Purpose: To summarize existing knowledge and to understand individual response to radiation exposure, the MELODI Association together with CONCERT European Joint Programme has organized a workshop in ...March 2018 on radiation sensitivity and susceptibility.
Methods: The workshop reviewed the current evidence on this matter, to inform the MELODI Strategic Research Agenda (SRA), to determine social and scientific needs and to come up with recommendations for suitable and feasible future research initiatives to be taken for the benefit of an improved medical diagnosis and treatment as well as for radiation protection.
Results: The present paper gives an overview of the current evidence in this field, including potential effect modifiers such as age, gender, genetic profile, and health status of the exposed population, based on clinical and epidemiological observations.
Conclusion: The authors conclude with the following recommendations for the way forward in radiation research: (a) there is need for large (prospective) cohort studies; (b) build upon existing radiation research cohorts; (c) use data from well-defined cohorts with good exposure assessment and biological material already collected; (d) focus on study quality with standardized data collection and reporting; (e) improve statistical analysis; (f) cooperation between radiobiology and epidemiology; and (g) take consequences of radiosensitivity and radiosusceptibility into account.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Lipid-lowering drugs are used for the prevention of cardiovascular diseases. Statins are the most commonly used lipid-lowering drugs. Evidence from preclinical and observational studies suggests that ...statins might improve the prognosis of breast cancer patients. We analyzed data from the German MARIEplus study, a large prospective population-based cohort of patients aged 50 and older, who were diagnosed with breast cancer between 2001 and 2005. For overall mortality, breast-cancer specific mortality, and non-breast-cancer mortality, we included 3189 patients with invasive breast cancer stage I-IV, and for recurrence risk 3024 patients with breast cancer stage I-III. We used Cox proportional hazards models to assess the association with self-reported lipid-lowering drug use at recruitment. We stratified by study region, tumor grade, and estrogen/progesterone receptor status, and adjusted for age, tumor size, nodal status, metastases (stage I-IV only), menopausal hormone treatment, mode of detection, radiotherapy, and smoking. Mortality analyses were additionally adjusted for cardiovascular disease, diabetes mellitus and body-mass index. During a median follow-up of 5.3 years, 404 of 3189 stage I-IV patients died, and 286 deaths were attributed to breast cancer. Self-reported use of lipid-lowering drugs was non-significantly associated with increased non-breast cancer mortality (Hazard ratio (HR) 1.49, 95% confidence interval (CI) 0.88-2.52) and increased overall mortality (HR 1.21, 95% CI 0.87-1.69) whereas no association with breast cancer-specific mortality was found (HR 1.04, 0.67-1.60). Restricted to stage I-III breast cancer patients, 387 recurrences occurred during a median follow-up of 5.4 years. We found lipid-lowering drug use to be non-significantly associated with a reduced risk of recurrence (HR 0.83, 95% CI 0.54-1.24) and of breast cancer-specific mortality (HR 0.89, 95% CI 0.52-1.49). Although compatible with previous findings of an improved prognosis associated with statin use, our results do not provide clear supportive evidence for an association with lipid-lowering drug use due to imprecise estimates.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Radiotherapy is a fundamental part of cancer treatment but its use is limited by the onset of late adverse effects in the normal tissue, especially radiation-induced fibrosis. Since the molecular ...causes for fibrosis are largely unknown, we analyse if epigenetic regulation might explain inter-individual differences in fibrosis risk. DNA methylation profiling of dermal fibroblasts obtained from breast cancer patients prior to irradiation identifies differences associated with fibrosis. One region is characterized as a differentially methylated enhancer of diacylglycerol kinase alpha (DGKA). Decreased DNA methylation at this enhancer enables recruitment of the profibrotic transcription factor early growth response 1 (EGR1) and facilitates radiation-induced DGKA transcription in cells from patients later developing fibrosis. Conversely, inhibition of DGKA has pronounced effects on diacylglycerol-mediated lipid homeostasis and reduces profibrotic fibroblast activation. Collectively, DGKA is an epigenetically deregulated kinase involved in radiation response and may serve as a marker and therapeutic target for personalized radiotherapy.
Oxaliplatin is frequently used as part of a chemotherapeutic regimen with 5‐fluorouracil in the treatment of colorectal cancer (CRC). The cellular availability of oxaliplatin is dependent on ...metabolic and transporter enzymes. Variants in genes encoding these enzymes may cause variation in response to oxaliplatin and could be potential predictive markers. Therefore, we used a two‐step procedure to comprehensively investigate 1,444 single nucleotide polymorphisms (SNPs) from these pathways for their potential as predictive markers for oxaliplatin treatment, using 623 stage II–IV CRC patients (of whom 201 patients received oxaliplatin) from a German prospective patient cohort treated with adjuvant or palliative chemotherapy. First, all genes were screened using the global test that evaluated SNP*oxaliplatin interaction terms per gene. Second, one model was created by backward elimination on all SNP*oxaliplatin interactions of the selected genes. The statistical procedure was evaluated using bootstrap analyses. Nine genes differentially associated with overall survival according to oxaliplatin treatment (unadjusted p values < 0.05) were selected. Model selection resulted in the inclusion of 14 SNPs from eight genes (six transporter genes, ABCA9, ABCB11, ABCC10, ATP1A1, ATP1B2, ATP8B3, and two metabolism genes GSTM5, GRHPR), which significantly improved model fit. Using bootstrap analysis we show an improvement of the prediction error of 3.7% in patients treated with oxaliplatin. Several variants in genes involved in metabolism and transport could thus be potential predictive markers for oxaliplatin treatment in CRC patients. If confirmed, inclusion of these variants in a predictive test could identify patients who are more likely to benefit from treatment with oxaliplatin.
