Laura J. van 't Veer

Gene expression profiling predicts clinical outcome of breast cancer.

Breast cancer patients with the same stage of disease can have markedly different treatment responses and overall outcome. The strongest predictors for metastases (for example, lymph node status and histological grade) fail to classify accurately breast tumours according to their clinical behaviour. Chemotherapy or hormonal therapy reduces the risk of distant metastases by approximately one-third; however, 70–80% of patients receiving this treatment would have survived without it. None of the signatures of breast cancer gene expression reported to date allow for patient-tailored therapy strategies. Here we used DNA microarray analysis on primary breast tumours of 117 young patients, and applied supervised classification to identify a gene expression signature strongly predictive of a short interval to distant metastases (‘poor prognosis’ signature) in patients without tumour cells in local lymph nodes at diagnosis (lymph node negative). In addition, we established a signature that identifies tumours of BRCA1 carriers. The poor prognosis signature consists of genes regulating cell cycle, invasion, metastasis and angiogenesis. This gene expression profile will outperform all currently used clinical parameters in predicting disease outcome. Our findings provide a strategy to select patients who would benefit from adjuvant therapy.

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.

Bilateral Prophylactic Mastectomy Reduces Breast Cancer Risk in BRCA1 and BRCA2 Mutation Carriers: The PROSE Study Group

PURPOSE Data on the efficacy of bilateral prophylactic mastectomy for breast cancer risk reduction in women with BRCA1 and BRCA2 (BRCA1/2) mutations are limited, despite the clinical use of this risk-management strategy. Thus, we estimated the degree of breast cancer risk reduction after surgery in women who carry these mutations. PATIENTS AND METHODS Four hundred eighty-three women with disease-associated germline BRCA1/2 mutations were studied for the occurrence of breast cancer. Cases were mutation carriers who underwent bilateral prophylactic mastectomy and who were followed prospectively from the time of their center ascertainment and their surgery, with analyses performed for both follow-up periods. Controls were BRCA1/2 mutation carriers with no history of bilateral prophylactic mastectomy matched to cases on gene, center, and year of birth. Both cases and controls were excluded for previous or concurrent diagnosis of breast cancer. Analyses were adjusted for duration of endogenous ovarian hormone exposure, including age at bilateral prophylactic oophorectomy if applicable. RESULTS Breast cancer was diagnosed in two (1.9%) of 105 women who had bilateral prophylactic mastectomy and in 184 (48.7%) of 378 matched controls who did not have the procedure, with a mean follow-up of 6.4 years. Bilateral prophylactic mastectomy reduced the risk of breast cancer by approximately 95% in women with prior or concurrent bilateral prophylactic oophorectomy and by approximately 90% in women with intact ovaries. CONCLUSION Bilateral prophylactic mastectomy reduces the risk of breast cancer in women with BRCA1/2 mutations by approximately 90%.

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.

A common coding variant in CASP8 is associated with breast cancer risk

The Breast Cancer Association Consortium (BCAC) has been established to conduct combined case-control analyses with augmented statistical power to try to confirm putative genetic associations with breast cancer. We genotyped nine SNPs for which there was some prior evidence of an association with breast cancer: CASP8 D302H (rs1045485), IGFBP3 −202 C → A (rs2854744), SOD2 V16A (rs1799725), TGFB1 L10P (rs1982073), ATM S49C (rs1800054), ADH1B 3′ UTR A → G (rs1042026), CDKN1A S31R (rs1801270), ICAM5 V301I (rs1056538) and NUMA1 A794G (rs3750913). We included data from 9–15 studies, comprising 11,391–18,290 cases and 14,753–22,670 controls. We found evidence of an association with breast cancer for CASP8 D302H (with odds ratios (OR) of 0.89 (95% confidence interval (c.i.): 0.85–0.94) and 0.74 (95% c.i.: 0.62–0.87) for heterozygotes and rare homozygotes, respectively, compared with common homozygotes; Ptrend = 1.1 × 10−7) and weaker evidence for TGFB1 L10P (OR = 1.07 (95% c.i.: 1.02–1.13) and 1.16 (95% c.i.: 1.08–1.25), respectively; Ptrend = 2.8 × 10−5). These results demonstrate that common breast cancer susceptibility alleles with small effects on risk can be identified, given sufficiently powerful studies.NOTE: In the version of this article initially published, there was an error that affected the calculations of the odds ratios, confidence intervals, between-study heterogeneity, trend test and test for association for SNP ICAM5 V301I in Table 1 (ICAM5 V301I); genotype counts in Supplementary Table 2 (ICAM5; ICR_FBCS and Kuopio studies) and minor allele frequencies, trend test and odds ratios for heterozygotes and rare homozygotes in Supplementary Table 3 (ICAM5; ICR_FBCS and Kuopio studies). The errors in Table 1 have been corrected in the PDF version of the article. The errors in supplementary information have been corrected online.

