Quantitative proteomic analysis exploring progression of colorectal cancer: Modulation of the serpin family. J Proteomics. 2016;148:139-148. [PMID: 27492143 DOI: 10.1016/j.jprot.2016.07.031]

Machine Learning-Enhanced Extraction of Biomarkers for High-Grade Serous Ovarian Cancer from Proteomics Data

Comprehensive biomedical proteomic datasets are accumulating exponentially, warranting robust analytics to deconvolute them for identifying novel biological insights. Here, we report a strategic machine learning (ML)-based feature extraction workflow that was applied to unveil high-performing protein markers for high-grade serous ovarian carcinoma (HGSOC) from publicly available ovarian cancer tissue and serum proteomics datasets. Diagnosis of HGSOC, an aggressive form of ovarian cancer, currently relies on diagnostic methods based on tissue biopsy and/or non-specific biomarkers such as the cancer antigen 125 (CA125) and human epididymis protein 4 (HE4). Our newly developed ML-based approach enabled the identification of new serum proteomic biomarkers for HGSOC. The performance verification of these marker combinations using two independent cohorts affirmed their outperformance against known biomarkers for ovarian cancer including clinically used serum markers with >97% AUC. Our analysis also added novel biological insights such as enriched cancer-related processes associated with HGSOC.

Mass Spectrometry Proteomics Characterization of Plasma Biomarkers for Colorectal Cancer Associated With Inflammation

Background

Colorectal cancer (CRC) prognosis is determined by the disease stage with low survival rates for advanced stages. Current CRC screening programs are mainly using colonoscopy, limited by its invasiveness and high cost. Therefore, non-invasive, cost-effective, and accurate alternatives are urgently needed.

Objective and design

This retrospective multi-center plasma proteomics study was performed to identify potential blood-based biomarkers in 36 CRC patients and 26 healthy volunteers by high-resolution mass spectrometry proteomics followed by the validation in an independent CRC cohort (60 CRC patients and 44 healthy subjects) of identified selected biomarkers.

Results

Among the 322 identified plasma proteins, 37 were changed between CRC patients and healthy volunteers and were associated with the complement cascade, cholesterol metabolism, and SERPIN family members. Increased levels in CRC patients of the complement proteins C1QB, C4B, and C5 as well as pro-inflammatory proteins, lipopolysaccharide-binding protein (LBP) and serum amyloid A4, constitutive (SAA4) were revealed for first time. Importantly, increased level of C5 was verified in an independent validation CRC cohort. Increased C4B and C8A levels were correlated with cancer-associated inflammation and CRC progression, while cancer-associated inflammation was linked to the acute-phase reactant leucine-rich alpha-2-glycoprotein 1 (LRG1) and ceruloplasmin. Moreover, a 4-protein signature including C4B, C8A, apolipoprotein C2 (APO) C2, and immunoglobulin heavy constant gamma 2 was changed between early and late CRC stages.

Conclusion

Our results suggest that C5 could be a potential biomarker for CRC diagnosis. Further validation studies will aid the application of these new potential biomarkers to improve CRC diagnosis and patient care.

Proteomics: Unraveling the Cross Talk Between Innate Immunity and Disease Pathophysiology, Diagnostics, and Treatment Options

Inflammation is crucial in diseases, and proteins play a key role in the interplay between innate immunity and pathology. This review explores how proteomics helps understanding this relationship, focusing on diagnosis and treatment. We explore the dynamic innate response and the significance of proteomic techniques in deciphering the complex network of proteins involved in prevalent diseases, including infections, cancer, autoimmune and neurodegenerative disorders. Proteomics identifies key proteins in host-pathogen interactions, shedding light on infection mechanisms and inflammation. These discoveries hold promise for diagnostic tools, therapies, and vaccines. In cancer research, proteomics reveals innate signatures associated with tumor development, immune evasion, and therapeutic response. Additionally, proteomic analysis has unveiled autoantigens and dysregulation of the innate immune system in autoimmunity, offering opportunities for early diagnosis, disease monitoring, and new therapeutic targets. Moreover, proteomic analysis has identified altered protein expression patterns in neurodegenerative diseases like Alzheimer's and Parkinson's, providing insights into potential therapeutic strategies. Proteomics of the innate immune system provides a comprehensive understanding of disease mechanisms, identifies biomarkers, and enables effective interventions in various diseases. Despite still in its early stages, this approach holds great promise to revolutionize innate immunity research and significantly improve patient outcomes across a wide range of diseases.

An Updated Review on Molecular Biomarkers in Diagnosis and Therapy of Colorectal Cancer

Colorectal cancer is one of the most common cancer types worldwide. Since colorectal cancer takes time to develop, its incidence and mortality can be treated effectively if it is detected in its early stages. As a result, non-invasive or invasive biomarkers play an essential role in the early diagnosis of colorectal cancer. Many experimental studies have been carried out to assess genetic, epigenetic, or protein markers in feces, serum, and tissue. It may be possible to find biomarkers that will help with the diagnosis of colorectal cancer by identifying the genes, RNAs, and/or proteins indicative of cancer growth. Recent advancements in the molecular subtypes of colorectal cancer, DNA methylation, microRNAs, long noncoding RNAs, exosomes, and their involvement in colorectal cancer have led to the discovery of novel biomarkers. In small-scale investigations, most biomarkers appear promising. However, large-scale clinical trials are required to validate their effectiveness before routine clinical implementation. Hence, this review focuses on small-scale investigations and results of big data analysis that may provide an overview of the biomarkers for the diagnosis, therapy, and prognosis of colorectal cancer.

Beneficial effects of alpha-1 antitrypsin therapy in a mouse model of colitis-associated colon cancer

BACKGROUND

It is widely accepted that chronic inflammatory bowel diseases significantly higher a risk for colorectal cancer development. Among different types of treatments for patients with colon cancer, novel protein-based therapeutic strategies are considered.

AIM

To explore the effect of human plasma alpha-1 antitrypsin (AAT) protein in the chemically induced mouse model of colorectal cancer.

METHODS

BALB/c mice with azoxymethane/dextran sodium sulfate (AOM/DSS)-induced colitis-associated colorectal cancer (CAC), we intraperitoneally treated with commercial preparation of human plasma AAT (4 mg per mouse). Effects of this therapy were evaluated histologically, and by immunohistochemical and gene expression assays.