What's new?
Oxaliplatin frequently is used in combination with 5‐fluorouracil and leucovorin as a first‐line therapy against colorectal cancer (CRC). However, the efficacy of oxaliplatin differs greatly between patients. Oxaliplatin availability to cells and its subsequent detoxification depend on the activity of certain metabolic and transporter enzymes, some of which, according to this study, carry genetic variants that alter the drug's effectiveness. The authors show that interactions between oxaliplatin and single nucleotide polymorphisms (SNPs) in multiple transporter and metabolism genes are associated with overall CRC survival. The SNPs could be used to predict the likelihood of response to oxaliplatin.
An individual's inherited genetic variation may contribute to the 'angiogenic switch', which is essential for blood supply and tumor growth of microscopic and macroscopic tumors. Polymorphisms in ...angiogenesis-related genes potentially predispose to colorectal cancer (CRC) or affect the survival of CRC patients. We investigated the association of 392 single nucleotide polymorphisms (SNPs) in 33 angiogenesis-related genes with CRC risk and survival of CRC patients in 1754 CRC cases and 1781 healthy controls within DACHS (Darmkrebs: Chancen der Verhütung durch Screening), a German population-based case-control study. Odds ratios and 95% confidence intervals (CI) were estimated from unconditional logistic regression to test for genetic associations with CRC risk. The Cox proportional hazard model was used to estimate hazard ratios (HR) and 95% CIs for survival. Multiple testing was adjusted for by a false discovery rate. No variant was associated with CRC risk. Variants in
,
and
were significantly associated with overall survival. The association of the
tagging SNP rs9520090 (
< 0.0001) was confirmed in two validation datasets (
-values: 0.01 and 0.05). The associations of the tagging SNPs rs6040062 in
(
-value 0.0003) and rs2241145 in
(
-value 0.0005) showed the same direction of association with overall survival in the first and second validation sets, respectively, although they did not reach significance (
-values: 0.09 and 0.25, respectively).
,
and
are known for their functional role in angiogenesis and the present study points to novel evidence for the impact of angiogenesis-related genetic variants on the CRC outcome.
Normal tissue complication probability (NTCP) models can be useful to estimate the risk of fibrosis after breast-conserving surgery (BCS) and radiotherapy (RT) to the breast. However, they are ...subject to uncertainties. We present the impact of contouring variation on the prediction of fibrosis.
280 breast cancer patients treated BCS-RT were included. Nine Clinical Target Volume (CTV) contours were created for each patient: i) CTV_crop (reference), cropped 5 mm from the skin and ii) CTV_skin, uncropped and including the skin, iii) segmenting the 95% isodose (Iso95%) and iv) 3 different auto-contouring atlases generating uncropped and cropped contours (Atlas_skin/Atlas_crop). To illustrate the impact of contour variation on NTCP estimates, we applied two equations predicting fibrosis grade ≥ 2 at 5 years, based on Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) models, respectively, to each contour. Differences were evaluated using repeated-measures ANOVA. For completeness, the association between observed fibrosis events and NTCP estimates was also evaluated using logistic regression.
There were minimal differences between contours when the same contouring approach was followed (cropped and uncropped). CTV_skin and Atlas_skin contours had lower NTCP estimates (−3.92%, IQR 4.00, p < 0.05) compared to CTV_crop. No significant difference was observed for Atlas_crop and Iso95% contours compared to CTV_crop. For the whole cohort, NTCP estimates varied between 5.3% and 49.5% (LKB) or 2.2% and 49.6% (RS) depending on the choice of contours. NTCP estimates for individual patients varied by up to a factor of 4. Estimates from “skin” contours showed higher agreement with observed events.
Contour variations can lead to significantly different NTCP estimates for breast fibrosis, highlighting the importance of standardising breast contours before developing and/or applying NTCP models.
•Differences in breast radiotherapy contouring after breast-conserving surgery influence the estimated probability of normal tissue complications.•For individual patients, the estimated risk of grade ≥ 1 breast fibrosis at five years after radiotherapy varies by up to factor of 4.•It is essential to define and standardise contours when developing/applying NTCP models.
