Expression profiling identifies genes that predict recurrence of breast cancer after adjuvant CMF-based chemotherapy.

Cyclophosphamide, methotrexate and 5-fluorouracile (CMF)-based chemotherapy for adjuvant treatment of breast cancer reduces the risk of relapse. In this exploratory study, we tested the feasibility of identifying molecular markers of recurrence in CMF-treated patients. Using Affymetrix U133A GeneChips, RNA samples from 19 patients with primary breast cancer who had been uniformly treated with adjuvant CMF chemotherapy were analyzed. Two supervised class prediction approaches were used to identify gene markers that can best discriminate between patients who would experience relapse and patients who would remain disease-free. An additional independent validation set of 51 patients and 21 genes were analyzed by quantitative RT-PCR. Applying different algorithms to evaluate our microarray data, we identified two gene expression signatures of 21 and 12 genes containing eight overlapping genes, that predict recurrence in 19 cases with high accuracy (94%). Quantitative RT-PCR demonstrated that six genes from the combined signatures (CXCL9, ITSN2, GNAI2, H2AFX, INDO, and MGC10986) were significantly differentially expressed in the recurrence versus the non-recurrence group of the 19 cases and the independent breast cancer patient cohort (n = 51) treated with CMF. High expression levels of CXCL9, ITSN2, and GNAI2 were associated with prolonged disease-free survival (DFS) (P = 0.029, 0.018 and 0.032, respectively). When patients were stratified by combined CXCL9/ITSN2 or CXCL9/FLJ22028 tumor levels, they exhibited significantly different disease-free survival curves (P = 0.0073 and P = 0.005, respectively). Finally, the CXCL9/ITSN2 and CXCL9/FLJ22028 ratio was an independent prognostic factor (P = 0.034 and P = 0.003, respectively) for DFS by multivariate Cox analysis in the 70-patient cohort. Our data highlight the feasibility of a prognostic assay that is applicable to therapeutic decision-making for breast cancer. Whether the biomarker profile is chemotherapy-specific or whether it is a more general indicator of bad prognosis of breast cancer patients remains to be explored.

Uncovering information on expression of natural antisense transcripts in Affymetrix MOE430 datasets.

BACKGROUND: The function and significance of the widespread expression of natural antisense transcripts (NATs) is largely unknown. The ability to quantitatively assess changes in NAT expression for many different transcripts in multiple samples would facilitate our understanding of this relatively new class of RNA molecules. RESULTS: Here, we demonstrate that standard expression analysis Affymetrix MOE430 and HG-U133 GeneChips contain hundreds of probe sets that detect NATs. Probe sets carrying a "Negative Strand Matching Probes" annotation in NetAffx were validated using Ensembl by manual and automated approaches. More than 50 % of the 1,113 probe sets with "Negative Strand Matching Probes" on the MOE430 2.0 GeneChip were confirmed as detecting NATs. Expression of selected antisense transcripts as indicated by Affymetrix data was confirmed using strand-specific RT-PCR. Thus, Affymetrix datasets can be mined to reveal information about the regulated expression of a considerable number of NATs. In a correlation analysis of 179 sense-antisense (SAS) probe set pairs using publicly available data from 1637 MOE430 2.0 GeneChips a significant number of SAS transcript pairs were found to be positively correlated. CONCLUSION: Standard expression analysis Affymetrix GeneChips can be used to measure many different NATs. The large amount of samples deposited in microarray databases represents a valuable resource for a quantitative analysis of NAT expression and regulation in different cells, tissues and biological conditions.

Gene expression profiles of different clinical stages of colorectal carcinoma: toward a molecular genetic understanding of tumor progression.

BACKGROUND AND AIMS: Colorectal cancer is one of the leading causes of cancer deaths in the Western world. A better understanding of the development and progression of colorectal carcinoma is needed to define novel targets and strategies for treatment. PATIENTS/METHODS: Gene expression profiles were determined for primary tumors of 10 locally restricted (T3N0M0), 8 lymphatically metastasized (T3N+M0), 7 systemically metastasized (T3N+M1) colorectal carcinomas, and 6 specimens of normal colorectal tissue by histology-guided oligonucleotide microarray analysis. RESULTS: A total of 1,995 genes were differently regulated in primary tumors of colorectal carcinoma compared with normal colorectal tissue. Besides common features of dedifferentiation and different expression of genes involved in cell division, cell adhesion, angiogenesis, signal transduction and metabolism we observed a deregulation of genes with an as yet unclear function. We identified 126 genes that were subsequently up- and 204 genes down-regulated during tumor progression. Furthermore, we found a cluster of five genes exclusively up-regulated in primary tumors of systemically metastasized colorectal carcinomas. A comparison of locally restricted (T3N0M0) and systemically metastasized (T3N+M1) primary tumors showed 50 deregulated genes with a massive down-regulation of immune-modulatory genes in primary tumors of systemically metastasized carcinomas. Primary tumors of lymphatically (T3N+M0) and systemically metastasized (T3N+M1) carcinomas differed in the expression of 19 genes. CONCLUSION: These results provide an additional step toward the identification of crucial genes for the progression of colorectal cancer and the identification of novel treatment targets or strategies.