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Author

Turid Aas

Other affiliations: University of Bergen
Bio: Turid Aas is an academic researcher from Haukeland University Hospital. The author has contributed to research in topics: Breast cancer & Cancer. The author has an hindex of 22, co-authored 56 publications receiving 14058 citations. Previous affiliations of Turid Aas include University of Bergen.


Papers
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Journal ArticleDOI
TL;DR: Survival analyses on a subcohort of patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.
Abstract: The purpose of this study was to classify breast carcinomas based on variations in gene expression patterns derived from cDNA microarrays and to correlate tumor characteristics to clinical outcome. A total of 85 cDNA microarray experiments representing 78 cancers, three fibroadenomas, and four normal breast tissues were analyzed by hierarchical clustering. As reported previously, the cancers could be classified into a basal epithelial-like group, an ERBB2-overexpressing group and a normal breast-like group based on variations in gene expression. A novel finding was that the previously characterized luminal epithelial/estrogen receptor-positive group could be divided into at least two subgroups, each with a distinctive expression profile. These subtypes proved to be reasonably robust by clustering using two different gene sets: first, a set of 456 cDNA clones previously selected to reflect intrinsic properties of the tumors and, second, a gene set that highly correlated with patient outcome. Survival analyses on a subcohort of patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.

10,791 citations

Journal ArticleDOI
TL;DR: Data is presented linking specific mutations in the P53 gene to primary resistance to doxorubicin therapy and early relapse in breast cancer patients.
Abstract: The mechanisms causing resistance to chemotherapeutic drugs in cancer patients are poorly understood. Recent evidence suggests that different forms of chemotherapy may exert their cytotoxic effects by inducing apoptosis. The tumor suppressor gene P53 has a pivotal role inducing apoptosis in response to cellular damage. In vitro investigations have shown intact p53 to play a critical role executing cell death in response to treatment with cytotoxic drugs like 5-fluorouracil, etoposide and doxorubicin. Recently, mutations in the P53 gene were found to confer resistance to anthracyclines in a mouse sarcoma tumor model, and overexpression of the p53 protein (which, in most cases, is due to a mutated gene) was found to be associated with lack of response to cisplatin-based chemotherapy in non-small cell lung cancer. Previous studies have shown mutations in the P53 gene or overexpression of the p53 protein to predict a poor prognosis, but also a beneficial effect of adjuvant radiotherapy or chemotherapy in breast cancer. In this study we present data linking specific mutations in the P53 gene to primary resistance to doxorubicin therapy and early relapse in breast cancer patients.

739 citations

Journal ArticleDOI
TL;DR: To understand the subclonal structure of primary breast cancer, whole-genome and targeted sequencing was applied to multiple samples from each of 50 patients' tumors, finding thatLandmarks of disease progression arose within detectable subclones of antecedent lesions.
Abstract: The sequencing of cancer genomes may enable tailoring of therapeutics to the underlying biological abnormalities driving a particular patient's tumor. However, sequencing-based strategies rely heavily on representative sampling of tumors. To understand the subclonal structure of primary breast cancer, we applied whole-genome and targeted sequencing to multiple samples from each of 50 patients' tumors (303 samples in total). The extent of subclonal diversification varied among cases and followed spatial patterns. No strict temporal order was evident, with point mutations and rearrangements affecting the most common breast cancer genes, including PIK3CA, TP53, PTEN, BRCA2 and MYC, occurring early in some tumors and late in others. In 13 out of 50 cancers, potentially targetable mutations were subclonal. Landmarks of disease progression, such as resistance to chemotherapy and the acquisition of invasive or metastatic potential, arose within detectable subclones of antecedent lesions. These findings highlight the importance of including analyses of subclonal structure and tumor evolution in clinical trials of primary breast cancer.

695 citations

Journal ArticleDOI
TL;DR: In breast cancer cell lines, the cDNA microarray-based comparative genomic hybridisation method is developed, revealing previously unrecognised genomic amplifications and deletions, and new complexities of amplicon structure.
Abstract: Gene amplifications and deletions frequently have pathogenetic roles in cancer. 30,000 radiation-hybrid mapped cDNAs provide a genomic resource to map these lesions with high resolution. We developed a cDNA microarray-based comparative genomic hybridisation method for analysing DNA copy number changes across thousands of genes simultaneously. Using this procedure, we could reliably detect DNA copy number alterations of twofold or less. In breast cancer cell lines, we have mapped regions of DNA copy number variation at high resolution, revealing previously unrecognised genomic amplifications and deletions, and new complexities of amplicon structure. Recurrent regions of DNA amplification, which may harbour novel oncogenes, were readily identified. Alterations of DNA copy number and gene expression could be compared and correlated in parallel analyses. We have now collected genome-wide DNA copy number information on a set of 9 breast cancer cell lines and over 35 primary breast tumours. For the breast tumours, DNA copy number information is being compared and correlated with data already collected on p53 status, microarray gene expression profiles, and treatment response and clinical outcome. The results of this analysis will be presented.

