| 1. |
- Sundgot-Borgen, Christine, et al.
(författare)
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The Norwegian healthy body image intervention promotes positive embodiment through improved self-esteem
- 2020
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Ingår i: Body image. - : Elsevier. - 1740-1445 .- 1873-6807. ; 35, s. 84-95
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Tidskriftsartikel (refereegranskat)abstract
- We examined both direct and indirect effects of the Healthy Body Image (HBI) intervention on positive embodiment among Norwegian high school students. In total, 2446 12th grade boys (43 %) and girls (mean age 16.8 years) from 30 schools participated in a cluster-randomized controlled study with the HBI intervention and a control condition as the study arms. We tested mediation models using path analysis and found that among several hypothesized mediators, only self-esteem mediated a positive intervention effect on positive embodiment for both boys and girls. A direct effect of the intervention on positive embodiment was only found in girls. The study provides novel findings indicating that health promotion interventions to address a positive embodiment should focus on enhancing adolescent's selfesteem. Serial mediation modeling might reveal more complex explanations of change mechanisms and could further evolve current knowledge.
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| 2. |
- Hartkopf, Andreas D., et al.
(författare)
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Disseminated tumour cells from the bone marrow of early breast cancer patients : Results from an international pooled analysis
- 2021
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Ingår i: European Journal of Cancer. - : Elsevier BV. - 0959-8049. ; 154, s. 128-137
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Presence of disseminated tumour cells (DTCs) in the bone marrow (BM) has been described as a surrogate of residual disease in patients with early breast cancer (EBC). PADDY (Pooled Analysis of DTC Detection in Early Breast Cancer) is a large international analysis of pooled data that aimed to assess the prognostic impact of DTCs in patients with EBC. Experimental design: Individual patient data were collected from 11 centres. Patients with EBC and available follow-up data in whom BM sampling was performed at the time of primary diagnosis before receiving any anticancer treatment were eligible. DTCs were identified by antibody staining against epithelial cytokeratins. Multivariate Cox regression was used to compare the survival of DTC-positive versus DTC-negative patients. Results: In total, 10,307 patients were included. Of these, 2814 (27.3%) were DTC-positive. DTC detection was associated with higher tumour grade, larger tumour size, nodal positivity, oestrogen receptor and progesterone receptor negativity, and HER2 positivity (all p < 0.001). Multivariate analyses showed that DTC detection was an independent prognostic marker for overall survival, disease-free survival and distant disease-free survival with hazard ratios (HR) and 95% confidence intervals (CI) of 1.23 (95% CI: 1.06–1.43, p = 0.006), 1.30 (95% CI: 1.12–1.52, p < 0.001) and 1.30 (95% CI: 1.08–1.56, p = 0.006), respectively. There was no association between locoregional relapse-free survival and DTC detection (HR 1.21; 95% CI 0.68–2.16; p = 0.512). Conclusions: DTCs in the BM represent an independent prognostic marker in patients with EBC. The heterogeneous metastasis-initiating potential of DTCs is consistent with the concept of cancer dormancy.
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| 3. |
- Haugen, Mads H., et al.
(författare)
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Protein signature predicts response to neoadjuvant treatment with chemotherapy and bevacizumab in HER2-negative breast cancers
- 2021
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Ingår i: JCO Precision Oncology. - 2473-4284. ; 5, s. 286-306
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE Antiangiogenic therapy using bevacizumab has proven effective for a number of cancers; however, in breast cancer (BC), there is an unmet need to identify patients who benefit from such treatment. PATIENTS AND METHODS In the NeoAva phase II clinical trial, patients (N = 132) with large (= 25 mm) human epidermal growth factor receptor 2 (HER2)-negative primary tumors were randomly assigned 1:1 to treatment with neoadjuvant chemotherapy (CTx) alone or in combination with bevacizumab (Bev plus CTx). The ratio of the tumor size after relative to before treatment was calculated into a continuous response scale. Tumor biopsies taken prior to neoadjuvant treatment were analyzed by reverse-phase protein arrays (RPPA) for expression levels of 210 BC-relevant (phospho-) proteins. Lasso regression was used to derive a predictor of tumor shrinkage from the expression of selected proteins prior to treatment. RESULTS We identified a nine-protein signature score named vascular endothelial growth factor inhibition response predictor (ViRP) for use in the Bev plus CTx treatment arm able to predict with accuracy pathologic complete response (pCR) (area under the curve [AUC] = 0.85; 95% CI, 0.74 to 0.97) and low residual cancer burden (RCB 0/I) (AUC = 0.80; 95% CI, 0.68 to 0.93). The ViRP score was significantly lower in patients with pCR (P< .001) and in patients with low RCB (P<.001). The ViRP score was internally validated on mRNA data and the resultant surrogate mRNA ViRP score significantly separated the pCR patients (P = .016). Similarly, the mRNA ViRP score was validated (P < .001) in an independent phase II clinical trial (PROMIX). CONCLUSION Our ViRP score, integrating the expression of nine proteins and validated on mRNA data both internally and in an independent clinical trial, may be used to increase the likelihood of benefit from treatment with bevacizumab combined with chemotherapy in patients with HER2-negative BC.
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| 4. |
- Johansson, Henrik J., et al.
