According to the World Health Organization, cancer is a leading
cause of death worldwide and accounted for nearly one in six deaths in 2020.
Cancer
is an uncontrolled growth of cells that can occur due to mutations in oncogenes
or tumor suppressor genes or both. However, not all mutations necessarily
result in cancer. Current cancer treatments are known to be detrimental to the
overall health of the patient. Knowledge of the genes responsible for the
initiation and progression of cancer in patients can help determine the
combination of drugs and therapy most suitable for a patient's recovery. The tool, described in a peer-reviewed journal Frontier in
Genetics, is based on a machine learning model that classifies genes as tumor
suppressor genes, oncogenes, or neutral genes.
According
to the researchers of the Indian Institute of Technology (IIT), Madras, an Artificial
Intelligence-based tool that can predict cancer-causing genes in an individual
has been developed, paving the way for devising personalized cancer treatment
strategies. According to researchers of IIT, Madras, it would be a great
tool to diagnose severe life-threatening diseases cancerin coming days.
The tool named 'PIVOT' is designed to predict cancer-causing
genes based on a model that utilizes information on mutations, expression of
genes, and copy number variation in genes and perturbations in the biological
network due to an altered gene expression. The tool, described in a
peer-reviewed journal Frontier in Genetics, is based on a machine learning
model that classifies genes as tumor suppressor genes, oncogenes, or neutral
genes.
Cancer, being a complex disease, cannot be dealt with in a
one-treatment-fits-all fashion. As cancer treatment increasingly shifts towards
personalized medicine, such models that build toward pinpointing differences
between patients can be very useful," said a Doctor, Core Member,
RBCDSAI, IIT Madras, in his statement.
The
new tool was able to successfully predict both the existing oncogenes and tumor-suppressor
genes like TP53, and PIK3CA, among others, and new cancer-related genes such as
PRKCA, SOX9, and PSMD4. The
researchers built AI prediction models for three different types of cancer
including breast invasive carcinoma, colon adenocarcinoma, and lung
adenocarcinoma." The
research area of precision medicine is still at a nascent stage.
PIVOT helps
push these boundaries and presents prospects for experimental research based on
the genes identified," informed by a Research Scholar, IIT
Madras. The team is planning to extend PIVOT further to
many more cancer types. The team is also working on a list of personalized
cancer-causing genes that can help in identifying the suitable drug for
patients based on their cancer profile.