LGALS4, CEACAM6, TSPAN8, and COL1A2: Blood Markers for Colorectal Cancer-Validation in a Cohort of Subjects With Positive Fecal Immunochemical Test Result. Clin Colorectal Cancer. 2018;17:e217-e228. [PMID: 29352642 DOI: 10.1016/j.clcc.2017.12.002]

Tspan protein family: focusing on the occurrence, progression, and treatment of cancer

The Tetraspanins (Tspan) protein family, also known as the tetraspanin family, contains 33 family members that interact with other protein molecules such as integrins, adhesion molecules, and T cell receptors by forming dimers or heterodimers. The Tspan protein family regulates cell proliferation, cell cycle, invasion, migration, apoptosis, autophagy, tissue differentiation, and immune response. More and more studies have shown that Tspan proteins are involved in tumorigenesis, epithelial-mesenchymal transition, thrombosis, tumor stem cell, and exosome signaling. Some drugs and microRNAs can inhibit Tspan proteins, thus providing new strategies for tumor therapy. An in-depth understanding of the functions and regulatory mechanisms of the Tspan protein family, which can promote or inhibit tumor development, will provide new strategies for targeted interventions in the future.

An integrated framework for prognosis prediction and drug response modeling in colorectal liver metastasis drug discovery

BACKGROUND

Colorectal cancer (CRC) is the third most prevalent cancer globally, and liver metastasis (CRLM) is the primary cause of death. Hence, it is essential to discover novel prognostic biomarkers and therapeutic drugs for CRLM.

METHODS

This study developed two liver metastasis-associated prognostic signatures based on differentially expressed genes (DEGs) in CRLM. Additionally, we employed an interpretable deep learning model utilizing drug sensitivity databases to identify potential therapeutic drugs for high-risk CRLM patients. Subsequently, in vitro and in vivo experiments were performed to verify the efficacy of these compounds.

RESULTS

These two prognostic models exhibited superior performance compared to previously reported ones. Obatoclax, a BCL-2 inhibitor, showed significant differential responses between high and low risk groups classified by prognostic models, and demonstrated remarkable effectiveness in both Transwell assay and CT26 colorectal liver metastasis mouse model.

CONCLUSIONS

This study highlights the significance of developing specialized prognostication approaches and investigating effective therapeutic drugs for patients with CRLM. The application of a deep learning drug response model provides a new drug discovery strategy for translational medicine in precision oncology.

Molecular Regulation and Oncogenic Functions of TSPAN8

Tetraspanins, a superfamily of small integral membrane proteins, are characterized by four transmembrane domains and conserved protein motifs that are configured into a unique molecular topology and structure in the plasma membrane. They act as key organizers of the plasma membrane, orchestrating the formation of specialized microdomains called "tetraspanin-enriched microdomains (TEMs)" or "tetraspanin nanodomains" that are essential for mediating diverse biological processes. TSPAN8 is one of the earliest identified tetraspanin members. It is known to interact with a wide range of molecular partners in different cellular contexts and regulate diverse molecular and cellular events at the plasma membrane, including cell adhesion, migration, invasion, signal transduction, and exosome biogenesis. The functions of cell-surface TSPAN8 are governed by ER targeting, modifications at the Golgi apparatus and dynamic trafficking. Intriguingly, limited evidence shows that TSPAN8 can translocate to the nucleus to act as a transcriptional regulator. The transcription of TSPAN8 is tightly regulated and restricted to defined cell lineages, where it can serve as a molecular marker of stem/progenitor cells in certain normal tissues as well as tumors. Importantly, the oncogenic roles of TSPAN8 in tumor development and cancer metastasis have gained prominence in recent decades. Here, we comprehensively review the current knowledge on the molecular characteristics and regulatory mechanisms defining TSPAN8 functions, and discuss the potential and significance of TSPAN8 as a biomarker and therapeutic target across various epithelial cancers.

