FGG promotes migration and invasion in hepatocellular carcinoma cells through activating epithelial to mesenchymal transition

A novel prognostic signature based on smoking-associated genes for predicting prognosis and immune microenvironment in NSCLC smokers

BACKGROUND

As a highly heterogeneous tumor, non-small cell lung cancer (NSCLC) is famous for its high incidence and mortality worldwide. Smoking can cause genetic changes, which leading to the occurrence and progress of NSCLC. Nevertheless, the function of smoking-related genes in NSCLC needs more research.

METHODS

We downloaded transcriptome data and clinicopathological parameters from Gene Expression Omnibus (GEO) databases, and screened smoking-related genes. Lasso regression were applied to establish the 7-gene signature. The associations between the 7-gene signature and immune microenvironment analysis, survival analysis, drug sensitivity analysis and enriched molecular pathways were studied. Ultimately, cell function experiments were conducted to research the function of FCGBP in NSCLC.

RESULTS

Through 7-gene signature, NSCLC samples were classified into high-risk group (HRG) and low-risk group (LRG). Significant difference in overall survival (OS) between HRG and LRG was found. Nomograms and ROC curves indicated that the 7-gene signature has a stable ability in predicting prognosis. Through the analysis of immune microenvironment, we found that LRG patients had better tumor immune activation. FCGBP showed the highest mutation frequency among the seven prognostic smoking related genes (LRRC31, HPGD, FCGBP, SPINK5, CYP24A1, S100P and FGG), and was notable down-regulated in NSCLC smokers compared with non-smoking NSCLC patients. The cell experiments confirmed that FCGBP knockdown promoting proliferation, migration, and invasion in NSCLC cells.

CONCLUSION

This smoking-related prognostic signature represents a promising tool for assessing prognosis and tumor microenvironment in smokers with NSCLC. The role of FCGBP in NSCLC was found by cell experiments, which can be served as diagnostic biomarker and immunotherapy target for NSCLC.

Fibrinogen and tumors

Elevated plasma fibrinogen (Fg) levels consistently correlate with an unfavorable prognosis in various tumor patient cohorts. Within the tumor microenvironment, aberrant deposition and expression of Fg have been consistently observed, interacting with multiple cellular receptors and thereby accentuating its role as a regulator of inflammatory processes. Specifically, Fg serves to stimulate and recruit immune cells and pro-inflammatory cytokines, thereby contributing to the promotion of tumor progression. Additionally, Fg and its fragments exhibit dichotomous effects on tumor angiogenesis. Notably, Fg also facilitates tumor migration through both platelet-dependent and platelet-independent mechanisms. Recent studies have illuminated several tumor-related signaling pathways influenced by Fg. This review provides a comprehensive summary of the intricate involvement of Fg in tumor biology, elucidating its multifaceted role and the underlying mechanisms.

Detection of Naturally occurring abortive transcripts by Base-Stacking Hybridization Assisted Ligation and PCR amplification

Abortive transcripts (ATs) refer to nascent 2-10 nucleotides (nt) RNAs released by RNA polymerases before synthesizing productive RNAs. The quantitative detection of ATs is important for studying transcription initiation and the biological function of ATs; however, no method is available for the qualitative and quantitative assessment of such ultra-short oligonucleotides (typically shorter than 11 nt) in vivo at present, even with the LNA probes, the detection limit can only reach 11 nt. Here, we demonstrated the base stacking hybridization assisted ligation (BSHAL) technique, combined with TaqMan-MGB qPCR, can detect 4-10 nt ATs with a specificity of nucleotide resolution and a sensitivity of approximately 10 pM. By this technique, we detected endogenous ATs in cell lines, mice plasmas, and mice liver tissues, respectively, and proved that naturally occurring ATs do exist. We found that the 8 nt ATs of HMSB and Gapdh could be used as reference ATs for data normalization in Homo and mouse respectively, and 8 nt ATs of Afp and Gpc3 were suitable for use as plasma biomarkers of Hepatocellular carcinoma in mouse, indicate ATs are promising biomarkers. This study offers opportunities to study ATs and other ultra-short oligonucleotides in biological samples.

Pien Tze Huang Inhibits Migration and Invasion of Hepatocellular Carcinoma Cells by Repressing PDGFRB/YAP/CCN2 Axis Activity

OBJECTIVE

To investigate the effects of Pien Tze Huang (PZH) on the migration and invasion of HCC cells and underlying molecular mechanism.

METHODS

Cell counting kit-8 (CCK-8) was applied to evaluate the cell viabilities of SMMC-7721, SK-Hep-1, C3A and HL-7702 (6 × 103 cells/well) co-incubated with different concentrations of PZH (0, 0.2, 0.4, 0.6, 0.8 mg/mL) for 24 h. Transwell, wound healing assay, CCK-8 and Annexin V-FITC/PI staining were conducted to investigate the effects of PZH on the migration, invasion, proliferation and apoptosis of SK-Hep-1 and SMMC-7721 cells (650 µ g/mL for SK-Hep-1 cells and 330 µ g/mL for SMMC-7721 cells), respectively. In vivo, lung metastasis mouse model constructed by tail vein injection of HCC cells was used for evaluating the anti-metastasis function of PZH. SK-Hep-1 cells (106 cells/200 µ L per mice) were injected into B-NDG mice via tail vein. Totally 8 mice were randomly divided into PZH and control groups, 4 mice in each group. After 2-d inoculation, mice in the PZH group were administered with PZH (250 mg/kg, daily) and mice in the control group received only vehicle (PBS) from the 2nd day after xenograft to day 17. Transcriptome analysis based on RNA-seq was subsequently used for deciphering anti-tumor mechanism of PZH. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot were applied to verify RNA-seq results. Luciferase reporter assay was performed to examine the transcriptional activity of yes-associated protein (YAP).

