Heat-Shock Factor 1 (HSF1), master regulator of the heat-shock response, facilitates malignant transformation, cancer cell survival, and proliferation in model systems. The common assumption is that ...these effects are mediated through regulation of heat-shock protein (HSP) expression. However, the transcriptional network that HSF1 coordinates directly in malignancy and its relationship to the heat-shock response have never been defined. By comparing cells with high and low malignant potential alongside their nontransformed counterparts, we identify an HSF1-regulated transcriptional program specific to highly malignant cells and distinct from heat shock. Cancer-specific genes in this program support oncogenic processes: cell-cycle regulation, signaling, metabolism, adhesion and translation. HSP genes are integral to this program, however, many are uniquely regulated in malignancy. This HSF1 cancer program is active in breast, colon and lung tumors isolated directly from human patients and is strongly associated with metastasis and death. Thus, HSF1 rewires the transcriptome in tumorigenesis, with prognostic and therapeutic implications.
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► Comprehensive study of the direct transactivating effects of HSF1 in cancer ► HSF1 regulates diverse cellular processes that extend far beyond heat-shock genes ► Fundamental differences in HSF1 program in cancer versus heat shock ► HSF1 activation in multiple cancers is strongly associated with metastasis and death
The purview of the transcription factor HSF1 extends far beyond heat shock in tumor cells, and the newly identified targets appear to play a key role in determining cancer aggressiveness.
Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only ...its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care.
Breast cancer is a heterogeneous disease with multiple intrinsic tumor subtypes. These subtypes vary in tumor gene expression and phenotype, and are most commonly grouped into four major subtypes: ...luminal A, luminal B, HER2-overexpressing and triple negative (or basal-like). A growing number of studies have evaluated the relationship between established breast cancer risk factors and risk of one or more intrinsic tumor subtypes. We conducted a systematic review of 38 studies to synthesize their results and identify areas requiring more research. Taken together, published studies suggest that most established breast cancer risk factors reflect risk factors for the luminal A subtype of breast cancer, and some breast cancer risk factors may be differentially associated with other intrinsic tumor subtypes. Future breast cancer research will need to consider etiologic differences across subtypes and design studies focused on understanding the etiology and prevention of less common tumor subtypes.
•Breast cancer risk factors vary across tumor subtypes.•Established breast cancer risk factors reflect risk factors for luminal A cancer.•Further research is needed to identify the risk factors for less common subtypes.
Young women are at increased risk for developing more aggressive subtypes of breast cancer. Although previous studies have shown a higher risk of breast cancer recurrence and death among young women ...with early-stage breast cancer, they have not adequately addressed the role of tumor subtype in outcomes.
We examined data from women with newly diagnosed stage I to III breast cancer presenting to one of eight National Comprehensive Cancer Network centers between January 2000 and December 2007. Multivariable Cox proportional hazards models were used to assess the relationship between age and breast cancer-specific survival.
A total of 17,575 women with stage I to III breast cancer were eligible for analysis, among whom 1,916 were ≤ 40 years of age at diagnosis. Median follow-up time was 6.4 years. In a multivariable Cox proportional hazards model controlling for sociodemographic, disease, and treatment characteristics, women ≤ 40 years of age at diagnosis had greater breast cancer mortality (hazard ratio HR, 1.4; 95% CI, 1.2 to 1.7). In stratified analyses, age ≤ 40 years was associated with statistically significant increases in risk of breast cancer death among women with luminal A (HR, 2.1; 95% CI, 1.4 to 3.2) and luminal B (HR 1.4; 95% CI, 1.1 to 1.9) tumors, with borderline significance among women with triple-negative tumors (HR, 1.4; 95% CI, 1.0 to 1.8) but not among those with human epidermal growth factor receptor 2 subtypes (HR, 1.2; 95% CI, 0.8 to 1.9). In an additional model controlling for detection method, young age was associated with significantly increased risk of breast cancer death only among women with luminal A tumors.
The effect of age on survival of women with early breast cancer seems to vary by breast cancer subtype. Young age seems to be particularly prognostic in women with luminal breast cancers.
Epidemiologic evidence suggests that certain dietary patterns were associated with breast cancer risk, but the results have been inconclusive. We assessed the associations between different dietary ...patterns and the risk of breast cancer by conducting a meta-analysis of observational studies.
Relevant articles were searched in PubMed, Embase, and Cochrane library databases through September 2017. Multivariable-adjusted relative risks (RRs) and 95% confidence intervals (CIs) comparing the highest and lowest categories of Western and prudent dietary patterns were combined by using the random-effects meta-analyses.
