Apolipoproteins as Differentiating and Predictive Markers for Assessing Clinical Outcomes in Patients with Small Cell Lung Cancer

Serum Lipid Levels, Genetic Risk, and Lung Cancer Incidence: A Large Prospective Cohort Study

BACKGROUND

Previous studies usually focused on the separate association of metabolism or genetic factors with lung cancer risk and have largely ignored their combined effect. We aimed to examine the associations between serum lipid levels, genetic risk, and lung cancer risk.

METHODS

A total of 426,524 participants of the UK Biobank were included. The Cox proportional hazards models and restricted cubic splines were performed to assess the association between serum lipid and lung cancer risk. Polygenic risk score (PRS) was constructed to assess its joint effect and interaction with serum lipid on lung cancer risk.

RESULTS

Higher level of apolipoprotein A was significantly correlated with lower lung cancer risk. An inverse-J-shaped relationship between high-density lipoprotein (HDL) and incident lung cancer was found. Individuals with low total cholesterol, HDL, low-density lipoprotein (LDL), apolipoprotein A, and apolipoprotein B, combined with high PRS, showed significantly elevated lung cancer risks. Compared to those with low PRS and low triglycerides, participants with high PRS and elevated triglyceride levels had a notably higher risk. The interaction effect of high PRS and low LDL [relative excess risk due to the interaction (RERI): 0.25, 95% confidence interval, 0.04-0.46], as well as the interaction effect of high PRS and low apolipoprotein B (RERI: 0.28, 95% confidence interval, 0.07-0.48), were both greater than the sum of their individual effects on lung cancer risk.

CONCLUSIONS

Serum lipids were associated with lung cancer risk. LDL or apolipoprotein B interacting with genetic risk may affect lung cancer risk.

IMPACT

Our findings emphasize the need for individuals with heightened genetic risk should pay more attention to their lipid levels to reduce lung cancer risk.

The roles and mechanisms of APOL1 in the development of colorectal cancer

Background

Research has demonstrated that apolipoprotein L1 (APOL1) has a role in the emergence and progression of a number of malignant cancers. It is unclear, however, how APOL1 functions in colorectal cancer (CRC). In this study, we examined the possible molecular processes underlying APOL1's biological role in CRC.

Methods

Quantitative real-time polymerase chain reaction (qRT-PCR) was used to identify APOL1 expression in patients with CRC and the cell line of cancer tissue. Following transfection of human colon carcinoma cells (HCT116) and human colon adenocarcinoma cells (SW1116) with sh-APOL1, the effects of APOL1 on the biological behavior of CRC cell lines were examined. In nude mice, the effect of APOL1 on tumor growth was noted. The protein interaction between APOL1 and RUNX1 was detected via coimmunoprecipitation. The expression of relevant proteins and cell biological behaviors were examined to confirm the APOL1-RUNX1 pathway in CRC cell lines.

Results

The CRC tissues and cells exhibited elevated expression of APOL1. HCT116 and SW1116 cells' proliferation, migration, and invasion were suppressed by sh-APOL1, and sh-APOL1 also increased the expression of E-cadherin and decreased the expression of RUNX1, cyclin D1, β-catenin, N-cadherin, and vimentin. APOL1 bound to the RUNX1 protein and regulated its protein levels. The counteractive effect of sh-APOL1 epithelial-mesenchymal transition (EMT), proliferation, migration, and invasion of CRC cells was counteracted by the overexpression of RUNX1. By silencing APOL1, the Wnt-β-catenin pathway was able to restrain EMT and regulate the biological behavior processes in CRC cells.

Conclusions

APOL1 has potential as a diagnostic biomarker for CRC. By preventing the Wnt-β-catenin pathway from being activated, the sh-APOL1-binding protein RUNX1 inhibited the EMT and biological behavior of CRC cells.

Progressions of the correlation between lipid metabolism and immune infiltration characteristics in gastric cancer and identification of BCHE as a potential biomarker

Background

Globally, gastric cancer (GC) is a category of prevalent malignant tumors. Its high occurrence and fatality rates represent a severe threat to public health. According to recent research, lipid metabolism (LM) reprogramming impacts immune cells' ordinary function and is critical for the onset and development of cancer. Consequently, the article conducted a sophisticated bioinformatics analysis to explore the potential connection between LM and GC.

