Hans Peterse

Bio: Hans Peterse is an academic researcher from Netherlands Cancer Institute. The author has contributed to research in topics: Breast cancer & Cancer. The author has an hindex of 31, co-authored 45 publications receiving 15925 citations.

Gene expression profiling predicts clinical outcome of breast cancer

Abstract: 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.

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 classifi ed 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 identifi ed differentially expressed genes in a training set of 64 estrogen receptor (ER) – positive tumor samples by comparing expression profi les between histologic grade 3 tumors and histologic grade 1 tumors and used the expression of these genes to defi ne 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 identifi ed 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% confi dence 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. [J Natl Cancer Inst 2006;98:262 – 72]

Efficacy of MRI and Mammography for Breast-Cancer Screening in Women with a Familial or Genetic Predisposition

Abstract: background The value of regular surveillance for breast cancer in women with a genetic or familial predisposition to breast cancer is currently unproven. We compared the efficacy of magnetic resonance imaging (MRI) with that of mammography for screening in this group of high-risk women. methods Women who had a cumulative lifetime risk of breast cancer of 15 percent or more were screened every six months with a clinical breast examination and once a year by mammography and MRI, with independent readings. The characteristics of the cancers that were detected were compared with the characteristics of those in two different agematched control groups. results We screened 1909 eligible women, including 358 carriers of germ-line mutations. Within a median follow-up period of 2.9 years, 51 tumors (44 invasive cancers, 6 ductal carcinomas in situ, and 1 lymphoma) and 1 lobular carcinoma in situ were detected. The sensitivity of clinical breast examination, mammography, and MRI for detecting invasive breast cancer was 17.9 percent, 33.3 percent, and 79.5 percent, respectively, and the specificity was 98.1 percent, 95.0 percent, and 89.8 percent, respectively. The overall discriminating capacity of MRI was significantly better than that of mammography (P<0.05). The proportion of invasive tumors that were 10 mm or less in diameter was significantly greater in our surveillance group (43.2 percent) than in either control group (14.0 percent [P<0.001] and 12.5 percent [P = 0.04], respectively). The combined incidence of positive axillary nodes and micrometastases in invasive cancers in our study was 21.4 percent, as compared with 52.4 percent (P<0.001) and 56.4 percent (P=0.001) in the two control groups. conclusions MRI appears to be more sensitive than mammography in detecting tumors in women with an inherited susceptibility to breast cancer.

Gene expression profiling and histopathological characterization of triple-negative/basal-like breast carcinomas.

Abstract: Introduction Breast cancer is a heterogeneous group of tumors, and can be subdivided on the basis of histopathological features, genetic alterations and gene-expression profiles One well-defined subtype of breast cancer is characterized by a lack of HER2 gene amplification and estrogen and progesterone receptor expression ('triple-negative tumors') We examined the histopathological and gene-expression profile of triple-negative tumors to define subgroups with specific characteristics, including risk of developing distant metastases

Risk factors in breast-conservation therapy.

Abstract: PURPOSETo identify clinical and pathologic factors associated with an increased risk of local recurrence following breast-conservation therapy (BCT) to assess the safety of this procedure for all subgroups of patients.PATIENTS AND METHODSThe study population consisted of 1,026 patients with clinical stage I and II breast cancer treated between 1979 and 1988 at the Netherlands Cancer Institute. The BCT regimen consisted of local excision and axillary lymph node dissection (ALND) followed by whole-breast irradiation to a total dose of 50 Gy in 2-Gy fractions and boost irradiation (mostly by iridium implant) of 15 to 25 Gy.RESULTSWith a median follow-up duration of 66 months, the actuarial breast recurrence rate was 4% at 5 years, counting all breast recurrences. Univariate analysis showed seven factors to be associated with an increased risk of local recurrence; age, residual tumor at reexcision, histologic tumor type, presence of any carcinoma-in-situ component, vascular invasion, microscopic margin involv...

Gene expression profiling predicts clinical outcome of breast cancer

Abstract: 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.

