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Background: The performance of deep learning segmentation (DLS) models for automatic organ extraction from CT images in the thorax and breast regions was investigated. Furthermore, the readiness and feasibility of integrating DLS into clinical practice were addressed by measuring the potential time savings and dosimetric impact. Material and Methods: Thirty patients referred to radiotherapy for breast cancer were prospectively included. A total of 23 clinically relevant left- and right-sided organs were contoured manually on CT images according to ESTRO guidelines. Next, auto-segmentation was executed, and the geometric agreement between the auto-segmented and manually contoured organs was qualitatively assessed applying a scale in the range [0-not acceptable, 3-no corrections]. A quantitative validation was carried out by calculating Dice coefficients (DSC) and the 95% percentile of Hausdorff distances (HD95). The dosimetric impact of optimizing the treatment plans on the uncorrected DLS contours, was investigated from a dose coverage analysis using DVH values of the manually delineated contours as references. Results: The qualitative analysis showed that 93% of the DLS generated OAR contours did not need corrections, except for the heart where 67% of the contours needed corrections. The majority of DLS generated CTVs needed corrections, whereas a minority were deemed not acceptable. Still, using the DLS-model for CTV and heart delineation is on average 14 minutes faster. An average DSC=0.91 and H95=9.8 mm were found for the left and right breasts, respectively. Likewise, and average DSC in the range [0.66, 0.76]mm and HD95 in the range [7.04, 12.05]mm were found for the lymph nodes. Conclusion: The validation showed that the DLS generated OAR contours can be used clinically. Corrections were required to most of the DLS generated CTVs, and therefore warrants more attention before possibly implementing the DLS models clinically. [ABSTRACT FROM AUTHOR]

The time after a breast cancer diagnosis is a potential period for making positive dietary changes, but previous results are conflicting. The main aim of the present study was to study breast cancer patients' dietary changes during the 12 months post-surgery and from 12 months pre-surgery to 12 months post-surgery with repeated administration of a 7-d pre-coded food diary and an FFQ, respectively. Women (n 506), mean age 55·3 years diagnosed with invasive breast cancer (stages I and II), were included. The dietary intake was quite stable over time, but the intake was lower for energy (0·3 and 0·4 MJ/d), alcohol (1·9 and 1·5 g/d) and vegetables (17 and 22 g/d) at 6 months than 3 weeks post-surgery (food diary) and at 12 months post-surgery than pre-surgery (FFQ), respectively. Furthermore, energy percentage (E%) from carbohydrates increased between 0·8 and 1·2 E% and E% from fat decreased between 0·6 and 0·8 E% over time, measured by both dietary assessment methods. We observed a higher intake of dairy products (11 g/d) at 6 months post-surgery (food diary), and a lower intake of dairy products (34 g/d) and red and processed meat (7·2 g/d) at 12 months post-surgery (FFQ). Moreover, 24 % of the patients claimed they made dietary changes, but mostly they did not change their diet differently compared with those patients who claimed no changes. In conclusion, breast cancer patients reported only minor dietary changes from 12 months pre-surgery and during the 12 months post-surgery. [ABSTRACT FROM AUTHOR]

Background: The introduction of immune check-point inhibition in non-small cell lung cancer (NSCLC) therapy represents improved prospects for the patients. The response rates to check-point inhibitors are approximately 20% in unselected NSCLC patients. Increasing levels of tumor PD-L1 expression are associated with higher response rates. However, patients with low PD-L1 levels may also have durable responses, and improved strategies for patient stratification are needed. Material and methods: In this study, we investigated circulating microRNAs aiming to identify circulating predictive biomarkers associated with increased overall survival after immune check-point treatment. Using next generation sequencing, we performed microRNA profiling in serum from NSCLC patients (n¼20) treated with nivolumab. Serum samples from 31 patients were used for validation using qPCR assays. Serum samples were collected prior to immune therapy initiation. Results: Based on multivariate regression analysis, we identified a signature of seven microRNAs (miR- 215-5p, miR-411-3p, miR-493-5p, miR-494-3p, miR-495-3p, miR-548j-5p and miR-93-3p) significantly associated with overall survival (OS)>6 months in discovery cohort (p¼ = .0003). We further validated this in another similar set of samples (n¼31) and the model was significantly associated with overall survival (OS)>6 months (p¼ = .001) with sensitivity and specificity of 71% and 90%, respectively. Conclusions: In this study of circulating microRNAs, we have identified a 7-miR signature associated with survival in nivolumab-treated NSCLC patients. This signature may lead to better treatment options for patients with NSCLC, but a validation in an independent cohort is needed to confirm the predicted potential. [ABSTRACT FROM AUTHOR]

