Clinical Proteomics in Colorectal Cancer, a Promising Tool for Improving Personalised Medicine

Multi-omics staging of locally advanced rectal cancer predicts treatment response: a pilot study

Treatment response assessment of rectal cancer patients is a critical component of personalized cancer care and it allows to identify suitable candidates for organ-preserving strategies. This pilot study employed a novel multi-omics approach combining MRI-based radiomic features and untargeted metabolomics to infer treatment response at staging. The metabolic signature highlighted how tumor cell viability is predictively down-regulated, while the response to oxidative stress was up-regulated in responder patients, showing significantly reduced oxoproline values at baseline compared to non-responder patients (p-value < 10-4). Tumors with a high degree of texture homogeneity, as assessed by radiomics, were more likely to achieve a major pathological response (p-value < 10-3). A machine learning classifier was implemented to summarize the multi-omics information and discriminate responders and non-responders. Combining all available radiomic and metabolomic features, the classifier delivered an AUC of 0.864 (± 0.083, p-value < 10-3) with a best-point sensitivity of 90.9% and a specificity of 81.8%. Our results suggest that a multi-omics approach, integrating radiomics and metabolomic data, can enhance the predictive value of standard MRI and could help to avoid unnecessary surgical treatments and their associated long-term complications.

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.

High-throughput proteomics profiling-derived signature associated with chemotherapy response and survival for stage II/III colorectal cancer

Adjuvant chemotherapy (ACT) is usually used to reduce the risk of disease relapse and improve survival for stage II/III colorectal cancer (CRC). However, only a subset of patients could benefit from ACT. Thus, there is an urgent need to identify improved biomarkers to predict survival and stratify patients to refine the selection of ACT. We used high-throughput proteomics to analyze tumor and adjacent normal tissues of stage II/III CRC patients with /without relapse to identify potential markers for predicting prognosis and benefit from ACT. The machine learning approach was applied to identify relapse-specific markers. Then the artificial intelligence (AI)-assisted multiplex IHC was performed to validate the prognostic value of the relapse-specific markers and construct a proteomic-derived classifier for stage II/III CRC using 3 markers, including FHL3, GGA1, TGFBI. The proteomics profiling-derived signature for stage II/III CRC (PS) not only shows good accuracy to classify patients into high and low risk of relapse and mortality in all three cohorts, but also works independently of clinicopathologic features. ACT was associated with improved disease-free survival (DFS) and overall survival (OS) in stage II (pN0) patients with high PS and pN2 patients with high PS. This study demonstrated the clinical significance of proteomic features, which serve as a valuable source for potential biomarkers. The PS classifier provides prognostic value for identifying patients at high risk of relapse and mortality and optimizes individualized treatment strategy by detecting patients who may benefit from ACT for survival.

Notch-Jagged1 signaling and response to bevacizumab therapy in advanced colorectal cancer: A glance to radiomics or back to physiopathology?

Introduction

The Notch intracellular domain (NICD) and its ligands Jagged-1(Jag1), Delta-like ligand (DLL-3) and DLL4 play an important role in neoangiogenesis. Previous studies suggest a correlation between the tissue levels of NICD and response to therapy with bevacizumab in colorectal cancer (CRC). Another marker that may predict outcome in CRC is radiomics of liver metastases. The aim of this study was to investigate the expression of NICD and its ligands and the role of radiomics in the selection of treatment-naive metastatic CRC patients receiving bevacizumab.

Methods

Immunohistochemistry (IHC) for NICD, Jag1 and E-cadherin was performed on the tissue microarrays (TMAs) of 111 patients with metastatic CRC treated with bevacizumab and chemotherapy. Both the intensity and the percentage of stained cells were evaluated. The absolute number of CD4+ and CD8+ lymphocytes was counted in three different high-power fields and the mean values obtained were used to determine the CD4/CD8 ratio. The positivity of tumor cells to DLL3 and DLL4 was studied. The microvascular density (MVD) was assessed in fifteen cases by counting the microvessels at 20x magnification and expressed as MVD score. Abdominal CT scans were retrieved and imported into a dedicated workstation for radiomic analysis. Manually drawn regions of interest (ROI) allowed the extraction of radiomic features (RFs) from the tumor.