We identified 32 eligible articles including 14 cohort and 18 case-control studies (34 Western and 35 prudent studies). The pooled analyses found that a Western dietary pattern was associated with a 14% increased risk (RR 1.14, 95% CI 1.02, 1.28), whereas a prudent dietary pattern was associated with an 18% reduced risk of breast cancer (RR 0.82, 95% CI 0.75, 0.89). In addition, sub-group analyses showed that the positive association between a Western dietary pattern and breast cancer risk was significant among postmenopausal (RR 1.20, 95% CI 1.06, 1.35), but not premenopausal women (RR 1.18, 95% CI 0.99, 1.40), and significant for hormone receptor-positive tumors (RR 1.18, 95% CI 1.04, 1.33), but not receptor-negative tumors (RR 0.97, 95% CI 0.83, 1.12). In contrast, the inverse association between a prudent dietary pattern and breast cancer was significant in premenopausal (RR 0.77, 95% CI 0.61, 0.98), but not postmenopausal women (RR 0.88, 95% CI 0.74, 1.03), and significant for both hormone receptor-positive and receptor-negative tumors.
The results of the current meta-analysis suggest a possible increased risk of breast cancer associated with a Western dietary pattern and a reduced risk with a prudent dietary pattern. Large-scale cohort studies with a high quality need to be conducted to further confirm the findings of the current meta-analysis. As dietary patterns are modifiable, these findings may provide viable strategies for breast cancer prevention through changes in dietary intake.
Animal and epidemiologic studies suggest that exposure to light at night (LAN) may disrupt circadian patterns and decrease nocturnal secretion of melatonin, which may disturb estrogen regulation, ...leading to increased breast cancer risk.
We examined the association between residential outdoor LAN and breast cancer incidence using data from the nationwide U.S.-based Nurses' Health Study II cohort.
We followed 109,672 women from 1989 through 2013. Cumulative LAN exposure was estimated using time-varying satellite data for a composite of persistent nighttime illumination at ∼1 km
scale for each residence during follow-up. Incident invasive breast cancer cases were confirmed by medical record review. We used Cox proportional hazard models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs), adjusting for anthropometric, reproductive, lifestyle, and socioeconomic risk factors.
Over 2,187,425 person-years, we identified 3,549 incident breast cancer cases. Based on a fully adjusted model, the estimated HR for incident breast cancer with an interquartile range (IQR) (31.6 nW/cm
/sr) increase in cumulative average outdoor LAN was 1.05 (95% CI: 1.00, 1.11). An association between LAN and breast cancer appeared to be limited to women who were premenopausal at the time of a case HR=1.07 (95% CI: 1.01, 1.14) based on 1,973 cases vs. HR=1.00 (95% CI: 0.91, 1.09) based on 1,172 cases in postmenopausal women;
-interaction=0.08. The LAN-breast cancer association was observed only in past and current smokers at the end of follow-up HR=1.00 (95% CI: 0.94, 1.07) based on 2,215 cases in never smokers; HR=1.10 (95% CI: 1.01, 1.19) based on 1,034 cases in past smokers vs. HR=1.21 (95% CI: 1.07, 1.37) for 300 cases in current smokers;
-interaction=0.08.
Although further work is required to confirm our results and to clarify potential mechanisms, our findings suggest that exposure to residential outdoor light at night may contribute to invasive breast cancer risk. https://doi.org/10.1289/EHP935.
Celotno besedilo
Dostopno za:
CEKLJ, DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
In 2007, the International Agency for Research on Cancer declared shift work that involved circadian disruption to be a "probable" carcinogen (group 2A), noting that human evidence was limited. Using ...data from 2 prospective cohort studies, the Nurses' Health Study (1988-2012; n = 78,516) and Nurses' Health Study II (1989-2013; n = 114,559), we examined associations between rotating night-shift work and breast cancer risk. In the 2 cohorts, there were a total of 9,541 incident invasive breast malignancies and 24 years of follow-up. In the Nurses' Health Study, women with 30 years or more of shift work did not have a higher risk of breast cancer (hazard ratio (HR) = 0.95, 95% confidence interval (95% CI): 0.77, 1.17; P for trend = 0.63) compared with those who never did shift work, although follow-up occurred primarily after retirement from shift work. Among participants in the Nurses' Health Study II, who were younger than participants in the other cohort, the risk of breast cancer was significantly higher in women with 20 years or more of shift work at baseline, reflecting young-adult exposure (HR = 2.15, 95% CI: 1.23, 3.73; P for trend = 0.23), and was marginally significantly higher for women with 20 years or more of cumulative shift work when we used updated exposure information (HR = 1.40, 95% CI: 1.00, 1.97; P for trend = 0.74). In conclusion, long-term rotating night-shift work was associated with a higher risk of breast cancer, particularly among women who performed shift work during young adulthood. Further studies should explore the role of shift work timing on breast cancer risk.
No prior study to our knowledge has examined the joint contribution of a polygenic risk score (PRS), mammographic density (MD), and postmenopausal endogenous hormone levels-all well-confirmed risk ...factors for invasive breast cancer-to existing breast cancer risk prediction models.
