Characterization of the prognostic values of the NDRG family in gastric cancer

NDRG1 acts as an oncogene in triple-negative breast cancer and its loss sensitizes cells to mitochondrial iron chelation

Multiple studies indicate that iron chelators enhance their anti-cancer properties by inducing NDRG1, a known tumor and metastasis suppressor. However, the exact role of NDRG1 remains controversial, as newer studies have shown that NDRG1 can also act as an oncogene. Our group recently introduced mitochondrially targeted iron chelators deferoxamine (mitoDFO) and deferasirox (mitoDFX) as effective anti-cancer agents. In this study, we evaluated the ability of these modified chelators to induce NDRG1 and the role of NDRG1 in breast cancer. We demonstrated that both compounds specifically increase NDRG1 without inducing other NDRG family members. We have documented that the effect of mitochondrially targeted chelators is at least partially mediated by GSK3α/β, leading to phosphorylation of NDRG1 at Thr346 and to a lesser extent on Ser330. Loss of NDRG1 increases cell death induced by mitoDFX. Notably, MDA-MB-231 cells lacking NDRG1 exhibit reduced extracellular acidification rate and grow slower than parental cells, while the opposite is true for ER+ MCF7 cells. Moreover, overexpression of full-length NDRG1 and the N-terminally truncated isoform (59112) significantly reduced sensitivity towards mitoDFX in ER+ cells. Furthermore, cells overexpressing full-length NDRG1 exhibited a significantly accelerated tumor formation, while its N-terminally truncated isoforms showed significantly impaired capacity to form tumors. Thus, overexpression of full-length NDRG1 promotes tumor growth in highly aggressive triple-negative breast cancer.

Identification and validation of functional roles for three MYC-associated genes in hepatocellular carcinoma

BACKGROUND

Aberrations in MYC underlie a large proportion of liver hepatocellular carcinoma (LIHC) cases; however, MYC is difficult to target because of its undruggable structure. We aimed to uncover MYC-associated molecular targets to provide new strategies for LIHC treatment.

METHODS

LIHC transcriptome datasets and clinical information were obtained from The Cancer Genome Atlas. A series of bioinformatics analyses were performed for 370 patients who were stratified based on the median MYC expression level (high-MYC group and low-MYC group). Correlation analysis was performed to determine relationships between the expression of key MYC-associated genes and prognosis, DNA promotor methylation, and immune cell infiltration. Gene ontology and Kyoto Encyclopedia of Genes and Genomes Pathway enrichment analyses were performed to elucidate the functions of these genes in LIHC. Their expression and functions in LIHC were further verified using transgenic mice overexpressing c-Myc under control of the hepatocyte-specific promoter (Alb-Cre).

RESULTS

AURKB, CCNB2, and CDKN3 were overexpressed in LIHC patients with high MYC expression and were associated with poor prognosis. Upregulation of these 3 genes was significantly correlated with hypomethylated promoter status, advanced T stage, metastasis, and immune cell infiltration in LIHC patients. Functional enrichment analyses indicated that these genes participate in the "p53 signaling pathway" and "cell cycle". Furthermore, RT-PCR and IHC analysis revealed that their mRNA and protein expression levels were upregulated in an Alb-Cre;cMYClsl/- mouse model. Drugs that target these 3 MYC-related genes were identified.

CONCLUSION

Taken together, our results identify biomarkers of potential utility for managing liver cancer therapy owing to their significance in tumorigenesis, proliferation, and tumor immunity.

Metal-dependent programmed cell death-related lncRNA prognostic signatures and natural drug sensitivity prediction for gastric cancer

Background: Gastric cancer is one of the most important malignancies with poor prognosis. Ferroptosis and cuproptosis are newly discovered metal-dependent types of programmed cell death, which may directly affect the outcome of gastric cancer. Long noncoding RNAs (lncRNAs) can affect the prognosis of cancer with stable structures, which could be potential prognostic prediction factors for gastric cancer.

Methods: Differentially expressed metal-dependent programmed cell death (PCD)-related lncRNAs were identified with DESeq2 and Pearson’s correlation analysis. Through GO and KEGG analyses and GSEA , we identified the potential effects of metal-dependent PCD-related lncRNAs on prognosis. Using Cox regression analysis with the LASSO method, we constructed a 12-lncRNA prognostic signature model. Also, we evaluated the prognostic efficiency with Kaplan–Meier (K-M) survival curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) methods. The sensitivities for antitumor drugs were then predicted with the pRRophetic method. Also, we discuss Chinese patent medicines and plant extracts that could induce metal-dependent programmed cell death.