Tumor circulating biomarkers in colorectal cancer

CRC is a major global health concern and is responsible for a significant number of cancer-related deaths each year. The successful treatment of CRC becomes more difficult when it goes undetected until it has advanced to a later stage. Diagnostic biomarkers can play a critical role in the early detection of CRC, which leads to improved patient outcomes and increased survival rates. It is important to develop reliable biomarkers for the early detection of CRC to enable timely diagnosis and treatment. To date, CRC detection methods such as endoscopy, blood, and stool tests are imperfect and often only identify cases in the later stages of the disease. To overcome these limitations, researchers are turning to molecular biomarkers as a promising avenue for improving CRC detection. Diagnostic information can be provided more reliably through a noninvasive approach using biomarkers such as mRNA, circulating cell-free DNA, micro-RNA, long non-coding RNA, and proteins. These biomarkers can be found in blood, tissue, feces, and volatile organic compounds. The identification of molecular biomarkers with high sensitivity and specificity for early detection of CRC that are safe, cost-effective, and easily measurable remains a significant challenge for researchers. In this article, we will explore the latest advancements in blood-based diagnostic biomarkers for CRC and their potential impact on improving patient survival rates.

DPHL v.2: An updated and comprehensive DIA pan-human assay library for quantifying more than 14,000 proteins

A comprehensive pan-human spectral library is critical for biomarker discovery using mass spectrometry (MS)-based proteomics. DPHL v.1, a previous pan-human library built from 1,096 data-dependent acquisition (DDA) MS data of 16 human tissue types, allows quantifying of 10,943 proteins. Here, we generated DPHL v.2 from 1,608 DDA-MS data. The data included 586 DDA-MS data acquired from 18 tissue types, while 1,022 files were derived from DPHL v.1. DPHL v.2 thus comprises data from 24 sample types, including several cancer types (lung, breast, kidney, and prostate cancer, among others). We generated four variants of DPHL v.2 to include semi-tryptic peptides and protein isoforms. DPHL v.2 was then applied to two colorectal cancer cohorts. The numbers of identified and significantly dysregulated proteins increased by at least 21.7% and 14.2%, respectively, compared with DPHL v.1. Our findings show that the increased human proteome coverage of DPHL v.2 provides larger pools of potential protein biomarkers.

Application and development of noninvasive biomarkers for colorectal cancer screening: a systematic review

BACKGROUND

Colorectal cancer (CRC) is the second most common cause of cancer-related death (9.4% of the 9.9 million cancer deaths). However, CRC develops slowly, and early detection and intervention can effectively improve the survival rate and quality of life. Although colonoscopy can detect and diagnose CRC, it is unsuitable for CRC screening in average-risk populations. Some commercial kits based on DNA mutation or methylation are approved for screening, but the low sensitivity for advanced adenoma or early-stage CRC would limit the applications.

MAIN RESULTS

Recently, researchers have focused on developing noninvasive or minimally invasive, easily accessible biomarkers with higher sensitivity and accuracy for CRC screening. Numerous reports describe advances in biomarkers, including DNA mutations and methylation, mRNA and miRNA, gut microbes, and metabolites, as well as low-throughput multiomics panels. In small cohorts, the specificity and sensitivity improved when fecal immunochemical testing combined with other biomarkers; further verification in large cohorts is expected. In addition, the continuous improvement of laboratory technology has also improved the sensitivity of detection technology, such as PCR, and the application of CRISPR/Cas technology. Besides, artificial intelligence has extensively promoted the mining of biomarkers. Machine learning was performed to construct a diagnosis model for CRC screening based on the cfDNA fragment features from whole-genome sequencing data. In another study, multiomics markers, including cfDNA, epigenetic, and protein signals, were also discovered by machine learning. Finally, advancements in sensor technology promote the applicability of volatile organic compounds in CRC early detection.

CONCLUSION

Here, the authors review advances in early detection and screening of CRC based on different biomarker types. Most studies reported optimistic findings based on preliminary research, and prospective clinical studies are ongoing. These promising biomarkers are expected to more accurately identify early-stage patients with CRC and be applied in the future.

Galectin Family Members: Emerging Novel Targets for Lymphoma Therapy?

The galectin family of proteins has high affinity with β-galactoside-containing glycans. These proteins participate in cell growth and differentiation, cell adhesion, cell signal transduction, cell apoptosis, and other cellular activities. In recent years, a large number of studies have described the expression and correlation of galectins in different tumors. Each member of the family plays a vital role in tumor growth, progression, angiogenesis, adhesion, and tumor immune escape. Studies on the roles of galectins in lymphoma have mainly involved galectin-1, -3, -7, and -9. The results suggest that galectins may become novel targets for precise tumor treatment. This article reviews current research progress regarding galectins in lymphoma and provides new ideas for exploring them as novel targets for treating lymphoma and other important medical issues.

