iTRAQ analysis of colorectal cancer cell lines suggests Drebrin (DBN1) is overexpressed during liver metastasis

Molecular Pathways, Targeted Therapies, and Proteomic Investigations of Colorectal Cancer

According to the GLOBOCAN 2020 data, colorectal cancer is the third most commonly diagnosed cancer and the second leading cause of cancer-related death. The risk factors for colorectal cancer include a diet abundant with fat, refined carbohydrates, animal protein, low fiber content, alcoholism, obesity, long-term cigarette smoking, low physical activity, and aging. Colorectal carcinomas are classified as adenocarcinoma, neuroendocrine, squamous cell, adenosquamous, spindle cell, and undifferentiated carcinomas. In addition, many variants of colorectal carcinomas have been recently distinguished based on histological, immunological, and molecular characteristics. Recently developed targeted molecules in conjunction with standard chemotherapeutics or immune checkpoint inhibitors provide promising treatment protocols for colorectal cancer. However, the benefit of targeted therapies is strictly dependent on the mutational status of signaling molecules (e.g., KRAS) or mismatch repair systems. Here it is aimed to provide a comprehensive view of colorectal cancer types, molecular pathways associated, recently developed targeted therapies, as well as proteomic investigations applied to colorectal cancer for the discovery of novel biomarkers and new targets for treatment protocols.

Drebrin promotes lung adenocarcinoma cell migration through inducing integrin β1 endocytosis

Lung adenocarcinoma (LUAD) is the most common type of lung cancers, which remains the leading cause of cancer-related death worldwide. Drebrin can promote cell migration and invasion with poor prognosis, but its roes in LUAD tumor progression remains unknown. We showed that the expression of Drebrin was upregulated in clinical LUAD samples. A Kaplan-Meier survival analysis showed that a high expression of Drebrin predicated poor prognosis in LUAD. In vitro, Drebrin promoted anchorage-independent growth and migration of LUAD cells. Drebrin interacted with dynamin through CT domain, and served as an adaptor to promote LUAD cell migration through inducing integrin β1 endocytosis. Thus, this study demonstrated the critical role of Drebrin in LUAD and associated mechanism.

Upregulation of long noncoding RNA W42 promotes tumor development by binding with DBN1 in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a malignancy found globally. Accumulating studies have shown that long noncoding RNAs (lncRNAs) play critical roles in HCC. However, the function of lncRNA in HCC remains poorly understood.

AIM

To understand the effect of lncRNA W42 on HCC and dissect the underlying molecular mechanisms.

METHODS

We measured the expression of lncRNA W42 in HCC tissues and cells (Huh7 and SMMC-7721) by quantitative reverse transcriptase polymerase chain reaction. Receiver operating characteristic curves were used to assess the sensitivity and specificity of lncRNA W42 expression. HCC cells were transfected with pcDNA3.1-lncRNA W42 or shRNA-lncRNA W42. Cell functions were detected by cell counting Kit-8 (CCK-8), colony formation, flow cytometry and Transwell assays. The interaction of lncRNA W42 and DBN1 was confirmed by RNA immunoprecipitation and RNA pull down assays. An HCC xenograft model was used to assess the role of lncRNA W42 on tumor growth in vivo. The Kaplan-Meier curve was used to evaluate the overall survival and recurrence-free survival after surgery in patients with HCC.

RESULTS

In this study, we identified a novel lncRNA (lncRNA W42), and investigated its biological functions and clinical significance in HCC. LncRNA W42 expression was upregulated in HCC tissues and cells. Overexpression of lncRNA W42 notably promoted the proliferative and invasion of HCC, and inhibited cell apoptosis. LncRNA W42 directly bound to DBN1 and activated the downstream pathway. LncRNA W42 knockdown suppressed HCC xenograft tumor growth in vivo. The clinical investigation revealed that HCC patients with high lncRNA W42 expression exhibited shorter survival times.

CONCLUSION

In vitro and in vivo results suggested that the novel lncRNA W42, which is upregulated in HCC, may serve as a potential candidate prognostic biomarker and therapeutic target in HCC patients.

Coexpressed Genes That Promote the Infiltration of M2 Macrophages in Melanoma Can Evaluate the Prognosis and Immunotherapy Outcome

Purpose

To improve immunotherapy efficacy for melanoma, a coexpression network and key genes of M2 macrophages in melanoma were explored. A prognostic risk assessment model was established for M2-related coexpressed genes, and the role of M2 macrophages in the immune microenvironment of melanoma was elucidated.