Results: We constructed a metal-dependent PCD-related lncRNA-gene co-expression network. Also, a metal-dependent PCD-related gastric cancer prognostic signature model including 12 lncRNAs was constructed. The K-M survival curve revealed a poor prognosis in the high-risk group. ROC curve analysis shows that the AUC of our model is 0.766, which is better than that of other published models. Moreover, the half-maximum inhibitory concentration (IC50) for dasatinib, lapatinib, sunitinib, cytarabine, saracatinib, and vinorelbine was much lower among the high-risk group.

Conclusion: Our 12 metal-dependent PCD-related lncRNA prognostic signature model may improve the OS prediction for gastric cancer. The antitumor drug sensitivity analysis results may also be helpful for individualized chemotherapy regimen design.

NDRG4 Alleviates Myocardial Infarction-Induced Apoptosis through the JAK2/STAT3 Pathway

OBJECTIVE

At present, studies have confirmed that NDRG4 is specifically expressed in the heart, while its effect on the heart is still unclear. This study is to explore the effect of NDRG4 on cardiomyocyte apoptosis caused by acute myocardial infarction (AMI).

METHODS

Twenty SD rats were randomly divided into Sham (left anterior descent of heart without ligation) and AMI groups. In this study, coronary artery ligation was used to establish an AMI model, and the AMI model was verified by auxiliary examination and pathological examination. Besides, quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting (WB) was used to detect the expression level of Bax and Bcl-2 in heart tissues, and NDRG mRNA levels in tissues were also detected. qRT-PCR technology was used to verify the transfection efficiency of NDRG4 in H9C2 cells, and the change of apoptosis level of H9C2 cells was detected by Cell Counting Kit-8 (CCK-8) assay and TUNEL staining; besides, the expression level of apoptosis-related factors was detected by WB and qRT-PCR technology. Simultaneously with the modeling of rats, we injected adenovirus (Ad) into the heart tissue and examined the structural and functional changes of the rat heart. Then, WB technology was used to detect the expression level of the JAK2/STAT3 signaling pathway.

RESULTS

The heart function and heart structure of rats in the MI group were dramatically worse, and the expression level of NDRG4 was also dramatically reduced. The overexpression of NDRG4 in H9C2 cells can effectively inhibit the ischemia/hypoxia- (I/H-) induced decrease in cell viability and increase in apoptosis rate and inhibit the increase in Bax/Bcl-2 ratio. Moreover, overexpression of NDRG4 in heart tissue can effectively improve the cardiac function and structural destruction caused by MI. In addition, NDRG4 can inhibit JAK2/STAT3 pathway activation.

CONCLUSION

The expression of NDRG4 in the MI tissue of rats was suppressed, while overexpression of NDRG4 by injection of Ad can obviously protect the rat heart. Furthermore, overexpression of NDRG4 in H9C2 cells can effectively inhibit the I/H-induced decrease in cell viability and increase in apoptosis rate, and this may be related to the inhibition of the JAK2/STAT3 signaling pathway.

NDRG4 sensitizes CRC cells to 5-FU by upregulating DDIT3 expression

The incidence of colorectal cancer (CRC) has remained high in recent years, and 5-fluorouracil (5-FU) is a vital chemotherapeutic agent for its treatment. Our previous study reported that N-myc downstream-regulated gene 4 (NDRG4) plays a tumor-suppressive role in CRC, but the mechanisms associated with NDRG4 and 5-FU chemosensitivity remain unclear. The results of the present study demonstrate that NDRG4 sensitized CRC cells to 5-FU by upregulating DNA damage inducible transcript 3 (DDIT3). NDRG4 inhibited the proliferation of CRC cells and the activation of PI3K/AKT and ERK signaling. Furthermore, NDRG4 promoted CRC cell apoptosis induced by 5-FU. Mechanistic analyses revealed that NDRG4 upregulated DDIT3 expression, and that the proapoptotic effect of NDRG4 under 5-FU treatment conditions was dependent on DDIT3. These findings support the biological value of the association between NDRG4, DDIT3 and 5-FU chemosensitivity in CRC, and may advance the clinical treatment of CRC in the future.

