Lung cancer has a high chance of relapse, so how do we get out of ahead of it?
Nancy Guo, SUNY Empire Innovation Professor in the school of computing at Binghamton University, discusses technology that helps us do so.
Nancy Guo is one of the newest additions to the Binghamton University School of Computing as a part of the SUNY Empire Innovation Program. With 62 peer reviewed publications amassing over 4,170 citations, her research on artificial intelligence and bioinformatics aims to develop and advance precision medicine.
The Search For Relapse Predictors In Lung Cancer Tumors
Bioinformatics is not a science of the distant future. Rather, it is a rapidly developing interdisciplinary field that allows us to analyze and interpret complex biological data.
This merging of technology with biology results in analysis tools crucial to treating diseases known for their unpredictability, such as lung cancer. My research focuses on using computer algorithms to find genes linked to lung cancer growth.
Lung cancer treatment comes with its own unique set of challenges. The first plan of treatment is typically surgery. However, this cancer has a high chance of relapse or metastasis, and subsequent chemotherapy is frequently unsuccessful. My research looks for recurring patterns in specific genes in order to predict early-stage patients who may develop tumors that will metastasize and may benefit from chemotherapy.
Using tumor samples collected from patients across several U.S. hospitals, we looked at tumors that were removed during surgery and started to identify genes that seemed to be linked to lung cancer growth.
When searching for genes involved in cancer relapse, the key is identifying the genetic networks that differ between patients who experience recurrence and those who remain relapse-free. Using bioinformatics, data can be uploaded into a computer algorithm that will look for patterns between genes that are expressed when a lung cancer tumor tends to metastasize.
If a link between the two is found, we can approach lung cancer from a preventative care aspect and determine if early-stage patients would benefit from chemotherapy before the disease is able to spread.
With our findings, we can assist patients who are unsure of the next step forward in their cancer treatment.