Method

We obtained mRNA data from melanoma and peritumor tissue samples from The Cancer Genome Atlas-skin cutaneous melanoma (TCGA-SKCM). Then, we used CIBERSORT to calculate the proportion of M2 macrophage cells. A coexpression module most related to M2 macrophages in TCGA-SKCM was determined by analyzing the weighted gene coexpression network, and a coexpression network was established. After survival analysis, factors with significant results were incorporated into a Cox regression analysis to establish a model. The model's essential genes were analyzed using functional enrichment, GSEA, and subgroup and total carcinoma. Finally, external datasets GSE65904 and GSE78220 were used to verify the prognostic risk model.

Results

The yellow-green module was the coexpression module most related to M2 macrophages in TCGA-SKCM; NOTCH3, DBN1, KDELC2, and STAB1 were identified as the essential genes that promoted the infiltration of M2 macrophages in melanoma. These genes are concentrated in antigen treatment and presentation, chemokine, cytokine, the T cell receptor pathway, and the IFN-γ pathway. These factors were analyzed for survival, and factors with significant results were included in a Cox regression analysis. According to the methods, a model related to M2-TAM coexpressed gene was established, and the formula was risk score = 0.25^∗NOTCH3 + 0.008^∗ DBN1 − 0.031^∗KDELC2 − 0.032^∗STAB1. The new model was used to perform subgroup evaluation and external queue validation. The results showed good prognostic ability.

Conclusion

We proposed a Cox proportional hazards regression model associated with coexpression genes of melanoma M2 macrophages that may provide a measurement method for generating prognosis scores in patients with melanoma. Four genes coexpressed with M2 macrophages were associated with high levels of infiltration of M2 macrophages. Our findings may provide significant candidate biomarkers for the treatment and monitoring of melanoma.

Integrated Analysis of Key Differentially Expressed Genes Identifies DBN1 as a Predictive Marker of Response to Endocrine Therapy in Luminal Breast Cancer

Endocrine therapy is the mainstay of adjuvant treatment for patients with luminal breast cancer. Despite ongoing advances in endocrine therapy to date, a proportion of patients ultimately develop endocrine resistance, resulting in failure of therapy and poor prognosis. Therefore, as part of the growing concept of personalised medicine, the need for identification of predictive markers of endocrine therapy response at an early stage, is recognised. The METABRIC series was used to identify differentially expressed genes (DEGs) in term of response to adjuvant endocrine therapy. Drebrin 1 (DBN1) was identified as a key DEG associated with response to hormone treatment. Next, large, well-characterised cohorts of primary luminal breast cancer with long-term follow-up were assessed at the mRNA and protein levels for the value of DBN1 as a prognostic marker in luminal breast cancer, as well as its potential for predicting the benefit of endocrine therapy. DBN1 positivity was associated with aggressive clinicopathological variables and poor patient outcomes. Importantly, high DBN1 expression predicted relapse patients who were subject to adjuvant endocrine treatment. Our results further demonstrate that DBN1 is an independent prognostic marker in luminal breast cancer. Its association with the response to endocrine therapy and outcome provides evidence for DBN1 as a potential biomarker in luminal breast cancer, particularly for the benefit of endocrine treatment. Further functional investigations into the mechanisms underlying sensitivity to endocrine therapy is required.

Prognostic values of a novel multi-mRNA signature for predicting relapse of cholangiocarcinoma

Cholangiocarcinoma (CCA) is an epithelial cancer and has high death and recurrence rates, current methods cannot satisfy the need for predicting cancer relapse effectively. So, we aimed at conducting a multi-mRNA signature to improve the relapse prediction of CCA. We analyzed mRNA expression profiling in large CCA cohorts from the Gene Expression Omnibus (GEO) database (GSE76297, GSE32879, GSE26566, GSE31370, and GSE45001) and The Cancer Genome Atlas (TCGA) database. The Least absolute shrinkage and selection operator (LASSO) regression model was used to establish a 7-mRNA-based signature that was significantly related to the recurrence-free survival (RFS) in two test series. Based on the 7-mRNA signature, the cohort TCGA patients could be divided into high-risk or low-risk subgroups with significantly different RFS [p < 0.001, hazard ratio (HR): 48.886, 95% confidence interval (CI): 6.226-3.837E+02]. Simultaneously, the prognostic value of the 7-mRNA signature was confirmed in clinical samples of Ren Ji hospital (p < 0.001, HR: 4.558, 95% CI: 1.829-11.357). Further analysis including multivariable and sub-group analyses revealed that the 7-mRNA signature was an independent prognostic value for recurrence of patients with CCA. In conclusion, our results might provide an efficient tool for relapse prediction and were beneficial to individualized management for CCA patients.

