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Gene Expression Profiling in Breast Cancer: Understanding the Molecular Basis of Histologic Grade To Improve Prognosis

ABSTRACT: Background: Histologic grade in breast cancer provides clinically important prognostic information. However, 30%-60% of tumors are classified as histologic grade 2. This grade is associated with an intermediate risk of recurrence and is thus not informative for clinical decision making. We examined whether histologic grade was associated with gene expression profi les of breast cancers and whether such profi les could be used to improve histologic grading. Methods: We analyzed microarray data from 189 invasive breast carcinomas and from three published gene expression datasets from breast carcinomas. We identified differentially expressed genes in a training set of 64 estrogen receptor (ER)-positive tumor samples by comparing expression profiles between histologic grade 3 tumors and histologic grade 1 tumors and used the expression of these genes to define the gene expression grade index. Data from 597 independent tumors were used to evaluate the association between relapse-free survival and the gene expression grade index in a Kaplan-Meier analysis. All statistical tests were two-sided. Results: We identified 97 genes in our training set that were associated with histologic grade; most of these genes were involved in cell cycle regulation and proliferation. In validation datasets, the gene expression grade index was strongly associated with histologic grade 1 and 3 status; however, among histologic grade 2 tumors, the index spanned the values for histologic grade 1-3 tumors. Among patients with histologic grade 2 tumors, a high gene expression grade index was associated with a higher risk of recurrence than a low gene expression grade index (hazard ratio = 3.61, 95% confidence interval = 2.25 to 5.78; P<.001, log-rank test). Conclusions: Gene expression grade index appeared to reclassify patients with histologic grade 2 tumors into two groups with high versus low risks of recurrence. This approach may improve the accuracy of tumor grading and thus its prognostic value. NB: The patients coming from Uppsala Hospital have been also used in other studies as in GSE3494. You can find the common set of patients in removing the abbreviation "UPP_" from the sample names and compare the results with the "INDEX (ID)" from the GSE3494 series. Keywords: disease state analysis

ORGANISM(S): Homo sapiens

PROVIDER: GSE2990 | GEO | 2006/02/16

SECONDARY ACCESSION(S): PRJNA91943

REPOSITORIES: GEO

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Project description:Background: Histologic grade in breast cancer provides clinically important prognostic information. However, 30%-60% of tumors are classified as histologic grade 2. This grade is associated with an intermediate risk of recurrence and is thus not informative for clinical decision making. We examined whether histologic grade was associated with gene expression profi les of breast cancers and whether such profi les could be used to improve histologic grading. Methods: We analyzed microarray data from 189 invasive breast carcinomas and from three published gene expression datasets from breast carcinomas. We identified differentially expressed genes in a training set of 64 estrogen receptor (ER)-positive tumor samples by comparing expression profiles between histologic grade 3 tumors and histologic grade 1 tumors and used the expression of these genes to define the gene expression grade index. Data from 597 independent tumors were used to evaluate the association between relapse-free survival and the gene expression grade index in a Kaplan-Meier analysis. All statistical tests were two-sided. Results: We identified 97 genes in our training set that were associated with histologic grade; most of these genes were involved in cell cycle regulation and proliferation. In validation datasets, the gene expression grade index was strongly associated with histologic grade 1 and 3 status; however, among histologic grade 2 tumors, the index spanned the values for histologic grade 1-3 tumors. Among patients with histologic grade 2 tumors, a high gene expression grade index was associated with a higher risk of recurrence than a low gene expression grade index (hazard ratio = 3.61, 95% confidence interval = 2.25 to 5.78; P<.001, log-rank test). Conclusions: Gene expression grade index appeared to reclassify patients with histologic grade 2 tumors into two groups with high versus low risks of recurrence. This approach may improve the accuracy of tumor grading and thus its prognostic value. NB: The patients coming from Uppsala Hospital have been also used in other studies as in GSE3494. You can find the common set of patients in removing the abbreviation "UPP_" from the sample names and compare the results with the "INDEX (ID)" from the GSE3494 series. Experiment Overall Design: 64 microarray experiments from primary breast tumors used as training set to identify genes differentially expressed in grade 1 and 3. Experiment Overall Design: 129 microarray experiments from primary breast tumors of untreated patients used as validation set to validate the list of genes and its correlation with survival. Experiment Overall Design: No replicate, no reference sample. **NOTE** There are some inconsistencies between the sample annotation provided by GEO for this experiment in the GSE2990_family.soft.gz file and the supplementary data file GSE2990_suppl_info.txt. ***

