Proteomics for early detection of colorectal cancer: recent updates

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.

Methods and biomarkers for early detection, prediction, and diagnosis of colorectal cancer

Colorectal cancer (CRC) is one of the most common digestive diseases worldwide. It has steadily ascended to the top three cancers in terms of incidence and mortality. The primary cause is the inability to diagnose it at an early stage. Therefore, early detection and diagnosis are essential for colorectal cancer prevention. Although there are now various methods for CRC early detection, in addition to recent developments in surgical and multimodal therapy, the poor prognosis and late detection of CRC still remain significant. Thus, it is important to investigate novel technologies and biomarkers to improve the sensitization and specification of CRC diagnosis. Here, we present some common methods and biomarkers for early detection and diagnosis of CRC, we hope this review will encourage the adoption of screening programs and the clinical use of these potential molecules as biomarkers for CRC early detection and prognosis.

Integrative Proteomic and Pharmacological Analysis of Colon Cancer Reveals the Classical Lipogenic Pathway with Prognostic and Therapeutic Opportunities

Despite recent advancements, the high mortality rate remains a concern in colon cancer (CAC). Identification of therapeutic markers could prove to be a great asset in CAC management. Multiple studies have reported hyperactivation of de novo lipogenesis (DNL), but its association with the pathology is unclear. This study aims to establish the importance as well as the prognostic and therapeutic potential of DNL in CAC. The key lipogenic enzymes fatty acid synthase along with ATP citrate lyase were quantified using an LC-MS/MS-based targeted proteomics approach in the samples along with the matched controls. The potential capacity of the proteins to distinguish between the tumor and controls was demonstrated using random forest-based class prediction analysis using the peptide intensities. Furthermore, in-depth proteomics of DNL inhibition in the CAC cell line revealed the significance of the pathway in proliferation and metastasis. DNL inhibition affected the major signaling pathways, including DNA repair, PI3K-AKT-mTOR pathway, membrane trafficking, proteasome, etc. The study revealed the upregulation of 26S proteasome machinery as a result of the treatment with subsequent induction of apoptosis. Again, in silico molecular docking-based drug repurposing was performed to find potential drug candidates. Furthermore, we have demonstrated that blocking DNL could be explored as a therapeutic option in CAC treatment.

Evaluating the predictive performance of gut microbiota for the early-stage colorectal cancer

BACKGROUND

Colorectal cancer (CRC) has been regarded as one of the most frequently diagnosed malignancies among the leading causes of cancer-related morbidity and mortality globally. Diagnosis of CRC at the early-stages of tumour might improve the survival rate of patients. The current study sought to determine the performance of fecal Fusobacterium nucleatum (F. nucleatum) and Streptococcus bovis (S. bovis) for timely predicting CRC.

METHODS

Through a case-control study, the fecal sample information of 83 individuals (38 females, 45 males) referring to a hospital in Tehran, Iran was used. All patients underwent a complete colonoscopy, regarded as a gold standard test. Bacterial species including S. bovis and F. nucleatum were measured by absolute quantitative real-time PCR. The Bayesian univariate and bivariate latent class models (LCMs) were applied to estimate the ability of the candidate bacterial markers in order to early detection of patients with CRC.

RESULTS

Bayesian univariate LCMs demonstrated that the sensitivities of S. bovis and F. nucleatum were estimated to be 86% [95% credible interval (CrI) 0.82-0.91] and 82% (95% CrI 0.75-0.88); while specificities were 84% (95% CrI 0.78-0.89) and 80% (95% CrI 0.73-0.87), respectively. Moreover, the area under the receiver operating characteristic curves (AUCs) were 0.88 (95% CrI 0.83-0.94) and 0.80 (95% CrI 0.73-0.85) respectively for S. bovis and F. nucleatum. Based on the Bayesian bivariate LCMs, the sensitivities of S. bovis and F. nucleatum were calculated as 93% (95% CrI 0.84-0.98) and 90% (95% CrI 0.85-0.97), the specificities were 88% (95% CrI 0.78-0.93) and 87% (95% CrI 0.79-0.94); and the AUCs were 0.91 (95% CrI 0.83-0.99) and 0.88(95% CrI 0.81-0.96), respectively.

CONCLUSIONS

Our data has identified that according to the Bayesian bivariate LCM, S. bovis and F. nucleatum had a more significant predictive accuracy compared with the univariate model. In summary, these intestinal bacteria have been highlighted as novel tools for early-stage CRC diagnosis.

