SPARC expression in gastric cancer predicts poor prognosis: Results from a clinical cohort, pooled analysis and GSEA assay

Cancer-Associated Fibroblasts Genes and Transforming Growth Factor Beta Pathway in Gastric Cancer for Novel Therapeutic Strategy

Background-Objective: Cancer-associated fibroblasts (CAFs) play a crucial role in the tumor microenvironment of gastric cancer (GC). Understanding the molecular characteristics of CAFs-associated genes (CAFGs) is essential for elucidating their role in tumor progression and prognosis. This review aims to summarize the current knowledge on CAFGs, highlighting their expression patterns, prognostic significance, and potential functional mechanisms. Methods: A comprehensive review of existing literature was conducted, focusing on molecular features of CAFGs in GC. Single-cell RNA sequencing (scRNA-seq) analyses were examined to assess the expression patterns of CAFGs in broad-sense CAFs, which include both CAFs and pericytes. Additionally, clinicopathological studies validating the prognostic significance of CAFGs were reviewed. Results: ScRNA-seq analyses revealed that CAFGs are not necessarily restricted to CAFs alone but may also reflect the activation status of surrounding cells. Several CAFGs, including SPARC, THBS2, COL1A1, COL3A1, INHBA, PDGFC, and SDC2, have been validated for their prognostic relevance in GC. However, compared with other cancers, the functional mechanisms of these genes in GC remain poorly understood. While CAFGs exhibit synchronized expression with TGFB1 in colorectal cancer (CRC), such patterns have yet to be confirmed in GC due to the limitations of available microdissected data. Conclusions: A comprehensive understanding of CAFGs and their interaction with the TGFB pathway, including LTBP family genes, may be critical for developing novel therapeutic strategies for GC. Further research is needed to elucidate their functional mechanisms and therapeutic potential.

Method for the extraction of circulating nucleic acids based on MOF reveals cell-free RNA signatures in liver cancer

Cell-free RNA (cfRNA) allows assessment of health, status, and phenotype of a variety of human organs and is a potential biomarker to non-invasively diagnose numerous diseases. Nevertheless, there is a lack of highly efficient and bias-free cfRNA isolation technologies due to the low abundance and instability of cfRNA. Here, we developed a reproducible and high-efficiency isolation technology for different types of cell-free nucleic acids (containing cfRNA and viral RNA) in serum/plasma based on the inclusion of nucleic acids by metal-organic framework (MOF) materials, which greatly improved the isolation efficiency and was able to preserve RNA integrity compared with the most widely used research kit method. Importantly, the quality of cfRNA extracted by the MOF method is about 10-fold that of the kit method, and the MOF method isolates more than three times as many different RNA types as the kit method. The whole transcriptome mapping characteristics of cfRNA in serum from patients with liver cancer was described and a cfRNA signature with six cfRNAs was identified to diagnose liver cancer with high diagnostic efficiency (area under curve = 0.905 in the independent validation cohort) using this MOF method. Thus, this new MOF isolation technique will advance the field of liquid biopsy, with the potential to diagnose liver cancer.

SPARC: a potential target for functional nanomaterials and drugs

Secreted protein acidic and rich in cysteine (SPARC), also termed osteonectin or BM-40, is a matricellular protein which regulates cell adhesion, extracellular matrix production, growth factor activity, and cell cycle. Although SPARC does not perform a structural function, it, however, modulates interactions between cells and the surrounding extracellular matrix due to its anti-proliferative and anti-adhesion properties. The overexpression of SPARC at sites, including injury, regeneration, obesity, cancer, and inflammation, reveals its application as a prospective target and therapeutic indicator in the treatment and assessment of disease. This article comprehensively summarizes the mechanism of SPARC overexpression in inflammation and tumors as well as the latest research progress of functional nanomaterials in the therapy of rheumatoid arthritis and tumors by manipulating SPARC as a new target. This article provides ideas for using functional nanomaterials to treat inflammatory diseases through the SPARC target. The purpose of this article is to provide a reference for ongoing disease research based on SPARC-targeted therapy.

