Integrating proteomics and transcriptomics for the identification of potential targets in early colorectal cancer.
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ABSTRACT:
SUBMITTER: Yang W
PROVIDER: S-EPMC6615923 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The aim of the present study was to identify potential therapeutic targets for colorectal cancer (CRC). The gene expression profile GSE32323, containing 34 samples, including 17 specimens of CRC tissues and 17 of paired normal tissues from CRC patients, was downloaded from the Gene Expression Omnibus database. Following data preprocessing using the Affy and preprocessCore packages, the differentially-expressed genes (DEGs) between the two types of samples were identified with the Linear Models for Microarray Analysis package. Next, functional and pathway enrichment analysis of the DEGs was performed using the Database for Annotation Visualization and Integrated Discovery. The protein-protein interaction (PPI) network was established using the Search Tool for the Retrieval of Interacting Genes database. Utilizing WebGestalt, the potential microRNAs (miRNAs/miRs) of the DEGs were screened and the integrated miRNA-target network was built. A cohort of 1,347 DEGs was identified, the majority of which were mainly enriched in cell cycle-related biological processes and pathways. Cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), MAD2 mitotic arrest deficient-like 1 (MAD2L1) and BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) were prominent in the PPI network, while the over-represented genes in the integrated miRNA-target network were SRY (sex determining region Y)-box 4 (SOX4; targeted by hsa-mir-129), v-myc avian myelocytomatosis viral oncogene homolog (MYC; targeted by hsa-let-7c and hsa-mir-145) and cyclin D1 (CCND1; targeted by hsa-let-7b). CDK1, CCNB1 and CCND1 were also associated with the p53 signaling pathway. Overall, several genes associated with the cell cycle and p53 pathway were identified as biomarkers for CRC. CDK1, CCNB1, MAD2L1, BUB1B, SOX4, collagen type I ?2 chain and MYC may play significant roles in CRC progression by affecting the cell cycle-related pathways, while CDK1, CCNB1 and CCND1 may serve as crucial regulators in the p53 signaling pathway. Furthermore, SOX4, MYC and CCND1 may be targets of miR-129, hsa-mir-145 and hsa-let-7c, respectively. However, further validation of these data is required.
| S-EPMC5228398 | biostudies-literature
Project description:Colorectal cancer (CRC) is a highly prevalent and lethal malignancy worldwide. Although immunotherapy has substantially improved CRC outcomes, intolerance remains a major concern among most patients. Considering the pivotal role of the tumor microenvironment (TME) in tumor progression and treatment outcomes, profiling the TME at the transcriptomic level can provide novel insights for developing CRC treatment strategies. Seventy-seven TME-associated signatures were acquired from previous studies. To elucidate variations in prognosis, clinical features, genomic alterations, and responses to immunotherapy in CRC, we employed a non-negative matrix factorization algorithm to categorize 2595 CRC samples of 27 microarrays from the Gene Expression Omnibus database. Three machine learning techniques were employed to identify a signature specific to immunotherapy. Subsequently, the mechanisms by which this signature interacts with TME subtypes and immunotherapy were investigated. Our findings revealed five distinct TME subtypes (TMESs; TMES1-TMES5) in CRC, each exhibiting a unique pattern of immunotherapy response. TMES1, TMES4, and TMES5 had relatively inferior outcomes, TMES2 was associated with the poorest prognosis, and TMES3 had a superior outcome. Subsequent investigations revealed that activated dendritic cells could enhance the immunotherapy response rate, with their augmentation effect closely associated with the activation of CD8+T cells. We successfully classified CRC into five TMESs, each demonstrating varying response rates to immunotherapy. Notably, the application of machine learning to identify activated dendritic cells helped elucidate the underlying mechanisms contributing to these differences. We posit that these TMESs hold promising clinical implications for prognostic evaluation and guidance of immunotherapy strategies, thereby providing valuable insights to inform clinical decision-making.