Methods

We first undertook a differential analysis of the TCGA queue to recognize lipid metabolism-related genes (LRGs) that are differentially expressed. Subsequently, we utilized the LASSO and Cox regression analyses to create a predictive signature and validated it with the GSE15459 cohort. Furthermore, we examined somatic mutations, immune checkpoints, tumor immune dysfunction and exclusion (TIDE), and drug sensitivity analyses to forecast the signature's immunotherapy responses.

Results

Kaplan-Meier (K-M) curves exhibited considerably longer OS and PFS (p<0.001) of the low-risk (LR) group. PCA analysis and ROC curves evaluated the model's predictive efficacy. Additionally, GSEA analysis demonstrated that a multitude of carcinogenic and matrix-related pathways were much in the high-risk (HR) group. We then developed a nomogram to enhance its clinical practicality, and we quantitatively analyzed tumor-infiltrating immune cells (TIICs) using the CIBERSORT and ssGSEA algorithms. The low-risk group has a lower likelihood of immune escape and more effective in chemotherapy and immunotherapy. Eventually, we selected BCHE as a potential biomarker for further research and validated its expression. Next, we conducted a series of cell experiments (including CCK-8 assay, Colony formation assay, wound healing assay and Transwell assays) to prove the impact of BCHE on gastric cancer biological behavior.

Discussion

Our research illustrated the possible consequences of lipid metabolism in GC, and we identified BCHE as a potential therapeutic target for GC. The LRG-based signature could independently forecast the outcome of GC patients and guide personalized therapy.

Lipid-lowering drugs affect lung cancer risk via sphingolipid metabolism: a drug-target Mendelian randomization study

Background: The causal relationship between lipid-lowering drug (LLD) use and lung cancer risk is controversial, and the role of sphingolipid metabolism in this effect remains unclear. Methods: Genome-wide association study data on low-density lipoprotein (LDL), apolipoprotein B (ApoB), and triglycerides (TG) were used to develop genetic instrumental variables (IVs) for LLDs. Two-step Mendelian randomization analyses were performed to examine the causal relationship between LLDs and lung cancer risk. The effects of ceramide, sphingosine-1-phosphate (S1P), and ceramidases on lung cancer risk were explored, and the proportions of the effects of LLDs on lung cancer risk mediated by sphingolipid metabolism were calculated. Results: APOB inhibition decreased the lung cancer risk in ever-smokers via ApoB (odds ratio [OR] 0.81, 95% confidence interval [CI] 0.70-0.92, p = 0.010), LDL (OR 0.82, 95% CI 0.71-0.96, p = 0.040), and TG (OR 0.63, 95% CI 0.46-0.83, p = 0.015) reduction by 1 standard deviation (SD), decreased small-cell lung cancer (SCLC) risk via LDL reduction by 1 SD (OR 0.71, 95% CI 0.56-0.90, p = 0.016), and decreased the plasma ceramide level and increased the neutral ceramidase level. APOC3 inhibition decreased the lung adenocarcinoma (LUAD) risk (OR 0.60, 95% CI 0.43-0.84, p = 0.039) but increased SCLC risk (OR 2.18, 95% CI 1.17-4.09, p = 0.029) via ApoB reduction by 1 SD. HMGCR inhibition increased SCLC risk via ApoB reduction by 1 SD (OR 3.04, 95% CI 1.38-6.70, p = 0.014). The LPL agonist decreased SCLC risk via ApoB (OR 0.20, 95% CI 0.07-0.58, p = 0.012) and TG reduction (OR 0.58, 95% CI 0.43-0.77, p = 0.003) while increased the plasma S1P level. PCSK9 inhibition decreased the ceramide level. Neutral ceramidase mediated 8.1% and 9.5% of the reduced lung cancer risk in ever-smokers via ApoB and TG reduction by APOB inhibition, respectively, and mediated 8.7% of the reduced LUAD risk via ApoB reduction by APOC3 inhibition. Conclusion: We elucidated the intricate interplay between LLDs, sphingolipid metabolites, and lung cancer risk. Associations of APOB, APOC3, and HMGCR inhibition and LPL agonist with distinct lung cancer risks underscore the multifaceted nature of these relationships. The observed mediation effects highlight the considerable influence of neutral ceramidase on the lung cancer risk reduction achieved by APOB and APOC3 inhibition.

