Biomarkers in Colorectal Cancer: The Role of Translational Proteomics Research

Recent Advances in SAW Sensors for Detection of Cancer Biomarkers

Surface acoustic wave (SAW) sensor technology is a promising approach to diagnosing cancer through the detection of cancer biomarkers due to its high sensitivity, potential label-free operation, and fast response times, and, fundamentally, because it is a non-invasive technique in comparison with the current traditional diagnostic techniques for cancer. This review focuses on this application, and for this purpose, the recent literature on cancer biomarkers detected by this advanced technology has been compiled, including that on volatile organic compounds (VOCs) from exhaled breath and larger biomolecules such as proteins, DNA, and microRNAs in body fluids, which demonstrates its great versatility. The conventional techniques for cancer biomarker detection in biofluids, such as ELISA, PCR, SPR, and UV absorbance, exhibit limitations including high costs, slow response times, a reduced sensitivity, the need for specialized instrumentation, and the requirement for highly trained personnel. Different SAW sensor configurations are discussed with attention paid to their specific properties, wave propagation modes, and suitability for different environments. Detailed studies are reviewed, highlighting biomarkers for lung, colorectal, prostate, breast, and ovarian cancer diagnostics, as well as the detection of circulating tumor cells and cancerous cell growth. This review identifies current challenges, including optimizing sensitivity, addressing environmental interferences, and the need for clinical validation. Finally, future research directions are proposed, emphasizing the use of VOC biomarkers and the integration of SAW technology into hybrid systems and microfluidic platforms to enable the creation of scalable, non-invasive diagnostic tools for the detection of cancer in early stages, and, in this way, to minimize the morbidity and mortality associated with this disease.

The HOX Gene Family's Role as Prognostic and Diagnostic Biomarkers in Hematological and Solid Tumors

The HOX gene family encodes for regulatory transcription factors that play a crucial role in embryogenesis and differentiation of adult cells. This highly conserved family of genes consists of thirty-nine genes in humans that are located in four clusters, A-D, on different chromosomes. While early studies on the HOX gene family have been focused on embryonic development and its related disorders, research has shifted to examine aberrant expression of HOX genes and the subsequent implication in cancer prediction and progression. Due to their role of encoding master regulatory transcription factors, the abnormal expression of HOX genes has been shown to affect all stages of tumorigenesis and metastasis. This review highlights the novel role of the HOX family's clinical relevance as both prognostic and diagnostic biomarkers in hematological and solid tumors.

Expression-Dependent Tumor Pretargeting via Engineered Avidity

Selective delivery of therapeutic modalities to tumor cells via binding of tumor-selective cell-surface biomarkers has empowered substantial advances in cancer treatment. Yet, tumor cells generally lack a truly specific biomarker that is present in high density on tumor tissue while being completely absent from healthy tissue. Rather, low but nonzero expression in healthy tissues results in on-target, off-tumor activity with detrimental side effects that constrain the therapeutic window or prevent use altogether. Advanced technologies to enhance the selectivity for tumor targeting are sorely needed. We have engineered a binding platform that is quantitatively dependent upon expression levels, via avidity-driven specificity, rather than binarily reliant on the presence or absence of a biomarker. We systematically varied monomeric binding affinity by engineering affibodies to target carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) and folate receptor 1 (FolR1). Two identical affibody ligands were tethered, with varying polypeptide linker lengths, to a nanobody that binds Alfa peptide to create a bispecific, trivalent protein for use in pretargeted radioligand therapy. Expression-dependent targeting was achieved in both systems: with 110 nM monomeric affinity to CEACAM5 with a two-amino-acid linker or with 250 nM monomeric affinity for FolR1 and a 10 amino acid linker. The latter bispecific, trivalent achieved over 25-fold differentiation between FolR1high and FolR1low cells in a mixed culture. Similar selectivity was achieved in a size-efficient bivalent molecule lacking a central nanobody. Moreover, the avid bivalent affibody molecule exhibited minimal inhibition by soluble antigen, whereas high-affinity bivalent antibody was inhibited by 97 ± 2%, which is indicative of serum inhibition of shed antigen. This work advances design principles for achieving expression-dependent tumor targeting via low-affinity, high-avidity ligands.

Identification of miR-20a as a Diagnostic and Prognostic Biomarker in Colorectal Cancer: MicroRNA Sequencing and Machine Learning Analysis

INTRODUCTION

The differential expression of miRNAs, a key regulator in many cell signaling pathways, has been studied in various malignancies and may have an important role in cancer progression, including colorectal cancer (CRC).

METHODS

The present study used machine learning and gene interaction study tools to explore the prognostic and diagnostic value of miRNAs in CRC. Integrative analysis of 353 CRC samples and normal tissue data was obtained from the TCGA database and further analyzed by R packages to define the deferentially expressed miRNAs (DEMs). Furthermore, machine learning and Kaplan Meier survival analysis helped better specify the significant prognostic value of miRNAs. A combination of online databases was then used to evaluate the interactions between target genes, their molecular pathways, and the correlation between the DEMs.

RESULTS

The results indicated that miR-19b and miR-20a have a significant prognostic role and are associated with CRC progression. The ROC curve analysis discovered that miR-20a alone and combined with other miRNAs, including hsa-mir-21 and hsa-mir-542, are diagnostic biomarkers in CRC. In addition, 12 genes, including NTRK2, CDC42, EGFR, AGO2, PRKCA, HSP90AA1, TLR4, IGF1, ESR1, SMAD2, SMAD4, and NEDD4L, were found to be the highest score targets for these miRNAs. Pathway analysis identified the two correlated tyrosine kinase and MAPK signaling pathways with the key interaction genes, i.e., EGFR, CDC42, and HSP90AA1.

CONCLUSION

To better define the role of these miRNAs, the ceRNA network, including lncRNAs, was also prepared. In conclusion, the combination of R data analysis and machine learning provides a robust approach to resolving complicated interactions between miRNAs and their targets.

Neoadjuvant immunotherapy for dMMR and pMMR colorectal cancers: therapeutic strategies and putative biomarkers of response

Approximately 15% of locally advanced colorectal cancers (CRC) have DNA mismatch repair deficiency (dMMR), resulting in high microsatellite instability and a high tumour mutational burden. These cancers are frequently sensitive to therapy with immune-checkpoint inhibitors (ICIs) in the metastatic setting. This sensitivity seems to be even more pronounced in locally advanced disease, and organ preservation has become a realistic aim in ongoing clinical trials involving patients with dMMR rectal cancer. By contrast, metastatic CRCs with proficient DNA mismatch repair (pMMR) are generally resistant to ICIs, although a proportion of locally advanced pMMR tumours seem to have a high degree of sensitivity to ICIs. In this Review, we describe the current and emerging clinical evidence supporting the use of neoadjuvant ICIs in patients with dMMR and pMMR CRC, and the potential advantages (based on a biological rationale) of such an approach. We discuss how neoadjuvant 'window-of-opportunity' trials are being leveraged to progress biomarker discovery and we provide an overview of potential predictive biomarkers of response to ICIs, exploring the challenges faced when evaluating such biomarkers in biopsy-derived samples. Lastly, we describe how these discoveries might be used to drive a rational approach to trialling novel immunotherapeutic strategies in patients with pMMR CRC, with the ultimate aim of disease eradication and the generation of long-term immunosurveillance.

The implicated role of GDF15 in gastrointestinal cancer

BACKGROUND

Growth differentiation factor 15 (GDF15), a stress-responsive cytokine from transforming growth factor superfamily, is highly expressed in mammalian tissues, including pancreas, stomach and intestine under pathological conditions. In particular, elevated levels of GDF15 might play an important role in the development and progression of various gastrointestinal cancers (GCs), suggesting its potential as a promising target for disease prediction and treatment.

METHODS

In this review, systematic reviews addressing the role of GDF15 in GCs were updated, along with the latest clinical trials focussing on the GDF15-associated digestive malignancies.

RESULTS

The multiple cellular pathways through which GDF15 is involved in the regulation of physiological and pathological conditions were first summarized. Then, GDF15 was also established as a valuable clinical index, functioning as a predictive marker in diverse GCs. Notably, latest clinical treatments targeting GDF15 were also highlighted, demonstrating its promising potential in mitigating and curing digestive malignancies.

CONCLUSIONS

This review unveils the pivotal roles of GDF15 and its potential as a promising target in the pathogenesis of GCs, which may provide insightful directions for future investigations.