TFAP2A Induced ITPKA Serves as an Oncogene and Interacts with DBN1 in Lung Adenocarcinoma

The inositol polyphosphate kinase (IPK) family member ITPKA (inositol 1,4,5-trisphosphate 3-kinase) regulates the levels of many inositol polyphosphates which are important in cellular signaling. Several recent studies reported the aberrant expression of ITPKA in malignancy disease and usually made cancer more aggressive. However, the contribution of the inositol polyphosphate kinase ITPKA to lung cancer development remains unclear.

Here we report that ITPKA is overexpressed in lung adenocarcinoma (LUAD) and positively correlated with advanced clinical parameters. ITPKA contributes to the malignant phenotypes in-vitro. Mechanistically, ITPKA executed its action through the inducting of epithelial-mesenchymal transition (EMT) and interacting with Drebrin 1 (which is related to cancer metastasis). Moreover, the hyper-expression of ITPKA in LUAD is transcriptionally activated by the transcription factor TFAP2A. In survival analysis by using tissue microarray (TMA), we indicate that ITPKA is hyper-expressed in LUAD tissues compared to adjacent normal tissues, and increased expression of ITPKA is associated with poor prognosis.

Collectively, this study indicates that TFAP2A induced ITPKA hyperexpression promotes LUAD via interacting with Drebrin 1 and activating epithelial-mesenchymal transition (EMT). ITPKA might represent a potent candidate for the treatment and prognostic prediction of LUAD.

Simultaneous Interrogation of Cancer Omics to Identify Subtypes With Significant Clinical Differences

Recent advances in high-throughput sequencing have accelerated the accumulation of omics data on the same tumor tissue from multiple sources. Intensive study of multi-omics integration on tumor samples can stimulate progress in precision medicine and is promising in detecting potential biomarkers. However, current methods are restricted owing to highly unbalanced dimensions of omics data or difficulty in assigning weights between different data sources. Therefore, the appropriate approximation and constraints of integrated targets remain a major challenge. In this paper, we proposed an omics data integration method, named high-order path elucidated similarity (HOPES). HOPES fuses the similarities derived from various omics data sources to solve the dimensional discrepancy, and progressively elucidate the similarities from each type of omics data into an integrated similarity with various high-order connected paths. Through a series of incremental constraints for commonality, HOPES can take both specificity of single data and consistency between different data types into consideration. The fused similarity matrix gives global insight into patients' correlation and efficiently distinguishes subgroups. We tested the performance of HOPES on both a simulated dataset and several empirical tumor datasets. The test datasets contain three omics types including gene expression, DNA methylation, and microRNA data for five different TCGA cancer projects. Our method was shown to achieve superior accuracy and high robustness compared with several benchmark methods on simulated data. Further experiments on five cancer datasets demonstrated that HOPES achieved superior performances in cancer classification. The stratified subgroups were shown to have statistically significant differences in survival. We further located and identified the key genes, methylation sites, and microRNAs within each subgroup. They were shown to achieve high potential prognostic value and were enriched in many cancer-related biological processes or pathways.