Identification of Potential Diagnostic and Prognostic Biomarkers for Gastric Cancer Based on Bioinformatic Analysis

Background: Gastric cancer (GC) is one of the most prevalent cancers all over the world. The molecular mechanisms of GC remain unclear and not well understood. GC cases are majorly diagnosed at the late stage, resulting in a poor prognosis. Advances in molecular biology techniques allow us to get a better understanding of precise molecular mechanisms and enable us to identify the key genes in the carcinogenesis and progression of GC.

Methods: The present study used datasets from the GEO database to screen differentially expressed genes (DEGs) between GC and normal gastric tissues. GO and KEGG enrichments were utilized to analyze the function of DEGs. The STRING database and Cytoscape software were applied to generate protein–protein network and find hub genes. The expression levels of hub genes were evaluated using data from the TCGA database. Survival analysis was conducted to evaluate the prognostic value of hub genes. The GEPIA database was involved to correlate key gene expressions with the pathological stage. Also, ROC curves were constructed to assess the diagnostic value of key genes.

Results: A total of 607 DEGs were identified using three GEO datasets. GO analysis showed that the DEGs were mainly enriched in extracellular structure and matrix organization, collagen fibril organization, extracellular matrix (ECM), and integrin binding. KEGG enrichment was mainly enriched in protein digestion and absorption, ECM-receptor interaction, and focal adhesion. Fifteen genes were identified as hub genes, one of which was excluded for no significant expression between tumor and normal tissues. COL1A1, COL5A2, P4HA3, and SPARC showed high values in prognosis and diagnosis of GC.

Conclusion: We suggest COL1A1, COL5A2, P4HA3, and SPARC as biomarkers for the diagnosis and prognosis of GC.

Characterization of the Cellular Microenvironment and Novel Specific Biomarkers in Pterygia Using RNA Sequencing

With a worldwide prevalence of ~12%, pterygium is a common degenerative and environmentally triggered ocular surface disorder characterized by wing-shaped growth of conjunctival tissue onto the cornea that can lead to blindness if left untreated. This study characterizes the transcriptional profile and the cellular microenvironment of conjunctival pterygia and identifies novel pterygia-specific biomarkers. Formalin-fixed and paraffin-embedded pterygia as well as healthy conjunctival specimens were analyzed using MACE RNA sequencing (n = 8 each) and immunohistochemistry (pterygia n = 7, control n = 3). According to the bioinformatic cell type enrichment analysis using xCell, the cellular microenvironment of pterygia was characterized by an enrichment of myofibroblasts, T-lymphocytes and various antigen-presenting cells, including dendritic cells and macrophages. Differentially expressed genes that were increased in pterygia compared to control tissue were mainly involved in autophagy (including DCN, TMBIM6), cellular response to stress (including TPT1, DDX5) as well as fibroblast proliferation and epithelial to mesenchymal transition (including CTNNB1, TGFBR1, and FN1). Immunohistochemical analysis confirmed a significantly increased FN1 stromal immunoreactivity in pterygia when compared to control tissue. In addition, a variety of factors involved in apoptosis were significantly downregulated in pterygia, including LCN2, CTSD, and NISCH. Furthermore, 450 pterygia-specific biomarkers were identified by including transcriptional data of different ocular surface pathologies serving as controls (training group), which were then validated using transcriptional data of cultured human pterygium cells. Among the most pterygia-specific factors were transcripts such as AHNAK, RTN4, TPT1, FSTL1, and SPARC. Immunohistochemical validation of SPARC revealed a significantly increased stromal immunoreactivity in pterygia when compared to controls, most notably in vessels and intravascular vessel wall-adherent mononuclear cells. Taken together, the present study provides new insights into the cellular microenvironment and the transcriptional profile of pterygia, identifies new and specific biomarkers and in addition to fibrosis-related genes, uncovers autophagy, stress response and apoptosis modulation as pterygium-associated processes. These findings expand our understanding of the pathophysiology of pterygia, provide new diagnostic tools, and may enable new targeted therapeutic options for this common and sight-threatening ocular surface disease.