TYK2 Protein Expression and Its Potential as a Tissue-Based Biomarker for the Diagnosis of Colorectal Cancer

BACKGROUND/OBJECTIVES

The aim of this study was to examine the expression of TYK2 in colorectal cancer (CRC) and to determine the potential diagnostic and prognostic significance of this kinase.

METHODS

Digital image analysis was performed to assess immunohistochemical TYK2 reactivity.

RESULTS

There were significant differences for all positive pixels between CRC and normal colonic mucosa, with higher TYK2 expression levels observed in surgical margins than in adenocarcinomas (p = 0.0004). Paired t tests showed elevated immunoreactivity for overall TYK2 expression in matched pairs of CRC with adjacent surgical margins (p < 0.0001). Higher percentages of weak (p < 0.0001) and strong pixels (p = 0.0260) were detected in normal colonic mucosa than in cancer tissues. To distinguish cancer from normal intestinal mucosa, the following cutoffs for the TYK2 immune score were found: 29.5% for all cases and 31% for matched pairs. Tumor budding (Bd) was negatively correlated with the percentage of strong pixels for TYK2 (ρ = -0.270, p = 0.0096). The percentage of strong pixels was significantly elevated for the T parameter (p = 0.0428). There was a positive correlation between the number of involved lymph nodes and weak pixels (ρ = 0.239, p = 0.0242). Immunofluorescence staining showed significantly higher signal intensities in colonic mucosa than in CRC. The protein level of TYK2 was significantly higher in controls than in cancer tissues. TEM imaging showed lower levels of TYK2 in cancer than in ulcerative colitis.

CONCLUSIONS

TYK2 protein expression may bring diagnostic value in patients diagnosed with CRC.

Screening differentially expressed proteins to distinguish thymoma (B1 and B3) from thymic cysts based on tandem mass tag (TMT) technology

The therapeutic approach to thymic cysts remains a subject of controversy. Predicted biomarkers for identifying thymic cysts and thymoma (THYM) are crucial. In this research, patients diagnosed with thymic cysts (MTC, n = 6) and thymoma (B1, n = 6; B3, n = 6) were enrolled. Proteins of superior quality were subjected to TMT labeling and UPLC-MS, and differentially expressed proteins (DEPs) were identified. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interactive network analyses were applied to the DEPs. Some key differentially expressed genes(DEGs) were corroborated through GEPIA 32. The pan-cancer expression levels of key DEGs remarkably linked with prognosis were determined utilizing The University of ALabama at Birmingham CANcer data analysis Portal (UALCAN). Eventually, 49 DEPs were identified in the B1 vs. MTC comparison (17 upregulated and 32 downregulated), 27 in the B3 vs. MTC comparison (8 upregulated and 19 downregulated), and 38 in the B3 vs. B1 comparison (9 upregulated and 29 downregulated). IL13RA1 (down), galectin-3 binding protein (LGALS3BP)(up), PRCSH (down), C3 (down), MXRA5 (down), TNN (down), CFHR1 (down), SUN3 (down) were jointly altered in both B1 vs. NZ and B3 vs. NZ. GEPIA validated that LGALS3BP was significantly upregulated in thymoma patients. In conclusion, LGALS3BP might be an essential biomarker to identify thymoma from the thymic cyst.

Some Glycoproteins Expressed on the Surface of Immune Cells and Cytokine Plasma Levels Can Be Used as Potential Biomarkers in Patients with Colorectal Cancer

Colorectal cancer (CRC) is a leading cause of mortality worldwide. Its incidence holds a major position among the most common life-threatening diseases. Hence, the early identification and precise characterization of disease activity based on proper biomarkers are of utmost importance for therapeutic strategy and patient survival. The identification of new biomarkers for colorectal cancer or disease-specific levels/combinations of biomarkers will significantly contribute to precise diagnosis and improved personalized treatment of patients. Therefore, the present study aims to identify colorectal cancer-specific immunological biomarkers. The plasma levels of several cytokines (interleukin-1β /IL-1β/, IL-2, IL-4, IL-10, IL-12, IL-15, TGFβ and IFNγ) of 20 patients with colorectal cancer and 21 healthy individuals were determined by ELISA. The expression of several types of glycoproteins on the surface of peripheral blood leukocytes isolated from CRC patients and healthy volunteers was evaluated by flow cytometry. Correlations between cytokine levels and cell surface glycoprotein expression were analyzed. The obtained results demonstrated significantly elevated levels of CD80, CD86, CD279 and CD274 expressing leukocyte populations in the cancer patient group, while the numbers of NK cells and CD8- and CD25-positive cells were decreased. Based on these data and the correlations with cytokine levels, it can be concluded that CD25, CD80, CD86, CD274 and CD279 glycoproteins combined with specific plasma levels of IL-1β, IL-2, IL-15 and TGFβ could represent potential biomarkers for colorectal cancer.

Personalised medicine based on host genetics and microbiota applied to colorectal cancer

Colorectal cancer (CRC) ranks second in incidence and third in cancer mortality worldwide. This situation, together with the understanding of the heterogeneity of the disease, has highlighted the need to develop a more individualised approach to its prevention, diagnosis and treatment through personalised medicine. This approach aims to stratify patients according to risk, predict disease progression and determine the most appropriate treatment. It is essential to identify patients who may respond adequately to treatment and those who may be resistant to treatment to avoid unnecessary therapies and minimise adverse side effects. Current research is focused on identifying biomarkers such as specific mutated genes, the type of mutations and molecular profiles critical for the individualisation of CRC diagnosis, prognosis and treatment guidance. In addition, the study of the intestinal microbiota as biomarkers is being incorporated due to the growing scientific evidence supporting its influence on this disease. This article comprehensively addresses the use of current and emerging diagnostic, prognostic and predictive biomarkers in precision medicine against CRC. The effects of host genetics and gut microbiota composition on new approaches to treating this disease are discussed. How the gut microbiota could mitigate the side effects of treatment is reviewed. In addition, strategies to modulate the gut microbiota, such as dietary interventions, antibiotics, and transplantation of faecal microbiota and phages, are discussed to improve CRC prevention and treatment. These findings provide a solid foundation for future research and improving the care of CRC patients.

The Prognostic and Predictive Utility of CDX2 in Colorectal Cancer

Caudal type homeobox transcription factor 2 (CDX2) is a gastrointestinal cancer biomarker that regulates epithelial development and differentiation. Absence or low levels of CDX2 have been associated with poor prognosis and proposed as a chemotherapy response predictor. Tumour tissue samples from 668 patients with stage I-IV colorectal cancer were stained for CDX2 and stratified into two subgroups according to expression levels. Statistical tests were used to evaluate CDX2's relationship with survival and chemotherapy response. Of 646 samples successfully stained, 51 (7.9%) had low CDX2 levels, and 595 (92.1%) had high levels. Low CDX2 staining was associated with poor differentiation and the presence of lymphovascular or perineural invasion and was more common in colon and right-sided tumours. Overall survival (p < 0.001) and disease-free survival (p = 0.009) were reduced in patients with low CDX2 expression. Multivariable analysis validated CDX2 as an independent poor prognostic factor after excluding confounding variables. There was no statistically significant improvement in survival with adjuvant chemotherapy in stage II colon cancer (p = 0.11). In the rectal cohort, there was no relationship between CDX2 levels and therapy response. While confirming the prognostic utility of CDX2 in colorectal cancer, our study highlights that larger studies are required to confirm its utility as a predictive chemotherapy biomarker, especially in left-sided and rectal cancers.

Comparison between 16S rRNA and shotgun sequencing in colorectal cancer, advanced colorectal lesions, and healthy human gut microbiota

BACKGROUND

Gut dysbiosis has been associated with colorectal cancer (CRC), the third most prevalent cancer in the world. This study compares microbiota taxonomic and abundance results obtained by 16S rRNA gene sequencing (16S) and whole shotgun metagenomic sequencing to investigate their reliability for bacteria profiling. The experimental design included 156 human stool samples from healthy controls, advanced (high-risk) colorectal lesion patients (HRL), and CRC cases, with each sample sequenced using both 16S and shotgun methods. We thoroughly compared both sequencing technologies at the species, genus, and family annotation levels, the abundance differences in these taxa, sparsity, alpha and beta diversities, ability to train prediction models, and the similarity of the microbial signature derived from these models.