Background: High-Density Lipoprotein (HDL)-cholesterol, has been associated with breast cancer development, but the association is under debate, and whether lipoprotein subfractions is associated with breast tumor characteristics remains unclear. Methods: Among 56 women with newly diagnosed invasive breast cancer stage I/II, aged 35–75 years, pre-surgery overnight fasting serum concentrations of lipids were assessed, and body mass index (BMI) was measured. All breast tumors were immunohistochemically examined in the surgical specimen. Serum metabolomics of lipoprotein subfractions and their contents of cholesterol, free cholesterol, phospholipids, apolipoprotein-A1 and apolipoprotein-A2, were assessed using nuclear magnetic resonance. Principal component analysis, partial least square analysis, and uni- and multivariable linear regression models were used to study whether lipoprotein subfractions were associated with breast cancer tumor characteristics. Results: The breast cancer patients had following means: age at diagnosis: 55.1 years; BMI: 25.1 kg/m2; total-Cholesterol: 5.74 mmol/L; HDL-Cholesterol: 1.78 mmol/L; Low-Density Lipoprotein (LDL)-Cholesterol: 3.45 mmol/L; triglycerides: 1.18 mmol/L. The mean tumor size was 16.4 mm, and the mean Ki67 hotspot index was 26.5 %. Most (93 %) of the patients had estrogen receptor (ER) positive tumors (≥1 % ER+), and 82 % had progesterone receptor (PgR) positive tumors (≥10 % PgR+). Several HDL subfraction contents were strongly associated with PgR expression: Apolipoprotein-A1 (β 0.46, CI 0.22–0.69, p < 0.001), HDL cholesterol (β 0.95, CI 0.51–1.39, p < 0.001), HDL free cholesterol (β 2.88, CI 1.28–4.48, p = 0.001), HDL phospholipids (β 0.70, CI 0.36–1.04, p < 0.001). Similar results were observed for the subfractions of HDL1-3. We observed inverse associations between HDL phospholipids and Ki67 (β -0.25, p = 0.008), and in particular between HDL1’s contents of cholesterol, phospholipids, apolipoprotein-A1, apolipoprotein-A2 and Ki67. No association was observed between lipoproteins and ER expression. Conclusion: Our findings hypothesize associations between different lipoprotein subfractions, and PgR expression, and Ki 67 % in breast tumors. These findings may have clinical implications, but require confirmation in larger studies. [ABSTRACT FROM AUTHOR]

Introduction High mammographic density is an established breast cancer risk factor, and circulating oestrogen influence oestrogen-regulating gene expression in breast cancer development. However, less is known about the interrelationships of common variants in the CYP19A1 gene, daily levels of oestrogens, mammographic density phenotypes, and body mass index (BMI) in premenopausal women. Methods Based on plausible biological mechanisms related to the oestrogen pathway, we investigated the association of single nucleotide polymorphisms (SNPs) in CYP19A1, 17β-estradiol and mammographic density in 202 premenopausal women. DNA was genotyped using the Illumina Golden Gate platform. Daily salivary 17β-estradiol concentrations were measured throughout an entire menstrual cycle. Mammographic density phenotypes were assessed using a computer-assisted method (Madena). We determined associations using multivariable linear and logistic regression models. Results The minor alleles of rs749292 were positively (P = 0.026), and the minor alleles of rs7172156 were inversely (P = 0.002) associated with daily 17β-estradiol. We observed an 87% lower level of daily 17β-estradiol throughout a menstrual cycle in heavier women (BMI >23.6 kg/m²) of rs7172156 with minor genotype aa compared with major genotype AA. Furthermore, the rs749292 minor alleles were inversely associated with absolute mammographic density (P = 0.032). Lean women with rs749292 minor alleles had 70 to 80% lower risk for high absolute mammographic density (>32.4 cm²); Aa: odds ratio (OR) = 0.23 (95% CI 0.07 to 0.75). Lean women with rs7172156 minor homozygous genotype had OR 5.45 for high absolute mammographic density (aa: OR = 5.45 (95% CI 1.13 to 26.3)). Conclusion Our findings suggest that two SNPs in CYP19A1, rs749292 and rs7172156, are associated with both daily oestrogen levels and mammographic density phenotypes. Body mass index may modify these associations, but larger studies are needed. [ABSTRACT FROM AUTHOR]