Identifying Diagnostic and Prognostic Biomarkers and Candidate Therapeutic Drugs of Gastric Cancer Based on Transcriptomics and Single-Cell Sequencing

Background and Objective: Gastric cancer (GC) is an important health burden and the prognosis of GC is poor. We aimed to explore new diagnostic and prognostic indicators as well as potential therapeutic targets for GC in the current study.

Methods: We screened the overlapped differentially expressed genes (DEGs) from GSE54129 and TCGA STAD datasets. Protein-protein interaction network analysis recognized the hub genes among the DEGs. The roles of these genes in diagnosis, prognosis, and their relationship with immune infiltrates and drug sensitivity of GC were analyzed using R studio. Finally, the clinically significant hub genes were verified using single-cell RNA sequencing (scRNA-seq) data.

Results: A total of 222 overlapping genes were screened, which were enriched in extracellular matrix-related pathways. Further, 17 hub genes were identified, and our findings demonstrated that BGN, COMP, COL5A2, and SPARC might be important diagnostic and prognostic indicators of GC, which were also correlated with immune cell infiltration, tumor mutation burden (TMB), microsatellite instability (MSI), and sensitivity of therapeutic drugs. The scRNA-seq results further confirmed that all four hub genes were highly expressed in GC.

Conclusion: Based on transcriptomics and single-cell sequencing, we identified four diagnostic and prognostic biomarkers of GC, including BGN, COMP, COL5A2, and SPARC, which can help predict drug sensitivity for GC as well.

Proteomic Signatures of Diffuse and Intestinal Subtypes of Gastric Cancer

Gastric cancer is a leading cause of death from cancer globally. Gastric cancer is classified into intestinal, diffuse and indeterminate subtypes based on histology according to the Laurén classification. The intestinal and diffuse subtypes, although different in histology, demographics and outcomes, are still treated in the same fashion. This study was designed to discover proteomic signatures of diffuse and intestinal subtypes. Mass spectrometry-based proteomics using tandem mass tags (TMT)-based multiplexed analysis was used to identify proteins in tumor tissues from patients with diffuse or intestinal gastric cancer with adjacent normal tissue control. A total of 7448 or 4846 proteins were identified from intestinal or diffuse subtype, respectively. This quantitative mass spectrometric analysis defined a proteomic signature of differential expression across the two subtypes, which included gremlin1 (GREM1), bcl-2-associated athanogene 2 (BAG2), olfactomedin 4 (OLFM4), thyroid hormone receptor interacting protein 6 (TRIP6) and melanoma-associated antigen 9 (MAGE-A9) proteins. Although GREM1, BAG2, OLFM4, TRIP6 and MAGE-A9 have all been previously implicated in tumor progression and metastasis, they have not been linked to intestinal or diffuse subtypes of gastric cancer. Using immunohistochemical labelling of a tissue microarray comprising of 124 cases of gastric cancer, we validated the proteomic signature obtained by mass spectrometry in the discovery cohort. Our findings should help investigate the pathogenesis of these gastric cancer subtypes and potentially lead to strategies for early diagnosis and treatment.

Unsupervised Hierarchical Clustering Identifies Immune Gene Subtypes in Gastric Cancer

Objectives: The pathogenesis of heterogeneity in gastric cancer (GC) is not clear and presents as a significant obstacle in providing effective drug treatment. We aimed to identify subtypes of GC and explore the underlying pathogenesis. Methods: We collected two microarray datasets from GEO (GSE84433 and GSE84426), performed an unsupervised cluster analysis based on gene expression patterns, and identified related immune and stromal cells. Then, we explored the possible molecular mechanisms of each subtype by functional enrichment analysis and identified related hub genes. Results: First, we identified three clusters of GC by unsupervised hierarchical clustering, with average silhouette width of 0.96, and also identified their related representative genes and immune cells. We validated our findings using dataset GSE84426. Subtypes associated with the highest mortality (subtype 2 in the training group and subtype C in the validation group) showed high expression of SPARC, COL3A1, and CCN. Both subtypes also showed high infiltration of fibroblasts, endothelial cells, hematopoietic stem cells, and a high stromal score. Furthermore, subtypes with the best prognosis (subtype 3 in the training group and subtype A in the validation group) showed high expression of FGL2, DLGAP1-AS5, and so on. Both subtypes also showed high infiltration of CD4+ T cells, CD8+ T cells, NK cells, pDC, macrophages, and CD4+ T effector memory cells. Conclusion: We found that GC can be classified into three subtypes based on gene expression patterns and cell composition. Findings of this study help us better understand the tumor microenvironment and immune milieu associated with heterogeneity in GC and provide practical information to guide personalized treatment.