Identification of fibroblast-related genes based on single-cell and machine learning to predict the prognosis and endocrine metabolism of pancreatic cancer

Background

Single-cell sequencing technology has become an indispensable tool in tumor mechanism and heterogeneity studies. Pancreatic adenocarcinoma (PAAD) lacks early specific symptoms, and comprehensive bioinformatics analysis for PAAD contributes to the developmental mechanisms.

Methods

We performed dimensionality reduction analysis on the single-cell sequencing data GSE165399 of PAAD to obtain the specific cell clusters. We then obtained cell cluster-associated gene modules by weighted co-expression network analysis and identified tumorigenesis-associated cell clusters and gene modules in PAAD by trajectory analysis. Tumor-associated genes of PAAD were intersected with cell cluster marker genes and within the signature module to obtain genes associated with PAAD occurrence to construct a prognostic risk assessment tool by the COX model. The performance of the model was assessed by the Kaplan-Meier (K-M) curve and the receiver operating characteristic (ROC) curve. The score of endocrine pathways was assessed by ssGSEA analysis.

Results

The PAAD single-cell dataset GSE165399 was filtered and downscaled, and finally, 17 cell subgroups were filtered and 17 cell clusters were labeled. WGCNA analysis revealed that the brown module was most associated with tumorigenesis. Among them, the brown module was significantly associated with C11 and C14 cell clusters. C11 and C14 cell clusters belonged to fibroblast and circulating fetal cells, respectively, and trajectory analysis showed low heterogeneity for fibroblast and extremely high heterogeneity for circulating fetal cells. Next, through differential analysis, we found that genes within the C11 cluster were highly associated with tumorigenesis. Finally, we constructed the RiskScore system, and K-M curves and ROC curves revealed that RiskScore possessed objective clinical prognostic potential and demonstrated consistent robustness in multiple datasets. The low-risk group presented a higher endocrine metabolism and lower immune infiltrate state.

Conclusion

We identified prognostic models consisting of APOL1, BHLHE40, CLMP, GNG12, LOX, LY6E, MYL12B, RND3, SOX4, and RiskScore showed promising clinical value. RiskScore possibly carries a credible clinical prognostic potential for PAAD.

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.

Circulating Proteins Associated with Response and Resistance to Neoadjuvant Chemotherapy in HER2-Positive Breast Cancer

Simple Summary

The goal of this study was to find circulating proteins that can be easily sampled and incorporated into a clinical setting to improve predictive treatment response in HER2-positive breast cancer patients receiving neoadjuvant chemotherapy. We looked for potential biomarkers in serum, which we identified using two proteomics techniques: qualitative LC-MS/MS and a quantitative assay that assessed protein expression between responders and non-responders HER2-positive breast cancer patients to neoadjuvant chemotherapy.

Abstract

Despite the increasing use of neoadjuvant chemotherapy (NAC) in HER2-positive breast cancer (BC) patients, the clinical problem of predicting individual treatment response remains unanswered. Furthermore, the use of ineffective chemotherapeutic regimens should be avoided. Serum biomarker levels are being studied more and more for their ability to predict therapy response and aid in the development of personalized treatment regimens. This study aims to identify effective protein networks and biomarkers to predict response to NAC in HER2-positive BC patients through an exhaustive large-scale LC-MS/MS-based qualitative and quantitative proteomic profiling of serum samples from responders and non-responders. Serum samples from HER2-positive BC patients were collected before NAC and were processed by three methods (with and without nanoparticles). The qualitative analysis revealed differences in the proteomic profiles between responders and non-responders, mainly in proteins implicated in the complement and coagulation cascades and apolipoproteins. Qualitative analysis confirmed that three proteins (AFM, SERPINA1, APOD) were correlated with NAC resistance. In this study, we show that serum biomarker profiles can predict treatment response and outcome in the neoadjuvant setting. If these findings are further developed, they will be of significant clinical utility in the design of treatment regimens for individual BC patients.

Predictive value of preoperative platelet-to-albumin ratio and apolipoprotein B-to-apolipoprotein A1 ratio for osteosarcoma in children and adolescents: a retrospective study of 118 cases

Background

This retrospective study investigated biomarkers that can reflect coagulation, inflammation, and lipid abnormalities: platelet-to-albumin ratio (PAR), platelet-to lymphocyte ratio (PLR), low-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (LDL-C/HDL-C), apolipoprotein B-to-apolipoprotein ratio (ApoB/ApoA1) whether may be viable prognostic predictors in children and adolescents with osteosarcoma.

