Diagnostic and prognostic significance of mRNA expressions of apolipoprotein A and C family genes in hepatitis B virus-related hepatocellular carcinoma

Integrative analysis of aging-related genes reveals CEBPA as a novel therapeutic target in non-small cell lung cancer

BACKGROUND

To explore the impact of ARGs on the prognosis of NSCLC, and its correlation with clinicopathological parameters and immune microenvironment. Preliminary research on the biological functions of CEBPA in NSCLC.

METHODS

Using consensus clustering analysis to identify molecular subtypes of ARGs in NSCLC patients; employing LASSO regression and multivariate Cox analysis to select 7 prognostic risk genes and construct a prognostic risk model; validating independent prognostic factors of NSCLC using forest plot analysis; analyzing immune microenvironment correlations using ESTIMATE and ssGSEA; assessing correlations between prognostic risk genes via qPCR and Western blot in NSCLC; measuring mRNA and protein expression levels of knocked down and overexpressed CEBPA in NSCLC using CCK-8 and EdU assays; evaluating the effects of knocked down and overexpressed CEBPA on cell proliferation using Transwell experiments; examining the correlation of CEBPA with T cells and B cells using mIHC analysis.

RESULTS

Consensus clustering analysis identified three molecular subtypes, suggesting significant differential expression of these ARGs in NSCLC prognosis and clinical pathological parameters. There was significant differential expression between the two risk groups in the prognostic risk model, with P < 0.001. The risk score of the prognostic risk model was also P < 0.001. CEBPA exhibited higher mRNA and protein expression levels in NSCLC cell lines. Knockdown of CEBPA significantly reduced mRNA and protein expression levels of CEBPB, YWHAZ, ABL1, and CDK1 in H1650 and A549 cells. siRNA-mediated knockdown of CEBPA markedly inhibited proliferation, migration, and invasion of NSCLC cells, whereas overexpression of CEBPA showed the opposite trend. mIHC results indicated a significant increase in CD3 + CD4+, CD3 + CD8+, and CD20 + cell counts in the high CEBPA expression group.

CONCLUSIONS

The risk score of the prognostic risk model can serve as an independent prognostic factor, guiding the diagnosis and treatment of NSCLC. CEBPA may serve as a potential tumor biomarker and immune target, facilitating further exploration of the biological functions and immunological relevance in NSCLC.

Lactylated Apolipoprotein C-II Induces Immunotherapy Resistance by Promoting Extracellular Lipolysis

Mortality rates due to lung cancer are high worldwide. Although PD-1 and PD-L1 immune checkpoint inhibitors boost the survival of patients with non-small-cell lung cancer (NSCLC), resistance often arises. The Warburg Effect, which causes lactate build-up and potential lysine-lactylation (Kla), links immune dysfunction to tumor metabolism. The role of non-histone Kla in tumor immune microenvironment and immunotherapy remains to be clarified. Here, global lactylome profiling and metabolomic analyses of samples from patients with NSCLC is conducted. By combining multi-omics analysis with in vitro and in vivo validation, that intracellular lactate promotes extracellular lipolysis through lactyl-APOC2 is revealed. Mechanistically, lactate enhances APOC2 lactylation at K70, stabilizing it and resulting in FFA release, regulatory T cell accumulation, immunotherapy resistance, and metastasis. Moreover, the anti-APOC2K70-lac antibody that sensitized anti-PD-1 therapy in vivo is developed. This findings highlight the potential of anti lactyl-APOC2-K70 approach as a new combination therapy for sensitizing immunotherapeutic responses.

Serum apolipoprotein B to apolipoprotein A-I ratio predicts mortality in patients with heart failure

AIMS

Apolipoproteins have been reported to be involved in many cardiovascular diseases. The aim of our study was to investigate the prognostic value of apolipoprotein B (ApoB) to apolipoprotein A-I (ApoA-I) ratio (ApoB/ApoA-I) in patients with heart failure (HF).

