On the 15^th of January, Dr Thang Thrinh, Karolinska Institutet, defended his thesis entitled ”Determinants of breast cancer risk; focusing on mammographic density”. Thang’s thesis deals with how physical activity, alcohol consumption and cigarette smoking affect the risk of breast cancer through their influence on mammographic density.

Mammographic density is defined as the radiographically dense tissue, consisting of glandular and connective tissues, appearing bright on a mammogram, whilst non-dense, fatty tissue appears dark on a mammogram. The more bright the mammogram, the more glandular cells and the higher the risk of developing breast cancer. See images below (left: non-dense breast, right: highly dense breast).

Women who participated in the Karma study answered a large number of questions related to lifestyle when they entered the study. Participants were invited to the study when they performed the biannual mammography screening. Dr Thang wanted to find out if women who, for example, drank more wine had more dense breasts than women who totally abstained from alcohol.

In short, the conclusions that could be drawn from this thesis was:

Women who were physically active had a lower mammographic density, which most certainly reduces the risk of breast cancer. The more vigorous the physical activity, the lower the breast density. We also wanted to find out if women with an increased risk of breast cancer needed to do harder physical exercise than women with a lower risk. Background risk of breast cancer was estimated using the Tyrer – Cuzick score. Our findings suggested that women with a higher background risk of breast cancer needs to be more physically active, to reduce breast density, than women with lesser background risk.

Regarding alcohol consumption the findings are quite the opposite. The more alcohol a woman drinks, the higher the breast density and the higher the risk of breast cancer. However, it seems that daily consumption of wine has to exceed 1 glass wine/day to influence breast density. Similar to the findings of physical activity, background risk of breast cancer influenced how alcohol affects mammographic density. If you have a high risk of breast cancer you should be careful with alcohol.

Finally dr Thang studied change in mammographic breast density among cigarette smoking women. Surprisingly enough, in women who smoke the density is lower than in non-smoking women, despite the fact that smoking is known to increase the risk of breast cancer. Thang explained the effect of cigarette smoking on breast density as tobacco having an ”anti-hormonal” effect (which lowers the density) but that tobacco contains so many other toxic / carcinogenic substances that increase the risk of breast cancer so the overall effect is an increased risk of breast cancer.

Professor Per Hall, dr Thang’s supervisor, comments on the results: ”The findings are exciting and show that in the future, when we are able to predict a woman’s individual risk of breast cancer, lifestyle related advise can be given in preventive breast cancer care. As a matter of fact, already today, we can advise women who wish to reduce their risk of breast cancer to be physically active, drink moderately and not to smoke.

Non-invasive monitoring of tumor burden hold great promise for early detection of recurrent breast cancer. Karma researchers recently evaluated and improved exome sequencing to interrogate trace amounts of breast tumors in the plasma of breast cancer patients. “We are encourage by the results”, says Daniel Klevebring, lead author of the study. The researchers are now planning a larger study to investigate the use of exome sequencing of plasma in a primary setting.

Published in PlosOne, Aug 2014. Link to the published paper:

http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0104417

KARMA is the first study validating the performance of a volumetric breast density software (VolparaDensity) in a large-scale setting. Results of the study show that distributions of volumetric density are similar across different vendor platforms and that Volpara breast density is associated with established density determinants and breast cancer risk.

Link to published article:

Cancer Epidemiol Biomarkers Prev. 2014 Sep;23(9):1764-72. doi: 10.1158/1055-9965.EPI-13-1219. Epub 2014 Jul 10. Link to Pubmed: http://www.ncbi.nlm.nih.gov/pubmed/25012995

Tamoxifen has been used for several years as adjuvant therapy for women diagnosed with breast cancer. Tamoxifen was introduced already in the 1970s and reduces the risk of breast cancer recurrence with approximately 30%. Recent studies also indicate that use of Tamoxifen as primary prevention for healthy women at high risk reduce breast cancer incidence.