Exercise could reduce the side-effects of adjuvant breast cancer treatment; however, socio-demographic, health, and intervention conditions may affect patients' adherence to interventions. This study aimed to examine adherence to a 12-month outdoor post-surgery exercise program among newly diagnosed breast cancer patients during adjuvant treatment, and to identify socio-demographic and health-related predictors. In total, 47 women with invasive breast cancer stage I–II or ductal/lobular carcinoma grade 3 were included pre-surgery and randomized two weeks post-surgery to exercise (2 × 60 min/week). Patient characteristics (body-mass index (BMI), socioeconomic status, comorbidity, physical activity, and maximal oxygen uptake (VO2max)) were recorded pre-surgery. Correlations between adherence and patient characteristics and statistics for between-group differences were performed. The mean age was 54.2 years, mean BMI 27.8 kg/m2, and 54.2% received chemotherapy. Completers had a mean adherence of 81%, independent of season. Withdrawals (23%) occurred after a mean of 6.5 weeks (0–24 weeks), they were suggestively older, had lower socioeconomic status and pre-surgery VO2max, and higher BMI. Household income was significantly lower among withdrawals. There were insignificant correlations between adherence and health conditions. High adherence is achievable in a Nordic outdoor physical exercise program in breast cancer patients during adjuvant treatment, including chemotherapy. Additional studies are needed to clarify follow-up needs in some groups. [ABSTRACT FROM AUTHOR]

Introduction  Physical activity may reduce the development of breast cancer. Whereas hypercoagulability has been linked to adverse outcomes in breast cancer patients, the effects of physical activity on their hemostatic factors are unknown. The study aimed to assess whether long-term (1 year) physical activity can affect hemostatic factors in breast cancer patients. Methods  Fifty-five women (35-75 years) with invasive breast cancer stage I/II were randomized to a physical activity intervention ( n  = 29) lasting 1 year or to a control group ( n  = 26), and analyzed as intention to treat. Fibrinogen, factor VII antigen, tissue factor pathway inhibitor, and von Willebrand factor (VWF) antigen as well as prothrombin fragment 1 + 2, the endogenous thrombin potential and D-dimer, were measured in plasma before intervention (baseline), and then after 6 and 12 months. Results  Maximal oxygen uptake (measure of cardiorespiratory fitness) decreased the first 6 months among the controls, but remained stable in the intervention group. We found no significant differences between the two study groups regarding any of the hemostatic factors, except a significantly higher increase in factor VII antigen in the intervention group. The effect of the intervention on VWF was, however, significantly affected by menopausal stage, and a significant effect of the intervention was found on VWF among postmenopausal women, even after adjustment for dietary intake. Conclusion  Long-term physical activity had no effect on the majority of the hemostatic factors measured, but led to increased plasma concentrations of factor VII antigen and prevented an increase in VWF concentration after breast cancer treatment in postmenopausal women. The clinical impact of these findings for risk of vascular thrombosis warrants further studies., Competing Interests: Conflict of interest None declared., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. ( https://creativecommons.org/licenses/by/4.0/ ).)

High-density lipoprotein-cholesterol (HDL-C) may influence the proliferation of breast tumor cells, but it is unclear whether low HDL-C levels, alone or in combination with cyclic estrogen and progesterone, are associated with mammographic density, a strong predictor of breast cancer development. Fasting morning serum concentrations of HDL-C were assessed in 202 premenopausal women, 25 to 35 years of age, participating in the Norwegian Energy Balance and Breast Cancer Aspects (EBBA) I study. Estrogen and progesterone were measured both in serum, and daily in saliva, throughout an entire menstrual cycle. Absolute and percent mammographic density was assessed by a computer-assisted method (Madena), from digitized mammograms (days 7-12). Multivariable models were used to study the associations between HDL-C, estrogen and progesterone, and mammographic density phenotypes. We observed a positive association between HDL-C and percent mammographic density after adjustments (P = 0.030). When combining HDL-C, estradiol, and progesterone, we observed among women with low HDL-C (<1.39 mmol/L), a linear association between salivary 17β-estradiol, progesterone, and percent and absolute mammographic density. Furthermore, in women with low HDL-C, each one SD increase of salivary mid-menstrual 17β-estradiol was associated with an OR of 4.12 (95% confidence intervals; CI, 1.30-13.0) of having above-median percent (28.5%), and an OR of 2.5 (95% CI, 1.13-5.50) of having above-median absolute mammographic density (32.4 cm(2)). On the basis of plausible biologic mechanisms linking HDL-C to breast cancer development, our findings suggest a role of HDL-C, alone or in combination with estrogen, in breast cancer development. However, our small hypothesis generating study requires confirmation in larger studies., (©2015 American Association for Cancer Research.)