RESULTS

PZH treatment significantly inhibited the migration, invasion, proliferation and promoted the apoptosis of HCC cells in vitro and in vivo (P<0.01). Transcriptome analysis indicated that Hippo signaling pathway was associated with anti-metastasis function of PZH. Mechanical study showed PZH significantly inhibited the expressions of platelet derived growth factor receptor beta (PDGFRB), YAP, connective tissue growth factor (CCN2), N-cadherin, vimentin and matrix metallopeptidase 2 (MMP2, P<0.01). Meanwhile, the phosphorylation of YAP was also enhanced by PZH treatment in vitro and in vivo. Furthermore, PZH played roles in inhibiting the transcriptional activity of YAP.

CONCLUSION

PZH restrained migration, invasion and epithelial-mesenchymal transition of HCC cells through repressing PDGFRB/YAP/CCN2 axis.

Tumor-infiltrating platelets promote the growth of lung adenocarcinoma

PURPOSE

Platelets could promote tumor growth and metastasis. However, the role of platelets in different subtypes of non-small cell lung cancer (NSCLC) and platelet infiltration in local tumor tissue remain unclear.

METHODS

Initially, platelet infiltration in lung adenocarcinoma (ADC) and lung squamous cell carcinoma (SCC) was estimated by CD41 expression using immunohistochemistry. Subsequently, co-incubation of NSCLC cell lines and platelets was performed to compare the ability of binding platelets. Subcutaneous tumor models were established to assess the ability of platelets to promote tumor growth. Then, RNA-seq data of NSCLC was used to identify differentially expressed genes and enriched pathways. Lastly, a clinical cohort comprising of ADC and SCC patients as well as meta-analysis was analyzed to compare the difference of coagulation associated clinical parameters.

RESULTS

We found high platelet infiltration in ADC, especially of advanced disease and metastases, whereas few platelets were observed in SCC. Moreover, ADC cell lines exhibited strong ability of binding platelets compared with SCC cell lines. Platelets could also promote the growth of ADC cell lines in vivo. Furthermore, coagulation cascades and fibrinogen were upregulated in ADC. And chemical inhibition of GPIIb/IIIa-fibrinogen axis reduced the binding of ADC cells and platelets. ADC patients were also in a hypercoagulable state characterized by higher d-dimer level and shorter clotting time. Finally, meta-analysis identified a higher risk of venous thromboembolism (VTE) in ADC patients and low molecular weight heparin (LMWH) treatment was effective at reducing this risk.

CONCLUSIONS

This study identified the differences of platelet infiltration and coagulation between ADC and SCC patients, which may inform the development of anticoagulation therapies for NSCLC.

In search of new stratification strategies: tissue proteomic profiling of papillary thyroid microcarcinoma in patients with localized disease and lateral neck metastases

INTRODUCTION

Papillary thyroid carcinomas (PTC) are the most common thyroid malignancies that are often diagnosed as microcarcinomas when the tumor is less than one centimetre in diameter. Currently, there are no valid stratification strategies that would reliably assess the risk of lateral neck metastases and optimize surgical treatment.

MATERIALS AND METHODS

Aiming to find potential tissue biomarkers of metastatic potential, we conducted a cross-sectional proteomic pilot study on formalin-fixed paraffin-embedded tissues of metastatic (N = 10) and non-metastatic (N = 10) papillary thyroid microcarcinoma patients. Samples were analysed individually using liquid chromatography/mass spectrometry, and the differentially expressed proteins (DEP) were functionally annotated.

RESULTS

We identified five overexpressed DEPs in the metastatic group (EPB41L2, CSE1L, GLIPR2, FGA and FGG) with a known association to tumour biology. Using bioinformatic-based tools, we found markedly different profiles of significantly enriched biological processes between the two groups.

CONCLUSIONS

The identified DEPs might have a role as potential tissue biomarkers for PTC metastases. However, further prospective research is needed to confirm our findings.

Identification of exosome protein panels as predictive biomarkers for non-small cell lung cancer

BACKGROUND

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related deaths worldwide, primarily due to its propensity for metastasis. Patients diagnosed with localized primary cancer have higher survival rates than those with metastasis. Thus, it is imperative to discover biomarkers for the early detection of NSCLC and the timely prediction of tumor metastasis to improve patient outcomes.

METHODS

Here, we utilized an integrated approach to isolate and characterize plasma exosomes from NSCLC patients as well as healthy individuals. We then conducted proteomics analysis and parallel reaction monitoring to identify and validate the top-ranked proteins of plasma exosomes.

RESULTS

Our study revealed that the proteome in exosomes from NSCLC patients with metastasis was distinctly different from that from healthy individuals. The former had larger diameters and lower concentrations of exosomes than the latter. Furthermore, among the 1220 identified exosomal proteins, we identified two distinct panels of biomarkers. The first panel of biomarkers (FGB, FGG, and VWF) showed potential for early NSCLC diagnosis and demonstrated a direct correlation with the survival duration of NSCLC patients. The second panel of biomarkers (CFHR5, C9, and MBL2) emerged as potential biomarkers for assessing NSCLC metastasis, of which CFHR5 alone was significantly associated with the overall survival of NSCLC patients.

CONCLUSIONS

These findings underscore the potential of plasma exosomal biomarkers for early NSCLC diagnosis and metastasis prediction. Notably, CFHR5 stands out as a promising prognostic indicator for NSCLC patients. The clinical utility of exosomal biomarkers offers the potential to enhance the management of NSCLC.