RESULTS

As expected, the results showed that 16S detects only part of the gut microbiota community revealed by shotgun, although some genera were only profiled by 16S. The 16S abundance data was sparser and exhibited lower alpha diversity. In lower taxonomic ranks, shotgun and 16S highly differed, partially due to a disagreement in reference databases. When considering only shared taxa, the abundance was positively correlated between the two strategies. We also found a moderate correlation between the shotgun and 16S alpha-diversity measures, as well as their PCoAs. Regarding the machine learning models, only some of the shotgun models showed some degree of predictive power in an independent test set, but we could not demonstrate a clear superiority of one technology over the other. Microbial signatures from both sequencing techniques revealed taxa previously associated with CRC development, e.g., Parvimonas micra.

CONCLUSIONS

Shotgun and 16S sequencing provide two different lenses to examine microbial communities. While we have demonstrated that they can unravel common patterns (including microbial signatures), shotgun often gives a more detailed snapshot than 16S, both in depth and breadth. Instead, 16S will tend to show only part of the picture, giving greater weight to dominant bacteria in a sample. Therefore, we recommend choosing one or another sequencing technique before launching a study. Specifically, shotgun sequencing is preferred for stool microbiome samples and in-depth analyses, while 16S is more suitable for tissue samples and studies with targeted aims.

Decoding immune-related gene-signatures in colorectal neoplasia

Background

Colorectal cancer (CRC) is a significant health issue, with notable incidence rates in Norway. The immune response plays a dual role in CRC, offering both protective effects and promoting tumor growth. This research aims to provide a detailed screening of immune-related genes and identify specific genes in CRC and adenomatous polyps within the Norwegian population, potentially serving as detection biomarkers.

Methods

The study involved 69 patients (228 biopsies) undergoing colonoscopy, divided into CRC, adenomatous polyps, and control groups. We examined the expression of 579 immune genes through nCounter analysis emphasizing differential expression in tumor versus adjacent non-tumorous tissue and performed quantitative reverse transcription polymerase chain reaction (RT-qPCR) across patient categories.

Results

Key findings include the elevated expression of CXCL1, CXCL2, IL1B, IL6, CXCL8 (IL8), PTGS2, and SPP1 in CRC tissues. Additionally, CXCL1, CXCL2, IL6, CXCL8, and PTGS2 showed significant expression changes in adenomatous polyps, suggesting their early involvement in carcinogenesis.

Conclusions

This study uncovers a distinctive immunological signature in colorectal neoplasia among Norwegians, highlighting CXCL1, CXCL2, IL1B, IL6, CXCL8, PTGS2, and SPP1 as potential CRC biomarkers. These findings warrant further research to confirm their role and explore their utility in non-invasive screening strategies.

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

Background

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

Objective and design

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

Results

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

Conclusion

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

Use of tryptic peptide MALDI mass spectrometry imaging to identify the spatial proteomic landscape of colorectal cancer liver metastases

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths worldwide. CRC liver metastases (CRLM) are often resistant to conventional treatments, with high rates of recurrence. Therefore, it is crucial to identify biomarkers for CRLM patients that predict cancer progression. This study utilised matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to spatially map the CRLM tumour proteome. CRLM tissue microarrays (TMAs) of 84 patients were analysed using tryptic peptide MALDI-MSI to spatially monitor peptide abundances across CRLM tissues. Abundance of peptides was compared between tumour vs stroma, male vs female and across three groups of patients based on overall survival (0-3 years, 4-6 years, and 7+ years). Peptides were then characterised and matched using LC-MS/MS. A total of 471 potential peptides were identified by MALDI-MSI. Our results show that two unidentified m/z values (1589.876 and 1092.727) had significantly higher intensities in tumours compared to stroma. Ten m/z values were identified to have correlation with biological sex. Survival analysis identified three peptides (Histone H4, Haemoglobin subunit alpha, and Inosine-5'-monophosphate dehydrogenase 2) and two unidentified m/z values (1305.840 and 1661.060) that were significantly higher in patients with shorter survival (0-3 years relative to 4-6 years and 7+ years). This is the first study using MALDI-MSI, combined with LC-MS/MS, on a large cohort of CRLM patients to identify the spatial proteome in this malignancy. Further, we identify several protein candidates that may be suitable for drug targeting or for future prognostic biomarker development.

Biomarker Identification through Proteomics in Colorectal Cancer

Colorectal cancer (CRC) is a devastating disease that ranks third in diagnosis and as the second leading cause of cancer-related deaths. The early detection of CRC has been shown to be the most effective strategy to improve treatment outcomes and patient survival. Therefore, current lines of research focus on the development of reliable diagnostic tools. Targeted therapies, in combination with standard chemotherapy and immune checkpoint inhibitors, have emerged as promising treatment protocols in CRC. However, their effectiveness is linked to the molecular characteristics of each patient. The importance of discovering biomarkers that help predict response to therapies and assess prognosis is evident as they allow for a fundamental step towards personalized care and successful treatments. Among the ongoing efforts to identify them, mass spectrometry-based translational proteomics presents itself as a unique opportunity as it enables the discovery and application of protein biomarkers that may revolutionize the early detection and treatment of CRC. Our objective is to show the most recent studies focused on the identification of CRC-related protein markers, as well as to provide an updated view of advances in the field of proteomics and cancer.

Mass Spectrometry-Based Pipeline for Identifying RNA Modifications Involved in a Functional Process: Application to Cancer Cell Adaptation

Cancer onset and progression are known to be regulated by genetic and epigenetic events, including RNA modifications (a.k.a. epitranscriptomics). So far, more than 150 chemical modifications have been described in all RNA subtypes, including messenger, ribosomal, and transfer RNAs. RNA modifications and their regulators are known to be implicated in all steps of post-transcriptional regulation. The dysregulation of this complex yet delicate balance can contribute to disease evolution, particularly in the context of carcinogenesis, where cells are subjected to various stresses. We sought to discover RNA modifications involved in cancer cell adaptation to inhospitable environments, a peculiar feature of cancer stem cells (CSCs). We were particularly interested in the RNA marks that help the adaptation of cancer cells to suspension culture, which is often used as a surrogate to evaluate the tumorigenic potential. For this purpose, we designed an experimental pipeline consisting of four steps: (1) cell culture in different growth conditions to favor CSC survival; (2) simultaneous RNA subtype (mRNA, rRNA, tRNA) enrichment and RNA hydrolysis; (3) the multiplex analysis of nucleosides by LC-MS/MS followed by statistical/bioinformatic analysis; and (4) the functional validation of identified RNA marks. This study demonstrates that the RNA modification landscape evolves along with the cancer cell phenotype under growth constraints. Remarkably, we discovered a short epitranscriptomic signature, conserved across colorectal cancer cell lines and associated with enrichment in CSCs. Functional tests confirmed the importance of selected marks in the process of adaptation to suspension culture, confirming the validity of our approach and opening up interesting prospects in the field.

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.

A Systems Biology Approach Unveils a Critical Role of DPP4 in Upper Gastrointestinal Cancer Patient Outcomes

Gastrointestinal (GI) cancers comprise of cancers that affect the digestive system and its accessory organs. The late detection and poor prognosis of GI cancer emphasizes the importance of identifying reliable and precise biomarkers for early diagnosis and prediction of prognosis. The membrane-bound glycoprotein dipeptidyl-peptidase 4 (DPP4), also known as CD26, is ubiquitously expressed and has a wide spectrum of biological roles. The role of DPP4/CD26 in tumor progression in different types of cancers remains elusive. However, the link between DPP4 and tumor-infiltrating cells, as well as its prognostic significance in malignancies, still require further investigation. This study was intended to elucidate the correlation of DPP4 expression and survival along with prognosis, followed by its associated enriched molecular pathways and immune cell marker levels in upper GI cancers. Results demonstrated a strong correlation between increased DPP4 expression and a worse prognosis in esophageal and gastric cancer and the co-expressed common genes with DPP4 were associated with crucial molecular pathways involved in tumorigenesis. Additionally, DPP4 was shown to be significantly linked to several immune infiltrating cell marker genes, including Macrophages (M1, M2 and Tumor Associated Macrophages), neutrophils, Treg, T-cell exhaustion, Th1 and Th2. Overall, our findings suggest that DPP4 may serve as a substantial prognostic biomarker, a possible therapeutic target, as well as it can play a critical role in the regulation of immune cell invasion in patients with gastroesophageal (esophageal, gastroesophageal junction and gastric) cancer. KEY WORDS: DPP4, integrated analysis, GI cancer, gastroesophageal cancer, gastroesophageal junction, prognosis.