LAMB1 Is Related to the T Stage and Indicates Poor Prognosis in Gastric Cancer

BACKGROUND AND OBJECTIVE

Gastric cancer (GC) is a common tumor malignancy with high incidence and poor prognosis. Laminin is an indispensable component of basement membrane and extracellular matrix, which is responsible for bridging the internal and external environment of cells and transmitting signals. This study mainly explored the association of the LAMB1 expression with clinicopathological characteristics and prognosis in gastric cancer.

METHODS

The expression data and clinical information of gastric cancer patients were downloaded from The Cancer Genome Atlas (TCGA) and Asian Cancer Research Group (ACRG). And we analyzed the relationship between LAMB1 expression and clinical characteristics through R. CIBERSORTx was used to calculate the absolute score of immune cells in gastric tumor tissues. Then COX proportional hazard models and Kaplan-Meier curves were performed to evaluate the role of LAMB1 and its influence on prognosis in gastric cancer patients. Finally, GO and KEGG analysis were applied for LAMB1-related genes in gastric cancer, and PPI network was constructed in Cytoscape software.

RESULTS

In the TCGA cohort, patients with gastric cancer frequently generated LAMB1 gene copy number variation, but had little effect on mRNA expression. Both in the TCGA and ACRG cohorts, the mRNA expression of LAMB1 in gastric cancer tissues was higher than it in normal tissues. All patients were divided into high expression group and low expression group according to the median expression level of LAMB1. The elevated expression group obviously had more advanced cases and higher infiltration levels of M2 macrophages. COX proportional hazard models and Kaplan-Meier curves revealed that patients with enhanced expression of LAMB1 have a worse prognosis. GO/KEGG analysis showed that LAMB1-related genes were enriched in PI3K-Akt signaling pathway, focal adhesion, ECM-receptor interaction, etc.

CONCLUSIONS

The high expression of LAMB1 in gastric cancer is related to the poor prognosis of patients, and it may be related to microenvironmental changes in tumors.

Genome-Scale Analysis Identified NID2, SPARC, and MFAP2 as Prognosis Markers of Overall Survival in Gastric Cancer

BACKGROUND Gastric cancer is the most common gastrointestinal tumor, and the rates of recurrence and metastasis are high. Research results on molecular biomarkers used for prognosis of gastric cancer remain inconclusive. This study aimed to explore the gene expression module of gastric cancer and to determine potential prognostic biomarkers. MATERIAL AND METHODS Three microarray datasets (GSE13911, GSE79973, and GSE29272) from Gene Expression Omnibus (GEO), including 206 pairs of gastric tumors and adjacent normal samples, were used for analysis of differentially expressed genes (DEGs). The 3 microarray datasets yielded 144 genes associated with the progression and prognosis of gastric cancer. After this, a risk score model was developed for result validation using an independent dataset from The Cancer Genome Atlas. RESULTS The validation of the independent dataset showed significantly increased NID2, SPARC, and MFAP2 expression in gastric tumor tissues, which were associated with poor outcomes in gastric cancer patients. Moreover, the high risk score obtained was associated with poor overall survival (HR: 1.787; 1.069-2.986; P=0.027). Subgroup analyses revealed that these significant prognostic values were detected in patients aged <65.0 years, tumors in the antrum/distal colon, grade 3 tumors, or TNM-M0 stages of cancer. CONCLUSIONS The findings of this study show that NID2, SPARC, and MFAP2 are upregulated in gastric tumor tissues and are significantly associated with poor overall survival. Therefore, the predictive values of the risk score model employed for the prognosis of gastric cancer could be improved by using these 3 upregulated DEGs.