Breast cancer is a complex disease and may be sub-divided into hormone-responsive (estrogen receptor (ER) positive) and non-hormone-responsive subtypes (ER-negative). Some evidence suggests that ...heterogeneity exists in the associations between coffee consumption and breast cancer risk, according to different estrogen receptor subtypes. We assessed the association between coffee consumption and postmenopausal breast cancer risk in a large population-based study (2,818 cases and 3,111 controls), overall, and stratified by ER tumour subtypes.
Odds ratios (OR) and corresponding 95% confidence intervals (CI) were estimated using the multivariate logistic regression models fitted to examine breast cancer risk in a stratified case-control analysis. Heterogeneity among ER subtypes was evaluated in a case-only analysis, by fitting binary logistic regression models, treating ER status as a dependent variable, with coffee consumption included as a covariate.
In the Swedish study, coffee consumption was associated with a modest decrease in overall breast cancer risk in the age-adjusted model (OR> 5 cups/day compared to OR≤ 1 cup/day: 0.80, 95% CI: 0.64, 0.99, P trend = 0.028). In the stratified case-control analyses, a significant reduction in the risk of ER-negative breast cancer was observed in heavy coffee drinkers (OR> 5 cups/day compared to OR≤ 1 cup/day : 0.43, 95% CI: 0.25, 0.72, P trend = 0.0003) in a multivariate-adjusted model. The breast cancer risk reduction associated with higher coffee consumption was significantly higher for ER-negative compared to ER-positive tumours (P heterogeneity (age-adjusted) = 0.004).
A high daily intake of coffee was found to be associated with a statistically significant decrease in ER-negative breast cancer among postmenopausal women.
To identify the main causes underlying the failure of prediction models for radiation therapy toxicity to replicate.
Data were used from two German cohorts, Individual Radiation Sensitivity (ISE) ...(n=418) and Mammary Carcinoma Risk Factor Investigation (MARIE) (n=409), of breast cancer patients with similar characteristics and radiation therapy treatments. The toxicity endpoint chosen was telangiectasia. The LASSO (least absolute shrinkage and selection operator) logistic regression method was used to build a predictive model for a dichotomized endpoint (Radiation Therapy Oncology Group/European Organization for the Research and Treatment of Cancer score 0, 1, or ≥2). Internal areas under the receiver operating characteristic curve (inAUCs) were calculated by a naïve approach whereby the training data (ISE) were also used for calculating the AUC. Cross-validation was also applied to calculate the AUC within the same cohort, a second type of inAUC. Internal AUCs from cross-validation were calculated within ISE and MARIE separately. Models trained on one dataset (ISE) were applied to a test dataset (MARIE) and AUCs calculated (exAUCs).
Internal AUCs from the naïve approach were generally larger than inAUCs from cross-validation owing to overfitting the training data. Internal AUCs from cross-validation were also generally larger than the exAUCs, reflecting heterogeneity in the predictors between cohorts. The best models with largest inAUCs from cross-validation within both cohorts had a number of common predictors: hypertension, normalized total boost, and presence of estrogen receptors. Surprisingly, the effect (coefficient in the prediction model) of hypertension on telangiectasia incidence was positive in ISE and negative in MARIE. Other predictors were also not common between the 2 cohorts, illustrating that overcoming overfitting does not solve the problem of replication failure of prediction models completely.
Overfitting and cohort heterogeneity are the 2 main causes of replication failure of prediction models across cohorts. Cross-validation and similar techniques (eg, bootstrapping) cope with overfitting, but the development of validated predictive models for radiation therapy toxicity requires strategies that deal with cohort heterogeneity.
Breast cancer is the most frequent cancer type among women in western countries. In addition to established risk factors like hormone replacement therapy, oxidative stress may play a role in ...carcinogenesis through an unbalanced generation of reactive oxygen species that leads to genetic instability. The aim of this study is to assess the influence of common single nucleotide polymorphisms (SNPs) in candidate genes related to oxidative stress on postmenopausal breast cancer risk. We genotyped 109 polymorphisms (mainly tagging SNPs) in 22 candidate genes in 1,639 postmenopausal breast cancer cases and 1,967 controls (set 1) from the German population‐based case‐control study “MARIE”. SNPs showing association in set 1 were tested in further 863 cases and 2,863 controls from MARIE (set 2) using a joint analysis strategy. Six polymorphisms evaluated in the combined set showed significantly modified breast cancer risk per allele in the joint analysis, including SNPs in CYBA (encoding a subunit of the NADPH oxidase: rs3794624), MT2A (metallothionein 2A: rs1580833), TXN (thioredoxin: rs2301241), and in TXN2 (thioredoxin 2: rs2267337, rs2281082, rs4821494). Associations with the CYBA rs3794624 (OR per allele: 0.93, 95% CI 0.87–0.99) and TXN rs2301241 variants (OR per allele: 1.05, 95% CI 1.00–1.10) were confirmed in the summary risk estimate analysis using up to three additional studies. We found some evidence for association of polymorphisms in genes of the thioredoxin system, CYBA, and MT2A with postmenopausal breast cancer risk. Summary evidence including independent datasets indicated moderate effects in CYBA and TXN that warrant confirmation in large independent studies.
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