Characterization of platelet-related genes and constructing signature combined with immune-related genes for predicting outcomes and immunotherapy response in lung squamous cell carcinoma

Lung squamous cell carcinoma (LUSC) is a highly malignant subtype of non-small cell lung cancer with poor prognosis. Platelets are known to play a critical role in cancer development and progression, and recent studies suggest that they can also regulate immune response in tumors. However, the relationship between platelet-related genes (PRGs) and LUSC prognosis and tumor microenvironments remains unclear. In this study, we used multiple bioinformatics algorithms to identify 25 dysregulated PRGs that were significantly associated with LUSC prognosis. We found that PRGs were involved in multiple biological processes, particularly in the tumor microenvironment, and that platelet-related scores (PRS) were a risk factor. Additionally, we established a 6-gene prognostic signature combining PRGs and immune-related genes that accurately predicted outcomes and immunotherapy efficacy in LUSC patients. Our study provides a comprehensive analysis of the biological functions and potential therapeutic targets of PRGs in LUSC, which may inform the development of new treatments for this disease.

Liquid biopsy-based protein biomarkers for risk prediction, early diagnosis, and prognostication of cholangiocarcinoma

BACKGROUND & AIMS

Cholangiocarcinoma (CCA), heterogeneous biliary tumours with dismal prognosis, lacks accurate early diagnostic methods especially important for individuals at high-risk (i.e. those with primary sclerosing cholangitis [PSC]). Here, we searched for protein biomarkers in serum extracellular vesicles (EVs).

METHODS

EVs from patients with isolated PSC (n = 45), concomitant PSC-CCA (n = 44), PSC who developed CCA during follow-up (PSC to CCA; n = 25), CCAs from non-PSC aetiology (n = 56), and hepatocellular carcinoma (n = 34) and healthy individuals (n = 56) were characterised by mass spectrometry. Diagnostic biomarkers for PSC-CCA, non-PSC CCA, or CCAs regardless of aetiology (Pan-CCAs) were defined and validated by ELISA. Their expression was evaluated in CCA tumours at a single-cell level. Prognostic EV biomarkers for CCA were investigated.

RESULTS

High-throughput proteomics of EVs identified diagnostic biomarkers for PSC-CCA, non-PSC CCA, or Pan-CCA, and for the differential diagnosis of intrahepatic CCA and hepatocellular carcinoma, which were cross-validated by ELISA using total serum. Machine learning-based algorithms disclosed CRP/FIBRINOGEN/FRIL for the diagnosis of PSC-CCA (local disease [LD]) vs. isolated PSC (AUC = 0.947; odds ratio [OR] =36.9) and, combined with carbohydrate antigen 19-9, overpowers carbohydrate antigen 19-9 alone. CRP/PIGR/VWF allowed the diagnosis of LD non-PSC CCAs vs. healthy individuals (AUC = 0.992; OR = 387.5). It is noteworthy that CRP/FRIL accurately diagnosed LD Pan-CCA (AUC = 0.941; OR = 89.4). Levels of CRP/FIBRINOGEN/FRIL/PIGR showed predictive capacity for CCA development in PSC before clinical evidence of malignancy. Multi-organ transcriptomic analysis revealed that serum EV biomarkers were mostly expressed in hepatobiliary tissues, and single-cell RNA sequencing and immunofluorescence analysis of CCA tumours showed their presence mainly in malignant cholangiocytes. Multivariable analysis unveiled EV prognostic biomarkers, with COMP/GNAI2/CFAI and ACTN1/MYCT1/PF4V associated negatively and positively with patients' survival, respectively.

CONCLUSIONS

Serum EVs contain protein biomarkers for the prediction, early diagnosis, and prognostication of CCA that are detectable using total serum, representing a tumour cell-derived liquid biopsy tool for personalised medicine.

IMPACT AND IMPLICATIONS

The accuracy of current imaging tests and circulating tumour biomarkers for cholangiocarcinoma (CCA) diagnosis is far from satisfactory. Most CCAs are considered sporadic, although up to 20% of patients with primary sclerosing cholangitis (PSC) develop CCA during their lifetime, constituting a major cause of PSC-related death. This international study has proposed protein-based and aetiology-related logistic models with predictive, diagnostic, or prognostic capacities by combining two to four circulating protein biomarkers, moving a step forward into personalised medicine. These novel liquid biopsy tools may allow the (i) easy and non-invasive diagnosis of sporadic CCAs, (ii) identification of patients with PSC with higher risk for CCA development, (iii) establishment of cost-effective surveillance programmes for the early detection of CCA in high-risk populations (e.g. PSC), and (iv) prognostic stratification of patients with CCA, which, altogether, may increase the number of cases eligible for potentially curative options or to receive more successful treatments, decreasing CCA-related mortality.

Proteomic research on new urinary biomarkers of renal disease in canine leishmaniosis: Survival and monitoring response to treatment

The objective of our study was to search for survival biomarkers (SB) and treatment response monitoring biomarkers (TRMB) in the urinary proteome of dogs with renal disease secondary to canine leishmaniosis (CanL), using UHPLC-MS/MS. The proteomic data are available via ProteomeXchange with identifier PXD042578. Initially, a group of 12 dogs was evaluated and divided into survivors (SG; n = 6) and nonsurvivors (NSG; n = 6). A total of 972 proteins were obtained from the evaluated samples. Then, bioinformatic analysis reduced them to 6 proteins like potential SB increased in the NSG, specifically, Haemoglobin subunit Alpha 1, Complement Factor I, Complement C5, Fibrinogen beta chain (fragment), Peptidase S1 domain-containing protein, and Fibrinogen gamma chain. Afterwards, SG was used to search for TRMB, studying their urine at 0, 30, and 90 days, and 9 proteins that decreased after treatment were obtained: Apolipoprotein E, Cathepsin B, Cystatin B, Cystatin-C-like, Lysozyme, Monocyte differentiation CD14, Pancreatitis-associated precursor protein, Profilin, and Protein FAM3C. Finally, enrichment analysis provided information about the biological mechanisms in which these proteins are involved. In conclusion, this study provides 15 new candidate urinary biomarkers and an improved understanding of the pathogenesis of kidney disease in CanL.

