisms underlying development of these phenotypes and be useful as markers of cancer spread. Gains or losses of the genes may be involved in development of the metastatic phenotypes in some cases, but other mechanisms for transcriptional regulation are probably important in the majority of tumors.
Lyng
Heidi
H
Department of Radiation Biology, Health Enterprise Rikshospitalet--Radiumhospitalet, Oslo, Norway. heidi.lyng@rr-research.no
Brøvig
Runar S
RS
Svendsrud
Debbie H
DH
Holm
Ruth
R
Kaalhus
Olav
O
Knutstad
Kjetil
K
Oksefjell
Halldis
H
Sundfør
Kolbein
K
Kristensen
Gunnar B
GB
Stokke
Trond
T
D064413:3-Phosphoinositide-Dependent Protein Kinases; D000704:Analysis of Variance; D042846:CDC2-CDC28 Kinases; D002294:Carcinoma, Squamous Cell / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D002352:Carrier Proteins / Q000235:genetics / Q000378:metabolism; D018797:Cell Cycle Proteins / Q000235:genetics / Q000378:metabolism; D016000:Cluster Analysis; D005260:Female; D018628:Gene Dosage; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics; D006801:Humans; D007150:Immunohistochemistry; D051741:Kruppel-Like Transcription Factors / Q000235:genetics / Q000378:metabolism; D008207:Lymphatic Metastasis / Q000235:genetics*; D008840:Microfilament Proteins / Q000235:genetics / Q000378:metabolism; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods / Q000706:statistics & numerical data; D010641:Phenotype; D016016:Proportional Hazards Models; D011494:Protein Kinases / Q000235:genetics / Q000378:metabolism; D017346:Protein Serine-Threonine Kinases / Q000235:genetics / Q000378:metabolism; D012044:Regression Analysis; D012269:Ribosomal Proteins / Q000235:genetics / Q000378:metabolism; D016019:Survival Analysis; D020825:T-Box Domain Proteins / Q000235:genetics / Q000378:metabolism; D002583:Uterine Cervical Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology
D002352:Carrier Proteins; D018797:Cell Cycle Proteins; C501168:KLF3 protein, human; D051741:Kruppel-Like Transcription Factors; D008840:Microfilament Proteins; D012269:Ribosomal Proteins; D020825:T-Box Domain Proteins; C106884:TBX3 protein, human; C027624:ribosomal protein L11; C071058:moesin; D011494:Protein Kinases; D064413:3-Phosphoinositide-Dependent Protein Kinases; D017346:Protein Serine-Threonine Kinases; D042846:CDC2-CDC28 Kinases; C083689:CKS2 protein, human