RESULTS

When compared with non-treated controls, AOM/DSS mice receiving AAT therapy exhibited significantly longer colons, and less anal bleeding. Concurrently, AAT-treated mice had significantly fewer polyps, and lower numbers of large colon tumors. Immunohistochemical examinations of colon tissues showed significantly lower neutrophil counts, more granzyme B-positive but fewer MMP9 (gelatinase B)-positive cancer cells and lower numbers of apoptotic cells in mice receiving AAT therapy. The expression levels of IL4 were significantly higher while TNFA was slightly reduced in tumor tissues of AOM/DSS mice treated with AAT than in AOM/DSS mice.

CONCLUSION

Human AAT is an acute phase protein with a broad-protease inhibitory and immunomodulatory activities used as a therapeutic for emphysema patients with inherited AAT deficiency. Our results are consistent with previous findings and support an idea that AAT alone and/or in combination with available anti-cancer therapies may represent a new personalized approach for patients with colitis-induced colon cancer.

Construction of a fecal immune-related protein-based biomarker panel for colorectal cancer diagnosis: a multicenter study

Purpose

To explore fecal immune-related proteins that can be used for colorectal cancer (CRC) diagnosis.

Patients and methods

Three independent cohorts were used in present study. In the discovery cohort, which included 14 CRC patients and 6 healthy controls (HCs), label-free proteomics was applied to identify immune-related proteins in stool that could be used for CRC diagnosis. Exploring potential links between gut microbes and immune-related proteins by 16S rRNA sequencing. The abundance of fecal immune-associated proteins was verified by ELISA in two independent validation cohorts and a biomarker panel was constructed that could be used for CRC diagnosis. The validation cohort I included 192 CRC patients and 151 HCs from 6 different hospitals. The validation cohort II included 141 CRC patients, 82 colorectal adenoma (CRA) patients, and 87 HCs from another hospital. Finally, the expression of biomarkers in cancer tissues was verified by immunohistochemistry (IHC).

Results

In the discovery study, 436 plausible fecal proteins were identified. And among 67 differential fecal proteins (|log2 fold change| > 1, P< 0.01) that could be used for CRC diagnosis, 16 immune-related proteins with diagnostic value were identified. The 16S rRNA sequencing results showed a positive correlation between immune-related proteins and the abundance of oncogenic bacteria. In the validation cohort I, a biomarker panel consisting of five fecal immune-related proteins (CAT, LTF, MMP9, RBP4, and SERPINA3) was constructed based on the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression. The biomarker panel was found to be superior to hemoglobin in the diagnosis of CRC in both validation cohort I and validation cohort II. The IHC result showed that protein expression levels of these five immune-related proteins were significantly higher in CRC tissue than in normal colorectal tissue.

Conclusion

A novel biomarker panel consisting of fecal immune-related proteins can be used for the diagnosis of CRC.

SERPINA3: Stimulator or Inhibitor of Pathological Changes

SERPINA3, also called α-1-antichymotrypsin (AACT, ACT), is one of the inhibitors of serine proteases, one of which is cathepsin G. As an acute-phase protein secreted into the plasma by liver cells, it plays an important role in the anti-inflammatory response and antiviral response. Elevated levels of SERPINA3 have been observed in heart failure and neurological diseases such as Alzheimer's disease or Creutzfeldt-Jakob disease. Many studies have shown increased expression levels of the SERPINA3 gene in various types of cancer, such as glioblastoma, colorectal cancer, endometrial cancer, breast cancer, or melanoma. In this case, the SERPINA3 protein is associated with an antiapoptotic function implemented by adjusting the PI3K/AKT or MAPK/ERK 1/2 signal pathways. However, the functions of the SERPINA3 protein are still only partially understood, mainly in the context of cancerogenesis, so it seems necessary to summarize the available information and describe its mechanism of action. In particular, we sought to amass the existing body of research focusing on the description of the underlying mechanisms of various diseases not related to cancer. Our goal was to present an overview of the correct function of SERPINA3 as part of the defense system, which unfortunately easily becomes the "Fifth Column" and begins to support processes of destruction.

Proteomic changes associated with maternal dietary low ω6:ω3 ratio in piglets supplemented with seaweed. Part I: Serum proteomes

This study examines whether maternal low ω6:ω3 ratio diet and offspring SW supplementation can improve offspring immunity and performance by elucidating the effects on piglet serum proteome. A total of 16 sows were given either a standard (CR, 13:1) or low ω6:ω3 ratio diet (LR, 4:1) during pregnancy and lactation and their male weaned piglets were supplemented with SW powder (4 g/kg, SW) or not (CT) in a 21-day post-weaning (PW) diet. Four PW piglet groups were then identified based on dam and piglet treatment, namely CRCT, CRSW, LRCT, and LRSW (n = 10 each). Piglet serum collected at weaning and d21 PW were analysed (n = 5 each) using TMT-based quantitative proteomics and validated by appropriate assays. The differentially abundant proteins (n = 122) displayed positive effects of maternal LR diet on anti-inflammatory properties and innate immune stimulation. Progeny SW diet activated the innate immunity and enhance the host defence during inflammation. These data demonstrate the value of decreasing ω6:ω3 ratio in maternal diet and SW supplementation in PW piglet's diet to boost their immunity and anti-inflammation properties. SIGNIFICANCE: This novel proteomic study in post-weaned piglets addresses the interplay between maternal and offspring nutritional interventions in a context of rapid and dynamic alterations in piglet metabolic status around weaning. Decreasing ω6:ω3 ratio in maternal diet and SW supplementation in PW piglet's diet can boost their immunity and anti-inflammation properties. This study also provides new insights into piglet serum proteome regulation during post-weaning, a critical development period in swine.