Methods

The retrospective review has enrolled a total of 118 children and adolescent patients diagnosed with osteosarcoma. Analyses with a receiver operating characteristic (ROC) curve were performed to evaluate the optimal cut-off values and to compare the area under curves (AUC). Kaplan–Meier curves were used to visualize survival outcome and a Cox proportional hazards model were used to confirm independent prognostic factors.

Results

Osteosarcoma patients in high PAR group (> 4.41) and high ApoB/ApoA1 group (> 0.82) experienced significantly shorter overall survival compared with those in low PAR group (≤ 4.41) and low ApoB/ApoA1 group (≤ 0.82). In univariate and multivariable analyses, preoperative PAR and ApoB/ApoA1 were identified as independent prognostic factors for OS in children and adolescents with osteosarcoma.

Conclusion

Preoperative PAR and ApoB/ApoA1 can be used as promising predictors in children and adolescents with osteosarcoma to help clinicians recognize patients with an increased risk of poor prognosis.

Circulating microvesicles and exosomes in small cell lung cancer by quantitative proteomics

BACKGROUND

Early detection of small cell lung cancer (SCLC) crucially demands highly reliable markers. Growing evidence suggests that extracellular vesicles carry tumor cell-specific cargo suitable as protein markers in cancer. Quantitative proteomic profiling of circulating microvesicles and exosomes can be a high-throughput platform for discovery of novel molecular insights and putative markers. Hence, this study aimed to investigate proteome dynamics of plasma-derived microvesicles and exosomes in newly diagnosed SCLC patients to improve early detection.

METHODS

Plasma-derived microvesicles and exosomes from 24 healthy controls and 24 SCLC patients were isolated from plasma by either high-speed- or ultracentrifugation. Proteins derived from these extracellular vesicles were quantified using label-free mass spectrometry and statistical analysis was carried out aiming at identifying significantly altered protein expressions between SCLC patients and healthy controls. Furthermore, significantly expressed proteins were subjected to functional enrichment analysis to identify biological pathways implicated in SCLC pathogenesis.

RESULTS

Based on fold change (FC) ≥ 2 or ≤ 0.5 and AUC ≥ 0.70 (p < 0.05), we identified 10 common and 16 and 17 unique proteins for microvesicles and exosomes, respectively. Among these proteins, we found dysregulation of coagulation factor XIII A (Log₂ FC =  - 1.1, p = 0.0003, AUC = 0.82, 95% CI: 0.69-0.96) and complement factor H-related protein 4 (Log₂ FC = 1.2, p = 0.0005, AUC = 0.82, 95% CI; 0.67-0.97) in SCLC patients compared to healthy individuals. Our data may indicate a novel tumor-suppressing role of blood coagulation and involvement of complement activation in SCLC pathogenesis.

CONCLUSIONS

In comparing SCLC patients and healthy individuals, several differentially expressed proteins were identified. This is the first study showing that circulating extracellular vesicles may encompass specific proteins with potential diagnostic attributes for SCLC, thereby opening new opportunities as novel non-invasive markers.

Quantitative Proteomics Analysis of Differentially Expressed Proteins in Serum of Former Uranium Miners by Isobaric Tags for the Relative and Absolute Quantitation

The carcinogenicity of radon has been convincingly documented through epidemiological studies of underground miners. However, there is a lack of early warning indicators for radon radiation damage. In this study, mixed serum samples of 3 groups were collected from 27 underground uranium miners and seven aboveground miners according to the radiation exposure dose. The differentially expressed proteins in the serum were identified using the isobaric tags for the relative and absolute quantitation (iTRAQ)-based method. Some differentially expressed proteins were validated by enzyme-linked immunosorbent assay (ELISA) in 84 underground and 32 aboveground miners. A total of 25 co-differentially expressed proteins in 2 underground miner groups were screened, of which 9 were downregulated and 13 were upregulated. Biological process analysis of these proteins using Metascape showed that 5 GO terms were enriched, such as negative regulation of very-low-density lipoprotein particle clearance, endocytosis, and regulated exocytosis. The results of the ELISA for the expression levels of GCN1, CIP2A, and IGHV1-24 in the serum of 116 miners’ serum showed that the levels of GCN1 and CIP2A were consistent with the iTRAQ results. In conclusion, APOC1, APOC2, APOC3, ORM1, ORM2, ANTXR1, GCN1, and CIP2A may be potential early markers of radon radiation damage.