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.

Prognostic value of protein biomarkers in liver transplantation: A systematic review

Liver transplantation is currently the preferred method for the treatment of advanced liver disease and early-stage hepatocellular carcinoma (HCC). Although advances in surgical techniques, immunosuppressive drugs and postoperative management have reduced the incidence of postoperative complications, how to effectively predict or diagnose postoperative complications earlier and reduce their incidence is still a clinical concern. We performed a comprehensive proteomics literature research to identified protein biomarkers in complications after liver transplantation. Seventeen studies met the inclusion criteria including ischemia reperfusion injury (IRI) (n = 4), acute rejection (AR) (n = 4), renal dysfunction (n = 4), HCC recurrence (n = 2), primary graft dysfunction (PGD) (n = 1), infection (n = 1), and liver fibrosis (n = 1). A total of 625 differentially expressed proteins (DEPs) have been reported between postoperative complications and controls, of which 63 have been validated by quantitative protein expression and 26 have been reported by at least two studies and showed consistently changes. The results of the bioinformation analysis show that the immune system, especially the innate immune system and cytokine signaling in immune system, is an important protein-mediated pathway that affects the prognosis of liver transplantation.

Identification of a prognostic signature in colorectal cancer using combinatorial algorithm-driven analysis

Colorectal carcinoma is one of the most common types of malignancy and a leading cause of cancer‐related death. Although clinicopathological parameters provide invaluable prognostic information, the accuracy of prognosis can be improved by using molecular biomarker signatures. Using a large dataset of immunohistochemistry‐based biomarkers (n = 66), this study has developed an effective methodology for identifying optimal biomarker combinations as a prognostic tool. Biomarkers were screened and assigned to related subsets before being analysed using an iterative algorithm customised for evaluating combinatorial interactions between biomarkers based on their combined statistical power. A signature consisting of six biomarkers was identified as the best combination in terms of prognostic power. The combination of biomarkers (STAT1, UCP1, p‐cofilin, LIMK2, FOXP3, and ICOS) was significantly associated with overall survival when computed as a linear variable (χ² = 53.183, p < 0.001) and as a cluster variable (χ² = 67.625, p < 0.001). This signature was also significantly independent of age, extramural vascular invasion, tumour stage, and lymph node metastasis (Wald = 32.898, p < 0.001). Assessment of the results in an external cohort showed that the signature was significantly associated with prognosis (χ² = 14.217, p = 0.007). This study developed and optimised an innovative discovery approach which could be adapted for the discovery of biomarkers and molecular interactions in a range of biological and clinical studies. Furthermore, this study identified a protein signature that can be utilised as an independent prognostic method and for potential therapeutic interventions.

Downregulating Long Non-coding RNAs CTBP1-AS2 Inhibits Colorectal Cancer Development by Modulating the miR-93-5p/TGF-β/SMAD2/3 Pathway

Background: Colorectal cancer (CRC), the most commonly diagnosed cancer in the world, has a high mortality rate. In recent decades, long non-coding RNAs (lncRNAs) have been proven to exert an important effect on CRC growth. However, the CTBP1-AS2 expression and function in CRC are largely unknown.

Materials and Methods: The CTBP1-AS2 and miR-93-5p expression in CRC and para-cancerous tissues was detected by reverse transcription-PCR. The expression of CTBP1-AS2, miR-93-5p and the transforming growth factor-beta (TGF-β)/small mothers against decapentaplegic 2/3 (SMAD2/3) pathway was selectively regulated to study the correlation between CTBP1-AS2 expression and prognosis of patients with CRC. CRC cell proliferation, apoptosis, and invasion were measured in vivo and in vitro. In addition, bioinformatics was applied to explore the targeting relationship between CTBP1-AS2 and miR-93-5p. The targeting binding sites between CTBP1-AS2 and miR-93-5p, as well as between miR-93-5p and TGF-β, were verified by the dual-luciferase reporter assay and the RNA immunoprecipitation experiment.

Results: Compared with normal para-cancerous tissues, CTBP1-AS2 was considerably overexpressed in CRC tissues and was closely associated with worse survival of patients with CRC. Functionally, gain and loss in experiments illustrated that CTBP1-AS2 accelerated CRC cell proliferation and invasion and inhibited cell apoptosis. Mechanistically, CTBP1-AS2 regulated the malignant phenotype of tumor cells through the TGF-β/SMAD2/3 pathway. Moreover, miR-93-5p, as an endogenous competitive RNA of CTBP1-AS2, attenuated the oncogenic effects mediated by CTBP1-AS2.

