Lung Cancer Progression Predicted by Tumor Matrix

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

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

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

“Our focus was on how the matrix is changing in squamous cell lung carcinoma, how this might make tumors more aggressive, and how it could be used to help with understanding 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 think is supporting cancer cells to keep growing and spreading, contributing to the poor outcome for some patients. But we didn’t really have an understanding of what the matrix looks like or why it makes lung cancer resistant to treatment. If we can understand that part of the tumor, we can reveal more effective ways to treat patients by targeting the way the matrix is making the cancer more aggressive.”

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

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

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

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

“These two tumors look very similar under the microscope, and are typically treated the same way, but are very different on a molecular level,” said associate professor Thomas Cox, PhD, head of the Matrix and Metastasis lab at Garvan. “This sheds light on why some patients progress well and others don’t, and how we might be able to stratify patients to provide more personalized treatment.”

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

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