| S-EPMC10987483 | biostudies-literature
Project description:Isothiocyanates (ITCs), such as phenethyl isothiocyanate (PEITC) and sulforaphane (SFN), are effective cancer chemopreventive compounds. It is believed that the major mechanism for the cancer preventive activity of ITCs is through the induction of cell cycle arrest and apoptosis. However, the upstream molecular targets of ITCs have been underexplored until recently. To identify proteins that are covalently modified by ITCs, human non-small cell lung cancer A549 cells were treated with (14)C-PEITC and (14)C-SFN, and the cell lysates were extracted for analysis by 2-D gel electrophoresis and mass spectrometry. After superimposing the colloidal Coomassie blue protein staining pattern with the pattern of radioactivity obtained from X-ray films, it was clear that only a small fraction of cellular proteins contained radioactivity, presumably resulting from selective binding with PEITC or SFN via thiocarbamation. More than 30 proteins with a variety of biological functions were identified with high confidence. Here, we report the identities of these potential ITC target proteins and discuss their biological relevance. The discovery of the protein targets may facilitate studies of the mechanisms by which ITCs exert their cancer preventive activity and provide the molecular basis for designing more efficacious ITC compounds.
| S-EPMC3493163 | biostudies-literature
Project description:BackgroundOne of the most significant challenges in colorectal cancer (CRC) management is the use of compliant early stage population-based diagnostic tests as adjuncts to confirmatory colonoscopy. Despite the near curative nature of early clinical stage surgical resection, mortality remains unacceptably high-as the majority of patients diagnosed by faecal haemoglobin followed by colonoscopy occur at latter stages. Additionally, current population-based screens reliant on fecal occult blood test (FOBT) have low compliance (~ 40%) and tests suffer low sensitivities. Therefore, blood-based diagnostic tests offer survival benefits from their higher compliance (≥ 97%), if they can at least match the sensitivity and specificity of FOBTs. However, discovery of low abundance plasma biomarkers is difficult due to occupancy of a high percentage of proteomic discovery space by many high abundance plasma proteins (e.g., human serum albumin).MethodsA combination of high abundance protein ultradepletion (e.g., MARS-14 and an in-house IgY depletion columns) strategies, extensive peptide fractionation methods (SCX, SAX, High pH and SEC) and SWATH-MS were utilized to uncover protein biomarkers from a cohort of 100 plasma samples (i.e., pools of 20 healthy and 20 stages I-IV CRC plasmas). The differentially expressed proteins were analyzed using ANOVA and pairwise t-tests (p < 0.05; fold-change > 1.5), and further examined with a neural network classification method using in silico augmented 5000 patient datasets.ResultsUltradepletion combined with peptide fractionation allowed for the identification of a total of 513 plasma proteins, 8 of which had not been previously reported in human plasma (based on PeptideAtlas database). SWATH-MS analysis revealed 37 protein biomarker candidates that exhibited differential expression across CRC stages compared to healthy controls. Of those, 7 candidates (CST3, GPX3, CFD, MRC1, COMP, PON1 and ADAMDEC1) were validated using Western blotting and/or ELISA. The neural network classification narrowed down candidate biomarkers to 5 proteins (SAA2, APCS, APOA4, F2 and AMBP) that had maintained accuracy which could discern early (I/II) from late (III/IV) stage CRC.ConclusionMS-based proteomics in combination with ultradepletion strategies have an immense potential of identifying diagnostic protein biosignature.
