Extracellular matrix proteins as circulating biomarkers for the diagnosis of non-small cell lung cancer patients

Knowledge-Guided "Community Network" Analysis Reveals the Functional Modules and Candidate Targets in Non-Small-Cell Lung Cancer

Non-small-cell lung cancer (NSCLC) represents a heterogeneous group of malignancies that are the leading cause of cancer-related death worldwide. Although many NSCLC-related genes and pathways have been identified, there remains an urgent need to mechanistically understand how these genes and pathways drive NSCLC. Here, we propose a knowledge-guided and network-based integration method, called the node and edge Prioritization-based Community Analysis, to identify functional modules and their candidate targets in NSCLC. The protein–protein interaction network was prioritized by performing a random walk with restart algorithm based on NSCLC seed genes and the integrating edge weights, and then a “community network” was constructed by combining Girvan–Newman and Label Propagation algorithms. This systems biology analysis revealed that the CCNB1-mediated network in the largest community provides a modular biomarker, the second community serves as a drug regulatory module, and the two are connected by some contextual signaling motifs. Moreover, integrating structural information into the signaling network suggested novel protein–protein interactions with therapeutic significance, such as interactions between GNG11 and CXCR2, CXCL3, and PPBP. This study provides new mechanistic insights into the landscape of cellular functions in the context of modular networks and will help in developing therapeutic targets for NSCLC.

Upregulation of LAMB1 via ERK/c-Jun Axis Promotes Gastric Cancer Growth and Motility

Gastric cancer is the fifth most common cancer worldwide with a poor survival rate. Therefore, it is important to identify predictive and prognostic biomarkers of gastric cancer. Laminin subunit beta 1 (LAMB1) is involved in attachment, migration, and organization during development, and its elevated expression has been associated with several cancers. However, the role and mechanism of LAMB1 in gastric cancer remains unknown. Here, we determined that LAMB1 is upregulated in gastric cancer tissues and contributes to cell growth and motility. Using a public database, we showed that LAMB1 expression was significantly upregulated in gastric cancer compared to normal tissues. LAMB1 was also found to be associated with poor prognosis in patients with gastric cancer. Overexpression of LAMB1 elevated cell proliferation, invasion, and migration; however, knockdown of LAMB1 decreased these effects in gastric cancer cells. U0126, an extracellular signal-regulated kinase (ERK) inhibitor, regulated the expression of LAMB1 in gastric cancer cells. Additionally, we showed that c-Jun directly binds to the LAMB1 promoter as a transcription factor and regulates its gene expression via the ERK pathway in gastric cancer cells. Therefore, our study indicates that LAMB1 promotes cell growth and motility via the ERK/c-Jun axis and is a potential biomarker and therapeutic target of gastric cancer.

The Extracellular Matrix-Derived Biomarkers for Diagnosis, Prognosis, and Personalized Therapy of Malignant Tumors

The tumor biomarkers already have proven clinical value and have become an integral part in cancer management and modern translational oncology. The tumor tissue microenvironment (TME), which includes extracellular matrix (ECM), signaling molecules, immune and stromal cells, and adjacent non-tumorous tissue, contributes to cancer pathogenesis. Thus, TME-derived biomarkers have many clinical applications. This review is predominately based on the most recent publications (manuscripts published in a last 5 years, or seminal publications published earlier) and fills a gap in the current literature on the cancer biomarkers derived from the TME, with particular attention given to the ECM and products of its processing and degradation, ECM-associated extracellular vesicles (EVs), biomechanical characteristics of ECM, and ECM-derived biomarkers predicting response to the immunotherapy. We discuss the clinical utility of the TME-incorporating three-dimensional in vitro and ex vivo cell culture models for personalized therapy. We conclude that ECM is a critical driver of malignancies and ECM-derived biomarkers should be included in diagnostics and prognostics panels of markers in the clinic.

