John A. Foekens

Signatures of mutational processes in human cancer

All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, ‘kataegis’, is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy.

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 landscape of cancer genes and mutational processes in breast cancer

All cancers carry somatic mutations in their genomes. A subset, known as driver mutations, confer clonal selective advantage on cancer cells and are causally implicated in oncogenesis, and the remainder are passenger mutations. The driver mutations and mutational processes operative in breast cancer have not yet been comprehensively explored. Here we examine the genomes of 100 tumours for somatic copy number changes and mutations in the coding exons of protein-coding genes. The number of somatic mutations varied markedly between individual tumours. We found strong correlations between mutation number, age at which cancer was diagnosed and cancer histological grade, and observed multiple mutational signatures, including one present in about ten per cent of tumours characterized by numerous mutations of cytosine at TpC dinucleotides. Driver mutations were identified in several new cancer genes including AKT2, ARID1B, CASP8, CDKN1B, MAP3K1, MAP3K13, NCOR1, SMARCD1 and TBX3. Among the 100 tumours, we found driver mutations in at least 40 cancer genes and 73 different combinations of mutated cancer genes. The results highlight the substantial genetic diversity underlying this common disease.

Genes that mediate breast cancer metastasis to the brain

The molecular basis for breast cancer metastasis to the brain is largely unknown. Brain relapse typically occurs years after the removal of a breast tumour, suggesting that disseminated cancer cells must acquire specialized functions to take over this organ. Here we show that breast cancer metastasis to the brain involves mediators of extravasation through non-fenestrated capillaries, complemented by specific enhancers of blood–brain barrier crossing and brain colonization. We isolated cells that preferentially infiltrate the brain from patients with advanced disease. Gene expression analysis of these cells and of clinical samples, coupled with functional analysis, identified the cyclooxygenase COX2 (also known as PTGS2), the epidermal growth factor receptor (EGFR) ligand HBEGF, and the α2,6-sialyltransferase ST6GALNAC5 as mediators of cancer cell passage through the blood–brain barrier. EGFR ligands and COX2 were previously linked to breast cancer infiltration of the lungs, but not the bones or liver, suggesting a sharing of these mediators in cerebral and pulmonary metastases. In contrast, ST6GALNAC5 specifically mediates brain metastasis. Normally restricted to the brain, the expression of ST6GALNAC5 in breast cancer cells enhances their adhesion to brain endothelial cells and their passage through the blood–brain barrier. This co-option of a brain sialyltransferase highlights the role of cell-surface glycosylation in organ-specific metastatic interactions.

Strong Time Dependence of the 76-Gene Prognostic Signature for Node-Negative Breast Cancer Patients in the TRANSBIG Multicenter Independent Validation Series

Purpose: Recently, a 76-gene prognostic signature able to predict distant metastases in lymph node–negative (N−) breast cancer patients was reported. The aims of this study conducted by TRANSBIG were to independently validate these results and to compare the outcome with clinical risk assessment. Experimental Design: Gene expression profiling of frozen samples from 198 N− systemically untreated patients was done at the Bordet Institute, blinded to clinical data and independent of Veridex. Genomic risk was defined by Veridex, blinded to clinical data. Survival analyses, done by an independent statistician, were done with the genomic risk and adjusted for the clinical risk, defined by Adjuvant! Online. Results: The actual 5- and 10-year time to distant metastasis were 98% (88-100%) and 94% (83-98%), respectively, for the good profile group and 76% (68-82%) and 73% (65-79%), respectively, for the poor profile group. The actual 5- and 10-year overall survival were 98% (88-100%) and 87% (73-94%), respectively, for the good profile group and 84% (77-89%) and 72% (63-78%), respectively, for the poor profile group. We observed a strong time dependence of this signature, leading to an adjusted hazard ratio of 13.58 (1.85-99.63) and 8.20 (1.10-60.90) at 5 years and 5.11 (1.57-16.67) and 2.55 (1.07-6.10) at 10 years for time to distant metastasis and overall survival, respectively. Conclusion: This independent validation confirmed the performance of the 76-gene signature and adds to the growing evidence that gene expression signatures are of clinical relevance, especially for identifying patients at high risk of early distant metastases.

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.

