Colorectal cancer atlas: An integrative resource for genomic and proteomic annotations from colorectal cancer cell lines and tissues

Transcriptomic correlates of cell cycle checkpoints with distinct prognosis, molecular characteristics, immunological regulation, and therapeutic response in colorectal adenocarcinoma

Backgrounds

Colorectal adenocarcinoma (COAD), accounting for the most common subtype of colorectal cancer (CRC), is a kind of malignant digestive tumor. Some cell cycle checkpoints (CCCs) have been found to contribute to CRC progression, whereas the functional roles of a lot of CCCs, especially the integrated role of checkpoint mechanism in the cell cycle, remain unclear.

Materials and methods

The Genomic Data Commons (GDC) The Cancer Genome Atlas (TCGA) COAD cohort was retrieved as the training dataset, and GSE24551 and GSE29623 were downloaded from Gene Expression Omnibus (GEO) as the validation datasets. A total of 209 CCC-related genes were derived from the Gene Ontology Consortium and were subsequently enrolled in the univariate, multivariate, and least absolute shrinkage and selection operator (LASSO) Cox regression analyses, finally defining a CCC signature. Cell proliferation and Transwell assay analyses were utilized to evaluate the functional roles of signature-related CCCs. The underlying CCC signature, molecular characteristics, immune-related features, and therapeutic response were finally estimated. The Genomics of Drug Sensitivity in Cancer (GDSC) database was employed for the evaluation of chemotherapeutic responses.

Results

The aberrant gene expression of CCCs greatly contributed to COAD development and progression. Univariate Cox regression analysis identified 27 CCC-related genes significantly affecting the overall survival (OS) of COAD patients; subsequently, LASSO analysis determined a novel CCC signature. Noticeably, CDK5RAP2, MAD1L1, NBN, RGCC, and ZNF207 were first identified to be correlated with the prognosis of COAD, and it was proven that all of them were significantly correlated with the proliferation and invasion of HCT116 and SW480 cells. In TCGA COAD cohort, CCC signature robustly stratified COAD patients into high and low CCC score groups (median OS: 57.24 months vs. unreached, p< 0.0001), simultaneously, with the good AUC values for OS prediction at 1, 2, and 3 years were 0.74, 0.78, and 0.77. Furthermore, the prognostic capacity of the CCC signature was verified in the GSE24551 and GSE29623 datasets, and the CCC signature was independent of clinical features. Moreover, a higher CCC score always indicated worse OS, regardless of clinical features, histological subtypes, or molecular subgroups. Intriguingly, functional enrichment analysis confirmed the CCC score was markedly associated with extracellular, matrix and immune (chemokine)-related signaling, cell cycle-related signaling, and metabolisms. Impressively, a higher CCC score was positively correlated with a majority of chemokines, receptors, immunostimulators, and anticancer immunity, indicating a relatively immune-promoting microenvironment. In addition, GSE173839, GSE25066, GSE41998, and GSE194040 dataset analyses of the underlying CCC signature suggested that durvalumab with olaparib and paclitaxel, taxane-anthracycline chemotherapy, neoadjuvant cyclophosphamide/doxorubicin with ixabepilone or paclitaxel, and immunotherapeutic strategies might be suitable for COAD patients with higher CCC score. Eventually, the GDSC database analysis showed that lower CCC scores were likely to be more sensitive to 5-fluorouracil, bosutinib, gemcitabine, gefitinib, methotrexate, mitomycin C, and temozolomide, while patients with higher CCC score seemed to have a higher level of sensitivity to bortezomib and elesclomol.

Conclusion

The novel CCC signature exhibited a good ability for prognosis prediction for COAD patients, and the CCC score was found to be highly correlated with molecular features, immune-related characteristics, and therapeutic responses, which would greatly promote clinical management and precision medicine for COAD.

Age-stratified proteomic characteristics and identification of promising precise clinical treatment targets of colorectal cancer

Colorectal cancer (CRC) is an extremely lethal disease worldwide. However, the underlying pathogenesis remains unclear. This study aimed to reveal the distinct characteristics of age-stratified CRC at the protein level and explore precise treatment targets. Patients who underwent surgical removal with pathologically confirmed CRC at China-Japan Friendship Hospital from January 2020 to October 2021 were recruited, cancer and para-carcinoma tissues (> 5 cm) were detected by mass spectrometry. Ninety-six clinical samples were collected and divided into three groups according to age: young (≤ 50 years), middle-aged (51-69 years), and old (≥ 70 years). Quantitative proteomic analysis was performed, as well as comprehensive bioinformatic analysis based on the Human Protein Atlas, Clinical Proteomic Tumor Analysis Consortium and Connectivity Map databases. The numbers of upregulated and downregulated proteins were 1315 and 560 in the young group, 757 and 311 in the old group, and 1052 and 468 in the middle-aged group, respectively. Bioinformatic analysis showed that these differentially expressed proteins had different molecular functions and participated in extensive signaling pathways. We also revealed ADH1B, ARRDC1, GATM, GTF2H4, MGME1, and LILRB2 as possible cancer-promoting molecules, which might serve as potential prognostic biomarkers and precise therapeutic targets for CRC. SIGNIFICANCE: This study comprehensively characterized the proteomic profiles of age-stratified colorectal cancer patients, focusing on the differentially expressed proteins between cancer and paracancerous tissues in different age groups, in an effort to find corresponding potential prognostic biomarkers and therapeutic targets. In addition, this study provides potentially valuable clinical small molecule inhibitory agents.

