Early signs that lung cancer may spread and become untreatable can be seen in samples of a patient’s blood and tumour, new research has suggested.
A trio of studies indicate which patients could be safely treated with milder therapies, such as surgery alone, and which may need additional treatments including chemotherapy.
Scientists say the discoveries could help in the development of new ways to treat more aggressive forms of lung cancer.
The three studies are part of Cancer Research UK’s £14 million TRACERx project, which aims to understand how lung cancer cells change over time and become resistant to treatment.
About 47,000 people are diagnosed with lung cancer in the UK each year and fewer than one in five survives for five years or more.
Researchers believe a key reason why so few people survive lung cancer is that the tumour cells rapidly evolve, developing resistance to current treatments and evading the body’s immune system.
TRACERx involves more than 750 patients from 13 UK hospitals and looks at how lung cancer cells evolve and spread via the blood, as well as how the body’s immune system responds.
In the first of the new studies, published in Nature Medicine, Professor Caroline Dive, of the Cancer Research UK Manchester Institute, University of Manchester, and colleagues wanted to see if it would be possible to predict whose lung cancer would come back after treatment.
They took samples from 100 patients’ blood from veins running away from their affected lungs, just before surgery to remove lung tumours.
The team analysed the blood samples for cancer cells that had escaped from the tumour site and looked at the number and types of these cells.
Prof Dive said: “We monitored the patients for up to four years and found that those with the most tumour cells in their blood samples taken from the site of the tumour were also the ones most likely to suffer a recurrence.
“By looking at an individual patient who unfortunately had their cancer come back and spread ten months after surgery, we were able to identify the possible cause.
“We traced the origin of the secondary tumour to particular cells that were escaping into the blood from the primary tumour at the time of surgery.”
The second study was conducted by Dhruva Biswas, medical student and researcher studying for a MBPhD, with Professor Charles Swanton and colleagues from The Francis Crick Institute, London, and UCL Cancer Institute.
They studied lung tumour samples and found clues as to which cancers were more likely to return after treatment, independent of clinical measures such as size or stage.
Doctors already use single biopsies taken from tumours at the point of diagnosis to help select the best treatment plan for each patient.
But scientists say previous research has shown lung tumours are genetically unstable and evolve over time.
This means the populations of cancer cells within an individual tumour may differ in different parts and from biopsy to biopsy, limiting a doctor’s ability to provide patients with an accurate prognosis.
Mr Biswas said: “To get over this issue, we’ve developed a new technique called ORACLE.
“ORACLE uses our understanding of tumour evolution to look for stable genetic features that we can find throughout a tumour.
“This is paired with a machine learning algorithm to identify features that predict how aggressive a tumour is likely to be.
“These features could be spotted no matter which part of the tumour is sampled for testing, meaning they could be a more accurate guide for predicting the future clinical outcome for patients.”
Professor Benny Chain from UCL and his colleagues carried out the third study, focusing on lung cancer patients’ immune systems.
Looking at tumour biopsies, they found that cells of the immune system called T cells were gathered among the cancer cells.
They say this suggests that the patients’ immune systems were recognising and trying to fight the cancer.
They also analysed these cells to see what was unique about the ones able to recognise cancer.
Prof Chain said: “We now think that watching a patient’s T cells in action against lung cancer could give us clues as to how well a treatment is working for that individual patient.
“Our research also suggests the possibility that specific groups of T cells from patients could be isolated and adapted to help treat their tumour more effectively.”
