Friday, May 20 2022 | Updated at 12:17 PM EDT

Stay Connected With Us F T R

Jul 04, 2016 08:07 AM EDT

New York University Researchers Develop Cutting-Edge Methods To Map Cancer Progression!


A group of scientists has invented a computational method that can map cancer progression; a development that offer a brand-new insight into the elements that drive this disease and fresh ways of selecting productive therapies.

According to New York University Professor and study co-author Bud Mishra, the research centers on 'causality-like' connection between various genes and their mutations that pushes the cancer progression as the tumor environment responds to changes, including cell mobility, lack of oxygen or immune response.

With the help of the model, it can then forecast how tumor's genomes will alter over a period of time, Mishra added. Co-author Giulio Caravagna, who serves as a research associate at the Institute for Adaptive and Neural Computation of the University of Edinburgh noted that the team is recommending a bioinformatics protocol to identify common 'regularities' in tumors' cause and advancement, according to a post on New York University official website.

Caravagna believes this could be a giant step towards understanding an illness that is defined by just a few genomic lesions in different victims.

The researchers concentrated on colorectal cancer, taking into consideration most recent advancements in understanding of the disease.

The existing cancer pathway models were not enough to predict how tumor would spread to other parts of the body via metastasis, study co-author Mr. Mishra told Digital Trends.

In collaboration with his co-author, Mr. Caravagna, he said their model presents an intricate modeling system dubbed, Pipeline for Cancer Inference a.ka. the cheerful-sounding PiCnIc.

With the help of gene sequencing data, this modeling system forms predictions about the environment under which tumors grow.

These include immune response, cell mobility and oxygen (and its lack thereof) in the tumor environment. PiCnIc considers all these factors to predict how the tumor's genomes will eventually change. When tested against current data about the colorectal cancer growth, the model did exceptionally well.

Caravagna noted that the next stage of the work is to come up with techniques to tackle with drug resistance, immunotherapy, liquid biopsies and the like.

The study appears in the journal Proceedings of the National Academy of Sciences.

See Now: Facebook will use AI to detect users with suicidal thoughts and prevent suicide

© 2017 University Herald, All rights reserved. Do not reproduce without permission.

Join the Conversation

Get Our FREE Newsletters

Stay Connected With Us F T R

Real Time Analytics