Risk assessment model constructed by differentially expressed lncRNAs for the prognosis of glioma

A risk assessment model was constructed using differentially expressed long non‑coding (lnc)RNAs for the prognosis of glioma. Transcriptome sequencing of the lncRNAs and mRNAs from glioma samples were obtained from the TCGA database. The samples were divided into bad and good prognosis groups based on survival time, then differently expressed lncRNAs between these two groups were screened using DEseq and edgeR packages. Multivariate Cox regression analysis was performed to establish a risk assessment system according to the weighted regression coefficient of lncRNA expression. Survival analysis and receiver operating characteristic curve were conducted for the risk assessment model. Furthermore, the co‑expression network of the screened lncRNAs was constructed, followed by the functional enrichment analysis for associated genes. A total of 117 lncRNAs were screened using edgeR and DEseq packages. Among all differently expressed lncRNAs, five lncRNAs (RP3‑503A6, LINC00940, RP11‑453M23, AC009411 and CDRT7) were identified to establish the risk assessment model. The risk assessment model demonstrated a good prognostic function with high area under the curve values in the training, validation and entire sets. The risk score was certified as an independent prognostic factor for gliomas. Multiple genes were screened to be co‑expressed with these five lncRNAs. Functional enrichment analysis demonstrated that they were involved in cytoskeleton, adhesion and Janus kinase/signal transducer and activator of transcription signaling pathway‑associated processes. The present study established a risk assessment model integrating five significantly different expressed lncRNAs, which may help to assess the prognosis of patients with glioma with increased accuracy.

The drebrin/EB3 pathway drives invasive activity in prostate cancer

Prostate cancer is the most common cancer in men and the metastatic form of the disease is incurable. We show here that the drebrin/EB3 pathway, which co-ordinates dynamic microtubule/actin filament interactions underlying cell shape changes in response to guidance cues, plays a role in prostate cancer cell invasion. Drebrin expression is restricted to basal epithelial cells in benign human prostate but is upregulated in luminal epithelial cells in foci of prostatic malignancy. Drebrin is also upregulated in human prostate cancer cell lines and co-localizes with actin filaments and dynamic microtubules in filopodia of pseudopods of invading cells under a chemotactic gradient of the chemokine CXCL12. Disruption of the drebrin/EB3 pathway using BTP2, a small molecule inhibitor of drebrin binding to actin filaments, reduced the invasion of prostate cancer cell lines in 3D in vitro assays. Furthermore, gain- or loss-of-function of drebrin or EB3 by over-expression or siRNA-mediated knockdown increases or decreases invasion of prostate cancer cell lines in 3D in vitro assays, respectively. Finally, expression of a dominant-negative construct that competes with EB3 binding to drebrin, also inhibited invasion of prostate cancer cell lines in 3D in vitro assays. Our findings show that co-ordination of dynamic microtubules and actin filaments by the drebrin/EB3 pathway drives prostate cancer cell invasion and is therefore implicated in disease progression.

Biomarker discovery by proteomics-based approaches for early detection and personalized medicine in colorectal cancer

About one million people per year develop colorectal cancer (CRC) and approximately half of them die. The extent of the disease (i.e. local invasion at the time of diagnosis) is a key prognostic factor. The 5-year survival rate is almost 90% in the case of delimited CRC and 10% in the case of metastasized CRC. Hence, one of the great challenges in the battle against CRC is to improve early diagnosis strategies. Large-scale proteomic approaches are widely used in cancer research to search for novel biomarkers. Such biomarkers can help in improving the accuracy of the diagnosis and in the optimization of personalized therapy. Herein, we provide an overview of studies published in the last 5 years on CRC that led to the identification of protein biomarkers suitable for clinical application by using proteomic approaches. We discussed these findings according to biomarker application, including also the role of protein phosphorylation and cancer stem cells in biomarker discovery. Our review provides a cross section of scientific approaches and can furnish suggestions for future experimental strategies to be used as reference by scientists, clinicians and researchers interested in proteomics for biomarker discovery.

Homer, Spikar, and Other Drebrin-Binding Proteins in the Brain

Drebrin is a major F-actin-binding protein in the brain. In the past two decades, many drebrin-binding proteins in addition to F-actin have been identified in several research fields including neuroscience, oncology, and immunology. Among the drebrin-binding proteins, there are various kinds of proteins including scaffold proteins, nuclear proteins, phosphatases, microtubule-binding proteins, G-actin-binding proteins, gap junction proteins, chemokine receptors, and cell-adhesion-related proteins. The interaction between drebrin and its binding partners seems to play important roles in higher brain functions, because drebrin is involved in the pathogenesis of some neurological diseases with cognitive defects. In this chapter, we will first review the interaction of Homer and spikar with drebrin, particularly focusing on spine morphogenesis and synaptic function. Homer contributes to spine morphogenesis by cooperating with shank and activated Cdc42 small GTPase, suggesting a novel signaling pathway comprising Homer, drebrin, shank, and Cdc42 for spine morphogenesis. Drebrin sequesters spikar in the cytoplasm and stabilizes it in dendritic spines, leading to spine formation. Finally, we will introduce some other drebrin-binding proteins including end-binding protein 3 (EB3), profilin, progranulin, and phosphatase and tensin homologue (PTEN). These proteins are involved in Alzheimer's disease and cancer. Therefore, further studies on drebrin and its binding proteins will be of great importance to elucidate the pathologies of various diseases and may contribute to their medical treatment and diagnostics development.