(författare)
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Breast cancer quantitative proteome and proteogenomic landscape
- 2019
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Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- In the preceding decades, molecular characterization has revolutionized breast cancer (BC) research and therapeutic approaches. Presented herein, an unbiased analysis of breast tumor proteomes, inclusive of 9995 proteins quantified across all tumors, for the first time recapitulates BC subtypes. Additionally, poor-prognosis basal-like and luminal B tumors are further subdivided by immune component infiltration, suggesting the current classification is incomplete. Proteome-based networks distinguish functional protein modules for breast tumor groups, with co-expression of EGFR and MET marking ductal carcinoma in situ regions of normal-like tumors and lending to a more accurate classification of this poorly defined subtype. Genes included within prognostic mRNA panels have significantly higher than average mRNA-protein correlations, and gene copy number alterations are dampened at the protein-level; underscoring the value of proteome quantification for prognostication and phenotypic classification. Furthermore, protein products mapping to non-coding genomic regions are identified; highlighting a potential new class of tumor-specific immunotherapeutic targets.
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| 5. |
- Kvastad, Linda, et al.
(författare)
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Single cell analysis of cancer cells using an improved RT-MLPA method has potential for cancer diagnosis and monitoring
- 2015
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Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 5
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Tidskriftsartikel (refereegranskat)abstract
- Single cell analysis techniques have great potential in the cancer genomics feld. The detection and characterization of circulating tumour cells are important for identifying metastatic disease at an early stage and monitoring it. This protocol is based on transcript profiling using Reverse Transcriptase Multiplex Ligation-dependent Probe Amplification (RT-MLPA), which is a specific method for simultaneous detection of multiple mRNA transcripts. Because of the small amount of (circulating) tumour cells, a pre-amplification reaction is performed after reverse transcription to generate a sufficient number of target molecules for the MLPA reaction. We designed a highly sensitive method for detecting and quantifying a panel of seven genes whose expression patterns are associated with breast cancer, and optimized the method for single cell analysis. For detection we used a fluorescence-dependent semi-quantitative method involving hybridization of unique barcodes to an array. We evaluated the method using three human breast cancer cell lines and identified specific gene expression profiles for each line. Furthermore, we applied the method to single cells and confirmed the heterogeneity of a cell population. Successful gene detection from cancer cells in human blood from metastatic breast cancer patients supports the use of RT-MLPA as a diagnostic tool for cancer genomics.
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| 6. |
- Lien, Tonje G., et al.
(författare)
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Sample preparation approach influences pam50 risk of recurrence score in early breast cancer
- 2021
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Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 13:23
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Tidskriftsartikel (refereegranskat)abstract
- The PAM50 gene expression subtypes and the associated risk of recurrence (ROR) score are used to predict the risk of recurrence and the benefits of adjuvant therapy in early-stage breast cancer. The Prosigna assay includes the PAM50 subtypes along with their clinicopathological fea-tures, and is approved for treatment recommendations for adjuvant hormonal therapy and chemotherapy in hormone-receptor-positive early breast cancer. The Prosigna test utilizes RNA extracted from macrodissected tumor cells obtained from formalin-fixed, paraffin-embedded (FFPE) tissue sections. However, RNA extracted from fresh-frozen (FF) bulk tissue without macrodissection is widely used for research purposes, and yields high-quality RNA for downstream analyses. To in-vestigate the impact of the sample preparation approach on ROR scores, we analyzed 94 breast carcinomas included in an observational study that had available gene expression data from macro-dissected FFPE tissue and FF bulk tumor tissue, along with the clinically approved Prosigna scores for the node-negative, hormone-receptor-positive, HER2-negative cases (n = 54). ROR scores were calculated in R; the resulting two sets of scores from FFPE and FF samples were compared, and treatment recommendations were evaluated. Overall, ROR scores calculated based on the macro-dissected FFPE tissue were consistent with the Prosigna scores. However, analyses from bulk tissue yielded a higher proportion of cases classified as normal-like; these were samples with relatively low tumor cellularity, leading to lower ROR scores. When comparing ROR scores (low, intermedi-ate, and high), discordant cases between the two preparation approaches were revealed among the luminal tumors; the recommended treatment would have changed in a minority of cases.
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| 7. |
- Tekpli, Xavier, et al.
(författare)
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An independent poor-prognosis subtype of breast cancer defined by a distinct tumor immune microenvironment
- 2019
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- How mixtures of immune cells associate with cancer cell phenotype and affect pathogenesis is still unclear. In 15 breast cancer gene expression datasets, we invariably identify three clusters of patients with gradual levels of immune infiltration. The intermediate immune infiltration cluster (Cluster B) is associated with a worse prognosis independently of known clinicopathological features. Furthermore, immune clusters are associated with response to neoadjuvant chemotherapy. In silico dissection of the immune contexture of the clusters identified Cluster A as immune cold, Cluster C as immune hot while Cluster B has a pro-tumorigenic immune infiltration. Through phenotypical analysis, we find epithelial mesenchymal transition and proliferation associated with the immune clusters and mutually exclusive in breast cancers. Here, we describe immune clusters which improve the prognostic accuracy of immune contexture in breast cancer. Our discovery of a novel independent prognostic factor in breast cancer highlights a correlation between tumor phenotype and immune contexture.
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