Many treatments designed to treat lung cancer stop working over time. For years researchers have been trying to understand the reason for this event. Now, seven studies published in “Nature” and in “Nature Medicine” analyze how lung cancer evolves, how metastasis occurs and how it influences resistance to treatments.
In addition, the results of some of the articles include demonstrations of a tool that can detect evidence of circulating tumor DNA, liquid biopsy, a potential marker to monitor clinical outcomes, and the identification of factors that can predict which part of the tumor may be responsible for recurrence. “Understanding the genomic evolution of tumors may offer insight into the factors that determine how and when cancer can relapse and thus improve our understanding of tumor biology, which may facilitate future therapies to improve outcomes in patients.” cancer patients,” the researchers note.
The TRACERx study (TRAcking Cancer Evolution through therapy (Rx)) seeks to understand how different clones or cell populations within a tumor evolve against treatments.
On this occasion, more than 1,600 tumor samples taken from 421 patients with lung cancer have been analyzed to determine the evolution suffered by different cell clones of the tumors depending on the treatments and how they evolve as the disease progresses, the risk of recurrence or how progress to be metastatic.
The information, Alberto Jiménez Schuhmacher, ARAID researcher and head of the Molecular Oncology Group at the Institute for Health Research of Aragón (IIS Aragón), tells the Science Media Center “demonstrates that tumor progression is influenced by tumor heterogeneity and should help in near future and influence the most rational selection of treatments and the search for new therapies.
Lung cancer is the leading cause of cancer-related death worldwide, but a complete understanding of the biological mechanisms underlying this disease is still lacking to this day.
Tumors are made up of different types of cancer cells, each with different characteristics; this so-called intratumoral heterogeneity can drive tumor evolution and disease progression.
The aim of the TRACERx study is to determine the relationship between intratumoral heterogeneity and clinical outcomes, the study authors explain.
In the main article published in “Nature”, the team led by Charles Swanton, director of the Francis Crick Institute (United Kingdom) obtained samples from 1,644 tumor regions during surgery or follow-up of 421 patients with non-small cell lung cancer (NSCLC). ), the most common type of lung cancer. The cohort consisted of patients with stage I, II, or III disease who had a variety of NSCLC subtypes, including 248 lung adenocarcinomas.
Lung cancer is the leading cause of cancer-related death worldwide.
The authors identified differences in genome stability and patterns of intratumor heterogeneity that are associated with patient outcomes.
In another article, the authors investigated why tumors recur or spread to other parts of the body and the effects of platinum-based chemotherapy (a standard treatment for advanced NSCLC) on intratumor heterogeneity. It was shown that these treatments contribute to the evolution and heterogeneity of the tumor.
For Jiménez Schuhmacher, these are “fascinating and very robust” works. He highlights one of the studies that has established that a new technology based on liquid biopsy, which makes it possible to read the DNA of a tumor in a blood sample, could help establish the metastatic potential of these tumors. “This advance will be important to propose new therapeutic strategies and conduct clinical trials to find new therapies and approaches.”
This latest update of the TRACERx studies, write in a commentary Tikvah K. Hayes and Matthew Meyerson of the Dana–Farber Institute at Harvard University, Boston, raises questions about the role of genomics in the development of metastasis and the benefits of periodic evaluation of tumors. Therefore, they emphasize, future studies should “incorporate these strategies to better understand the complexities associated with a tumor and its microenvironment.”