Multi-Omics Approaches in Colorectal Cancer Screening and Diagnosis, Recent Updates and Future Perspectives

Colorectal cancer (CRC) is common Cancer as well as the third leading cause of mortality around the world; its exact molecular mechanism remains elusive. Although CRC risk is significantly correlated with genetic factors, the pathophysiology of CRC is also influenced by external and internal exposures and their interactions with genetic factors. The field of CRC research has recently benefited from significant advances through Omics technologies for screening biomarkers, including genes, transcripts, proteins, metabolites, microbiome, and lipidome unbiasedly. A promising application of omics technologies could enable new biomarkers to be found for the screening and diagnosis of CRC. Single-omics technologies cannot fully understand the molecular mechanisms of CRC. Therefore, this review article aims to summarize the multi-omics studies of Colorectal cancer, including genomics, transcriptomics, proteomics, microbiomics, metabolomics, and lipidomics that may shed new light on the discovery of novel biomarkers. It can contribute to identifying and validating new CRC biomarkers and better understanding colorectal carcinogenesis. Discovering biomarkers through multi-omics technologies could be difficult but valuable for disease genotyping and phenotyping. That can provide a better knowledge of CRC prognosis, diagnosis, and treatments.

Synergistic effects of nab-PTX and anti-PD-1 antibody combination against lung cancer by regulating the Pi3K/AKT pathway through the Serpinc1 gene

Lung cancer is a type of cancer with higher morbidity and mortality. In spite of the impressive response rates of nab-paclitaxel (nab-PTX) or programmed cell death-1 (PD-1) and its ligand inhibitors, the effective treatment remains limited. Currently, alternative strategies aim at drug combination of nab-PTX and PD-1/PD-L1 inhibitors. Even as the clinical impact of the combined agents continues to increase, basic research studies are still limited and the mechanisms underlying this synergy are not well studied. In this study, we evaluated the antitumor efficacy and the molecular mechanisms of action of nab-PTX in combination with anti-PD-1 antibody, using Lewis lung carcinoma (LLC) cell and subcutaneously transplanted tumor models. The combination of nab-PTX and anti-PD-1 antibody displayed stronger antitumor effects, manifested at tumor volume, proliferation and apoptosis through Ki67 and TUNEL staining. In-vivo experiments showed significant increases in CD4+ T cells, CD8+ T cells, IFN-γ, TNF-α, IL-2, PF, and Gzms-B, exerting antitumor effects with reductions in MDSCs and IL-10 after the treatments. Furthermore, transcriptomic analysis indicated 20 overlapped differentially expressed genes, and Serpin peptidase inhibitor clade C Member 1 (Serpinc1) was downregulated during treatment in vivo, whose expression level was markedly related to metastasis and overall survival of lung cancer patients. Functional enrichment analysis of the target gene revealed primary GO terms related to tumor, which warrants further investigation. We also found that Serpinc1 overexpression promoted cell proliferation, migration, and invasion and inhibited cell apoptosis of LLC cells in vitro, possibly regulating the associated factors via the Pi3K/AKT pathway. In summary, our results reveal the synergistic antitumor responses of nab-PTX combined with anti-PD-1 antibody, in which Serpinc1 may play an important role, providing a target gene for combination treatment strategy.

Distant Metastasis Pattern and Prognostic Prediction Model of Colorectal Cancer Patients Based on Big Data Mining

Aims

This study aimed to investigate the distant metastasis pattern from newly diagnosed colorectal cancer (CRC) and also construct and validate a prognostic nomogram to predict both overall survival (OS) and cancer-specific survival (CSS) of CRC patients with distant metastases.

Methods

Primary CRC patients who were initially diagnosed from 2010 to 2016 in the SEER database were included in the analysis. The independent risk factors affecting the OS, CSS, all-cause mortality, and CRC-specific mortality of the patients were screened by the Cox regression and Fine–Gray competitive risk model. The nomogram models were constructed to predict the OS and CSS of the patients. The reliability and accuracy of the prediction model were evaluated by consistency index (C-index) and calibration curve. The gene chip GSE41258 was downloaded from the GEO database, and differentially expressed genes (DEGs) were screened by the GEO2R online tool (p < 0.05, |logFC|>1.5). The Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway and Gene Ontology (GO) annotation and String website were used for enrichment analysis and protein–protein interaction (PPI) analysis of DEGs, respectively, and Cytoscape software was used to construct PPI network and screen function modules and hub genes.

Results

A total of 57,835 CRC patients, including 47,823 without distant metastases and 10,012 (17.31%) with metastases, were identified. Older age, unmarried status, poorly differentiated or undifferentiated grade, right colon site, larger tumor size, N2 stage, more metastatic sites, and elevated carcinoembryonic antigen (CEA) might lead to poorer prognosis (all p < 0.01). The independent risk factors of OS and CSS were included to construct a prognosis prediction model for predicting OS and CSS in CRC patients with distant metastasis. C-index and calibration curve of the training group and validation group showed that the models had acceptable predictive performance and high calibration degree. Furthermore, by comparing CRC tissues with and without liver metastasis, 158 DEGs and top 10 hub genes were screened. Hub genes were mainly concentrated in liver function and coagulation function.

Conclusion

The big data in the public database were counted and transformed into a prognostic evaluation tool that could be applied to the clinic, which has certain clinical significance for the formulation of the treatment plan and prognostic evaluation of CRC patients with distant metastasis.

Advances in High Throughput Proteomics Profiling in Establishing Potential Biomarkers for Gastrointestinal Cancer

Gastrointestinal cancers (GICs) remain the most diagnosed cancers and accounted for the highest cancer-related death globally. The prognosis and treatment outcomes of many GICs are poor because most of the cases are diagnosed in advanced metastatic stages. This is primarily attributed to the deficiency of effective and reliable early diagnostic biomarkers. The existing biomarkers for GICs diagnosis exhibited inadequate specificity and sensitivity. To improve the early diagnosis of GICs, biomarkers with higher specificity and sensitivity are warranted. Proteomics study and its functional analysis focus on elucidating physiological and biological functions of unknown or annotated proteins and deciphering cellular mechanisms at molecular levels. In addition, quantitative analysis of translational proteomics is a promising approach in enhancing the early identification and proper management of GICs. In this review, we focus on the advances in mass spectrometry along with the quantitative and functional analysis of proteomics data that contributes to the establishment of biomarkers for GICs including, colorectal, gastric, hepatocellular, pancreatic, and esophageal cancer. We also discuss the future challenges in the validation of proteomics-based biomarkers for their translation into clinics.

