Anieta M. Sieuwerts

Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer

BACKGROUND Genome-wide measures of gene expression can identify patterns of gene activity that subclassify tumours and might provide a better means than is currently available for individual risk assessment in patients with lymph-node-negative breast cancer. METHODS We analysed, with Affymetrix Human U133a GeneChips, the expression of 22000 transcripts from total RNA of frozen tumour samples from 286 lymph-node-negative patients who had not received adjuvant systemic treatment. FINDINGS In a training set of 115 tumours, we identified a 76-gene signature consisting of 60 genes for patients positive for oestrogen receptors (ER) and 16 genes for ER-negative patients. This signature showed 93% sensitivity and 48% specificity in a subsequent independent testing set of 171 lymph-node-negative patients. The gene profile was highly informative in identifying patients who developed distant metastases within 5 years (hazard ratio 5.67 [95% CI 2.59-12.4]), even when corrected for traditional prognostic factors in multivariate analysis (5.55 [2.46-12.5]). The 76-gene profile also represented a strong prognostic factor for the development of metastasis in the subgroups of 84 premenopausal patients (9.60 [2.28-40.5]), 87 postmenopausal patients (4.04 [1.57-10.4]), and 79 patients with tumours of 10-20 mm (14.1 [3.34-59.2]), a group of patients for whom prediction of prognosis is especially difficult. INTERPRETATION The identified signature provides a powerful tool for identification of patients at high risk of distant recurrence. The ability to identify patients who have a favourable prognosis could, after independent confirmation, allow clinicians to avoid adjuvant systemic therapy or to choose less aggressive therapeutic options.

The Life History of 21 Breast Cancers

Summary Cancer evolves dynamically as clonal expansions supersede one another driven by shifting selective pressures, mutational processes, and disrupted cancer genes. These processes mark the genome, such that a cancers life history is encrypted in the somatic mutations present. We developed algorithms to decipher this narrative and applied them to 21 breast cancers. Mutational processes evolve across a cancers lifespan, with many emerging late but contributing extensive genetic variation. Subclonal diversification is prominent, and most mutations are found in just a fraction of tumor cells. Every tumor has a dominant subclonal lineage, representing more than 50% of tumor cells. Minimal expansion of these subclones occurs until many hundreds to thousands of mutations have accumulated, implying the existence of long-lived, quiescent cell lineages capable of substantial proliferation upon acquisition of enabling genomic changes. Expansion of the dominant subclone to an appreciable mass may therefore represent the final rate-limiting step in a breast cancers development, triggering diagnosis. PaperClip

Complex landscapes of somatic rearrangement in human breast cancer genomes.

Multiple somatic rearrangements are often found in cancer genomes; however, the underlying processes of rearrangement and their contribution to cancer development are poorly characterized. Here we use a paired-end sequencing strategy to identify somatic rearrangements in breast cancer genomes. There are more rearrangements in some breast cancers than previously appreciated. Rearrangements are more frequent over gene footprints and most are intrachromosomal. Multiple rearrangement architectures are present, but tandem duplications are particularly common in some cancers, perhaps reflecting a specific defect in DNA maintenance. Short overlapping sequences at most rearrangement junctions indicate that these have been mediated by non-homologous end-joining DNA repair, although varying sequence patterns indicate that multiple processes of this type are operative. Several expressed in-frame fusion genes were identified but none was recurrent. The study provides a new perspective on cancer genomes, highlighting the diversity of somatic rearrangements and their potential contribution to cancer development.

Landscape of somatic mutations in 560 breast cancer whole-genome sequences

We analysed whole genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. 93 protein-coding cancer genes carried likely driver mutations. Some non-coding regions exhibited high mutation frequencies but most have distinctive structural features probably causing elevated mutation rates and do not harbour driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed 12 base substitution and six rearrangement signatures. Three rearrangement signatures, characterised by tandem duplications or deletions, appear associated with defective homologous recombination based DNA repair: one with deficient BRCA1 function; another with deficient BRCA1 or BRCA2 function; the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operative, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.