In Silico Pipeline to Identify Tumor-Specific Antigens for Cancer Immunotherapy Using Exome Sequencing Data

Tumor-specific antigens or neoantigens are peptides that are expressed only in cancer cells and not in healthy cells. Some of these molecules can induce an immune response, and therefore, their use in immunotherapeutic strategies based on cancer vaccines has been extensively explored. Studies based on these approaches have been triggered by the current high-throughput DNA sequencing technologies. However, there is no universal nor straightforward bioinformatic protocol to discover neoantigens using DNA sequencing data. Thus, we propose a bioinformatic protocol to detect tumor-specific antigens associated with single nucleotide variants (SNVs) or "mutations" in tumoral tissues. For this purpose, we used publicly available data to build our model, including exome sequencing data from colorectal cancer and healthy cells obtained from a single case, as well as frequent human leukocyte antigen (HLA) class I alleles in a specific population. HLA data from Costa Rican Central Valley population was selected as an example. The strategy included three main steps: (1) pre-processing of sequencing data; (2) variant calling analysis to detect tumor-specific SNVs in comparison with healthy tissue; and (3) prediction and characterization of peptides (protein fragments, the tumor-specific antigens) derived from the variants, in the context of their affinity with frequent alleles of the selected population. In our model data, we found 28 non-silent SNVs, present in 17 genes in chromosome one. The protocol yielded 23 strong binders peptides derived from the SNVs for frequent HLA class I alleles for the Costa Rican population. Although the analyses were performed as an example to implement the pipeline, to our knowledge, this is the first study of an in silico cancer vaccine using DNA sequencing data in the context of the HLA alleles. It is concluded that the standardized protocol was not only able to identify neoantigens in a specific but also provides a complete pipeline for the eventual design of cancer vaccines using the best bioinformatic practices.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-022-00084-9.

Potentiating effect of reovirus on immune checkpoint inhibition in microsatellite stable colorectal cancer

The majority of colorectal cancers (CRCs) are microsatellite stable (MSS) and resistant to immunotherapy. The current study explores the possibility of using oncolytic reovirus to sensitize MSS CRC to immune checkpoint inhibition. While reovirus reduced metabolic activity among KRAS Mut cells, microarray/computational analysis revealed microsatellite status-oriented activation of immune-response pathways. Reovirus plus anti-PD-1 treatment increased cell death among MSS cells ex vivo. Reduced tumorigenicity and proliferative index, and increased apoptosis were evident among CT26 [MSS, KRAS Mut], but not in MC38 [microsatellite unstable/MSI, KRAS Wt] syngeneic mouse models under combinatorial treatment. PD-L1-PD-1 signaling axis were differentially altered among CT26/MC38 models. Combinatorial treatment activated the innate immune system, pattern recognition receptors, and antigen presentation markers. Furthermore, we observed the reduction of immunosuppressive macrophages and expansion of effector T cell subsets, as well as reduction in T cell exhaustion. The current investigation sheds light on the immunological mechanisms of the reovirus-anti-PD-1 combination to reduce the growth of MSS CRC.

Exosome Carrier Effects; Resistance to Digestion in Phagolysosomes May Assist Transfers to Targeted Cells; II Transfers of miRNAs Are Better Analyzed via Systems Approach as They Do Not Fit Conventional Reductionist Stoichiometric Concepts

Carrier effects of extracellular vesicles (EV) like exosomes refer to properties of the vesicles that contribute to the transferred biologic effects of their contents to targeted cells. This can pertain to ingested small amounts of xenogeneic plant miRNAs and oral administration of immunosuppressive exosomes. The exosomes contribute carrier effects on transfers of miRNAs by contributing both to the delivery and the subsequent functional intracellular outcomes. This is in contrast to current quantitative canonical rules that dictate just the minimum copies of a miRNA for functional effects, and thus successful transfers, independent of the EV carrier effects. Thus, we argue here that transfers by non-canonical minute quantities of miRNAs must consider the EV carrier effects of functional low levels of exosome transferred miRNA that may not fit conventional reductionist stoichiometric concepts. Accordingly, we have examined traditional stoichiometry vs. systems biology that may be more appropriate for delivered exosome functional responses. Exosome carrier properties discussed include; their required surface activating interactions with targeted cells, potential alternate targets beyond mRNAs, like reaching a threshold, three dimensional aspects of the RNAs, added EV kinetic dynamic aspects making transfers four dimensional, and unique intracellular release from EV that resist intracellular digestion in phagolysosomes. Together these EV carrier considerations might allow systems analysis. This can then result in a more appropriate understanding of transferred exosome carrier-assisted functional transfers. A plea is made that the miRNA expert community, in collaboration with exosome experts, perform new experiments on molecular and quantitative miRNA functional effects in systems that include EVs, like variation in EV type and surface constituents, delivery, dose and time to hopefully create more appropriate and truly current canonical concepts of the consequent miRNA functional transfers by EVs like exosomes.

Yusof NF, Mohd Yunos RI, Ishak M, Saidin S, Rose IM, Sagap I, Mazlan L, Mohd Azman ZA, Mazlan M, Ab Rahim S, Wan Ngah WZ, Nathan S, Hashim NAA, Mohamed-Hussein ZA, Jamal R. TCGA-My: A Systematic Repository for Systems Biology of Malaysian Colorectal Cancer

Colorectal cancer (CRC) ranks second among the most commonly occurring cancers in Malaysia, and unfortunately, its pathobiology remains unknown. CRC pathobiology can be understood in detail with the implementation of omics technology that is able to generate vast amounts of molecular data. The generation of omics data has introduced a new challenge for data organization. Therefore, a knowledge-based repository, namely TCGA-My, was developed to systematically store and organize CRC omics data for Malaysian patients. TCGA-My stores the genome and metabolome of Malaysian CRC patients. The genome and metabolome datasets were organized using a Python module, pandas. The variants and metabolites were first annotated with their biological information using gene ontologies (GOs) vocabulary. The TCGA-My relational database was then built using HeidiSQL PorTable 9.4.0.512, and Laravel was used to design the web interface. Currently, TCGA-My stores 1,517,841 variants, 23,695 genes, and 167,451 metabolites from the samples of 50 CRC patients. Data entries can be accessed via search and browse menus. TCGA-My aims to offer effective and systematic omics data management, allowing it to become the main resource for Malaysian CRC research, particularly in the context of biomarker identification for precision medicine.

CancerLivER: a database of liver cancer gene expression resources and biomarkers

Liver cancer is the fourth major lethal malignancy worldwide. To understand the development and progression of liver cancer, biomedical research generated a tremendous amount of transcriptomics and disease-specific biomarker data. However, dispersed information poses pragmatic hurdles to delineate the significant markers for the disease. Hence, a dedicated resource for liver cancer is required that integrates scattered multiple formatted datasets and information regarding disease-specific biomarkers. Liver Cancer Expression Resource (CancerLivER) is a database that maintains gene expression datasets of liver cancer along with the putative biomarkers defined for the same in the literature. It manages 115 datasets that include gene-expression profiles of 9611 samples. Each of incorporated datasets was manually curated to remove any artefact; subsequently, a standard and uniform pipeline according to the specific technique is employed for their processing. Additionally, it contains comprehensive information on 594 liver cancer biomarkers which include mainly 315 gene biomarkers or signatures and 178 protein- and 46 miRNA-based biomarkers. To explore the full potential of data on liver cancer, a web-based interactive platform was developed to perform search, browsing and analyses. Analysis tools were also integrated to explore and visualize the expression patterns of desired genes among different types of samples based on individual gene, GO ontology and pathways. Furthermore, a dataset matrix download facility was provided to facilitate the users for their extensive analysis to elucidate more robust disease-specific signatures. Eventually, CancerLivER is a comprehensive resource which is highly useful for the scientific community working in the field of liver cancer.Availability: CancerLivER can be accessed on the web at https://webs.iiitd.edu.in/raghava/cancerliver.