Anti-HPV16 oncoproteins siRNA therapy for cervical cancer using a novel transdermal peptide PKU12

In this study, an innovative transdermal peptide, #PKU12, was developed based on transdermal peptide TD-1, and the anti-tumor effect of PKU12-based siRNA against HPV was investigated in vivo. Furthermore, transcriptome differences between PKU12 + siRNA treatment and control groups were compared to assess treatment effects. The top five upregulated and downregulated genes identified by RNA sequencing were further subjected to survival analysis. The present study, for the first time, showed that this novel peptide could enhance the transdermal delivery of the siRNA targeting HPV16 L1, E6, and E7. PKU12-based siRNA delivery significantly repressed the mRNA expression levels of HPV16 L1, E6, and E7 in the SiHa xenograft tumors and attenuated tumor growth as well. The RNA-sequencing results showed that a total of 586 DEGs were detected in the PKU12 + siRNA-treated tumor tissues compared to the control tumor tissues. The GSEA analysis revealed that DEGs were inversely associated with the HIF-1 signaling pathway, the TNF signaling pathway, the AGE-RAGE signaling pathway, the NF-kappa B signaling pathway, ferroptosis, the IL-17 signaling pathway, ovarian steroidogenesis, and rheumatoid arthritis. Further functional enrichment analysis revealed that DEGs were significantly enriched in several key pathways, including cytokine-cytokine receptor interaction, the TNF signaling pathway, and the IL-17 signaling pathway. High expression of MYH1, MYH4, FGG, DEPP1, and ZBTB16 was associated with shorter overall survival of patients with cervical cancer; high expression of SULT1E1, RAB3C, CXCR3, and PROX2 was associated with longer overall survival of patients with cervical cancer. In conclusion, the transdermal peptide PKU12 is potentially a good candidate for a siRNA delivery vehicle for the treatment of cervical cancer.

Spatial transcriptomics reveals the heterogeneity and FGG+CRP+ inflammatory cancer-associated fibroblasts replace islets in pancreatic ductal adenocarcinoma

Background

Understanding the spatial heterogeneity of the tumor microenvironment (TME) in pancreatic cancer (PC) remains challenging.

Methods

In this study, we performed spatial transcriptomics (ST) to investigate the gene expression features across one normal pancreatic tissue, PC tissue, adjacent tumor tissue, and tumor stroma. We divided 18,075 spatial spots into 22 clusters with t-distributed stochastic neighbor embedding based on gene expression profiles. The biological functions and signaling pathways involved in each cluster were analyzed with gene set enrichment analysis.

Results

The results revealed that KRT13+FABP5+ malignant cell subpopulation had keratinization characteristics in the tumor tissue. Fibroblasts from adjacent tumor tissue exhibited a tumor-inhibiting role such as "B-cell activation" and "positive regulation of leukocyte activation." The FGG+CRP+ inflammatory cancer-associated fibroblasts replaced the islets in tumor stroma. During PC progression, the damage to pancreatic structure and function was heavier in the pancreatic exocrine (AMYA2+PRSS1+) than in the endocrine (INS+GCG+).

Conclusion

Our results revealed the spatial heterogeneity of dynamic changes and highlighted the significance of impaired exocrine function in PC.

scAB detects multiresolution cell states with clinical significance by integrating single-cell genomics and bulk sequencing data

Although single-cell sequencing has provided a powerful tool to deconvolute cellular heterogeneity of diseases like cancer, extrapolating clinical significance or identifying clinically-relevant cells remains challenging. Here, we propose a novel computational method scAB, which integrates single-cell genomics data with clinically annotated bulk sequencing data via a knowledge- and graph-guided matrix factorization model. Once combined, scAB provides a coarse- and fine-grain multiresolution perspective of phenotype-associated cell states and prognostic signatures previously not visible by single-cell genomics. We use scAB to enhance live cancer single-cell RNA-seq data, identifying clinically-relevant previously unrecognized cancer and stromal cell subsets whose signatures show a stronger poor-survival association. The identified fine-grain cell subsets are associated with distinct cancer hallmarks and prognosis power. Furthermore, scAB demonstrates its utility as a biomarker identification tool, with the ability to predict immunotherapy, drug responses and survival when applied to melanoma single-cell RNA-seq datasets and glioma single-cell ATAC-seq datasets. Across multiple single-cell and bulk datasets from different cancer types, we also demonstrate the superior performance of scAB in generating prognosis signatures and survival predictions over existing models. Overall, scAB provides an efficient tool for prioritizing clinically-relevant cell subsets and predictive signatures, utilizing large publicly available databases to improve prognosis and treatments.

Screening potential biomarkers of cholangiocarcinoma based on gene chip meta-analysis and small-sample experimental research

Cholangiocarcinoma (CCA) is a rare malignant tumor associated with poor prognosis. This study aimed to identify CCA biomarkers by investigating differentially expressed genes (DEGs) between CCA patients and healthy subjects obtained from the Gene Expression Omnibus database. Bioinformatics tools, including the Illumina BaseSpace Correlation Engine (BSCE) and Gene Expression Profiling Interactive Analysis (GEPIA), were used. The initial DEGs from GSE26566, GSE31370, and GSE77984 were analyzed using GEO2R and Venn, and protein–protein interaction networks were constructed using STRING. The BSCE was applied to assess curated CCA studies to select additional DEGs and them DEGs across the 10 biosets, which was supported by findings in the literature. The final 18 DEGs with clinical significance for CCA were further verified using GEPIA. These included CEACAM6, EPCAM, LAMC2, MMP11, KRT7, KRT17, KRT19, SFN, and SOX9, which were upregulated, and ADH1A, ALDOB, AOX1, CTH, FGA, FGB, FGG, GSTA1, and OTC, which were downregulated in CCA patients. Among these 18 genes, 56 groups of genes (two in each group) were significantly related, and none were independently and differentially expressed. The hub genes FGA, OTC, CTH, and MMP11, which were most correlated with the 18 DEGs, were screened using STRING. The significantly low expression of FGA, OTC, and CTH and significantly high expression of MMP11 were verified by immunohistochemical analysis. Overall, four CCA biomarkers were identified that might regulate the occurrence and development of this disease and affect the patient survival rate, and they have the potential to become diagnostic and therapeutic targets for patients with CCA.