Definition of Clinically Distinct Molecular Subtypes in Estrogen Receptor–Positive Breast Carcinomas Through Genomic Grade

PURPOSE A number of microarray studies have reported distinct molecular profiles of breast cancers (BC), such as basal-like, ErbB2-like, and two to three luminal-like subtypes. These were associated with different clinical outcomes. However, although the basal and the ErbB2 subtypes are repeatedly recognized, identification of estrogen receptor (ER) -positive subtypes has been inconsistent. Therefore, refinement of their molecular definition is needed. MATERIALS AND METHODS We have previously reported a gene expression grade index (GGI), which defines histologic grade based on gene expression profiles. Using this algorithm, we assigned ER-positive BC to either high-or low-genomic grade subgroups and compared these with previously reported ER-positive molecular classifications. As further validation, we classified 666 ER-positive samples into subtypes and assessed their clinical outcome. RESULTS Two ER-positive molecular subgroups (high and low genomic grade) could be defined using the GGI. Despite tracking a single biologic pathway, these were highly comparable to the previously described luminal A and B classification and significantly correlated to the risk groups produced using the 21-gene recurrence score. The two subtypes were associated with statistically distinct clinical outcome in both systemically untreated and tamoxifen-treated populations. CONCLUSION The use of genomic grade can identify two clinically distinct ER-positive molecular subtypes in a simple and highly reproducible manner across multiple data sets. This study emphasizes the important role of proliferation-related genes in predicting prognosis in ER-positive BC.

Young Age at Diagnosis Correlates With Worse Prognosis and Defines a Subset of Breast Cancers With Shared Patterns of Gene Expression

PURPOSE Breast cancer arising in young women is correlated with inferior survival and higher incidence of negative clinicopathologic features. The biology driving this aggressive disease has yet to be defined. PATIENTS AND METHODS Clinically annotated, microarray data from 784 early-stage breast cancers were identified, and prospectively defined, age-specific cohorts (young: </= 45 years, n = 200; older: >/= 65 years, n = 211) were compared by prognosis, clinicopathologic variables, mRNA expression values, single-gene analysis, and gene set enrichment analysis (GSEA). Univariate and multivariate analyses were performed. RESULTS Using clinicopathologic variables, young women illustrated lower estrogen receptor (ER) positivity (immunohistochemistry [IHC], P = .027), larger tumors (P = .012), higher human epidermal growth factor receptor 2 (HER-2) overexpression (IHC, P = .075), lymph node positivity (P = .008), higher grade tumors (P < .0001), and trends toward inferior disease-free survival (DFS; hazard ratio = 1.32; P = .094). Using genomic expression analysis, tumors arising in young women had significantly lower ERalpha mRNA (P < .0001), ERbeta (P = .02), and progesterone receptor (PR) expression (P < .0001), but higher HER-2 (P < .0001) and epidermal growth factor receptor (EGFR) expression (P < .0001). Exploratory analysis (GSEA) revealed 367 biologically relevant gene sets significantly distinguishing breast tumors arising in young women. Combining clinicopathologic and genomic variables among tumors arising in young women demonstrated that younger age and lower ERbeta and higher EGFR mRNA expression were significant predictors of inferior DFS. CONCLUSION This large-scale genomic analysis illustrates that breast cancer arising in young women is a unique biologic entity driven by unifying oncogenic signaling pathways, is characterized by less hormone sensitivity and higher HER-2/EGFR expression, and warrants further study to offer this poor-prognosis group of women better preventative and therapeutic options.

Latent Bone Metastasis in Breast Cancer Tied to Src-Dependent Survival Signals

Metastasis may arise years after removal of a primary tumor. The mechanisms allowing latent disseminated cancer cells to survive are unknown. We report that a gene expression signature of Src activation is associated with late-onset bone metastasis in breast cancer. This link is independent of hormone receptor status or breast cancer subtype. In breast cancer cells, Src is dispensable for homing to the bones or lungs but is critical for the survival and outgrowth of these cells in the bone marrow. Src mediates AKT regulation and cancer cell survival responses to CXCL12 and TNF-related apoptosis-inducing ligand (TRAIL), factors that are distinctively expressed in the bone metastasis microenvironment. Breast cancer cells that lodge in the bone marrow succumb in this environment when deprived of Src activity.

Anti-Epithelial Cell Adhesion Molecule Antibodies and the Detection of Circulating Normal-Like Breast Tumor Cells

Identification of specific subtypes of circulating tumor cells in peripheral blood of cancer patients can provide information about the biology of metastasis and improve patient management. However, to be effective, the method used to identify circulating tumor cells must detect all tumor cell types. We investigated whether the five subtypes of human breast cancer cells that have been defined by global gene expression profiling—normal-like, basal, HER2-positive, and luminal A and B—were identified by CellSearch, a US Food and Drug Administration–approved test that uses antibodies against the cell surface–expressed epithelial cell adhesion molecule (EpCAM) to isolate circulating tumor cells. We used global gene expression profiling to determine the subtypes of a well-defined panel of 34 human breast cancer cell lines (15 luminal, nine normal-like, five basal-like, and five Her2-positive). We mixed 50-150 cells from 10 of these cell lines with 7.5 mL of blood from a single healthy human donor, and the mixtures were subjected to the CellSearch test to isolate the breast cancer cells. We found that the CellSearch isolation method, which uses EpCAM on the surface of circulating tumor cells for cell isolation, did not recognize, in particular, normal-like breast cancer cells, which in general have aggressive features. New tests that include antibodies that specifically recognize normal-like breast tumor cells but not cells of hematopoietic origin are needed.