Identification of key candidate genes and pathways associated with colorectal aberrant crypt foci-to-adenoma-to-carcinoma progression

AIM

The present study aimed to detect key candidate genes and pathways involved in colorectal aberrant crypt foci-to-adenoma-to-carcinoma progression.

BACKGROUND

Although colorectal cancer (CRC) is the third most common type of cancer, the involved signaling pathways and driver-genes remain largely unclear. CRC begins with the malignant transformation of precancerous lesions including aberrant crypt foci (ACF) and benign adenomatous polyp or adenoma.

METHODS

A list of formerly reported ACF, adenoma, and CRC-associated proteins was obtained from GeneCards, and then the data in online David Bioinformatics Resources was analyzed. The protein-protein interactions were surveyed utilizing String database and Cytoscape software. After hubs and bottlenecks were recognized, the key genes and pathways were identified through different bioinformatics analysis.

RESULTS

The most important pathways associated with colorectal aberrant crypt foci-to-adenoma progression were attributed to "pathways in cancer" and "chemokine signaling pathway" and those in adenoma-to-carcinoma progression were related to "pathways in cancer," "chemokine signaling pathway," and "Ras signaling pathway." The genes participating in these pathways are key ones. Furthermore, PRKACB, CUL2, and GSK3B were significant as the seed in the clusters related to adenoma and GNB1, RALBP1, ROCK1, and IKBKG in the clusters related to cancer.

CONCLUSION

The key candidate genes and pathways in progress CRC formed precursor lesions were identified by integrated bioinformatics analysis. The results could lead to a better understanding of the cause and underlying molecular events as well as detection of therapeutic targets for CRC.

Clustering of Tir during enteropathogenic E. coli infection triggers calcium influx-dependent pyroptosis in intestinal epithelial cells

Clustering of the enteropathogenic Escherichia coli (EPEC) type III secretion system (T3SS) effector translocated intimin receptor (Tir) by intimin leads to actin polymerisation and pyroptotic cell death in macrophages. The effect of Tir clustering on the viability of EPEC-infected intestinal epithelial cells (IECs) is unknown. We show that EPEC induces pyroptosis in IECs in a Tir-dependent but actin polymerisation-independent manner, which was enhanced by priming with interferon gamma (IFNγ). Mechanistically, Tir clustering triggers rapid Ca2+ influx, which induces lipopolysaccharide (LPS) internalisation, followed by activation of caspase-4 and pyroptosis. Knockdown of caspase-4 or gasdermin D (GSDMD), translocation of NleF, which blocks caspase-4 or chelation of extracellular Ca2+, inhibited EPEC-induced cell death. IEC lines with low endogenous abundance of GSDMD were resistant to Tir-induced cell death. Conversely, ATP-induced extracellular Ca2+ influx enhanced cell death, which confirmed the key regulatory role of Ca2+ in EPEC-induced pyroptosis. We reveal a novel mechanism through which infection with an extracellular pathogen leads to pyroptosis in IECs.

A High-Resolution Mass Spectrometry-Based Quantitative Metabolomic Workflow Highlights Defects in 5-Fluorouracil Metabolism in Cancer Cells with Acquired Chemoresistance

Currently, 5-fluorouracil (5-FU)-based combination chemotherapy is the mainstay in the treatment of metastatic colorectal cancer (CRC), which benefits approximately 50% of the patients. However, these tumors inevitably acquire chemoresistance resulting in treatment failure. The molecular mechanisms driving acquired chemotherapeutic drug resistance in CRC is fundamental for the development of novel strategies for circumventing resistance. However, the specific phenomenon that drives the cancer cells to acquire resistance is poorly understood. Understanding the molecular mechanisms that regulate chemoresistance will uncover new avenues for the treatment of CRC. Among the various mechanisms of acquired chemoresistance, defects in the drug metabolism pathways could play a major role. In the case of 5-FU, it gets converted into various active metabolites, which, directly or indirectly, interferes with the replication and transcription of dividing cells causing DNA and RNA damage. In this project, we developed a high-resolution mass spectrometry-based method to effectively extract and quantify levels of the 5-FU metabolites in cell lysates and media of parental and 5-FU resistant LIM1215 CRC cells. The analysis highlighted that the levels of 5-FU metabolites are significantly reduced in 5-FU resistant cells. Specifically, the level of the nucleotide fluorodeoxyuridine monophosphate (FdUMP) is reduced with treatment of 5-FU clarifying the compromised 5-FU metabolism in resistant cells. Corroborating the metabolomic analysis, treatment of the resistant cells with FdUMP, an active metabolite of 5-FU, resulted in effective killing of the resistant cells. Overall, in this study, an effective protocol was developed for comparative quantitation of polar metabolites and nucleotide analogues from the adherent cells efficiently. Furthermore, the utility of FdUMP as an alternative for CRC therapy is highlighted.

Dynamic gene regulatory network reconstruction and analysis based on clinical transcriptomic data of colorectal cancer

Inferring dynamic regulatory networks that rewire at different stages is a reasonable way to understand the mechanisms underlying cancer development. In this study, we reconstruct the stage-specific gene regulatory networks (GRNs) for colorectal cancer to understand dynamic changes of gene regulations along different disease stages. We combined multiple sets of clinical transcriptomic data of colorectal cancer patients and employed a supervised approach to select initial gene set for network construction. We then developed a dynamical system-based optimization method to infer dynamic GRNs by incorporating mutual information-based network sparsification and a dynamic cascade technique into an ordinary differential equations model. Dynamic GRNs at four different stages of colorectal cancer were reconstructed and analyzed. Several important genes were revealed based on the rewiring of the reconstructed GRNs. Our study demonstrated that reconstructing dynamic GRNs based on clinical transcriptomic profiling allows us to detect the dynamic trend of gene regulation as well as reveal critical genes for cancer development which may be important candidates of master regulators for further experimental test.