Oncogene APOL1 promotes proliferation and inhibits apoptosis via activating NOTCH1 signaling pathway in pancreatic cancer

APOL1 encodes a secreted high-density lipoprotein, which has been considered as an aberrantly expressed gene in multiple cancers. Nevertheless, the role of APOL1 in the regulatory mechanisms of pancreatic cancer remains unknown and should be explored. We identified APOL1 was abnormally elevated in human pancreatic cancer tissues compared with that in adjacent tissues and was associated with poor prognosis. The effects of APOL1 in PC cell proliferation, cell cycle, and apoptosis was verified via functional in vitro and in vivo experiments. The results showed that knockdown of APOL1 significantly inhibited the proliferation and promoted apoptosis of pancreatic cancer. In addition, we identified APOL1 could be a regulator of NOTCH1 signaling pathway using bioinformatics tools, qRT-PCR, dual-luciferase reporter assay, and western blotting. In summary, APOL1 could function as an oncogene to promote proliferation and inhibit apoptosis through activating NOTCH1 signaling pathway expression in pancreatic cancer; therefore, it may act as a novel therapeutic target for pancreatic cancer.

[Correlation between Pretreatment Serum Apolipoprotein Level and Prognosis of Small Cell Lung Cancer Patients]

BACKGROUND

Lung cancer is the leading cause of cancer-related death, and small cell lung cancer (SCLC) has a poor prognosis in all types of lung cancer. This study evaluated the relationship between pretreatment serum apolipoprotein levels and prognosis in patients with SCLC, seeks a new index can guide diagnosis and treatment of SCLC.

METHODS

This study retrospectively analyzed the clinical data of 122 patients with SCLC. The clinical results of patients with serum apolipoprotein levels within 2 weeks before treatment were collected, including apolipoprotein AI (ApoA-I), apolipoprotein B (ApoB), and the ratio of apolipoprotein B to apolipoprotein AI (ApoB/ApoA-I). Patients' progression-free survival (PFS) and overall survival (OS) are the main outcome indicators. The best critical to determine the index's value by X-tile tool. For survival analysis, Kaplan-Meier method was used for analysis, and Cox regression analysis method was used for single factor analysis and multifactor analysis.

RESULTS

Compared with patients with low ApoA-I levels, patients with high ApoA-I levels (ApoA-I>1.12 g/L) had better OS (21.5 mon vs 12.3 mon, P=0.007) and PFS (7.3 mon vs 5.5 mon, P=0.017). In contrast, patients with higher ApoB/ApoA-I levels had worse median OS than patients with lower ApoB/ApoA-I levels (13.4 mon vs 20.7 mon, P=0.012). Multivariate Cox regression analysis showed that ApoA-I was an independent prognostic factor affecting PFS in SCLC patients (HR=0.67, 95%CI: 0.45-0.99, P=0.043). ApoB/ApoA-I is an independent risk factor for OS in patients with SCLC (HR=1.98, 95%CI: 1.21-3.23, P=0.007).

CONCLUSIONS

Serum ApoA-I level and ApoB/ApoA-I level before treatment can be important prognostic factors for SCLC, which is helpful to judge the prognosis of patients.

Proteomic Workflows for High-Quality Quantitative Proteome and Post-Translational Modification Analysis of Clinically Relevant Samples from Formalin-Fixed Paraffin-Embedded Archives

Well-characterized archival formalin-fixed paraffin-embedded (FFPE) tissues are of much value for prospective biomarker discovery studies, and protocols that offer high throughput and good reproducibility are essential in proteomics. Therefore, we implemented efficient paraffin removal and protein extraction from FFPE tissues followed by an optimized two-enzyme digestion using suspension trapping (S-Trap). The protocol was then combined with TMTpro 16plex labeling and applied to lung adenocarcinoma patient samples. In total, 9585 proteins were identified, and proteins related to the clinical outcome were detected. Because acetylation is known to play a major role in cancer development, a fast on-trap acetylation protocol was developed for studying endogenous lysine acetylation, which allows identification and localization of the lysine acetylation together with quantitative comparison between samples. We demonstrated that FFPE tissues are equivalent to frozen tissues to study the degree of acetylation between patients. In summary, we present a reproducible sample preparation workflow optimized for FFPE tissues that resolves known proteomic-related challenges. We demonstrate compatibility of the S-Trap with isobaric labeling and for the first time, we prove that it is feasible to study endogenous lysine acetylation stoichiometry in FFPE tissues, contributing to better utility of the existing global tissue archives. The MS proteomic data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifiers PXD020157, PXD021986, and PXD021964.