The cancer cell secretome drives cooperative manipulation of the tumour microenvironment to accelerate tumourigenesis

Cellular secretions are a fundamental aspect of cell-cell and cell-matrix interactions in vivo. In malignancy, cancer cells have an aberrant secretome compared to their non-malignant counterparts, termed the "cancer cell secretome". The cancer cell secretome can influence every stage of the tumourigenic cascade. At the primary site, cancer cells can secrete a multitude of factors that facilitate invasion into surrounding tissue, allowing interaction with the local tumour microenvironment (TME), driving tumour development and progression. In more advanced disease, the cancer cell secretome can be involved in extravasation and metastasis, including metastatic organotropism, pre-metastatic niche (PMN) preparation, and metastatic outgrowth. In this review, we will explore the latest advances in the field of cancer cell secretions, including its dynamic and complex role in activating the TME and potentiating invasion and metastasis, with comments on how these secretions may also promote therapy resistance.

Could microtubule inhibitors be the best choice of therapy in gastric cancer with high immune activity: mutant DYNC1H1 as a biomarker

Immune checkpoint blockade (ICB) has achieved unprecedented breakthroughs in various cancers, including gastric cancer (GC) with high immune activity (MSI-H or TMB-H), yet clinical benefits from ICB were moderate. Here we aimed to identify the most appropriate drugs which can improve outcomes in GC. We firstly compared MSI-H and TMB-H GC samples with normal samples in TCGA-STAD cohort, respectively. After that, Connectivity Map database repurposed nine candidate drugs (CMap score < -90). Then, microtubule inhibitors (MTIs) were screened as the significant candidate drugs with their representative gene sets strongly enriched (p < 0.05) via GSEA. GDSC database validated higher activities of some MTIs in GC cells with MSI-H and TMB-H (p < 0.05). Furthermore, some MTIs activities were positively associated with mutant Dynein Cytoplasmic 1 Heavy Chain 1 (DYNC1H1) (p < 0.05) based on NCI-60 cancer cell line panel. DYNC1H1 was high frequently alteration in GC and was positively associated with TMB-H and MSI-H. Mutant DYNC1H1 may be accompanied with down-regulation of MTIs-related genes in GC or change the binding pocket to sensitize MTIs. Overall, this study suggested that some MTIs may be the best candidate drugs to treat GC with high immune activity, especially patients with DYNC1H1 mutated.

Accumulation of stabilin-1 positive macrophages in the early stage of gastric cancer is associated with short cumulative survival

The scavenger receptor stabilin-1 has been reported to be expressed by tumor-associated macrophages (TAMs) and to facilitate tumor growth and metastasis in mouse models of breast carcinoma and melanoma. However, to the best of our knowledge, its expression and association with prognosis in human gastric cancer has not been evaluated. The present study investigated the expression of stabilin-1 and its association with clinicopathological parameters in patients with gastric cancer. The expression of stabilin-1 was evaluated by immunohistochemical staining of gastric cancer tissue samples of 371 Chinese patients with primary gastric adenocarcinoma. Confocal laser scanning microscopy was used to determine the cellular source of stabilin-1 in the gastric cancer tissues using anti-CD68, anti-CD163, anti-stabilin-1 and anti-secreted protein acidic and rich in cysteine antibodies. A higher number of stabilin-1-positive cells were observed in the cancer tissues of primary gastric adenocarcinoma compared with adjacent non-cancerous tissues of primary gastric adenocarcinoma (P<0.001); the majority of stabilin-1-positve cells were CD68⁺/CD163⁺ macrophages. Poorly-differentiated gastric cancer tissue had fewer stabilin-1-positive cells compared with medium- and well-differentiated gastric cancer (P=0.030). A higher number of stabilin-1-positive cells were found in the early Tumor-Node-Metastasis (TNM) stage (TNM I stage) of primary gastric adenocarcinoma (P=0.038) compared with TNM stage IV. For patients with TNM stage I disease, a higher number of stabilin-1-positive TAMs was associated with shorter cumulative survival (P<0.05). Overall, stabilin-1 was found to be expressed by CD68⁺ TAMs in human gastric cancer. The high expression of stabilin-1 in TNM stage I disease was associated with poor patient survival, indicating the clinical significance of stabilin-1 in gastric cancer.