Identification of Autophagy-Associated Biomarkers and Corresponding Regulatory Factors in the Progression of Colorectal Cancer

Autophagy is a self-degradation process that maintains homeostasis against stress in cells. Autophagy dysfunction plays a central role in the development of tumors, such as colorectal cancer (CRC). In this study, autophagy-related differentially expressed genes, their downstream functions, and upstream regulatory factors including RNA-binding proteins (RBP) involved in programmed cell death in the CRC were investigated. Transcription factors (TFs) and miRNAs have been shown to mainly regulate autophagy genes. Interestingly, we found that some of the RBP in the CRC, such as DDX17, SETDB1, and POLR3A, play an important regulatory role in maintaining autophagy at a basal level during growth by acting as TFs that regulate autophagy. Promoter methylations showed negative regulations on differentially expressed autophagy gene (DEAG), while copy number variations revealed a positive role in them. A proportional hazards regression analysis indicated that using autophagy-related prognostic signature can divide patients into high-risk and low-risk groups. Autophagy associated FDA-approved drugs were studied by a prognostic network. This would contribute to the identifications of new potential molecular therapeutic targets for CRC.

The proprotein convertase furin is a pro-oncogenic driver in KRAS and BRAF driven colorectal cancer

Mutations in KRAS and/or BRAF that activate the ERK kinase are frequently found in colorectal cancer (CRC) and drive resistance to targeted therapies. Therefore, the identification of therapeutic targets that affect multiple signaling pathways simultaneously is crucial for improving the treatment of patients with KRAS or BRAF mutations. The proprotein convertase furin activates several oncogenic protein precursors involved in the ERK-MAPK pathway by endoproteolytic cleavage. Here we show that genetic inactivation of furin suppresses tumorigenic growth, proliferation, and migration in KRAS or BRAF mutant CRC cell lines but not in wild-type KRAS and BRAF cells. In a mouse xenograft model, these KRAS or BRAF mutant cells lacking furin displayed reduced growth and angiogenesis, and increased apoptosis. Mechanistically, furin inactivation prevents the processing of various protein pecursors including proIGF1R, proIR, proc-MET, proTGF-β1 and NOTCH1 leading to potent and durable ERK-MAPK pathway suppression in KRAS or BRAF mutant cells. Furthermore, we identified genes involved in activating the ERK-MAPK pathway, such as PTGS2, which are downregulated in the KRAS or BRAF mutant cells after furin inactivation but upregulated in wild-type KRAS and BRAF cells. Analysis of human colorectal tumor samples reveals a positive correlation between enhanced furin expression and KRAS or BRAF expression. These results indicate that furin plays an important role in KRAS or BRAF-associated ERK-MAPK pathway activation and tumorigenesis, providing a potential target for personalized treatment.

Genomic variation as a marker of response to neoadjuvant therapy in locally advanced rectal cancer

There is variation in the responsiveness of locally advanced rectal cancer to neoadjuvant chemoradiation, from complete response to total resistance. This study compared genetic variation in rectal cancer patients who had a complete response to chemoradiation versus poor response, using tumor tissue samples sequenced with genomics analysis software. Rectal cancer patients treated with chemoradiation and proctectomy June 2006-March 2017 were grouped based on response to chemoradiation: those with no residual tumor after surgery (CR, complete responders, AJCC-CPR tumor grade 0, n = 8), and those with poor response (PR, AJCC-CPR tumor grade two or three on surgical resection, n = 8). We identified 195 variants in 83 genes in tissue specimens implicated in colorectal cancer biopathways. PR patients showed mutations in four genes not mutated in complete responders: KDM6A, ABL1, DAXX-ZBTB22, and KRAS. Ten genes were mutated only in the CR group, including ARID1A, PMS2, JAK1, CREBBP, MTOR, RB1, PRKAR1A, FBXW7, ATM C11orf65, and KMT2D, with specific discriminating variants noted in DMNT3A, KDM6A, MTOR, APC, and TP53. Although conclusions may be limited by small sample size in this pilot study, we identified multiple genetic variations in tumor DNA from rectal cancer patients who are poor responders to neoadjuvant chemoradiation, compared to complete responders.

A network view of microRNA and gene interactions in different pathological stages of colon cancer

BACKGROUND

Colon cancer is one of the common cancers in human. Although the number of annual cases has decreased drastically, prognostic screening and translational methods can be improved. Hence, it is critical to understand the molecular mechanisms of disease progression and prognosis.

RESULTS

In this study, we develop a new strategy for integrating microRNA and gene expression profiles together with clinical information toward understanding the regulation of colon cancer. Particularly, we use this approach to identify microRNA and gene expression networks that are specific to certain pathological stages. To demonstrate the application of our method, we apply this approach to identify microRNA and gene interactions that are specific to pathological stages of colon cancer in The Cancer Genome Atlas (TCGA) datasets.

CONCLUSIONS

Our results show that there are significant differences in network connections between miRNAs and genes in different pathological stages of colon cancer. These findings point to a hypothesis that these networks signify different roles of microRNA and gene regulation in the pathogenesis and tumorigenesis of colon cancer.

An in vivo RNAi screen uncovers the role of AdoR signaling and adenosine deaminase in controlling intestinal stem cell activity

Metabolites are increasingly appreciated for their roles as signaling molecules. To dissect the roles of metabolites, it is essential to understand their signaling pathways and their enzymatic regulations. From an RNA interference (RNAi) screen for regulators of intestinal stem cell (ISC) activity in the Drosophila midgut, we identified adenosine receptor (AdoR) as a top candidate gene required for ISC proliferation. We demonstrate that Ras/MAPK and Protein Kinase A (PKA) signaling act downstream of AdoR and that Ras/MAPK mediates the major effect of AdoR on ISC proliferation. Extracellular adenosine, the ligand for AdoR, is a small metabolite that can be released by various cell types and degraded in the extracellular space by secreted adenosine deaminase. Interestingly, down-regulation of adenosine deaminase-related growth factor A (Adgf-A) from enterocytes is necessary for extracellular adenosine to activate AdoR and induce ISC overproliferation. As Adgf-A expression and its enzymatic activity decrease following tissue damage, our study provides important insights into how the enzymatic regulation of extracellular adenosine levels under tissue-damage conditions facilitates ISC proliferation.