Translational research of new developments in targeted therapy of colorectal cancer

A severe global health concern is the rising incidence and mortality rate of colorectal cancer (CRC). Chemotherapy, which is typically used to treat CRC, is known to have limited specificity and can have noticeable side effects. A paradigm shift in cancer treatment has been brought about by the development of targeted therapies, which has led to the appearance of pharmacological agents with improved efficacy and decreased toxicity. Epidermal growth factor receptor (EGFR), vascular endothelial growth factor (VEGF), human epidermal growth factor receptor 2 (HER2), and BRAF are among the molecular targets covered in this review that are used in targeted therapy for CRC. The current discussion also covers advancements in targeted therapeutic approaches, such as antibody-drug conjugates, immune checkpoint inhibitors, and chimeric antigen receptor (CAR) T-cell therapy. A review of the clinical trials and application of these particular therapies in treating CRC is also done. Despite the improvements in targeted therapy for CRC, problems such as drug resistance and patient selection remain to be solved. Despite this, targeted therapies have offered fresh possibilities for identifying and treating CRC, paving the way for the development of personalized medicine and extending the life expectancy and general well-being of CRC patients.

The cubosome-based nanoplatforms in cancer therapy: Seeking new paradigms for cancer theranostics

Lyotropic liquid crystals are self-assembled, non-lamellar, and mesophase nanostructured materials that have garnered significant attention as drug carriers. Cubosomes, a subtype of lyotropic liquid crystalline nanoparticles, possess three-dimensional structures that display bicontinuous cubic liquid-crystalline patterns. These patterns are formed through the self-organization of unsaturated monoglycerides (amphphilic lipids such as glyceryl monooleate or phytantriol), followed by stabilization using steric polymers (poloxamers). Owing to their bicontinuous structure and steric polymer-based stabilization, cubosomes have been demonstrated to possess greater entrapment efficiency for hydrophobic drugs compared to liposomes, while also exhibiting high stability. In the past decade, there has been significant interest in cubosomes due to their ability to deliver therapeutic and contrast agents for cancer treatment and imaging with minimal side effects, establishing them as a safe and effective approach. Concerning these advantages, the present review elaborates on the general aspects, composition, and preparation techniques of cubosomes, followed by explanations of their mechanisms of drug loading and release patterns. Furthermore, the review provides meticulous discussions on the use of cubosomes in the treatment and imaging of various types of cancer, culminating in the enumeration of patents related to cubosome-based drug delivery systems.

Current advances in detecting genetic and epigenetic biomarkers of colorectal cancer

Colorectal carcinoma (CRC) is the third most common cancer in terms of diagnosis and the second in terms of mortality. Recent studies have shown that various proteins, extracellular vesicles (i.e., exosomes), specific genetic variants, gene transcripts, cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and altered epigenetic patterns, can be used to detect, and assess the prognosis of CRC. Over the last decade, a plethora of conventional methodologies (e.g., polymerase chain reaction [PCR], direct sequencing, enzyme-linked immunosorbent assay [ELISA], microarray, in situ hybridization) as well as advanced analytical methodologies (e.g., microfluidics, electrochemical biosensors, surface-enhanced Raman spectroscopy [SERS]) have been developed for analyzing genetic and epigenetic biomarkers using both optical and non-optical tools. Despite these methodologies, no gold standard detection method has yet been implemented that can analyze CRC with high specificity and sensitivity in an inexpensive, simple, and time-efficient manner. Moreover, until now, no study has critically reviewed the advantages and limitations of these methodologies. Here, an overview of the most used genetic and epigenetic biomarkers for CRC and their detection methods are discussed. Furthermore, a summary of the major biological, technical, and clinical challenges and advantages/limitations of existing techniques is also presented.

Promoter methylation of matrix metallopeptidase 9 in peripheral blood mononuclear cells: A novel biomarker in a promising source for noninvasive colorectal cancer diagnosis

OBJECTIVES

Colorectal cancer (CRC) has been described as a "silent disease," which can be readily treated in most patients when discovered in its early stages. Considering the limitations of the current conventional tests for the diagnosis of CRC, researchers strive to find noninvasive and more valid biomarkers for the early detection of CRC. It has been shown that tumor-specific methylation patterns can also be identified in peripheral blood mononuclear cells (PBMCs) and are reliable sources of methylation analysis for CRC screening.

MATERIALS AND METHODS

We carried out a quantitative methylation analysis on matrix metallopeptidase 9 (MMP9) promoter using methylation quantification endonuclease-resistant DNA (MethyQESD) method. A total of 70 patients with CRC and 70 normal controls were enrolled in this study for methylation analysis in the PBMCs.

RESULTS

Our findings discovered a considerable hypermethylation of MMP9 promoter in CRC patients compared with healthy controls (mean: 47.30% and 20.31%, respectively; P > 0.001). The sensitivity and specificity of the MMP9 gene for the diagnosis of CRC were 88% and 78%, respectively. In addition, on the basis of area under the curve values, the diagnostic power of the MMP9 gene was 0.976 (P < 0.001). Moreover, our analysis established that MMP9 methylation was significantly different between the different stages of CRC (P: 0.034).

CONCLUSIONS

Our results showed that MMP9 promoter methylation in PBMCs can be used as an outstanding biomarker for CRC diagnosis. Besides, we confirmed that PBMCs are reliable sources of methylation analysis for CRC screening and MethyQESD is an accurate and fast method for quantitative methylation analyses.

Ibero-American Consensus Review and Incorporation of New Biomarkers for Clinical Practice in Colorectal Cancer

Advances in genomic technologies have significantly improved the management of colorectal cancer (CRC). Several biomarkers have been identified in CRC that enable personalization in the use of biologic agents that have shown to enhance the clinical outcomes of patients. However, technologies used for their determination generate massive amounts of information that can be difficult for the clinician to interpret and use adequately. Through several discussion meetings, a group of oncology experts from Spain and several Latin American countries reviewed the latest literature to provide practical recommendations on the determination of biomarkers in CRC based on their clinical experience. The article also describes the importance of looking for additional prognostic biomarkers and the use of histopathology to establish an adequate molecular classification. Present and future of immunotherapy biomarkers in CRC patients are also discussed, together with several techniques for marker determination, including liquid biopsy, next-generation sequencing (NGS), polymerase chain reaction (PCR), and fecal immunohistochemical tests. Finally, the role of Molecular Tumor Boards in the diagnosis and treatment of CRC is described. All of this information will allow us to highlight the importance of biomarker determination in CRC.

KRAS mutations and their associations with clinicopathological features and survival in Vietnamese non‑polyp colon cancer patients

The aim of the present study was to determine Kirsten Ras sarcoma virus (KRAS) mutations and the associations of KRAS mutations with clinicopathological features and treatment outcomes in Vietnamese non-polyp colon cancer (NPCC) patients. The data in the present study covered 194 patients with non-polyp colon cancers at stages II or III, according to the 8th edition of the American Joint Committee on Cancer staging system, in northern Vietnam from January 2016 to August 2020. All patients underwent radical surgery and adjuvant therapy with FOLFOX4 or XELOX. Subsequently, the recruited patients were followed-up with scheduled hospital exams for diagnosing recurrence. Genomic DNA samples were prepared from dissected tumors and specific sequences of the KRAS gene were amplified by polymerase chain reactions (PCR). The mutations at codons 12, 13, 59, 60, 61, 117 and 146 of the gene were determined. Possible associations of the KRAS mutations with clinicopathological properties and the survival of patients were analysed. The KRAS mutation rate was 47.9% in Vietnamese patients with NPCC, of those, mutations in exon 2 accounted for 91.4% of all detected mutations. The mutated-KRAS patients exhibited a significantly higher rate of anemia. Moreover, the KRAS mutation rate was higher in females (57.1%) than in males (39.8%). The KRAS mutation rate was also higher in patients with right colon cancers. Furthermore, KRAS mutations were an independent prognosis for poor disease-free survival (DFS) and overall survival (OS) in stage II patients. Among left-sided colon patients, mutated KRAS was a significant predictive factor for poor DFS but not for OS. The present study revealed a very high mutation rate of KRAS in Vietnamese patients with NPCC. The data of the present study indicated that the mutation status was associated with female patients and right-sided tumors. The KRAS mutations were a negative factor for the survival of patients with stage II NPCC and patients with left-sided colon cancer.