Multicenter Validation of a Gene Expression–Based Prognostic Signature in Lymph Node–Negative Primary Breast Cancer

PURPOSE We previously identified in a single-center study a 76-gene prognostic signature for lymph node-negative (LNN) breast cancer patients. The aim of this study was to validate this gene signature in an independent more diverse population of LNN patients from multiple institutions. PATIENTS AND METHODS Using custom-designed DNA chips we analyzed the expression of the 76 genes in RNA of frozen tumor samples from 180 LNN patients who did not receive adjuvant systemic treatment. RESULTS In this independent validation, the 76-gene signature was highly informative in identifying patients with distant metastasis within 5 years (hazard ratio, [HR], 7.41; 95% CI, 2.63 to 20.9), even when corrected for traditional prognostic factors in multivariate analysis (HR, 11.36; 95% CI, 2.67 to 48.4). The actuarial 5- and 10-year distant metastasis-free survival were 96% (95% CI, 89% to 99%) and 94% (95% CI, 83% to 98%), respectively, for the good profile group and 74% (95% CI, 64% to 81%) and 65% (53% to 74%), respectively for the poor profile group. The sensitivity for 5-yr distant metastasis-free survival was 90%, and the specificity was 50%. The positive and negative predictive values were 38% (95% CI, 29% to 47%) and 94% (95% CI, 86% to 97%), respectively. The 76-gene signature was confirmed as a strong prognostic factor in subgroups of estrogen receptor-positive patients, pre- and postmenopausal patients, and patients with tumor sizes 20 mm or smaller. The subgroup of patients with estrogen receptor-negative tumors was considered too small to perform a separate analysis. CONCLUSION Our data provide a strong methodologic and clinical multicenter validation of the predefined prognostic 76-gene signature in LNN breast cancer patients.

Four miRNAs associated with aggressiveness of lymph node-negative, estrogen receptor-positive human breast cancer

In this study, we quantified 249 mature micro-RNA (miRNA) transcripts in estrogen receptor-positive (ER+) primary breast tumors of patients with lymph node-negative (LNN) disease to identify miRNAs associated with metastatic capability. In addition, the prognostic value of the candidate miRNAs was determined in ER−/LNN breast cancer. Unsupervised analysis in a prescreening set of 38 patients identified three subgroups predominantly driven by three miRNA signatures: an ER-driven luminal B-associated miRNA signature, a stromal miRNA signature, and an overexpressed miRNA cluster located on chromosome 19q23, but these intrinsic miRNA signatures were not associated with tumor aggressiveness. Supervised analysis in the initial subset and subsequent analysis in additional tumors significantly linked four miRNAs (miR-7, miR-128a, miR-210, and miR-516–3p) to ER+/LNN breast cancer aggressiveness (n = 147) and one miRNA (miR-210) to metastatic capability in ER−/LNN breast cancer (n = 114) and in the clinically important triple-negative subgroup (n = 69) (all P < 0.05). Bioinformatic analysis coupled miR-210 to hypoxia/VEGF signaling, miR-7 and miR-516–3p to cell cycle progression and chromosomal instability, and miR-128a to cytokine signaling. In conclusion, our work connects four miRNAs to breast cancer progression and to several distinct biological processes involved therein.

Molecular Classification of Tamoxifen-Resistant Breast Carcinomas by Gene Expression Profiling

PURPOSE To discover a set of markers predictive for the type of response to endocrine therapy with the antiestrogen tamoxifen using gene expression profiling. PATIENTS AND METHODS The study was performed on 112 estrogen receptor-positive primary breast carcinomas from patients with advanced disease and clearly defined types of response (ie, 52 patients with objective response v 60 patients with progressive disease) from start of first-line treatment with tamoxifen. Main clinical end points are the effects of therapy on tumor size and time until tumor progression (progression-free survival [PFS]). RNA isolated from tumor samples was amplified and hybridized to 18,000 human cDNA microarrays. RESULTS Using a training set of 46 breast tumors, 81 genes were found to be differentially expressed (P < or = .05) between tamoxifen-responsive and -resistant tumors. These genes were involved in estrogen action, apoptosis, extracellular matrix formation, and immune response. From the 81 genes, a predictive signature of 44 genes was extracted and validated on an independent set of 66 tumors. This 44-gene signature is significantly superior (odds ratio, 3.16; 95% CI, 1.10 to 9.11; P = .03) to traditional predictive factors in univariate analysis and also significantly related with a longer PFS in univariate (hazard ratio, 0.54; 95% CI, 0.31 to 0.94; P = .03) as well as in multivariate analyses (P = .03). CONCLUSION Our data show that gene expression profiling can be used to discriminate between breast cancer patients with progressive disease and objective response to tamoxifen. Additional studies are needed to confirm if the predictive signature might allow identification of individual patients who could benefit from other (adjuvant) endocrine therapies.