G-quadruplex located in the 5'UTR of the BAG-1 mRNA affects both its cap-dependent and cap-independent translation through global secondary structure maintenance

The anti-apoptotic BAG-1 protein isoforms are known to be overexpressed in colorectal tumors and are considered to be potential therapeutic targets. The isoforms are derived from alternative translation initiations occuring at four in-frame start codons of a single mRNA transcript. Its 5′UTR also contains an internal ribosome entry site (IRES) regulating the cap-independent translation of the transcript. An RNA G-quadruplex (rG4) is located at the 5′end of the BAG-1 5′UTR, upstream of the known cis-regulatory elements. Herein, we observed that the expression of BAG-1 isoforms is post-transcriptionally regulated in colorectal cancer cells and tumors, and that stabilisation of the rG4 by small molecules ligands reduces the expression of endogenous BAG-1 isoforms. We demonstrated a critical role for the rG4 in the control of both cap-dependent and independent translation of the BAG-1 mRNA in colorectal cancer cells. Additionally, we found an upstream ORF that also represses BAG-1 mRNA translation. The structural probing of the complete 5′UTR showed that the rG4 acts as a steric block which controls the initiation of translation at each start codon of the transcript and also maintains the global 5′UTR secondary structure required for IRES-dependent translation.

Extracellular vesicles containing oncogenic mutant β-catenin activate Wnt signalling pathway in the recipient cells

Mutations in β-catenin, especially at the residues critical for its degradation, render it constitutively active. Here, we show that mutant β-catenin can be transported via extracellular vesicles (EVs) and activate Wnt signalling pathway in the recipient cells. An integrative proteogenomic analysis identified the presence of mutated β-catenin in EVs secreted by colorectal cancer (CRC) cells. Follow-up experiments established that EVs released from LIM1215 CRC cells stimulated Wnt signalling pathway in the recipient cells with wild-type β-catenin. SILAC-based quantitative proteomics analysis confirmed the transfer of mutant β-catenin to the nucleus of the recipient cells. In vivo tracking of DiR-labelled EVs in mouse implanted with RKO CRC cells revealed its bio-distribution, confirmed the activation of Wnt signalling pathway in tumour cells and increased the tumour burden. Overall, for the first time, this study reveals that EVs can transfer mutant β-catenin to the recipient cells and promote cancer progression.

Inferring novel genes related to colorectal cancer via random walk with restart algorithm

Colorectal cancer (CRC) is the third most common type of cancer. In recent decades, genomic analysis has played an increasingly important role in understanding the molecular mechanisms of CRC. However, its pathogenesis has not been fully uncovered. Identification of genes related to CRC as complete as possible is an important way to investigate its pathogenesis. Therefore, we proposed a new computational method for the identification of novel CRC-associated genes. The proposed method is based on existing proven CRC-associated genes, human protein-protein interaction networks, and random walk with restart algorithm. The utility of the method is indicated by comparing it to the methods based on Guilt-by-association or shortest path algorithm. Using the proposed method, we successfully identified 298 novel CRC-associated genes. Previous studies have validated the involvement of the majority of these 298 novel genes in CRC-associated biological processes, thus suggesting the efficacy and accuracy of our method.

Locally advanced rectal cancer transcriptomic-based secretome analysis reveals novel biomarkers useful to identify patients according to neoadjuvant chemoradiotherapy response

Most patients with locally advanced rectal cancer (LARC) present incomplete pathological response (pIR) to neoadjuvant chemoradiotherapy (nCRT). Despite the efforts to predict treatment response using tumor-molecular features, as differentially expressed genes, no molecule has proved to be a strong biomarker. The tumor secretome analysis is a promising strategy for biomarkers identification, which can be assessed using transcriptomic data. We performed transcriptomic-based secretome analysis to select potentially secreted proteins using an in silico approach. The tumor expression profile of 28 LARC biopsies collected before nCRT was compared with normal rectal tissues (NT). The expression profile showed no significant differences between complete (pCR) and incomplete responders to nCRT. Genes with increased expression (pCR = 106 and pIR = 357) were used for secretome analysis based on public databases (Vesiclepedia, Human Cancer Secretome, and Plasma Proteome). Seventeen potentially secreted candidates (pCR = 1, pIR = 13 and 3 in both groups) were further investigated in two independent datasets (TCGA and GSE68204) confirming their over-expression in LARC and association with nCRT response (GSE68204). The expression of circulating amphiregulin and cMET proteins was confirmed in serum from 14 LARC patients. Future studies in liquid biopsies could confirm the utility of these proteins for personalized treatment in LARC patients.

Activation of Epithelial-Mesenchymal Transition and Altered β-Catenin Signaling in a Novel Indian Colorectal Carcinoma Cell Line

Colorectal cancer is the third major cause of cancer-related mortality worldwide. The upward trend in incidence and mortality rates, poor sensitivity to conventional therapies and a dearth of early diagnostic parameters pose a huge challenge in the management of colorectal cancer in India. Due to the high level of genetic diversity present in the Indian population, unraveling the genetic contributions toward pathogenesis is key for understanding the etiology of colorectal cancer and in reversing this trend. We have established a novel cell line, MBC02, from an Indian colorectal cancer patient and have carried out extensive molecular characterization to unravel the pathological alterations in this cell line. In-depth molecular analysis of MBC02 revealed suppression of E-cadherin expression, concomitant with overexpression of EMT related molecules, which manifested in the form of highly migratory and invasive cells. Loss of membrane-tethered E-cadherin released β-catenin from the adherens junction resulting in its cytoplasmic and nuclear accumulation and consequently, upregulation of c-Myc. MBC02 also showed dramatic transcriptional upregulation of β-catenin. Remarkably, we observed significantly elevated proteasome activity that perhaps co-evolved to compensate for the unnaturally high mRNA level of β-catenin to regulate the increased protein load. In addition, there was substantial misregulation of other clinically relevant signaling pathways that have clinical relevance in the pathogenesis of colorectal cancer. Our findings pave the way toward understanding the molecular differences that could define pathogenesis in cancers originating in the Indian population.

