A study published in GenomeMedicine reports a comprehensive analysis of the squamous cell carcinoma matrisomal landscape and the key components associated with an increased risk of lung cancer.
The extracellular matrix is significantly dysregulated in tumor compared with non-tumor tissue in SqCC.Figure S3.
A) tSNE plot visualization of the expression scores for matrix risk signature genes with positive and negative odds ratios for different cell types in SqCC scRNAseq data presented in Fig.D. D) ROC analysis of the minimum matrix risk signature distinguishing progressive from regressive premalignant lesions. E) Matrix risk score at age at diagnosis in the TCGA cohort. Blue line shows linear regression with standard error indicated by grey shading. p=0.00073, r=-0.23, Spearman’s correlation.
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Extracellular matrix profiles determine risk and prognosis of the squamous cell carcinoma subtype of non-small cell lung carcinoma - Genome MedicineBackground Squamous cell carcinoma (SqCC) is a subtype of non-small cell lung cancer for which patient prognosis remains poor. The extracellular matrix (ECM) is critical in regulating cell behavior; however, its importance in tumor aggressiveness remains to be comprehensively characterized. Methods Multi-omics data of SqCC human tumor specimens was combined to characterize ECM features associated with initiation and recurrence. Penalized logistic regression was used to define a matrix risk signature for SqCC tumors and its performance across a panel of tumor types and in SqCC premalignant lesions was evaluated. Consensus clustering was used to define prognostic matreotypes for SqCC tumors. Matreotype-specific tumor biology was defined by integration of bulk RNAseq with scRNAseq data, cell type deconvolution, analysis of ligand-receptor interactions and enriched biological pathways, and through cross comparison of matreotype expression profiles with aging and idiopathic pulmonary fibrosis lung profiles. Results This analysis revealed subtype-specific ECM signatures associated with tumor initiation that were predictive of premalignant progression. 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. Conclusions Collectively, this analysis defines matrix-driven features of poor prognosis to inform precision medicine prevention and treatment strategies towards improving SqCC patient outcome.
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