Advances in Early Detection of Colorectal Cancer: A Focus on Non-invasive Biomarkers

BACKGROUND

Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide. Currently, colonoscopy remains the gold standard diagnostic test for CRC detection. Nonetheless, this technique is invasive and expensive. Remarkable ongoing strategies are focusing on the development of affordable methods to diagnose CRC at earlier stages. The introduction of suitable noninvasive, sensitive and specified diagnostic tests for early CRC detection by employing biomarker analysis seems to be a fundamental need to reduce the numbers of unnecessary colonoscopies. In this review, we provide an overview of single- and multi-panel biomarkers (Genomic markers, transcriptome markers, proteomic markers, inflammatory markers, and microbiome markers) encompassing noninvasive tests in blood and stool for early CRC detection.

METHODS

A bibliographic search using PubMed/Medline, Web of Science, and EBSCOhost databases was performed to find relevant published studies over the last 6 years. Forty-three pertinent studies were included in this review.

RESULTS

The primary outcome highlights the sensitivity and specificity of single diagnostic biomarkers studied in blood or stool. The secondary outcome reveals the sensitivity and specificity of the biomarkers panel (combinations) in blood or stool. While some markers show better performance, others are not suitable for screening purposes.

CONCLUSION

There is a need to adjust experimental and analytical tests that can interfere with a robust result to replace or supplement those markers that are currently in use. Nevertheless, robust verification and validation with large clinical cohorts are needed for successful noninvasive tests that can fulfill the role of colonoscopy.

Integration of the Microbiome, Metabolome and Transcriptomics Data Identified Novel Metabolic Pathway Regulation in Colorectal Cancer

Integrative multiomics data analysis provides a unique opportunity for the mechanistic understanding of colorectal cancer (CRC) in addition to the identification of potential novel therapeutic targets. In this study, we used public omics data sets to investigate potential associations between microbiome, metabolome, bulk transcriptomics and single cell RNA sequencing datasets. We identified multiple potential interactions, for example 5-aminovalerate interacting with Adlercreutzia; cholesteryl ester interacting with bacterial genera Staphylococcus, Blautia and Roseburia. Using public single cell and bulk RNA sequencing, we identified 17 overlapping genes involved in epithelial cell pathways, with particular significance of the oxidative phosphorylation pathway and the ACAT1 gene that indirectly regulates the esterification of cholesterol. These findings demonstrate that the integration of multiomics data sets from diverse populations can help us in untangling the colorectal cancer pathogenesis as well as postulate the disease pathology mechanisms and therapeutic targets.

Circulating PTGS2, JAG1, GUCY2C and PGF mRNA in Peripheral Blood and Serum as Potential Biomarkers for Patients with Metastatic Colon Cancer

Genes involved in the angiogenic process have been proposed for the diagnosis and therapeutic response of metastatic colorectal cancer (CRC). This study aimed to investigate the value of PTGS2, JAG1, GUCY2C and PGF-circulating RNA as biomarkers in metastatic CRC. Blood cells and serum mRNA from 59 patients with metastatic CRC and 47 healthy controls were analyzed by digital PCR. The area under the receiver operating characteristic curve (AUC) was used to estimate the diagnostic value of each mRNA alone or mRNA combinations. A significant upregulation of the JAG1, PTGS2 and GUCY2C genes in blood cells and serum samples from metastatic CRC patients was detected. Circulating mRNA levels in the serum of all genes were significantly more abundant than in blood. The highest discrimination ability between metastatic CRC patients and healthy donors was obtained with PTGS2 (AUC of 0.984) and GUCY2C (AUC of 0.896) in serum samples. Biomarker combinations did not improve the discriminatory capacity of biomarkers separately. Analyzed biomarkers showed no correlation with overall survival or progression-free survival, but GUCY2C and GUCY2C/PTGS2 expression in serum correlated significantly with the response to antiangiogenic agents. These findings demonstrate that assessment of genes involved in the angiogenic process may be a potential non-invasive diagnostic tool for metastatic CRC and its response to antiangiogenic therapy.