Post-translational modifications of prostaglandin-endoperoxide synthase 2 in colorectal cancer: An update

The biosynthesis of prostanoids is involved in both physiological and pathological processes. The expression of prostaglandin-endoperoxide synthase 2 (PTGS2; also known as COX-2) has been traditionally associated to the onset of several pathologies, from inflammation to cardiovascular, gastrointestinal and oncologic events. For this reason, the search of selective PTGS2 inhibitors has been a focus for therapeutic interventions. In addition to the classic non-steroidal anti-inflammatory drugs, selective and specific PTGS2 inhibitors, termed coxibs, have been generated and widely used. PTGS2 activity is less restrictive in terms of substrate specificity than the homeostatic counterpart PTGS1, and it accounts for the elevated prostanoid synthesis that accompanies several pathologies. The main regulation of PTGS2 occurs at the transcription level. In addition to this, the stability of the mRNA is finely regulated through the interaction with several cytoplasmic elements, ranging from specific microRNAs to proteins that control mRNA degradation. Moreover, the protein has been recognized to be the substrate for several post-translational modifications that affect both the enzyme activity and the targeting for degradation via proteasomal and non-proteasomal mechanisms. Among these modifications, phosphorylation, glycosylation and covalent modifications by reactive lipidic intermediates and by free radicals associated to the pro-inflammatory condition appear to be the main changes. Identification of these post-translational modifications is relevant to better understand the role of PTGS2 in several pathologies and to establish a correct analysis of the potential function of this protein in diseases progress. Finally, these modifications can be used as biomarkers to establish correlations with other parameters, including the immunomodulation dependent on molecular pathological epidemiology determinants, which may provide a better frame for potential therapeutic interventions.

dbDEPC 3.0: the database of differentially expressed proteins in human cancer with multi-level annotation and drug indication

Proteins are major effectors of biological functions, and differentially expressed proteins (DEPs) are widely reported as biomarkers in pathological mechanism, prognosis prediction as well as treatment targeting in cancer research. High-throughput technology of mass spectrometry (MS) has identified large amounts of DEPs in human cancers. Through mining published researches with detailed experiment information, dbDEPC was the first database aimed to provide a systematic resource for the storage and query of the DEPs generated by MS in cancer research. It was updated to dbDEPC 2.0 in 2012. Here, we provide another updated version of dbDEPC, with improvement of database contents and enhanced web interface. The current version of dbDEPC 3.0 contains 11 669 unique DEPs in 26 different cancer types. Multi-level annotations of DEPs have been firstly introduced this time, including cancer-related peptide amino acid variations, post-translational modifications and drug information. Moreover, these multi-level annotations can be displayed in the biological networks, which can benefit integrative analysis. Finally, an online enrichment analysis tool has been developed, to support a KEGG enrichment analysis and to browse the relationship among interested protein list and known DEPs in KEGG pathways. In summary, dbDEPC 3.0 provides a comprehensive resource for accessing integrated and highly annotated DEPs in human cancer.

Database URL: https://www.scbit.org/dbdepc3/index.php

The Cellosaurus, a Cell-Line Knowledge Resource

The Cellosaurus is a knowledge resource on cell lines. It aims to describe all cell lines used in biomedical research. Its scope encompasses both vertebrates and invertebrates. Currently, information for >100,000 cell lines is provided. For each cell line, it provides a wealth of information, cross-references, and literature citations. The Cellosaurus is available on the ExPASy server (https://web.expasy.org/cellosaurus/) and can be downloaded in a variety of formats. Among its many uses, the Cellosaurus is a key resource to help researchers identify potentially contaminated/misidentified cell lines, thus contributing to improving the quality of research in the life sciences.

The response to neoadjuvant chemoradiotherapy with 5-fluorouracil in locally advanced rectal cancer patients: a predictive proteomic signature

BACKGROUND

Colorectal cancer is the third most common and the fourth most lethal cancer in the world. In the majority of cases, patients are diagnosed at an advanced stage or even metastatic, thus explaining the high mortality. The standard treatment for patients with locally advanced non-metastatic rectal cancer is neoadjuvant radio-chemotherapy (NRCT) with 5-fluorouracil (5-FU) followed by surgery, but the resistance rate to this treatment remains high with approximately 30% of non-responders. The lack of evidence available in clinical practice to predict NRCT resistance to 5-FU and to guide clinical practice therefore encourages the search for biomarkers of this resistance.

METHODS

From twenty-three formalin-fixed paraffin-embedded (FFPE) biopsies performed before NRCT with 5-FU of locally advanced non-metastatic rectal cancer patients, we extracted and analysed the tumor proteome of these patients. From clinical data, we were able to classify the twenty-three patients in our cohort into three treatment response groups: non-responders (NR), partial responders (PR) and total responders (TR), and to compare the proteomes of these different groups.

RESULTS

We have highlighted 384 differentially abundant proteins between NR and PR, 248 between NR and TR and 417 between PR and TR. Among these proteins, we have identified many differentially abundant proteins identified as having a role in cancer (IFIT1, FASTKD2, PIP4K2B, ARID1B, SLC25A33: overexpressed in TR; CALD1, CPA3, B3GALT5, CD177, RIPK1: overexpressed in NR). We have also identified that DPYD, the main degradation enzyme of 5-FU, was overexpressed in NR, as well as several ribosomal and mitochondrial proteins also overexpressed in NR. Data are available via ProteomeXchange with identifier PXD008440.

CONCLUSIONS

From these retrospective study, we implemented a protein extraction protocol from FFPE biopsy to highlight protein differences between different response groups to RCTN with 5-FU in patients with locally advanced non-metastatic rectal cancer. These results will pave the way for a larger cohort for better sensitivity and specificity of the signature to guide decisions in the choice of treatment.