Results

A positive association was found between NICD and Jag1 expression (p < 0.001). Median PFS was significantly shorter in patients whose tumors expressed high NICD and Jag1 (6.43 months vs 11.53 months for negative cases; p = 0.001). Those with an MVD score ≥5 (CD31-high, NICD/Jag1 positive) experienced significantly poorer survival. The radiomic model developed to predict short and long-term survival and PFS yielded a ROC-AUC of 0.709; when integrated with clinical and histopathological data, the integrated model improved the predictive score (ROC-AUC of 0.823).

Discussion

These results show that high NICD and Jag1 expression are associated with progressive disease and early disease progression to anti VEGF-based therapy; the preliminary radiomic analyses show that the integration of quantitative information with clinical and histological data display the highest performance in predicting the outcome of CRC patients.

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.

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.

Label-Free Quantification (LFQ) of Fecal Proteins for Potential Pregnancy Detection in Polar Bears

Reliable pregnancy diagnostics would be beneficial for monitoring polar bear (Ursus maritimus) populations both in situ and ex situ, but currently there is no method of non-invasive pregnancy detection in this species. Recent reports in several carnivore species described the identification of fecal proteins that may serve as pregnancy biomarkers; however, repeatability has been limited. The objective of the current analysis was to utilize an unbiased, antibody-free, label-free method for the identification and quantification of fecal proteins to determine if differences associated with pregnancy are detectable in polar bears. Protein was extracted from fecal samples (n = 48) obtained from parturient (n = 6) and non-parturient (n = 6) profiles each at four timepoints: pre-breeding season, embryonic diapause, early placental pregnancy, and mid-placental pregnancy. Protein was prepared and analyzed on the Thermo Orbitrap Eclipse nanoLC-MS/MS system. A total of 312 proteins was identified and quantified; however, coefficients of variation (CV) were high for both abundance ratio variability (384.8 ± 61.0% SEM) and within group variability (86.8 ± 1.5%). Results of this study suggest that the inconsistencies in specific protein concentrations revealed previously by antibody-based assays may not be due to that methodology’s limitations, but rather, are reflective of true variation that exists among samples.

Downregulation of KRAB zinc finger proteins in 5-fluorouracil resistant colorectal cancer cells

Radio-chemotherapy with 5-flu orouracil (5-FU) is the standard of care treatment for patients with colorectal cancer, but it is only effective for a third of them. Despite our understanding of the mechanism of action of 5-FU, drug resistance remains a significant limitation to the clinical use of 5-FU, as both intrinsic and acquired chemoresistance represents the major obstacles for the success of 5-FU-based chemotherapy. In order to identify the mechanism of acquired resistance, 5-FU chemoresistance was induced in CRC cell lines by passaging cells with increasing concentrations of 5-FU. To study global molecular changes, quantitative proteomics and transcriptomics analyses were performed on these cell lines, comparing the resistant cells as well as the effect of chemo and radiotherapy. Interestingly, a very high proportion of downregulated genes were annotated as transcription factors coding for Krüppel-associated box (KRAB) domain-containing zinc-finger proteins (KZFPs), the largest family of transcriptional repressors. Among nearly 350 KRAB-ZFPs, almost a quarter were downregulated after the induction of a 5-FU-resistance including a common one between the three CRC cell lines, ZNF649, whose role is still unknown. To confirm the observations of the proteomic and transcriptomic approaches, the abundance of 20 different KZFPs and control mRNAs was validated by RT-qPCR. In fact, several KZFPs were no longer detectable using qPCR in cell lines resistant to 5-FU, and the KZFPs that were downregulated only in one or two cell lines showed similar pattern of expression as measured by the omics approaches. This proteomic, transcriptomic and genomic analysis of intrinsic and acquired resistance highlights a possible new mechanism involved in the cellular adaptation to 5-FU and therefore identifies potential new therapeutic targets to overcome this resistance.