Comprehensive molecular portraits of human breast tumours

Abstract: We analysed primary breast cancers by genomic DNA copy number arrays, DNA methylation, exome sequencing, messenger RNA arrays, microRNA sequencing and reverse-phase protein arrays. Our ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity. Somatic mutations in only three genes (TP53, PIK3CA and GATA3) occurred at >10% incidence across all breast cancers; however, there were numerous subtype-associated and novel gene mutations including the enrichment of specific mutations in GATA3, PIK3CA and MAP3K1 with the luminal A subtype. We identified two novel protein-expression-defined subgroups, possibly produced by stromal/microenvironmental elements, and integrated analyses identified specific signalling pathways dominant in each molecular subtype including a HER2/phosphorylated HER2/EGFR/phosphorylated EGFR signature within the HER2-enriched expression subtype. Comparison of basal-like breast tumours with high-grade serous ovarian tumours showed many molecular commonalities, indicating a related aetiology and similar therapeutic opportunities. The biological finding of the four main breast cancer subtypes caused by different subsets of genetic and epigenetic abnormalities raises the hypothesis that much of the clinically observable plasticity and heterogeneity occurs within, and not across, these major biological subtypes of breast cancer.

Epithelial–mesenchymal transitions in tumour progression

Abstract: Without epithelial–mesenchymal transitions, in which polarized epithelial cells are converted into motile cells, multicellular organisms would be incapable of getting past the blastula stage of embryonic development. However, this important developmental programme has a more sinister role in tumour progression. Epithelial–mesenchymal transition provides a new basis for understanding the progression of carcinoma towards dedifferentiated and more malignant states.

A Gene-Expression Signature as a Predictor of Survival in Breast Cancer

Abstract: Background A more accurate means of prognostication in breast cancer will improve the selection of patients for adjuvant systemic therapy. Methods Using microarray analysis to evaluate our previously established 70-gene prognosis profile, we classified a series of 295 consecutive patients with primary breast carcinomas as having a gene-expression signature associated with either a poor prognosis or a good prognosis. All patients had stage I or II breast cancer and were younger than 53 years old; 151 had lymph-node–negative disease, and 144 had lymph-node–positive disease. We evaluated the predictive power of the prognosis profile using univariable and multivariable statistical analyses. Results Among the 295 patients, 180 had a poor-prognosis signature and 115 had a good-prognosis signature, and the mean (±SE) overall 10-year survival rates were 54.6±4.4 percent and 94.5±2.6 percent, respectively. At 10 years, the probability of remaining free of distant metastases was 50.6±4.5 percent in the group with a...

A Multigene Assay to Predict Recurrence of Tamoxifen-Treated, Node-Negative Breast Cancer

Abstract: background The likelihood of distant recurrence in patients with breast cancer who have no involved lymph nodes and estrogen-receptor–positive tumors is poorly defined by clinical and histopathological measures. methods We tested whether the results of a reverse-transcriptase–polymerase-chain-reaction (RT-PCR) assay of 21 prospectively selected genes in paraffin-embedded tumor tissue would correlate with the likelihood of distant recurrence in patients with node-negative, tamoxifen-treated breast cancer who were enrolled in the National Surgical Adjuvant Breast and Bowel Project clinical trial B-14. The levels of expression of 16 cancerrelated genes and 5 reference genes were used in a prospectively defined algorithm to calculate a recurrence score and to determine a risk group (low, intermediate, or high) for each patient. results Adequate RT-PCR profiles were obtained in 668 of 675 tumor blocks. The proportions of patients categorized as having a low, intermediate, or high risk by the RT-PCR assay were 51, 22, and 27 percent, respectively. The Kaplan–Meier estimates of the rates of distant recurrence at 10 years in the low-risk, intermediate-risk, and high-risk groups were 6.8 percent (95 percent confidence interval, 4.0 to 9.6), 14.3 percent (95 percent confidence interval, 8.3 to 20.3), and 30.5 percent (95 percent confidence interval, 23.6 to 37.4). The rate in the low-risk group was significantly lower than that in the high-risk group (P<0.001). In a multivariate Cox model, the recurrence score provided significant predictive power that was independent of age and tumor size (P<0.001). The recurrence score was also predictive of overall survival (P<0.001) and could be used as a continuous function to predict distant recurrence in individual patients. conclusions The recurrence score has been validated as quantifying the likelihood of distant recurrence in tamoxifen-treated patients with node-negative, estrogen-receptor–positive breast cancer.