Drebrin at Junctional Plaques

Adhesion, segregation, and cellular plasticity are regulated by actin filaments anchored at the plaques of adherens junctions, sites of mechanical stabilization, and interfaces of multiple signaling networks. Drebrins were originally identified in neuronal cells, but the isoform drebrin E was also detected at adherens junctions of a wide range of non-neuronal cells, including polarized epithelia, endothelia, and fibroblasts. Here the protein is enriched at actin filament bundles associated with junctional plaques. Polarized epithelial cells contain two types of actin-associated complexes, one comprising drebrin but not vinculin and the other involving vinculin, but not drebrin. At gap junctions drebrin interacts with connexin 43, stabilizes this protein at membranes, and links it to the actin cytoskeleton. In vivo drebrin is widespread in diverse non-neuronal tissues of epithelial, endothelial, and smooth muscle origin, but not ubiquitous. In intestinal cells it is involved in cell compaction, linking of actin filaments to microtubules and formation and stabilization of the terminal web. Upregulation of drebrin was noted in several types of cancers, e.g., basal cell carcinomas for which it may serve as marker, liver metastases of colon carcinomas, and bladder cancer, suggesting that it is involved in regulating actin dynamics during tumor development, progression, and metastasis.

Cofilin-1 and Other ADF/Cofilin Superfamily Members in Human Malignant Cells

Identification of actin-depolymerizing factor homology (ADF-H) domains in the structures of several related proteins led first to the formation of the ADF/cofilin family, which then expanded to the ADF/cofilin superfamily. This superfamily includes the well-studied cofilin-1 (Cfl-1) and about a dozen different human proteins that interact directly or indirectly with the actin cytoskeleton, provide its remodeling, and alter cell motility. According to some data, Cfl-1 is contained in various human malignant cells (HMCs) and is involved in the formation of malignant properties, including invasiveness, metastatic potential, and resistance to chemotherapeutic drugs. The presence of other ADF/cofilin superfamily proteins in HMCs and their involvement in the regulation of cell motility were discovered with the use of various OMICS technologies. In our review, we discuss the results of the study of Cfl-1 and other ADF/cofilin superfamily proteins, which may be of interest for solving different problems of molecular oncology, as well as for the prospects of further investigations of these proteins in HMCs.

Drebrin: A new oncofetal biomarker associated with prognosis of lung adenocarcinoma

OBJECTIVES

With the aim of searching for novel oncofetal tumor biomarkers of lung adenocarcinoma other than carcinoembryonic antigen (CEA) and alpha-fetoprotein (AFP), we developed a strategy involving monoclonal antibodies generated from embryonic tissue of miniature swine.

MATERIALS AND METHODS

Using immunohistochemistry, we selected suitable hybridoma clones that were reactive against swine fetal lung but not adult lung using tissue microarray loading of human normal lung, lung cancer, and fetal and adult swine tissues.

RESULTS

The selected clones included several that were uniquely reactive against both swine fetal lung and human lung adenocarcinoma, and protein microarray revealed that the antigen they recognized was "drebrin" (DBN1). We then examined the association between the pattern of drebrin expression and the clinicopathological characteristics of lung adenocarcinoma using surgically resected samples of human lung adenocarcinoma. Two hundred formalin-fixed and paraffin-embedded tumor samples were immunostained for drebrin using clone B246, one of the clones that were reactive against drebrin. The cases were divided into those with strong (n=85) and weak (n=115) drebrin expression. In terms of disease-free survival, cases showing strong drebrin expression had a significantly poorer prognosis than those with weak drebrin expression (p=0.033).

CONCLUSION

The present findings indicate that "drebrin" is a unique oncofetal protein that can be applied as a new biomarker of lung adenocarcinoma.

