Novel blood biomarkers of human urinary bladder cancer.
OBJECTIVE
Recent data indicate that cDNA microarray gene expression profile of blood cells can reflect disease states and thus have diagnostic value. We tested the hypothesis that blood cell gene expression can differentiate between bladder cancer and other genitourinary cancers as well as between bladder cancer and healthy controls.


METHODS
We used Affymetrix U133 Plus 2.0 GeneChip (Affymetrix, Santa Clara, CA) to profile circulating blood total RNA from 35 patients diagnosed with one of three types of genitourinary cancer [bladder cancer (n = 16), testicular cancer (n = 10), and renal cell carcinoma (n = 9)] and compared their cDNA profiles with those of 10 healthy subjects. We then verified the expression levels of selected genes from the Affymetrix results in a larger number of bladder cancer patients (n = 40) and healthy controls (n = 27).


RESULTS
Blood gene expression profiles distinguished bladder cancer patients from healthy controls and from testicular and renal cancer patients. Differential expression of a combined set of seven gene transcripts (insulin-like growth factor-binding protein 7, sorting nexin 16, chondroitin sulfate proteoglycan 6, and cathepsin D, chromodomain helicase DNA-binding protein 2, nell-like 2, and tumor necrosis factor receptor superfamily member 7) was able to discriminate bladder cancer from control samples with a sensitivity of 83% (95% confidence interval, 67-93%) and a specificity of 93% (95% confidence interval, 76-99%).


CONCLUSIONS
We have shown that the gene expression profile of circulating blood cells can distinguish bladder cancer from other types of genitourinary cancer and healthy controls and can be used to identify novel blood markers for bladder cancer.
Osman
Iman
I
New York University School of Medicine, New York 10016, USA. Iman.Osmqan@med.nyu.edu
Bajorin
Dean F
DF
Sun
Tung-Tien
TT
Zhong
Hong
H
Douglas
Diah
D
Scattergood
Joseph
J
Zheng
Run
R
Han
Mark
M
Marshall
K Wayne
KW
Liew
Choong-Chin
CC
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D014408:Biomarkers, Tumor / Q000097:blood* / Q000235:genetics*; D002292:Carcinoma, Renal Cell / Q000175:diagnosis* / Q000235:genetics / Q000628:therapy; D002402:Cathepsin D / Q000235:genetics; D018797:Cell Cycle Proteins / Q000235:genetics; D011508:Chondroitin Sulfate Proteoglycans / Q000235:genetics; D002868:Chromosomal Proteins, Non-Histone / Q000235:genetics; D016000:Cluster Analysis; D005260:Female; D005500:Follow-Up Studies; D020869:Gene Expression Profiling; D006801:Humans; D018969:Insulin-Like Growth Factor Binding Proteins / Q000235:genetics; D007680:Kidney Neoplasms / Q000175:diagnosis* / Q000235:genetics / Q000556:secondary / Q000628:therapy; D008297:Male; D008875:Middle Aged; D009419:Nerve Tissue Proteins / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D015203:Reproducibility of Results; D020133:Reverse Transcriptase Polymerase Chain Reaction / Q000379:methods; D012680:Sensitivity and Specificity; D058305:Sorting Nexins; D013736:Testicular Neoplasms / Q000175:diagnosis* / Q000235:genetics / Q000628:therapy; D016896:Treatment Outcome; D018127:Tumor Necrosis Factor Receptor Superfamily, Member 7 / Q000235:genetics; D001749:Urinary Bladder Neoplasms / Q000175:diagnosis* / Q000235:genetics / Q000628:therapy; D033921:Vesicular Transport Proteins / Q000235:genetics
D014408:Biomarkers, Tumor; D018797:Cell Cycle Proteins; D011508:Chondroitin Sulfate Proteoglycans; D002868:Chromosomal Proteins, Non-Histone; D018969:Insulin-Like Growth Factor Binding Proteins; C104145:NELL2 protein, human; D009419:Nerve Tissue Proteins; C492318:SMC3 protein, human; C477748:SNX16 protein, human; D058305:Sorting Nexins; D018127:Tumor Necrosis Factor Receptor Superfamily, Member 7; D033921:Vesicular Transport Proteins; C102529:insulin-like growth factor binding protein-related protein 1; D002402:Cathepsin D