615 citations

Journal Article
TL;DR: The observation that the majority of patients with TP53 mutations affecting or disrupting the L2/L3 domains with LOH in addition obtained a partial response or stabilization of disease during chemotherapy suggests redundant mechanisms to compensate for loss of p53 function.
Abstract: TP53 status [mutations, immunostaining, and loss of heterozygosity (LOH)], expression of c-erbB-2, bcl-2, and histological grading were correlated to the response to doxorubicin monotherapy (14 mg/m 2 ) administered weekly to 90 patients with locally advanced breast cancer. Mutations in the TP53 gene, in particular those affecting or disrupting the loop domains L2 or L3 of the p53 protein, were associated with lack of response to chemotherapy ( P = 0.063 for all mutations and P = 0.008 for mutations affecting L2/L3, respectively). Similarly, expression of c-erbB-2 ( P = 0.041), a high histological grade ( P = 0.023), and lack of expression of bcl-2 ( P = 0.018) all predicted chemoresistance. No statistically significant association between either p53 immunostaining or TP53 LOH and response to therapy was recorded, despite the finding that both were associated with TP53 mutation status (p53 immunostaining, P P = 0.021). Lack of immunostaining for p53 despite mutation of the TP53 gene was particularly seen in tumors harboring nonsense mutations or deletions/splices (7 of 10 negative for staining compared with 4 of 16 with missense mutations). TP53 mutations (total/affecting L2/L3 domains) were associated with expression of c-erbB-2 ( P P = 0.001 and P = 0.025), and bcl-2 negativity ( P = 0.003 and P = 0.002). TP53 mutations, histological grade, and expression of bcl-2 (but not LOH or c-erbB-2 expression) all predicted for relapse-free as well as breast cancer-specific survival in univariate analysis ( P s between P = 0.01 and P = 0.0007, respectively). Our data are consistent with the hypothesis that certain TP53 mutations predict for resistance to doxorubicin in breast cancer patients. However, the observation that the majority of patients with TP53 mutations affecting or disrupting the L2/L3 domains with LOH in addition ( n = 12) obtained a partial response ( n = 4) or stabilization of disease ( n = 5) during chemotherapy suggests redundant mechanisms to compensate for loss of p53 function. Our findings are consistent with the hypothesis that other defects may act in concert with loss of p53 function, causing resistance to doxorubicin in breast cancers.

326 citations


Cited by
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Journal ArticleDOI
17 Aug 2000-Nature
TL;DR: Variation in gene expression patterns in a set of 65 surgical specimens of human breast tumours from 42 different individuals were characterized using complementary DNA microarrays representing 8,102 human genes, providing a distinctive molecular portrait of each tumour.
Abstract: Human breast tumours are diverse in their natural history and in their responsiveness to treatments. Variation in transcriptional programs accounts for much of the biological diversity of human cells and tumours. In each cell, signal transduction and regulatory systems transduce information from the cell's identity to its environmental status, thereby controlling the level of expression of every gene in the genome. Here we have characterized variation in gene expression patterns in a set of 65 surgical specimens of human breast tumours from 42 different individuals, using complementary DNA microarrays representing 8,102 human genes. These patterns provided a distinctive molecular portrait of each tumour. Twenty of the tumours were sampled twice, before and after a 16-week course of doxorubicin chemotherapy, and two tumours were paired with a lymph node metastasis from the same patient. Gene expression patterns in two tumour samples from the same individual were almost always more similar to each other than either was to any other sample. Sets of co-expressed genes were identified for which variation in messenger RNA levels could be related to specific features of physiological variation. The tumours could be classified into subtypes distinguished by pervasive differences in their gene expression patterns.

14,768 citations

Journal ArticleDOI
TL;DR: Survival analyses on a subcohort of patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.
Abstract: The purpose of this study was to classify breast carcinomas based on variations in gene expression patterns derived from cDNA microarrays and to correlate tumor characteristics to clinical outcome. A total of 85 cDNA microarray experiments representing 78 cancers, three fibroadenomas, and four normal breast tissues were analyzed by hierarchical clustering. As reported previously, the cancers could be classified into a basal epithelial-like group, an ERBB2-overexpressing group and a normal breast-like group based on variations in gene expression. A novel finding was that the previously characterized luminal epithelial/estrogen receptor-positive group could be divided into at least two subgroups, each with a distinctive expression profile. These subtypes proved to be reasonably robust by clustering using two different gene sets: first, a set of 456 cDNA clones previously selected to reflect intrinsic properties of the tumors and, second, a gene set that highly correlated with patient outcome. Survival analyses on a subcohort of patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.

10,791 citations

Journal ArticleDOI
31 Jan 2002-Nature
TL;DR: DNA microarray analysis on primary breast tumours of 117 young patients is used and supervised classification is applied 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, providing a strategy to select patients who would benefit from adjuvant therapy.
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.

9,664 citations

Journal ArticleDOI
07 Feb 1997-Cell
TL;DR: The author regrets the lack of citations for many important observations mentioned in the text, but their omission is made necessary by restrictions in the preparation of review manuscripts.

7,653 citations

Journal ArticleDOI
TL;DR: The gene-expression profile studied is a more powerful predictor of the outcome of disease in young patients with breast cancer than standard systems based on clinical and histologic criteria.
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...

5,902 citations