Identification of gene signature in RNA-Seq hepatocellular carcinoma data by Pareto-optimal cluster algorithm

Aim

This study aimed to detect gene signatures in RNA-sequencing (RNA-seq) data using Pareto-optimal cluster size identification.

Background

RNA-seq has emerged as an important technology for transcriptome profiling in recent years. Gene expression signatures involving tens of genes have been proven to be predictive of disease type and patient response to treatment.

Methods

Data related to the liver cancer RNA-seq dataset, which included 35 paired hepatocellular carcinoma (HCC) and non-tumor tissue samples, was used in this study. The differentially expressed genes (DEGs) were identified after performing pre-filtering and normalization. After that, a multi-objective optimization technique, namely multi-objective optimization for collecting cluster alternatives (MOCCA), was used to discover the Pareto-optimal cluster size for these DEGs. Then, the k-means clustering method was performed on the RNA-seq data. The best cluster, as a signature for the disease, was found by calculating the average Spearman's correlation score of all genes in the module in a pair-wise manner. All analyses were performed in the R 4.1.1 package in virtual space with 100 Gb of RAM memory.

Results

Using MOCCA, eight Pareto-optimal clusters were obtained. Ultimately, two clusters with the greatest average Spearman's correlation coefficient scores were chosen as gene signatures. Eleven prognostic genes involved in HCC's abnormal metabolism were identified. In addition, three differentially expressed pathways were identified between tumor and non-tumor tissues.

Conclusion

These identified metabolic prognostic genes help us to provide more powerful prognostic information and enhance survival prediction for HCC patients. In addition, Pareto-optimal cluster size identification is suggested for gene signature in other RNA-Seq data.

AC093797.1 as a Potential Biomarker to Indicate the Prognosis of Hepatocellular Carcinoma and Inhibits Cell Proliferation, Invasion, and Migration by Reprogramming Cell Metabolism and Extracellular Matrix Dynamics

Purpose: The risk signature composed of four lncRNA (AC093797.1, POLR2J4, AL121748.1, and AL162231.4.) can be used to predict the overall survival (OS) of patients with hepatocellular carcinoma (HCC). However, the clinical significance and biological function of AC093797.1 are still unexplored in HCC or other malignant tumors. In this study, we aimed to investigate the biological function of AC093797.1 in HCC and screen the candidate hub genes and pathways related to hepatocarcinogenesis.

Methods: RT-qPCR was employed to detect AC093797.1 in HCC tissues and cell lines. The role of AC093797.1 in HCC was evaluated via the cell-counting kit-8, transwell, and wound healing assays. The effects of AC093797.1 on tumor growth in vivo were clarified by nude mice tumor formation experiments. Then, RNA-sequencing and bioinformatics analysis based on subcutaneous tumor tissue was performed to identify the hub genes and pathways associated with HCC.

Results: The expression of AC093797.1 decreased in HCC tissues and cell lines, and patients with low expressed AC093797.1 had poor overall survival (OS). AC093797.1 overexpression impeded HCC cell proliferation, invasion, and migration in vitro and suppressed tumor growth in vivo. Compared with the control group, 710 differentially expressed genes (243 upregulated genes and 467 downregulated genes) were filtered via RNA-sequencing, which mainly enriched in amino acid metabolism, extracellular matrix structure constituents, cell adhesion molecules cams, signaling to Ras, and signaling to ERKs.

Conclusion: AC093797.1 may inhibit cell proliferation, invasion, and migration in HCC by reprograming cell metabolism or regulating several pathways, suggesting that AC093797.1 might be a potential therapeutic and prognostic marker for HCC patients.

Integrative Analysis of Epigenome and Transcriptome Data Reveals Aberrantly Methylated Promoters and Enhancers in Hepatocellular Carcinoma

DNA methylation is a key transcription regulator, whose aberration was ubiquitous and important in most cancers including hepatocellular carcinoma (HCC). Whole-genome bisulfite sequencing (WGBS) was conducted for comparison of DNA methylation in tumor and adjacent tissues from 33 HCC patients, accompanying RNA-seq to determine differentially methylated region-associated, differentially expressed genes (DMR-DEGs), which were independently replicated in the TCGA-LIHC cohort and experimentally validated via 5-aza-2-deoxycytidine (5-azadC) demethylation. A total of 9,867,700 CpG sites showed significantly differential methylation in HCC. Integrations of mRNA-seq, histone ChIP-seq, and WGBS data identified 611 high-confidence DMR-DEGs. Enrichment analysis demonstrated activation of multiple molecular pathways related to cell cycle and DNA repair, accompanying repression of several critical metabolism pathways such as tyrosine and monocarboxylic acid metabolism. In TCGA-LIHC, we replicated about 53% of identified DMR-DEGs and highlighted the prognostic significance of combinations of methylation and expression of nine DMR-DEGs, which were more efficient prognostic biomarkers than considering either type of data alone. Finally, we validated 22/23 (95.7%) DMR-DEGs in 5-azadC-treated LO2 and/or HepG2 cells. In conclusion, integration of epigenome and transcriptome data depicted activation of multiple pivotal cell cycle-related pathways and repression of several metabolic pathways triggered by aberrant DNA methylation of promoters and enhancers in HCC.