Fluorescent imaging using novel conjugated polymeric nanoparticles-affimer probes in complex in vitro models of colorectal cancer

We developed a carcinoembryonic antigen (CEA) conjugated polymer nanoparticle (CPN510-CEA-Af) probe to target CEA-expressing CRC cells in vitro. Its efficacy was evaluated in 2D and 3D cultures of LS174T, LoVo, and HT29 CRC cell lines. CPN510-CEA-Af produced greater fluorescent signal intensity than unconjugated particles in both 2D cells and 3D spheriods, indicating its potential as a probe for image-guided colorectal cancer surgery.

Recent Developments in Diagnostic and Prognostic Biomarkers for Colorectal Cancer: A Narrative Review

BACKGROUND

Colorectal cancer was reported as the second most common cause of cancer death worldwide, in the year 2020. This disease is an important public health problem considering its high incidence and mortality rates.

SUMMARY

The molecular events that lead to colorectal cancer include genetic and epigenetic abnormalities. Some of the most important molecular mechanisms involved include the APC/β-catenin pathway, the microsatellite pathway, and the CpG island hypermethylation. Evidence in the literature supports a role for the microbiota in the development of colon carcinogenesis, and specific microbes may contribute to or prevent carcinogenesis. Progress in prevention, screening, and management has improved the overall prognosis of the disease when diagnosed at an early stage; yet metastatic disease continues to have a poor long-term prognosis due to late-stage diagnosis and treatment failure. Biomarkers are a key tool for early detection and prognosis and aim to reduce morbidity and mortality associated with colorectal cancer. The main focus of this narrative review is to provide an update on the recent development of diagnostic and prognostic biomarkers in stool, blood, and tumor tissue samples.

KEY MESSAGES

The review focuses on recent investigations in microRNAs, cadherins, Piwi-interacting RNAs, circulating cell-free DNA, and microbiome biomarkers which can be applied for the diagnosis and prognosis of colorectal cancer.

Association between Ki67 expression and therapeutic outcome in colon cancer

Ki67 is a commonly used proliferation marker in pathological diagnosis of tumors; however, its prognostic value in colon cancer is controversial. A total of 312 consecutive patients with stage I-III colon cancer who underwent radical surgery with or without adjuvant chemotherapy were included in the present study. Ki67 expression was assessed using immunohistochemistry and was classified according to 25% intervals. The association between Ki67 expression and clinicopathological features was analyzed. Long-term postoperative survival, including disease-free survival (DFS) and overall survival, was calculated, and its association with Ki67 was analyzed. High Ki67 expression (>50%) was associated with improved DFS in patients treated with adjuvant chemotherapy postoperatively, but not in patients who received surgery alone (P=0.138). Ki67 expression was significantly associated with histological differentiation of the tumor (P=0.01), while it was not associated with other clinicopathological factors. Multivariate analysis demonstrated that pathological T and N stage were independent prognostic factors. In conclusion, high Ki67 expression was associated with a good therapeutic outcome in patients receiving adjuvant chemotherapy in colon cancer.

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.

A protein microarray-based serum proteomic investigation reveals distinct autoantibody signature in colorectal cancer

PURPOSE

Colorectal cancer (CRC) has been reported as the second leading cause of cancer death worldwide. The 5-year annual survival is around 50%, mainly due to late diagnosis, striking necessity for early detection. This study aims to identify autoantibody in patients' sera for early screening of cancer.

EXPERIMENTAL DESIGN

The study used a high-density human proteome array with approximately 17,000 recombinant proteins. Screening of sera from healthy individuals, CRC from Indian origin, and CRC from middle-east Asia origin were performed. Bio-statistical analysis was performed to identify significant autoantibodies altered. Pathway analysis was performed to explore the underlying mechanism of the disease.

RESULTS

The comprehensive proteomic analysis revealed dysregulation of 15 panels of proteins including CORO7, KCNAB1, WRAP53, NDUFS6, KRT30, and COLGALT2. Further biological pathway analysis for the top dysregulated autoantigenic proteins revealed perturbation in important biological pathways such as ECM degradation and cytoskeletal remodeling etc. CONCLUSIONS AND CLINICAL RELEVANCE: The generation of an autoimmune response against cancer-linked pathways could be linked to the screening of the disease. The process of immune surveillance can be detected at an early stage of cancer. Moreover, AAbs can be easily extracted from blood serum through the least invasive test for disease screening.

Is serum thymidine kinase 1 a prognostic biomarker in primary tumor location of colorectal carcinomas?

AIM

To assess whether serum thymidine kinase 1 (STK1p), CEA and CA19.9 can be used as prognostic biomarkers in the primary tumor location (PTL) of colorectal carcinoma (CRC). Additional clinical factors of TNM stage, pathological grade, age and sex were also included.

METHODS

STK1p was determined by an ECL-dot-blot assay, and CEA/CA19.9 was determined by an automatic electrochemiluminescence analyzer in a retrospective presurgery of right-colon carcinoma (R-CC, n = 90), left-colon carcinoma (L-CC, n = 128) and rectal carcinoma (RC, n = 270). Prognostic factors were evaluated by COX and overall survival (OS).

RESULTS

The multivariate-COX and OS in relation to the prognostic factors of PTL in CRC were different and complex. An elevated STK1p value was significantly associated with poor OS in RC (P = 0.002) and L-CC (P = 0.037) but not in R-CC (P > 0.05). Elevated CEA (P≈.000) and CA19.9 (P≈.000) were significantly associated with poor OS in RC but not in L-CC and R-CC. Multivariate-COX showed that STK1p (P = 0.02, HR = 1.779, 95%CI 1.30-7.582), CEA (P = 0.001, HR = 2.052, 95%CI 1.320-3.189), CA19.9 (P≈.000, HR = 2.574, 95%CI 1.592-4.162) and TNM-stage (P≈.000, HR = 2.368, 95%CI 1.518-3.694) were independent prognostic factors in RC, while TNM-stage was an independent prognostic factor only in R-CC (P = 0.011, HR = 3.139, 95% CI 1.30-7.582) and L-CC (P≈.000, HR = 4.168, 95%CI 1.980-8.852). Moreover, elevated STK1p was significantly more sensitive (P < .001) for predicting mortality than CEA and CA19.9. No correlation was found between STK1p, CEA or AFP.

CONCLUSION

Combining TNM stage and suitable biomarkers, STK1p provides further reliable information on the survival of PTL of CRC.

Artificial intelligence fusion for predicting survival of rectal cancer patients using immunohistochemical expression of Ras homolog family member B in biopsy

Aim

The process of biomarker discovery is being accelerated with the application of artificial intelligence (AI), including machine learning. Biomarkers of diseases are useful because they are indicators of pathogenesis or measures of responses to therapeutic treatments, and therefore, play a key role in new drug development. Proteins are among the candidates for biomarkers of rectal cancer, which need to be explored using state-of-the-art AI to be utilized for prediction, prognosis, and therapeutic treatment. This paper aims to investigate the predictive power of Ras homolog family member B (RhoB) protein in rectal cancer.

Methods

This study introduces the integration of pretrained convolutional neural networks and support vector machines (SVMs) for classifying biopsy samples of immunohistochemical expression of protein RhoB in rectal-cancer patients to validate its biologic measure in biopsy. Features of the immunohistochemical expression images were extracted by the pretrained networks and used for binary classification by the SVMs into two groups of less and more than 5-year survival rates.

Results

The fusion of neural search architecture network (NASNet)-Large for deep-layer feature extraction and classifier using SVMs provided the best average classification performance with a total accuracy = 85%, prediction of survival rate of more than 5 years = 90%, and prediction of survival rate of less than 5 years = 75%.

Conclusions

The finding obtained from the use of AI reported in this study suggest that RhoB expression on rectal-cancer biopsy can be potentially used as a biomarker for predicting survival outcomes in rectal-cancer patients, which can be informative for clinical decision making if the patient would be recommended for preoperative therapy.

BIRCH: An Automated Workflow for Evaluation, Correction, and Visualization of Batch Effect in Bottom-Up Mass Spectrometry-Based Proteomics Data

Recent surges in large-scale mass spectrometry (MS)-based proteomics studies demand a concurrent rise in methods to facilitate reliable and reproducible data analysis. Quantification of proteins in MS analysis can be affected by variations in technical factors such as sample preparation and data acquisition conditions leading to batch effects, which adds to noise in the data set. This may in turn affect the effectiveness of any biological conclusions derived from the data. Here we present Batch-effect Identification, Representation, and Correction of Heterogeneous data (BIRCH), a workflow for analysis and correction of batch effect through an automated, versatile, and easy to use web-based tool with the goal of eliminating technical variation. BIRCH also supports diagnosis of the data to check for the presence of batch effects, feasibility of batch correction, and imputation to deal with missing values in the data set. To illustrate the relevance of the tool, we explore two case studies, including an iPSC-derived cell study and a Covid vaccine study to show different context-specific use cases. Ultimately this tool can be used as an extremely powerful approach for eliminating technical bias while retaining biological bias, toward understanding disease mechanisms and potential therapeutics.

