Lung cancer is a devastating disease that affects upwards of 200,000 individuals each year. According to the National Cancer Organization, 1 out of 15 men will develop lung cancer, and 1 out of 17 women will develop lung cancer.
While the term “lung cancer” seems to point to one type of cancer, it is an umbrella term encompassing a variety of different types of lung cancer. The two most common types of lung cancer are non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). Each is a category of their own that diverges into even more specific lung cancer types. With such a variety of lung cancers, comes a range of treatments. One treatment may work for a particular subtype of lung cancer, while another may not. Because of this, it is challenging to determine the prognosis of each patient with a lung cancer subtype.
A valuable tool for identifying cancer is the use of molecular biomarkers. Molecular biomarkers are any measurable characteristic, be it a protein, small molecular, genetic sequences of DNA, and many more.
In terms of lung cancer, there is an inconsistency of reliable biomarkers. Dr. Dhruva Biswas and a team of scientists, aim to streamline the process of finding a biomarker by lessening sampling bias and useless techniques studied previously. They needed to find a marker consistent in all lung cancers, but different enough to be able to classify the type of lung cancer it is.
Through a series of experiments and statistical analyses, they discovered an RNA marker (Q4) that was consistent in all lung cancer tumor samples. Interestingly, it had many variations between each tumor. This RNA marker could be used to determine which type of lung cancer is present. In a three year study, they found that Q4 genes significantly correlated with survival rates of patients.
From Q4, a “23 gene prognostic signature,” known as ORACLE, was discovered, meaning that the Q4 RNA Marker is associated with 23 genes consistent in each lung cancer. ORACLE was significantly associated with survival and mortality rates in patients with a specific type of stage 1 lung cancer. These results indicate that ORACLE “may serve as a molecular read-out for tumor aggressiveness and metazoic potential.” In further experiments, they found that Q4 genes, including ORACLE, are involved in cell division and gene regulation, both of which are central components of cancer that are put into overdrive.
With these results, we get closer to being able to determine precisely which type of lung cancer a patient has, what their prognosis is, and most importantly, what the most effective treatment will be.
To learn more about biomarkers, watch this video below:
Biswas, Dhruva, et al. “A Clonal Expression Biomarker Associates with Lung Cancer Mortality.” Nature Medicine, vol. 25, no. 10, 2019, pp. 1540–1548.