Conclusion: CTBP1-AS2 promotes the TGF-β/SMAD2/3 pathway activation by inhibiting miR-93-5p, thereby accelerating CRC development.

Colorectal cancer screening and diagnosis: omics-based technologies for development of a non-invasive blood-based method

Introduction: Colorectal cancer (CRC) is one of the most important health problems in the Western world. In order to reduce the burden of the disease, two strategies are proposed: screening and prompt detection in symptomatic patients. Although diagnosis and prevention are mainly based on colonoscopy, fecal hemoglobin detection has been widely implemented as a noninvasive strategy. Various studies aiming to discover blood-based biomarkers have recently emerged.Areas covered: The burgeoning omics field provides diverse high-throughput approaches for CRC blood-based biomarker discovery. In this review, we appraise the most robust and commonly used technologies within the fields of genomics, transcriptomics, epigenomics, proteomics, and metabolomics, together with their targeted validation approaches. We summarize the transference process from the discovery phase until clinical translation. Finally, we review the best candidate biomarkers and their potential clinical applicability.Expert opinion: Some available biomarkers are promising, especially in the field of epigenomics: DNA methylation and microRNA. Transference requires the joint collaboration of basic researchers, intellectual property experts, technology transfer officers and clinicians. Blood-based biomarkers will be selected not only based on their diagnostic accuracy and cost but also on their reliability, applicability to clinical analysis laboratories and their acceptance by the population.

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.

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.

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.

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.

Upregulation of STC2 in colorectal cancer and its clinicopathological significance

Background

Stanniocalcin 2 (STC2) is a glycoprotein hormone involved in many biological processes and a secretory protein that regulates malignant tumor progression. The aim of the present study was to further explore the clinicopathological significance and prognostic role of STC2 in colorectal cancer (CRC).

Methods

In this study, STC2 expression was first investigated in Gene Expression Omnibus and The Cancer Genome Atlas, and then validated with the data from our medical center. Univariate and multivariate analyses were performed to assess the association between prognostic factors and survival outcome.

Results

In Gene Expression Omnibus and The Cancer Genome Atlas databases, bioinformatics analysis confirmed that STC2 was significantly increased in CRC compared with that in normal tissues (P<0.01), and CRC patients with high STC2 expression had a shorter overall survival. By analyzing data from our medical center, the results also showed that STC2 expression of CRC tissues was higher than that in normal tissues, whether the transcriptional or protein levels. In the CRC tissues, high STC2 expression was significantly correlated with lymph node metastasis (P=0.047), distant metastasis (P=0.040), and advanced clinical stage (P=0.047). Moreover, Kaplan–Meier analyses indicated that high STC2 expression predicted a worse prognosis, and multivariate Cox regression analysis revealed that STC2 was an independent prognostic factor for overall survival (HR =1.976, 95% CI: 1.092–3.576, P=0.024) in patients with CRC.

Conclusion

Our results suggested that STC2 played an important role in CRC progression and prognosis, and could be a useful biomarker for survival prediction.

Hydrogen Sulfide-Activatable Second Near-Infrared Fluorescent Nanoassemblies for Targeted Photothermal Cancer Therapy

Near-infrared (NIR)-II fluorescence agents hold great promise for deep-tissue photothermal therapy (PTT) of cancers, which nevertheless remains restricted by the inherent nonspecificity and toxicity of PTT. In response to this challenge, we herein develop a hydrogen sulfide (H₂S)-activatable nanostructured photothermal agent (Nano-PT) for site-specific NIR-II fluorescence-guided PTT of colorectal cancer (CRC). Our in vivo studies reveal that this theranostic Nano-PT probe is specifically activated in H₂S-rich CRC tissues, whereas it is nonfunctional in normal tissues. Activation of Nano-PT not only emits NIR-II fluorescence with deeper tissue penetration ability than conventional fluorescent probes but also generates high NIR absorption resulting in efficient photothermal conversion under NIR laser irradiation. Importantly, we establish NIR-II imaging-guided PTT of CRC by applying the Nano-PT agent in tumor-bearing mice, which results in complete tumor regression with minimal nonspecific damages. Our studies thus shed light on the development of cancer biomarker-activated PTT for precision medicine.