Serum proteomics analysis of feline mammary carcinoma based on label-free and PRM techniques

Background

Feline mammary carcinoma is the third most common cancer that affects female cats.

Objectives

The purpose of this study was to screen differential serum proteins in feline and clarify the relationship between them and the occurrence of feline mammary carcinoma.

Methods

Chinese pastoral cats were used as experimental animals. Six serum samples from cats with mammary carcinoma (group T) and six serum samples from healthy cats (group C) were selected. Differential protein analysis was performed using a Label-free technique, while parallel reaction monitoring (PRM) was performed to verify the screened differential proteins.

Results

A total of 82 differential proteins were detected between group T and group C, of which 55 proteins were down regulated and 27 proteins were up regulated. Apolipoprotein A-I, Apolipoprotein A-II (ApoA-II), Apolipoprotein B (ApoB), Apolipoprotein C-III (ApoC-III), coagulation factor V, coagulation factor X, C1q, albumen (ALB) were all associated with the occurrence of feline mammary carcinoma. Differential proteins were involved in a total of 40 signaling pathways, among which the metabolic pathways associated with feline mammary carcinoma were the complement and coagulation cascade and cholesterol metabolism. According to the Label-free results, ApoB, ApoC-III, ApoA-II, FN1, an uncharacterized protein, and ALB were selected for PRM target verification. The results were consistent with the trend of the label-free.

Conclusions

This experimen is the first to confirm ApoA-II and ApoB maybe new feline mammary carcinoma biomarkers and to analyze their mechanisms in the development of such carcinoma in feline.

FOXO transcription factor family in cancer and metastasis

Forkhead box O (FOXO) transcription factors regulate diverse biological processes, affecting development, metabolism, stem cell maintenance and longevity. They have also been increasingly recognised as tumour suppressors through their ability to regulate genes essential for cell proliferation, cell death, senescence, angiogenesis, cell migration and metastasis. Mechanistically, FOXO proteins serve as key connection points to allow diverse proliferative, nutrient and stress signals to converge and integrate with distinct gene networks to control cell fate, metabolism and cancer development. In consequence, deregulation of FOXO expression and function can promote genetic disorders, metabolic diseases, deregulated ageing and cancer. Metastasis is the process by which cancer cells spread from the primary tumour often via the bloodstream or the lymphatic system and is the major cause of cancer death. The regulation and deregulation of FOXO transcription factors occur predominantly at the post-transcriptional and post-translational levels mediated by regulatory non-coding RNAs, their interactions with other protein partners and co-factors and a combination of post-translational modifications (PTMs), including phosphorylation, acetylation, methylation and ubiquitination. This review discusses the role and regulation of FOXO proteins in tumour initiation and progression, with a particular emphasis on cancer metastasis. An understanding of how signalling networks integrate with the FOXO transcription factors to modulate their developmental, metabolic and tumour-suppressive functions in normal tissues and in cancer will offer a new perspective on tumorigenesis and metastasis, and open up therapeutic opportunities for malignant diseases.

Apolipoproteins and cancer

The role of apolipoproteins in cardiovascular disease has been well investigated, but their participation in cancer has only been explored in a few published studies which showed a close link with certain kinds of cancer. In this review, we focused on the function of different kinds of apolipoproteins in cancers, autophagy, oxidative stress, and drug resistance. The potential application of apolipoproteins as biomarkers for cancer diagnosis and prognosis was highlighted, together with an investigation of their potential as drug targets for cancer treatment. Many important roles of apolipoproteins and their mechanisms in cancers were reviewed in detail and future perspectives of apolipoprotein research were discussed.