METHODS AND RESULTS

We randomly assigned 2400 HF patients into the training cohort (n = 1400) and the validation cohort (n = 1000). Using a receiver operating characteristic curve, we identified the optimal cut-off value of the ApoB/ApoA-I in the training cohort as 0.69, which was further validated in the validation cohort. A propensity score matching (PSM) analysis was conducted to eliminate the imbalance in the baseline characteristics of the high and low ApoB/ApoA-I group. A total of 2242 HF patients were generated in the PSM cohort. We also validated our results with an independent cohort (n = 838). Univariate and multivariate analyses were conducted to explore the independent prognostic value of ApoB/ApoA-I in the training cohort (n = 1400), the validation cohort (n = 1000), the PSM cohort (n = 2242), and the independent cohort (n = 838). Patients with high ApoB/ApoA-I ratio had significantly poorer prognosis compared with those with low ApoB/ApoA-I ratio in the training cohort, the validation cohort, the PSM cohort, and the independent cohort (P < 0.05). Multivariate analysis indicated that the ApoB/ApoA-I was an independent prognostic factor for HF in the training cohort [hazard ratio (HR) = 1.637, 95% confidence interval (CI) = 1.201-2.231, P = 0.002], the validation cohort (HR = 1.54, 95% CI = 1.051-2.257, P = 0.027), the PSM cohort (HR = 1.645, 95% CI = 1.273-2.125, P < 0.001), and the independent cohort (HR = 1.987, 95% CI = 1.251-3.155, P = 0.004).

CONCLUSIONS

Serum ApoB/ApoA-I ratio is an independent predictor for the prognosis of HF patients.

Lipids, cholesterols, statins and liver cancer: a Mendelian randomization study

Aim

To investigate the causal relationship of serum lipid indicators and lipid-lowering drugs with the risk of liver cancer using Mendelian randomization study.

Methods

A two-sample Mendelian randomization (TSMR) study was performed to investigate the causal relationship between serum levels of lipid indicators and liver cancer, including low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), triglycerides (TG), total cholesterol (TC), Apolipoprotein B (ApoB), and Apolipoprotein A1 (ApoA1).Furthermore, instrumental variable weighted regression (IVW) and summary data-based MR (SMR) analyses were performed to investigate the causal effects of lipid-lowering drugs, including statins and PCSK9 inhibitors, on the risk of liver cancer.

Results

Serum LDL-c and serum TC levels showed negatively associated with liver cancer (n = 22 SNPs, OR = 0.363, 95% CI = 0.231 - 0.570; p = 1.070E-5) (n = 83 SNPs; OR = 0.627, 95% CI = 0.413-0.952; p = 0.028). However, serum levels of TG, HDL-c, and ApoA1 did not show any significant correlation with liver cancer. In the drug target MR (DMR) analyses, HMGCR-mediated level of LDL-c showed an inverse relationship with the risk of liver cancer in the IVW-MR analysis (n = 5 SNPs, OR = 0.201, 95% CI = 0.064 - 0.631; p = 5.95E-03) and SMR analysis (n = 20 SNPs, OR = 0.245, 95% CI = 0.065 - 0.926; p = 0.038) However, PCSK9 did not show any significant association with liver cancer based on both the IVW-MR and SMR analyses.

Conclusion

Our results demonstrated that reduced levels of LDL-c and TC were associated with an increased risk of liver cancer. Furthermore, lipid-lowering drugs targeting HMGCR such as statins were associated with increased risk of liver cancer.

Establishment and Clinical Application of the Nomogram Related to Risk or Prognosis of Hepatocellular Carcinoma: A Review

Hepatocellular carcinoma (HCC) is the most prevalent primary liver malignancy, accounting for approximately 90% of all primary liver cancers, with high mortality and a poor prognosis. A large number of predictive models have been applied that integrate multiple clinical factors and biomarkers to predict the prognosis of HCC. Nomograms, as easy-to-use prognostic predictive models, are widely used to predict the probability of clinical outcomes. We searched PubMed with the keywords "hepatocellular carcinoma" and "nomogram", and 974 relative literatures were retrieved. According to the construction methodology and the real validity of the nomograms, in this study, 97 nomograms for HCC were selected in 77 publications. These 97 nomograms were established based on more than 100,000 patients, covering seven main prognostic outcomes. The research data of 56 articles are from hospital-based HCC patients, and 13 articles provided external validation results of the nomogram. In addition to AFP, tumor size, tumor number, stage, vascular invasion, age, and other common prognostic risk factors are included in the HCC-related nomogram, more and more biomarkers, including gene mRNA expression, gene polymorphisms, and gene signature, etc. were also included in the nomograms. The establishment, assessment and validation of these nomograms are also discussed in depth. This study would help clinicians construct and select appropriate nomograms to guide precise judgment and appropriate treatments.