DNA and RNA Sequencing Recapitulated Aberrant Tumor Metabolism in Liver Cancer Cell Lines

AIM

Metabolic reprogramming has recently attracted extensive attention for understanding cancer development. We aimed to demonstrate a genomic and transcriptomic landscape of metabolic reprogramming underlying liver cancer cell lines.

METHODS

We investigated metabolic aberrant at both the transcriptome and genome levels using transcriptome and whole-exome sequencing data from 12 human liver cancer cell lines (hLCCLs) and one normal liver cell line.

RESULTS

Three subgroups of hLCCLs characterized from transcriptome sequencing data exhibit significantly different aberrations in various metabolic processes, including amino acid, lipid, energy, and carbohydrate metabolism. Furthermore, whole-exome sequencing revealed distinct mutational signatures among different subgroups of hLCCLs and identified a total of 19 known driver genes implicated in metabolism.

CONCLUSION

Our findings highlighted differential metabolic mechanisms in the development of liver cancer and provided a resource for further investigating its metabolic mechanisms.

The combination of fibrinogen concentrations and the platelet-to-lymphocyte ratio predicts survival in patients with advanced lung adenocarcinoma treated with EGFR-TKIs

OBJECTIVE

This study aimed to identify a predictive marker of response to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) in patients with EGFR-mutant advanced lung adenocarcinoma.

METHODS

A cohort of 190 patients with EGFR-mutant advanced lung adenocarcinoma was analyzed. Receiver operating characteristic curve analysis was used to evaluate the optimal cutoffs for fibrinogen levels, the neutrophil-to-lymphocyte ratio (NLR), and the platelet-to-lymphocyte ratio (PLR) for predicting progression-free survival (PFS). Univariate and multivariate survival analyses were performed to identify factors correlated with PFS and overall survival (OS).

RESULTS

High NLR was associated with worse performance status. In univariate analysis, fibrinogen levels, NLR, and PLR were correlated with OS and PFS. In multivariate analysis, all three variables remained predictive of OS, whereas only fibrinogen levels and PLR were independent prognostic factors for PFS. Furthermore, the combination of fibrinogen levels and PLR (F-PLR score) could stratify patients into three groups with significantly different prognoses, and the score was independently predictive of survival.

CONCLUSION

The F-PLR score predicted the prognosis of patients with EGFR-mutant advanced lung adenocarcinoma who received EGFR-TKIs, and this score may serve as a convenient blood-based marker for identifying high-risk patients.

Persistent effects of pair bonding in lung cancer cell growth in monogamous Peromyscus californicus

Epidemiological evidence suggests that social interactions and especially bonding between couples influence tumorigenesis, yet whether this is due to lifestyle changes, homogamy (likelihood of individuals to marry people of similar health), or directly associated with host-induced effects in tumors remains debatable. In the present study, we explored if tumorigenesis is associated with the bonding experience in monogamous rodents at which disruption of pair bonds is linked to anxiety and stress. Comparison of lung cancer cell spheroids that formed in the presence of sera from bonded and bond-disrupted deer mice showed that in monogamous Peromyscus polionotus and Peromyscus californicus, but not in polygamous Peromyscus maniculatus, the disruption of pair bonds altered the size and morphology of spheroids in a manner that is consistent with the acquisition of increased oncogenic potential. In vivo, consecutive transplantation of human lung cancer cells between P. californicus, differing in bonding experiences (n = 9 for bonded and n = 7 for bond-disrupted), and nude mice showed that bonding suppressed tumorigenicity in nude mice (p<0.05), suggesting that the protective effects of pair bonds persisted even after bonding ceased. Unsupervised hierarchical clustering indicated that the transcriptomes of lung cancer cells clustered according to the serum donors' bonding history while differential gene expression analysis pointed to changes in cell adhesion and migration. The results highlight the pro-oncogenic effects of pair-bond disruption, point to the acquisition of expression signatures in cancer cells that are relevant to the bonding experiences of serum donors, and question the ability of conventional mouse models to capture the whole spectrum of the impact of the host in tumorigenesis.

Combination of preoperative fibrinogen and D-dimer as a prognostic indicator in pancreatic ductal adenocarcinoma patients undergoing R0 resection

BACKGROUND

Patients with malignant tumors frequently exhibit hyperactivation of the coagulation system and secondary increased fibrinolytic activity. Fibrinogen and D-dimer are common indicators that are crucial in the coagulation/fibrinolysis system. Both indicators have been verified to have predictive value in the overall survival (OS) of many patients with solid malignancies.

AIM

To explore the prognostic significance of fibrinogen combined with D-dimer in pancreatic ductal adenocarcinoma (PDAC) patients undergoing radical R0 resection.

METHODS

We retrospectively analyzed the clinical data of 282 patients with PDAC undergoing radical R0 resection in the Cancer Hospital, Chinese Academy of Medical Sciences, between January 2010 and December 2019. The surv_cutpoint function of R language was used to determine the optimal cutoff values of the preoperative fibrinogen concentration and preoperative D-dimer concentration. Enrolled patients were further divided into the any-high group (high preoperative fibrinogen concentration and/or high preoperative D-dimer concentration) and the low-low group (low preoperative fibrinogen and D-dimer concentrations) according to the optimal cutoff values.

