Johanna Smeds

Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts

IntroductionAdjuvant breast cancer therapy significantly improves survival, but overtreatment and undertreatment are major problems. Breast cancer expression profiling has so far mainly been used to identify women with a poor prognosis as candidates for adjuvant therapy but without demonstrated value for therapy prediction.MethodsWe obtained the gene expression profiles of 159 population-derived breast cancer patients, and used hierarchical clustering to identify the signature associated with prognosis and impact of adjuvant therapies, defined as distant metastasis or death within 5 years. Independent datasets of 76 treated population-derived Swedish patients, 135 untreated population-derived Swedish patients and 78 Dutch patients were used for validation. The inclusion and exclusion criteria for the studies of population-derived Swedish patients were defined.ResultsAmong the 159 patients, a subset of 64 genes was found to give an optimal separation of patients with good and poor outcomes. Hierarchical clustering revealed three subgroups: patients who did well with therapy, patients who did well without therapy, and patients that failed to benefit from given therapy. The expression profile gave significantly better prognostication (odds ratio, 4.19; P = 0.007) (breast cancer end-points odds ratio, 10.64) compared with the Elston–Ellis histological grading (odds ratio of grade 2 vs 1 and grade 3 vs 1, 2.81 and 3.32 respectively; P = 0.24 and 0.16), tumor stage (odds ratio of stage 2 vs 1 and stage 3 vs 1, 1.11 and 1.28; P = 0.83 and 0.68) and age (odds ratio, 0.11; P = 0.55). The risk groups were consistent and validated in the independent Swedish and Dutch data sets used with 211 and 78 patients, respectively.ConclusionWe have identified discriminatory gene expression signatures working both on untreated and systematically treated primary breast cancer patients with the potential to spare them from adjuvant therapy.

Genetic Reclassification of Histologic Grade Delineates New Clinical Subtypes of Breast Cancer

Histologic grading of breast cancer defines morphologic subtypes informative of metastatic potential, although not without considerable interobserver disagreement and clinical heterogeneity particularly among the moderately differentiated grade 2 (G2) tumors. We posited that a gene expression signature capable of discerning tumors of grade 1 (G1) and grade 3 (G3) histology might provide a more objective measure of grade with prognostic benefit for patients with G2 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 with 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.

Intrinsic molecular signature of breast cancer in a population-based cohort of 412 patients

BackgroundMolecular markers and the rich biological information they contain have great potential for cancer diagnosis, prognostication and therapy prediction. So far, however, they have not superseded routine histopathology and staging criteria, partly because the few studies performed on molecular subtyping have had little validation and limited clinical characterization.MethodsWe obtained gene expression and clinical data for 412 breast cancers obtained from population-based cohorts of patients from Stockholm and Uppsala, Sweden. Using the intrinsic set of approximately 500 genes derived in the Norway/Stanford breast cancer data, we validated the existence of five molecular subtypes – basal-like, ERBB2, luminal A/B and normal-like – and characterized these subtypes extensively with the use of conventional clinical variables.ResultsWe found an overall 77.5% concordance between the centroid prediction of the Swedish cohort by using the Norway/Stanford signature and the k-means clustering performed internally within the Swedish cohort. The highest rate of discordant assignments occurred between the luminal A and luminal B subtypes and between the luminal B and ERBB2 subtypes. The subtypes varied significantly in terms of grade (p < 0.001), p53 mutation (p < 0.001) and genomic instability (p = 0.01), but surprisingly there was little difference in lymph-node metastasis (p = 0.31). Furthermore, current users of hormone-replacement therapy were strikingly over-represented in the normal-like subgroup (p < 0.001). Separate analyses of the patients who received endocrine therapy and those who did not receive any adjuvant therapy supported the previous hypothesis that the basal-like subtype responded to adjuvant treatment, whereas the ERBB2 and luminal B subtypes were poor responders.ConclusionWe found that the intrinsic molecular subtypes of breast cancer are broadly present in a diverse collection of patients from a population-based cohort in Sweden. The intrinsic gene set, originally selected to reveal stable tumor characteristics, was shown to have a strong correlation with progression-related properties such as grade, p53 mutation and genomic instability.

Gene Expression Preferentially Regulated by Tamoxifen in Breast Cancer Cells and Correlations with Clinical Outcome

The beneficial effect of the selective estrogen receptor (ER) modulator tamoxifen in the treatment and prevention of breast cancer is assumed to be through its ability to antagonize the stimulatory actions of estrogen, although tamoxifen can also have some estrogen-like agonist effects. Here, we report that, in addition to these mixed agonist/antagonist actions, tamoxifen can also selectively regulate a unique set of >60 genes, which are minimally regulated by estradiol (E2) or raloxifene in ERalpha-positive MCF-7 human breast cancer cells. This gene regulation by tamoxifen is mediated by ERalpha and reversed by E2 or ICI 182,780. Introduction of ERbeta into MCF-7 cells reverses tamoxifen action on approximately 75% of these genes. To examine whether these genes might serve as markers of tamoxifen sensitivity and/or the development of resistance, their expression level was examined in breast cancers of women who had received adjuvant therapy with tamoxifen. High expression of two of the tamoxifen-stimulated genes, YWHAZ/14-3-3z and LOC441453, was found to correlate significantly with disease recurrence following tamoxifen treatment in women with ER-positive cancers and hence seem to be markers of a poor prognosis. Our data indicate a new dimension in tamoxifen action, involving gene expression regulation that is tamoxifen preferential, and identify genes that might serve as markers of tumor responsiveness or resistance to tamoxifen therapy. This may have a potential effect on the choice of tamoxifen versus aromatase inhibitors as adjuvant endocrine therapy.