Our aim is to identify an optimal Tamoxifen dose for reducing risk of breast cancer. Mammographic density reduction will be used as a proxy for therapy response and thereby indirectly incidence.

The clinical trial is in planning phase and will be launched during 2015

Dr Li Jingmei, 31, received this year’s UNESCO-L’Oreal International For Women In Science Fellowship, one of 15 women scientists around the world to do so. Li Jingmei currently work as postdoctoral research fellow at the Agency for Science, Technology and Research’s Genome Institute of Singapore, but have strong connections to Karolinska Institutet and the Karma-group

She will receive her award at a ceremony in Paris this month.

With her US$40,000 award, Dr Li will spend two years at Karolinska Institutet in Sweden, where she previously completed her doctorate in medical science.

Dr Li Jingmei with mammogram images, which she studies to see how breast density predicts cancer risks. A young breast cancer researcher from Singapore will soon have the chance to continue her research on the data from the Karma cohort, thanks to a prestigious international science fellowship. — PHOTO:  L’OREAL SINGAPOR

Mammographic Density Reduction Is a Prognostic Marker of Response to Adjuvant Tamoxifen Therapy in Postmenopausal Patients With Breast Cancer

Tamoxifen treatment is associated with a reduction in mammographic density and an improved
survival. However, the extent to which change in mammographic density during adjuvant
tamoxifen therapy can be used to measure response to treatment is unknown.

Overall, 974 postmenopausal patients with breast cancer who had both a baseline and a follow-up
mammogram were eligible for analysis. On the basis of treatment information abstracted from
medical records, 474 patients received tamoxifen treatment and 500 did not. Mammographic
density was measured by using an automated thresholding method and expressed as absolute
dense area. Change in mammographic density was calculated as percentage change from
baseline. Survival analysis was performed by using delayed-entry Cox proportional hazards
regression models, with death as a result of breast cancer as the end point. Analyses were
adjusted for a range of patient and tumor characteristics.

During a 15-year follow-up, 121 patients (12.4%) died from breast cancer. Women treated with
tamoxifen who experienced a relative density reduction of more than 20% between baseline and
first follow-up mammogram had a reduced risk of death as a result of breast cancer of 50% (hazard
ratio, 0.50; 95% CI, 0.27 to 0.93) compared with women with stable mammographic density. In
the no-tamoxifen group, there was no statistically significant association between mammographic
density change and survival. The survival advantage was not observed when absolute dense areas
at baseline or follow-up were evaluated separately.

A decrease in mammographic density after breast cancer diagnosis appears to serve as a
prognostic marker for improved long-term survival in patients receiving adjuvant tamoxifen, and
these data should be externally validated.

Jingmei Li, Keith Humphreys, Louise Eriksson, Gustaf Edgren, Kamila Czene, and Per Hall

Click here for full article in Journal of Clinical Oncology

[Press release, 27 March 2013] More than 80 genetic ’spelling mistakes’ that can increase the risk of breast, prostate and ovarian cancer have been found in a large, international research study within the framework of the EU Network COGS. For the first time, the researchers also have a relatively clear picture of the total number of genetic alterations that can be linked to these cancers. Ultimately the researchers hope to be able to calculate the individual risk of cancer, to better understand how these cancers develop and to be able to generate new treatments.

The main findings are published in five articles in a special issue on genetic risk factors for cancer in the prestigious scientific journal Nature Genetics. The articles originate from COGS (Collaborative Oncological Gene-environment Study), an EU-based consortium where more than 160 research groups from all over the world are included. In the five COGS studies 100,000 patients with breast, ovarian or prostate cancer and 100,000 healthy individuals from the general population were included.
http://www.nature.com/ng/journal/v45/n4/full/ng.2592.html?WT.ec_id=NG-201304 

In a substudy to Karma, scientists will study why it is more common among women with high mammographic density to develop breast cancer. The study will investigate breast tissue biopsies from women with low breast density and compare this with biopsies from women with dense breasts.