Construction on of a Ferroptosis-Related lncRNA-Based Model to Improve the Prognostic Evaluation of Gastric Cancer Patients Based on Bioinformatics

Background

Gastric cancer is one of the most serious gastrointestinal malignancies with bad prognosis. Ferroptosis is an iron-dependent form of programmed cell death, which may affect the prognosis of gastric cancer patients. Long non-coding RNAs (lncRNAs) can affect the prognosis of cancer through regulating the ferroptosis process, which could be potential overall survival (OS) prediction factors for gastric cancer.

Methods

Ferroptosis-related lncRNA expression profiles and the clinicopathological and OS information were collected from The Cancer Genome Atlas (TCGA) and the FerrDb database. The differentially expressed ferroptosis-related lncRNAs were screened with the DESeq2 method. Through co-expression analysis and functional annotation, we then identified the associations between ferroptosis-related lncRNAs and the OS rates for gastric cancer patients. Using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) algorithm, we constructed a prognostic model based on 17 ferroptosis-related lncRNAs. We also evaluated the prognostic power of this model using Kaplan–Meier (K-M) survival curve analysis, receiver operating characteristic (ROC) curve analysis, and decision curve analysis (DCA).

Results

A ferroptosis-related “lncRNA–mRNA” co-expression network was constructed. Functional annotation revealed that the FOXO and HIF-1 signaling pathways were dysregulated, which might control the prognosis of gastric cancer patients. Then, a ferroptosis-related gastric cancer prognostic signature model including 17 lncRNAs was constructed. Based on the RiskScore calculated using this model, the patients were divided into a High-Risk group and a low-risk group. The K-M survival curve analysis revealed that the higher the RiskScore, the worse is the obtained prognosis. The ROC curve analysis showed that the area under the ROC curve (AUC) of our model is 0.751, which was better than those of other published models. The multivariate Cox regression analysis results showed that the lncRNA signature is an independent risk factor for the OS rates. Finally, using nomogram and DCA, we also observed a preferable clinical practicality potential for prognosis prediction of gastric cancer patients.

Conclusion

Our prognostic signature model based on 17 ferroptosis-related lncRNAs may improve the overall survival prediction in gastric cancer.

Exome hits demystified: The next frontier

Severe mental illnesses such as schizophrenia and bipolar disorder have complex inheritance patterns, involving both common and rare variants. Whole exome sequencing is a promising approach to find out the rare genetic variants. We had previously reported several rare variants in multiplex families with severe mental illnesses. The current article tries to summarise the biological processes and pattern of expression of genes harbouring the aforementioned variants, linking them to known clinical manifestations through a methodical narrative review. Of the 28 genes considered for this review from 7 families with multiple affected individuals, 6 genes are implicated in various neuropsychiatric manifestations including some variations in the brain morphology assessed by magnetic resonance imaging. Another 15 genes, though associated with neuropsychiatric manifestations, did not have established brain morphological changes whereas the remaining 7 genes did not have any previously recorded neuropsychiatric manifestations at all. Wnt/b-catenin signaling pathway was associated with 6 of these genes and PI3K/AKT, calcium signaling, ERK, RhoA and notch signaling pathways had at least 2 gene associations. We present a comprehensive review of biological and clinical knowledge about the genes previously reported in multiplex families with severe mental illness. A 'disease in dish approach' can be helpful to further explore the fundamental mechanisms.

Construction of a Myc-associated ceRNA network reveals a prognostic signature in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains an extremely lethal disease worldwide. High-throughput methods have revealed global transcriptome dysregulation; however, a comprehensive investigation of the complexity and behavioral characteristics of the competing endogenous RNA (ceRNA) network in HCC is lacking. In this study, we extracted the transcriptome (RNA) sequencing data of 371 HCC patients from The Cancer Genome Atlas platform. With the comparison of the high Myc expression (Myc^high) tumor and low Myc expression (Myc^low) tumor groups in HCC, we identified 1,125 differentially expressed (DE) mRNAs, 589 long non-coding RNAs (lncRNAs), and 93 microRNAs (miRNAs). DE RNAs predicted the interactions necessary to construct an associated Myc ceRNA network, including 19 DE lncRNAs, 5 miRNAs, and 72 mRNAs. We identified a significant signature (long intergenic non-protein-coding [LINC] RNA 2691 [LINC02691] and LINC02499) that effectively predicted overall survival and had protective effects. The target genes of microRNA (miR)-212-3p predicted to intersect with DE mRNAs included SEC14-like protein 2 (SEC14L2) and solute carrier family 6 member 1 (SLC6A1), which were strongly correlated with survival and prognosis. With the use of the lncRNA-miRNA-mRNA axis, we constructed a ceRNA network containing four lncRNAs (LINC02691, LINC02499, LINC01354, and NAV2 antisense RNA 4), one miRNA (miR-212-3p), and two mRNAs (SEC14L2 and SLC6A1). Overall, we successfully constructed a mutually regulated ceRNA network and identified potential precision-targeted therapies and prognostic biomarkers.