Identification of cholesterol metabolism-related subtypes in nonfunctioning pituitary neuroendocrine tumors and analysis of immune infiltration

OBJECTIVE

This study aimed to investigate the role of cholesterol metabolism-related genes in nonfunctioning pituitary neuroendocrine tumors (NF-PitNETs) invading the cavernous sinus and analyze the differences in immune cell infiltration between invasive and noninvasive NF-PitNETs.

METHODS

First, a retrospective analysis of single-center clinical data was performed. Second, the immune cell infiltration between invasive and noninvasive NF-PitNETs in the GSE169498 dataset was further analyzed, and statistically different cholesterol metabolism-related gene expression matrices were obtained from the dataset. The hub cholesterol metabolism-related genes in NF-PitNETs were screened by constructing machine learning models. In accordance with the hub gene, 73 cases of NF-PitNETs were clustered into two subtypes, and the functional differences and immune cell infiltration between the two subtypes were further analyzed.

RESULTS

The clinical data of 146 NF-PitNETs were evaluated, and the results showed that the cholesterol (P = 0.034) between invasive and noninvasive NF-PitNETs significantly differed. After binary logistic analysis, cholesterol was found to be an independent risk factor for cavernous sinus invasion (CSI) in NF-PitNETs. Bioinformatics analysis found three immune cells between invasive and noninvasive NF-PitNETs were statistically significant in the GSE169498 dataset, and 34 cholesterol metabolism-related genes with differences between the two groups were obtained 12 hub genes were selected by crossing the two machine learning algorithm results. Subsequently, cholesterol metabolism-related subgroups, A and B, were obtained by unsupervised hierarchical clustering analysis. The results showed that 12 immune cells infiltrated differentially between the two subgroups. The chi-square test revealed that the two subgroups had statistically significance in the invasive and noninvasive samples (P = 0.001). KEGG enrichment analysis showed that the differentially expressed genes were mainly enriched in the neural ligand-receptor pathway. GSVA analysis showed that the mTORC signaling pathway was upregulated and played an important role in the two-cluster comparison.

CONCLUSION

By clinical data and bioinformatics analysis, cholesterol metabolism-related genes may promote the infiltration abundance of immune cells in NF-PitNETs and the invasion of cavernous sinuses by NF-PitNETs through the mTOR signaling pathway. This study provides a new perspective to explore the pathogenesis of cavernous sinus invasion by NF-PitNETs and determine potential therapeutic targets for this disease.

Hepatocellular carcinoma cell differentiation trajectory predicts immunotherapy, potential therapeutic drugs, and prognosis of patients

The aim of this study is to explore a novel classification and investigate the clinical significance of hepatocellular carcinoma (HCC) cells. We analyzed integrated single-cell RNA sequencing and bulk RNA-seq data obtained from HCC samples. Cell trajectory analysis divided HCC cells into three subgroups with different differentiation states: state 1 was closely related to phosphoric ester hydrolase activity, state 2 was involved in eukaryotic initiation factor 4E binding, translation regulator activity and ribosome, and state 3 was associated with oxidoreductase activity and metabolism. Three molecular classes based on HCC differentiation-related genes (HDRGs) from HCC samples were identified, which revealed immune checkpoint gene expression and overall survival (OS) of HCC patients. Moreover, a prognostic risk scoring (RS) model was generated based on eight HDRGs, and the results showed that the OS of the high-risk group was worse than that of the low-risk group. Further, potential therapeutic drugs were screened out based on eight prognostic RS-HDRGs. This study highlights the importance of HCC cell differentiation in immunotherapy, clinical prognosis, and potential molecular-targeted drugs for HCC patients, and proposes a direction for the development of individualized treatments for HCC.

Multi-region sampling with paired sample sequencing analyses reveals sub-groups of patients with novel patient-specific dysregulation in Hepatocellular Carcinoma

BACKGROUND

Conventional differential expression (DE) testing compares the grouped mean value of tumour samples to the grouped mean value of the normal samples, and may miss out dysregulated genes in small subgroup of patients. This is especially so for highly heterogeneous cancer like Hepatocellular Carcinoma (HCC).

METHODS

Using multi-region sampled RNA-seq data of 90 patients, we performed patient-specific differential expression testing, together with the patients' matched adjacent normal samples.

RESULTS

Comparing the results from conventional DE analysis and patient-specific DE analyses, we show that the conventional DE analysis omits some genes due to high inter-individual variability present in both tumour and normal tissues. Dysregulated genes shared in small subgroup of patients were useful in stratifying patients, and presented differential prognosis. We also showed that the target genes of some of the current targeted agents used in HCC exhibited highly individualistic dysregulation pattern, which may explain the poor response rate.

DISCUSSION/CONCLUSION

Our results highlight the importance of identifying patient-specific DE genes, with its potential to provide clinically valuable insights into patient subgroups for applications in precision medicine.

Apolipoproteins: New players in cancers

Apolipoproteins (APOs), the primary protein moiety of lipoproteins, are known for their crucial role in lipid traffic and metabolism. Despite extensive exploration of APOs in cardiovascular diseases, their roles in cancers did not attract enough attention. Recently, research focusing on the roles of APOs in cancers has flourished. Multiple studies demonstrate the interaction of APOs with classical pathways of tumorigenesis. Besides, the dysregulation of APOs may indicate cancer occurrence and progression, thus serving as potential biomarkers for cancer patients. Herein, we summarize the mechanisms of APOs involved in the development of various cancers, their applications as cancer biomarkers and their genetic polymorphism associated with cancer risk. Additionally, we also discuss the potential anti-cancer therapies by virtue of APOs. The comprehensive review of APOs in cancers may advance the understanding of the roles of APOs in cancers and their potential mechanisms. We hope that it will provide novel clues and new therapeutic strategies for cancers.

Screening for Lipid-Metabolism-Related Genes and Identifying the Diagnostic Potential of ANGPTL6 for HBV-Related Early-Stage Hepatocellular Carcinoma

Lipid metabolic reprogramming is one of the hallmarks of hepatocarcinogenesis and development. Therefore, lipid-metabolism-related genes may be used as potential biomarkers for hepatocellular carcinoma (HCC). This study aimed to screen for genes with dysregulated expression related to lipid metabolism in HCC and explored the clinical value of these genes. We screened differentially expressed proteins between tumorous and adjacent nontumorous tissues of hepatitis B virus (HBV)-related HCC patients using a Nanoscale Liquid Chromatography–Tandem Mass Spectrometry platform and combined it with transcriptomic data of lipid-metabolism-related genes from the GEO and HPA databases to identify dysregulated genes that may be involved in lipid metabolic processes. The potential clinical values of these genes were explored by bioinformatics online analysis tools (GEPIA, cBioPortal, SurvivalMeth, and TIMER). The expression levels of the secreted protein (angiopoietin-like protein 6, ANGPTL6) in serum were analyzed by ELISA. The ability of serum ANGPTL6 to diagnose early HCC was assessed by ROC curves. The results showed that serum ANGPTL6 could effectively differentiate between HBV-related early HCC patients with normal serum alpha-fetoprotein (AFP) levels and the noncancer group (healthy participants and chronic hepatitis B patients) (AUC = 0.717, 95% CI: from 0.614 to 0.805). Serum ANGPTL6 can be used as a potential second-line biomarker to supplement serum AFP in the early diagnosis of HBV-related HCC.

Leveraging knowledge of HDLs major protein ApoA1: Structure, function, mutations, and potential therapeutics

Apolipoprotein A1 (ApoA1) is a member of the Apolipoprotein family of proteins. It's a vital protein that helps in the production of high-density lipoprotein (HDL) particles, which are crucial for reverse cholesterol transport (RCT). It also has anti-inflammatory, anti-atherogenic, anti-apoptotic, and anti-thrombotic properties. These functions interact to give HDL particles their cardioprotective characteristics. ApoA1 has recently been investigated for its potential role in atherosclerosis, diabetes, neurological diseases, cancer, and certain infectious diseases. Since ApoA1's discovery, numerous mutations have been reported that affect its structural integrity and alter its function. Hence these insights have led to the development of clinically relevant peptides and synthetic reconstituted HDL (rHDL) that mimics the function of ApoA1. As a result, this review has aimed to provide an organized explanation of our understanding of the ApoA1 protein structure and its role in various essential pathways. Furthermore, we have comprehensively reviewed the important ApoA1 mutations (24 mutations) that are reported to be involved in various diseases. Finally, we've focused on the therapeutic potentials of some of the beneficial mutations, small peptides, and synthetic rHDL that are currently being researched or developed, since these will aid in the development of novel therapeutics in the future.

Plasma Proteomic Analysis Distinguishes Severity Outcomes of Human Ebola Virus Disease

Ebola virus (EBV) disease (EVD) is a highly virulent systemic disease characterized by an aggressive systemic inflammatory response and impaired vascular and coagulation systems, often leading to uncontrolled hemorrhaging and death. In this study, the proteomes of 38 sequential plasma samples from 12 confirmed EVD patients were analyzed. Of these 12 cases, 9 patients received treatment with interferon beta 1a (IFN-β-1a), 8 survived EVD, and 4 died; 2 of these 4 fatalities had received IFN-β-1a. Our analytical strategy combined three platforms targeting different plasma subproteomes: a liquid chromatography-mass spectrometry (LC-MS)-based analysis of the classical plasma proteome, a protocol that combines the depletion of abundant plasma proteins and LC-MS to detect less abundant plasma proteins, and an antibody-based cytokine/chemokine multiplex assay. These complementary platforms provided comprehensive data on 1,000 host and viral proteins. Examination of the early plasma proteomes revealed protein signatures that differentiated between fatalities and survivors. Moreover, IFN-β-1a treatment was associated with a distinct protein signature. Next, we examined those proteins whose abundances reflected viral load measurements and the disease course: resolution or progression. Our data identified a prognostic 4-protein biomarker panel (histone H1-5, moesin, kininogen 1, and ribosomal protein L35 [RPL35]) that predicted EVD outcomes more accurately than the onset viral load. IMPORTANCE As evidenced by the 2013-2016 outbreak in West Africa, Ebola virus (EBV) disease (EVD) poses a major global health threat. In this study, we characterized the plasma proteomes of 12 individuals infected with EBV, using two different LC-MS-based proteomics platforms and an antibody-based multiplexed cytokine/chemokine assay. Clear differences were observed in the host proteome between individuals who survived and those who died, at both early and late stages of the disease. From our analysis, we derived a 4-protein prognostic biomarker panel that may help direct care. Given the ease of implementation, a panel of these 4 proteins or subsets thereof has the potential to be widely applied in an emergency setting in resource-limited regions.

Single-Cell Sequencing of Hepatocellular Carcinoma Reveals Cell Interactions and Cell Heterogeneity in the Microenvironment

BACKGROUND

Hepatocellular carcinoma (HCC) is the main histological subtype of liver cancer, which has the characteristics of poor prognosis and high fatality rate. Single-cell sequencing can provide quantitative and unbiased characterization of cell heterogeneity by analyzing the molecular profile of the whole genome of thousands of single cells. Thus, the purpose of this study was to identify novel prognostic markers for HCC based on single-cell sequencing data.

METHODS

Single-cell sequencing of 21 HCC samples and 256 normal liver tissue samples in the GSE124395 dataset was collected from the Gene Expression Omnibus (GEO) database. The quality-controlled cells were grouped by unsupervised cluster analysis and identified the marker genes of each cell cluster. Hereafter, these cell clusters were annotated by singleR and CellMarker according to the expression patterns of the marker genes. Pseudotime analysis was performed to construct the trajectory of cell evolution and to define hub genes in the evolution process. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to explore the potential regulatory mechanism of hub genes in HCC. Next, the differential expression of hub genes and the correlation of the expression of these genes with patients' survival and diagnosis were investigated in The Cancer Genome Atlas (TCGA) database.

RESULTS

A total of 9 clusters corresponding to 9 cell types, including NKT cells, hepatocytes, endothelial cells, Kupffer cells, EPCAM+ cells, cancer cells, plasma cells (B cells), immature B cells, and myofibroblasts were identified. We screened 63 key genes related to cell differentiation through trajectory analysis, which were enriched in the process of coagulation. Ultimately, we identified 10 survival-related hub genes in the TCGA database, namely ALDOB, APOC3, APOH, CYP2E1, CYP3A4, GC, HRG, LINC01554, PDK4, and TXN.

CONCLUSION

In conclusion, ALDOB, APOC3, APOH, CYP2E1, CYP3A4, GC, HRG, LINC01554, PDK4, and TXN may serve as hub genes in the diagnosis and prognosis for HCC.

Investigation of Specific Proteins Related to Different Types of Coronary Atherosclerosis

Objective: Coronary heart disease (CHD) is a complex disease caused by multifaceted interaction between genetic and environmental factors, which makes identification of the most likely disease candidate proteins and their associated risk markers a big challenge. Atherosclerosis is presented by a broad spectrum of heart diseases, including stable coronary artery disease (SCAD) and acute myocardial infarction (AMI), which is the progressive stage of SCAD. As such, the correct and prompt diagnosis of atherosclerosis turns into imperative for precise and prompt disease diagnosis, treatment and prognosis. Methods: The current work aims to look for specific protein markers for differential diagnosis of coronary atherosclerosis. Thirty male patients between 45 and 55 years diagnosed with atherosclerosis were analyzed by tandem mass tag (TMT) mass spectrometry. The study excluded those who were additionally diagnosed with hypertension and type 1 and 2 diabetes. The Mufuzz analysis was applied to select target proteins for precise and prompt diagnosis of atherosclerosis, most of which were most related to high lipid metabolism. The parallel reaction monitoring (PRM) was used to verify the selected target proteins. Finally, The receiver operating characteristic curve (ROC) was calculated by a random forest experiment. Results: One thousand one hundred and forty seven proteins were identified in the TMT mass spectrometry, 907 of which were quantifiable. In the PRM study, six proteins related to lipid metabolism pathway were selected for verification and they were ALB, SHBG, APOC2, APOC3, APOC4, SAA4. Conclusion: Through the detected specific changes in these six proteins, our results provide accuracy in atherosclerosis patients' diagnosis, especially in cases with varying types of the disease.

An Aging-Related Gene Signature-Based Model for Risk Stratification and Prognosis Prediction in Lung Adenocarcinoma

Aging is an inevitable time-dependent process associated with a gradual decline in many physiological functions. Importantly, some studies have supported that aging may be involved in the development of lung adenocarcinoma (LUAD). However, no studies have described an aging-related gene (ARG)-based prognosis signature for LUAD. Accordingly, in this study, we analyzed ARG expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). After LASSO and Cox regression analyses, a six ARG-based signature (APOC3, EPOR, H2AFX, MXD1, PLCG2, and YWHAZ) was constructed using TCGA dataset that significantly stratified cases into high- and low-risk groups in terms of overall survival (OS). Cox regression analysis indicated that the ARG signature was an independent prognostic factor in LUAD. A nomogram based on the ARG signature and clinicopathological factors was developed in TCGA cohort and validated in the GEO dataset. Moreover, to visualize the prediction results, we established a web-based calculator yurong.shinyapps.io/ARGs_LUAD/. Calibration plots showed good consistency between the prediction of the nomogram and actual observations. Receiver operating characteristic curve and decision curve analyses indicated that the ARG nomogram had better OS prediction and clinical net benefit than the staging system. Taken together, these results established a genetic signature for LUAD based on ARGs, which may promote individualized treatment and provide promising novel molecular markers for immunotherapy.

Identification of docetaxel-related biomarkers for prostate cancer

Prostate cancer (PCa) which was the second commonly diagnosed malignancy, contributed to the top fifth carcinoma death in men. Nevertheless, the main chemotherapeutic agent docetaxel came to failure due to chemoresistance. Recently, increasing evidence suggested the importance of tumour microenvironment (TME) in PCa. The present study aimed to explore the specific TME in PCa and find biomarkers related to both immune infiltration and docetaxel. The docetaxel-specific genes and differential expression genes comparing PCa with normal control samples were derived using DESeq2 and zinbwave with GSE140440, TCGA and GTEx datasets. Immune-infiltration-related genes were identified using CIBERSORT and co-expression network analysis. Key genes related to both docetaxel and immune infiltrating in PCa, including nine genes, namely ZNF486, IFI6, TMOD2, HSPA4L, ITPR1, LRRC37A7P, APOC1, APOBEC3G, and ITGA2, were determined by overlapping above three gene sets. ITGA2 was then defined as the hub gene for its significant prognostic implications. Further validations conducted on Oncomine, GEO, TISIDB, MSigDB, and The Human Protein Atlas confirmed the docetaxel-specific and immune infiltrating characteristics of ITGA2. To sum up, our findings could provide a better understanding of immune infiltrating and docetaxel-resistance in PCa, mostly, ITGA2 could serve as potential prognosis biomarkers and targets for the combination of docetaxel.