Identification of High Serum Apolipoprotein A1 as a Favorable Prognostic Indicator in Patients with Multiple Myeloma

This study is to explore the prognostic significance of serum lipid profiles in patients with multiple myeloma (MM). The study retrospectively enrolled 307 MM patients in Zhongshan Hospital, Shanghai, China, from 2007 to 2016. We evaluated the prognostic significance of the pre-diagnostic serum lipid profile [cholesterol, triglyceride, low-density lipoprotein (LDL), high-density lipoprotein (HDL), Apolipoprotein A1 (Apo A1) and Apolipoprotein B (Apo B)]. Prognostic factors identified through univariate and multivariate analysis were used to construct a new model based on Lasso Cox regression. Results indicated that lipid levels showed significant difference between ISS stages: Apo A1, Apo B, Cholesterol and LDL levels were lower in late ISS stage. However, only Apo A1 showed statistically significance in overall survival (OS), progression free survival (PFS) and cause specific survival (CSS) (P=0.038, P=0.028, P=0.011) in univariate Cox regression. Patients with higher Apo A1 displayed longer OS (median OS, 67 months vs. 30 months; P<0.001). Also, Apo A1 was revealed to be an independent prognostic indicator through multivariate analysis. Combining the Apo A1 level, Zhongshan Score model was constructed with Lasso regression for prognosis prediction. This model exhibited higher accuracy than International Staging System (ISS) and Durie and Salmon (DS) system. In conclusion, among all the serum lipid profiles, serum Apo A1 is a powerful prognostic indicator for patients with MM.

Apolipoprotein E is a predictive marker for assessing non-small cell lung cancer patients with lymph node metastasis

BACKGROUND

Apolipoprotein E (APOE) modulates lipid homeostasis in the systemic circulation and induces inflammatory immune responses in the tumor microenvironment. We evaluated APOE expression in order to assess tumor progression in non-small cell lung cancer (NSCLC).

METHODS

Immunohistochemical staining for APOE was performed on tissue microarray blocks from 148 patients who had undergone surgery for NSCLC. The staining intensity and the proportion of APOE-positive tumor cells (based on distinct membranous and cytoplasmic staining) were scored. The relationships between APOE expression and clinical (age, sex, and smoking history) and pathological (TNM stage and histological type) factors were evaluated.

RESULTS

Positive APOE staining was observed in 93 (64.6%) patients. APOE expression patterns differed among NSCLC histological types (p-value = 0.016). Negative APOE expression was significantly associated with lymph node metastasis in NSCLC (p-value = 0.040). Both cases of N2 (stage IIIA) disease showed negative APOE expression.

CONCLUSIONS

APOE is a useful marker for assessing NSCLC patients with lymph node metastasis.

Diagnostic value of apolipoprotein C-I, transthyretin and apolipoprotein C-III in gastric cancer

Diagnostic value of apolipoprotein C-I (ApoC-I), transthyretin (TTR) and ApoC-III in gastric cancer were evaluated. Retrospective analysis methods were used to collect 60 patients with gastric cancer first diagnosed in The First Affiliated Hospital of Jiaxing University. There were 60 patients with chronic atrophic gastritis in the benign lesion group and 60 healthy individuals in the control group. The expression levels of serum ApoC-I, TTR and ApoC-III was detected by enzyme-linked immunosorbent assay. Differences existed in the expression levels of ApoC-I, TTR and ApoC-III in the gastric cancer group, benign lesion group and control group (P<0.001), with the expression levels of ApoC-I, TTR and ApoC-III in the gastric cancer group being lower than that of the benign lesion group (P<0.05), and the expression levels of ApoC-I, TTR and ApoC-III in the benign lesion group being lower than that of the control group (P<0.05). The expression levels of ApoC-I, TTR and ApoC-III in the gastric cancer group were to a certain degree correlated with the clinical stage, lymph node metastasis and differentiation of patients in the gastric cancer group (P<0.05). The specificity and negative predictive value of combined detection were proven to be higher than the separate detection of the three factors (P<0.05). The detection of serum ApoC-I, TTR and ApoC-III was of great significance in the diagnosis of gastric cancer and the estimation of its severity. The method of combined detection is worth a further in-depth study as it could improve the specificity of diagnosis and have a higher negative predictive value.

Exploitation of nanoparticle–protein corona for emerging therapeutic and diagnostic applications

Exposure of nanoparticles (NPs) to biological fluids (e.g., plasma, interstitial fluid, and cytoplasm) leads to the absorption of proteins on the NP surface, forming a protein corona (PC) that drastically influences the NP physicochemical properties.