Apolipoprotein E Overexpression Is Associated With Tumor Progression and Poor Survival in Colorectal Cancer

Macrophage diversity in human cancers: New insight provided by single-cell resolution and spatial context

M1/M2 paradigm of macrophage plasticity has existed for decades. Now it becomes clear that this dichotomy doesn't adequately reflect the diversity of macrophage phenotypes in tumor microenvironment (TME). Tumor-associated macrophages (TAMs) are a major population of innate immune cells in the TME that promotes tumor cell proliferation, angiogenesis and lymphangiogenesis, invasion and metastatic niche formation, as well as response to anti-tumor therapy. However, the fundamental restriction in therapeutic TAM targeting is the limited knowledge about the specific TAM states in distinct human cancer types. Here we summarized the results of the most recent studies that use advanced technologies (e.g. single-cell RNA sequencing and spatial transcriptomics) allowing to decipher novel functional subsets of TAMs in numerous human cancers. The transcriptomic profiles of these TAM subsets and their clinical significance were described. We emphasized the characteristics of specific TAM subpopulations - TREM2+, SPP1+, MARCO+, FOLR2+, SIGLEC1+, APOC1+, C1QC+, and others, which have been most extensively characterized in several cancers, and are associated with cancer prognosis. Spatial transcriptomics technologies defined specific spatial interactions between TAMs and other cell types, especially fibroblasts, in tumors. Spatial transcriptomics methods were also applied to identify markers of immunotherapy response, which are expressed by macrophages or in the macrophage-abundant regions. We highlighted the perspectives for novel techniques that utilize spatial and single cell resolution in investigating new ligand-receptor interactions for effective immunotherapy based on TAM-targeting.

Increased heterogeneity in expression of genes associated with cancer progression and drug resistance

Fluctuations in the number of regulatory molecules and differences in timings of molecular events can generate variation in gene expression among genetically identical cells in the same environmental condition. This variation, termed as expression noise, can create differences in metabolic state and cellular functions, leading to phenotypic heterogeneity. Expression noise and phenotypic heterogeneity have been recognized as important contributors to intra-tumor heterogeneity, and have been associated with cancer growth, progression, and therapy resistance. However, how expression noise changes with cancer progression in actual cancer patients has remained poorly explored. Such an analysis, through identification of genes with increasing expression noise, can provide valuable insights into generation of intra-tumor heterogeneity, and could have important implications for understanding immune-suppression, drug tolerance and therapy resistance. In this work, we performed a genome-wide identification of changes in gene expression noise with cancer progression using single-cell RNA-seq data of lung adenocarcinoma patients at different stages of cancer. We identified 37 genes in epithelial cells that showed an increasing noise trend with cancer progression, many of which were also associated with cancer growth, EMT and therapy resistance. We found that expression of several of these genes was positively associated with expression of mitochondrial genes, suggesting an important role of mitochondria in generation of heterogeneity. In addition, we uncovered substantial differences in sample-specific noise profiles which could have implications for personalized prognosis and treatment.

Identification macrophage signatures in prostate cancer by single-cell sequencing and machine learning

BACKGROUND

The tumor microenvironment (TME) encompasses a variety of cells that influence immune responses and tumor growth, with tumor-associated macrophages (TAM) being a crucial component of the TME. TAM can guide prostate cancer in different directions in response to various external stimuli.

METHODS

First, we downloaded prostate cancer single-cell sequencing data and second-generation sequencing data from multiple public databases. From these data, we identified characteristic genes associated with TAM clusters. We then employed machine learning techniques to select the most accurate TAM gene set and developed a TAM-related risk label for prostate cancer. We analyzed the tumor-relatedness of the TAM-related risk label and different risk groups within the population. Finally, we validated the accuracy of the prognostic label using single-cell sequencing data, qPCR, and WB assays, among other methods.

RESULTS

In this study, the TAM_2 cell cluster has been identified as promoting the progression of prostate cancer, possibly representing M2 macrophages. The 9 TAM feature genes selected through ten machine learning methods and demonstrated their effectiveness in predicting the progression of prostate cancer patients. Additionally, we have linked these TAM feature genes to clinical pathological characteristics, allowing us to construct a nomogram. This nomogram provides clinical practitioners with a quantitative tool for assessing the prognosis of prostate cancer patients.

CONCLUSION

This study has analyzed the potential relationship between TAM and PCa and established a TAM-related prognostic model. It holds promise as a valuable tool for the management and treatment of PCa patients.

Jun-APOE-LRP1 axis promotes tumor metastasis in colorectal cancer

Apolipoprotein E (apoE) has previously been reported to play vital roles in tumor progression. However, the impact of apoE on colorectal cancer (CRC) metastasis remains largely unexplored. This study aimed to investigate the role of apoE in CRC metastasis and to identify the transcription factor and receptor of apoE involved in regulation of CRC metastasis. Bioinformatic analyses were conducted to examine the expression pattern and prognosis of apolipoproteins. APOE-overexpressing cell lines were utilized to explore the effects of apoE on proliferation, migration and invasion of CRC cells. Additionally, the transcription factor and receptor of apoE were screened via bioinformatics, and further validated through knockdown experiments. We discovered that the mRNA levels of APOC1, APOC2, APOD and APOE were higher in lymphatic invasion group, and a higher apoE level indicated poorer overall survival and progression-free interval. In vitro studies demonstrated that APOE-overexpression did not affect proliferation but promoted the migration and invasion of CRC cells. We also reported that APOE-expression was modulated by the transcription factor Jun by activating the proximal promoter region of APOE, and APOE-overexpression reversed the metastasis suppression of JUN knockdown. Furthermore, bioinformatics analysis suggested an interaction between apoE and low-density lipoprotein receptor-related protein 1 (LRP1). LRP1 was highly expressed in both the lymphatic invasion group and the APOEHigh group. Additionally, we found that APOE-overexpression upregulated LRP1 protein levels, and LRP1 knockdown attenuated the metastasis-promoting function of APOE. Overall, our study suggests that the Jun-APOE-LRP1 axis contributes to tumor metastasis in CRC.

Glioblastoma initiation, migration, and cell types are regulated by core bHLH transcription factors ASCL1 and OLIG2

Glioblastomas (GBMs) are highly aggressive, infiltrative, and heterogeneous brain tumors driven by complex driver mutations and glioma stem cells (GSCs). The neurodevelopmental transcription factors ASCL1 and OLIG2 are co-expressed in GBMs, but their role in regulating the heterogeneity and hierarchy of GBM tumor cells is unclear. Here, we show that oncogenic driver mutations lead to dysregulation of ASCL1 and OLIG2, which function redundantly to initiate brain tumor formation in a mouse model of GBM. Subsequently, the dynamic levels and reciprocal binding of ASCL1 and OLIG2 to each other and to downstream target genes then determine the cell types and degree of migration of tumor cells. Single-cell RNA sequencing (scRNA-seq) reveals that a high level of ASCL1 is key in defining GSCs by upregulating a collection of ribosomal protein, mitochondrial, neural stem cell (NSC), and cancer metastasis genes - all essential for sustaining the high proliferation, migration, and therapeutic resistance of GSCs.

