Navigation Links
Tumor growth and chemo response may be predicted by mathematical model
Date:5/18/2009

The aggressiveness of tumors and their susceptibility to chemotherapy may become easier to predict based on a mathematical model developed at The University of Texas Health Science Center at Houston.

In spite of extensive experimental and clinical studies, the process of cancer growth is not well understood. Tumors are complex systems, with changes at the molecular and cellular levels influencing shape and behavior in sometimes unpredictable ways. New research by a scientist in mathematical oncology at the UT Health Science Center at Houston suggests that mathematical modeling based on data from the molecular and cellular levels could shed light on tumor development and lead to better treatments.

Cancer is the second most common cause of death in the United States, exceeded only by heart disease, according to the American Cancer Society.

At the 100th annual meeting of the American Association for Cancer Research in Denver this spring, Vittorio Cristini, Ph.D., an associate professor of health informatics at The University of Texas School of Health Information Sciences at Houston, demonstrated the predictability of tumor growth in brain cancer and chemotherapy response in breast cancer. Findings appear in two different papers in the May 15 print issue of the association's peer-reviewed journal Cancer Research.

The mathematical model developed by Cristini's lab works by defining tumor biologic and molecular properties relating to laboratory and clinical observations of cancers. In this model, the behavior of cancer cells and their surroundings is linked to tumor growth, shape and treatment response.

"The central finding of this work is that tumor growth and invasion are not erratic or unpredictable, or solely explained through genomic and molecular events, but rather are predictable processes obeying biophysical laws," the authors wrote in the paper addressing predictability of tumor growth in brain cancer.

Tumors obtain nutrients and oxygen by harnessing the surrounding blood vessels and making new vessels. Since there typically aren't enough nutrients and oxygen to support tumor cells, an uneven distribution of these substances is created inside and around the tumor mass, Cristini said.

The research of Cristini and colleagues, who worked in collaboration with Elaine L. Bearer, M.D., Ph.D., professor at the Brown School of Medicine, suggests that tumor growth and invasion could be predicted by using biophysical laws that link the effects of the uneven distribution of cell nutrients and oxygen to overall tumor behavior.

For different values of the input parameters, the model consistently reproduced the patterns of tumor invasion observed in experiments and in patient tumors, Cristini said. The patterns were regulated by changes in cellular characteristics, causing more aggressive tumor cells to invade the healthy tissue. As cancer cells invade and replicate themselves, they make the tumor shape unstable and more invasive. The model correctly predicted the different types of invasion under a variety of conditions.

The model further predicted that the different forms of cancer invasion correspond to different stages of tumor progression, Cristini said. In regions of low oxygen, these changes may include a slowdown in cell replication and heightened cell migration, which can result in a "single-cell file" invasion pattern. As cells aggregate in regions that have better access to nutrients and oxygen, migration is lessened and cell replication is resumed. This leads to the formation of wave-like patterns of cell rearrangements at the tumor boundary and the formation of round infiltrative "fingers" that can detach from the tumor as clusters of cells.

In the second paper, working in collaboration with Mary Edgerton, M.D., Ph.D., associate professor of pathology at The University of Texas M. D. Anderson Cancer Center, the researchers used the mathematical model to successfully predict the effects of doxorubicin on breast tumor growth. The model incorporates information gleaned from cancer cells grown in the laboratory to determine whether a prescribed drug will reach the tumor in sufficient quantities to kill the malignant cells. "We seek to improve the precision of prescribing chemotherapeutic drugs, since it is sometimes hard to tell which will work and which will not, and what the optimal dose is for a particular patient," said Hermann Frieboes, Ph.D., lead author of the chemotherapy study and a post doctoral fellow at the UT School of Health Information Sciences.

In the not-too-distant future, the mathematical model could help design therapies in which the molecular and cellular characteristics of a patient's tumor are manipulated, Cristini said. This could decrease the spread of the tumor and help surgeons remove growths more effectively. This manipulation could also increase the susceptibility of tumors to chemotherapy, he added. The model could augment efforts to predict drug response, which currently include removing a tiny sample of cancer tissue and testing the response of its cells to cancer drugs in a laboratory situation before the patient starts treatment. By basing the model input parameters on specific patient data, the treatment outcomes could be predicted better.


'/>"/>

Contact: Robert Cahill
Robert.Cahill@uth.tmc.edu
713-500-3030
University of Texas Health Science Center at Houston
Source:Eurekalert  

Related biology news :

1. Invasion of the brain tumors
2. Novel 3-D cell culture model shows selective tumor uptake of nanoparticles
3. Bits of junk RNA aid master tumor-suppressor gene
4. Analysis of breast and colon cancer genes finds many areas of differences between tumors
5. Tumor genome analysis unveils new insights into lung cancer
6. Cell response to stress signals predicts tumors in women with common pre-breast cancer
7. Synthetic compound promotes death of lung-cancer cells, tumors
8. MIT: Remote-control nanoparticles deliver drugs directly into tumors
9. New X-ray technique targets terrorists and tumors
10. DNA methylation shown to promote development of colon tumors
11. Gene variation may elevate risk of liver tumor in patients with cirrhosis
Post Your Comments:
*Name:
*Comment:
*Email:
Related Image:
Tumor growth and chemo response may be predicted by mathematical model
(Date:4/11/2017)... 11, 2017 Research and Markets has announced ... report to their offering. ... global eye tracking market to grow at a CAGR of 30.37% ... Tracking Market 2017-2021, has been prepared based on an in-depth market ... landscape and its growth prospects over the coming years. The report ...
(Date:4/5/2017)... April 5, 2017  The Allen Institute for Cell ... Explorer: a one-of-a-kind portal and dynamic digital window into ... data, the first application of deep learning to create ... cell lines and a growing suite of powerful tools. ... these and future publicly available resources created and shared ...
(Date:4/3/2017)... , April 3, 2017  Data ... precision engineering platform, detected a statistically significant ... product prior to treatment and objective response ... the potential to predict whether cancer patients ... to treatment, as well as to improve ...
Breaking Biology News(10 mins):
(Date:10/10/2017)... , Oct. 10, 2017 SomaGenics announced the ... NIH to develop RealSeq®-SC (Single Cell), expected to be ... small RNAs (including microRNAs) from single cells using NGS ... the need to accelerate development of approaches to analyze ... "New techniques for measuring levels of mRNAs ...
(Date:10/9/2017)... ... , ... The award-winning American Farmer television series will feature 3 Bar Biologics ... at 8:30aET on RFD-TV. , With global population estimates nearing ten billion people ... to feed a growing nation. At the same time, many of our valuable resources ...
(Date:10/7/2017)... , ... October 06, 2017 ... ... experience providing advanced instruments and applications consulting for microscopy and surface analysis, ... in application consulting, Nanoscience Analytical offers a broad range of contract analysis ...
(Date:10/6/2017)... , ... October 06, 2017 , ... ... a lunch discussion and webinar on INSIGhT, the first-ever adaptive clinical trial for ... Dana-Farber Cancer Institute. The event is free and open to the public, but ...
Breaking Biology Technology: