Scientists from New York University Grossman School of Medicine, as part of a research team, found that lung cancer recurrence can be predicted by analyzing healthy tissue near the removed tumor. results published In the journal Nature.
The study by American scientists focuses on predicting the recurrence of lung adenocarcinoma, a disease in which tumors form in alveolar epithelial cells. In the United States, lung adenocarcinoma accounts for approximately one-third of all lung cancer cases. Most patients can return to normal life after surgical removal of tumors in the early stages of disease progression. However, the disease recurs in approximately 30% of cases.
During the study, scientists performed RNA sequencing of almost 300 tumor and healthy tissue samples from lung adenocarcinoma patients. This is the general name for methods that allow you to determine the nucleotide sequence in a DNA molecule. The resulting dataset, the transcriptome, contains information about the activity level of all genes in the cell. Monitoring the activity of specific genes helps identify pathological processes that accompany the growth of cancerous tumors.
It turned out that RNA sequencing of tissues located near a previously removed tumor allows predicting the recurrence of lung cancer with 83% accuracy. Scientists hope that the new technique will make diagnosing tumors that have started to grow again more effective. The research team plans to test this method to prospectively assess the risk of recurrence in patients treated for early-stage lung cancer.
Previous scientists listed oral cancer symptoms.