GeNetOntology: identifying affected gene ontology terms via grouping, scoring, and modeling of gene expression data utilizing biological knowledge-based machine learning

Introduction: Identifying significant sets of genes that are up/downregulated under specific conditions is vital to understand disease development mechanisms at the molecular level. Along this line, in order to analyze transcriptomic data, several computational feature selection (i.e., gene selection) methods have been proposed. On the other hand, uncovering the core functions of the selected genes provides a deep understanding of diseases. In order to address this problem, biological domain knowledge-based feature selection methods have been proposed. Unlike computational gene selection approaches, these domain knowledge-based methods take the underlying biology into account and integrate knowledge from external biological resources. Gene Ontology (GO) is one such biological resource that provides ontology terms for defining the molecular function, cellular component, and biological process of the gene product. Methods: In this study, we developed a tool named GeNetOntology which performs GO-based feature selection for gene expression data analysis. In the proposed approach, the process of Grouping, Scoring, and Modeling (G-S-M) is used to identify significant GO terms. GO information has been used as the grouping information, which has been embedded into a machine learning (ML) algorithm to select informative ontology terms. The genes annotated with the selected ontology terms have been used in the training part to carry out the classification task of the ML model. The output is an important set of ontologies for the two-class classification task applied to gene expression data for a given phenotype. Results: Our approach has been tested on 11 different gene expression datasets, and the results showed that GeNetOntology successfully identified important disease-related ontology terms to be used in the classification model. Discussion: GeNetOntology will assist geneticists and scientists to identify a range of disease-related genes and ontologies in transcriptomic data analysis, and it will also help doctors design diagnosis platforms and improve patient treatment plans.

Hepatic passaging of NRAS-mutant melanoma influences adhesive properties and metastatic pattern

BACKGROUND

Liver metastasis is a poor prognostic factor for treatment of advanced cutaneous melanoma with either immunotherapy or targeted therapies. In this study we focused on NRAS mutated melanoma, a cohort with high unmet clinical need.

METHODS

WT31 melanoma was repeatedly passaged over the liver after intravenous injections five times generating the subline WT31_P5IV. The colonization of target organs, morphology, vascularization and the gene expression profiles of metastases were analyzed.

RESULTS

After intravenous injection lung metastasis was significantly decreased and a trend towards increased liver metastasis was detected for WT31_P5IV as compared to parental WT31. Besides, the ratio of lung to liver metastases was significantly smaller. Histology of lung metastases revealed reduced proliferation of WT31_P5IV in relation to WT31 while both size and necrotic areas were unaltered. Liver metastases of both sublines showed no differences in vascularization, proliferation or necrosis. To identify tumor-intrinsic factors that altered the metastatic pattern of WT31_P5IV RNA sequencing was performed and revealed a differential regulation of pathways involved in cell adhesion. Ex vivo fluorescence imaging confirmed that initial tumor cell retention in the lungs was significantly reduced in WT31_P5IV in comparison to WT31.

CONCLUSION

This study demonstrates that tumor-intrinsic properties influencing the metastatic pattern of NRAS mutated melanoma are strongly affected by hepatic passaging and the hematogenous route tumor cells take. It has implications for the clinical setting as such effects might also occur during metastatic spread or disease progression in melanoma patients.

Spatial Transcriptomics Depict Ligand-Receptor Cross-talk Heterogeneity at the Tumor-Stroma Interface in Long-Term Ovarian Cancer Survivors

Advanced high-grade serous ovarian cancer (HGSC) is an aggressive disease that accounts for 70% of all ovarian cancer deaths. Nevertheless, 15% of patients diagnosed with advanced HGSC survive more than 10 years. The elucidation of predictive markers of these long-term survivors (LTS) could help identify therapeutic targets for the disease, and thus improve patient survival rates. To investigate the stromal heterogeneity of the tumor microenvironment (TME) in ovarian cancer, we used spatial transcriptomics to generate spatially resolved transcript profiles in treatment-naïve advanced HGSC from LTS and short-term survivors (STS) and determined the association between cancer-associated fibroblasts (CAF) heterogeneity and survival in patients with advanced HGSC. Spatial transcriptomics and single-cell RNA-sequencing data were integrated to distinguish tumor and stroma regions, and a computational method was developed to investigate spatially resolved ligand-receptor interactions between various tumor and CAF subtypes in the TME. A specific subtype of CAFs and its spatial location relative to a particular ovarian cancer cell subtype in the TME correlated with long-term survival in patients with advanced HGSC. Also, increased APOE-LRP5 cross-talk occurred at the stroma-tumor interface in tumor tissues from STS compared with LTS. These findings were validated using multiplex IHC. Overall, this spatial transcriptomics analysis revealed spatially resolved CAF-tumor cross-talk signaling networks in the ovarian TME that are associated with long-term survival of patients with HGSC. Further studies to confirm whether such cross-talk plays a role in modulating the malignant phenotype of HGSC and could serve as a predictive biomarker of patient survival are warranted.

SIGNIFICANCE

Generation of spatially resolved gene expression patterns in tumors from patients with ovarian cancer surviving more than 10 years allows the identification of novel predictive biomarkers and therapeutic targets for better patient management. See related commentary by Kelliher and Lengyel, p. 1383.

Identification of hub genes and pathways in lung metastatic colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is one of the most prevalent types of malignant tumours. Metastasis is the leading cause of cancer-related mortality, with lung metastases accounting for 32.9% of all metastatic CRCs. However, since the biological mechanism of lung metastatic CRC is poorly understood, limited therapeutic targets are available. In the present study, we aimed to identify the key genes and molecular processes involved in CRC lung metastasis.

METHODS

The differentially expressed genes (DEGs) between primary and lung metastatic CRC patients were obtained from the Gene Expression Omnibus (GEO) database via the GEO2R tool. The enriched biological processes and pathways modulated by the DEGs were determined with Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome Gene Sets analyses. The search tool Retrieval of Interacting Genes (STRING) and Cytoscape were used to construct a protein-protein interaction (PPI) network among DEGs.

RESULTS

The DEGs were enriched in surfactant metabolism, cell-cell communication and chemokine signaling pathways. The defined hub genes were included CLU, SFTPD, CCL18, SPP1, APOE, BGN and MMP3. Among them, CLU, SFTPD and CCL18 might be associated with the specific lung tropism metastasis in CRC. In addition, the expression and prognostic values of the hub genes in CRC patients were verified in database of The Cancer Genome Atlas (TCGA) and GEO. Moreover, the protein levels of the hub genes were detected in primary and lung metastatic CRC cells, serum or tissues. Furthermore, SFTPD was confirmed to facilitate cellular proliferation and lung metastasis in CRC.

