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

A miRNA-disease association prediction model based on tree-path global feature extraction and fully connected artificial neural network with multi-head self-attention mechanism

BACKGROUND

MicroRNAs (miRNAs) emerge in various organisms, ranging from viruses to humans, and play crucial regulatory roles within cells, participating in a variety of biological processes. In numerous prediction methods for miRNA-disease associations, the issue of over-dependence on both similarity measurement data and the association matrix still hasn't been improved. In this paper, a miRNA-Disease association prediction model (called TP-MDA) based on tree path global feature extraction and fully connected artificial neural network (FANN) with multi-head self-attention mechanism is proposed. The TP-MDA model utilizes an association tree structure to represent the data relationships, multi-head self-attention mechanism for extracting feature vectors, and fully connected artificial neural network with 5-fold cross-validation for model training.

RESULTS

The experimental results indicate that the TP-MDA model outperforms the other comparative models, AUC is 0.9714. In the case studies of miRNAs associated with colorectal cancer and lung cancer, among the top 15 miRNAs predicted by the model, 12 in colorectal cancer and 15 in lung cancer were validated respectively, the accuracy is as high as 0.9227.

CONCLUSIONS

The model proposed in this paper can accurately predict the miRNA-disease association, and can serve as a valuable reference for data mining and association prediction in the fields of life sciences, biology, and disease genetics, among others.

Biomarker Profile of Colorectal Cancer: Current Findings and Future Perspective

OBJECTIVE

Breakthroughs in omics technology have led to a deeper understanding of the fundamental molecular changes that play a critical role in the development and progression of cancer. This review delves into the hidden molecular drivers of colorectal cancer (CRC), offering potential for clinical translation through novel biomarkers and personalized therapies.

METHODS

We summarizes recent studies utilizing various omics approaches, including genomics, transcriptomics, proteomics, epigenomics, metabolomics and data integration with computational algorithms, to investigate CRC.

RESULTS

Integrating multi-omics data in colorectal cancer research unlocks hidden biological insights, revealing new pathways and mechanisms. This powerful approach not only identifies potential biomarkers for personalized prognosis, diagnosis, and treatment, but also predicts patient response to specific therapies, while computational tools illuminate the landscape by deciphering complex datasets.

CONCLUSIONS

Future research should prioritize validating promising biomarkers and seamlessly translating them into clinical practice, ultimately propelling personalized CRC management to new heights.

The utility of liquid biopsy-based methylation biomarkers for colorectal cancer detection

Colorectal cancer (CRC) is one of the most prevalent cancers and the second leading cause of cancer-related deaths in the United States. It is also one of the few cancers with established screening guidelines, however these methods have significant patient burden (e.g., time, invasive). In recent years, the development of liquid biopsy-based screening methods for biomarker detection have emerged as alternatives to traditional screening. Methylation biomarkers are of particular interest, and these markers can be identified and measured on circulating tumor and cell-free DNA. This perspective summarizes the current state of CRC screening and the potential integration of DNA methylation markers into liquid biopsy-based techniques. Finally, I discuss limitations to these methods and strategies for improvement. The continued development and implementation of liquid biopsy-based cancer screening approaches may provide an acceptable alternative to individuals unwilling to be screened by traditional methods.

Chinmedomics: a potent tool for the evaluation of traditional Chinese medicine efficacy and identification of its active components

As an important part of medical science, Traditional Chinese Medicine (TCM) attracts much public attention due to its multi-target and multi-pathway characteristics in treating diseases. However, the limitations of traditional research methods pose a dilemma for the evaluation of clinical efficacy, the discovery of active ingredients and the elucidation of the mechanism of action. Therefore, innovative approaches that are in line with the characteristics of TCM theory and clinical practice are urgently needed. Chinmendomics, a newly emerging strategy for evaluating the efficacy of TCM, is proposed. This strategy combines systems biology, serum pharmacochemistry of TCM and bioinformatics to evaluate the efficacy of TCM with a holistic view by accurately identifying syndrome biomarkers and monitoring their complex metabolic processes intervened by TCM, and finding the agents associated with the metabolic course of pharmacodynamic biomarkers by constructing a bioinformatics-based correlation network model to further reveal the interaction between agents and pharmacodynamic targets. In this article, we review the recent progress of Chinmedomics to promote its application in the modernisation and internationalisation of TCM.