Transcriptomic data analysis coupled with copy number aberrations reveals a blood-based 17-gene signature for diagnosis and prognosis of patients with colorectal cancer

Background: Colorectal cancer (CRC) is the third most common cancer and third leading cause of cancer-associated deaths worldwide. Diagnosing CRC patients reliably at an early and curable stage is of utmost importance to reduce the risk of mortality. Methods: We identified global differentially expressed genes with copy number alterations in patients with CRC. We then identified genes that are also expressed in blood, which resulted in a blood-based gene signature. We validated the gene signature's diagnostic and prognostic potential using independent datasets of gene expression profiling from over 800 CRC patients with detailed clinical data. Functional enrichment, gene interaction networks and pathway analyses were also performed. Results: The analysis revealed a 17-gene signature that is expressed in blood and demonstrated that it has diagnostic potential. The 17-gene SVM classifier displayed 99 percent accuracy in predicting the patients with CRC. Moreover, we developed a prognostic model and defined a risk-score using 17-gene and validated that high risk score is strongly associated with poor disease outcome. The 17-gene signature predicted disease outcome independent of other clinical factors in the multivariate analysis (HR = 2.7, 95% CI = 1.3-5.3, p = 0.005). In addition, our gene network and pathway analyses revealed alterations in oxidative stress, STAT3, ERK/MAPK, interleukin and cytokine signaling pathways as well as potentially important hub genes, including BCL2, MS4A1, SLC7A11, AURKA, IL6R, TP53, NUPR1, DICER1, DUSP5, SMAD3, and CCND1. Conclusion: Our results revealed alterations in various genes and cancer-related pathways that may be essential for CRC transformation. Moreover, our study highlights diagnostic and prognostic value of our gene signature as well as its potential use as a blood biomarker as a non-invasive diagnostic method. Integrated analysis transcriptomic data coupled with copy number aberrations may provide a reliable method to identify key biological programs associated with CRC and lead to improved diagnosis and therapeutic options.

Pilot proteomic study of locally advanced rectal cancer before and after neoadjuvant chemoradiotherapy indicates high metabolic activity in non-responders' tumor tissue

PURPOSE

In the search for candidate predictive biomarkers to evaluate response to neoadjuvant chemoradiotherapy (nCRT) in rectal cancer, only a few studies report proteomic profiles of tumor tissue before and after nCRT. The aim of our study was to determine differentially expressed proteins between responders and non-responders before and after the therapy in order to identify candidate molecules for prediction and follow-up of response to nCRT.

EXPERIMENTAL DESIGN

The study has included tissue sections of rectal tumor and non-tumor mucosa from five responders and five non-responders taken before and after nCRT from patients with locally advanced rectal cancer. Extracted proteins were analyzed by LC-MS/MS analysis followed by a set of bioinformatics analyses.

RESULT

Proteomics analysis provided a mean of approximately 1050 protein identifications per sample. A comparison of proteomic profiles between responders and non-responders has identified 18 differentially expressed proteins. Pathway analysis demonstrated high metabolic activity in non-responders' tumors before nCRT, indicating the presence of intrinsic chemoradioresistance in these subjects. Two proteins associated with poor prognosis in colorectal cancer, ADAM10 and CAD, were identified as candidate predictive biomarkers as they were present in non-responders only.

CONCLUSIONS AND CLINICAL RELEVANCE

Shortlisted proteins from our study should be further validated as candidate biomarkers for response to routinely applied nCRT protocols.

Studies on 1,4-Quinone Derivatives Exhibiting Anti-Leukemic Activity along with Anti-Colorectal and Anti-Breast Cancer Effects

Colorectal cancer (CRC), breast cancer, and chronic myeloid leukemia (CML) are life-threatening malignancies worldwide. Although potent therapeutic and screening strategies have been developed so far, these cancer types are still major public health problems. Therefore, the exploration of more potent and selective new agents is urgently required for the treatment of these cancers. Quinones represent one of the most important structures in anticancer drug discovery. We have previously identified a series of quinone-based compounds (ABQ-1-17) as anti-CML agents. In the current work, ABQ-3 was taken to the National Cancer Institute (NCI) for screening to determine its in vitro antiproliferative effects against a large panel of human tumor cell lines at five doses. ABQ-3 revealed significant growth inhibition against HCT-116 CRC and MCF-7 breast cancer cells with 2.00 µM and 2.35 µM GI₅₀ values, respectively. The MTT test also showed that ABQ-3 possessed anticancer effects towards HCT-116 and MCF-7 cells with IC₅₀ values of 5.22 ± 2.41 μM and 7.46 ± 2.76 μM, respectively. Further experiments indicated that ABQ-3 induced apoptosis in both cell lines, and molecular docking studies explicitly suggested that ABQ-3 exhibited DNA binding in a similar fashion to previously reported compounds. Based on in silico pharmacokinetic prediction, ABQ-3 might display drug-like features enabling this compound to become a lead molecule for future studies.

Diagnostic and prognostic biomarkers in colorectal cancer and the potential role of exosomes in drug delivery

Colorectal cancer (CRC) is the third most common cancer with the second most frequent cause of death worldwide. One fourth to one fifth of the CRC cases are detected at advance stage. Early detection of colorectal cancer might help in decreasing mortality and morbidity worldwide. CRC being a heterogeneous disease, new non-invasive approaches are needed to complement and improve the screening and management of CRC. Reliable and early detectable biomarkers would improve diagnosis, prognosis, therapeutic responses, and will enable the prediction of drug response and recurrence risk. Over the past decades molecular research has demonstrated the potentials of CTCs, ctDNAs, circulating mRNAs, ncRNAs, and exosomes as tumor biomarkers. Non-invasive screening approaches using fecal samples for identification of altered gut microbes in CRC is also gaining attention. Exosomes can be potential candidates that can be employed in the drug delivery system. Further, the integration of in vitro, in vivo and in silico models that involve CRC biomarkers will help to understand the interactions occurring at the cellular level. This review summarizes recent update on CRC biomarkers and their application along with the nanoparticles followed by the application of organoid culture in CRC.

Colorectal Cancer and the Role of the Gut Microbiota-Do Medical Students Know More Than Other Young People?-Cross-Sectional Study

(1) Background: Malignant neoplasms account for an increasing share of the disease burden of the world population and are an increasingly common cause of death. In the aspect of colorectal cancer, increasing attention is paid to the microbiota. According to current knowledge, the composition of gut microbiota in patients diagnosed with colorectal cancer significantly differs from the composition of microorganisms in the intestines of healthy individuals. (2) Material and methods: The survey included 571 students from the three universities located in Silesia. The research tool was an original, anonymous questionnaire created for the study. The ratio of correct answers to the total number of points possible to obtain was evaluated according to the adopted criteria (≤25%—very low level of knowledge; >75%—high level of knowledge). (3) Results: From the questions about the gut microbiota, the subjects scored an average of six points (SD ± 1.31) out of nine possible points. Statistical analysis showed differences between the number of correct answers among students of the Medical University of Silesia and the University of Silesia (p = 0.04, p < 0.05). On the other hand, in the field of colorectal cancer, the respondents scored on average four points (SD ± 2.07) out of eight possible. Statistical analysis showed significant differences between the ratio of correct answers and the respondent’s university affiliation (p < 0.05). Both age and place of residence did not positively correlate with knowledge level (p = 0.08 NS). In contrast, chronic diseases were found to have a significant effect on the amount of information held by the students surveyed (p < 0.05). (4) Conclusions: The level of knowledge of the surveyed students of the Silesia Province is unsatisfactory. The higher awareness among the students of medical universities results from the presence of issues related to microbiota and CRC in the medical educational content. Therefore, there is a need to consider the introduction of educational activities in the field of cancer prevention, including CRC, especially among non-medical university students.

Analysis of blood markers for early colorectal cancer diagnosis

BACKGROUND

Colorectal cancer (CRC) is a very common tumor worldwide. Its mortality can be limited by early diagnosis through screening programs. These programs are based on fecal occult blood testing and colonoscopy. Our objective was to find a model based on the determination of blood biomarkers that was efficacious enough to become part of the early diagnosis of CRC.

