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Researchers linked obesity with breast cancer

Scientists compared genetic data from tumors of breast cancer patients, and found patients with high body mass indexes had unique gene alterations.

Image Credit: Photo by National Cancer Institute on Unsplash

Breast cancer affects thousands of people every year.  Scientists have shown many factors can influence breast cancer, like age, lack of physical activity, and obesity. But they don’t know exactly how obesity and breast cancer are linked. 

Researchers in the past hypothesized that tissue inflammation in obese patients was linked to cancer. Other researchers showed that obese patients have a specific genetic mutation that is also linked to cancer. However, they don’t fully understand how this mutation acts to produce different tumor types.

Ha-Linh Nguyen and colleagues recently investigated the connection between breast cancer and obesity. Nguyen and his team wanted to determine how obesity affects breast cancer, by examining tissue cells and genetic profiles of breast tumors in obese patients. Their goal was to see if doctors could create more targeted treatments for breast cancer based on the genetic mutations involved.

They gathered genetic data from the tumors of over 2,000 breast cancer patients, taken during multiple large-scale breast cancer studies done by 5 accredited cancer research institutions. To ensure the breast tumors had not been altered in any way, they only used data from patients who had not yet begun cancer treatment. 

The researchers defined obesity based on a ratio of the patient’s weight and height, called body mass index, or BMI. They used the patients’ BMI data to categorize them into 3 categories: obese, overweight, and lean. Obese patients had a BMI higher than 30 kilograms per square meter (kg/m2), overweight patients had a BMI between 25 to 30 kg/m2, and lean patients had a BMI from 18.5 to 25 kg/m2. For reference, the average BMI for adults is about 26 kg/m2

Then they sorted the patients into further categories based on the type of breast tumors they had. These categories included patients with tumors that started in the milk production glands in the breast, termed Invasive Lobular Carcinomas tumors, or ILC tumors, versus patients with no special type of tumors. 

The researchers also took into account other biological factors used to identify types of breast cancer, like estrogen receptors. In people with estrogen receptor-positive breast cancer, their tumor contains a receptor that uses the hormone estrogen to help fuel tumor cell growth. In people with estrogen receptor-negative breast cancer, their tumor does not contain this receptor. 

They also considered another way of determining the type of tumor, called the HER2 factor. An HER2-positive breast cancer patient contains a protein called the human epidermal growth factor 2, which allows the cancer cells to multiply quickly. After the researchers used these biochemical markers to categorize the patients by tumor type, they used statistical analyses to compare tumor types in obese patients versus the lean and overweight groups. 

The scientists found that in obese patients with estrogen receptor-positive and HER2-negative non-special tumors, their BMI influenced their breast cancer similar to the way aging influenced cancer development. They explained that as we age our body’s immune response slows down, which gives cancer cells more time to build up before our body responds to stop the process. They suggested these results reinforced the idea that both age and obesity are risk factors for developing breast cancer. 

Next, the scientists looked at whether tumors from each group had one or more cancer-causing mutations. The team specifically looked at genes that researchers had previously shown to have mutations that cause breast cancer. They also looked at the tumor DNA to see if there were any mutations that cause deletion or amplification of certain sections of DNA, called copy number alterations

The researchers found different gene mutations in patients with different BMIs. They found that a gene involved in signaling cell division, called P1K3CA, was mutated less often in obese patients with estrogen receptor-positive, HER2-negative, non-special tumors. Mutations in 2 other genes, CCND1 and CCNE1, were more common in obese patients with estrogen receptor-positive tumors.

The researchers concluded their study points to a genetic link between breast cancer and obesity. They suggested some gene mutations found in tumors of obese patients, particularly the CCND1 and CCNE1 mutations, could allow for targeted breast cancer treatments. They suggested future researchers should examine how the biochemical pathways these genes are associated with actually contribute to breast cancer formation to better develop treatments. 