Metaproteomic Profile of the Colonic Luminal Microbiota From Patients With Colon Cancer

Recent studies have provided evidence of interactions among the gut microbiota (GM), local host immune cells, and intestinal tissues in colon carcinogenesis. However, little is known regarding the functions exerted by the GM in colon cancer (CC), particularly with respect to tumor clinical classification and lymphocyte infiltration. In addition, stool, usually employed as a proxy of the GM, cannot fully represent the original complexity of CC microenvironment. Here, we present a pilot study aimed at characterizing the metaproteome of CC-associated colonic luminal contents and identifying its possible associations with CC clinicopathological features. Colonic luminal contents were collected from 24 CC tissue specimens immediately after surgery. Samples were analyzed by shotgun metaproteomics. Almost 30,000 microbial peptides were quantified in the samples, enabling the achievement of the taxonomic and functional profile of the tumor-associated colonic luminal metaproteome. Upon sample aggregation based on tumor stage, grade, or tumor-infiltrating lymphocytes (TILs), peptide sets enabling discrimination of sample groups were identified through discriminant analysis (DA). As a result, Bifidobacterium and Bacteroides fragilis were significantly enriched in high-stage and high-grade CC, respectively. Among metabolic functions, formate-tetrahydrofolate ligase was significantly associated with high-stage CC. Finally, based on the results of this pilot study, we assessed the optimal sample size for differential metaproteomic studies analyzing colonic luminal contents. In conclusion, we provide a detailed picture of the microbial and host components of the colonic luminal proteome and propose promising associations between GM taxonomic/functional features and CC clinicopathological features. Future studies will be needed to verify the prognostic value of these data and to fully exploit the potential of metaproteomics in enhancing our knowledge concerning CC progression.

Commentary on: Screening of immunosuppressive cells from colorectal adenocarcinoma and identification of prognostic markers

Colorectal adenocarcinoma (COAD) is one subtype of colorectal carcinoma (CRC), whose development is associated with genetics, inappropriate immune response, and environmental factors. Although significant advances have been made in the treatment of COAD, the mortality rate remains high. It is a pressing need to explore novel therapeutic targets of COAD. Available evidence indicated that immune cell infiltration was correlated with cancer prognosis. To reveal the roles of immune cells in the COAD prognosis, a study published in Bioscience Reports by Li et al. (Bioscience Reports (2021) 41, https://doi.org/10.1042/BSR20203496) analyzed data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) dataset. It demonstrated a beneficial effect of Th17 cells in COAD prognosis. In addition, six hub genes (KRT23, ULBP2, ASRGL1, SERPINA1, SCIN, and SLC28A2) were identified to correlate with Th17 cells and COAD prognosis, suggesting one new therapy strategy and some predictive biomarkers of COAD. These findings reported by Li et al. may pave one way to explore the molecular mechanism of COAD further.

Identification of potential core genes in colorectal carcinoma and key genes in colorectal cancer liver metastasis using bioinformatics analysis

Colorectal carcinoma (CRC) is one of the most prevalent malignant tumors worldwide. Meanwhile, the majority of CRC related deaths results from liver metastasis. Gene expression profile of CRC patients with liver Metastasis was identified using 4 datasets. The data was analyzed using GEO2R tool. GO and KEGG pathway analysis were performed. PPI network of the DEGs between 1 and 2 gene sets was also constructed. The set 1 is named between primary CRC tissues and metastatic CRC tissues. The set 2 is named between primary CRC tissues and normal tissues. Finally, the prognostic value of hub genes was also analyzed. 35 DEGs (set 1) and 142 DEGs (set 2) were identified between CRC liver metastatic cancer patients. The PPI network was constructed using the top 10 set 1 hub genes which included AHSG, SERPINC1, FGA, F2, CP, ITIH2, APOA2, HPX, PLG, HRG and set 2 hub genes which included TIMP1, CXCL1, COL1A2, MMP1, AURKA, UBE2C, CXCL12, TOP2A, ALDH1A1 and PRKACB. Therefore, ITIH2 might represent the potential core gene for colon cancer liver metastasis. COL1A2 behaves as a key gene in colorectal carcinoma.

Systems-level biomarkers identification and drug repositioning in colorectal cancer

Colorectal cancer (CRC) is the most commonly diagnosed fatal cancer in both women and men worldwide. CRC ranked second in mortality and third in incidence in 2020. It is difficult to diagnose CRC at an early stage as there are no clinical symptoms. Despite advances in molecular biology, only a limited number of biomarkers have been translated into routine clinical practice to predict risk, prognosis and response to treatment. In the last decades, systems biology approaches at the omics level have gained importance. Over the years, several biomarkers for CRC have been discovered in terms of disease diagnosis and prognosis. On the other hand, a few drugs are being developed and used in clinics for the treatment of CRC. However, the development of new drugs is very costly and time-consuming as the research and development takes about 10 years and more than $1 billion. Therefore, drug repositioning (DR) could save time and money by establishing new indications for existing drugs. In this review, we aim to provide an overview of biomarkers for the diagnosis and prognosis of CRC from the systems biology perspective and insights into DR approaches for the prevention or treatment of CRC.

Extracellular Granzyme A Promotes Colorectal Cancer Development by Enhancing Gut Inflammation

If not properly regulated, the inflammatory immune response can promote carcinogenesis, as evident in colorectal cancer (CRC). Aiming to gain mechanistic insight into the link between inflammation and CRC, we perform transcriptomics analysis of human CRC, identifying a strong correlation between expression of the serine protease granzyme A (GzmA) and inflammation. In a dextran sodium sulfate and azoxymethane (DSS/AOM) mouse model, deficiency and pharmacological inhibition of extracellular GzmA both attenuate gut inflammation and prevent CRC development, including the initial steps of cell transformation and epithelial-to-mesenchymal transition. Mechanistically, extracellular GzmA induces NF-κB-dependent IL-6 production in macrophages, which in turn promotes STAT3 activation in cultured CRC cells. Accordingly, colon tissues from DSS/AOM-treated, GzmA-deficient animals present reduced levels of pSTAT3. By identifying GzmA as a proinflammatory protease that promotes CRC development, these findings provide information on mechanisms that link immune cell infiltration to cancer progression and present GzmA as a therapeutic target for CRC.

Screening of immunosuppressive cells from colorectal adenocarcinoma and identification of prognostic markers

Background: Colorectal cancer (CRC) is the most common type of gastrointestinal malignant tumour. Colorectal adenocarcinoma (COAD) – the most common type of CRC – is particularly dangerous. The role of the immune system in the development of tumour-associated inflammation and cancer has received increasing attention recently.