METHODS

In a total of 221 patients who underwent a colonoscopy, two types of markers were identified (I) classic: carcinoembryonic antigen (CEA), CA19.9, α-fetoprotein, CA125, CA72.4, and ferritin; and (II) experimental: neutrophil gelatinase-associated lipocalin (NGAL), estimated glomerular filtration rate (EGFR), 8-hydroxydeoxyguanosine (8OHdG), calprotectin, and cysteine-rich 61 (Cyr61). We divided the patients into four groups according to colonoscopy results: a control group (n=83) with normal colonoscopy, a polyp group (n=56), a CRC group (n=45), and an inflammatory disease group (n=37). We built an algorithm based on multivariate logistic regression analysis.

RESULTS

A total of 51.6% were males, and the median age was 63 years. We designed an algorithm based on the combination of several markers that discriminated CRC patients from the rest of the patients with a performance of 94%, a sensitivity of 95.6%, and a specificity of 80.6%. Discriminating by sex also resulted in two powerful algorithms, although it performed better in males (97% vs. 91%).

CONCLUSIONS

Our study has devised a predictive model with high efficacy based on the determination of several biomarkers. We think that it could be incorporated into the set of methods used in CRC screening.

A bioinformatics framework to identify the biomarkers and potential drugs for the treatment of colorectal cancer

Colorectal cancer (CRC), a common malignant tumor, is one of the main causes of death in cancer patients in the world. Therefore, it is critical to understand the molecular mechanism of CRC and identify its diagnostic and prognostic biomarkers. The purpose of this study is to reveal the genes involved in the development of CRC and to predict drug candidates that may help treat CRC through bioinformatics analyses. Two independent CRC gene expression datasets including The Cancer Genome Atlas (TCGA) database and GSE104836 were used in this study. Differentially expressed genes (DEGs) were analyzed separately on the two datasets, and intersected for further analyses. 249 drug candidates for CRC were identified according to the intersected DEGs and the Crowd Extracted Expression of Differential Signatures (CREEDS) database. In addition, hub genes were analyzed using Cytoscape according to the DEGs, and survival analysis results showed that one of the hub genes, TIMP1 was related to the prognosis of CRC patients. Thus, we further focused on drugs that could reverse the expression level of TIMP1. Eight potential drugs with documentary evidence and two new drugs that could reverse the expression of TIMP1 were found among the 249 drugs. In conclusion, we successfully identified potential biomarkers for CRC and achieved drug repurposing using bioinformatics methods. Further exploration is needed to understand the molecular mechanisms of these identified genes and drugs/small molecules in the occurrence, development and treatment of CRC.

Proteomics approaches to characterize the immune responses in cancer

Despite the dynamic development of cancer research, annually millions of people die of cancer. The human immune system is the major 'guard' against tumor development. Unfortunately, cancer cells have the ability to evade the immune system and continue to grow. The proper understanding of the intricate immune response in tumorigenesis remains the holy grail of cancer immunology and designing effective immunotherapy. To decode the immune responses in cancer, in recent years, proteomics studies have received considerable attention. Proteomics studies focus on the detection and quantification of proteins, which are the effectors of biological functions, and as such, are proven to reflect the cell state more accurately, in comparison to genomic or transcriptomic studies. In this review, we discuss the proteomics studies applied to characterize the immune responses in cancer and tumor immune microenvironment heterogeneity. Further, we describe emerging single-cell proteomics approaches that have the potential to be applied in cancer immunity studies.

Proteomic analysis of low- and high-grade human colon adenocarcinoma tissues and tissue-derived primary cell lines reveals unique biological functions of tumours and new protein biomarker candidates

Background

Colon cancer is the third most common cancer and second highest cause of cancer deaths worldwide. The aim of the study was to find new biomarkers for diagnosis, prognosis and therapeutic drug targets for this disease.

Methods

Four low-grade and four high-grade human colon adenocarcinoma tumours with patient-matched normal colon tissues were analysed. Additionally, tissue-derived primary cell lines were established from each tumour tissue. The cell lines were validated using DNA sequencing to confirm that they are a suitable in vitro model for colon adenocarcinoma based on conserved gene mutations. Label-free quantitation proteomics was performed to compare the proteomes of colon adenocarcinoma samples to normal colon samples, and of colon adenocarcinoma tissues to tissue-derived cell lines to find significantly differentially abundant proteins. The functions enriched within the differentially expressed proteins were assessed using STRING. Proteomics data was validated by Western blotting.

Results

A total of 4767 proteins were identified across all tissues, and 4711 across primary tissue-derived cell lines. Of these, 3302 proteins were detected in both the tissues and the cell lines. On average, primary cell lines shared about 70% of proteins with their parent tissue, and they retained mutations to key colon adenocarcinoma-related genes and did not diverge far genetically from their parent tissues. Colon adenocarcinoma tissues displayed upregulation of RNA processing, steroid biosynthesis and detoxification, and downregulation of cytoskeletal organisation and loss of normal muscle function. Tissue-derived cell lines exhibited increased interferon-gamma signalling and aberrant ferroptosis. Overall, 318 proteins were significantly up-regulated and 362 proteins significantly down-regulated by comparisons of high-grade with low-grade tumours and low-grade tumour with normal colon tissues from both sample types.

Conclusions

The differences exhibited between tissues and cell lines highlight the additional information that can be obtained from patient-derived primary cell lines. DNA sequencing and proteomics confirmed that these cell lines can be considered suitable in vitro models of the parent tumours. Various potential biomarkers for colon adenocarcinoma initiation and progression and drug targets were identified and discussed, including seven novel markers: ACSL4, ANK2, AMER3, EXOSC1, EXOSC6, GCLM, and TFRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12014-022-09364-y.

Transcriptome profiling and co-expression network analysis of lncRNAs and mRNAs in colorectal cancer by RNA sequencing

Background

Long non-coding RNAs (lncRNAs) are widely involved in the pathogenesis of cancers. However, biological roles of lncRNAs in occurrence and progression of colorectal cancer (CRC) remain unclear. The current study aimed to evaluate the expression pattern of lncRNAs and messenger RNAs (mRNAs).

Methods

RNA sequencing (RNA-Seq) in CRC tissues and adjacent normal tissues from 6 CRC patients was performed and functional lncRNA-mRNA co-expression network was constructed afterwards. Gene enrichment analysis was demonstrated using DAVID 6.8 tool. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) was used to validate the expression pattern of differentially expressed lncRNAs. Pearson correlation analysis was applied to evaluate the relationships between selected lncRNAs and mRNAs.

Results

One thousand seven hundred and sixteenth differentially expressed mRNAs and 311 differentially expressed lncRNAs were screened out. Among these, 568 mRNAs were up-regulated while 1148 mRNAs down-regulated, similarly 125 lncRNAs were up-regulated and 186 lncRNAs down-regulated. In addition, 1448 lncRNA–mRNA co-expression pairs were screened out from 940,905 candidate lncRNA-mRNA pairs. Gene enrichment analysis revealed that these lncRNA-related mRNAs are associated with cell adhesion, collagen adhesion, cell differentiation, and mainly enriched in ECM-receptor interaction and PI3K-Akt signaling pathways. Finally, RT-qPCR results verified the expression pattern of lncRNAs, as well as the relationships between lncRNAs and mRNAs in 60 pairs of CRC tissues.

Conclusions

In conclusion, these results of the RNA-seq and bioinformatic analysis strongly suggested that the dysregulation of lncRNA is involved in the complicated process of CRC development, and providing important insight regarding the lncRNAs involved in CRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09878-6.