Varied clinical significance of ATP-binding cassette C sub-family members for lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a lethal malignancy worldwide and a major public health concern. We explored the potential clinical significance for LUAD of ATP-binding cassette (ABC), sub-family C, consisting of ABCC1-6, 8-12, and cystic fibrosis transmembrane conductance regulator (CFTR).Five hundred LUAD patients from The Cancer Genome Atlas database were used for analysis, including differential expression and diagnostic and prognostic significance. Oncomine and MERAV databases were used to validate differential expression and diagnostic significance. A risk score model was constructed using prognosis-related ABCC members. Prognosis-related genes were further explored to correlate their expression with tumor stage progression. Interaction networks, including biological processes and metabolic pathways, were constructed using Cytoscape software and STRING website.ABCC1-3 consistently showed high expression in tumor tissues (all P ≤ 0.05). Most datasets indicated that ABCC5, 10, and 11 were highly expressed in tumor tissues whereas ABCC6, 9, and CFTR were highly expressed in nontumor tissues (all P ≤ 0.05). Diagnostic significance of ABCC3 and ABCC5 was consistently assessed and validated in three datasets (all area under the curve > 0.700) whereas ABCC6, 8, 10, 11, and CFTR were assessed in The Cancer Genome Atlas dataset and validated in one dataset (all area under the curve > 0.700). Prognostic analysis indicated that ABCC2, 6, and 8 mRNA expression was associated with survival of LUAD (all adjusted P ≤ .037). The risk score model constructed using ABCC2, 6, and 8 suggested prognostic significance for survival predictions. ABCC2 expression was associated with tumor stage, whereas ABCC6 and 8 were not. Interaction networks indicated that they were involved in establishment of localization, ion transport, plasma membrane, apical plasma membrane, adenylyl nucleotide binding, ABC transporters, ABC transporter disorders, ABC-family-protein-mediated transport, and bile secretion.Differentially expressed ABCC2 and ABCC5 might be diagnostic whereas ABCC2, 6, and 8 may be prognostic biomarkers for LUAD, possibly through ABC-family-mediated transporter disorders.

Neutrophil-to-Apolipoprotein A1 Ratio Predicted Overall Survival in Hepatocellular Carcinoma Receiving Transarterial Chemoembolization

PURPOSE

The purpose of this study was to investigate the predictive capability of neutrophil-to-apolipoprotein A1 ratio (NAR) for predicting overall survival (OS) among patients with hepatocellular carcinoma (HCC) receiving transarterial chemoembolization (TACE).

PATIENTS AND METHODS

We investigated the clinical features of 554 patients with HCC receiving TACE and assessed NAR's predictive value for OS with 222 patients (the discovery cohort) and 332 patients (the validation cohort). The association of NAR with circulation lectin-type oxidized low-density lipoprotein receptor-1-positive (LOX-1⁺ ) polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) was illustrated.

RESULTS

Multivariate Cox regression revealed that lymphocyte count; Tumor, Node, Metastasis (TNM) stage; and NAR were independent prognostic factors in the discovery cohort. The validation cohort confirmed the independent prognostic value of TNM stage and NAR. Patients with low NAR (<2.7) displayed significantly increased OS in the discovery cohort (59.8 months vs. 21 months), the validation group (38.0 months vs. 23.6 months), and the total cohort (44.1 months vs. 22.0 months). A Cox proportional hazards model was used to combine Cancer of the Liver Italian Program (CLIP) score with discretized NAR. C-index illustrated that NAR-integrated CLIP score was the best model compared with NAR and CLIP score. Furthermore, NAR-CLIP presented superior predictive capacity for 10-, 20-, 30-, 40-, 50-, and 60-month survival compared with CLIP score by survival receiver-operator characteristic analysis in the discovery cohort, validation cohort, and total cohort. NAR was significantly associated with LOX-1⁺ PMN-MDSCs by linear regression.

CONCLUSION

This study identified NAR as an independent predictor for OS among patients with HCC receiving TACE. NAR reflected circulation LOX-1⁺ PMN-MDSC level.

IMPLICATIONS FOR PRACTICE

The present study identified neutrophil-to-apolipoprotein A1 ratio (NAR) as an independent predictor for overall survival among patients with hepatocellular carcinoma receiving transarterial chemoembolization. NAR reflected circulation level of lectin-type oxidized low-density lipoprotein receptor-1-positive polymorphonuclear myeloid-derived suppressor cells.