CONCLUSION

This bioinformatics study may provide a better understanding of the candidate therapeutic targets and molecular mechanisms for CRC lung metastasis.

Molecular characterization of colorectal mucinous adenocarcinoma and adenocarcinoma, not otherwise specified, identified by multiomic data analysis

Adenocarcinoma not otherwise specified (AC) and mucinous adenocarcinoma (MC) have different biological behaviors and clinical features. We utilized our previous proteomic data and public transcriptome, single-cell transcriptome, and spatial transcriptome databases to profile the molecular atlas of the tumor microenvironments of MC, AC, and normal colon tissues. By exploring the general and specific molecular features of AC and MC, we found that AC was immune-active but exposed to a hypoxic microenvironment. MC cells could protect against DNA damage, and the microenvironment was unfavorable to leukocyte transendothelial migration. We identified several potential molecular and cellular targets of AC and MC for future research. We also highlighted that the major difference between AC and MC was not the variety of cell types and functions but possibly cell interactions. Stromal and epithelial cell interactions play important roles in both MC and AC, but different regulatory pathways were involved.

Proteomic analysis identifies dysregulated proteins and associated molecular pathways in a cohort of gallbladder cancer patients of African ancestry

BACKGROUND

Gallbladder cancer (GBC) is a lethal cancer with a poor prognosis. The lack of specific and sensitive biomarkers results in delayed diagnosis with most patients presenting at late stages of the disease. Furthermore, there is little known about the molecular mechanisms associated with GBC, especially in patients of African ancestry. This study aimed to determine dysregulated proteins in South African GBC patients to identify potential mechanisms of the disease progression and plausible biomarkers.

METHODS

Tissues (27 GBC, 13 Gallstone disease, and 5 normal tissues) and blood plasma (54 GBC and 73 Benign biliary pathology) were obtained from consenting patients. Protein extraction was performed on all tissues and liquid chromatography-mass spectrometry was used for proteomic profiling. A project-specific spectral library was built using the Pulsar search algorithm. Principal component and Spearman's rank correlation analyses were performed using PAST (V4.07b). Pathway and Network analyses were conducted using REACTOME (v3.7) and stringAPP (v1.7.0), respectively.

RESULTS

In the tissue sample group, there were 62 and 194 dysregulated proteins in GBC compared to normal and gallstone groups, respectively. In the plasma group, there were 33 altered proteins in GBC compared to the benign biliary pathology group. We found 9 proteins (APOA1, APOA2, RET4, TTR, HEMO, HBB, HBA, PIGR, and APOE) to be commonly dysregulated in both tissue and plasma. Furthermore, a subset analysis demonstrated that 2 proteins, S100A8 and S100A9, were downregulated in GBC patients with GD history compared to those without. Pathway analysis showed that the dysregulated proteins in GBC patients were enriched in pathways involved in smooth muscle contraction, metabolism, ECM organization, and integrin cell surface interactions.

CONCLUSION

The identified dysregulated proteins help in understanding GBC molecular mechanisms in our patient group. Furthermore, the alteration of specific proteins in both tissue and plasma samples suggests their potential utility as biomarkers of GBC in this sample cohort.

From degenerative disease to malignant tumors: Insight to the function of ApoE

Apolipoprotein E (ApoE) is a multifunctional protein involved in lipid transport and lipoprotein metabolism, mediating lipid distribution/redistribution in tissues and cells. It can also regulate inflammation and immune function, maintain cytoskeleton stability, and improve neural tissue Function. Due to genetic polymorphisms of ApoE (ε2, ε3, and ε4), its three common structural isoforms (ApoE2, ApoE3, ApoE4) are also associated with the risk of many diseases, especially degenerative diseases, such as vascular degenerative diseases including atherosclerosis (AS), coronary heart disease (CHD), and neurodegenerative disease like Alzheimer's disease (AD). The frequency of the ε4 allele and APOE variants were significantly higher than that of the ε2 and ε3 alleles in the patients with CHD or AD. In recent years, ApoE has frequently appeared in tumor research and become a tumor biomarker gradually. It has been found that ApoE is highly expressed in most solid tumor tissues, such as glioblastoma, gastric cancer, pancreatic ductal cell carcinoma, etc. Studies illustrated that ApoE could regulate the polarization changes of macrophages, participate in the construction of tumor immune microenvironment, regulate tumor inflammation and immune response and play a role in tumor progression, invasion, and metastasis. Of course, many functions of ApoE and its relationship with diseases are still under research. By reviewing the structure and function of ApoE from degeneration diseases to tumor neoplasms, we hope to better understand such a biomarker and further explore the value of ApoE in later studies.

A Label-Free Proteomic Approach for the Identification of Biomarkers in the Exosome of Endometrial Cancer Serum

Endometrial cancers (ECs) are mostly adenocarcinomas arising from the inner part of the uterus. The identification of serum biomarkers, either soluble or carried in the exosome, may be useful in making an early diagnosis. We used label-free quantification mass spectrometry (LFQ-MS)-based proteomics to investigate the proteome of exosomes in the albumin-depleted serum from 12 patients with EC, as compared to 12 healthy controls. After quantification and statistical analysis, we found significant changes in the abundance (p < 0.05) of 33 proteins in EC vs. control samples, with a fold change of ≥1.5 or ≤0.6. Validation using Western blotting analysis in 36 patients with EC as compared to 36 healthy individuals confirmed the upregulation of APOA1, HBB, CA1, HBD, LPA, SAA4, PF4V1, and APOE. A multivariate logistic regression model based on the abundance of these proteins was able to separate the controls from the EC patients with excellent sensitivity levels, particularly for stage 1 ECs. The results show that using LFQ-MS to explore the specific proteome of serum exosomes allows for the identification of biomarkers in EC. These observations suggest that PF4V1, CA1, HBD, and APOE represent biomarkers that are able to reach the clinical stage, after a validation phase.

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.

Tumor Apolipoprotein E is a key checkpoint blocking anti-tumor immunity in mouse melanoma

Immunotherapy is a key modality in the treatment of cancer, but many tumors remain immune resistant. The classic mouse model of B16-F10 melanoma is immune resistant even in the face of checkpoint inhibition. Apolipoprotein E (apoE), a known immune suppressant is strikingly elevated in many human tumors, but its role in cancer immunology is not defined. We investigated the role of apoE in the immune micro-environment using a mouse melanoma model. We demonstrate that ApoE is -highly expressed in wild-type B16-F10 melanoma and serum levels progressively increase as tumors grow. The conditioned media from wild type ApoE secreting melanoma cells suppress T-cell activation in vitro while this suppressive effect is absent in conditioned media from ApoE knock out tumor cells. Mechanistically, apoE induces IL-10 secreting dendritic cells and stimulates T-cell apoptosis and arrest partially via the lrp8 receptor. Ablating ApoE in mice inoculated with tumor cells enabled tumor cell rejection and was associated with induction of immune pathway activation and immune cell infiltration. Tumor secreted apoE appears to be a potent immune cell checkpoint and targeting apoE is associated with enhanced tumor immunity in the mouse melanoma model.