The Roadmap of Colorectal Cancer Screening

Colorectal cancer (CRC) is the third most common form of cancer in terms of incidence and the second in terms of mortality worldwide. CRC develops over several years, thus highlighting the importance of early diagnosis. National screening programs based on fecal occult blood tests and subsequent colonoscopy have reduced the incidence and mortality, however improvements are needed since the participation rate remains low and the tests present a high number of false positive results. This review provides an overview of the CRC screening globally and the state of the art in approaches aimed at improving accuracy and participation in CRC screening, also considering the need for gender and age differentiation. New fecal tests and biomarkers such as DNA methylation, mutation or integrity, proteins and microRNAs are explored, including recent investigations into fecal microbiota. Liquid biopsy approaches, involving novel biomarkers and panels, such as circulating mRNA, micro- and long-non-coding RNA, DNA, proteins and extracellular vesicles are discussed. The approaches reported are based on quantitative PCR methods that could be easily applied to routine screening, or arrays and sequencing assays that should be better exploited to describe and identify candidate biomarkers in blood samples.

Comparison of Proteomic Technologies for Blood-Based Detection of Colorectal Cancer

Blood-based protein biomarkers are increasingly being explored as supplementary or efficient alternatives for population-based screening of colorectal cancer (CRC). The objective of the current study was to compare the diagnostic potential of proteins measured with different proteomic technologies. The concentrations of protein biomarkers were measured using proximity extension assays (PEAs), liquid chromatography/multiple reaction monitoring-mass spectrometry (LC/MRM-MS) and quantibody microarrays (QMAs) in plasma samples of 56 CRC patients and 99 participants free of neoplasms. In another approach, proteins were measured in serum samples of 30 CRC cases and 30 participants free of neoplasm using immunome full-length functional protein arrays (IpAs). From all the measurements, 9, 6, 35 and 14 protein biomarkers overlapped for comparative evaluation of (a) PEA and LC/MRM-MS, (b) PEA and QMA, (c) PEA and IpA, and (d) LC/MRM-MS and IpA measurements, respectively. Correlation analysis was performed, along with calculation of the area under the curve (AUC) for assessing the diagnostic potential of each biomarker. DeLong's test was performed to assess the differences in AUC. Evaluation of the nine biomarkers measured with PEA and LC/MRM-MS displayed correlation coefficients >+0.6, similar AUCs and DeLong's p-values indicating no differences in AUCs for biomarkers like insulin-like growth factor binding protein 2 (IGFBP2), matrix metalloproteinase 9 (MMP9) and serum paraoxonase lactonase 3 (PON3). Comparing six proteins measured with PEA and QMA showed good correlation and similar diagnostic performance for only one protein, growth differentiation factor 15 (GDF15). The comparison of 35 proteins measured with IpA and PEA and 14 proteins analyzed with IpA and LC/MRM-MS revealed poor concordance and comparatively better AUCs when measured with PEA and LC/MRM-MS. The comparison of different proteomic technologies suggests the superior performance of novel technologies like PEA and LC/MRM-MS over the assessed array-based technologies in blood-protein-based early detection of CRC.

Identification of candidate biomarkers and therapeutic drugs of colorectal cancer by integrated bioinformatics analysis

Most colorectal cancer (CRC) patients are diagnosed with advanced stages and low prognosis. We aimed to identify potential diagnostic and prognostic biomarkers, as well as active small molecules of CRC. Microarray data (GSE9348, GSE35279, and GSE106582) were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified by the GEO2R platform. Common DEGs were selected for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Cytoscape software was used to construct protein-protein interaction networks and identify hub genes. Hub genes were evaluated by Kaplan-Meier survival analysis in the GEPIA database and validated in two independent microarray data (GSE74602 and GSE83889). Common DEGs were used to select active small molecules by the connectivity map database. A total of 166 DEGs were identified as common DEGs. GO analysis demonstrated that common DEGs were significantly enriched in the apoptotic process, cell proliferation, and cell adhesion. KEGG analysis indicated that the most enriched pathways were the PI3K-Akt signaling pathway and extracellular matrix-receptor interaction. COL1A2, THBS2, TIMP1, and CXCL8 significantly upregulated in colorectal tumor. High expressions of COL1A2, THBS2, and TIMP1 were associated with poor survival, while high expressions of CXCL8 were associated with better survival. We selected 11 small molecules for CRC therapy. In conclusion, we found key dysregulated genes associated with CRC and potential small molecules to reverse them. COL1A2, THBS2, TIMP1, and CXCL8 may act as diagnostic and prognostic biomarkers of CRC.

