The multifaceted roles of matrix metalloproteinases in lung cancer

Multiplex plasma protein assays as a diagnostic tool for lung cancer

Lack of the established noninvasive diagnostic biomarkers causes delay in diagnosis of lung cancer (LC). The aim of this study was to explore the association between inflammatory and cancer-associated plasma proteins and LC and thereby discover potential biomarkers. Patients referred for suspected LC and later diagnosed with primary LC, other cancers, or no cancer (NC) were included in this study. Demographic information and plasma samples were collected, and diagnostic information was later retrieved from medical records. Relative quantification of 92 plasma proteins was carried out using the Olink Immuno-Onc-I panel. Association between expression levels of panel of proteins with different diagnoses was assessed using generalized linear model (GLM) with the binomial family and a logit-link function, considering confounder effects of age, gender, smoking, and pulmonary diseases. The analysis showed that the combination of five plasma proteins (CD83, GZMA, GZMB, CD8A, and MMP12) has higher diagnostic performance for primary LC in both early and advanced stages compared with NC. This panel demonstrated lower diagnostic performance for other cancer types. Moreover, inclusion of four proteins (GAL9, PDCD1, CD4, and HO1) to the aforementioned panel significantly increased the diagnostic performance for primary LC in advanced stage as well as for other cancers. Consequently, the collective expression profiles of select plasma proteins, especially when analyzed in conjunction, might have the potential to distinguish individuals with LC from NC. This suggests their utility as predictive biomarkers for identification of LC patients. The synergistic application of these proteins as biomarkers could pave the way for the development of diagnostic tools for early-stage LC detection.

Impacts of Matrix Metalloproteinase-9 Promoter Genotypes on Asthma Risk

BACKGROUND/AIM

The overexpression of matrix metalloproteinase-9 (MMP9) has been observed in asthmatic patients, yet the role of MMP9 genotype in determining asthma susceptibility remains unresolved. This study aimed to elucidate the contribution of MMP9 promoter rs3918242 genotype to asthma risk in Taiwan.

MATERIALS AND METHODS

A cohort comprising 453 non-asthmatic healthy controls and 198 asthmatic cases was assembled, and the MMP9 rs3918242 genotypes were determined using polymerase chain reaction-restriction fragment length polymorphism methodology.

RESULTS

Our findings indicated that people carrying the variant CT or TT genotype of MMP9 rs3918242 did not demonstrate an elevated risk of asthma compared to wild-type CC carriers (odds ratio=1.28 and 1.72, 95% confidence interval=0.87-1.87 and 0.72-4.13; p=0.2417 and 0.3201, respectively). Furthermore, individuals carrying the T allele at MMP9 rs3918242 did not exhibit a higher risk of asthma than those carrying the C allele (odds ratio=1.31, 95% confidence interval=0.96-1.79, p=0.0869). Interestingly, a positive association was observed between MMP9 rs3918242 CT or TT genotypes and the severity of asthma symptoms among asthmatic patients (p=0.0035).

CONCLUSION

Although the T allele at MMP9 rs3918242 was not associated with asthma risk, it may serve as a predictor for asthma symptom severity. These findings warrant validation in larger and more diverse populations to further elucidate the significance of MMP9 in asthma etiology.

Hydrogel-embedded precision-cut lung slices support ex vivo culture of in vivo -induced premalignant lung lesions

Lung cancer is the leading cause of global cancer death and prevention strategies are key to reducing mortality. Medical prevention may have a larger impact than treatment on mortality by targeting high-risk populations and reducing their lung cancer risk. Premalignant lesions (PMLs) that can be intercepted by prevention agents are difficult to study in humans but easily accessible in murine preclinical carcinogenesis studies. Precision-cut lung slices (PCLS) are underutilized as an ex vivo model for lung cancer studies due to limited culture time. Embedding PCLS within bioengineered hydrogels extends PCLS viability and functionality for up to six weeks. Here, we embedded PCLS generated from urethane-induced murine PMLs in cell-degradable and non-degradable hydrogels to study viability and activity of the tissues over six weeks. PMLs in hydrogel-embedded PCLS maintained viability, gene expression, and proliferation. Treatment of hydrogel-embedded PCLS containing urethane-induced PMLs with iloprost, a known lung cancer prevention agent, recapitulated in vivo gene expression and activity. These studies also showed that iloprost reduced proliferation and PML size in hydrogel-embedded PCLS, with some differences based on hydrogel formulation and suggested that hydrogel-embedded PCLS models may support long-term culture of in vivo generated PMLs to improve preclinical studies of lung cancer and prevention agents.

Integrative bioinformatics analysis reveals ECM and nicotine-related genes in both LUAD and LUSC, but different lung fibrosis-related genes are involved in LUAD and LUSC

There are several bioinformatics studies related to lung cancer, but most of them have mainly focused on either microarray data or RNA-Seq data alone. In this study, we have combined both types of data to identify differentially expressed genes (DEGs) specific to lung cancer subtypes. We obtained six microarray datasets from the GEO and also the expression matrix of LUSC and LUAD from TCGA, which were analyzed by GEO2R tool and GEPIA2, respectively. Enrichment analyses of DEGs were performed using the Enrichr database. Protein module identification was done by MCODE plugin in cytoscape software. We identified 30 LUAD-specific, 17 LUSC-specific, and 17 DEGs shared between LUAD and LUSC. Enrichment analyses revealed that LUSC-specific DEGs are involved in lung fibrosis. In addition, DEGs shared between LUAD and LUSC are involved in extracellular matrix (ECM), nicotine metabolism, and lung fibrosis. We identified lung fibrosis-related genes, including SPP1, MMP9, and CXCL2, involved in both LUAD and LUSC, but SERPINA1 and PLAU genes involved only in LUSC. We also found an important module separately for LUAD-specific, LUSC-specific, and shared DEGs between LUSC and LUAD. S100P, GOLM, AGR2, AK1, TMEM125, SLC2A1, COL1A1, and GHR genes were significantly associated with survival. Our findings suggest that different lung fibrosis-related genes may play roles in LUSC and LUAD. Additionally, nicotine metabolism and ECM remodeling were found to be associated with both LUSC and LUAD, regardless of subtype, emphasizing the role of smoking in the development of lung cancer and ECM in the high aggressiveness and mortality of lung cancer.