Construction of 2DE Patterns of Plasma Proteins: Aspect of Potential Tumor Markers

The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for “ideal” tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways—by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called “classical plasma proteins”, may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of “classical plasma proteins”. Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.

The correlation between APOE expression and the clinical characteristics and prognosis of patients with endometrial cancer

To analyze the expression of apolipoprotein E (APOE) in endometrial cancer and its influence on the long-term prognostic survival of endometrial cancer patients. The specimens of tumor tissues and adjacent normal tissues from 96 endometrial cancer patients from January 2013 to December 2015 were included in this study. Immunohistochemistry was used to measure the expression of APOE in tumor tissues and adjacent normal tissues. Statistical analysis was used to examine the correlation between APOE expression and the clinicopathological characteristics and survival of patients. Kaplan-Meier survival curve was drawn to study the effects of APOE on the prognosis of patients. The positive rate of APOE in endometrial cancer tissue was higher than that in adjacent normal tissues. The expression level of APOE in endometrial cancer was correlated with histological grade, lymph node metastasis, and FIGO stage (P < .05). Lymph node metastasis and APOE were independent risk factors affecting the prognosis and survival of patients (P < .05). The results of Kaplan-Meier survival analysis showed that the survival time of APOE high expression group was shorter than that of low APOE expression. APOE is overexpressed in endometrial cancer tissues, and its expression level can provide important information for clinical diagnosis and treatment.

The Role of ApoE Serum Levels and ApoE Gene Polymorphisms in Patients with Laryngeal Squamous Cell Carcinoma

Recent studies have revealed that the inflammatory ApoE effect may play a significant role in various cancer development. However, this effect has still not been analyzed in patients with laryngeal squamous cell carcinoma (LSCC). In the present study, we evaluated two single nucleotide polymorphisms (SNPs) of ApoE (rs7412 and rs429358) and determined their associations with LSCC development and the LSCC patients’ five-year survival rate. Additionally, we analyzed serum ApoE levels using an enzyme-linked immunosorbent assay. A total of 602 subjects (291 histologically verified LSCC patients and 311 healthy controls) were involved in this study. The genotyping was carried out using the real-time PCR. We revealed that ApoE ε3/ε3 was associated with a 1.7-fold higher probability of developing LSCC (p = 0.001), with 1.7-fold increased odds of developing LSCC without metastasis to the lymph nodes (p = 0.002) and with a 2.0-fold increased odds of developing well-differentiated LSCC (p = 0.008), as well as 1.6-fold increased odds of developing poorly differentiated LSCC development (p = 0.012). The ApoE ε2/ε4 and ε3/ε4 genotypes were associated with a 2.9-fold and 1.5-fold decrease in the likelihood of developing LSCC (p = 0.042; p = 0.037, respectively). ApoE ε3/ε4 was found associated with a 2.4-fold decreased likelihood of developing well-differentiated LSCC (p = 0.013). Conclusion: ApoE ε2/ε4 and ε3/ε4 were found to play a protective role in LSCC development, while ApoE ε3/ε3 may have a risk position in LSCC development.

Nanoparticle personalized biomolecular corona: implications of pre-existing conditions for immunomodulation and cancer

Nanoparticles (NPs) have demonstrated great promise as immunotherapies for applications ranging from cancer, autoimmunity, and infectious disease. Upon encountering biological fluids, NPs rapidly adsorb biomolecules, forming the "biomolecular corona" (BC), and the altered character of NPs due to their newly acquired biological identity can impact their in vivo fate. Recently, it has been shown that the NP-BC is person-specific, and even minute differences in the biomolecule composition can give rise to altered immune recognition, cellular interactions, pharmacokinetics, and biodistribution. Given the current rise in the development of NP-based therapeutics, it is of utmost importance to better understand how pre-existing conditions, that result in the formation of a personalized BC, can be leveraged to aid in the prediction of the therapeutic outcomes of NPs. In this minireview, we will discuss the formation of the BC, implications of the BC for NP-biological interactions, and its clinical importance in the context of immunomodulation and cancer therapeutics.

Immune-Related Biomarkers Associated with Lung Metastasis from the Colorectal Cancer Microenvironment

Immune-associated biomarkers can predict lung metastases from colorectal cancer. Differentially expressed genes (DEGs) were screened from sample data extracted from gene expression omnibus (GEO) database. The DEGs were screened from the lung metastasis (LM) and primary cancer (PC) groups of the Moffitt Cancer Center cohort dataset. Then, the tumor immune microenvironment and abundance of immune cell infiltration analyses were performed, and the immune-related DEGs were retrieved. In addition, the transcription factor (TF)-miRNA-mRNA network was constructed and enrichment analyses of the immune-related DEGs and upregulated and downregulated DEGs were carried out. Then, the protein-protein interaction (PPI) network was conducted and the drug-gene interaction was predicted. A total of 268 DEGs were screened. The Immune_Score of samples in the LM group was significantly higher compared with the PC group. The infiltration ratio of M0 macrophages and M2 macrophages of samples was higher than others. A total of 54 immune-related DEGs in M0 macrophages were screened. Moreover, the TF-miRNA-mRNA network was constructed among 8 miRNA-mRNA and 50 TF-mRNA, and the secreted phosphoprotein 1 was regulated by 12 TFs, and the oxidized low-density lipoprotein receptor 1 was regulated by 3 miRNAs and 3 TFs. The TF SAM pointed domain containing ETS TF was also a downregulated DEG. The Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that the DEGs in the TF-miRNA-mRNA network were mainly involved in the interleukin-7 signaling pathway and cell adhesion molecules. In total, 23 protein interactions in this PPI network of M0 macrophage cells were involved in 27 mRNAs. There were 38 drug-gene interactions of immune-related DEGs of M0 macrophage cells predicted to contain 34 small molecule drugs and 8 mRNAs. Finally, the CON cohort dataset verified that the infiltration ratio of M0 and M2 macrophages of the samples was higher.

Colorectal liver metastasis: molecular mechanism and interventional therapy

Colorectal cancer (CRC) is one of the most frequently occurring malignancy tumors with a high morbidity additionally, CRC patients may develop liver metastasis, which is the major cause of death. Despite significant advances in diagnostic and therapeutic techniques, the survival rate of colorectal liver metastasis (CRLM) patients remains very low. CRLM, as a complex cascade reaction process involving multiple factors and procedures, has complex and diverse molecular mechanisms. In this review, we summarize the mechanisms/pathophysiology, diagnosis, treatment of CRLM. We also focus on an overview of the recent advances in understanding the molecular basis of CRLM with a special emphasis on tumor microenvironment and promise of newer targeted therapies for CRLM, further improving the prognosis of CRLM patients.

