The influence of cancer tissue sampling on the identification of cancer characteristics.
Cancer tissue sampling affects the identification of cancer characteristics. We aimed to clarify the source of differentially expressed genes (DEGs) in macro-dissected cancer tissue and develop a robust prognostic signature against the effects of tissue sampling. For estrogen receptor (ER)+ breast cancer patients, we identified DEGs in macro-dissected cancer tissues, malignant epithelial cells and stromal cells, defined as Macro-Dissected-DEGs, Epithelial-DEGs and Stromal-DEGs, respectively. Comparing Epithelial-DEGs to Stromal-DEGs (false discovery rate (FDR) < 10%), 86% of the overlapping genes exhibited consistent dysregulation (defined as Consistent-DEGs), and the other 14% of genes were dysregulated inconsistently (defined as Inconsistent-DEGs). The consistency score of dysregulation directions between Macro-Dissected-DEGs and Consistent-DEGs was 91% (P-value < 2.2 × 10(-16), binomial test), whereas the score was only 52% between Macro-Dissected-DEGs and Inconsistent-DEGs (P-value = 0.9, binomial test). Among the gene ontology (GO) terms significantly enriched in Macro-Dissected-DEGs (FDR < 10%), 18 immune-related terms were enriched in Inconsistent-DEGs. DEGs associated with proliferation could reflect common changes of malignant epithelial and stromal cells; DEGs associated with immune functions are sensitive to the percentage of malignant epithelial cells in macro-dissected tissues. A prognostic signature which was insensitive to the cellular composition of macro-dissected tissues was developed and validated for ER+ breast patients.
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Hui
H
Xu
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Xin
X
Guo
Genomics Research Center, Harbin Medical University, Harbin, 150086, China.
Qiang
Q
Sun
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Mengmeng
M
Zhang
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Lishuang
L
Qi
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Yang
Y
Li
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Libin
L
Chen
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Yunyan
Y
Gu
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.|Key Laboratory of Ministry of Education for Gastrointestinal Cancer, Department of Bioinformatics, Fujian Medical University, Fuzhou, 350004, China.
Zheng
Z
Guo
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Wenyuan
W
Zhao
D001943:Breast Neoplasms / Q000235:genetics* / Q000473:pathology; D019295:Computational Biology; D018572:Disease-Free Survival; D047628:Estrogen Receptor alpha / Q000096:biosynthesis / Q000235:genetics; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics*; D006801:Humans; D053208:Kaplan-Meier Estimate; D009363:Neoplasm Proteins / Q000096:biosynthesis* / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis; D011379:Prognosis; D017154:Stromal Cells / Q000378:metabolism* / Q000473:pathology
D047628:Estrogen Receptor alpha; D009363:Neoplasm Proteins