Inhibitory effects of estrogen receptor beta on specific hormone-responsive gene expression and association with disease outcome in primary breast cancer.

IntroductionThe impact of interactions between the two estrogen receptor (ER) subtypes, ERα and ERβ, on gene expression in breast cancer biology is not clear. The goal of this study was to examine transcriptomic alterations in cancer cells co-expressing both receptors and the association of gene expression signatures with disease outcome.MethodsTranscriptional effects of ERβ overexpression were determined in a stably transfected cell line derived from ERα-positive T-47D cells. Microarray analysis was carried out to identify differential gene expression in the cell line, and expression of key genes was validated by quantitative polymerase chain reaction. Microarray and clinical data from patient samples were then assessed to determine the in vivo relevance of the expression profiles observed in the cell line.ResultsA subset of 14 DNA replication and cell cycle-related genes was found to be specifically downregulated by ERβ. Expression profiles of four genes, CDC2, CDC6, CKS2, and DNA2L, were significantly inversely correlated with ERβ transcript levels in patient samples, consistent with in vitro observations. Kaplan-Meier analysis revealed better disease outcome for the patient group with an expression signature linked to higher ERβ expression as compared to the lower ERβ-expressing group for both disease-free survival (p = 0.00165) and disease-specific survival (p = 0.0268). These findings were further validated in an independent cohort.ConclusionOur findings revealed a transcriptionally regulated mechanism for the previously described growth inhibitory effects of ERβ in ERα-positive breast tumor cells and provide evidence for a functional and beneficial impact of ERβ in primary breast tumors.

A single nucleotide polymorphism in the 3'untranslated region of the CDKN2A gene is common in sporadic primary melanomas but mutations in the CDKN2B, CDKN2C, CDK4 and p53 genes are rare.

In this report we present the results of mutational analysis of the CDKN2B, CDKN2C, CDK4, p53 genes and 5′UTR of the CDKN2A gene in a set of 44 sporadic primary melanomas, which had been earlier analysed for mutations in the CDKN2A (p16/p14ARF) gene. No tumour‐associated mutations were detected except in 1 melanoma where we found a CC>T* deletion‐mutation in the codon 151–152 (exon 5) of the p53 gene. On the basis of our preliminary results, we did extended genotyping of the 500 C>G and 540 C>T polymorphisms in the 3′UTR of the CDKN2A gene in 229 melanoma cases and 235 controls. The T‐allele frequency (for 540 C>T polymorphism) in melanomas was significantly higher than in controls (0.14 vs. 0.08; χ2 = 5.95, p = 0.01; OR = 1.71, 95%CI = 1.11–2.66). The heterozygote frequency for this polymorphism was 0.26 (59/229) in melanomas compared to 0.13 (30/235) in healthy controls (χ2 = 11.4; p = 0.0007; OR = 2.34, 95% CI = 1.40–3.92). The frequency of the 500 C>G polymorphism in the 3′UTR in the CDKN2A gene was not significantly higher in melanomas compared to healthy controls. The 500 C>G polymorphism, however, was in linkage disequilibrium with ∼50 kb apart the C>A intronic polymorphism in the CDKN2B gene (determined in 44 melanomas and 90 controls; Fisher exact test, p<0.0001). Finally, the sequence analysis of genomic DNA isolated from T cell lymphocytes of healthy individuals exhibited that the codon reported as last of exon 2 of the CDKN2C gene is rather the first codon of exon 3.