We conducted a nested case-control study within the prospective Nurses' Health Study and Nurses' Health Study II including 4,006 cases and 7,874 controls ages 34-70 years up to 1 June 2010. We added a breast cancer PRS using 67 single nucleotide polymorphisms, MD, and circulating testosterone, estrone sulfate, and prolactin levels to existing risk models. We calculated area under the curve (AUC), controlling for age and stratified by menopausal status, for the 5-year absolute risk of invasive breast cancer. We estimated the population distribution of 5-year predicted risks for models with and without biomarkers. For the Gail model, the AUC improved (p-values < 0.001) from 55.9 to 64.1 (8.2 units) in premenopausal women (Gail + PRS + MD), from 55.5 to 66.0 (10.5 units) in postmenopausal women not using hormone therapy (HT) (Gail + PRS + MD + all hormones), and from 58.0 to 64.9 (6.9 units) in postmenopausal women using HT (Gail + PRS + MD + prolactin). For the Rosner-Colditz model, the corresponding AUCs improved (p-values < 0.001) by 5.7, 6.2, and 6.5 units. For estrogen-receptor-positive tumors, among postmenopausal women not using HT, the AUCs improved (p-values < 0.001) by 14.3 units for the Gail model and 7.3 units for the Rosner-Colditz model. Additionally, the percentage of 50-year-old women predicted to be at more than twice 5-year average risk (≥2.27%) was 0.2% for the Gail model alone and 6.6% for the Gail + PRS + MD + all hormones model. Limitations of our study included the limited racial/ethnic diversity of our cohort, and that general population exposure distributions were unavailable for some risk factors.
In this study, the addition of PRS, MD, and endogenous hormones substantially improved existing breast cancer risk prediction models. Further studies will be needed to confirm these findings and to determine whether improved risk prediction models have practical value in identifying women at higher risk who would most benefit from chemoprevention, screening, and other risk-reducing strategies.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We examined the proportions of multiple types of breast cancers in the population that were attributable to established risk factors, focusing on behaviors that are modifiable at menopause. We ...estimated the full and partial population attributable risk percentages (PAR%) by combining the relative risks and the observed prevalence rates of the risk factors of interest. A total of 8,421 cases of invasive breast cancer developed in postmenopausal women (n = 121,700) in the Nurses' Health Study from 1980-2010. We included the following modifiable risk factors in our analyses: weight change since age 18 years, alcohol consumption, physical activity level, breastfeeding, and menopausal hormone therapy use. Additionally, the following nonmodifiable factors were included: age, age at menarche, height, a combination of parity and age at first birth, body mass index at age 18 years, family history of breast cancer, and prior benign breast disease. When we considered all risk factors (and controlled for age), the PAR% for invasive breast cancers was 70.0% (95% confidence interval: 55.0, 80.7). When considering only modifiable factors, we found that changing the risk factor profile to the lowest weight gain, no alcohol consumption, high physical activity level, breastfeeding, and no menopausal hormone therapy use was associated with a PAR% of 34.6% (95% confidence interval: 22.7, 45.4). The PAR% for modifiable factors was higher for estrogen receptor-positive breast cancers (PAR% = 39.7%) than for estrogen receptor-negative breast cancers (PAR% = 27.9%). Risk factors that are modifiable at menopause account for more than one-third of postmenopausal breast cancers; therefore, a substantial proportion of breast cancer in the United States is preventable.
Epidemiologic data suggest that parity increases risk of hormone receptor-negative breast cancer and that breastfeeding attenuates this association. Prospective data, particularly on the joint ...effects of higher parity and breastfeeding, are limited.
We investigated parity, breastfeeding, and breast cancer risk by hormone-receptor (estrogen (ER) and progesterone receptor (PR)) and molecular subtypes (luminal A, luminal B, HER2-enriched, and basal-like) in the Nurses' Health Study (NHS; 1976-2012) and NHSII (1989-2013). A total of 12,452 (ER+ n = 8235; ER- n = 1978) breast cancers were diagnosed among 199,514 women. We used Cox proportional hazards models, adjusted for breast cancer risk factors, to calculate hazard ratios (HR) and 95% confidence intervals (CI).
Parous women had lower risk of ER+ breast cancer (vs. nulliparous, HR = 0.82 0.77-0.88); no association was observed for ER- disease (0.98 0.84-1.13; P
= 0.03). Among parous women, breastfeeding was associated with lower risk of ER- (vs. never 0.82 0.74-0.91), but not ER+, disease (0.99 0.94-1.05; P
< 0.001). Compared to nulliparous women, higher parity was inversely associated with luminal B breast cancer regardless of breastfeeding (≥ 3 children: ever breastfed, 0.78 0.62-0.98; never breastfed, 0.76 0.58-1.00) and luminal A disease only among women who had breastfed (≥ 3 children, 0.84 0.71-0.99). Basal-like breast cancer risk was suggestively higher among women with higher parity who never breastfed; associations were null among those who ever breastfed.
This study provides evidence that breastfeeding is inversely associated with hormone receptor-negative breast cancers, representing an accessible and cost-effective risk-reduction strategy for aggressive disease subtypes.
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