Population-based screening for colorectal cancer in Wuhan, China

Fecal DNA test has emerged as a non-invasive alternative for colorectal cancer (CRC) screening in average-risk population. However, there is currently insufficient evidence in China to demonstrate the effectiveness of population-based CRC screening using fecal DNA based test. Here, a large-scale real-world study for CRC screening was implemented in Wuhan, Hubei province, China. A total of 98,683 subjects aged between 45 and 60 years were screened by a fecal DNA test (ColoTect®) which detected methylation status of SDC2, ADHFE1, and PPP2R5C. Participants who tested positive were advised to receive diagnostic colonoscopy. 4449 (4.5%) subjects tested positive for fecal DNA test, and 3200 (71.9%) underwent colonoscopy. Among these, 2347 (73.3%) had abnormal colonoscopy findings, of which 1330 (56.7%) subjects received pathological diagnosis. Detection rates for CRC and advanced precancerous lesions were 1.3% and 2.3%, respectively. Detection rates for nonadvanced adenomas and polyps were 14.0% and 21.6%, respectively. 28.0% of all colonoscopies showed colorectal neoplasm but lack pathological diagnosis. 6.1% showed other abnormalities such as enteritis. In conclusion, preliminary real-world evidence suggested that fecal DNA tests had promising diagnostic yield in population-based CRC screening.

Clinical trial registration

https://www.chictr.org.cn/showproj.html?proj=192838, identifier ChiCTR2300070520.

Current Research on Molecular Biomarkers for Colorectal Cancer in Stool Samples

Colorectal cancer (CRC) is one of the most diagnosed cancers worldwide, with a high incidence and mortality rate when diagnosed late. Currently, the methods used in healthcare to diagnose CRC are the fecal occult blood test, flexible sigmoidoscopy, and colonoscopy. However, the lack of sensitivity and specificity and low population adherence are driving the need to implement other technologies that can identify biomarkers that not only help with early CRC detection but allow for the selection of more personalized treatment options. In this regard, the implementation of omics technologies, which can screen large pools of biological molecules, coupled with molecular validation, stands out as a promising tool for the discovery of new biomarkers from biopsied tissues or body fluids. This review delves into the current state of the art in the identification of novel CRC biomarkers that can distinguish cancerous tissue, specifically from fecal samples, as this could be the least invasive approach.

Profiling the metabolic disorder and detection of colorectal cancer based on targeted amino acids metabolomics

BACKGROUND

The morbidity of cancer keeps growing worldwide, and among that, the colorectal cancer (CRC) has jumped to third. Existing early screening tests for CRC are limited. The aim of this study was to develop a diagnostic strategy for CRC by plasma metabolomics.

METHODS

A targeted amino acids metabolomics method was developed to quantify 32 plasma amino acids in 130 CRC patients and 216 healthy volunteers, to identify potential biomarkers for CRC, and an independent sample cohort comprising 116 CRC subjects, 33 precancerosiss patients and 195 healthy volunteers was further used to validate the diagnostic model. Amino acids-related genes were retrieved from Gene Expression Omnibus and Molecular Signatures Database and analyzed.

RESULTS

Three were chosen out of the 32 plasma amino acids examined. The tryptophan / sarcosine / glutamic acid -based receiver operating characteristic (ROC) curve showed the area under the curve (AUC) of 0.955 (specificity 83.3% and sensitivity 96.8%) for all participants, and the logistic regression model were used to distinguish between early stage (I and II) of CRC and precancerosiss patients, which showed superiority to the commonly used carcinoembryonic antigen. The GO and KEGG enrichment analysis proved many alterations in amino acids metabolic pathways in tumorigenesis.

CONCLUSION

This altered plasma amino acid profile could effectively distinguish CRC patients from precancerosiss patients and healthy volunteers with high accuracy. Prognostic tests based on the tryptophan/sarcosine/glutamic acid biomarkers in the large population could assess the clinical significance of CRC early detection and intervention.