Methods: In the present study, we compiled the expression profiles of 262 patients with complete follow-up data from The Cancer Genome Atlas (TCGA) database as an experimental group and selected 65 samples from the Gene Expression Omnibus (GEO) dataset (of which 46 samples were with M0) as a verification group. First, we screened the immune T helper 17 (Th17) cells related to the prognosis of COAD. Subsequently, we identified Th17 cells-related hub genes by utilising Weighted Gene Co-expression Network Analysis (WGCNA) and Least Absolute Shrinkage and Selector Operation (LASSO) regression analysis. Six genes associated with the prognosis in patients with COAD were identified, including: KRT23, ULBP2, ASRGL1, SERPINA1, SCIN, and SLC28A2. We constructed a clinical prediction model and analysed its predictive power.

Results: The identified hub genes are involved in developing many diseases and closely linked to digestive disorders. Our results suggested that the hub genes could influence the prognosis of COAD by regulating Th17 cells’ infiltration.

Conclusions: These newly discovered hub genes contribute to clarifying the mechanisms of COAD development and metastasis. Given that they promote COAD development, they may become new therapeutic targets and biomarkers of COAD.

A Meta-Analysis of Proteomic Blood Markers of Colorectal Cancer

BACKGROUND

Early diagnosis will significantly improve the survival rate of colorectal cancer (CRC); however, the existing methods for CRC screening were either invasive or inefficient. There is an emergency need for novel markers in CRC's early diagnosis. Serum proteomics has gained great potential in discovering novel markers, providing markers that reflect the early stage of cancer and prognosis prediction of CRC. In this paper, the results of proteomics of CRC studies were summarized through a meta-analysis in order to obtain the diagnostic efficiency of novel markers.

METHODS

A systematic search on bibliographic databases was performed to collect the studies that explore blood-based markers for CRC applying proteomics. The detection and validation methods, as well as the specificity and sensitivity of the biomarkers in these studies, were evaluated. Newcastle- Ottawa Scale (NOS) case-control studies version was used for quality assessment of included studies.

RESULTS

Thirty-four studies were selected from 751 studies, in which markers detected by proteomics were summarized. In total, fifty-nine proteins were classified according to their biological function. The sensitivity, specificity, or AUC varied among these markers. Among them, Mammalian STE20-like protein kinase 1/ Serine threonine kinase 4 (MST1/STK4), S100 calcium-binding protein A9 (S100A9), and Tissue inhibitor of metalloproteinases 1 (TIMP1) were suitable for effect sizes merging, and their diagnostic efficiencies were recalculated after merging. MST1/STK4 obtained a sensitivity of 68% and a specificity of 78%. S100A9 achieved a sensitivity of 72%, a specificity of 83%, and an AUC of 0.88. TIMP1 obtained a sensitivity of 42%, a specificity of 88%, and an AUC of 0.71.

CONCLUSION

MST1/STK4, S100A9, and TIMP1 showed excellent performance for CRC detection. Several other markers also presented optimized diagnostic efficacy for CRC early detection, but further verification is still needed before they are suitable for clinical use. The discovering of more efficient markers will benefit CRC treatment.

Identification of immune-related gene signature predicting survival in the tumor microenvironment of lung adenocarcinoma

The tumor microenvironment (TME) plays an essential role in the occurrence and progression of malignancy. The potential prognostic TME-related biomarkers of lung adenocarcinoma (LUAD) remained unclear, which were investigated in this research. The RNA-sequencing profiles and corresponding clinical parameters were extracted from TCGA and GEO databases, based on which the stromal and immune scores were calculated through the ESTIMATE algorithm. Overlapping differentially expressed genes between stromal and immune score group were analyzed by the LASSO and Random Forrest algorithms and validated in cases from our center. And a prognostic 8-gene signature was constructed using Cox regression. The infiltration of 22 hematopoietic cell phenotypes was assessed by the CIBERSORT algorithms. We found that female, elder patients, and solid predominant subtype had obviously higher stromal and immune scores. And patients with early stage LUAD received a prominently higher immune score. A high stromal or immune score meant a good prognosis. Subsequently, eight TME-related prognostic genes (ATAD5, CYP4F3, CYP4F12, ESPNL, FXYD2, GPX2, NLGN4Y, and SERPINC1) were identified by both LASSO regression and Radom Forest algorithms. High 8-gene signature group exhibited worse overall survival. Furthermore, B cell naïve, plasma cells, T cell follicular helper, and macrophages M1 were prominently more in high signature group. Nevertheless, fewer T cells CD4 memory resting, monocytes, and dendritic cell resting were identified in the high signature group. The composition of the tumor microenvironment significantly affected the prognosis of LUAD patients. We provided a new strategy for the exploration of prognostic TME-related biomarkers and immunotherapy.

Identification of a Multi-RNA-Type-Based Signature for Recurrence-Free Survival Prediction in Patients with Uterine Corpus Endometrial Carcinoma

Uterine corpus endometrial carcinoma (UCEC) is one of the leading causes of death from gynecological cancer due to the high recurrence rate. A recent study indicated that molecular biomarkers can enhance the recurrence prediction power if they were integrated with clinical information. In this study, we attempted to identify a new multi-RNA-type-based molecular biomarker for predicting the recurrence risk and recurrence-free survival (RFS). Matched mRNA (including lncRNA) and miRNA RNA-sequencing data from 463 UCEC patients (n = 75, recurrent; n = 388, non-recurrent) were downloaded from The Cancer Genome Atlas database. LASSO (least absolute shrinkage and selection operator) analysis was used to screen the optimal combination of prognostic RNAs and then the risk score model was constructed. Moreover, the molecular mechanisms of prognostic RNAs were explored by establishing various interaction networks based on corresponding predictive databases. A multi-RNA-type-based signature (including three miRNAs: hsa-miR-6511b, hsa-miR-184, hsa-miR-4461; three lncRNAs: ENO1-IT1, MCCC1-AS1, AATBC; and 7 mRNAs: EPPK1, ASB9, BDNF, CYP11A1, ECEL1, EN2, F13A1) was developed for the prediction of RFS. The risk scoring system established by these signature genes was effective for the discrimination of the 5-year RFS in the high-risk from low-risk patients in the training [an area under the receiver operating characteristic curve (AUC) = 0.960], validation (AUC = 0.863), and entire datasets (AUC = 0.873). This risk score model was also proved to be a more excellent, independent prognostic discriminator than the single-RNA-type (overall AUC: 0.947 vs. 0.677, lncRNAs; 0.709, miRNAs; 0.899, mRNAs) and clinical staging (overall AUC: 0.947 vs. 0.517). Furthermore, the downstream mechanisms for some prognostic miRNAs or lncRNAs (HAND2-AS1-hsa-miR-6511b-APC2, PAX8-AS1-hsa-miR-4461-TNIK and MCCC1-AS1/ENO1-IT1-TNIK) were newly predicted based on the coexpression or competitive endogenous RNA theories. In conclusion, our findings may provide novel biomarkers for recurrence prediction and targets for treatment of UCEC.