Analysis of colorectal cancer glyco-secretome identifies laminin β-1 (LAMB1) as a potential serological biomarker for colorectal cancer

The high mortality rate in colorectal cancer is mostly ascribed to metastasis, but the only clinical biomarker available for disease monitoring and prognosis is the carcinoembryonic antigen (CEA). However, the prognostic utility of CEA remains controversial. In an effort to identify novel biomarkers that could be potentially translated for clinical use, we collected the secretomes from the colon adenocarcinoma cell line HCT-116 and its metastatic derivative, E1, using the hollow fiber culture system, and utilized the multilectin affinity chromatography approach to enrich for the secreted glycoproteins (glyco-secretome). The HCT-116 and E1 glyco-secretomes were compared using the label-free quantitative SWATH-MS technology, and a total of 149 glycoproteins were differentially secreted in E1 cells. Among these glycoproteins, laminin β-1 (LAMB1), a glycoprotein not previously known to be secreted in colorectal cancer cells, was observed to be oversecreted in E1 cells. In addition, we showed that LAMB1 levels were significantly higher in colorectal cancer patient serum samples as compared to healthy controls when measured using ELISA. ROC analyses indicated that LAMB1 performed better than CEA at discriminating between colorectal cancer patients from controls. Moreover, the diagnostic performance was further improved when LAMB1 was used in combination with CEA.

Tumor size, stage and grade alterations of urinary peptidome in RCC

Background

Several promising biomarkers have been found for RCC, but none of them has been used in clinical practice for predicting tumour progression. The most widely used features for predicting tumour aggressiveness still remain the cancer stage, size and grade. Therefore, the aim of our study is to investigate the urinary peptidome to search and identify peptides whose concentrations in urine are linked to tumour growth measure and clinical data.

Methods

A proteomic approach applied to ccRCC urinary peptidome (n = 117) based on prefractionation with activated magnetic beads followed by MALDI-TOF profiling was used. A systematic correlation study was performed on urinary peptide profiles obtained from MS analysis. Peptide identity was obtained by LC–ESI–MS/MS.

Results

Fifteen, twenty-six and five peptides showed a statistically significant alteration of their urinary concentration according to tumour size, pT and grade, respectively. Furthermore, 15 and 9 signals were observed to have urinary levels statistically modified in patients at different pT or grade values, even at very early stages. Among them, C1RL, A1AGx, ZAG2G, PGBM, MMP23, GP162, ADA19, G3P, RSPH3, DREB, NOTC2 SAFB2 and CC168 were identified.

Conclusions

We identified several peptides whose urinary abundance varied according to tumour size, stage and grade. Among them, several play a possible role in tumorigenesis, progression and aggressiveness. These results could be a useful starting point for future studies aimed at verifying their possible use in the managements of RCC patients.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-015-0693-8) contains supplementary material, which is available to authorized users.

Quantitative proteomic analysis of paired colorectal cancer and non-tumorigenic tissues reveals signature proteins and perturbed pathways involved in CRC progression and metastasis

Modern proteomics has proven instrumental in our understanding of the molecular deregulations associated with the development and progression of cancer. Herein, we profile membrane-enriched proteome of tumor and adjacent normal tissues from eight CRC patients using label-free nanoLC-MS/MS-based quantitative proteomics and advanced pathway analysis. Of the 948 identified proteins, 184 proteins were differentially expressed (P<0.05, fold change>1.5) between the tumor and non-tumor tissue (69 up-regulated and 115 down-regulated in tumor tissues). The CRC tumor and non-tumor tissues clustered tightly in separate groups using hierarchical cluster analysis of the differentially expressed proteins, indicating a strong CRC-association of this proteome subset. Specifically, cancer associated proteins such as FN1, TNC, DEFA1, ITGB2, MLEC, CDH17, EZR and pathways including actin cytoskeleton and RhoGDI signaling were deregulated. Stage-specific proteome signatures were identified including up-regulated ribosomal proteins and down-regulated annexin proteins in early stage CRC. Finally, EGFR(+) CRC tissues showed an EGFR-dependent down-regulation of cell adhesion molecules, relative to EGFR(-) tissues. Taken together, this study provides a detailed map of the altered proteome and associated protein pathways in CRC, which enhances our mechanistic understanding of CRC biology and opens avenues for a knowledge-driven search for candidate CRC protein markers.