Karma Normal is a collaboration between researchers at the Karolinska Institute and physicians at the mammography clinic in Helsingborg Hospital. The study will invite randomly selected women in the Helsingborg area who already participates in Karma.

Medical doctors take biopsies from healthy breasts using the same procedures as in investigating a breast lump. The biopsies are analyzed with different methods which will present a picture of what the tissue looks like. The researchers will look into any cell composition that represents density and any composition that represents changes that would lead to a cancer later on in life.

The aim is to understand what gives rise to the density and what cell types and genes are influencing development of cancer, and hopefully to prevent breast cancer in the future.

Breast cancer has steadily increased over the past 40 years. In Sweden, one woman per hour is diagnosed with breast cancer and every six hours a woman dies from the disease. The need to prevent the onset of breast cancer is high.

Therefore researchers at the Karolinska Institute in collaboration with four hospitals in Sweden perform the largest cancer study ever in Sweden – Karma.  The objective of this study is to significantly reduce the incidence of breast cancer. Karma will identify high risk women based on lifestyle, genetics, mammographic morphology and other markers. When we can assess the individual risk for breast cancer, the next step is to tailor a preventive treatment for each woman based on the treatments available to them at the time.

Thanks to the 1000 women who voluntarily choose to join the Karma study every week, we have today reached a major milestone with 50,000 participating women!

Karma study has been made possible thanks to a donation of 50 million SEK from Märit and Hans Rausing’s Initiative Against Breast Cancer.

Mammographic density (MD) is a strong, independent risk factor of breast cancer, but measuring MD is time-consuming and reader-dependent. Objective MD measurement in a high-throughput fashion would enable its wider use as a biomarker for breast cancer. We use a public domain image processing software for the fully automated analysis of MD and penalised regression to construct a measure which mimics a well-established semi-automated measure (Cumulus). We also describe measures which incorporate additional features of mammographic images for improving the risk associations of MD and breast cancer risk.

We randomly partitioned our dataset into a training set for model building (733 cases, 748 controls) and a test set for model assessment (765 cases, 747 controls). Pearson’s product moment correlation coefficient (r) was used to compare the MD measurements by Cumulus and our automated measure which mimics Cumulus. The likelihood ratio test was used to validate the performance of logistic regression models for breast cancer risk, which included our measure capturing additional information in mammographic images.

We observed a high correlation between the Cumulus measure and our measure mimicking Cumulus (r = 0.884, 95% CI: 0.872 to 0.894) in an external test set. Adding a variable, which includes extra information to percent density, significantly improved the fit of the logistic regression model of breast cancer risk (P=0.0002).

Our results demonstrate the potential to facilitate the integration of mammographic density measurements into large-scale research studies and subsequently into clinical practice.

Li J, Szekely L, Eriksson L, Heddson B, Sundbom A, Czene K, Hall P, Humphreys K.
Breast Cancer Res. 2012 Jul 30;14(4):R114.

The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in ∼40% of genes, with the landscape dominated by cis- and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP and MAP2K4. Unsupervised analysis of paired DNA-RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the ‘CNA-devoid’ subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome.

Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, Speed D, Lynch AG, Samarajiwa S, Yuan Y, Gräf S, Ha G, Haffari G, Bashashati A, Russell R, McKinney S; METABRIC Group; Co-chairs, Caldas C, Aparicio S; Writing committee, Curtis C, Shah SP, Caldas C, Aparicio S; Steering committee, Brenton JD, Ellis I, Huntsman D, Pinder S, Purushotham A, Murphy L, Caldas C, Aparicio S; Tissue and clinical data source sites:; University of Cambridge/Cancer Research UK Cambridge Research Institute, Caldas C, Bardwell H, Chin SF, Curtis C, Ding Z, Gräf S, Jones L, Liu B, Lynch AG, Papatheodorou I, Sammut SJ, Wishart G; British Columbia Cancer Agency, Aparicio S, Chia S, Gelmon K, Huntsman D, McKinney S, Speers C, Turashvili G, Watson P; University of Nottingham, Ellis I, Blamey R, Green A, Macmillan D, Rakha E; King’s College London, Purushotham A, Gillett C, Grigoriadis A, Pinder S, di Rinaldis E, Tutt A; Manitoba Institute of Cell Biology, Murphy L, Parisien M, Troup S; Cancer genome/transcriptome characterization centres:; University of Cambridge/Cancer Research UK Cambridge Research Institute, Caldas C, Chin SF, Chan D, Fielding C, Maia AT, McGuire S, Osborne M, Sayalero SM, Spiteri I, Hadfield J; British Columbia Cancer Agency, Aparicio S, Turashvili G, Bell L, Chow K, Gale N, Huntsman D, Kovalik M, Ng Y, Prentice L; Data analysis subgroup:; University of Cambridge/Cancer Research UK Cambridge Research Institute, Caldas C, Tavaré S, Curtis C, Dunning MJ, Gräf S, Lynch AG, Rueda OM, Russell R, Samarajiwa S, Speed D, Markowetz F, Yuan Y, Brenton JD; British Columbia Cancer Agency, Aparicio S, Shah SP, Bashashati A, Ha G, Haffari G, McKinney S, Langerød A, Green A, Provenzano E, Wishart G, Pinder S, Watson P, Markowetz F, Murphy L, Ellis I, Purushotham A, Børresen-Dale AL, Brenton JD, Tavaré S, Caldas C, Aparicio S.

1] Department of Oncology, University of Cambridge, Hills Road, Cambridge CB2 2XZ, UK [2] Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK [3] Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California 90033, USA (Ch.C.); University College London, Genetics Institute, WC1E 6BT, UK (D.S.). [4].

Nature. 2012 Apr 18. doi: 10.1038/nature10983. [Epub ahead of print]

The 19p13.1 breast cancer susceptibility locus is a modifier of breast cancer risk in BRCA1 mutation carriers and is also associated with risk of ovarian cancer. Here we investigated 19p13.1 variation and risk of breast cancer subtypes, defined by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) status, using 48,869 breast cancer cases and 49,787 controls from the Breast Cancer Association Consortium (BCAC). Variants from 19p13.1 were not associated with breast cancer overall or with ER-positive breast cancer but were significantly associated with ER-negative breast cancer risk [rs8170 Odds Ratio (OR)=1.10, 95% Confidence Interval (CI) 1.05 – 1.15, p=3.49 x 10-5] and triple negative (TN) (ER, PR and HER2 negative) breast cancer [rs8170 OR=1.22, 95% CI 1.13 – 1.31, p=2.22 x 10-7]. However, rs8170 was no longer associated with ER-negative breast cancer risk when TN cases were excluded [OR=0.98, 95% CI 0.89 – 1.07, p=0.62]. In addition, a combined analysis of TN cases from BCAC and the Triple Negative Breast Cancer Consortium (TNBCC) (n=3,566) identified a genome-wide significant association between rs8170 and TN breast cancer risk [OR=1.25, 95% CI 1.18 – 1.33, p=3.31 x 10-13]. Thus, 19p13.1 is the first triple negative-specific breast cancer risk locus and the first locus specific to a histological subtype defined by ER, PR, and HER2 to be identified. These findings provide convincing evidence that genetic susceptibility to breast cancer varies by tumor subtype and that triple negative tumors and other subtypes likely arise through distinct etiologic pathways.