Diagnostic and therapeutic biomarkers in colorectal cancer: a review

Colorectal cancer (CRC) is a public health concern and the second most common type of cancer among men and women causing a significant mortality. Biomarkers closely linked to the disease morbidity could holds potential as diagnostic and/or prognostic biomarker for the disease. This review provides an overview of recent advances in the search for colorectal cancer biomarkers through genomics and proteomics according to clinical function and application. Specifically, a number of biomarkers were identified and discussed. Emphasis was placed on their clinical applications relative to the diagnosis and prognosis of CRC. The discovery of more sensitive and specific markers for CRC is an urgent need, and the study of molecular targets is extremely important in this process, as they will allow for a better understanding of colorectal carcinogenesis, identification and validation of potential genetic signatures.

Use of Omics Technologies for the Detection of Colorectal Cancer Biomarkers

Colorectal cancer (CRC) is one of the most frequently diagnosed cancers with high mortality rates, especially when detected at later stages. Early detection of CRC can substantially raise the 5-year survival rate of patients, and different efforts are being put into developing enhanced CRC screening programs. Currently, the faecal immunochemical test with a follow-up colonoscopy is being implemented for CRC screening. However, there is still a medical need to describe biomarkers that help with CRC detection and monitor CRC patients. The use of omics techniques holds promise to detect new biomarkers for CRC. In this review, we discuss the use of omics in different types of samples, including breath, urine, stool, blood, bowel lavage fluid, or tumour tissue, and highlight some of the biomarkers that have been recently described with omics data. Finally, we also review the use of extracellular vesicles as an improved and promising instrument for biomarker detection.

Multi-Omic Approaches in Colorectal Cancer beyond Genomic Data

Colorectal cancer (CRC) is one of the most frequent tumours and one of the major causes of morbidity and mortality globally. Its incidence has increased in recent years and could be linked to unhealthy dietary habits combined with environmental and hereditary factors, which can lead to genetic and epigenetic changes and induce tumour development. The model of CRC progression has always been based on a genomic, parametric, static and complex approach involving oncogenes and tumour suppressor genes. Recent advances in omics sciences have sought a paradigm shift to a multiparametric, immunological-stromal, and dynamic approach for a better understanding of carcinogenesis and tumour heterogeneity. In the present paper, we review the most important preclinical and clinical data and present recent discoveries in the field of transcriptomics, proteomics, metagenomics and radiomics in CRC disease.

Molecular Network of Colorectal Cancer and Current Therapeutic Options

Colorectal cancer (CRC), a leading cause of cancer-related mortalities globally, results from the accumulation of multiple genetic and epigenetic alterations in the normal colonic and rectum epithelium, leading to the progression from colorectal adenomas to invasive carcinomas. Almost half of CRC patients will develop metastases in the course of the disease and most patients with metastatic CRC are incurable. Particularly, the 5-year survival rate of patients with stage 4 CRC at diagnosis is less than 10%. Although genetic understanding of these CRC tumors and paired metastases has led to major advances in elucidating early driver genes responsible for carcinogenesis and metastasis, the pathophysiological contribution of transcriptional and epigenetic aberrations in this malignancy which influence many central signaling pathways have attracted attention recently. Therefore, treatments that could affect several different molecular pathways may have pivotal implications for their efficacy. In this review, we summarize our current knowledge on the molecular network of CRC, including cellular signaling pathways, CRC microenvironment modulation, epigenetic changes, and CRC biomarkers for diagnosis and predictive/prognostic use. We also provide an overview of opportunities for the treatment and prevention strategies in this field.

The Roadmap of Colorectal Cancer Screening

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

The Multiomics Analyses of Fecal Matrix and Its Significance to Coeliac Disease Gut Profiling

Gastrointestinal (GIT) diseases have risen globally in recent years, and early detection of the host’s gut microbiota, typically through fecal material, has become a crucial component for rapid diagnosis of such diseases. Human fecal material is a complex substance composed of undigested macromolecules and particles, and the processing of such matter is a challenge due to the unstable nature of its products and the complexity of the matrix. The identification of these products can be used as an indication for present and future diseases; however, many researchers focus on one variable or marker looking for specific biomarkers of disease. Therefore, the combination of genomics, transcriptomics, proteomics and metabonomics can give a detailed and complete insight into the gut environment. The proper sample collection, sample preparation and accurate analytical methods play a crucial role in generating precise microbial data and hypotheses in gut microbiome research, as well as multivariate data analysis in determining the gut microbiome functionality in regard to diseases. This review summarizes fecal sample protocols involved in profiling coeliac disease.