Biomarkers in Colorectal Cancer: The Role of Translational Proteomics Research

Colorectal cancer is one of the most common cancers in the world, and it is one of the leading causes of cancer-related death. Despite recent progress in the development of screening programs and in the management of patients with colorectal cancer, there are still many gaps to fill, ranging from the prevention and early diagnosis to the determination of prognosis factors and treatment of metastatic disease, to establish a personalized approach. The genetic profile approach has been increasingly used in the decision-making process, especially in the choice of targeted therapies and in the prediction of drug response, but there are still few validated biomarkers of colorectal cancer for clinical practice. The discovery of non-invasive, sensitive, and specific biomarkers is an urgent need, and translational proteomics play a key role in this process, as they enable better comprehension of colorectal carcinogenesis, identification of potential markers, and subsequent validation. This review provides an overview of recent advances in the search for colorectal cancer biomarkers through proteomics studies according to biomarker function and clinical application.

In-Depth Characterization of Mass Spectrometry-Based Proteomic Profiles Revealed Novel Signature Proteins Associated with Liver Metastatic Colorectal Cancers

Liver metastasis is the most common form of metastatic colorectal cancers during the course of the disease. The global change in protein abundance in liver metastatic colorectal cancers and its role in metastasis establishment have not been comprehensively analyzed. In the present study, fresh-frozen tissue samples including normal colon/localized/liver metastatic CRCs from each recruited patient were analyzed by quantitative proteomics using a multiplexed TMT labeling strategy. Around 5000 protein groups were quantified from all samples. The proteomic profile of localized/metastatic CRCs varied greatly from that of normal colon tissues; differential proteins were mainly from extracellular regions and participate in immune activities, which is crucial for the chronic inflammation signaling pathways in the tumor microenvironment. Further statistical analysis revealed 47 proteins exhibiting statistical significance between localized and metastatic CRCs, of which FILI1P1 and PLG were identified for the first time in proteomic data, which were highly associated with liver metastasis in CRCs.

Proteomics of epicardial adipose tissue in patients with heart failure

Epicardial adipose tissue (EAT) is a metabolically active visceral fat depot closely linked to the pathogenesis of heart failure (HF). But the molecular signatures related to the mechanism of HF have not been systematically explored. Here, we present comprehensive proteomic analysis of EAT in HF patients and non‐HF patients as controls. A total of 771 proteins were identified in liquid chromatography‐tandem mass spectrometry experiments. Amongst them, 17 increased in abundance in HF and seven decreased. They were involved in HF‐related processes including inflammation and oxidative stress response and lipid metabolism. Of these proteins, serine proteinase inhibitor A3 (Serpina3) levels in EAT were highly up‐regulated in HF, with HF/non‐HF ratio of 4.63 (P = .0047). Gene expression of Serpina3 via quantitative polymerase chain reaction was significantly increased in the HF group. ELISA analysis confirmed a significant increase in circulating plasma Serpina3 levels in the HF group (P = .004). In summary, for the first time, we describe that parts of EAT proteome may be reactive and work as modulators of HF. Our profiling provides a comprehensive basis for linking EAT with pathogenesis of HF. Understanding the role of EAT may offer new insights into the treatment of HF.

Heart Failure Stimulates Tumor Growth by Circulating Factors

BACKGROUND

Heart failure (HF) survival has improved, and nowadays, many patients with HF die of noncardiac causes, including cancer. Our aim was to investigate whether a causal relationship exists between HF and the development of cancer.

METHODS

HF was induced by inflicting large anterior myocardial infarction in APC^min mice, which are prone to developing precancerous intestinal tumors, and tumor growth was measured. In addition, to rule out hemodynamic impairment, a heterotopic heart transplantation model was used in which an infarcted or sham-operated heart was transplanted into a recipient mouse while the native heart was left in situ. After 6 weeks, tumor number, volume, and proliferation were quantified. Candidate secreted proteins were selected because they were previously associated both with (colon) tumor growth and with myocardial production in post-myocardial infarction proteomic studies. Myocardial gene expression levels of these selected candidates were analyzed, as well as their proliferative effects on HT-29 (colon cancer) cells. We validated these candidates by measuring them in plasma of healthy subjects and patients with HF. Finally, we associated the relation between cardiac specific and inflammatory biomarkers and new-onset cancer in a large, prospective general population cohort.

RESULTS

The presence of failing hearts, both native and heterotopically transplanted, resulted in significantly increased intestinal tumor load of 2.4-fold in APC^min mice (all P<0.0001). The severity of left ventricular dysfunction and fibrotic scar strongly correlated with tumor growth ( P=0.002 and P=0.016, respectively). We identified several proteins (including serpinA3 and A1, fibronectin, ceruloplasmin, and paraoxonase 1) that were elevated in human patients with chronic HF (n=101) compared with healthy subjects (n=180; P<0.001). Functionally, serpinA3 resulted in marked proliferation effects in human colon cancer (HT-29) cells, associated with Akt-S6 phosphorylation. Finally, elevated cardiac and inflammation biomarkers in apparently healthy humans (n=8319) were predictive of new-onset cancer (n=1124) independently of risk factors for cancer (age, smoking status, and body mass index).

CONCLUSIONS

We demonstrate that the presence of HF is associated with enhanced tumor growth and that this is independent of hemodynamic impairment and could be caused by cardiac excreted factors. A diagnosis of HF may therefore be considered a risk factor for incident cancer.