Ferroptosis-Related APOE, BCL3 and ALOX5AP Gene Polymorphisms are Associated with the Risk of Thyroid Cancer

Purpose

This study aimed to evaluate the association between polymorphisms in the ferroptosis-related genes apolipoprotein E (APOE), BCL3 transcription coactivator (BCL3) and arachidonate 5-lipoxygenase activating protein (ALOX5AP) and the risk of thyroid cancer.

Methods

Six single nucleotide polymorphisms (SNPs) of APOE (rs429358 and rs7412), BCL3 (rs34698726 and rs8100239) and ALOX5AP (rs4076128 and rs4073259) were genotyped in 520 papillary thyroid carcinoma cases and 520 healthy controls using the MassARRAY platform.

Results

The rs429358-TC, rs34698726-TA/TT, and rs8100239-AT/AA genotypes exhibited an elevated risk of thyroid cancer (p_rs429358 = 0.002, p_rs34698726 = 0.007, p_rs8100239 = 0.002), while rs7412-CT/TT and rs4076128-GA/GG were found to be protective genotypes against the risk of disease (p_rs7412 = 0.0003, p_rs4076128 = 0.0001). Genetic model analysis showed that APOE-rs429358 was correlated with an increased risk of disease under dominant and log-additive models (p_dominant = 0.0004, p_log-additive = 0.0006). BCL3-s34698726 and rs8100239 were associated with an elevated risk of disease under all three genetic models (p < 0.05). In contrast, APOE-rs7412 was related to a decreased risk of thyroid cancer under dominant and log-additive models (p_dominant = 0.0001, p_log-additive = 0.0001). Moreover, ALOX5AP-rs4076128 was also correlated with a reduced risk of disease under all three genetic models (p < 0.05).

Conclusion

The results help us better understand how genetic polymorphisms in ferroptosis-related genes are relevant to thyroid cancer susceptibility.

Gene expression profiles of breast cancer metastasis according to organ site

In advanced breast cancer, biomarker identification and patient selection using a metastatic tumor biopsy is becoming more necessary. However, the biology of metastasis according to the organ site is largely unknown. Here, we evaluated the expression of 771 genes in 184 metastatic samples across 11 organs, including liver, lung, brain, and bone, and made the following observations. First, all PAM50 molecular intrinsic subtypes were represented across organs and within immunohistochemistry-based groups. Second, HER2-low disease was identified across all organ sites, including bone, and HER2 expression significantly correlated with ERBB2 expression. Third, the majority of expression variation was explained by intrinsic subtype and not organ of metastasis. Fourth, subtypes and individual subtype-related genes/signatures were significantly associated with overall survival. Fifth, we identified 74 genes whose expression was organ-specific and subtype-independent. Finally, immune profiles were found more expressed in lung compared to brain or liver metastasis. Our results suggest that relevant tumor biology can be captured in metastatic tissues across a variety of organ sites; however, unique biological features according to organ site were also identified and future studies should explore their implications in diagnostic and therapeutic interventions.

Transcriptome analysis of human Leydig cell tumours reveals potential mechanisms underlying its development

Leydig cell tumours are the most common sex cord-stromal tumours. In the last years, apparent increased incidence is noted while aetiology of the tumour is still unknown. Therefore, here, we focused on the genetics of Leydig cell tumours using the next-generation sequencing. Leydig cell micronodules were revealed in patients with azoospermia who were qualified for testicular biopsy. Complete gene set of Leydig cell tumours was compared with transcriptome of healthy Leydig cells obtained from donors. Bioinformatic analysis of the obtained sequencing data revealed alterations in expression of 219 transcripts. We showed, for the first time, that a significant proportion of differentially expressed genes is directly involved in regulation of apoptotic process, which downregulation might be important to Leydig cell tumour development. Additionally, we found a significant upregulation of heat shock protein genes that might be a unique feature of Leydig cell tumours when compared to other tumour types. Our study offers fundamental transcriptomic data for future studies on human Leydig cell tumour that are crucial to determine its causes. Moreover, presented here the in-depth analysis and discussion of alterations observed in tumour transcriptome may be important for the diagnosis and therapy of this pathology.

Identification of ferroptosis genes in immune infiltration and prognosis in thyroid papillary carcinoma using network analysis

BACKGROUND

Papillary thyroid carcinoma (PTC) is the most common thyroid cancer. While many patients survive, a portion of PTC cases display high aggressiveness and even develop into refractory differentiated thyroid carcinoma. This may be alleviated by developing a novel model to predict the risk of recurrence. Ferroptosis is an iron-dependent form of regulated cell death (RCD) driven by lethal accumulation of lipid peroxides, is regulated by a set of genes and shows a variety of metabolic changes. To elucidate whether ferroptosis occurs in PTC, we analyse the gene expression profiles of the disease and established a new model for the correlation.

METHODS

The thyroid carcinoma (THCA) datasets were downloaded from The Cancer Genome Atlas (TCGA), UCSC Xena and MisgDB, and included 502 tumour samples and 56 normal samples. A total of 60 ferroptosis related genes were summarised from MisgDB database. Gene set enrichment analysis (GSEA) and Gene set variation analysis (GSVA) were used to analyse pathways potentially involving PTC subtypes. Single sample GSEA (ssGSEA) algorithm was used to analyse the proportion of 28 types of immune cells in the tumour immune infiltration microenvironment in THCA and the hclust algorithm was used to conduct immune typing according to the proportion of immune cells. Spearman correlation analysis was performed on the ferroptosis gene expression and the correlation between immune infiltrating cells proportion. We established the WGCNA to identify genes modules that are highly correlated with the microenvironment of immune invasion. DEseq2 algorithm was further used for differential analysis of sequencing data to analyse the functions and pathways potentially involving hub genes. GO and KEGG enrichment analysis was performed using Clusterprofiler to explore the clinical efficacy of hub genes. Univariate Cox analysis was performed for hub genes combined with clinical prognostic data, and the results was included for lasso regression and constructed the risk regression model. ROC curve and survival curve were used for evaluating the model. Univariate Cox analysis and multivariate Cox analysis were performed in combination with the clinical data of THCA and the risk score value, the clinical efficacy of the model was further evaluated.

RESULTS

We identify two subtypes in PTC based on the expression of ferroptosis related genes, with the proportion of cluster 1 significantly higher than cluster 2 in ferroptosis signature genes that are positively associated. The mutations of Braf and Nras are detected as the major mutations of cluster 1 and 2, respectively. Subsequent analyses of TME immune cells infiltration indicated cluster 1 is remarkably richer than cluster 2. The risk score of THCA is in good performance evaluated by ROC curve and survival curve, in conjunction with univariate Cox analysis and multivariate Cox analysis results based on the clinical data shows that the risk score of the proposed model could be used as an independent prognostic indicator to predict the prognosis of patients with papillary thyroid cancer.