Characterizing the Antitumor Effect of Coptis chinensis and Mume Fructus against Colorectal Cancer Based on Pharmacological Analysis

Colorectal cancer (CRC) is the third most diagnosed cancer worldwide and is a significant cause of cancer-related deaths. Previous studies have observed that Coptis chinensis (CC) and Mume Fructus (MF) are effective against CRC, enteritis, and intestinal dysbiosis, but the chemical and pharmacological mechanisms remain poorly understood. In this study, we employed pharmacological network analysis to reveal mechanisms underlying the therapeutic effect of CC and MF against CRC. All compounds and targeted genes were obtained from the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP). Differentially expressed genes (DEGs) were identified based on GSE146587, GSE156720, and GSE184093 datasets. A protein-protein interaction (PPI) network was constructed to identify putative target genes of CC and MF. Ten key targeted genes were identified, including CCND1, ICAM1, IL1B, IL-6, MMP1, MMP3, MMP9, MYC, SERPINE1, and VEGFA. Among these genes, six (ICAM1, IL1B, IL-6, MMP1, MMP3, MMP9, and SERPINE1) were positively correlated with levels of effector memory CD4 T cells and natural killer T cells, and three (CCND1, MYC, and VEGFA) were negatively correlated with type 17 T helper cells and CD56dim natural killer cells. Molecular docking analysis showed that four compounds of CC and MF (kaempferol, oleanolic acid, quercetin, and ursolic acid) could affect CRC by interacting with target genes. Our study proved that pharmacological analysis could reliably assess the mechanism of traditional Chinese medicines for treating cancer.

Bottom-Up Approach to the Discovery of Clinically Relevant Biomarker Genes: The Case of Colorectal Cancer

Traditional approaches to genome-wide marker discovery often follow a common top-down strategy, where a large scale ‘omics’ investigation is followed by the analysis of functional pathways involved, to narrow down the list of identified putative biomarkers, and to deconvolute gene expression networks, or to obtain an insight into genetic alterations observed in cancer. We set out to investigate whether a reverse approach would allow full or partial reconstruction of the transcriptional programs and biological pathways specific to a given cancer and whether the full or substantially expanded list of putative markers could thus be identified by starting with the partial knowledge of a few disease-specific markers. To this end, we used 10 well-documented differentially expressed markers of colorectal cancer (CRC), analyzed their transcription factor networks and biological pathways, and predicted the existence of 193 new putative markers. Incredibly, the use of a validation marker set of 10 other completely different known CRC markers and the same procedure resulted in a very similar set of 143 predicted markers. Of these, 138 were identical to those found using the training set, confirming our main hypothesis that a much-expanded set of disease markers can be predicted by starting with just a small subset of validated markers. Further to this, we validated the expression of 42 out of 138 top-ranked predicted markers experimentally using qPCR in surgically removed CRC tissues. We showed that 41 out of 42 mRNAs tested have significantly altered levels of mRNA expression in surgically excised CRC tissues. Of the markers tested, 36 have been reported to be associated with aspects of CRC in the past, whilst only limited published evidence exists for another three genes (BCL2, PDGFRB and TSC2), and no published evidence directly linking genes to CRC was found for CCNA1, SHC1 and TGFB3. Whilst we used CRC to test and validate our marker discovery strategy, the reported procedures apply more generally to cancer marker discovery.

Quantitative Proteogenomic Characterization of Inflamed Murine Colon Tissue Using an Integrated Discovery, Verification, and Validation Proteogenomic Workflow

Chronic inflammation of the colon causes genomic and/or transcriptomic events, which can lead to expression of non-canonical protein sequences contributing to oncogenesis. To better understand these mechanisms, Rag2-/-Il10-/- mice were infected with Helicobacter hepaticus to induce chronic inflammation of the cecum and the colon. Transcriptomic data from harvested proximal colon samples were used to generate a customized FASTA database containing non-canonical protein sequences. Using a proteogenomic approach, mass spectrometry data for proximal colon proteins were searched against this custom FASTA database using the Galaxy for Proteomics (Galaxy-P) platform. In addition to the increased abundance in inflammatory response proteins, we also discovered several non-canonical peptide sequences derived from unique proteoforms. We confirmed the veracity of these novel sequences using an automated bioinformatics verification workflow with targeted MS-based assays for peptide validation. Our bioinformatics discovery workflow identified 235 putative non-canonical peptide sequences, of which 58 were verified with high confidence and 39 were validated in targeted proteomics assays. This study provides insights into challenges faced when identifying non-canonical peptides using a proteogenomics approach and demonstrates an integrated workflow addressing these challenges. Our bioinformatic discovery and verification workflow is publicly available and accessible via the Galaxy platform and should be valuable in non-canonical peptide identification using proteogenomics.

Identification of proteomic markers for prediction of the response to 5-Fluorouracil based neoadjuvant chemoradiotherapy in locally advanced rectal cancer patients

Background

Neoadjuvant chemoradiotherapy (nCRT) prior to surgery is the standard treatment for patients with locally advanced rectal cancer (LARC), while parts of them show poor therapeutic response accompanied by therapy adverse effects. Predictive biomarkers for nCRT response could facilitate the guidance on treatment decisions but are still insufficient until now, which limits the clinical applications of nCRT in LARC patients.

Methods

In our study, 37 formalin-fixed paraffin-embedded tumor biopsies were obtained from patients with LARC before receiving 5-fluorouracil based nCRT. Proteomics analyses were conducted to identify the differentially expressed proteins (DEPs) between total responders (TR) and poor responders (PR). The DEPs were validated via ROC plotter web tool and their predictive performance was evaluated by receiver operating characteristic analysis. Functional enrichment analyses were performed to further explore the potential mechanisms underlying nCRT response.

Results

Among 3,998 total proteins, 91 DEPs between TR and PR were screened out. HSPA4, NIPSNAP1, and SPTB all with areas under the curve (AUC) ~ 0.8 in the internal discovery cohort were independently validated by the external mRNA datasets (AUC ~ 0.7), and their protein levels were linearly correlated with the graded responses to nCRT in the internal cohort. The combination of HSPA4 and SPTB could distinctly discriminate the TR and PR groups (AUC = 0.980, p < 0.0001). Moreover, multiple combinations of the three proteins realized increased specificity and/or sensitivity, while achieving favorable predictive value when moderate responders were introduced into the ROC analysis. Pathways including DNA damage repair, cell cycle, and epithelial mesenchymal transition were involved in nCRT response according to the enrichment analysis results.

Conclusions

HSPA4, SPTB and NIPSNAP1 in tumor biopsies and/or their optional combinations might be potential predictive markers for nCRT response in patients with LARC. The DEPs and their related functions have implications for the potential mechanisms of treatment response to nCRT in patients with LARC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02530-0.

Application Progress of Organoids in Colorectal Cancer

Currently, colorectal cancer is still the third leading cause of cancer-related mortality, and the incidence is rising. It is a long time since the researchers used cancer cell lines and animals as the study subject. However, these models possess various limitations to reflect the cancer progression in the human body. Organoids have more clinical significance than cell lines, and they also bridge the gap between animal models and humans. Patient-derived organoids are three-dimensional cultures that simulate the tumor characteristics in vivo and recapitulate tumor cell heterogeneity. Therefore, the emergence of colorectal cancer organoids provides an unprecedented opportunity for colorectal cancer research. It retains the molecular and cellular composition of the original tumor and has a high degree of homology and complexity with patient tissues. Patient-derived colorectal cancer organoids, as personalized tumor organoids, can more accurately simulate colorectal cancer patients’ occurrence, development, metastasis, and predict drug response in colorectal cancer patients. Colorectal cancer organoids show great potential for application, especially preclinical drug screening and prediction of patient response to selected treatment options. Here, we reviewed the application of colorectal cancer organoids in disease model construction, basic biological research, organoid biobank construction, drug screening and personalized medicine, drug development, drug toxicity and safety, and regenerative medicine. In addition, we also displayed the current limitations and challenges of organoids and discussed the future development direction of organoids in combination with other technologies. Finally, we summarized and analyzed the current clinical trial research of organoids, especially the clinical trials of colorectal cancer organoids. We hoped to lay a solid foundation for organoids used in colorectal cancer research.

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

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

Expression of Spermine Oxidase Is Associated with Colorectal Carcinogenesis and Prognosis of Patients

Uncovering tumor markers of colorectal cancer is important for the early detection and prognosis of the patients. Spermine oxidase (SMOX) is upregulated in various cancers. The present study aims to explore the biologic function and expression patterns of SMOX in colorectal cancer (CRC), the third most common type of cancer worldwide. We used quantitative real-time PCR, Western blot, and in vitro functional studies in four CRC cell lines knocked down by SMOX siRNA and immunohistochemistry in 350 cases of CRC tissues. The results showed that SMOX was overexpressed in CRC cell lines and clinical samples. SMOX overexpression in tumor tissues was an independent prognostic factor, worsening overall survival (p = 0.001). The knock-down of SMOX inhibited CRC cell proliferation, invasion, and soft agar colony formation, uncovering its carcinogenic functions. This study indicated that SMOX overexpression could be an important oncogene in CRC and might serve as a valuable prognostic marker and potential therapeutic target for CRC.