Colorectal cancer screening: Assessment of CEACAM6, LGALS4, TSPAN8 and COL1A2 as blood markers in faecal immunochemical test negative subjects

Prevention is essential to reduce Colorectal Cancer (CRC) mortality. We previously reported a panel of four genes: CEACAM6, LGALS4, TSPAN8, COL1A2 (CELTiC) able to discriminate patients with CRC. Here, we assessed the CELTiC panel by quantitative polymerase chain reaction, in the blood of 174 healthy subjects, who resulted negative to the faecal immunochemical test (FITN). Using non-parametric statistic and multinomial logistic models, the FITN were compared to previously analysed subjects: 36 false positive FIT (NFIT), who were negative at colonoscopy, 36 patients with low risk lesions (LR) and 92 patients with high risk lesions or CRC (HR/CRC). FITN showed a significantly lower expression of the four genes when compared to HR/CRC. Moreover, FITN showed a significantly lower expression of TSPAN8 and COL1A2 compared to NFIT and LR patients.

The multinomial logistic model confirmed that TSPAN8 alone specifically discriminated FITN from NFIT, LR and HR/CRC, while LGALS4 was able to differentiate FITN from false positive FIT. Finally, ROC curves analysis of the comparisons between FITN and HR/CRC, LR or NFIT reported AUC greater than 0.87, with a sensitivity and specificity of 83% and 76%, respectively. The CELTiC panel was confirmed a useful tool to identify CRC patients and to discriminate false FIT positive subjects.

Biomarkers for detecting colorectal cancer non-invasively: DNA, RNA or proteins?

Colorectal cancer (CRC) is a global problem affecting millions of people worldwide. This disease is unique because of its slow progress that makes it preventable and often curable. CRC symptoms usually emerge only at advanced stages of the disease, consequently its early detection can be achieved only through active population screening, which markedly reduces mortality due to this cancer. CRC screening tests that employ non-invasively detectable biomarkers are currently being actively developed and, in most cases, samples of either stool or blood are used. However, alternative biological substances that can be collected non-invasively (colorectal mucus, urine, saliva, exhaled air) have now emerged as new sources of diagnostic biomarkers. The main categories of currently explored CRC biomarkers are: (1) Proteins (comprising widely used haemoglobin); (2) DNA (including mutations and methylation markers); (3) RNA (in particular microRNAs); (4) Low molecular weight metabolites (comprising volatile organic compounds) detectable by metabolomic techniques; and (5) Shifts in gut microbiome composition. Numerous tests for early CRC detection employing such non-invasive biomarkers have been proposed and clinically studied. While some of these studies generated promising early results, very few of the proposed tests have been transformed into clinically validated diagnostic/screening techniques. Such DNA-based tests as Food and Drug Administration-approved multitarget stool test (marketed as Cologuard®) or blood test for methylated septin 9 (marketed as Epi proColon® 2.0 CE) show good diagnostic performance but remain too expensive and technically complex to become effective CRC screening tools. It can be concluded that, despite its deficiencies, the protein (haemoglobin) detection-based faecal immunochemical test (FIT) today presents the most cost-effective option for non-invasive CRC screening. The combination of non-invasive FIT and confirmatory invasive colonoscopy is the current strategy of choice for CRC screening. However, continuing intense research in the area promises the emergence of new superior non-invasive CRC screening tests that will allow the development of improved disease prevention strategies.

Multiplex quantitation of 270 plasma protein markers to identify a signature for early detection of colorectal cancer

Blood-based protein biomarker signatures might be an alternative or supplement to existing methods for early detection of colorectal cancer (CRC) for population-based screening. The objective of this study was to derive a protein biomarker signature for early detection of CRC and its precursor advanced adenoma (AA). In a two-stage design, 270 protein markers were measured by liquid chromatography/multiple reaction monitoring/mass spectrometry in plasma samples of discovery and validation sets. In the discovery set consisting of 100 newly diagnosed CRC cases and 100 age- and sex-matched controls free of neoplasm at screening colonoscopy, the algorithms predicting the presence of early- or late-stage CRC were derived by Lasso regression and .632 + bootstrap. The prediction algorithms were then externally validated in an independent validation set consisting of participants of screening colonoscopy including 56 participants with CRC, 99 with AA and 99 controls without any colorectal neoplasms. Three different signatures for all-, early- and late-stage CRC consisting of five-, three- and eight-protein markers were obtained in the discovery set with areas under the curves (AUCs) after .632 + bootstrap adjustment of 0.85, 0.83 and 0.96, respectively. External validation in the representative screening population yielded AUCs of 0.79 (95% CI, 0.70-0.86), 0.79 (95% CI, 0.66-0.89) and 0.80 (95% CI, 0.70-0.89) for all-, early- and late-stage CRCs, respectively. The three-marker early-stage algorithm yielded an AUC of 0.65 (95% CI, 0.56-0.73) for detection of AA in the validation set. Although not yet competitive with available stool-based tests for CRC early detection, the identified proteins may contribute to the development of powerful blood-based tests for early detection of CRC and its precursors AAs.