Genes Associated With Breast Cancer Metastatic to Bone

PURPOSE The biology of tumors relapsing to bone is poorly understood. In this study, we initiated a search for genes that are implicated in tumors relapsing to bone in breast cancer. PATIENTS AND METHODS We analyzed 107 primary breast tumors in patients who were all lymph node negative at the time of diagnosis and all had experienced relapse. Total RNA isolated from frozen tumor samples was used to gather gene expression data using oligo microarrays. RESULTS A panel of 69 genes was found significantly differentially expressed between patients who experienced relapse to bone versus those who experienced relapse elsewhere in the body. The most differentially expressed gene, TFF1, was confirmed by quantitative reverse transcriptase polymerase chain reaction in an independent cohort (n = 122; P = .0015). Our differentially expressed genes, combined with a recently reported gene set relevant to tumors relapsing to bone in an animal model system, pointed to the involvement of the fibroblast growth factor receptor signaling pathway in preference of tumor cells that relapse to bone. Given that patients who experience relapse to bone may benefit from bisphosphonate therapy, we developed a classifier of 31 genes, which in an independent validation set correctly predicts all tumors relapsing to bone with a specificity of 50%. CONCLUSION Our study identifies a panel of genes relevant to bone metastasis in breast cancer. The subsequently developed classifier of tumors relapsing to bone could, after thorough confirmation on an extended number of independent samples, and in combination with our previously developed high-risk profile, provide a diagnostic tool for the recommendation of adjuvant bisphosphonate therapy in addition to endocrine therapy or chemotherapy.

CCAT2, a novel noncoding RNA mapping to 8q24, underlies metastatic progression and chromosomal instability in colon cancer

The functional roles of SNPs within the 8q24 gene desert in the cancer phenotype are not yet well understood. Here, we report that CCAT2, a novel long noncoding RNA transcript (lncRNA) encompassing the rs6983267 SNP, is highly overexpressed in microsatellite-stable colorectal cancer and promotes tumor growth, metastasis, and chromosomal instability. We demonstrate that MYC, miR-17-5p, and miR-20a are up-regulated by CCAT2 through TCF7L2-mediated transcriptional regulation. We further identify the physical interaction between CCAT2 and TCF7L2 resulting in an enhancement of WNT signaling activity. We show that CCAT2 is itself a WNT downstream target, which suggests the existence of a feedback loop. Finally, we demonstrate that the SNP status affects CCAT2 expression and the risk allele G produces more CCAT2 transcript. Our results support a new mechanism of MYC and WNT regulation by the novel lncRNA CCAT2 in colorectal cancer pathogenesis, and provide an alternative explanation of the SNP-conferred cancer risk.

mRNA and microRNA expression profiles in circulating tumor cells and primary tumors of metastatic breast cancer patients

Purpose: Molecular characterization of circulating tumor cells (CTC) holds great promise. Unfortunately, routinely isolated CTC fractions currently still contain contaminating leukocytes, which makes CTC-specific molecular characterization extremely challenging. In this study, we determined mRNA and microRNA (miRNA) expression of potentially CTC-specific genes that are considered to be clinically relevant in breast cancer. Experimental Design: CTCs were isolated with the epithelial cell adhesion molecule–based CellSearch Profile Kit. Selected genes were measured by real-time reverse transcriptase PCR in CTCs of 50 metastatic breast cancer patients collected before starting first-line systemic therapy in blood from 53 healthy blood donors (HBD) and in primary tumors of 8 of the patients. The molecular profiles were associated with CTC counts and clinical parameters and compared with the profiles generated from the corresponding primary tumors. Results: We identified 55 mRNAs and 10 miRNAs more abundantly expressed in samples from 32 patients with at least 5 CTCs in 7.5 mL of blood compared with samples from 9 patients without detectable CTCs and HBDs. Clustering analysis resulted in 4 different patient clusters characterized by 5 distinct gene clusters. Twice the number of patients from cluster 2 to 4 had developed both visceral and nonvisceral metastases. Comparing transcript levels in CTCs with those measured in corresponding primary tumors showed clinically relevant discrepancies in estrogen receptor and HER2 levels. Conclusions: Our study shows that molecular profiling of low numbers of CTCs in a high background of leukocytes is feasible and shows promise for further studies on the clinical relevance of molecular characterization of CTCs. Clin Cancer Res; 17(11); 3600–18. ©2011 AACR.