| 1. |
- 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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| 2. |
- 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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| 3. |
- Larsson, Peter, et al.
(författare)
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Optimization of cell viability assays to improve replicability and reproducibility of cancer drug sensitivity screens.
- 2020
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- Cancer drug development has been riddled with high attrition rates, in part, due to poor reproducibility of preclinical models for drug discovery. Poor experimental design and lack of scientific transparency may cause experimental biases that in turn affect data quality, robustness and reproducibility. Here, we pinpoint sources of experimental variability in conventional 2D cell-based cancer drug screens to determine the effect of confounders on cell viability for MCF7 and HCC38 breast cancer cell lines treated with platinum agents (cisplatin and carboplatin) and a proteasome inhibitor (bortezomib). Variance component analysis demonstrated that variations in cell viability were primarily associated with the choice of pharmaceutical drug and cell line, and less likely to be due to the type of growth medium or assay incubation time. Furthermore, careful consideration should be given to different methods of storing diluted pharmaceutical drugs and use of DMSO controls due to the potential risk of evaporation and the subsequent effect on dose-response curves. Optimization of experimental parameters not only improved data quality substantially but also resulted in reproducible results for bortezomib- and cisplatin-treated HCC38, MCF7, MCF-10A, and MDA-MB-436 cells. Taken together, these findings indicate that replicability (the same analyst re-performs the same experiment multiple times) and reproducibility (different analysts perform the same experiment using different experimental conditions) for cell-based drug screens can be improved by identifying potential confounders and subsequent optimization of experimental parameters for each cell line.
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| 4. |
- Larsson, Peter, et al.
(författare)
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Pan-cancer analysis of genomic and transcriptomic data reveals the prognostic relevance of human proteasome genes in different cancer types.
- 2022
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Ingår i: BMC cancer. - : Springer Science and Business Media LLC. - 1471-2407. ; 22
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Tidskriftsartikel (refereegranskat)abstract
- The human proteasome gene family (PSM) consists of 49 genes that play a crucial role in cancer proteostasis. However, little is known about the effect of PSM gene expression and genetic alterations on clinical outcome in different cancer forms.Here, we performed a comprehensive pan-cancer analysis of genetic alterations in PSM genes and the subsequent prognostic value of PSM expression using data from The Cancer Genome Atlas (TCGA) containing over 10,000 samples representing up to 33 different cancer types. External validation was performed using a breast cancer cohort and KM plotter with four cancer types.The PSM genetic alteration frequency was high in certain cancer types (e.g. 67%; esophageal adenocarcinoma), with DNA amplification being most common. Compared with normal tissue, most PSM genes were predominantly overexpressed in cancer. Survival analysis also established a relationship with PSM gene expression and adverse clinical outcome, where PSMA1 and PSMD11 expression were linked to more unfavorable prognosis in≥30% of cancer types for both overall survival (OS) and relapse-free interval (PFI). Interestingly, PSMB5 gene expression was associated with OS (36%) and PFI (27%), and OS for PSMD2 (42%), especially when overexpressed.These findings indicate that several PSM genes may potentially be prognostic biomarkers and novel therapeutic targets for different cancer forms.
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| 5. |
- Biermann, Jana, et al.
(författare)
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A 17-marker panel for global genomic instability in breast cancer.
- 2020
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Ingår i: Genomics. - : Elsevier BV. - 0888-7543 .- 1089-8646. ; 112:2, s. 1151-1161
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Tidskriftsartikel (refereegranskat)abstract
- Genomic instability is a hallmark of cancer that plays a pivotal role in breast cancer development and evolution. A number of existing prognostic gene expression signatures for breast cancer are based on proliferation-related genes. Here, we identified a 17-marker panel associated with genome stability. A total of 136 primary breast carcinomas were stratified by genome stability. Matched gene expression profiles showed an innate segregation based on genome stability. We identified a 17-marker panel stratifying the training and validation cohorts into high- and low-risk patients. The 17 genes associated with genomic instability strongly impacted clinical outcome in breast cancer. Pathway analyses determined chromosome organisation, cell cycle regulation, and RNA processing as the underlying biological processes, thereby offering options for drug development and treatment tailoring. Our work supports the applicability of the 17-marker panel to improve clinical outcome prediction for breast cancer patients based on a signature accounting for genomic instability.
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| 6. |
- Biermann, Jana, et al.
(författare)
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Radiation-induced genomic instability in breast carcinomas of the Swedish haemangioma cohort.
- 2019
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Ingår i: Genes, chromosomes & cancer. - : Wiley. - 1098-2264 .- 1045-2257. ; 58:9, s. 627-35
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Tidskriftsartikel (refereegranskat)abstract
- Radiation-induced genomic instability (GI) is hypothesized to persist after exposure and ultimately promote carcinogenesis. Based on the absorbed dose to the breast, an increased risk of developing breast cancer was shown in the Swedish haemangioma cohort that was treated with radium-226 for skin haemangioma as infants. Here, we screened 31 primary breast carcinomas for genetic alterations using the OncoScan CNV Plus Assay to assess GI and chromothripsis-like patterns associated with the absorbed dose to the breast. Higher absorbed doses were associated with increased numbers of copy number alterations (CNAs) in the tumour genome and thus a more unstable genome. Hence, the observed dose-dependent GI in the tumour genome is a measurable manifestation of the long-term effects of irradiation. We developed a highly predictive Cox regression model for overall survival based on the interaction between absorbed dose and GI. The Swedish haemangioma cohort is a valuable cohort to investigate the biological relationship between absorbed dose and GI in irradiated humans. This work gives a biological basis for improved risk assessment to minimize carcinogenesis as a secondary disease after radiation therapy. This article is protected by copyright. All rights reserved.
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| 7. |
- De Lara, Shahin, et al.
(författare)
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GATA3 as a putative marker of breast cancer metastasis-A retrospective immunohistochemical study.
- 2018
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Ingår i: The breast journal. - : Hindawi Limited. - 1524-4741 .- 1075-122X. ; 24:2, s. 184-188
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Tidskriftsartikel (refereegranskat)abstract
- Diagnostic verification of breast cancer metastasis with histopathology and imaging analysis is essential to determine tumor staging. The aim of this study was to validate the utility of GATA3 immunohistochemistry as a diagnostic marker for breast cancer metastases and metastases of unknown primary origin. Retrospective immunohistochemical analysis of GATA3 expression in 164 breast cancer metastases diagnosed between 2004 and 2014 showed a striking difference between mammaglobin and GATA3 expression (51.2% vs 94% positivity). These findings highlight GATA3 as a more reliable and sensitive diagnostic marker for breast cancer metastases and possibly metastatic tumors of unknown origin than mammaglobin.
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| 8. |
- De Lara, Shahin, 1966, et al.
(författare)
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The prognostic relevance of FOXA1 and Nestin expression in breast cancer metastases: a retrospective study of 164 cases during a 10-year period (2004-2014)
- 2019
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Ingår i: Bmc Cancer. - : Springer Science and Business Media LLC. - 1471-2407. ; 19
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundCurrent prognostic markers cannot adequately predict the clinical outcome of breast cancer patients. Therefore, additional biomarkers need to be included in routine immune panels. FOXA1 was a significant predictor of favorable outcome in primary breast cancer, while Nestin expression is preferentially found in triple-negative tumors with increased rate of nodal metastases, and reduced survival. No studies have investigated the prognostic value of FOXA1 and Nestin expression in breast cancer metastases.MethodsBreast cancer metastases (n=164) from various anatomical sites were retrospectively analyzed by immunohistochemistry for FOXA1, Nestin and GATA3 expression. Cox regression analysis assessed the prognostic value of FOXA1 and Nestin expression.ResultsIn breast cancer metastases, FOXA1 expression was associated with Nestin-negativity, GATA3-positivity, ER-positivity, HER2-positivity and non-triple-negative status (P<0.05). In contrast, Nestin expression was associated with FOXA1-negative, GATA3-negative, ER-negative, and triple-negative metastases (P<0.05). Univariate Cox regression analysis showed FOXA1 expression was predictive of overall survival (OS, P=0.00048) and metastasis-free survival (DMFS, P=0.0011), as well as, distant metastasis-free survival in ER-positive patients (P=0.036) and overall survival in ER-negative patients (P=0.024). Multivariate analysis confirmed the significance of FOXA1 for both survival endpoints in metastatic breast cancer patients (OS, P=0.0033; DMFS, P=0.015).ConclusionsIn our study, FOXA1 was expressed mostly in ER-positive breast cancer metastases. Expression of Nestin was related to triple-negative metastases, where brain was the most frequent metastatic site. These findings highlight the clinical utility of FOXA1 and Nestin expression and warrant their inclusion in routine immunohistochemical panels for breast carcinoma.
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| 9. |
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| 10. |
- Engqvist, Hanna, 1985, et al.
(författare)
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Immunohistochemical validation of COL3A1, GPR158 and PITHD1 as prognostic biomarkers in early-stage ovarian carcinomasn
- 2019
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Ingår i: BMC Cancer. - : Springer Science and Business Media LLC. - 1471-2407. ; 19:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Ovarian cancer is the main cause of gynecological cancer-associated death. However, 5- Methods: Here, we evaluated the prognostic role of 29 genes for early-stage (I and II) ovarian Results: We provide evidence of aberrant protein expression patterns for Collagen type III alpha 1 Conclusions: The novel biomarkers identified here may improve prognostication at the time of
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