Somatic APC mosaicism and oligogenic inheritance in genetically unsolved colorectal adenomatous polyposis patients

Germline variants in the APC gene cause familial adenomatous polyposis. Inherited variants in MutYH, POLE, POLD1, NTHL1, and MSH3 genes and somatic APC mosaicism have been reported as alternative causes of polyposis. However, ~30-50% of cases of polyposis remain genetically unsolved. Thus, the aim of this study was to investigate the genetic causes of unexplained adenomatous polyposis. Eight sporadic cases with >20 adenomatous polyps by 35 years of age or >50 adenomatous polyps by 55 years of age, and no causative germline variants in APC and/or MutYH, were enrolled from a cohort of 56 subjects with adenomatous colorectal polyposis. APC gene mosaicism was investigated on DNA from colonic adenomas by Sanger sequencing or Whole Exome Sequencing (WES). Mosaicism extension to other tissues (peripheral blood, saliva, hair follicles) was evaluated using Sanger sequencing and/or digital PCR. APC second hit was investigated in adenomas from mosaic patients. WES was performed on DNA from peripheral blood to identify additional polyposis candidate variants. We identified APC mosaicism in 50% of patients. In three cases mosaicism was restricted to the colon, while in one it also extended to the duodenum and saliva. One patient without APC mosaicism, carrying an APC in-frame deletion of uncertain significance, was found to harbor rare germline variants in OGG1, POLQ, and EXO1 genes. In conclusion, our restrictive selection criteria improved the detection of mosaic APC patients. In addition, we showed for the first time that an oligogenic inheritance of rare variants might have a cooperative role in sporadic colorectal polyposis onset.

Insulin Mediated Activation of PI3K/Akt Signalling Pathway Modifies the Proteomic Cargo of Extracellular Vesicles

Epidemiological studies suggest that diabetes and obesity increases the risk of colorectal cancer (CRC) and lowers the patient survival rate. An important attribute in diabetes and obesity is the presence of high levels of growth factors including insulin in blood which can activate the PI3K/Akt signalling pathway. Dysregulation of PI3K/Akt signalling pathway leads to sustained proliferative signals thereby allowing the cells susceptible to cancer. Extracellular vesicles (EVs), secreted nanovesicles of endocytic origin, are implicated in mediating the transfer of oncogenic cargo in the tumour microenvironment. In this study, CRC cells were treated with insulin to activate PI3K/Akt signaling pathway. Insulin treatment significantly increased the number of EVs secreted by CRC cells. Furthermore, pAkt was exclusively packaged in EVs secreted by PI3K/Akt activated cells. Quantitative proteomics analysis confirmed that the protein cargo of EVs are modified upon activation of PI3K/Akt signaling pathway. Bioinformatics analysis highlighted the enrichment of proteins implicated in cell proliferation in EVs secreted by PI3K/Akt activated cells. Furthermore, incubation of EVs secreted by PI3K/Akt activated cells induced proliferation in recipient CRC cells. These findings suggest that EVs can amplify the signal provided by the growth factors in the tumor microenvironment and hence aid in cancer progression.

Epistasis analysis of microRNAs on pathological stages in colon cancer based on an Empirical Bayesian Elastic Net method

Background

Colon cancer is a leading cause of worldwide cancer death. It has become clear that microRNAs (miRNAs) play a role in the progress of colon cancer and understanding the effect of miRNAs on tumorigenesis could lead to better prognosis and improved treatment. However, most studies have focused on studying differentially expressed miRNAs between tumor and non-tumor samples or between stages in tumor tissue. Limited work has conducted to study the interactions or epistasis between miRNAs and how the epistasis brings about effect on tumor progression. In this study, we investigate the main and pair-wise epistatic effects of miRNAs on the pathological stages of colon cancer using datasets from The Cancer Genome Atlas.

Results

We develop a workflow composed of multiple steps for feature selection based on the Empirical Bayesian Elastic Net (EBEN) method. First, we identify the main effects using a model with only main effect on the phenotype. Second, a corrected phenotype is calculated by removing the significant main effect from the original phenotype. Third, we select features with epistatic effect on the corrected phenotype. Finally, we run the full model with main and epistatic effects on the previously selected main and epistatic features. Using the multi-step workflow, we identify a set of miRNAs with main and epistatic effect on the pathological stages of colon cancer. Many of miRNAs with main effect on colon cancer have been previously reported to be associated with colon cancer, and the majority of the epistatic miRNAs share common target genes that could explain their epistasis effect on the pathological stages of colon cancer. We also find many of the target genes of detected miRNAs are associated with colon cancer. Go Ontology Enrichment Analysis of the experimentally validates targets of main and epistatic miRNAs, shows that these target genes are enriched for biological processes associated with cancer progression.

Conclusion

Our results provide a set of candidate miRNAs associated with colon cancer progression that could have potential translational and therapeutic utility. Our analysis workflow offers a new opportunity to efficiently explore epistatic interactions among genetic and epigenetic factors that could be associated with human diseases. Furthermore, our workflow is flexible and can be applied to analyze the main and epistatic effect of various genetic and epigenetic factors on a wide range of phenotypes.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4130-7) contains supplementary material, which is available to authorized users.

Integrating Next-Generation Genomic Sequencing and Mass Spectrometry To Estimate Allele-Specific Protein Abundance in Human Brain

Gene expression contributes to phenotypic traits and human disease. To date, comparatively less is known about regulators of protein abundance, which is also under genetic control and likely influences clinical phenotypes. However, identifying and quantifying allele-specific protein abundance by bottom-up proteomics is challenging since single nucleotide variants (SNVs) that alter protein sequence are not considered in standard human protein databases. To address this, we developed the GenPro software and used it to create personalized protein databases (PPDs) to identify single amino acid variants (SAAVs) at the protein level from whole exome sequencing. In silico assessment of PPDs generated by GenPro revealed only a 1% increase in tryptic search space compared to a direct translation of all human transcripts and an equivalent search space compared to the UniProtKB reference database. To identify a large unbiased number of SAAV peptides, we performed high-resolution mass spectrometry-based proteomics for two human post-mortem brain samples and searched the collected MS/MS spectra against their respective PPD. We found an average of ∼117 000 unique peptides mapping to ∼9300 protein groups for each sample, and of these, 977 were unique variant peptides. We found that over 400 reference and SAAV peptide pairs were, on average, equally abundant in human brain by label-free ion intensity measurements and confirmed the absolute levels of three reference and SAAV peptide pairs using heavy labeled peptides standards coupled with parallel reaction monitoring (PRM). Our results highlight the utility of integrating genomic and proteomic sequencing data to identify sample-specific SAAV peptides and support the hypothesis that most alleles are equally expressed in human brain.