Immune gene prognostic signature for disease free survival of gastric cancer: Translational research of an artificial intelligence survival predictive system

The progress of artificial intelligence algorithms and massive data provide new ideas and choices for individual mortality risk prediction for cancer patients. The current research focused on depict immune gene related regulatory network and develop an artificial intelligence survival predictive system for disease free survival of gastric cancer.

Multi-task logistic regression algorithm, Cox survival regression algorithm, and Random survival forest algorithm were used to develop the artificial intelligence survival predictive system.

Nineteen transcription factors and seventy immune genes were identified to construct a transcription factor regulatory network of immune genes. Multivariate Cox regression identified fourteen immune genes as prognostic markers. These immune genes were used to construct a prognostic signature for gastric cancer. Concordance indexes were 0.800, 0.809, and 0.856 for 1-, 3- and 5- year survival. An interesting artificial intelligence survival predictive system was developed based on three artificial intelligence algorithms for gastric cancer. Gastric cancer patients with high risk score have poor survival than patients with low risk score.

The current study constructed a transcription factor regulatory network and developed two artificial intelligence survival prediction tools for disease free survival of gastric cancer patients. These artificial intelligence survival prediction tools are helpful for individualized treatment decision.

High expression of NDRG3 correlates with poor prognosis in gastric cancer patients

INTRODUCTION

N-myc downstream-regulated gene 3 (NDRG3) is an important member of the NDRG family and is linked with malignant tumors. However, the relationship between NDRG3 and gastric cancer (GC) is vague.

MATERIAL AND METHODS

Western blot, qRT-PCR and immunohistochemistry (IHC) detected the expression of NDRG3 in GC cell lines and GC tissues; public databases were used to analyze NDRG3 in GC patients and the association with EBV infection.

RESULTS

NDRG3 was up-regulated in GC cell lines and tissues. IHC data suggested that NDRG3 was correlated with histologic grade (p = 0.006) and is associated with patient survival.

DISCUSSION

thus, NDRG3 may be a novel predictor of GC prognosis.

Reversing oncogenic transformation with iron chelation

Cancer cells accumulate iron to supplement their aberrant growth and metabolism. Depleting cells of iron by iron chelators has been shown to be selectively cytotoxic to cancer cells in vitro and in vivo. Iron chelators are effective at combating a range of cancers including those which are difficult to treat such as androgen insensitive prostate cancer and cancer stem cells. This review will evaluate the impact of iron chelation on cancer cell survival and the underlying mechanisms of action. A plethora of studies have shown iron chelators can reverse some of the major hallmarks and enabling characteristics of cancer. Iron chelators inhibit signalling pathways that drive proliferation, migration and metastasis as well as return tumour suppressive signalling. In addition to this, iron chelators stimulate apoptotic and ER stress signalling pathways inducing cell death even in cells lacking a functional p53 gene. Iron chelators can sensitise cancer cells to PARP inhibitors through mimicking BRCAness; a feature of cancers trademark genomic instability. Iron chelators target cancer cell metabolism, attenuating oxidative phosphorylation and glycolysis. Moreover, iron chelators may reverse the major characteristics of oncogenic transformation. Iron chelation therefore represent a promising selective mode of cancer therapy.