Evaluation of Alpha 1-Antitrypsin for the Early Diagnosis of Colorectal Cancer

Previous proteomic studies have identified alpha 1-antitrypsin (A1AT) as a potential serum biomarker for colorectal cancer (CRC). In this case-control study, we evaluated plasma A1AT concentration and activity as a biomarker for the early diagnosis of colorectal cancer in a group of 113 sporadic CRC patients. We also analyzed A1AT gene promoter methylation, and genotypes in this group of CRC patients. The plasma A1AT and CEA concentrations were measured using the nephelometric and ELISA methods, respectively. A1AT activity was determined by Trypsin Inhibitor Capacity assay. The genomic DNA from blood samples were subjected to Z and S genotype analysis using PCR-RFLP method and the gene promoter methylation in tumors and their adjacent normal tissues was determined by methylation specific-PCR assay. The plasma levels of A1AT and CEA in patients (median, 2.3 g/L and 5.96 ng/ml, respectively) were significantly higher than those in healthy controls (medians, 1.43 g/L and 2.57 ng/ml, respectively) (p = 0.0001). The plasma A1AT activity and concentrations were positively correlated with the tumor stage and well-discriminated between early and advanced stages. The A1AT activity in plasma was the most useful marker for CRC diagnosis (median 4.8 mmol/min/ml in cases vs 1.91 mmol/min/ml in controls, p = 0.0001). No deficient Z or S alleles of A1AT was observed in patients' genotype and the gene promoter tends to be more methylated in normal mucosa than in tumor tissues. We conclude that plasma A1AT activity has better sensitivity and specificity than CEA measurement for the early detection of CRC. Promoter demethylation might play a role in increasing plasma A1AT levels in CRC patients.

Urinary Cysteine-Rich Protein 61 and Trefoil Factor 3 as Diagnostic Biomarkers for Colorectal Cancer

Since a fecal occult blood test for colorectal cancer (CRC) does not offer sufficient diagnostic power for CRC, novel non-invasive biomarkers are hopeful for CRC screening. We conducted the current study to discover non-invasive urinary biomarkers for diagnosing CRC. Among urine samples from 258 patients (CRC, n = 148; healthy controls, n = 110), a cohort of 176 patients composed of 88 patients with GC and 88 healthy controls was selected after age- and sex-matching using propensity score. This cohort was then randomly divided into 2 groups: 53 pairs (106 patients) in the training cohort, and 35 pairs (70 patients) in the validation cohort. No significant differences were found for baseline characteristics between the CRC and healthy control groups in both training and validation cohorts. On multivariate analysis in the training cohort, urinary levels of cysteine-rich protein 61 (uCyr61) and trefoil factor 3 (uTFF3) were identified as independent significant diagnostic markers for CRC. Moreover, uCyr61 alone and the combination of uCyr61 and uTFF3 allowed significant differentiation between healthy controls and CRC groups in the training set (uCyr61: area under the curve (AUC) = 0.745 [95% CI, 0.653–0.838]; uCyr61 + uTFF3: AUC = 0.753 [95% CI, 0.659–0.847]). In the validation cohort, uCyr61 and uTFF3 were significantly higher in the CRC group than in the healthy control group, and they also allowed significant differentiation between healthy control and CRC groups (uCyr61: AUC = 0.696 [95% CI, 0.571–0.822]; uTFF3: AUC = 0.639 [95% CI, 0.508–0.770]; uCyr61 + uTFF3: AUC = 0.720 [95% CI, 0.599–0.841]), as in the training cohort. A panel combining uCyr61 and uTFF3 offers a promising non-invasive biomarker for diagnosing CRC.

Identifying the key genes and microRNAs in colorectal cancer liver metastasis by bioinformatics analysis and in vitro experiments

Colorectal cancer (CRC) is one of the principal causes of cancer‑associated mortality worldwide. The high incidence of liver metastasis is the leading risk factor of mortality in patients with CRC, and the mechanisms of CRC liver metastasis are poorly understood. In the present study, 7 datasets, including 3 gene expression profile datasets and 4 microRNA (miRNA) expression profile datasets were downloaded from the NCBI Gene Expression Omnibus (GEO) database to identify potential key genes and miRNAs, which may be candidate biomarkers for CRC liver metastasis. Differentially expressed (DE) genes (DEGs) and DE miRNAs of primary CRC tumor tissues and liver metastatic CRC tumor tissues were selected using the GEO2R tool. Gene Ontology and Kyoto Encyclopedia of Gene and Genome pathway enrichment analyses were conducted using the Database for Annotation, Visualization and Integrated Discovery online database. Furthermore, Cytoscape with cytoHubba and the Molecular Complex Detection (MCODE) plug‑in were used to visualize a protein‑protein interaction (PPI) network for these DEGs, and to screen hub genes and gene modules in the PPI network. In addition, the online databases, TargetScan, miRanda, PITA, miRWalk and miRDB, were used to identify the target genes of the DE miRNAs. In the present study, 141 DEGs (97 upregulated and 44 downregulated) and 3 DE miRNAs (2 upregulated and 1 downregulated) were screened from the 3 gene expression microarray datasets and 4 miRNA expression microarray datasets, respectively. In total, 10 hub genes with a high degree of connectivity were selected from the PPI network, including albumin (ALB), coagulation factor II (F2), thrombin, apolipoprotein H (APOH), serpin family C member 1 (SERPINC1), apolipoprotein A1 (APOA1), α‑1‑microglobulin/bikunin precursor (AMBP), apolipoprotein C3 (APOC3), plasminogen (PLG), α‑2 HS glycoprotein (AHSG) and apolipoprotein B (APOB). The most important module was detected in the PPI network using the MCODE plug‑in. A total of 20 DEGs were identified to be potential target genes of these DE miRNAs, and novel miRNA‑DEGs regulatory axes were constructed. In vitro experiments were performed to demonstrate that miR‑885 promoted CRC cell migration by, at least partially, decreasing the expression of von Willebrand factor (vWF) and insulin‑like growth factor binding protein 5 (IGFBP5). In conclusion, by using integrated bioinformatics analysis and in vitro experiments, key candidate genes were identified and novel miRNA‑mRNA regulatory axes in CRC liver metastasis were constructed, which may improve understanding of the molecular mechanisms underlying CRC liver metastasis.