Global transcriptomic analysis identifies SERPINE1 as a prognostic biomarker associated with epithelial-to-mesenchymal transition in gastric cancer

Background

The plasminogen activation system plays a pivotal role in regulating tumorigenesis. In this work, we aim to identify key regulators of plasminogen activation associated with tumorigenesis and explore potential mechanisms in gastric cancer (GC).

Methods

Gene profiling datasets were extracted from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were screened for and obtained by the GEO2R tool. The Database for Annotation, Visualization and Integrated Discovery was used for GO and KEGG enrichment analysis. Gene set enrichment analysis (GSEA) was performed to verify molecular signatures and pathways among The Cancer Genome Atlas or GEO datasets. Correlations between SERPINE1 and markers of epithelial-to-mesenchymal transition (EMT) were analyzed using the GEPIA database and quantitative real-time PCR (qRT-PCR). Interactive networks of selected genes were built by STRING and Cytoscape software. Finally, selected genes were verified with the Kaplan–Meier (KM) plotter database.

Results

A total of 104 overlapped upregulated and 61 downregulated DEGs were obtained. Multiple GO and KEGG terms associated with the extracellular matrix were enriched among the DEGs. SERPINE1 was identified as the only regulator of angiogenesis and the plasminogen activator system among the DEGs. A high level of SERPINE1 was associated with a poor prognosis in GC. GSEA analysis showed a strong correlation between SERPINE1 and EMT, which was also confirmed with the GEPIA database and qRT-PCR validation. FN1, TIMP1, MMP2, and SPARC were correlated with SERPINE1.The KM plotter database showed that an overexpression of these genes correlated with a shorter survival time in GC patients.

Conclusions

In conclusion, SERPINE1 is a potent biomarker associated with EMT and a poor prognosis in GC. Furthermore, FN1, TIMP1, MMP2, and SPARC are correlated with SERPINE1 and may serve as therapeutic targets in reversing EMT in GC.

Elevated limb-bud and heart development (LBH) expression indicates poor prognosis and promotes gastric cancer cell proliferation and invasion via upregulating Integrin/FAK/Akt pathway

The limb-bud and heart development (LBH) gene is a highly conserved, tissue-specific transcription cofactor in vertebrates that regulates multiple key genes in embryonic development. The role of LBH in various cancer types is still controversial, and its specific role and molecular mechanism in the oncogenesis of gastric cancer (GC) remains largely unexplored. In the present study, the prognostic significance and clinicopathological characteristics of LBH in GC was determined. The LBH mRNA expression was first investigated in four independent public datasets (TCGA-STAD, GSE15459, GSE29272, and GSE62254) and then validated with our samples at the protein level. LBH was overexpressed at both the mRNA and protein levels in cancer compared with normal tissues. High LBH expression was correlated with advanced T, N, and M stages. Kaplan–Meier analysis and log-rank test indicated that higher LBH expression was statistically correlated with shorter overall survival (OS) in the public datasets and our study samples. Univariate and multivariate Cox regression analysis showed that LBH was an independent prognostic biomarker for survival in TCGA-STAD, GSE15459, GSE62254 cohorts, and our GC patients. In vitro experiments showed that knockdown of LBH can significantly inhibit the proliferation and invasion of HGC-27 cells, while overexpression of LBH can significantly enhance the proliferation and invasion of BGC-823 cells. Gene Set Enrichment Analysis (GSEA), Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomics (KEGG) indicated that high LBH expression is associated with the PI3K-Akt pathway, focal adhesion, and extracellular matrix (ECM)-receptor interaction. Western blot analysis showed that knockdown of LBH significantly inhibited the expression of integrin α5, integrin β1, p-FAK, and p-Akt. Therefore, results from the present study indicate that LBH is a potential independent prognostic biomarker and promotes proliferation and invasion of GC cells by activating the integrin/FAK/Akt pathway.

