| 1. |
- Karlsson, Elin, 1979, et al.
(författare)
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Chromosomal changes associated with clinical outcome in lymph node-negative breast cancer.
- 2007
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Ingår i: Cancer genetics and cytogenetics. - : Elsevier BV. - 0165-4608 .- 1873-4456. ; 172:2, s. 139-46
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Tidskriftsartikel (refereegranskat)abstract
- Breast cancer is the most common malignancy among women and accounts for over one million new cases worldwide per year. Lymph node-negative breast cancer patients are reputed as having a better prognosis than lymph node-positive ones. Around 20% of the lymph node-negative patients die within 10 years after diagnosis. To improve the prognostics of node-negative breast cancer, it is important to understand the underlying biologic mechanisms promoting survival, such as specific genetic changes in the tumor genome. In this study, CGH was applied to analyze 64 tumors from node-negative breast cancer patients to identify DNA copy number changes in chromosomes and chromosome regions that may be correlated to survival. The main findings show gains at 4q, 5q31 approximately qter, 6q12 approximately q16, and 12q14 approximately q22, as well as losses of 17p, 18p, and Xq, which were significantly more recurrent in tumors from deceased patients than in tumors from survivors. The average number of chromosomal changes was higher in the tumors from deceased compared to the survivor tumors. Our findings suggest that tumors with specific chromosomal aberrations at 4q, 5q31 approximately qter, 6q12 approximately q16, 12q14 approximately q22, 17p, 18p, and Xq result in an aggressive form of breast cancer and that these patients are predisposed to succumb to breast cancer.
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| 2. |
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| 3. |
- Biermann, Jana, et al.
(författare)
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Clonal relatedness in tumour pairs of breast cancer patients.
- 2018
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Ingår i: Breast cancer research : BCR. - : Springer Science and Business Media LLC. - 1465-542X. ; 20:1
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Tidskriftsartikel (refereegranskat)abstract
- Molecular classification of tumour clonality is currently not evaluated in multiple invasive breast carcinomas, despite evidence suggesting common clonal origins. There is no consensus about which type of data (e.g. copy number, mutation, histology) and especially which statistical method is most suitable to distinguish clonal recurrences from independent primary tumours.Thirty-seven invasive breast tumour pairs were stratified according to laterality and time interval between the diagnoses of the two tumours. In a multi-omics approach, tumour clonality was analysed by integrating clinical characteristics (n=37), DNA copy number (n=37), DNA methylation (n=8), gene expression microarray (n=7), RNA sequencing (n=3), and SNP genotyping data (n=3). Different statistical methods, e.g. the diagnostic similarity index (SI), were used to classify the tumours as clonally related recurrences or independent primary tumours.The SI and hierarchical clustering showed similar tendencies and the highest concordance with the other methods. Concordant evidence for tumour clonality was found in 46% (17/37) of patients. Notably, no association was found between the current clinical guidelines and molecular tumour features.A more accurate classification of clonal relatedness between multiple breast tumours may help to mitigate treatment failure and relapse by integrating tumour-associated molecular features, clinical parameters, and statistical methods. Guidelines need to be defined with exact thresholds to standardise clonality testing in a routine diagnostic setting.
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| 4. |
- Biermann, Jana, et al.
(författare)
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Tumour clonality in paired invasive breast carcinomas
- 2019
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Ingår i: Cancer Research. - 0008-5472.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Background: Multiple invasive breast tumours may represent either independent primary tumours or clonal recurrences of the first tumour, where the same progenitor cell gives rise to all of the detected tumours. Consequently, the driver events for the progenitor cell need to have been identical in early tumour development. Molecular classification of tumour clonality is not currently evaluated in multiple invasive breast carcinomas, despite evidence suggesting common clonal origins. Furthermore, there is no consensus about which type of biological data (e.g. copy number, mutation, histology) and especially which statistical method is most suitable to distinguish clonal recurrences from independent primary tumours. Methods: Thirty-seven invasive breast tumour pairs were stratified by laterality (bilateral vs. ipsilateral) and the time interval between the diagnoses of the first and second tumours (synchronous vs. metachronous). Both tumours from the same patient were analysed by integrating clinical characteristics (n = 37), DNA copy number (n = 37), DNA methylation (n = 8), gene expression microarray (n = 7), RNA sequencing (n = 3), and SNP genotyping data (n = 3). Different statistical methods, e.g. the diagnostic similarity index (SI), distance measure, shared segment analysis etc., were used to classify the tumours from the same patient as clonally related recurrences or independent primary tumours. Results: The SI applied on DNA copy numbers derived from aCGH (array comparative genomic hybridization) data was determined as the strongest indicator of clonal relatedness as it showed the highest concordance with all other methods. The distance measure was the most conservative method and the shared segment analysis most liberal. Concordant evidence for tumour clonality was found in 46% (17/37) of the patients. Notably, no significant association was found between the clinical characteristics and molecular tumour features. Conclusions: A more accurate classification of clonal relatedness between multiple breast tumours may help to mitigate treatment failure and relapse by integrating tumour-associated molecular features, clinical parameters, and statistical methods. In cases of extremely similar or different tumour pairs, the results showed consistency regardless of the method used. The SI can be easily integrated into clinical routine using FFPE samples to obtain copy number data. However, clinical guidelines with exact thresholds need to be defined to standardize clonality testing in a routine diagnostic setting.
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| 5. |
- Möllerström, Elin, et al.
(författare)
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High-resolution genomic profiling to predict 10-year overall survival in node-negative breast cancer.