CONCLUSIONS

Our study finds seven crucial genes, including Ac008063.2, Apoe, Bcl3, Acap3, Alox5ap, Atxn2l and B2m, and regulation of apoptosis by parathyroid hormone-related proteins significantly associated with ferroptosis and immune cells in PTC, and we construct the risk score model which can be used as an independent prognostic index to predict the prognosis of patients with PTC.

IgG Fc Binding Protein (FCGBP) is Down-Regulated in Metastatic Lesions and Predicts Survival in Metastatic Colorectal Cancer Patients

Background

The liver is the most frequent site for metastatic spread in colorectal cancer (CRC) patients, and these patients have much poorer prognosis than those without metastasis. Previous studies have shown that IgG Fc binding protein (FCGBP) plays important roles in tumorigenesis, progression, and prognosis, but its role in CRC metastasis remains unclear.

Purpose

In this study, we are aimed to explore the significance of FCGBP in liver metastatic CRC (LMCRC) patients.

Methods

We analyzed the expression of FCGBP RNA between CRC primary samples and liver metastatic samples in the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA). Next, we assessed the expression of FCGBP protein in 135 paired primary CRC (PC) samples and LMCRC samples. Finally, we explored the relationship between the expression features and clinicopathological characteristics.

Results

The expression data of FCGBP were obtained from the GEO and TCGA databases. FCGBP RNA expression was evaluated between primary lesions (PC) and liver metastatic lesions (LM). FCGBP RNA was down-regulated in PC and LM, and especially lower in LM (p<0.001). Next, the expression of FCGBP protein was evaluated by an immunohistochemistry array in 135 paired primary tumor tissues and metastatic tissues. We found that FCGBP protein was down-regulated in primary lesions and metastatic lesions, especially in metastatic lesions. According to the immunohistochemistry score (SI), each cohort was divided into FCGBP-positive (SI=4–12) and FCGBP-negative (SI=0–3) groups. In both groups, the levels of CEA (PC group, 3.880 vs 77.049, p<0.001; LM group, 3.890 vs 14.239, p=0.008) and CA19-9 (PC group, 8.610 vs 111.700, p<0.001; LM group, 7.660 vs 19.380, p=0.037) were lower than those in the FCGBP-negative group. FCGBP positivity in the LM cohort was an independent risk factor in both overall survival (HR 1.573, 95% Cl [1.017–2.433], p=0.042) and disease-free survival (HR 1.869, 95% Cl [1.256–2.781], p=0.002).

Conclusion

This study found a relationship between FCGBP expression and clinical information of LMCRC patients, and found that FCGBP expression decreased with disease development. The expression of FCGBP in liver metastasis is associated with both the overall and progression-free survival. Our results show that FCGBP could be a promising prognostic factor for LMCRC.

Proteomic profiling of milk small extracellular vesicles from bovine leukemia virus-infected cattle

Milk small extracellular vesicles (sEV) contain proteins that provide potential information of host physiology and immunology. Bovine leukemia virus (BLV) is an oncogenic virus that causes progressive B-cell lymphosarcoma in cattle. In this study, we aimed to explore the proteomic profile of milk sEV from BLV-infected cattle compared with those from uninfected cattle. Milk sEV were isolated from three BLV-infected and three uninfected cattle. Proteomic analysis was performed by using a comprehensive nanoLC-MS/MS method. Furthermore, gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were used to evaluate the candidates for uniquely or differentially expressed proteins in milk sEV from BLV-infected cattle. Proteomic analysis revealed a total of 1330 common proteins in milk sEV among BLV-infected cattle, whereas 118 proteins were uniquely expressed compared with those from uninfected cattle. Twenty-six proteins in milk sEV were differentially expressed proteins more than two-fold significant difference (p < 0.05) in BLV-infected cattle. GO and KEGG analyses indicated that the candidates for uniquely or differentially expressed proteins in milk sEV had been involved in diverse biological activities including metabolic processes, cellular processes, respond to stimulus, binding, catalytic activities, cancer pathways, focal adhesion, and so on. Taken together, the present findings provided a novel insight into the proteomes of milk sEV from BLV-infected cattle.

The clinical relevance of gene expression based prognostic signatures in colorectal cancer

Colorectal cancer (CRC) is one of the most prevalent cancers, with more than one million new cases every year. In the last few decades, several advancements in therapeutic and preventative levels have reduced the mortality rate, but new biomarkers are required for improved prognosis. The alterations at the genetic and epigenetic level have been recognized as major players in tumorigenesis. The products of gene expression in the form of mRNA, microRNA, and long-noncoding RNA, have started to emerge as important regulatory molecules, playing an important role in cancer. Gene-expression based prognostic risk scores, which quantify and compare their expression, have emerged as promising biomarkers with enormous clinical value. These composite multi-gene models in which more than one gene is used to predict prognosis have been shown to be significantly effective in identifying patients with multiple clinico-pathological risks like overall mortality, response to chemotherapy, risk of metastasis, etc. The advent of microarray and advanced sequencing technologies have led to the generation of large datasets like TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus), which have fueled the search for new biomarkers. Continuous evaluation of these candidate biomarkers in clinical settings is promising to improve the management of CRC. These composite gene signatures provide potential in identifying high-risk patients, which might help clinicians to better manage these patients and design appropriate personalized therapeutic interventions. In this review, we emphasize on composite prognostic scores from diverse resources with clinical utility in CRC.

Atherosclerosis and Inflammatory Bowel Disease-Shared Pathogenesis and Implications for Treatment

Atherosclerosis and inflammatory bowel disease (IBD) are often regarded as 2 distinct entities. The commonest manifestation of atherosclerosis is ischemic heart disease (IHD), and an association between IHD and IBD has been reported. Atherosclerosis and IBD share common pathophysiological mechanisms in terms of their genetics, immunology, and contributing environmental factors. Factors associated with atherosclerosis are implicated in the development of IBD and vice versa. Therefore, treatments targeting the common pathophysiology pathways may be effective in both conditions. The current review considers the pathophysiological pathways that are shared between the 2 conditions and discusses the implications for treatment and research.

Identification of Key Genes in Gastric Cancer by Bioinformatics Analysis

Gastric cancer (GC) is one of the most common malignancies of the digestive system with few genetic markers for its early detection and prevention. In this study, differentially expressed genes (DEGs) were analyzed using GEO2R from GSE54129 and GSE13911 of the Gene Expression Omnibus (GEO). Then, gene enrichment analysis, protein-protein interaction (PPI) network construction, and topological analysis were performed on the DEGs by the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, STRING, and Cytoscape. Finally, we performed survival analysis of key genes through the Kaplan-Meier plotter. A total of 1034 DEGs were identified in GC. GO and KEGG results showed that DEGs mainly enriched in plasma membrane, cell adhesion, and PI3K-Akt signaling pathway. Subsequently, the PPI network with 44 nodes and 333 edges was constructed, and 18 candidate genes in the network were focused on by centrality analysis and module analysis. Furthermore, data showed that high expressions of fibronectin 1(FN1), the tissue inhibitor of metalloproteinases 1 (TIMP1), secreted phosphoprotein 1 (SPP1), apolipoprotein E (APOE), and versican (VCAN) were related to poor overall survivals in GC patients. In summary, this study suggests that FN1, TIMP1, SPP1, APOE, and VCAN may act as the key genes in GC.

