Gene expression profiling in cervical cancer: an exploration of intratumor heterogeneity.
OBJECTIVE
To explore intratumor heterogeneity in gene expression profiles from patients with cervical cancer.


METHODS
A total of 33 biopsies were obtained from 11 patients, sampling between two and five different areas for each tumor. The extracted RNA was hybridized onto the Affymetrix U133 Plus 2.0 oligonucleotide chip. The variance of expression within a patient (W), between patients (B) and the total variance (T = W + B) were calculated for each ProbeSet, and the ratio W/T was used as a measure of intratumor heterogeneity. Gene Ontology functional analysis was done to assess the function of genes that had high W/T (top 10%) and low W/T (bottom 10%) values.


RESULTS
In total, 448 ProbeSets (2.2% of the total) had W/T < 0.10, indicating low intratumor heterogeneity, and 537 ProbeSets (2.7% of the total) had W/T > 0.90, indicating high intratumor heterogeneity. In total 14,473 ProbeSets (72.4%) had higher intertumor than intratumor heterogeneity (W/T < 0.5). Genes with low intratumor heterogeneity were characterized by a statistically significant enrichment of immune-related functions (P < 0.0001). Genes with high intratumor heterogeneity were characterized by a significant tendency towards nuclear localization and nucleic acid binding (both P < 0.0001). For genes with W/T > 0.5, more than six biopsies would be required to minimize the intratumoral heterogeneity to <0.15; if W/T is 0.3 to 0.4, four biopsies are required; and for low W/T of 0.16 to 0.3, only two to three biopsies would be needed.


CONCLUSIONS
Although the intratumor heterogeneity was low for the majority of the tested ProbeSets, for many genes, multiple biopsies are required to obtain a reliable estimate of gene expression.
Bachtiary
Barbara
B
Department of Radiation Oncology, Clinical Study Coordination and Biostatistics, Division of Cancer Genomics and Proteomics, Princess Margaret Hospital, Toronto, Ontario, Canada.
Boutros
Paul C
PC
Pintilie
Melania
M
Shi
Willa
W
Bastianutto
Carlo
C
Li
Jian-Hua
JH
Schwock
Joerg
J
Zhang
Wendy
W
Penn
Linda Z
LZ
Jurisica
Igor
I
Fyles
Anthony
A
Liu
Fei-Fei
FF
D000230:Adenocarcinoma / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D000328:Adult; D000368:Aged; D002294:Carcinoma, Squamous Cell / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D005260:Female; D020869:Gene Expression Profiling / Q000706:statistics & numerical data; D006801:Humans; D008875:Middle Aged; D009363:Neoplasm Proteins / Q000235:genetics* / Q000378:metabolism; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data; D012334:RNA, Neoplasm / Q000235:genetics / Q000302:isolation & purification; D020133:Reverse Transcriptase Polymerase Chain Reaction; D002583:Uterine Cervical Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology
D009363:Neoplasm Proteins; D012334:RNA, Neoplasm