- 2010
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Ingår i: Cancer genetics and cytogenetics. - : Elsevier BV. - 1873-4456 .- 0165-4608. ; 198:2, s. 79-89
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Tidskriftsartikel (refereegranskat)abstract
- Women with clinically node-negative breast cancer have a better prognosis than do those with axillary lymph node metastasis. Nonetheless, approximately 20% of node-negative patients die within 15 years of diagnosis, and thus additional prognostic markers are greatly needed. To identify specific copy number alterations (CNAs) that differed in frequency between 10-year survivors and deceased patients with node-negative breast cancer, array comparative genomic hybridization (aCGH) was applied to 41 primary node-negative breast tumors. Fisher's exact test was used to identify significantly different CNAs between 10-year survivors and deceased patients. Losses at 8p21.2 approximately p21.3, 8p23.1 approximately p23.2, Xp21.3, and Xp22.31 approximately p22.33 were significantly more common in tumors from deceased patients, suggesting that these alterations may contribute to tumor aggressiveness. Gains at 1q25.2 approximately q25.3 and 1q31.3 approximately q41 were more prevalent in tumors from survivors; specific gains at these genomic regions may inhibit further tumor progression, resulting in a less aggressive form of node-negative breast cancer. Evaluation of the identified CNAs in an independent external data set verified the prognostic potential of the 1q31.3 approximately q41 region. Although further extensive validation is needed, the prognostic CNAs identified in this work may in time facilitate the clinical assessment of breast cancer.
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| 6. |
- Möllerström, Elin, et al.
(författare)
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Up-regulation of cell cycle arrest protein BTG2 correlates with increased overall survival in breast cancer, as detected by immunohistochemistry using tissue microarray.
- 2010
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Ingår i: BMC cancer. - : Springer Science and Business Media LLC. - 1471-2407. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- ABSTRACT: BACKGROUND: Previous studies have shown that the ADIPOR1, ADORA1, BTG2 and CD46 genes differ significantly between long-term survivors of breast cancer and deceased patients, both in levels of gene expression and DNA copy numbers. The aim of this study was to characterize the expression of the corresponding proteins in breast carcinoma and to determine their correlation with clinical outcome. METHODS: Protein expression was evaluated using immunohistochemistry in an independent breast cancer cohort of 144 samples represented on tissue microarrays. Fisher's exact test was used to analyze the differences in protein expression between dead and alive patients. We used Cox-regression multivariate analysis to assess whether the new markers predict the survival status of the patients better than the currently used markers. RESULTS: BTG2 expression was demonstrated in a significantly lower proportion of samples from dead patients compared to alive patients, both in overall expression (P=0.026) and cell membrane specific expression (P=0.013), whereas neither ADIPOR1, ADORA1 nor CD46 showed differential expression in the two survival groups. Furthermore, a multivariate analysis showed that a model containing BTG2 expression in combination with HER2 and Ki67 expression along with patient age performed better than a model containing the currently used prognostic markers (tumour size, nodal status, HER2 expression, hormone receptor status, histological grade, and patient age). Interestingly, BTG2 has previously been described as a tumour suppressor gene involved in cell cycle arrest and p53 signalling. CONCLUSIONS: We conclude that high-level BTG2 protein expression correlates with prolonged survival in patients with breast carcinoma.
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| 7. |
- Nemes, Szilard, 1977, et al.
(författare)
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A diagnostic algorithm to identify paired tumors with clonal origin.
- 2013
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Ingår i: Genes, chromosomes & cancer. - : Wiley. - 1098-2264 .- 1045-2257. ; 52:11, s. 1007-16
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Tidskriftsartikel (refereegranskat)abstract
- Despite practical implications we still lack standardized methods for clonality testing of tumor pairs. Each tumor is characterized by a set of chromosomal abnormalities, nonrandom changes preferentially involving specific chromosomes and chromosomal regions. Although tumors accumulate chromosomal abnormalities during their development, the majority of these alterations is specific and characteristic for each individual tumor is not exhibited at the population level. Assumingly, secondary tumors that develop from disseminated cells from the primary tumor inherit not only chromosomal changes specific for the cancerous process but also random chromosomal changes that accumulate during tumor development. Based on this assumption, we adopted an intuitive index for genomic similarities of paired tumors, which ranges between zero (completely different genomic profiles) and one (identical genomic profiles). To test the assumption that two tumors have clonal origins if they share a higher degree of genomic similarity than two randomly paired tumors, we built a permutation-based null-hypothesis procedure. The procedure is demonstrated using two publicly available data sets. The article highlights the complexities of clonality testing and aims to offer an easy to follow blueprint that will allow researchers to test genomic similarities of paired tumors, with the proposed index or any other index that fits their need. © 2013 Wiley Periodicals, Inc.
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| 8. |
- Parris, Toshima Z, 1978, et al.
(författare)
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Clinical implications of gene dosage and gene expression patterns in diploid breast carcinoma.
- 2010
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Ingår i: Clinical cancer research : an official journal of the American Association for Cancer Research. - 1078-0432. ; 16:15, s. 3860-74
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Tidskriftsartikel (refereegranskat)abstract
- Deregulation of key cellular pathways is fundamental for the survival and expansion of neoplastic cells. In cancer, regulation of gene transcription can be mediated in a variety of ways. The purpose of this study was to assess the impact of gene dosage on gene expression patterns and the effect of other mechanisms on transcriptional levels, and to associate these genomic changes with clinicopathologic parameters.
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