Down syndrome iPSC model: endothelial perspective on tumor development

Trisomy 21 (T21), known as Down syndrome (DS), is a widely studied chromosomal abnormality. Previous studies have shown that DS individuals have a unique cancer profile. While exhibiting low solid tumor prevalence, DS patients are at risk for hematologic cancers, such as acute megakaryocytic leukemia and acute lymphoblastic leukemia. We speculated that endothelial cells are active players in this clinical background. To this end, we hypothesized that impaired DS endothelial development and functionality, impacted by genome-wide T21 alterations, potentially results in a suboptimal endothelial microenvironment with the capability to prevent solid tumor growth.

To test this hypothesis, we assessed molecular and phenotypic differences of endothelial cells differentiated from Down syndrome and euploid iPS cells. Microarray, RNA-Seq, and bioinformatic analyses revealed that most significantly expressed genes belong to angiogenic, cytoskeletal rearrangement, extracellular matrix remodeling, and inflammatory pathways. Interestingly, the majority of these genes are not located on Chromosome 21. To substantiate these findings, we carried out functional assays. The obtained phenotypic results correlated with the molecular data and showed that Down syndrome endothelial cells exhibit decreased proliferation, reduced migration, and a weak TNF-α inflammatory response. Based on this data, we provide a set of genes potentially associated with Down syndrome’s elevated leukemic incidence and its unfavorable solid tumor microenvironment—highlighting the potential use of these genes as therapeutic targets in translational cancer research.

Leptin Overexpression as a Poor Prognostic Factor for Colorectal Cancer. Biomed Res Int. 2020;2020:7532514. [PMID: 32596369 DOI: 10.1155/2020/7532514.]

Leptin acts as an adipocytokine functions via the leptin receptor, which stimulates growth, migration, and invasion of cancer cells. This study is aimed at identifying leptin as a prognostic factor in colorectal cancer (CRC). The differentially expressed genes with prognostic value in CRC tissues either with or without liver metastasis were assessed based on The Cancer Genomic Atlas (TCGA). Leptin was considered a candidate gene for further analysis. Its expression features of 206 CRC patients without liver metastasis and 201 patients with metastasis on tissue microarrays were assessed by immunochemical staining, and the effect of leptin on survival was assessed by Kaplan-Meier analyses. Overexpressed leptin indicated a poorer prognosis for CRC patients in overall survival (p < 0.05, log-rank test) based on the TCGA database. The leptin expression significantly correlated with metastasis stage (p < .010) and lymph node involvement (p < .010). Multivariate analysis also indicated that strong leptin expression was an independent adverse prognosticator in CRC (p = .017). Leptin may be valued as a prognostic marker could contribute to predicting a clinical outcome for patients with CRC.

Leptin Overexpression as a Poor Prognostic Factor for Colorectal Cancer

Leptin acts as an adipocytokine functions via the leptin receptor, which stimulates growth, migration, and invasion of cancer cells. This study is aimed at identifying leptin as a prognostic factor in colorectal cancer (CRC). The differentially expressed genes with prognostic value in CRC tissues either with or without liver metastasis were assessed based on The Cancer Genomic Atlas (TCGA). Leptin was considered a candidate gene for further analysis. Its expression features of 206 CRC patients without liver metastasis and 201 patients with metastasis on tissue microarrays were assessed by immunochemical staining, and the effect of leptin on survival was assessed by Kaplan-Meier analyses. Overexpressed leptin indicated a poorer prognosis for CRC patients in overall survival (p < 0.05, log-rank test) based on the TCGA database. The leptin expression significantly correlated with metastasis stage (p < .010) and lymph node involvement (p < .010). Multivariate analysis also indicated that strong leptin expression was an independent adverse prognosticator in CRC (p = .017). Leptin may be valued as a prognostic marker could contribute to predicting a clinical outcome for patients with CRC.

Apolipoprotein: prospective biomarkers in digestive tract cancer

Digestive tract cancer, which is characterized by high morbidity and mortality, seriously affects the quality of life of patients worldwide. The digestive tract has abundant blood supply and nutriment, providing a suitable environment for tumor cells. Under chemical, physical, and biological stimuli, the activated cancer-related genes promote tumorigenesis. The synthesis of apolipoprotein occurs in the liver, intestine, and other digestive organs. However, the functions of apolipoproteins are not limited to lipid metabolism. An increasing number of studies have revealed that apolipoproteins take part in the regulation of tumor behavior. Apolipoprotein A (apoA) has recently been acknowledged as a beneficial indicator of several cancers, including colon, hepatocellular, and pancreatic cancer. Apolipoprotein E (apoE) can affect tumor susceptibility on account of genetic polymorphism. Levels of apolipoprotein C (apoC), B (apoB), and D (apoD) also impact tumor progression and the prognosis of patients. However, because of individual, racial, and genetic differences, a consensus has not yet been reached. Based on clinical data and analysis, apolipoproteins could be a novel target and marker in tumor therapy and prevention.

Quantitative proteomic analysis of bile in extrahepatic cholangiocarcinoma patients

Background and Aims: Extrahepatic cholangiocarcinoma (CCA) without liver-fluke is increasing. Multifactorial carcinogenesis makes it hard to find biomarkers related to CCA. Although there are a few studies of bile proteomics, these showed different protein profiles because of having heterogeneous groups of patients and different sampling methods. Our aim was to identify the specific bile proteins of extrahepatic CCA patients. Methods: We collected bile from 23 patients undergoing endoscopic nasobiliary drainage in Korea University Guro Hospital from May 2018 to January 2019. The CCA group included 18 patients diagnosed with extrahepatic CCA, and the control group included 5 patients with benign biliary conditions. We analyzed bile proteome using liquid chromatography mass spectrometry. We compared the relative abundance of various proteins in the CCA and control groups. Results: In all, we identified a total of 245 proteins in the bile of CCA and control patients. Increased top 14 proteins in CCA patients were immunoglobulin kappa light chain, apolipoprotein B, inter-alpha-trypsin inhibitor heavy chain H4, apolipoprotein E, Mucin 5B, inter-alpha-trypsin inhibitor heavy chain H1, apolipoprotein A-IV, intercellular adhesion molecule 1, complement C7, complement C5, apolipoprotein C-III, albumin, antithrombin-III, and apolipoprotein A-II. However, the significantly increased proteins in bile of CCA patients comparing with control patients were immunoglobulin kappa light chain, apolipoprotein E, albumin, apolipoprotein A-I, antithrombin-III, α1-antitrypsin, serotransferrin, immunoglobulin heavy constant mu, immunoglobulin J chain, complement C4-A, and complement C3 (p<0.05). Conclusions: In this study, we identified several proteins that were significantly increased in the bile of extrahepatic CCA. Further study is needed to validate them as potential tumor-associated proteins that may be potential biomarkers for CCA.