Analysis of G1/S checkpoint regulators in metastatic melanoma

We have analyzed the expression of the CDKN1A (p21CIP1), CDKN1B (p27Kip1), TP53, RB1 and MDM2 proteins and tumor cell proliferation by immunohistochemical staining in 59 cases of metastatic melanoma. The genomic status of the CDKN2A (INK4‐ARF, p16/p14ARF), CDKN2B (p15) and CDKN2C (p18) genes was determined by PCR‐SSCP (single‐strand conformation polymorphism) in 46 of these cases. These results were correlated with various clinico‐pathological parameters, including the outcome of combined chemoimmunotherapy. We found positive correlations between the expression of CDKN1A and MDM2 (r = 0.5063, P = 0.001), between the expression of CDKN1B and RB1 (r = 0.5026, P = 0.001), and between RB1 expression and tumor cell proliferation (0.5564, P < 0.001). Two mutations in the CDKN2A (p16) gene were detected, including a novel base change AAC→ATC (Asn to Ile) at codon 71, that also changes the codon 85 of the alternative reading frame gene p14ARF from CAA to CAT (Gln to His). Homozygous deletion at exon 2 of the CDKN2A (INK4‐ARF) gene was detected in six cases. In seven cases, the 540C→G polymorphism in the 3′UTR of the CDKN2A (p16) gene was found in linkage disequilibrium with the 74C→A polymorphism in intron 1 of the CDKN2B gene (P < 0.0001). These cases had significantly lower expression of the TP53 protein (P = 0.0032). Both 540C→G and 580C→T polymorphisms in the 3′UTR of the CDKN2A (p16) gene were associated with significantly shorter progression time from primary to metastatic disease (P = 0.0071). We conclude, that although none of the analyzed cell cycle regulators could be singled out as a major prognostic factor, G1/S checkpoint abnormalities remain one of the most significant factors in the development of malignant melanoma. Genes Chromosomes Cancer 28:404–414, 2000.

Loss of heterozygosity at chromosome 9p21 (INK4-p14ARF locus): homozygous deletions and mutations in the p16 and p14ARF genes in sporadic primary melanomas.

Loss of heterozygosity (LOH) was determined in 45 sporadic primary melanomas at six polymorphic microsatellite markers that flank the INK4a (p16-p14ARF) locus on chromosome 9p21. We also determined allelic loss at two markers on chromosome 9q and two markers at the Rb locus on chromosome 13. Homozygous deletion of the p16 and p14ARF genes was determined by a fluorescent-based quantitative multiplex polymerase chain reaction method. LOH at one or more polymorphic microsatellite markers on locus 9p21 was found in 32 of the melanomas (71%). The highest proportion of LOH was found at markers D9S736 and D9S104, which are telomeric and centromeric to the INK4 locus, respectively. Five melanomas showed LOH at all the analysed markers located on chromosome 9p21. LOH at markers D9S942 and D9S974, which are located close to the p16 and p14ARF genes, was found in 39% and 46% of melanomas, respectively. Analysis of the marker D9S257 on 9q22.1 showed LOH in 13 melanomas (44% of the informative cases). A subset of melanomas with LOH at the INK4 locus also carried inactivating mutations within the p16 coding sequence. Four melanomas carried homozygous deletions at the p16-p14ARF locus. Our results suggest, besides the involvement of the INK4 locus in sporadic melanomas, the possibility of the existence of additional tumour suppressor loci on chromosome 9.

Hormone-replacement therapy influences gene expression profiles and is associated with breast-cancer prognosis: a cohort study

BackgroundPostmenopausal hormone-replacement therapy (HRT) increases breast-cancer risk. The influence of HRT on the biology of the primary tumor, however, is not well understood.MethodsWe obtained breast-cancer gene expression profiles using Affymetrix human genome U133A arrays. We examined the relationship between HRT-regulated gene profiles, tumor characteristics, and recurrence-free survival in 72 postmenopausal women.ResultsHRT use in patients with estrogen receptor (ER) protein positive tumors (n = 72) was associated with an altered regulation of 276 genes. Expression profiles based on these genes clustered ER-positive tumors into two molecular subclasses, one of which was associated with HRT use and had significantly better recurrence free survival despite lower ER levels. A comparison with external data suggested that gene regulation in tumors associated with HRT was negatively correlated with gene regulation induced by short-term estrogen exposure, but positively correlated with the effect of tamoxifen.ConclusionOur findings suggest that post-menopausal HRT use is associated with a distinct gene expression profile related to better recurrence-free survival and lower ER protein levels. Tentatively, HRT-associated gene expression in tumors resembles the effect of tamoxifen exposure on MCF-7 cells.

Gene expression in 16q is associated with survival and differs between Sørlie breast cancer subtypes

We have investigated the relationship between gene expression and chromosomal positions in 402 breast cancer patients. Using an overrepresentation approach based on Fishers exact test, we identified disproportionate contributions of specific chromosomal positions to genes associated with survival. Our major finding is that the gene expression in the long arm of chromosome 16 stands out in its relationship to survival. This arm contributes 36 (18%) and 55 (11%) genes to lists negatively associated with recurrence‐free survival (set to sizes 200 and 500). This is a highly disproportionate contribution from the 313 (2%) genes in this arm represented on the used Affymetrix U133A and B microarray platforms (Bonferroni corrected Fisher test: P < 2.2 × 10−16). We also demonstrate differential expression in 16q across tumor subtypes, which suggests that the ERBB2, basal, and luminal B tumors progress along a high grade–poor prognosis path, while luminal A and normal‐like tumors progress along a low grade–good prognosis path, in accordance with a previously proposed model of tumor progression. We conclude that important biological information can be extracted from gene expression data in breast cancer by studying non‐random connections between chromosomal positions and gene expression. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045‐2257/suppmat.