Project description:Histological grading of breast cancer defines morphological subtypes informative of metastatic potential, although not without considerable inter-observer disagreement and clinical heterogeneity particularly among the moderately differentiated grade II (G2) tumors. We posited that a gene expression signature capable of discerning tumors of grade I (G1) and grade III (G3) histology might provide a more objective measure of grade with prognostic benefit for patients with moderately differentiated disease. To this end, we studied the expression profiles of 347 primary invasive breast tumors analyzed on Affymetrix microarrays. Using class prediction algorithms, we identified 264 robust grade-associated markers, six of which could accurately classify G1 and G3 tumors, and separate G2 tumors into two highly discriminant classes (termed G2a and G2b genetic grades) with patient survival outcomes highly similar to those with G1 and G3 histology, respectively. Statistical analysis of conventional clinical variables further distinguished G2a and G2b subtypes from each other, but also from histologic G1 and G3 tumors. In multivariate analyses, genetic grade was consistently found to be an independent prognostic indicator of disease recurrence comparable to that of lymph node status and tumor size. When incorporated into the Nottingham Prognostic Index, genetic grade enhanced detection of patients with less harmful tumors, likely to benefit little from adjuvant therapy. Our findings show that a genetic grade signature can improve prognosis and therapeutic planning for breast cancer patients, and support the view that low and high grade disease, as defined genetically, reflect independent pathobiological entities rather than a continuum of cancer progression. Three separate breast cancer cohorts were analyzed: 1) Uppsala (n=249), 2) Stockholm (n=58), 3) Singapore (n=40). The Uppsala and Singapore data can be accessed here. The Stockholm cohort data can be accessed at GEO Series GSE1456. Experiment Overall Design: All tumor specimens were assessed on U133 A and B arrays.

Project description:Current prognostic factors are insufficient for precise risk-discrimination in breast cancer patients with low grade breast tumors, which, in disagreement with theoretical prognosis, occasionally form early lymph node metastasis. To identify markers for this group of patients, we employed iTRAQ-2DLC-MS/MS proteomics to 24 lymph node positive and 24 lymph node negative grade 1 luminal A primary breast tumors. Another group of 48 high-grade tumors (luminal B, triple negative, Her-2 subtypes) was also analyzed to investigate marker specificity for grade 1 luminal A tumors. From the total of 4405 proteins identified (FDR<5%), the top 65 differentially expressed together with 30 previously identified and control markers were analyzed also at transcript level. Increased levels of carboxypeptidase B1 (CPB1), PDZ and LIM domain protein 2 (PDLIM2) and ring finger protein 25 (RNF25) were associated specifically with lymph node positive grade 1 tumors, whereas stathmin 1 (STMN1) and thymosin beta 10 (TMSB10) associated with aggressive tumor phenotype also in high grade tumors at both protein and transcript level. For CPB1, these differences were also observed by immunohistochemical analysis on tissue microarrays. Upregulation of putative biomarkers in lymph node positive (vs. negative) luminal A tumors was validated by gene expression analysis of an independent published dataset (N=343) for CPB1 (p=0.00155), PDLIM2 (p=0.02027) and RELA (p=0.00015). Moreover, statistically significant connections with patient survival were identified in another public dataset (N=1678). Our findings indicate unique pro-metastatic mechanisms in grade 1 tumors that can include up-regulation of CPB1, activation of NF-κB pathway and changes in cell survival and cytoskeleton. These putative biomarkers have potential to identify the specific minor sub-population of breast cancer patients with low grade tumors who are at higher than expected risk of recurrence and who would benefit from more intensive follow-up and may require more personalized therapy.

Project description:PURPOSE: Current histopathologic systems for classifying breast tumors require evaluation of multiple variables and are often associated with significant interobserver variability. Recent studies suggest that gene expression profiles may represent a promising alternative for clinical cancer classification. Here, we investigated the use of a customized microarray as a potential tool for clinical practice. EXPERIMENTAL DESIGN: We fabricated custom 188-gene microarrays containing expression signatures for three breast cancer molecular subtypes [luminal/estrogen receptor (ER) positive, human epidermal growth factor receptor 2 (HER2), and "basaloid"], the Nottingham prognostic index (NPI-ES), and low histologic grade (TuM1). The reliability of these multiple-signature arrays (MSA) was tested in a prospective cohort of 165 patients with primary breast cancer. RESULTS: The MSA-ER signature exhibited a high concordance of 90% with ER immunohistochemistry reported on diagnosis (P < 0.001). This remained unchanged at 89% (P < 0.001) when the immunohistochemistry was repeated using current laboratory standards. Expression of the HER2 signature showed a good correlation of 76% with HER2 fluorescence in situ hybridization (FISH; ratio > or =2.2; P < 0.001), which further improved to 89% when the ratio cutoff was raised to > or =5. A proportion of low-level FISH-amplified samples (ratio, 2.2-5) behaved comparably to FISH-negative samples by HER2 signature expression, HER2 quantitative reverse transcription-PCR, and HER2 immunohistochemistry. Luminal/ER+ tumors with high NPI-ES expression were associated with high NPI scores (P = 0.001), and luminal/ER+ TuM1-expressing tumors were significantly correlated with low histologic grade (P = 0.002) and improved survival outcome in an interim analysis (hazard ratio, 0.2; P = 0.019). CONCLUSION: The consistency of the MSA platform in an independent patient population suggests that custom microarrays could potentially function as an adjunct to standard immunohistochemistry and FISH in clinical practice.

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Gene Expression Profiling in Breast Cancer: Understanding the Molecular Basis of Histologic Grade To Improve Prognosis

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