NDRG1 enhances the sensitivity of cetuximab by modulating EGFR trafficking in colorectal cancer

N-myc downstream-regulated gene 1 (NDRG1) is a key regulator that interacts with many classic tumor signaling pathways, including some molecules downstream of the epidermal growth factor receptor (EGFR). However, whether NDRG1 is involved in the mechanism of resistance to cetuximab (CTX), the first monoclonal antibody targeting the EGFR has not been reported. Here, we found that NDRG1 enhanced the sensitivity of CTX in colorectal cancer (CRC) cell lines. Afterwards, we determined the underlying mechanism of this phenomenon. We demonstrated that NDRG1 inhibited the expression of EGFR; blocked EGFR phosphorylation and reduced the EGFR distribution in the cell membrane, cytoplasm and nucleus. And then, NDRG1 suppressed the EGFR downstream signaling: RAS/RAF/ERK and PI3k/AKT/mTOR pathways. Moreover, we discovered that NDRG1 attenuated the endocytosis and degradation of EGFR induced by caveolin-1 (Cav1). Additionally, our findings were further observed in an animal model and human tissues. Our results represent a potentially significant discovery that explains the mechanisms of NDRG1 in CTX resistance. NDRG1 could be a promising biomarker to predict optimum responses to CTX, and a key target to enhance CTX activity in the treatment of metastatic CRC (mCRC).

Integrative Analysis of DNA Methylation Identified 12 Signature Genes Specific to Metastatic ccRCC

Background: Abnormal epigenetic alterations can contribute to the development of human malignancies. Identification of these alterations for early screening and prognosis of clear cell renal cell carcinoma (ccRCC) has been a highly sought-after goal. Bioinformatic analysis of DNA methylation data provides broad prospects for discovery of epigenetic biomarkers. However, there is short of exploration of methylation-driven genes of ccRCC.

Methods: Gene expression data and DNA methylation data in metastatic ccRCC were sourced from the Gene Expression Omnibus (GEO) database. Differentially methylated genes (DMGs) at 5′-C-phosphate-G- 3′ (CpG) sites and differentially expressed genes (DEGs) were screened and the overlapping genes in DMGs and DEGs were then subject to gene set enrichment analysis. Next, the weighted gene co-expression network analysis (WGCNA) was used to search hub DMGs associated with ccRCC. Cox regression and ROC analyses were performed to screen potential biomarkers and develop a prognostic model based on the screened hub genes.

Results: Three hundred and fourteen overlapping DMGs were obtained from two independent GEO datasets. The turquoise module contained 79 hub DMGs, which represent the most significant module screened by WGCNA. Furthermore, a total of 12 hub genes (CETN3, DCAF7, GPX4, HNRNPA0, NUP54, SERPINB1, STARD5, TRIM52, C4orf3, C12orf51, and C17orf65) were identified in the TCGA database by multivariate Cox regression analyses. All the 12 genes were then used to generate the model for diagnosis and prognosis of ccRCC. ROC analysis showed that these genes exhibited good diagnostic efficiency for metastatic and non-metastatic ccRCC. Furthermore, the prognostic model with the 12 methylation-driven genes demonstrated a good prediction of 5-year survival rates for ccRCC patients.

Conclusion: Integrative analysis of DNA methylation data identified 12 signature genes, which could be used as epigenetic biomarkers for prognosis of metastatic ccRCC. This prognostic model has a good prediction of 5-year survival for ccRCC patients.

Construction of a Nomogram Based on a Hypoxia-Related lncRNA Signature to Improve the Prediction of Gastric Cancer Prognosis

Background

Gastric cancer is one of the most common malignant tumors and has a poor prognosis. Hypoxia is related to the poor prognosis of cancer patients. We searched for hypoxia-related long non-coding RNAs (lncRNAs) to predict both overall survival (OS) and disease-free survival (DFS) of gastric cancer patients.

Methods

We obtained hypoxia-related lncRNA expression profiles and clinical follow-up data of patients with gastric cancer from The Cancer Genome Atlas and the Molecular Signatures Database. The patients were randomly divided into a training group, test group and combined group. The hypoxia-related prognostic signature was constructed by Lasso regression and Cox regression models, the prognoses in different groups were compared by Kaplan-Meier (K-M) analysis, and the accuracy of the prognostic model was assessed by receiver operating characteristic (ROC) analysis.

Results

A hypoxia-related prognostic signature comprising 10 lncRNAs was constructed to predict both OS and DFS in gastric cancer. In the training, test and combined groups, patients were divided into high- and low-risk groups according to the formula. Kaplan-Meier analysis showed that patients in the high-risk group have poor prognoses, and the difference was significant in the subgroup analyses. Receiver operating characteristic analysis revealed that the predictive power of the model prediction is more accurate than that of standard benchmarks. The signature differed across Helicobacter pylori (Hp) status and T stages. Multivariate Cox analysis showed that the signature is an independent risk factor for both OS and DFS. A clinically predictive nomogram combining the lncRNA signature and clinical features was constructed; the nomogram accurately predicted both OS and DFS and had high clinical application value. Weighted correlation network analysis combined with enrichment analysis showed that the primary pathways were the PI3K-Akt, JAK-STAT, and IL-17 signaling pathways. The target genes NOX4, COL8A1, and CHST1 were associated with poor prognosis in the Gene Expression Profiling Interactive Analysis, Gene Expression Omnibus, and K-M Plotter databases.