Screening of Potential Biomarkers for Gastric Cancer with Diagnostic Value Using Label-free Global Proteome Analysis

Gastric cancer (GC) is known as a top malignant type of tumors worldwide. Despite the recent decrease in mortality rates, the prognosis remains poor. Therefore, it is necessary to find novel biomarkers with early diagnostic value for GC. In this study, we present a large-scale proteomic analysis of 30 GC tissues and 30 matched healthy tissues using label-free global proteome profiling. Our results identified 537 differentially expressed proteins, including 280 upregulated and 257 downregulated proteins. The ingenuity pathway analysis (IPA) results indicated that the sirtuin signaling pathway was the most activated pathway in GC tissues whereas oxidative phosphorylation was the most inhibited. Moreover, the most activated molecular function was cellular movement, including tissue invasion by tumor cell lines. Based on IPA results, 15 hub proteins were screened. Using the receiver operating characteristic curve, most of hub proteins showed a high diagnostic power in distinguishing between tumors and healthy controls. A four-protein (ATP5B-ATP5O-NDUFB4-NDUFB8) diagnostic signature was built using a random forest model. The area under the curve (AUC) values of this model were 0.996 and 0.886 for the training and testing sets, respectively, suggesting that the four-protein signature has a high diagnostic power. This signature was further tested with independent datasets using plasma enzyme-linked immune sorbent assays, resulting in an AUC value of 0.778 for distinguishing GC tissues from healthy controls, and using immunohistochemical tissue microarray analysis, resulting in an AUC value of 0.805. In conclusion, this study identifies potential biomarkers and improves our understanding of the pathogenesis, providing novel therapeutic targets for GC.

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.

Proteogenomic biomarkers in colorectal cancers: clinical applications

INTRODUCTION

Colorectal cancer (CRC) is one of the leading cancers in terms of incidence and mortality, rate requiring a multidisciplinary approach. The discovery of specific CRC biomarkers has caused a paradigm shift in its clinical management.

AREAS COVERED

The aim is to illustrate the possible clinical applications of CRC biomarkers through an updated literature review (from 2015 to 2020) based on the PubMed database. A relationship between cancer localization and genetic profile has been identified. Nowadays, the tumor markers are largely used to select patients that could really benefit from a specific type of adjuvant therapy, in order to optimize treatment programs, especially in metastatic patients. This review highlights both CRC biomarkers' advantages and critical issues.

EXPERT OPINION

New biomarker discoveries allow to set noninvasive tests that could increase patient's compliance with therapy. They also permit a cost-effective early diagnosis, as well as patient-tailored treatments, improving the overall survival. The CRC biomarkers could also have a prognostic value, and usually, they are included in follow-up programs. However, despite the continuous progression of new technologies, their clinical validation is still debated. In this context, additional clinical studies are still necessary to identify, among potential markers, the most effective ones.

Monoamine Oxidase B Expression Correlates with a Poor Prognosis in Colorectal Cancer Patients and Is Significantly Associated with Epithelial-to-Mesenchymal Transition-Related Gene Signatures

Monoamine oxidases (MAOs) including MAOA and MAOB are enzymes located on the outer membranes of mitochondria, which are responsible for catalyzing monoamine oxidation. Recently, increased level of MAOs were shown in several cancer types. However, possible roles of MAOs have not yet been elucidated in the progression and prognosis of colorectal carcinoma (CRC). We therefore analyzed the importance of MAOs in CRC by an in silico analysis and tissue microarrays. Several independent cohorts indicated that high expression of MAOB, but not MAOA, was correlated with a worse disease stage and poorer survival. In total, 203 colorectal adenocarcinoma cases underwent immunohistochemical staining of MAOs, and associations with clinicopathological parameters and patient outcomes were evaluated. We found that MAOB is highly expressed in CRC tissues compared to normal colorectal tissues, and its expression was significantly correlated with a higher recurrence rate and a poor prognosis. Moreover, according to the univariate and multivariate analyses, we found that MAOB could be an independent prognostic factor for overall survival and disease-free survival, and its prognostic value was better than T and N stage. Furthermore, significant positive and negative correlations of MAOB with mesenchymal-type and epithelial-type gene expressions were observed in CRC tissues. According to the highlighted characteristics of MAOB in CRC, MAOB can be used as a novel indicator to predict the progression and prognosis of CRC patients.