RESULTS

The optimal cutoff values of the preoperative fibrinogen concentration and preoperative D-dimer concentration were 3.31 g/L and 0.53 mg/L, respectively. Furthermore, multivariate Cox regression analysis showed that the preoperative fibrinogen concentration (HR: 1.603, 95%CI: 1.201-2.140, P = 0.001) and preoperative D-dimer concentration (HR: 1.355, 95%CI: 1.019-1.801, P = 0.036) exhibited obvious correlations with the OS of PDAC patients undergoing radical R0 resection. A prognostic analysis was further performed based on the subgroup results by using fibrinogen combined with D-dimer. The median OS duration of the low-low group (31.17 mo) was significantly longer than that of the any-high group (15.43 mo). Additionally, multivariate Cox regression analysis revealed that the degree of differentiation (P < 0.001), lymph node metastasis (HR: 0.663, 95%CI: 0.497-0.883, P = 0.005), preoperative CA19-9 level (HR: 1.699, 95%CI: 1.258-2.293, P = 0.001), adjuvant therapy (HR: 1.582, 95%CI: 1.202-2.081, P = 0.001) and preoperative combined grouping (HR: 2.397, 95%CI: 1.723-3.335, P < 0.001) were independent predictors of OS in PDAC patients undergoing radical R0 resection.

CONCLUSION

Preoperative fibrinogen combined with D-dimer plays a predictive role in OS, and low preoperative fibrinogen and D-dimer concentrations can indicate prolonged OS in PDAC patients undergoing radical R0 resection.

Transcriptome analysis of sinensetin-treated liver cancer cells guided by biological network analysis

Hepatocellular carcinoma is recognized as one of the most frequently occurring malignant types of liver cancer globally, making the identification of biomarkers critically important. The aim of the present study was to identify the genes involved in the anticancer effects of flavonoid compounds so that they may be used as targets for cancer treatment. Sinensetin (SIN), an isolated polymethoxyflavone monomer compound, possesses broad antitumor activities in vitro. Therefore, the identification of a transcriptome profile on the condition of cells treated with SIN may aid to better understand the genes involved and its mechanism of action. Genomic profiling studies of cancer are increasing rapidly in order to provide gene expression data that can reveal prognostic biomarkers to combat liver cancer. In the present study, high-throughput RNA sequencing (RNA-seq) was performed to reveal differential gene expression patterns between SIN-treated and SIN-untreated human liver cancer HepG2 cells. A total of 43 genes were identified to be differentially expressed (39 downregulated and 4 upregulated in the SIN-treated group compared with the SIN-untreated group). An extensive network analysis for these 43 genes resulted in the identification of 10 upregulated highly interconnected hub genes that contributed to the progression of cancer. Functional enrichment analysis of these 10 hub genes revealed their involvement in the regulation of apoptotic processes, immune response and tumor necrosis factor production. Additionally, the mRNA expression levels of these 10 genes were evaluated using reverse transcription-quantitative PCR, and the results were consistent with the RNA-seq data. Overall, the results of the present study revealed differentially expressed genes involved in cancer after SIN treatment in HepG2 cells and may help to develop strategies targeting these genes for treating liver cancer.

Fibrinogen/Albumin Ratio as a Promising Marker for Predicting Survival in Pancreatic Neuroendocrine Neoplasms

Background

The fibrinogen/albumin ratio (FAR) has been widely reported to be a possible biomarker for predicting prognosis in several types of tumors, but the prognostic value of the FAR in pancreatic neuroendocrine neoplasms (Pan-NENs) has not been systematically studied.

Patients and Methods

In total, 324 patients with Pan-NENs were recruited. The patients were divided into 2 subgroups according to the FAR cutoff value, and clinicopathological characteristics of the 2 subgroups were compared. Overall survival (OS) was the primary endpoint, and progression-free survival (PFS) was the secondary endpoint. The prognostic value of the FAR was analyzed in univariate and multivariate analyses.

Results

The optimal cutoff value for the FAR was calculated to be 0.08 for OS. The patients with a FAR ≥0.08 had higher proportions of nonfunctioning tumors, Pan-NECs, grade 3 tumors, and stage IV tumors than those with a FAR <0.08. In the univariate analysis, a FAR ≥ 0.08 was associated with poor OS (hazard ratio (HR) = 2.37, P < 0.001) and PFS (HR = 2.37, P < 0.001). In the multivariate analysis, a FAR ≥0.08 was an independent risk factor for poor OS (HR = 4.70, P < 0.001) and PFS (HR = 1.80, P = 0.006).

Conclusion

The pretreatment FAR, which includes fibrinogen and albumin, was a feasible and predictive biomarker for prognosis in patients with Pan-NENs. An elevated FAR, based on a cutoff value of 0.08, was an independent risk factor for poor OS and PFS.

Small extracellular vesicles containing miR-30a-3p attenuate the migration and invasion of hepatocellular carcinoma by targeting SNAP23 gene

Cancer cells under hypoxic, endoplasmic reticulum, and reactive oxygen species stress secrete copious amounts of small extracellular vesicles (sEVs) to promote tumor metastasis. The effects of blocking stress-induced sEV release on tumor metastasis remain unknown. We found that miR-30a-3p was selectively sorted into sEVs by hepatocellular carcinoma (HCC) cells under the influence of multiple stressors. miR-30a-3p removal from cancer cells through sEVs promoted HCC cell migration and invasion, whereas exogenous overexpression of miR-30a-3p could inhibit migration, invasion, and sEV release by directly targeting SNAP23. HCC cells efficiently absorbed hepatic stellate cell (HSC) sEVs, providing an advantage in the treatment of HCC using HSC sEVs. Treatment with HSC sEVs rich in miR-30a-3p cargo effectively attenuated HCC migration, invasion, and metastasis. Overall, sEVs containing miR-30a-3p decreased sEV secretion as well as the migration, invasion, and metastasis of HCC by directly targeting SNAP23, thereby providing an effective strategy to attenuate metastasis of HCC.