Conclusions

Our 10-lncRNA prognostic signature and nomogram are accurate, reliable tools for predicting both OS and DFS in gastric cancer.

An immune risk score with potential implications in prognosis and immunotherapy of metastatic melanoma

Melanoma is a highly aggressive cancer with a poor prognosis. We found that immune response played important roles in melanoma metastasis by GSEA analysis. Therefore, we constructed the immune risk score (IRS) by the LASSO-COX analysis in the sequencing metastatic samples from the TCGA database. Then, initial diagnosis patients with metastasis were selected as the test cohort. Importantly, we adopted overall survival (OS) as the survival outcome for initial diagnosis patients, while adopting the observed survival interval (OBS) as the survival outcome for sequencing samples which could avoid biologically meaningless associations. We found that the IRS had high power for predicting 2, 3 and 5-year survival in training (AUC = 0.70, 0.69 and 0.68) and test cohorts (AUC = 0.72, 0.70 and 0.65). The IRS was significantly associated with prognosis both in the metastatic samples (HR = 1.60, 95% CI = 1.16-2.19) and patients with metastasis (HR = 2.89, 95% CI = 1.69-4.53). we further used other independent melanoma cohorts from the GEO databases to confirm the reliability and validity of the IRS (P < 0.01 in all cohorts). The practical nomogram was also built using the IRS and clinical information with high c-index both in training (0.76, 95%CI = 0.72-0.80) and test cohorts (0.72, 95%CI = 0.65-0.79). Finally, IRS showed the predictive value of survival outcome and response of immunotherapy patients, and increased the predictive ability of current immune checkpoint gene markers. In conclusion, the IRS can serve as a potential biomarker for prognosis and responsiveness to immune checkpoint blockade immunotherapy in metastatic melanoma patients.

Systematic Review of Prognostic Gene Signature in Gastric Cancer Patients

Gastric cancer (GC) is the second leading cause of cancer mortality and remains the fourth common cancer worldwide. The effective and feasible methods for predicting the possible outcomes for GC patients are still lacking. While genetic profiling might be suitable in some way, the application of gene expression signatures has been show to be a robust tool. Here, by performing a comprehensive search in PubMed, we provided an up-to-date summary of 39 prognostic gene signatures for GC patients, and described the processing procedure of the selection, calculation and construction of gene signature. We also reviewed current web tools including PROGgene and SurvExpress that can be used to analyze the prognostic value of multiple genes for GC. This review will aid in comprehensive understanding of the current prognostic gene signatures to accurately predict the outcome of GC patients, and may guide the future clinical management when the reliability of these signatures is validated in clinics.

Non-Invasive Colorectal Cancer Screening: An Overview

BACKGROUND

Colorectal cancer (CRC) follows a protracted stepwise progression, from benign adenomas to malignant adenocarcinomas. If detected early, 90% of deaths are preventable. However, CRC is asymptomatic in its early-stage and arises sporadically within the population. Therefore, CRC screening is a public health priority.

SUMMARY

Faecal immunochemical test (FIT) is gradually replacing guaiac faecal occult blood test and is now the most commonly used screening tool for CRC screening program globally. However, FIT is still limited by the haemoglobin degradation and the intermittent bleeding patterns, so that one in four CRC cases are still diagnosed in a late stage, leading to poor prognosis. A multi-target stool DNA test (Cologuard, a combination of NDRG4 and BMP3 DNA methylation, KRAS mutations, and haemoglobin) and a plasma SEPT9 DNA methylation test (Epi proColon) are non-invasive tools also approved by the US FDA, but those screening approaches are not cost-effective, and the detection accuracies remain unsatisfactory. In addition to the approved tests, faecal-/blood-based microRNA and CRC-related gut microbiome screening markers are under development, with work ongoing to find the best combination of molecular biomarkers which maximise the screening sensitivity and specificity.

KEY MESSAGE

Maximising the detection accuracy with a cost-effective approach for non-invasive CRC screening is urgently needed to further reduce the incidence of CRC and associated mortality rates.