A Positive Tetraspanin 8 (TSPAN8)/β-Catenin Regulatory Loop Enhances the Stemness of Colorectal Cancer Cells

BACKGROUND The expression of TSPAN8 (tetraspanin 8) is upregulated in colorectal cancer; however, its roles in colorectal cancer progression are never been revealed. This work aimed to investigate TSPAN8 effects and the molecular basis in regulating colorectal cancer stemness. MATERIAL AND METHODS Real-time quantitative polymerase chain reaction and western blot analysis were used to detect the expression of TSPAN8 expression in clinical samples and the expression of stemness genes in colorectal cancer cells. Sphere forming analysis was performed to detect TSPAN8 effects on sphere forming ability of colorectal cancer cells. Co-IP and ChIP analysis were performed to confirm the molecular basis contributing to TSPAN8-mediated effects on colorectal cancer stemness. RESULTS TSPAN8 expression is increased in colorectal cancer tissues. Knockdown of TSPAN8 reduced the expression of stemness genes and sphere forming capacity in colorectal cancer cells. Mechanistically, TSPAN8 directly interacted ß-catenin and enhanced its protein expression, which is necessary for TSPAN8-mediated effects on colorectal cancer stemness. Conversely, ß-catenin directly bound to TSPAN8 promoter and enhanced TSPAN8 transcription. CONCLUSIONS TSPAN8 promotes colorectal cancer stemness through a positive TSPAN8/ß-catenin regulatory loop.

Identification of hub genes and construction of transcriptional regulatory network for the progression of colon adenocarcinoma hub genes and TF regulatory network of colon adenocarcinoma

The aim of this study was to identify key genes related to the progression of colon adenocarcinoma (COAD), and to investigate the regulatory network of hub genes and transcription factors (TFs). Dataset GSE20916 including 44 normal colon, 55 adenoma, and 36 adenocarcinoma tissue samples was used to construct co‐expression networks via weighted gene co‐expression network. Gene Ontology annotation and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis for the objective module were performed using the online Database for Annotation, Visualization and Integrated Discovery. Hub genes were identified by taking the intersection of differentially expressed genes between dataset GSE20916 and GSE39582 and validated using The Cancer Genome Atlas (TCGA) database. The correlations between microRNA (miRNA) and hub genes were analyzed using the online website StarBase. Cytoscape was used to establish a regulatory network of TF‐miRNA‐target gene. We found that the orange module was a key module related to the tumor progression in COAD. In datasets GSE20916 and GSE39582, a total of eight genes (BGN, SULF1, COL1A1, FAP, THBS2, CTHRC1, COL5A2, and COL1A2) were selected, which were closely related with patients’ survivals in TCGA database and dataset GSE20916. COAD patients with higher expressions of each hub gene had a worse prognosis than those with lower expressions. A regulatory network of TF‐miRNA‐target gene with 144 TFs, 26 miRNAs, and 7 hub genes was established, including model KLF11‐miR149‐BGN, TCEAL6‐miR29B2‐COL1A1, and TCEAL6‐miR29B2‐COL1A2. In conclusion, during the progression of COAD, eight core genes (BGN, SULF1, COL1A1, FAP, THBS2, CTHRC1, COL5A2, and COL1A2) play vital roles. Regulatory networks of TF‐miRNA‐target gene can help to understand the disease progression and optimize treatment strategy.