Increased expression of TMED2 is an unfavorable prognostic factor in patients with breast cancer

Background: We obtained 2 types of clones which were termed SC (sphere-shaped clone) and NSC (non-sphere-shaped clone) from 4T1 cells by monoclonal culture. SC and NSC were distinct in morphology, surface marker, metabolism and proliferation rate. With the transcriptome sequencing data analysis, we found TMED2 expressed higher in SCs. TMED2 was a member of the transmembrane emp24 domain and might play roles in cancer cell proliferation. However, its prognostic roles in breast cancer remained unknown. We aimed to investigate the prognostic values of TMED2 in patients with breast cancer.

Methods: We used UALCAN (http://ualcan.path.uab.edu) and the Human Protein Atlas (www.proteinatlas.org) to explore the TMED2 expression level and DNA methylation data between breast cancer and normal breast tissue. With Oncomine (www.oncomine.org), we investigated the copy number of TMED2 in breast cancer sample and normal breast tissue. We used the Kaplan–Meier Plotter database (http://kmplot.com/analysis) to analyze prognostic values of TMED2 mRNA expression in all breast cancers and in different intrinsic subtypes. Moreover, protein expression levels of TMED2 were confirmed by Western blot in breast cancer tissues and normal mammary tissue as well as SCs and NSCs.

Results: TMED2 significantly upregulated in breast cancer patients compared to normal mammary samples. Meanwhile, the increased expression of TMED2 mRNA was closely associated with reduced overall survival (OS) in all breast cancers, and with reduced OS in patients with ER-positive, Luminal A or Luminal B breast cancer subtypes. Moreover, western blot confirmed that TMED2 increased expressed was correlated with the reduced OS at protein levels.

Conclusion: Increased expression of TMED2 was significantly related to unfavorable outcomes in patients with breast cancer. Thus, we supposed TMED2 is oncogenic and a potential target for breast cancer therapy and these preliminary findings require further study to determine whether TMED2-targeting reagents might be developed for clinical application in breast cancer.

Diagnostic role of circulating extracellular matrix-related proteins in non-small cell lung cancer

Background

Interactions between cancer cells and the surrounding microenvironment are crucial determinants of cancer progression. During this process, bi-directional communication among tumor cells and cancer associated fibroblasts (CAF) regulate extracellular matrix (ECM) deposition and remodeling. As a result of this dynamic process, soluble ECM proteins can be released into the bloodstream and may represent novel circulating biomarkers useful for cancer diagnosis. The aim of the present study was to measure the levels of three circulating ECM related proteins (COL11A1, COL10A1 and SPARC) in plasma samples of lung cancer patients and in healthy heavy-smokers controls and test whether such measurements have diagnostic or prognostic value.

Methods

Gene expression profiling of lung fibroblasts isolated from paired normal and cancer tissue of NSCLC patients was performed by gene expression microarrays. The prioritization of the candidates for the study of circulating proteins in plasma was based on the most differentially expressed genes in cancer associated fibroblasts. Soluble ECM proteins were assessed by western blot in the conditioned medium of lung fibroblasts and by ELISA assays in plasma samples.

Results

Plasma samples from lung cancer patients and healthy heavy-smokers controls were tested for levels of COL11A1 and COL10A1 (n = 57 each) and SPARC (n = 90 each). Higher plasma levels of COL10A1 were detected in patients (p ≤ 0.001), a difference that was driven specifically by females (p < 0.001). No difference in COL11A1 levels between patients and controls was found. SPARC levels were also higher in plasma patients than controls (p < 0.001) with good performance in discriminating the two groups (AUC = 0.744). No significant association was observed between plasma proteins levels and clinicopathological features or survival.

Conclusion

Soluble factors related to proficient tumor-stroma cross-talk are detectable in plasma of primary lung cancer patients and may represent a valuable complementary diagnostic tool to discriminate lung cancer patients from healthy heavy-smokers individuals as shown for the SPARC protein.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4772-0) contains supplementary material, which is available to authorized users.