ApoC1 promotes the metastasis of clear cell renal cell carcinoma via activation of STAT3

Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer and frequently diagnosed at an advanced stage. It is prone to develop unpredictable metastases even with proper treatment. Antiangiogenic therapy is the most effective medical treatment for metastatic ccRCC. Thus, exploration of novel approaches to inhibit angiogenesis and metastasis may potentially lead to a better therapeutic option for ccRCC. Among all the types of cancer, renal cancer samples exhibited the maximum upregulation of ApoC1 as referred to in the Oncomine database. The expression of ApoC1 was increased accompanied by ccRCC progression. A high level of ApoC1 was closely related to poor survival time in ccRCC patients. Furthermore, ApoC1 was over-expressed in the highly invasive ccRCC cells as compared to that in the low-invasive ccRCC cells. Besides, ApoC1 promoted metastasis of ccRCC cells via EMT pathway, whereas depletion of ApoC1 alleviated these effects. ApoC1 as a novel pro-metastatic factor facilitates the activation of STAT3 and enhances the metastasis of ccRCC cells. Meanwhile, ApoC1 in the exosomes were transferred from the ccRCC cells to the vascular endothelial cells and promoted metastasis of the ccRCC cells via activating STAT3. Finally, the metastatic potential of the ccRCC cells driven by ApoC1 was suppressed by DPP-4 inhibition. Our study not only identifies a novel ApoC1-STAT3 pathway in ccRCC metastasis but also provides direction for the exploration of novel strategies to predict and treat metastatic ccRCC in the future.

Sorafenib-Conjugated Zinc Phthalocyanine Based Nanocapsule for Trimodal Therapy in an Orthotopic Hepatocellular Carcinoma Xenograft Mouse Model

Sorafenib, a multitargeted kinase inhibitor, has been reported to elicit a limited therapeutic effect in hepatocellular carcinoma (HCC). Currently, phototherapy, including photodynamic therapy (PDT) and photothermal therapy (PTT), is emerging as a powerful modality for cancer therapy. However, few studies have been reported the effectiveness of the combination of sorafenib with PDT and PTT in HCC. Herein, we designed and synthesized bovine serum albumin (BSA)-coated zinc phthalocyanine (ZnPc) and sorafenib (SFB) nanoparticle (ZnPc/SFB@BSA). The obtained ZnPc/SFB@BSA was able to trigger PDT, PTT, and chemotherapy. After irradiation by a 730 nm light, ZnPc/SFB@BSA significantly suppressed HCC cell proliferation and metastasis while promoted cell apoptosis in vitro. Furthermore, intravenous injection of ZnPc/SFB@BSA led to dramatically reduced tumor growth in an orthotopic xenograft HCC model. More importantly, ZnPc/SFB@BSA presented low toxicity and adequate blood compatibility. Therefore, a combination of ZnPc with sorafenib via BSA-assembled nanoparticle can markedly suppress HCC growth, representing a promising strategy for HCC patients.

Apolipoprotein C1: Its Pleiotropic Effects in Lipid Metabolism and Beyond

Apolipoprotein C1 (apoC1), the smallest of all apolipoproteins, participates in lipid transport and metabolism. In humans, APOC1 gene is in linkage disequilibrium with APOE gene on chromosome 19, a proximity that spurred its investigation. Apolipoprotein C1 associates with triglyceride-rich lipoproteins and HDL and exchanges between lipoprotein classes. These interactions occur via amphipathic helix motifs, as demonstrated by biophysical studies on the wild-type polypeptide and representative mutants. Apolipoprotein C1 acts on lipoprotein receptors by inhibiting binding mediated by apolipoprotein E, and modulating the activities of several enzymes. Thus, apoC1 downregulates lipoprotein lipase, hepatic lipase, phospholipase A2, cholesterylester transfer protein, and activates lecithin-cholesterol acyl transferase. By controlling the plasma levels of lipids, apoC1 relates directly to cardiovascular physiology, but its activity extends beyond, to inflammation and immunity, sepsis, diabetes, cancer, viral infectivity, and-not last-to cognition. Such correlations were established based on studies using transgenic mice, associated in the recent years with GWAS, transcriptomic and proteomic analyses. The presence of a duplicate gene, pseudogene APOC1P, stimulated evolutionary studies and more recently, the regulatory properties of the corresponding non-coding RNA are steadily emerging. Nonetheless, this prototypical apolipoprotein is still underexplored and deserves further research for understanding its physiology and exploiting its therapeutic potential.