Enabling personalized cancer medicine through analysis of gene-expression patterns

Therapies for patients with cancer have changed gradually over the past decade, moving away from the administration of broadly acting cytotoxic drugs towards the use of more-specific therapies that are targeted to each tumour. To facilitate this shift, tests need to be developed to identify those individuals who require therapy and those who are most likely to benefit from certain therapies. In particular, tests that predict the clinical outcome for patients on the basis of the genes expressed by their tumours are likely to increasingly affect patient management, heralding a new era of personalized medicine.

Converting a breast cancer microarray signature into a high-throughput diagnostic test

BackgroundA 70-gene tumor expression profile was established as a powerful predictor of disease outcome in young breast cancer patients. This profile, however, was generated on microarrays containing 25,000 60-mer oligonucleotides that are not designed for processing of many samples on a routine basis.ResultsTo facilitate its use in a diagnostic setting, the 70-gene prognosis profile was translated into a customized microarray (MammaPrint) containing a reduced set of 1,900 probes suitable for high throughput processing. RNA of 162 patient samples from two previous studies was subjected to hybridization to this custom array to validate the prognostic value. Classification results obtained from the original analysis were then compared to those generated using the algorithms based on the custom microarray and showed an extremely high correlation of prognosis prediction between the original data and those generated using the custom mini-array (p < 0.0001).ConclusionIn this report we demonstrate for the first time that microarray technology can be used as a reliable diagnostic tool. The data clearly demonstrate the reproducibility and robustness of the small custom-made microarray. The array is therefore an excellent tool to predict outcome of disease in breast cancer patients.

Gene expression profiles of primary breast tumors maintained in distant metastases

It has been debated for decades how cancer cells acquire metastatic capability. It is unclear whether metastases are derived from distinct subpopulations of tumor cells within the primary site with higher metastatic potential, or whether they originate from a random fraction of tumor cells. Here we show, by gene expression profiling, that human primary breast tumors are strikingly similar to the distant metastases of the same patient. Unsupervised hierarchical clustering, multidimensional scaling, and permutation testing, as well as the comparison of significantly expressed genes within a pair, reveal their genetic similarity. Our findings suggest that metastatic capability in breast cancer is an inherent feature and is not based on clonal selection.

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.

Gene Expression Signature to Improve Prognosis Prediction of Stage II and III Colorectal Cancer

PURPOSE This study aims to develop a robust gene expression classifier that can predict disease relapse in patients with early-stage colorectal cancer (CRC). PATIENTS AND METHODS Fresh frozen tumor tissue from 188 patients with stage I to IV CRC undergoing surgery was analyzed using Agilent 44K oligonucleotide arrays. Median follow-up time was 65.1 months, and the majority of patients (83.6%) did not receive adjuvant chemotherapy. A nearest mean classifier was developed using a cross-validation procedure to score all genes for their association with 5-year distant metastasis-free survival. RESULTS An optimal set of 18 genes was identified and used to construct a prognostic classifier (ColoPrint). The signature was validated on an independent set of 206 samples from patients with stage I, II, and III CRC. The signature classified 60% of patients as low risk and 40% as high risk. Five-year relapse-free survival rates were 87.6% (95% CI, 81.5% to 93.7%) and 67.2% (95% CI, 55.4% to 79.0%) for low- and high-risk patients, respectively, with a hazard ratio (HR) of 2.5 (95% CI, 1.33 to 4.73; P = .005). In multivariate analysis, the signature remained one of the most significant prognostic factors, with an HR of 2.69 (95% CI, 1.41 to 5.14; P = .003). In patients with stage II CRC, the signature had an HR of 3.34 (P = .017) and was superior to American Society of Clinical Oncology criteria in assessing the risk of cancer recurrence without prescreening for microsatellite instability (MSI). CONCLUSION ColoPrint significantly improves the prognostic accuracy of pathologic factors and MSI in patients with stage II and III CRC and facilitates the identification of patients with stage II disease who may be safely managed without chemotherapy.