Prognostic Value of Combination of Pretreatment Red Cell Distribution Width and Neutrophil-to-Lymphocyte Ratio in Patients with Gastric Cancer

Aims

Gastric cancer (GC) is often diagnosed at an advanced stage; inexpensive and valid biomarkers for GC are still unavailable. We aimed to evaluate the prognosis of the combination of pretreatment red cell distribution width (RDW) and neutrophil-to-lymphocyte ratio (NLR) in patients with GC.

Methods

A retrospective analysis from 103 GC patients who were diagnosed at our institution from 2012 to 2016 was performed. Both pretreatment RDW and NLR were calculated based on the recommended cutoff values of 13.4% and 2.755, respectively. Combined values of RDW and NLR (RDW + NLR) stratified patients into a score of 0 (RDW ≤ 13.4% and NLR ≤ 2.755), a score of 1 (RDW > 13.4% or NLR > 2.755), and a score of 2 (RDW > 13.4% and NLR > 2.755). Prognostic significances for overall survival (OS) and progression-free survival (PFS) were assessed.

Results

Pretreatment RDW + NLR was a significantly independent prognostic factor for OS and PFS. Moreover, high RDW + NLR was strongly related to age, tumor location, TNM stage, CA125, and CA199. In a subgroup analysis for patients with advanced gastric cancer (AGC), we observed that the level of RDW + NLR was markedly associated with OS and PFS.

Conclusion

Pretreatment RDW + NLR is a simple, inexpensive, and valid prognostic system to predict the survival in patients with GC, especially AGC.

Identification of a novel gene pairs signature in the prognosis of gastric cancer

Current prognostic signatures need to be improved in identifying high-risk patients of gastric cancer (GC). Thus, we aimed to develop a reliable prognostic signature that could assess the prognosis risk in GC patients. Two microarray datasets of GSE662254 (n = 300, training set) and GSE15459 (n = 192, test set) were included into analysis. Prognostic genes were screened to construct prognosis-related gene pairs (PRGPs). Then, a penalized Cox proportional hazards regression model identified seven PRGPs, which constructed a prognostic signature and divided patients into high- and low-risk groups according to the signature score. High-risk patients showed a poorer prognosis than low-risk patients in both the training set (hazard ratios [HR]: 6.086, 95% confidence interval [CI]: 4.341-8.533) and test set (1.773 [1.107-2.840]). The PRGPs signature also achieved a higher predictive accuracy (concordance index [C-index]: 0.872, 95% CI: 0.846-0.897) than two existing molecular signatures (0.706 [0.667-0.744] for a 11-gene signature and 0.684 [0.642-0.726] for a 24-lncRNA signature) and TNM stage (0.764 [0.715-0.814]). In conclusion, our study identified a novel gene pairs signature in the prognosis of GC.

Nab-paclitaxel as First Line Treatment for NSCLC in Elderly Patients More Than 75 Years Old

Introduction: Lung cancer is still the leading cause of cancer among cancer patients. Although there are novel therapies as second line treatment for NSCLC, there is an issue for elderly patients. Patients and Methods: We collected retrospectively data from 60 patients >75 years of age. Thirty of these patients received nab-paclitaxel and first line treatment and were compared to thirty patients that received only best supportive care. Results: The median life of patients at the date of disease progression, although increased by the administration of the drug (92 days versus 70) was not confirmed statistically significantly (Mann-Whitney test: W = 280, p = 0.138). The administration of drug seems to keep stable the biological condition of patients (McNemar's test: χ² = 0.033, p = 0.99). Patients with chemotherapy the death rate was increased by 50% as compared to those with best supportive care (12 vs 8), the median life until the unfortunate event surpassed statistically significantly the latter (150 days of life as compared to 108, Mann-Whitney test: W = 57.5, p = 0.045). Discussion: Nab-paclitaxel as a monotherapy could be considered as a first line treatment option for patients > 75 years of age without any previous cardiological medical history when compared to best supportive care.