Revelation of Proteomic Indicators for Colorectal Cancer in Initial Stages of Development

Background: Colorectal cancer (CRC) at a current clinical level is still hardly diagnosed, especially with regard to nascent tumors, which are typically asymptotic. Searching for reliable biomarkers of early diagnosis is an extremely essential task. Identification of specific post-translational modifications (PTM) may also significantly improve net benefits and tailor the process of CRC recognition. We examined depleted plasma samples obtained from 41 healthy volunteers and 28 patients with CRC at different stages to conduct comparative proteome-scaled analysis. The main goal of the study was to establish a constellation of protein markers in combination with their PTMs and semi-quantitative ratios that may support and realize the distinction of CRC until the disease has a poor clinical manifestation. Results: Proteomic analysis revealed 119 and 166 proteins for patients in stages I–II and III–IV, correspondingly. Plenty of proteins (44 proteins) reflected conditions of the immune response, lipid metabolism, and response to stress, but only a small portion of them were significant (p < 0.01) for distinguishing stages I–II of CRC. Among them, some cytokines (Clusterin (CLU), C4b-binding protein (C4BP), and CD59 glycoprotein (CD59), etc.) were the most prominent and the lectin pathway was specifically enhanced in patients with CRC. Significant alterations in Inter-alpha-trypsin inhibitor heavy chains (ITIH1, ITIH2, ITIH3, and ITIH4) levels were also observed due to their implication in tumor growth and the malignancy process. Other markers (Alpha-1-acid glycoprotein 2 (ORM2), Alpha-1B-glycoprotein (A1BG), Haptoglobin (HP), and Leucine-rich alpha-2-glycoprotein (LRG1), etc.) were found to create an ambiguous core involved in cancer development but also to exactly promote tumor progression in the early stages. Additionally, we identified post-translational modifications, which according to the literature are associated with the development of colorectal cancer, including kininogen 1 protein (T327-p), alpha-2-HS-glycoprotein (S138-p) and newly identified PTMs, i.e., vitamin D-binding protein (K75-ac and K370-ac) and plasma protease C1 inhibitor (Y294-p), which may also contribute and negatively impact on CRC progression. Conclusions: The contribution of cytokines and proteins of the extracellular matrix is the most significant factor in CRC development in the early stages. This can be concluded since tumor growth is tightly associated with chronic aseptic inflammation and concatenated malignancy related to loss of extracellular matrix stability. Due attention should be paid to Apolipoprotein E (APOE), Apolipoprotein C1 (APOC1), and Apolipoprotein B-100 (APOB) because of their impact on the malfunction of DNA repair and their capability to regulate mTOR and PI3K pathways. The contribution of the observed PTMs is still equivocal, but a significant decrease in the likelihood between modified and native proteins was not detected confidently.

Integrated bioinformatics analysis of the association between apolipoprotein E expression and patient prognosis in papillary thyroid carcinoma

The prognosis of most patients with papillary thyroid carcinoma (PTC) is excellent despite some cases of tumor progression or relapse. The present study was designed to reveal possible prognostic risk indicators for PTC. Differentially expressed genes (DEGs) extracted from 4 Gene Expression Omnibus (GEO) cohorts were subjected to functional enrichment analyses by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis. A dataset from The Cancer Genome Atlas (TCGA) was obtained to filter and validate significant genes using cytoHubba, followed by analysis of their association with clinicopathological characteristics and prognosis. In total, 240 DEGs were identified after data preprocessing. These DEGs were enriched in ‘intracellular redox equilibrium’, ‘release of exosome’, ‘cell adhesion’, ‘regulation of extracellular matrix’, ‘collagen binding’ and ‘energy metabolism’ based on GO analysis which including cellular component, molecular function and biological process. KEGG pathway analysis revealed that the DEGs were enriched in thyroid hormone synthesis, pathways in cancer, focal adhesion, metabolic pathways, apoptosis, PPAR signaling pathway and PI3K/AKT signaling pathway. Using cytoHubba, the following hub genes were identified: Apolipoprotein E (APOE); hemoglobin subunit α1 (HBA1); angiotensin II receptor 1 (AGTR1); collagen I α1 (COL1A1); galectin 3 (LGALS3) and TIMP metallopeptidase inhibitor 1 (TIMP1). The expression of these genes was found to be consistent in TCGA datasets. Kaplan-Meier analysis revealed that APOE was significantly associated with overall survival (P=0.00067) and disease free survival (P=0.00220). Additionally, low expression of APOE was significantly associated with older age (P<0.001) and higher TNM stage (P<0.001) compared with the high expression group. Therefore, APOE may function as a predictive risk indicator for progression as well as prognosis of PTC.

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.

Identification and Clinical Validation of a Novel 4 Gene-Signature with Prognostic Utility in Colorectal Cancer

Colorectal cancer (CRC) is a high burden disease with several genes involved in tumor progression. The aim of the present study was to identify, generate and clinically validate a novel gene signature to improve prediction of overall survival (OS) to effectively manage colorectal cancer. We explored The Cancer Genome Atlas (TCGA), COAD and READ datasets (597 samples) from The Protein Atlas (TPA) database to extract a total of 595 candidate genes. In parallel, we identified 29 genes with perturbations in > 6 cancers which are also affected in CRC. These genes were entered in cBioportal to generate a 17 gene panel with highest perturbations. For clinical validation, this gene panel was tested on the FFPE tissues of colorectal cancer patients (88 patients) using Nanostring analysis. Using multivariate analysis, a high prognostic score (composite 4 gene signature-DPP7/2, YWHAB, MCM4 and FBXO46) was found to be a significant predictor of poor prognosis in CRC patients (HR: 3.42, 95% CI: 1.71-7.94, p < 0.001 *) along with stage (HR: 4.56, 95% CI: 1.35-19.15, p = 0.01 *). The Kaplan-Meier analysis also segregated patients on the basis of prognostic score (log-rank test, p = 0.001 *). The external validation using GEO dataset (GSE38832, 122 patients) corroborated the prognostic score (HR: 2.7, 95% CI: 1.99-3.73, p < 0.001 *). Additionally, higher score was able to differentiate stage II and III patients (130 patients) on the basis of OS (HR: 2.5, 95% CI: 1.78-3.63, p < 0.001 *). Overall, our results identify a novel 4 gene prognostic signature that has clinical utility in colorectal cancer.