Proteomic investigations into resistance in colorectal cancer

Introduction: Despite advances in screening and treatment options, colorectal cancer (CRC) remains one of the most prevalent and lethal cancer subtypes. Resistance to cytotoxic or targeted therapy has remained a constant challenge to the treatment and long-term management of patients, attracting intense worldwide investigation since the 1950s. Through extensive investigations into the proteomic mechanisms and functions that convey resistance to therapy/s, researchers have become able to implicate alterations in several signaling pathways that provide and sustain resistance to treatment.Areas covered: In this review, we summarize how protein alterations are associated with resistance to therapy, with particular emphasis on CRC. An overview of the mechanisms of therapeutic resistance is described, highlighting recent studies which endeavor to elucidate the proteomic changes that are associated with the acquisition and promulgation of therapeutic resistance.Expert opinion: While cancers such as CRC have been intensively studied for decades, unresponsiveness and the resistance to therapy remain critical obstacles in the treatment of patients. Due to the inherent biological and clinical heterogeneity of individual CRCs, proteomic methods stand to become powerful tools to provide biological insights that may guide therapeutic strategies with the ultimate goal of refining emergent immunotherapeutic treatments.

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.

In-Depth Characterization of Mass Spectrometry-Based Proteomic Profiles Revealed Novel Signature Proteins Associated with Liver Metastatic Colorectal Cancers

Liver metastasis is the most common form of metastatic colorectal cancers during the course of the disease. The global change in protein abundance in liver metastatic colorectal cancers and its role in metastasis establishment have not been comprehensively analyzed. In the present study, fresh-frozen tissue samples including normal colon/localized/liver metastatic CRCs from each recruited patient were analyzed by quantitative proteomics using a multiplexed TMT labeling strategy. Around 5000 protein groups were quantified from all samples. The proteomic profile of localized/metastatic CRCs varied greatly from that of normal colon tissues; differential proteins were mainly from extracellular regions and participate in immune activities, which is crucial for the chronic inflammation signaling pathways in the tumor microenvironment. Further statistical analysis revealed 47 proteins exhibiting statistical significance between localized and metastatic CRCs, of which FILI1P1 and PLG were identified for the first time in proteomic data, which were highly associated with liver metastasis in CRCs.

Investigating the Proteomic Profile of HT-29 Colon Cancer Cells After Lactobacillus kefiri SGL 13 Exposure Using the SWATH Method

Despite some studies revealed that kefir acts on different cancers, such as colorectal cancer, the proteomic changes that occur in the colon cancer cells remain to be explored. In this study, the proteomic analysis was combined with determination of kefir characteristics (e.g., adhesion capacity, gastrointestinal and antibiotic resistances), in order to confirm its use as a probiotic. Therefore, a label-free strategy based on SWATH-MS was applied to investigate the proteomic profile of HT-29 cells after exposure for 24 h to a specific strain of Lactobacillus kefiri named SGL 13. We identified a total of 60 differentially expressed proteins in HT-29 cells, among which most are located into the extracellular exosome, playing important/crucial roles in translation and cell adhesion, as indicated by the enrichment analysis. The eIF2 and retinoid X receptor activation pathways appeared to be correlated with the anti-tumoral effect of SGL 13. Immunoblot analysis showed an increase in Bax and a decrease in caspase 3 and mutant p53, and ELISA assay revealed inhibition of IL-8 secretion from HT-29 cells stimulated with LPS upon SGL 13 treatment, suggesting pro-apoptotic and anti-inflammatory properties of kefir. In conclusion, the results of this study, the first of its kind using co-culture of kefir and colon cancer cells, demonstrate that L. kefiri SGL 13 possesses probiotic potency and contribute to elucidate the molecular mechanisms involved in the L. kefiri-colon cancer cell interactions.