Application of open-access databases to determine functional connectivity between resveratrol-binding protein QR2 and colorectal carcinoma

Colorectal cancer (CRC) is a major cause of cancer-associated deaths worldwide. Recently, oral administration of resveratrol (trans-3,5,4'-trihydroxystilbene) has been reported to significantly reduce tumor proliferation in colorectal cancer patients, however, with little specific information on functional connections. The pathogenesis and development of colorectal cancer is a multistep process that can be categorized using three phenotypic pathways, respectively, chromosome instability (CIN), microsatellite instability (MSI), and CpG island methylator (CIMP). Targets of resveratrol, including a high-affinity binding protein, quinone reductase 2 (QR2), have been identified with little information on disease association. We hypothesize that the relationship between resveratrol and different CRC etiologies might be gleaned using publicly available databases. A web-based microarray gene expression data-mining platform, Oncomine, was selected and used to determine whether QR2 may serve as a mechanistic and functional biotarget within the various CRC etiologies. We found that QR2 messenger RNA (mRNA) is overexpressed in CRC characterized by CIN, particularly in cells showing a positive KRAS (Kirsten rat sarcoma viral oncogene homolog) mutation, as well as by the MSI but not the CIMP phenotype. Mining of Oncomine revealed an excellent correlation between QR2 mRNA expression and certain CRC etiologies. Two resveratrol-associated genes, adenomatous polyposis coli (APC) and TP53, found in CRC were further mined, using cBio portal and Colorectal Cancer Atlas which predicted a mechanistic link to exist between resveratrol→QR2/TP53→CIN. Multiple web-based data mining can provide valuable insights which may lead to hypotheses serving to guide clinical trials and design of therapies for enhanced disease prognosis and patient survival. This approach resembles a BioGPS, a capability for mining web-based databases that can elucidate the potential links between compounds to provide correlations of these interactions with specific diseases.

Proteomic Data Storage and Sharing

With the advent of high-throughput genomic and proteomic techniques, there is a massive amount of multidimensional data being generated and has increased several orders of magnitude. But the amount of data that is cataloged in the central repositories and shared publicly with the scientific community does not correlate the same rate at which the data is generated. Here, in this chapter, we discuss various proteomics data repositories that are freely accessible to the researchers for further downstream meta-analysis.

Network Tools for the Analysis of Proteomic Data

Recent advancements in high-throughput technologies such as mass spectrometry have led to an increase in the rate at which data is generated and accumulated. As a result, standard statistical methods no longer suffice as a way of analyzing such gigantic amounts of data. Network analysis, the evaluation of how nodes relate to one another, has over the years become an integral tool for analyzing high throughput proteomic data as they provide a structure that helps reduce the complexity of the underlying data.Computational tools, including pathway databases and network building tools, have therefore been developed to store, analyze, interpret, and learn from proteomics data. These tools enable the visualization of proteins as networks of signaling, regulatory, and biochemical interactions. In this chapter, we provide an overview of networks and network theory fundamentals for the analysis of proteomics data. We further provide an overview of interaction databases and network tools which are frequently used for analyzing proteomics data.

Label-Based and Label-Free Strategies for Protein Quantitation

The precise quantification of changes between various physiological states in a biological system is highly complex in nature. Over the past few years, in combination with classical methods, mass spectrometry based approaches have become an indispensable tool in deciphering exact abundance of proteins in composite mixtures. The technique is now well established and employs both label-based and label-free quantitation strategies. Label-based quantitation methods utilize stable isotope labels which are incorporated within the peptides, introducing an expectable mass difference within the two or more experimental conditions. In contrast, label-free proteomics quantitates both relative and absolute protein quantity by utilizing signal intensity and spectral counting of peptides. This chapter focuses on the commonly used quantitative mass spectrometry methods for high-throughput proteomic analysis.

Identification of cancer risk lncRNAs and cancer risk pathways regulated by cancer risk lncRNAs based on genome sequencing data in human cancers

Cancer is a group of diseases involving abnormal cell growth with the potential to invade or spread to other parts of the body. The complexity of cancer can be reduced to a small number of underlying principles like cancer hallmarks which could govern the transformation of normal cells to cancer. Besides, the growth and metastasis of cancer often relate to combined effects of long non-coding RNAs (lncRNAs). Here, we performed comprehensive analysis for lncRNA expression profiles and clinical data of six types of human cancer patients from The Cancer Genome Atlas (TCGA), and identified six risk pathways and twenty three lncRNAs. In addition, twenty three cancer risk lncRNAs which were closely related to the occurrence or development of cancer had a good classification performance for samples of testing datasets of six cancer datasets. More important, these lncRNAs were able to separate samples in the entire cancer dataset into high-risk group and low-risk group with significantly different overall survival (OS), which was further validated in ten validation datasets. In our study, the robust and effective cancer biomarkers were obtained from cancer datasets which had information of normal-tumor samples. Overall, our research can provide a new perspective for the further study of clinical diagnosis and treatment of cancer.

Alternative splicing of U2AF1 reveals a shared repression mechanism for duplicated exons

The auxiliary factor of U2 small nuclear ribonucleoprotein (U2AF) facilitates branch point (BP) recognition and formation of lariat introns. The gene for the 35-kD subunit of U2AF gives rise to two protein isoforms (termed U2AF35a and U2AF35b) that are encoded by alternatively spliced exons 3 and Ab, respectively. The splicing recognition sequences of exon 3 are less favorable than exon Ab, yet U2AF35a expression is higher than U2AF35b across tissues. We show that U2AF35b repression is facilitated by weak, closely spaced BPs next to a long polypyrimidine tract of exon Ab. Each BP lacked canonical uridines at position -2 relative to the BP adenines, with efficient U2 base-pairing interactions predicted only for shifted registers reminiscent of programmed ribosomal frameshifting. The BP cluster was compensated by interactions involving unpaired cytosines in an upstream, EvoFold-predicted stem loop (termed ESL) that binds FUBP1/2. Exon Ab inclusion correlated with predicted free energies of mutant ESLs, suggesting that the ESL operates as a conserved rheostat between long inverted repeats upstream of each exon. The isoform-specific U2AF35 expression was U2AF65-dependent, required interactions between the U2AF-homology motif (UHM) and the α6 helix of U2AF35, and was fine-tuned by exon Ab/3 variants. Finally, we identify tandem homologous exons regulated by U2AF and show that their preferential responses to U2AF65-related proteins and SRSF3 are associated with unpaired pre-mRNA segments upstream of U2AF-repressed 3′ss. These results provide new insights into tissue-specific subfunctionalization of duplicated exons in vertebrate evolution and expand the repertoire of exon repression mechanisms that control alternative splicing.