Submitted by itadmin on
Colorectal cancer is one of the most common types of cancer. While more predominant in older patients, with an average age of presentation of 70-71 years, it is still considered the cancer with the second-highest incidence in western countries. In male patients, only lung cancer is more prevalent, while in women, the most common is breast cancer.
Despite advancements in diagnoses and new therapies that have made it possible to reach a five-year survival rate in 64% of cases in Spain (higher than the European average of 57%), much remains to be done. According to data from the American Cancer Society, this type of tumor will cause nearly 50,000 deaths in the United States throughout 2016. Research carried out from technological cores is contributing to new resources in the fight against colorectal cancer, as shown by the first molecular consensus to classify the different types of tumors based on genomic information.
Figure 1.- Blausen Medical Communications Inc. (Wikimedia)
Big data and DNA sequencing are not the only tools that will allow progress to be made against colorectal cancer. Computation, which has already proved its worth in the study of multiple myeloma, or reduction of the number of animals used in experiments, is opening new doors to treat this type of tumor. To wit, a team of researchers has developed a new computational method to assess the progression of colorectal cancer. Their results, published in Proceedings of the National Academy of Sciences, propose a bioinformatic protocol to detect irregularities common in the origin and development of the tumor. Scientists from the University of Barcelona (UB), the Bellvitge Biomedical Research Institute (IDIBELL) and the Catalan Institute of Oncology (ICO) have taken part in the study.
This way, it will be possible to track a disease characterized by presentation of a very low number of common genomic alterations in different patients, with the aim of following the tumor’s evolution over time and determining whether the genome of the cancer cells changes. Since the arrival of massive sequencing techniques and tools such as the liquid biopsy, the conception of cancer progression has changed completely. Now it is known that tumors are more heterogeneous at the cellular level, in such a way that the interactions among malignant cells can explain the progression of the different tumors. In the work published in PNAS, researchers presented an algorithm nicknamed Pipeline for Cancer Inference, or PiCnIc, which uses genomic data to generate a “cellular image” of colorectal cancer progression.
The PiCnIc modeling system analyzes the roles played by the so-called driver mutations that explain a tumor’s evolution. Furthermore, the algorithm considers other phenomena like the alterations in the number of copies (deletions or amplifications), the influence of these genetic error cascades and the impact on other driver factors. “This methodology is innovative because it features a probabilistic model that infers the order of the events (mutations and alterations in the number of copies),” states Dr. Victor Moreno, professor at the Faculty of Medicine and Health Sciences at the University of Barcelona.
Figure 2.- University of Barcelona
Last, to determine whether the algorithm was useful, researchers have compared the knowledge now available on the dynamics of colorectal cancer growth with the predictions made by the bioinformatic protocol. By doing so, they were able to demonstrate that PiCnIc is an effective tool to apply scientific evidence available in the study of the evolution and progression of this type of tumor. Once again, technological cores and especially, the systems derived from modeling and computation have been found to be applicable to the study of cancer. The pipeline developed and disseminated in PNAS has been published openly to, in the words of the researchers, test its reproducibility and interoperability, and enable future improvements.