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Träfflista för sökning "WFRF:(Karlsson Per 1963) ;pers:(Nemes Szilard 1977)"

Sökning: WFRF:(Karlsson Per 1963) > Nemes Szilard 1977

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1.
  • Parris, Toshima Z, 1978, et al. (författare)
  • Additive effect of the AZGP1, PIP, S100A8, and UBE2C molecular biomarkers improves outcome prediction in breast carcinoma
  • 2014
  • Ingår i: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 134:7
  • Tidskriftsartikel (refereegranskat)abstract
    • The deregulation of key cellular pathways is fundamental for the survival and expansion of neoplastic cells, which in turn can have a detrimental effect on patient outcome. To develop effective individualized cancer therapies, we need to have a better understanding of which cellular pathways are perturbed in a genetically defined subgroup of patients. Here, we validate the prognostic value of a 13-marker signature in independent gene expression microarray datasets (n = 1,141) and immunohistochemistry with full-faced FFPE samples (n = 71). The predictive performance of individual markers and panels containing multiple markers was assessed using Cox regression analysis. In the external gene expression dataset, six of the 13 genes (AZGP1, NME5, S100A8, SCUBE2, STC2, and UBE2C) retained their prognostic potential and were significantly associated with disease-free survival (P < 0.001). Protein analyses refined the signature to a four-marker panel (AZGP1, PIP, S100A8, and UBE2C) significantly correlated with cycling, high grade tumors and lower disease-specific survival rates. AZGP1 and PIP were found in significantly lower levels in invasive breast tissue compared with adjacent normal tissue, whereas elevated levels of S100A8 and UBE2C were observed. A predictive model containing the four-marker panel in conjunction with established clinical variables outperformed a model containing the clinical variables alone. Our findings suggest that deregulated AZGP1, PIP, S100A8, and UBE2C are critical for the aggressive breast cancer phenotype, which may be useful as novel therapeutic targets for drug development to complement established clinical variables. © 2013 Wiley Periodicals, Inc.
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2.
  • Parris, Toshima Z, 1978, et al. (författare)
  • Clinical relevance of breast cancer-related genes as potential biomarkers for oral squamous cell carcinoma
  • 2014
  • Ingår i: BMC Cancer. - : Springer Science and Business Media LLC. - 1471-2407. ; 14
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Squamous cell carcinoma of the oral cavity (OSCC) is a common cancer form with relatively low 5-year survival rates, due partially to late detection and lack of complementary molecular markers as targets for treatment. Molecular profiling of head and neck cancer has revealed biological similarities with basal-like breast and lung carcinoma. Recently, we showed that 16 genes were consistently altered in invasive breast tumors displaying varying degrees of aggressiveness. Methods: To extend our findings from breast cancer to another cancer type with similar characteristics, we performed an integrative analysis of transcriptomic and proteomic data to evaluate the prognostic significance of the 16 putative breast cancer-related biomarkers in OSCC using independent microarray datasets and immunohistochemistry. Predictive models for disease-specific (DSS) and/or overall survival (OS) were calculated for each marker using Cox proportional hazards models. Results: We found that CBX2, SCUBE2, and STK32B protein expression were associated with important clinicopathological features for OSCC (peritumoral inflammatory infiltration, metastatic spread to the cervical lymph nodes, and tumor size). Consequently, SCUBE2 and STK32B are involved in the hedgehog signaling pathway which plays a pivotal role in metastasis and angiogenesis in cancer. In addition, CNTNAP2 and S100A8 protein expression were correlated with DSS and OS, respectively. Conclusions: Taken together, these candidates and the hedgehog signaling pathway may be putative targets for drug development and clinical management of OSCC patients.
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3.
  • Biermann, Jana, et al. (författare)
  • A novel 18-marker panel predicting clinical outcome in breast cancer
  • 2017
  • Ingår i: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. - 1538-7755. ; 26:11, s. 1619-28
  • Tidskriftsartikel (refereegranskat)abstract
    • Gene expression profiling has made considerable contributions to our understanding of cancer biology and clinical care. This study describes a novel gene expression signature for breast cancer-specific survival that was validated using external datasets. Gene expression signatures for invasive breast carcinomas (mainly Luminal B subtype) corresponding to 136 patients were analysed using Cox regression and the effect of each gene on disease-specific survival (DSS) was estimated. Iterative Bayesian Model Averaging was applied on multivariable Cox regression models resulting in an 18-marker panel, which was validated using three external validation datasets. The 18 genes were analysed for common pathways and functions using the Ingenuity Pathway Analysis software. This study complied with the REMARK criteria. The 18-gene multivariable model showed a high predictive power for DSS in the training and validation cohort and a clear stratification between high- and low-risk patients. The differentially expressed genes were predominantly involved in biological processes such as cell cycle, DNA replication, recombination, and repair. Furthermore, the majority of the 18 genes were found to play a pivotal role in cancer. Our findings demonstrated that the 18 molecular markers were strong predictors of breast cancer-specific mortality. The stable time-dependent area under the ROC curve function (AUC(t)) and high C-indices in the training and validation cohorts were further improved by fitting a combined model consisting of the 18-marker panel and established clinical markers. Our work supports the applicability of this 18-marker panel to improve clinical outcome prediction for breast cancer patients.
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4.
  • Biermann, Jana, et al. (författare)
  • Clonal relatedness in tumour pairs of breast cancer patients.
  • 2018
  • Ingår i: Breast cancer research : BCR. - : Springer Science and Business Media LLC. - 1465-542X. ; 20:1
  • 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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5.
  • Biermann, Jana, et al. (författare)
  • Radiation-induced genomic instability in breast carcinomas of the Swedish haemangioma cohort.
  • 2019
  • Ingår i: Genes, chromosomes & cancer. - : Wiley. - 1098-2264 .- 1045-2257. ; 58:9, s. 627-35
  • 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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6.
  • Biermann, Jana, et al. (författare)
  • Tumour clonality in paired invasive breast carcinomas
  • 2019
  • Ingår i: Cancer Research. - 0008-5472.
  • 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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7.
  • Engqvist, Hanna, 1985, et al. (författare)
  • Immunohistochemical validation of COL3A1, GPR158 and PITHD1 as prognostic biomarkers in early-stage ovarian carcinomasn
  • 2019
  • Ingår i: BMC Cancer. - : Springer Science and Business Media LLC. - 1471-2407. ; 19:1
  • 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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8.
  • Möllerström, Elin, et al. (författare)
  • Up-regulation of cell cycle arrest protein BTG2 correlates with increased overall survival in breast cancer, as detected by immunohistochemistry using tissue microarray.
  • 2010
  • Ingår i: BMC cancer. - : Springer Science and Business Media LLC. - 1471-2407. ; 10:1
  • 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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9.
  • Nemes, Szilard, 1977, et al. (författare)
  • A diagnostic algorithm to identify paired tumors with clonal origin.
  • 2013
  • Ingår i: Genes, chromosomes & cancer. - : Wiley. - 1098-2264 .- 1045-2257. ; 52:11, s. 1007-16
  • 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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10.
  • Parris, Toshima Z, 1978, et al. (författare)
  • Clinical implications of gene dosage and gene expression patterns in diploid breast carcinoma.
  • 2010
  • Ingår i: Clinical cancer research : an official journal of the American Association for Cancer Research. - 1078-0432. ; 16:15, s. 3860-74
  • 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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