Lung cancer progression predicted by tumor matrix

Squamous cell carcinoma (SqCC) is the second most prevalent type of lung cancer. However, treatment options for these patients remain limited and largely unchanged over decades. Now, a new study by researchers at the Garvan Institute of Medical Research has identified molecular profiles of the matrix surrounding squamous cell carcinoma that may indicate which patients are likely to develop aggressive tumors.

Their findings, “Extracellular matrix profiles determine risk and prognosis of squamous cell carcinoma subtype of non-small cell lung carcinoma,” were published in the journal BMC Genome Medicine🇧🇷

“SqCC is a subtype of non-small cell lung cancer for which the patient’s prognosis remains poor,” the researchers wrote. “The extracellular matrix (ECM) is critical in regulating cell behavior; however, its importance in tumor aggressiveness has yet to be comprehensively characterized.”

“Our focus was on how the matrix is ​​changing in squamous cell lung carcinoma, how this can make tumors more aggressive, and how it can be used to help understand patient prognosis,” explained Amelia Parker, PhD, first author of the study.

“Tumors are an ecosystem, made up of cancer cells held together by the matrix – it is this matrix that we believe is helping cancer cells to continue to grow and spread, contributing to the poor outcome of some patients. But we really didn’t have an understanding of what the matrix looks like or why it makes lung cancer resistant to treatment. If we can understand this part of the tumor, we can reveal more effective ways to treat patients by targeting how the matrix is ​​making the cancer more aggressive.”

The findings could be used to develop biomarkers to determine which patients might benefit from more aggressive and targeted treatment.

The researchers studied the molecular and protein composition of the matrix surrounding squamous cell carcinoma lung tumors, taken from patient tissue samples.

“This analysis revealed subtype-specific ECM signatures associated with tumor onset that were predictive of premalignant progression,” the researchers wrote. “We identified an ECM-enriched tumor subtype associated with worse prognosis. In silico analysis indicates that matrix remodeling programs differentially activate intracellular signaling in tumor and stromal cells to enhance matrix remodeling associated with resistance and progression. The matrix subtype with the worst prognosis resembles ECM remodeling in idiopathic pulmonary fibrosis and may represent a field of cancerization associated with an increased risk of cancer.”

The team also found that although adenocarcinomas and squamous cell carcinomas look similar in the clinic, they are quite different in their matrix composition. These differences have the potential to be taken advantage of by existing therapies developed to treat other diseases.

“These two tumors look very similar under the microscope and are usually treated in the same way, but they are very different on a molecular level,” said Associate Professor Thomas Cox, PhD, head of the Matrix and Metastasis laboratory at Garvan. “It sheds light on why some patients progress well and others don’t, and how we can stratify patients to provide more personalized care.”

Moving forward, researchers are looking to engage with clinical partners in a clinical trial to repurpose therapies that may prevent this matrix remodeling in lung cancer patients and improve response to therapy.

Lung cancer progression predicted by tumor matrix

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