Biomarkers of tumor invasiveness in proteomics (Review)

Over the past two decades, quantitative proteomics has emerged as an important tool for deciphering the complex molecular events involved in cancers. The number of references involving studies on the cancer metastatic process has doubled since 2010, while the last 5 years have seen the development of novel technologies combining deep proteome coverage capabilities with quantitative consistency and accuracy. To highlight key findings within this huge amount of information, the present review identified a list of tumor invasive biomarkers based on both the literature and data collected on a biocollection of experimental cell lines, tumor models of increasing invasiveness and tumor samples from patients with colorectal or breast cancer. Crossing these different data sources led to 76 proteins of interest out of 1,245 mentioned in the literature. Information on these proteins can potentially be translated into clinical prospects, since they represent potential targets for the development and evaluation of innovative therapies, alone or in combination. Herein, a systematical review of the biology of each of these proteins, including their specific subcellular/extracellular or multiple localizations is presented. Finally, as an important advantage of quantitative proteomics is the ability to provide data on all these molecules simultaneously in cell pellets, body fluids or paraffin‑embedded sections of tumors/invaded tissues, the significance of some of their interconnections is discussed.

Combining the Fibrinogen/Albumin Ratio and Systemic Inflammation Response Index Predicts Survival in Resectable Gastric Cancer

Aims

Predicting the prognosis of gastric cancer using tumour-node-metastasis (TNM) staging is difficult as patients with the same TNM stage exhibit different prognoses.

Methods

This study investigated the prognostic value of the preoperative fibrinogen/albumin ratio (FAR)-systemic inflammation response index (SIRI) score in resectable gastric cancer (rGC).

Results

Clinicopathological features of 231 rGC patients were analysed retrospectively. Patients were divided into three groups: FAR-SIRI score 2 (FAR ≥ 0.071 and SIRI ≥ 0.84), 1 (FAR < 0.071 and SIRI ≥ 0.84), and 0 (SIRI < 0.84). Higher FAR-SIRI scores were associated with larger tumours, poorer differentiation, and advanced TNM stage (P < 0.05). Compared to those with FAR-SIRI scores of 0, patients with scores of 2 had poorer overall survival (OS). The FAR-SIRI score was an independent prognostic factor for OS in rGC.

Conclusion

The present data demonstrated that FAR-SIRI scores predicted radical gastric cancer surgical outcomes and may serve as a blood marker for identifying high-risk patients.

Moesin facilitates metastasis of hepatocellular carcinoma cells by improving invadopodia formation and activating β-catenin/MMP9 axis

Moesin has been proved to be implicated in invasiveness and metastasis in many other cancers, but unclear in HCC. Thus, this study was performed to investigate the clinical significance of moesin and its biological functions in HCC. The results showed that moesin was significantly up-regulated in HCC tissues and was an independent prognostic factor for predicting the recurrence of HCC patients, postoperatively. Furthermore, we also demonstrated that moesin promoted the migration and invasion of HCC cells in vitro and in vivo. And the mechanism studies indicated that moesin overexpression increased the formation of invadopodia and improved the activation of β-catenin/MMP9 axis. Taken together, our findings revealed that moesin acted as an important onco-protein participating in the metastasis of HCC.

Clinical significance of urinary plasminogen and fibrinogen gamma chain as novel potential diagnostic markers for non-small-cell lung cancer

BACKGROUND

Urinary proteins could be useful as markers for the detection of non-small-cell lung cancer (NSCLC). We investigated the levels of two different proteins in urine samples from NSCLC patients and assessed their diagnostic value.

METHODS

Urinary plasminogen (PLG) and fibrinogen gamma chain (FGG) levels in 112 NSCLC patients and 197 controls were detected using enzyme linked immunosorbent assay (ELISA). The expression of FGG and PLG in 20 NSCLC tissues and paired adjacent non-tumour tissues were detected through immunohistochemistry. The diagnostic value of FGG and PLG for NSCLC was evaluated through a receiver operating characteristic curve (ROC).

RESULTS

PLG and FGG were significantly elevated in NSCLC tissues vs paired adjacent non-tumour tissues (p = 0.000) and in urinary samples from NSCLC patients vs healthy controls (p = 0.000). The expression level of PLG in urinary samples was related only to the histological type (p = 0.001). Further, ROC curve analysis revealed that PLG, FGG, and their combination could distinguish NSCLC and its subtypes from healthy controls with an AUC ranging from 0.827 to 0. 947. By comparing urine samples with matching plasma CEA from NSCLC stage I-IV patients (n = 81) and healthy controls (n = 31), the combination of CEA with PLG or FGG showed that the AUC was 0.889 and 0.806, respectively, which is superior to a single biomarker alone.

CONCLUSIONS

These two urinary proteins could serve as potential markers for the diagnosis of NSCLC.

MT1G serves as a tumor suppressor in hepatocellular carcinoma by interacting with p53

Poor prognosis of hepatocellular carcinoma (HCC) patients is frequently associated with rapid tumor growth, recurrence and drug resistance. MT1G is a low-molecular weight protein with high affinity for zinc ions. In the present study, we investigated the expression of MT1G, analyzed clinical significance of MT1G, and we observed the effects of MT1G overexpression on proliferation and apoptosis of HCC cell lines in vitro and in vivo. Our results revealed that MT1G was significantly downregulated in tumor tissues, and could inhibit the proliferation as well as enhance the apoptosis of HCC cells. The mechanism study suggested that MT1G increased the stability of p53 by inhibiting the expression of its ubiquitination factor, MDM2. Furthermore, MT1G also could enhance the transcriptional activity of p53 through direct interacting with p53 and providing appropriate zinc ions to p53. The modulation of MT1G on p53 resulted in upregulation of p21 and Bax, which leads cell cycle arrest and apoptosis, respectively. Our in vivo assay further confirmed that MT1G could suppress HCC tumor growth in nude mice. Overall, this is the first report on the interaction between MT1G and p53, and adequately uncover a new HCC suppressor which might have therapeutic values by diminishing the aggressiveness of HCC cells.