The expression pattern of matrix-producing tumor stroma is of prognostic importance in breast cancer.
There are several indications that the composition of the tumor stroma can contribute to the malignancy of a tumor. Here we utilized expression data sets to identify metagenes that may serve as surrogate marker for the extent of matrix production and vascularization of a tumor and to characterize prognostic molecular components of the stroma.



TCGA data sets from six cancer forms, two breast cancer microarray sets and one mRNA data set of xenografted tumors were downloaded. Using the mean correlation as distance measure compact clusters with genes representing extracellular matrix production (ECM metagene) and vascularization (endothelial metagene) were defined. Explorative Cox modeling was used to identify prognostic stromal gene sets.



Clustering of stromal genes in six cancer data sets resulted in metagenes, each containing three genes, representing matrix production and vascularization. The ECM metagene was associated with poor prognosis in renal clear cell carcinoma and in lung adenocarcinoma but not in other cancers investigated. Explorative Cox modeling using gene pairs identified gene sets that in multivariate models were prognostic in breast cancer. This was validated in two microarray sets. Two notable genes are TCF4 and P4HA3 which were included in the sets associated with positive and negative prognosis, respectively. Data from laser-microdissected tumors, a xenografted tumor data set and from correlation analyses demonstrate the stroma specificity of the genes.



It is possible to construct ECM and endothelial metagenes common for several cancer forms. The molecular composition of matrix-producing cells, rather than the extent of matrix production seem to be important for breast cancer prognosis.
Department of Laboratory Medicine, Lund University Cancer Center, Translational Cancer Research, Lund University, Lund, Sweden.|Institute of Biochemistry I, Faculty of Medicine, Goethe-University Frankfurt, Frankfurt, Germany.
Sofia
S
Winslow
Department of Pathology, Regional Laboratories Region Skåne, Lund, Sweden.|Department of Clinical Sciences Lund, Division of Oncology and Pathology, Lund University, Lund, Sweden.
Kajsa Ericson
KE
Lindquist
Department of Pathology, Regional Laboratories Region Skåne, Lund, Sweden.|Department of Pathology, Sahlgrenska Cancer Center, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Anders
A
Edsjö
Department of Laboratory Medicine, Lund University Cancer Center, Translational Cancer Research, Lund University, Lund, Sweden. christer.larsson@med.lu.se.
Christer
C
Larsson
D001943:Breast Neoplasms / Q000235:genetics* / Q000401:mortality* / Q000473:pathology; D066264:Datasets as Topic; D004727:Endothelium / Q000378:metabolism / Q000473:pathology; D005109:Extracellular Matrix / Q000235:genetics / Q000378:metabolism; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D011379:Prognosis; D016016:Proportional Hazards Models; D017154:Stromal Cells / Q000378:metabolism*; D059467:Transcriptome
Breast cancer; ECM metagenes; Endothelial metagenes; P4HA3; TCF4; Tumor stroma