Unveiling the genetic and epigenetic landscape of colorectal cancer: new insights into pathogenic pathways

Colorectal cancer (CRC) is a complex disease characterized by genetic and epigenetic alterations, playing a crucial role in its development and progression. This review aims to provide insights into the emerging landscape of these alterations in CRC pathogenesis to develop effective diagnostic tools and targeted therapies. Genetic alterations in signaling pathways such as Wnt/β-catenin, and PI3K/Akt/mTOR are pivotal in CRC development. Genetic profiling has identified distinct molecular subtypes, enabling personalized treatment strategies. Epigenetic modifications, including DNA methylation and histone modifications, also contribute to CRC pathogenesis by influencing critical cellular processes through gene silencing or activation. Non-coding RNAs have emerged as essential players in epigenetic regulation and CRC progression. Recent research highlights the interplay between genetic and epigenetic alterations in CRC. Genetic mutations can affect epigenetic modifications, leading to dysregulated gene expression and signaling cascades. Conversely, epigenetic changes can modulate genetic expression, amplifying or dampening the effects of genetic alterations. Advancements in understanding pathogenic pathways have potential clinical applications. Identifying genetic and epigenetic markers as diagnostic and prognostic biomarkers promises more accurate risk assessment and early detection. Challenges remain, including validating biomarkers and developing robust therapeutic strategies through extensive research and clinical trials. The dynamic nature of genetic and epigenetic alterations necessitates a comprehensive understanding of their temporal and spatial patterns during CRC progression. In conclusion, the genetic and epigenetic landscape of CRC is increasingly being unraveled, providing valuable insights into its pathogenesis. Integrating genetic and epigenetic knowledge holds great potential for improving diagnostics, prognostics, and personalized therapies in CRC. Continued research efforts are vital to translate these findings into clinical practice, ultimately improving patient outcomes.

Proteomics-based identification of proteins in tumor-derived exosomes as candidate biomarkers for colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is the second leading cause of cancer-related death, with high morbidity worldwide. There is an urgent need to find reliable diagnostic biomarkers of CRC and explore the underlying molecular mechanisms. Exosomes are involved in intercellular communication and participate in multiple pathological processes, serving as an important part of the tumor microenvironment.

AIM

To investigate the proteomic characteristics of CRC tumor-derived exosomes and to identify candidate exosomal protein markers for CRC.

METHODS

In this study, 10 patients over 50 years old who were diagnosed with moderately differentiated adenocarcinoma were recruited. We paired CRC tissues and adjacent normal intestinal tissues (> 5 cm) to form the experimental and control groups. Purified exosomes were extracted separately from each tissue sample. Data-independent acquisition mass spectrometry was implemented in 8 matched samples of exosomes to explore the proteomic expression profiles, and differentially expressed proteins (DEPs) were screened by bioinformatics analysis. Promising exosomal proteins were verified using parallel reaction monitoring (PRM) analysis in 10 matched exosome samples.

RESULTS

A total of 1393 proteins were identified in the CRC tissue group, 1304 proteins were identified in the adjacent tissue group, and 283 proteins were significantly differentially expressed between them. Enrichment analysis revealed that DEPs were involved in multiple biological processes related to cytoskeleton construction, cell movement and migration, immune response, tumor growth and telomere metabolism, as well as ECM-receptor interaction, focal adhesion and mTOR signaling pathways. Six differentially expressed exosomal proteins (NHP2, OLFM4, TOP1, SAMP, TAGL and TRIM28) were validated by PRM analysis and evaluated by receiver operating characteristic curve (ROC) analysis. The area under the ROC curve was 0.93, 0.96, 0.97, 0.78, 0.75, and 0.88 (P < 0.05) for NHP2, OLFM4, TOP1, SAMP, TAGL, and TRIM28, respectively, indicating their good ability to distinguish CRC tissues from adjacent intestinal tissues.

CONCLUSION

In our study, comprehensive proteomic profiles were obtained for CRC tissue exosomes. Six exosomal proteins, NHP2, OLFM4, TOP1, SAMP, TAGL and TRIM28, may be promising diagnostic markers and effective therapeutic targets for CRC, but further experimental investigation is needed.

From Omic Layers to Personalized Medicine in Colorectal Cancer: The Road Ahead

Colorectal cancer is a major health concern since it is a highly diagnosed cancer and the second cause of death among cancers. Thus, the most suitable biomarkers for its diagnosis, prognosis, and treatment have been studied to improve and personalize the prevention and clinical management of colorectal cancer. The emergence of omic techniques has provided a great opportunity to better study CRC and make personalized medicine feasible. In this review, we will try to summarize how the analysis of the omic layers can be useful for personalized medicine and the existing difficulties. We will discuss how single and multiple omic layer analyses have been used to improve the prediction of the risk of CRC and its outcomes and how to overcome the challenges in the use of omic layers in personalized medicine.

