Ed Brown works with Marvin Doyley on Tissue Stiffness is a Mosh Pit Where Cancer Cells Thrive
Thursday, December 6, 2018
Imagine being at a packed concert hall with a mosh pit full of dancers creating a wall against outsiders. When targeted drugs try to make their way toward a pancreas tumor, they encounter a similar obstacle in stiff tissue that surrounds and protects the cancer.
A new University of Rochester study demonstrates how imaging technology can be used to accurately measure tissue stiffness — thereby predicting the likelihood that drugs will be able get through to the tumor and guide drug penetration.
“Being able to ‘see’ stiff tissue in the tumor microenvironment is a detection strategy that could help oncologists plan treatments for their patients and monitor progress,” said senior author Marvin Doyley, Ph.D.
A medical physicist and associate professor of Electrical and Computer Engineering and Biomedical Engineering, Doyley is collaborating with David Linehan, M.D., director of clinical operations at UR Medicine’s Wilmot Cancer Institute, and a surgeon/scientist who also has a special interest in pancreatic cancer. For years Linehan has been investigating the critical role the microenvironment plays in promoting pancreas tumors, and he has designed clinical trials for drugs that stimulate the immune system to attack pancreas tumors.
Their collaboration recognizes that chemotherapy followed by surgery is currently the best treatment, and therefore reducing tissue stiffness is critical for that goal.
Doyley and Linehan are seeking funding to continue the investigation in humans. They would like to confirm that ultrasound technology can be used effectively to guide drug delivery; their team is also working with Wilmot scientist Edward Brown, Ph.D., an associate professor of Biomedical Engineering, who studies the collagen-rich fibers near tumors that contribute to tissue stiffness and cancer metastasis.Read More: Ed Brown works with Marvin Doyley on Tissue Stiffness is a Mosh Pit Where Cancer Cells Thrive
Professor Ed Brown receives NIH grant for research project, "Using Second Harmonic Generation to Predict Metastatic Outcome in Colon Adenocarcinoma"
Monday, March 20, 2017
Professor Edward Brown has received NIH funding for his research project titled, "Using Second Harmonic Generation to Predict Metastatic Outcome in Colon Adenocarcinoma."
"In summary, we previously discovered that an optical scattering phenomenon from primary tumor samples provides an independent prognostic indicator of time to metastasis in colon cancer patients," Professor Brown says. "With this grant we will explore if and how this can be used to improve prediction of outcomes for individual patients, leading to improved therapy decisions."
When treating a colon adenocarcinoma (CA) patient, after surgical resection of the tumor the clinician must formulate a plan for adjuvant systemic therapy. This decision is based upon an assessment of the risk of systemic disease recurrence, and is currently informed by pathological factors such as stage, histological grade, and lymph node status. Improvement of the accuracy of risk assessment for individual patients is an area of recognized need. Much of the current information used to assess risk focuses on the cells within tumors, including their morphological properties. Less attention is paid to the extracellular matrix through which metastasizing cells must travel. Second harmonic generation (SHG) is an optical scattering phenomenon whose directionality (as quantified by the “F/B” ratio) is affected by the diameter, spacing, and disorder of fibrils within collagen fibers. Our preliminary data suggests that F/B analysis of tumor samples provides prognostic information about future metastasis that is “matrix-focused” and hence complementary to current “cell-focused” methods. Consequently we hypothesize that F/B is a clinically useful predictor of metastatic outcome in colon adenocarcinoma. In a preliminary study in 44 Stage I colon adenocarcinoma samples we found that F/B of the primary tumor is a significant prognostic indicator of progression free survival time. Significantly, the quartile of patients with the lowest F/B ratio had a 15 year progression free survival percentage of below 50%. In other words, in this study F/B could identify a subset of Stage I patients who had survival statistics similar to Stage III patients. Stage I patients are rarely prescribed adjuvant chemotherapy while Stage III patients are almost always prescribed it. This suggests that F/B can identify patients who would have benefitted from adjuvant chemotherapy and who were left untreated based upon current prognostic indicators. The prognostic trend was also evident in a cohort of 72 Stage II colon adenocarcinoma samples, although it was not significant. This project will move this idea closer to the clinic by first (Aim 1) using archived samples and follow up data in separate training and validation sets to develop predictive algorithms that include F/B, in addition to clinical and genomic information. Second it will (Aim 2) quantify the effect of adjuvant chemotherapy on the predictive ability of the algorithms, as well as quantify their ability to predict chemotherapeutic efficacy. We predict that F/B analysis will be an effective tool that can reach the clinic rapidly after this study to improve metastatic risk assessment. Improving the accuracy of risk estimation for an individual patient will allow clinicians to treat those patients who are destined for metastases, improving outcomes, while avoiding treatment for those patients who are not, reducing overtreatment.
Professor Edward Brown and Professor Catherine K. Kuo receive grant from Department of Defense office of the Congressionally Directed Medical Research Programs
Thursday, February 23, 2017
The Department of Defense office of the Congressionally Directed Medical Research Programs has awarded Professor Edward Brown and Professor Catherine K. Kuo a grant for their research project titled, "Understanding the Role of Matrix Microstructure in Metastasis.” The goal of this project is to evaluate molecular mechanisms underlying the ability of an optical scattering phenomenon to predict metastatic outcome in patient samples.