Surviving Breast Cancer: Mia K. Markey’s Quest to Improve Patients’ Lives from Diagnosis to Reconstruction

October 29, 2019
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An emphasis on the psychosocial elements of living with diseases such as breast cancer may seem uncommon in engineering. But Mia K. Markey, biomedical engineering professor in the Cockrell School of Engineering, is dedicated to designing decision-support systems for patients, aiming to help enhance their quality of life post-treatment.

Markey Mia

Her research approach is firmly rooted in finding data-driven solutions for cancer diagnosis and treatment. Her most recent work is focused on creating a cost-effective computational decision-making aid for breast cancer survivors.

Markey is acutely aware that every number generated by the algorithms and datasets she relies on for her work represents a human being suffering from a terrifying disease.  

"Cancer robs us of our days,” she said. “The thievery can come as a direct reduction in lifespan. But the days stolen by suffering are just as lost to us. My research is important to me because I believe it will help improve the quality of people’s lives.”

markey breast cancer infographic

Her and her team’s recent study focuses on the welfare of patients considering breast reconstruction surgery following breast cancer treatment. They found that women wish their doctors gave them more information on all potential outcomes before making a decision on which procedure was right for them. The study was presented this month by Krista Nicklaus, one of Markey’s Ph.D. students, at the Biomedical Engineering Society Annual Meeting and is part of a National Institutes of Health-funded multi-year study that aims to enhance the consultation process for women undergoing breast reconstruction surgery.

The team conducted a small survey of women who had recently undergone breast reconstruction surgery, asking about their experiences, with particular emphasis on the decision-making process and communication from doctors. Of the respondents, 93% said they would like to have been shown more visual examples of outcomes from different surgical procedures before making a final decision.

“Doctors are conscious of providing too much detail on the worst possible post-surgery outcomes, especially if they are statistically unlikely,” Markey said. “Their concern is that it only serves to cause undue stress on women already under severe pressure.”

But the study found that patients want as much information as possible before making a decision. Without it, many resort to conducting their own online research, which can lead them to viewing post-surgery images that may be unreliable and unverifiable and so increase their stress and uncertainty.

Markey is looking at the broader psychosocial factors at play for women who must choose between different breast reconstruction surgery options, a decision that women currently must make without much context to help inform their choice. This study will help Markey and her team design a patient-specific decision-support system providing personalized visual information about post-surgery outcomes.


Breast Cancer Research in the Cockrell School

Reprogramming Cancer Cells and Creating a Backbone for Personalized Medicine

While mammography is great at detecting certain lesions, only a small fraction of these abnormalities develop into breast cancer. At this time, there are no good biomarkers that predict which lesions may become life-threatening. Biomedical engineering assistant professor Amy Brock is identifying new, less drastic ways to treat abnormal cells. She’s identifying what triggers the journey to cancer in order to develop new interventions that could reverse the growth of malignant tumors early on and eliminate the need for invasive surgery and chemotherapy.

Brock has also developed an innovative barcoding technology to track and tag individual tumor cells. Tagging individual cells will allow Brock and her collaborators at Dell Medical School’s LIVESTRONG Cancer Institutes to study them in greater depth and treat them with different therapies to learn which ones respond by dying off and which ones come back more resistant.

Stimulating the Immune System with Laser Therapies

Biomedical engineers James Tunnell and Laura Suggs are collaborating to treat breast cancer by perturbing immune cells called macrophages to help them find and fight cancer cells. Immunotherapy has seen great progress in treating some forms of cancer, but the response rates in breast cancer have been very low. One possible reason is that breast tumors are abundant in a type of macrophage that suppresses the immune response, inhibiting the immune system from recognizing and killing the cancer cells. Tunnell and Suggs use low-energy laser light along with specifically shaped nanoparticles to precisely manipulate tumor-associated-macrophage cells, making these immune cells pro-inflammatory and inciting the immune system to attack cancer. If successful, this strategy will improve immune therapies in tumors that currently don’t respond to treatment.

Using Math to Forecast Breast Cancer Tumor Growth for Patient-Specific Treatment

Professor Tom Yankeelov develops mathematical models to forecast how breast tumors will grow, change and respond to treatment. Yankeelov and his colleagues in the Center for Computational Oncology, use advanced imaging techniques to measure specific tumor characteristics (e.g. blood flow and proliferation), and then puts these data into biophysical models to predict how a tumor will respond to therapy. Advances in imaging science, applied mathematics and computer simulation make it possible for Yankeelov and his team to build models designed to optimize treatments on an individual patient basis. Importantly, their team is performing these studies in collaboration with US Oncology, Seton Healthcare Family and Austin Radiological Society — a true public-private partnership between biomedical engineers and practicing physicians in the Austin metropolitan area.

“Our goal is to learn the mathematical laws of cancer, so that ultimately we have a set of equations that we are confident can recapitulate the spatial and temporal development of a tumor,” Yankeelov said.