Massachusetts General Hospital (MGH) research team have identified markers that can distinguish between major subtypes of lung cancer and can accurately isolate lung cancer stage. They engaged in a proof-of-concept study and accurately predicted whether the blood samples they studied originated from patients with shorter or lengthier survival after lung cancer surgery. The study included patients with early-stage disease. Thanks to this effort, an oncologist may have new tools to help them determine if a lung cancer patient should go through standard treatment or if they potentially could benefit from more aggressive therapy.
The U.S. Preventative Services Task Force recommends that middle-aged and older persons with a history of heavy smoking get screened once a year for lung cancer using low-dose CT. Low-dose CT is effective at detecting small lung tumors—however, It uses is limited due to costs and radiation risks reports MedicalXpress.
There is a need for a low cost, minimally invasive method for identifying people who may require more CT screening to catch the onset of cancer earlier at more easily treatable stages reports co-principal investigator Leo L. Cheng, Ph.D., an associate biophysicist, department of Pathology and Radiology, Massachusetts General Hospital. Cheng continued “You cannot use CT as a screening tool for every patient or even for every at-risk patient every year, so what we’re trying to do is develop biomarkers from blood samples that could be incorporated into physical exams, and there is any suspicious of lung cancer, then we would put the patient through CT” Cheng continued.
Lung Cancer Biomarker Study
The MGH investigative team studied paired blood samples and blood tissues extracted during surgery and reviewed and analyzed these samples for unique metabolomic markers using high-resolution magnetic resonance spectroscopy (MRS), a sophisticated method for characterizing tissue chemical composition. The MGH team’s study is unique in that they have paired samples from patients obtained at the same time as surgery.
The study is based on the sampling of 42 patients with squamous cell carcinoma (SCC) of the lung and 41 patient samples with adenocarcinomas of the lung. Additionally, blood samples from 29 healthy volunteers served as controls. In total patients included 58 with early (Stage I) lung cancer, and 35 with more advanced disease (Stage II-IV). Of particular focus was whether the blood and tumor tissue samples from the same patient had common features that would do the following:
- Identify the presence or absence of lung cancer
- Discriminate between cancer subtypes
- Confirm the diagnostic accuracy of a simple blood test
The investigators identified specific profiles of metabolites common to both types of samples and evidenced differences between the profiles could indicate whether the patient had SCC or adenocarcinoma—both of which require different treatments.
Interestingly, the derived profiles could help investigators determine what stage the patient was in—e.g. early-stage (highly treatable) vs. later stage (requires far more aggressive approaches).
Biomarkers May Determine How Dangerous the Cancer Stage
Of note, these tests were able to reveal to the investigators the samples that came from patients who lived an average of 41 months post-surgery or those patients who lived longer than 41 months. This finding needs to be validated in other studies—however if it is a powerful new diagnostic capability could enter the market as moving forward physicians could use biomarkers to identify those patients at high risk of early death and who may benefit from new investigational therapies in clinical trials, for example.
Ultimately the investigators sought to develop a biomarker test that is included as part of the standard physical exam. Such a biomarker test could ultimately save many more lives and of course, represent a valuable clinical biomarker.
Leo L. Cheng, Ph.D., associate biophysicist, department of Pathology and Radiology, MGH
David C. Christiani, MD, MPH, Department of Medicine, MGH