High plasma levels of COL10A1 are associated with advanced tumor stage in gastric cancer patients

BACKGROUND

Gastric cancer (GC) remains an aggressive malignancy with a high rate of mortality, being the third leading cause of cancer-related death. More than one million newly diagnosed cases and 782685 deaths due to GC were reported in 2018. GC is characterized by limited effective treatment options and the lack of consistent biomarkers for the diagnosis and prognosis of these patients. The discovery of new biomarkers useful in the early diagnosis of GC is mandatory.

AIM

To evaluate the potential of COL10A1 as a circulating biomarker for the diagnosis and prognosis of gastric adenocarcinoma patients.

METHODS

Plasma and tissue obtained from 49 patients with gastric adenocarcinoma have been used in exploring the expression of COL10A1. Real-time PCR and western blot techniques were used to evaluate COL10A1 level in gastric tumor tissue compared to normal adjacent tissue. The circulating level of COL10A1 was also evaluated by ELISA in plasma of gastric adenocarcinoma patients. Survival analysis was made in order to evaluate the potential of COL10A1 as a biomarker for the diagnosis and prognosis of gastric adenocarcinoma patients.

RESULTS

Our results showed a significant increase in COL10A1 gene expression and protein levels in gastric tumor tissue compared to adjacent normal tissue (P < 0.05). COL10A1 seems to show an elevated expression from the beginning of carcinogenesis, in the early stages, and its increased level remains elevated during cancer progression. A significant increase of COL10A1 plasma level in gastric adenocarcinoma patients was also identified. Moreover, increased COL10A1 plasma level was associated with poor survival of the patients. Plasma COL10A1 performed a diagnostic value in GC with area under the receiver operating characteristic curve (AUC) of 0.9171 (P = 0.0002), sensitivity of 87.76%, and specificity of 100.0%. Furthermore, this study demonstrated the potential role of plasma COL10A1 in the early detection of GC, as in the early stage, we obtained an AUC of 0.8789 (P = 0.0030), sensitivity of 81.25%, and specificity of 100.0%.

CONCLUSION

Circulating expression level of COL10A1 is significantly increased in gastric adenocarcinoma patients being associated with poor survival and is a potential biomarker for early detection of GC.

Matrix metalloproteinase family gene polymorphisms and lung cancer susceptibility: an updated meta-analysis

Background

Many studies have investigated the association between matrix metalloproteinase polymorphisms and lung cancer susceptibility. However, the results are still controversial. To clarify these associations, we conducted a meta-analysis.

Methods

A systematic search of studies was conducted in PubMed, Embase, and China National Knowledge Infrastructure. Overall and subgroup analysis stratified by ethnicity was conducted. OR with 95% CI was used to assess the strength of the association. Furthermore, false-positive report probability (FPRP) tests were also performed for associations obtained in this meta-analysis.

Results

Twenty-four studies, including 10,099 cases and 9,395 controls, were analyzed. Nine polymorphisms were reported. For MMP1 -1607 1G/2G and MMP7 -181 A/G, increased lung cancer risk was found in Asians. For MMP2 -1306 C/T and MMP2 -735 C/T, decreased lung cancer risk was found in both “diverse populations” and Asians. For MMP9 -1562, C/T decreased lung cancer risk was found in both “diverse populations” and Caucasians. For MMP13 -77A/G, the A/G genotype decreased lung cancer risk in Asians. However, only associations between MMP1 -1607 1G/2G, MMP2 -1306 C/T, MMP2 -735 C/T, and MMP7 -181 A/G and lung cancer risk were considered noteworthy according to FPRP tests. There was no association between MMP3 -1171 5A/6A, MMP9 R279Q, and MMP12 -82A/G and lung cancer risk.

Conclusions

Our meta-analysis suggested that MMP1 -1607 1G/2G and MMP7 -181 A/G were risk factors for lung cancer, while MMP2 -1306 C/T, MMP2 -735 C/T, MMP9 -1562 C/T, and MMP13 -77A/G might be protective factors. However, results for MMP9 -1562 C/T and MMP13 -77A/G should be interpreted with caution due to the probability of false-positive reports.