Study Information

Original study: Obesity-associated changes in molecular biology of primary breast cancer

Study was published on: July 21, 2023

Study author(s): Ha-Linh Nguyen, Tatjana Geukens, Marion Maetens, Samuel Aparicio, Ayse Bassez, Ake Borg, Jane Brock, Annegien Broeks, Carlos Caldas, Fatima Cardoso, Maxim De Schepper, Mauro Delorenzi, Caroline A. Drukker, Annuska M. Glas, Andrew R. Green, Edoardo Isnaldi, Jórunn Eyfjörð, Hazem Khout, Stian Knappskog, Savitri Krishnamurthy, Sunil R. Lakhani, Anita Langerod, John W. M. Martens, Amy E. McCart Reed, Leigh Murphy, Stefan Naulaerts, Serena Nik-Zainal, Ines Nevelsteen, Patrick Neven, Martine Piccart, Coralie Poncet, Kevin Punie, Colin Purdie, Emad A. Rakha, Andrea Richardson, Emiel Rutgers, Anne Vincent-Salomon, Peter T. Simpson, Marjanka K. Schmidt, Christos Sotiriou, Paul N. Span, Kiat Tee Benita Tan, Alastair Thompson, Stefania Tommasi, Karen Van Baelen, Marc Van de Vijver, Steven Van Laere, Laura van’t Veer, Giuseppe Viale, Alain Viari, Hanne Vos, Anke T. Witteveen, Hans Wildiers, Giuseppe Floris, Abhishek D. Garg, Ann Smeets, Diether Lambrechts, Elia Biganzoli, François Richard, Christine Desmedt

The study was done at: Katholieke Universiteit Leuven (Belgium), Lund University (Sweden), Netherlands Cancer Institute (Netherlands), University of Cambridge (UK), Champalimaud Clinical Center/Champalimaud Foundation (Portugal), University of Lausanne (Switzerland), SIB Swiss Institute of Bioinformatics (Switzerland), Antoni van Leeuwenhoek Hospital (Netherlands), University of Nottingham (UK), University of Iceland (Iceland), University Hospitals of Leicester NHS Trust (UK), University of Bergen (Norway), The University of Texas MD Anderson Cancer Center (USA), The University of Queensland, Herston (Australia), The Royal Brisbane and Women’s Hospital, Herston (Australia), Oslo University Hospital, Ullernchausseen (Norway), Erasmus University Medical Center, Rotterdam (Netherlands), University of Manitoba and Cancer Care Manitoba Research Institute (Canada), University Hospitals Leuven (Belgium), Institut Jules Bordet and Université Libre de Bruxelles (Belgium), European Organisation for Research and Treatment of Cancer (EORTC) Headquarters (Belgium), University of Dundee (UK), Nottingham University Hospital NHS Trust (UK), Johns Hopkins University (USA), Netherlands Cancer Institute (Netherlands), Institut Curie, PSL Research University (France), Radboud University Medical Center (Netherlands), Sengkang General Hospital (Singapore), National Cancer Centre (Singapore), Baylor College of Medicine (USA), IRCCS Istituto Tumouri “Giovanni Paolo II” (Italy), University of Amsterdam (Netherlands), University of Antwerp (Belgium), UCSF Helen Diller Family Comprehensive Cancer Center (USA), European Institute of Oncology IRCCS (Italy), University of Milan (Italy), Synergie Lyon Cancer, Plateforme de Bio-informatique ‘Gilles Thomas’ (France), Università degli Studi di Milano (Italy)

The study was funded by: Luxembourg Cancer Foundation, European Research Council, KU Leuven

Raw data availability: Data from the ICGC cohort can be accessed through the ICGC Data Portal, data from ELBC can be accessed through the Gene Expression Omnibus at accession number GSE88770, data from MINDACT can be accessed through the EORTC, read count data for individual patients can be accessed from BioKey, raw sequencing reads can be accessed in the European Genome-phenomeArchive under study no. EGAS00001004809 and data accession no. EGAD00001006608

Featured image credit: Photo by National Cancer Institute on Unsplash

This summary was edited by: Aubrey Zerkle