Evaluation and Validation of Plasma Proteins Using Two Different Protein Detection Methods for Early Detection of Colorectal Cancer

Objective: Plasma protein biomarkers could be an efficient alternative for population-based screening for early detection of colorectal cancer (CRC). The objective of this study was to evaluate and validate plasma proteins individually and as a signature for early detection of CRC. Methods: In a three-stage design, proteins were measured firstly by liquid chromatography/multiple reaction monitoring-mass spectrometry (LC/MRM-MS) and later by proximity extension assay (PEA) in a discovery set consisting of 96 newly diagnosed CRC cases and 94 controls free of neoplasms at screening colonoscopy. Two algorithms (one for each measurement method) were derived by Lasso regression and .632+ bootstrap based on 11 proteins that were included in both the LC/MRM-MS and PEA measurements. Additionally, another algorithm was constructed from the same eleven biomarkers plus amphireglin, the most promising protein marker in the PEA measurements that had not been available from the LC/MRM-MS measurements. Lastly the three prediction signatures were validated with PEA in independent samples of participants of screening colonoscopy (CRC (n = 56), advanced adenoma (n = 101), and participants free of neoplasm (n = 102)). Results: The same four proteins were included in all three prediction signatures; mannan binding lectin serine protease 1, osteopontin, serum paraoxonase lactonase 3 and transferrin receptor protein 1, and the third prediction signature additionally included amphiregulin. In the independent validation set from a true screening setting, the five-marker blood-based signature including AREG presented areas under the curves of 0.82 (95% CI, 0.74–0.89), 0.86 (95% CI, 0.77–0.92) and 0.76 (95% CI, 0.64–0.86) for all, early and late stages CRC, respectively. Conclusion: Two different measurement methods consistently identified four protein markers and an algorithm additionally including amphiregulin, a marker measured by PEA only, showed promising performance for detecting early stage CRC in an independent validation in a true screening setting. These proteins may be potential candidates for blood-based tests for early detection of CRC.

Circulating cell-free nucleic acids as biomarkers in colorectal cancer screening and diagnosis - an update

Introduction: Screening methods for one of the most frequently diagnosed malignancy, colorectal cancer (CRC), have limitations. Circulating cell-free nucleic acids (cfNA) hold clinical relevance as screening, prognostic and therapy monitoring markers. Area covered: In this review, we summarize potential CRC-specific cfNA biomarkers, the recently developed sample preparation techniques, their applications, and pitfalls. Expert opinion: Automated extraction of cfDNA is highly reproducible, however, cfDNA yield is less compared to manual isolation. Quantitative and highly sensitive detection techniques (e.g. digital PCR, NGS) can be applied to analyze genetic and epigenetic changes. Detection of DNA mutations or methylation in cfDNA and related altered levels of mRNA, miRNA, and lncRNA may improve early cancer recognition, based on specific, CRC-related patterns. Detection of cfDNA mutations (e.g. TP53, KRAS, APC) has limited diagnostic sensitivity (40-60%), however, methylated DNA including SEPT9, SFRP1, SDC2 can be applied with higher sensitivity (up to 90%) for CRC. Circulating miRNAs (e.g. miR-21, miR-92, miR-141) provide comparably high sensitivity for CRC as the circulating tumor cell mRNA markers (e.g. EGFR, CK19, CK20, CEA). Automation of cfNA isolation coupled with quantitative analysis of CRC-related, highly sensitive biomarkers may enhance CRC screening and early detection in the future.

Prognostic and Clinicopathological Significance of SATB1 in Colorectal Cancer: A Meta-Analysis

Background: A large number of studies have reported the aberrant expression of special AT-rich sequence binding protein 1 (SATB1) in colorectal cancer (CRC). However, the role of SATB1 in CRC is still controversial. Therefore, we performed this meta-analysis to elucidate the prognostic and clinical value of SATB1 in CRC patients.

Methods: We searched Web of Science, EMBASE and PubMed entirely in January 2018 to identify related articles. Pooled Hazard ratio (HR) was adopted to evaluate the prognostic value of SATB1 in CRC and odd ratio (OR) was used to assess the clinicopathological significance of SATB1 in CRC.

Results: Ten eligible studies containing 7 on prognosis and 9 on clinicopathological characteristics were finally included in the present meta-analysis. Results revealed that patients with high expression of SATB1 tended to have shorter overall survival (OS) (pooled HR: 1.64, 95% CI: 1.04–2.57). Besides, we also discovered that the expression of SATB1 was associated with histologic grade (OR = 1.88, 95% CI: 1.06–3.34), distant metastasis (OR = 1.43, 95% CI: 1.11–1.85) and lymph node metastasis (OR = 1.50, 95% CI: 1.03–2.19).

Conclusion: Broadly speaking, our meta-analysis demonstrated that high expression level of SATB1 was related to poor prognosis in CRC patients.