SERPINA3 Silencing Inhibits the Migration, Invasion, and Liver Metastasis of Colon Cancer Cells

OBJECTIVE

To investigate the impact of SERPINA3 on the migration, invasion, and liver metastasis of colon cancer cells.

METHODS

Immunohistochemical staining was conducted to determine SERPINA3 expression in the cancer and adjacent normal tissues of 131 patients suffering from colon cancer. In vitro experiment, colon cancer cells with low (HT-29P), intermediate (KM-12C), and high (HT-29LMM, KM-12L4) metastatic potential were obtained to examine SERPINA3 expression levels. Besides, quantitative real-time PCR (qRT-PCR) and Western Blot were performed to detect SERPINA3 expression in HT-29LMM and KM-12L4 cells transfected with SERPINA3 siRNA; Wound-healing and Transwell assays to measure cell migration and invasion, respectively; and ELISA to detect MMP-2 and MMP-9 levels. In vivo experiment, mice with liver metastasis of colon cancer were established to observe the effect of SERPINA3 silencing on liver metastasis. Immunohistochemical assay was applied to evaluate the expressions of Serpina3, Mmp-2, Mmp-9, and proliferating cell nuclear antigen (Pcna) in liver metastasis tissues.

RESULTS

SERPINA3 in colon cancer tissues was higher than in adjacent normal tissues, which was associated with patients' clinicopathological features. Besides, SERPINA3 expression showed a rising trend in low, intermediate, and high metastatic potential colon cancer cells. After KM-12L4 and HT-29LMM cells transfected with SERPINA3 siRNA, the migration and invasive ability of cells, as well as the expression levels of MMP-2 and MMP-9 were all decreased. Moreover, SERPINA3 siRNA could not only reduce live metastasis of mice, but also down-regulate the expression of Mmp-2 and Mmp-9 in liver metastasis tissues.

CONCLUSION

SERPINA3 silencing could inhibit the migration, invasion, and liver metastasis of colon cancer cells.

Probing the colorectal cancer proteome for biomarkers: Current status and perspectives

Colorectal cancer (CRC) is one of the most prevalent malignancies worldwide. Biomarkers that can facilitate better clinical management of CRC are in high demand to improve patient outcome and to reduce mortality. In this regard, proteomic analysis holds a promising prospect in the hunt of novel biomarkers for CRC and in understanding the mechanisms underlying tumorigenesis. This review aims to provide an overview of the current progress of proteomic research, focusing on discovery and validation of diagnostic biomarkers for CRC. We will summarize the contributions of proteomic strategies to recent discoveries of protein biomarkers for CRC and also briefly discuss the potential and challenges of different proteomic approaches in biomarker discovery and translational applications.

Activation peptide of the coagulation factor XIII (AP-F13A1) as a new biomarker for the screening of colorectal cancer

Background

Colorectal cancer (CRC) remains a major cause of cancer fatalities in developed countries. The risk of death is correlated to the stage of CRC during the primary diagnosis. Early diagnosis is closely associated with enhanced survival rate. We therefore investigated the AP-F13A1 as a potential protein marker of CRC.

Methods

The protein expression of FXIII in 40 serum samples was evaluated by enzyme-linked immunosorbent assays. Additionally, targeted proteomic assays (LC-PRM) were used to evaluate the expression of the activation peptide of F13A1 (AP-F13A1) in a further 113 serum samples. Results were analyzed by the Wilcoxon test and receiver operating characteristic curves generated to assess statistical differences and diagnostic factors between CRC patients and controls.

Results

AP-F13A1 was quantified in human serum samples using calibration curves with excellent linearity. AP-F13A1 was reduced in CRC patients using PRM assays from two distinct biobanks. The AUC for AP-F13A1 were 0.95 and 0.93. Sensitivity/specificity values for the two sets of patients were 75%/95% and 71%/95% respectively.

Conclusion

We have presented the proof of principle that in vivo release of AP-F13A1 can be measured by PRM-based strategies in CRC serum samples. AP-F13A1 may be an effective serological biomarker as part of a screening program of CRC detection.

Electronic supplementary material

The online version of this article (10.1186/s12014-018-9191-3) contains supplementary material, which is available to authorized users.

Proteomics for early detection of colorectal cancer: recent updates

INTRODUCTION

Colorectal cancer (CRC) is a common type of cancer with a relatively poor survival rate. The survival rate of patients could be improved if CRC is detected early. Biomarkers associated with early stages of tumor development might provide useful tools for the early diagnosis of colorectal cancer. Areas covered: Online searches using PubMed and Google Scholar were performed using keywords and with a focus on recent proteomic studies. The aim of this review is to highlight the need for biomarkers to improve the detection rate of early CRC and provide an overview of proteomic technologies used for biomarker discovery and validation. This review will also discuss recent proteomic studies which focus on identifying biomarkers associated with the early stages of CRC development. Expert commentary: A large number of CRC biomarkers are increasingly being identified by proteomics using diverse approaches. However, the clinical relevance and introduction of these markers into clinical practice cannot be determined without a robust validation process. The size of validation cohorts remains a major limitation in many biomarker studies.

Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed.

Decreased serum apolipoprotein A1 levels are associated with poor survival and systemic inflammatory response in colorectal cancer

Recent studies have reported of an association between high serum apolipoprotein A1 (APOA1) levels and favorable prognosis in several malignancies, while the significance of apolipoprotein B (APOB) in cancer is less well-known. In this study, we analyzed the correlation between serum APOA1 and APOB levels, and APOB/APOA1 ratio, and their associations with clinicopathologic parameters, the levels of twenty systemic inflammatory markers, and survival in 144 colorectal cancer (CRC) patients. We demonstrated that low serum APOA1 levels associated with advanced T-class and TNM-stage but low serum APOB levels did not significantly correlate with tumor characteristics. Serum APOA1 levels showed strong negative correlation with the markers of systemic inflammation including serum CRP and interleukin (IL)-8 levels and blood neutrophil count, whereas high serum APOB levels associated with high serum CCL2 levels. High APOA1 and APOB levels and low APOB/APOA1 ratio associated with improved cancer specific and overall survival. APOA1 had independent prognostic value in Cox regression analysis. In conclusion, low serum APOA1 levels are associated with advanced stage and systemic inflammation, while serum APOB does not significantly correlate with tumor stage. Serum APOA1 represents a promising additional prognostic parameter in CRC.