Comprehensive Insight into Colorectal Cancer Metabolites and Lipids for Human Serum: A Proof-of-Concept Study

Colorectal cancer (CRC) ranks as the third most frequently diagnosed cancer and the second leading cause of cancer-related deaths. The current endoscopic-based or stool-based diagnostic techniques are either highly invasive or lack sufficient sensitivity. Thus, there is a need for less invasive and more sensitive screening approaches. We, therefore, conducted a study on 64 human serum samples representing three different groups (adenocarcinoma, adenoma, and control) using cutting-edge GC×GC-LR/HR-TOFMS (comprehensive two-dimensional gas chromatography coupled with low/high-resolution time-of-flight mass spectrometry). We analyzed samples with two different specifically tailored sample preparation approaches for lipidomics (fatty acids) (25 μL serum) and metabolomics (50 μL serum). In-depth chemometric screening with supervised and unsupervised approaches and metabolic pathway analysis were applied to both datasets. A lipidomics study revealed that specific PUFA (ω-3) molecules are inversely associated with increased odds of CRC, while some PUFA (ω-6) analytes show a positive correlation. The metabolomics approach revealed downregulation of amino acids (alanine, glutamate, methionine, threonine, tyrosine, and valine) and myo-inositol in CRC, while 3-hydroxybutyrate levels were increased. This unique study provides comprehensive insight into molecular-level changes associated with CRC and allows for a comparison of the efficiency of two different analytical approaches for CRC screening using same serum samples and single instrumentation.

Protein Posttranslational Modification in Stemness Remodeling and Its Emerging Role as a Novel Therapeutic Target in Gastrointestinal Cancers

The posttranslational modifications (PTMs) of proteins, as critical mechanisms for protein regulation, are well known to enhance the functional diversity of the proteome and dramatically participate in complicated biological processes. Recent efforts in the field of cancer biology have illustrated the extensive landscape of PTMs and their crosstalk with a wide range of pro-tumorigenic signaling pathways that decisively contribute to neoplastic transformation, tumor recurrence, and resistance to oncotherapy. Cancer stemness is an emerging concept that maintains the ability of tumor cells to self-renew and differentiate and has been recognized as the root of cancer development and therapy resistance. In recent years, the PTM profile for modulating the stemness of various tumor types has been identified. This breakthrough has shed light on the underlying mechanisms by which protein PTMs maintain cancer stemness, initiate tumor relapse, and confer resistance to oncotherapies. This review focuses on the latest knowledge of protein PTMs in reprogramming the stemness of gastrointestinal (GI) cancer. A deeper understanding of abnormal PTMs in specific proteins or signaling pathways provides an opportunity to specifically target cancer stem cells and highlights the clinical relevance of PTMs as potential biomarkers and therapeutic targets for patients with GI malignancies.

The protective effects of baicalin for respiratory diseases: an update and future perspectives

Background: Respiratory diseases are common and frequent diseases. Due to the high pathogenicity and side effects of respiratory diseases, the discovery of new strategies for drug treatment is a hot area of research. Scutellaria baicalensis Georgi (SBG) has been used as a medicinal herb in China for over 2000 years. Baicalin (BA) is a flavonoid active ingredient extracted from SBG that BA has been found to exert various pharmacological effects against respiratory diseases. However, there is no comprehensive review of the mechanism of the effects of BA in treating respiratory diseases. This review aims to summarize the current pharmacokinetics of BA, baicalin-loaded nano-delivery system, and its molecular mechanisms and therapeutical effects for treating respiratory diseases.

Method: This review reviewed databases such as PubMed, NCBI, and Web of Science from their inception to 13 December 2022, in which literature was related to “baicalin”, “Scutellaria baicalensis Georgi”, “COVID-19”, “acute lung injury”, “pulmonary arterial hypertension”, “asthma”, “chronic obstructive pulmonary disease”, “pulmonary fibrosis”, “lung cancer”, “pharmacokinetics”, “liposomes”, “nano-emulsions”, “micelles”, “phospholipid complexes”, “solid dispersions”, “inclusion complexes”, and other terms.