Stevens KN, Fredericksen Z, Vachon CM, Wang X, Margolin S, Lindblom A, Nevanlinna H, Greco D, Aittomäki K, Blomqvist C, Chang-Claude J, Vrieling A,Flesch-Janys D, Sinn HP, Wang-Gohrke S, Nickels S, Brauch H, Ko YD, Fischer HP, Network TG, Schmutzler RK, Meindl A, Bartram CR, Schott S, Engel C,Godwin AK, Weaver J, Pathak HB, Sharma P, Brenner H, Muller H, Arndt V, Stegmaier C, Miron P, Yannoukakos D, Stavropoulou A, Fountzilas G, Gogas HJ,Swann R, Dwek M, Perkins KA, Milne RL, Benítez J, Zamora MP, Ignacio Arias Pérez J, Bojesen SE, Nielsen SF, Nordestgaard BG, Flyger H, Guénel P, Truong T, Menegaux F, Cordina-Duverger E, Burwinkel B, Marmé F, Schneeweiss A, Sohn C, Sawyer E, Tomlinson I, Kerin MJ, Peto J, Johnson N, Fletcher O, Dos Santos Silva I, Fasching PA, Beckmann MW, Hartmann A, Ekici AB, Lophatananon A, Muir K, Puttawibul P, Wiangnon S, Schmidt MK, Broeks A, Braaf LM,Rosenberg EH, Hopper JL, Apicella C, Park DJ, Southey MC, Swerdlow AJ, Ashworth A, Orr N, Schoemaker MJ, Anton-Culver H, Ziogas A, Bernstein L, Clarke Dur C, Shen CY, Yu JC, Hsu HM, Hsiung CN, Hamann U, Dünnebier T, Rüdiger T, Ulrich Ulmer H, Pharoah PD, Dunning AM, Humphreys MK, Wang Q, Cox A,Cross SS, Reed MW, Hall P, Czene K, et al.
To the article … 

Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for ∼8% of the heritability of the disease. We attempted to replicate 72 promising associations from two independent genome-wide association studies (GWAS) in ∼70,000 cases and ∼68,000 controls from 41 case-control studies and 9 breast cancer GWAS. We identified three new breast cancer risk loci at 12p11 (rs10771399; P = 2.7 × 10(-35)), 12q24 (rs1292011; P = 4.3 × 10(-19)) and 21q21 (rs2823093; P = 1.1 × 10(-12)). rs10771399 was associated with similar relative risks for both estrogen receptor (ER)-negative and ER-positive breast cancer, whereas the other two loci were associated only with ER-positive disease. Two of the loci lie in regions that contain strong plausible candidate genes: PTHLH (12p11) has a crucial role in mammary gland development and the establishment of bone metastasis in breast cancer, and NRIP1 (21q21) encodes an ER cofactor and has a role in the regulation of breast cancer cell growth.

Ghoussaini M, Fletcher O, Michailidou K, Turnbull C, Schmidt MK, Dicks E, Dennis J, Wang Q, Humphreys MK, Luccarini C, Baynes C, Conroy D, Maranian M, Ahmed S, Driver K, Johnson N, Orr N, Dos Santos Silva I, Waisfisz Q, Meijers-Heijboer H, Uitterlinden AG, Rivadeneira F; Netherlands Collaborative Group on Hereditary Breast and Ovarian Cancer (HEBON), Hall P, Czene K, et al.
To the article …

The Karma Research Platform (beta) is now up and running. As of today, any scientist with sound science can get access to the world’s best-characterized breast cancer cohort.

“We are proud to present the Karma Research Platform. With more than 20,000 participants and a steady inflow of more than 800 women per week I believe the Karma Research Platform will become a game-changer for breast cancer research” says Professor Per Hall, Karma PI.

Interested scientists will get access after an inquiry has been sent to Karma’s Research Platform scientific manager. Then, in just a few simple steps the researcher can look at the collected Karma material, select interesting variables and values, modulate the material and finally export selected variables.

“With the Karma Research Platform a scientist can quickly find out how Karma can strengthen his or her research with access to unprecedented real life data and bio-samples” continues Per Hall. “We strongly believe that by sharing data freely, research leading to reduced mortality and incidence in breast cancer will come faster and better.”

To get access to Karma Research Platform, please follow this link.