Result: The pharmacokinetics of BA involves mainly gastrointestinal hydrolysis, the enteroglycoside cycle, multiple metabolic pathways, and excretion in bile and urine. Due to the poor bioavailability and solubility of BA, liposomes, nano-emulsions, micelles, phospholipid complexes, solid dispersions, and inclusion complexes of BA have been developed to improve its bioavailability, lung targeting, and solubility. BA exerts potent effects mainly by mediating upstream oxidative stress, inflammation, apoptosis, and immune response pathways. It regulates are the NF-κB, PI3K/AKT, TGF-β/Smad, Nrf2/HO-1, and ERK/GSK3β pathways.

Conclusion: This review presents comprehensive information on BA about pharmacokinetics, baicalin-loaded nano-delivery system, and its therapeutic effects and potential pharmacological mechanisms in respiratory diseases. The available studies suggest that BA has excellent possible treatment of respiratory diseases and is worthy of further investigation and development.

Correlation between SMADs and Colorectal Cancer Expression, Prognosis, and Immune Infiltrates

Background

In recent years, the incidence and mortality of colorectal cancer (CRC) are increasing, and the 5-year survival rate of advanced metastatic CRC is poor. Small mothers against decapentaplegic (SMAD) superfamily are intracellular signal transduction proteins associated with the development and prognosis of a variety of tumors. At present, no study has systematically analysed the relationship between SMADs and CRC.

Methods

Here, R3.6.3 was used to analyse the expression of SMADs in pan-cancer and CRC. Protein expression of SMADs were analysed by Human Protein Atlas (HPA). Gene expression profiling interactive analysis (GEPIA) was used to evaluate the correlation between SMADs and tumor stage in CRC. The effect of R language and GEPIA on prognosis was analysed. Mutation rates of SMADs in CRC were determined by cBioPortal, and potentially related genes were predicted using GeneMANIA. R analysis was used to correlate immune cell infiltration in CRC.

Results

Both SMAD1 and SMAD2 were found to be weakly expressed in CRC and correlated with the immune invasion level. SMAD1 was correlated with patient prognosis, and SMAD2 was correlated with tumor stage. SMAD3, SMAD4, and SMAD7 were all expressed at low levels in CRC and associated with a variety of immune cells. SMAD3 and SMAD4 proteins were also expressed at low levels, and SMAD4 had the highest mutation rate. SMAD5 and SMAD6 were overexpressed in CRC, and SMAD6 was also associated with patient overall survival (OS) and CD8+ T cells, macrophages, and neutrophils.

Conclusions

Our results reveal innovative and strong evidence that SMADs can be used as biomarkers for the treatment and prognosis of CRC.

Integrated analysis of multi-omics data for the discovery of biomarkers and therapeutic targets for colorectal cancer

The considerable burden of colorectal cancer and the rising trend in young adults emphasize the necessity of understanding its underlying mechanisms, providing new diagnostic and prognostic markers, and improving therapeutic approaches. Precision medicine is a new trend all over the world and identification of novel biomarkers and therapeutic targets is a step forward towards this trend. In this context, multi-omics data and integrated analysis are being investigated to develop personalized medicine in the management of colorectal cancer. Given the large amount of data from multi-omics approach, data integration and analysis is a great challenge. In this Review, we summarize how statistical and machine learning techniques are applied to analyze multi-omics data and how it contributes to the discovery of useful diagnostic and prognostic biomarkers and therapeutic targets. Moreover, we discuss the importance of these biomarkers and therapeutic targets in the clinical management of colorectal cancer in the future. Taken together, integrated analysis of multi-omics data has great potential for finding novel diagnostic and prognostic biomarkers and therapeutic targets, however, there are still challenges to overcome in future studies.

Targeting lncRNAs of colorectal cancers with natural products

Non-coding RNA (ncRNA) is one of the functional classes of RNA that has a regulatory role in various cellular processes, such as modulation of disease onset, progression, and prognosis. ncRNAs, such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), have been actively studied in recent years. The change in ncRNA levels is being actively studied in numerous human diseases, especially auto-immune disorders and cancers; however, targeting and regulating ncRNA with natural products to cure cancer has not been fully established. Recently many groups reported the relationship between ncRNA and natural products showing promising effects to serve as additional therapeutic approaches to cure cancers. This mini-review summarizes the aspects of lncRNAs related to cancer biology focusing on colorectal cancers that natural products can target.