| S-EPMC6712843 | biostudies-literature
Project description:BackgroundBurkholderia cenocepacia is an endemic soil dweller and emerging opportunistic pathogen in patients with cystic fibrosis (CF). The identification of virulence factors and potential therapeutic targets has been hampered by the genomic diversity within the species as many factors are not shared among the pathogenic members of the species.Methodology/principal findingsIn this study, global identification of putative virulence factors was performed by analyzing the transcriptome of two related strains of B. cenocepacia (one clinical, one environmental) under conditions mimicking cystic fibrosis sputum versus soil. Soil is a natural reservoir for this species; hence, genes induced under CF conditions relative to soil may represent adaptations that have occurred in clinical strains. Under CF conditions, several genes encoding proteins thought to be involved in virulence were induced and many new ones were identified. Our analysis, in combination with previous studies, reveals 458 strain-specific genes, 126 clinical-isolate-specific, and at least four species-specific genes that are induced under CF conditions. The chromosomal distribution of the induced genes was disproportionate to the size of the chromosome as genes expressed under soil conditions by both strains were more frequent on the second chromosome and those differentially regulated between strains were more frequent on the third chromosome. Conservation of these induced genes was established using the 11 available Bcc genome sequences to indicate whether potential therapeutic targets would be species-wide.Conclusions/significanceComparative transcriptomics is a useful way to identify new potential virulence factors and therapeutic targets for pathogenic bacteria. We identified eight genes induced under CF conditions that were also conserved in the Bcc and may constitute particularly attractive therapeutic targets due to their signal sequence, predicted cellular location, and homology to known therapeutic targets.
| S-EPMC2806911 | biostudies-literature
Project description:The step-wise development of colorectal neoplasia from adenoma to carcinoma suggests that specific interventions could delay or prevent the development of invasive cancer. Several key factors involved in colorectal cancer pathogenesis have already been identified including cyclooxygenase 2 (COX-2), nuclear factor kappa B (NF-κB), survivin and insulin-like growth factor-I (IGF-I). Clinical trials of COX-2 inhibitors have provided the "proof of principle" that inhibition of this enzyme can prevent the formation of colonic adenomas and potentially carcinomas, however concerns regarding the potential toxicity of these drugs have limited their use as a chemopreventative strategy. Curcumin, resveratrol and quercetin are chemopreventive agents that are able to suppress multiple signaling pathways involved in carcinogenesis and hence are attractive candidates for further research.
| S-EPMC3794728 | biostudies-literature
Project description:Studies integrating transcriptomic data with proteomic data can illuminate the proteome more clearly than either separately. Integromic studies can deepen understanding of the dynamic complex regulatory relationship between the transcriptome and the proteome. Integrating these data dictates a reliable mapping between the identifier nomenclature resultant from the two high-throughput platforms. However, this kind of analysis is well known to be hampered by lack of standardization of identifier nomenclature among proteins, genes, and microarray probe sets. Therefore data integration may also play a role in critiquing the fallible gene identifications that both platforms emit.We compared three freely available internet-based identifier mapping resources for mapping UniProt accessions (ACCs) to Affymetrix probesets identifications (IDs): DAVID, EnVision, and NetAffx. Liquid chromatography-tandem mass spectrometry analyses of 91 endometrial cancer and 7 noncancer samples generated 11,879 distinct ACCs. For each ACC, we compared the retrieval sets of probeset IDs from each mapping resource. We confirmed a high level of discrepancy among the mapping resources. On the same samples, mRNA expression was available. Therefore, to evaluate the quality of each ACC-to-probeset match, we calculated proteome-transcriptome correlations, and compared the resources presuming that better mapping of identifiers should generate a higher proportion of mapped pairs with strong inter-platform correlations. A mixture model for the correlations fitted well and supported regression analysis, providing a window into the performance of the mapping resources. The resources have added and dropped matches over two years, but their overall performance has not changed.The methods presented here serve to achieve concrete context-specific insight, to support well-informed decisions in choosing an ID mapping strategy for "omic" data merging.
| S-EPMC3124437 | biostudies-literature
Project description:The breast is a dynamic organ whose response to physiological and pathophysiological conditions alters its disease susceptibility, yet the specific effects of these clinical variables on cell state remain poorly annotated. We present a unified, high-resolution breast atlas by integrating single-cell RNA-seq, mass cytometry, and cyclic immunofluorescence, encompassing a myriad of states. We define cell subtypes within the alveolar, hormone-sensing, and basal epithelial lineages, delineating associations of several subtypes with cancer risk factors, including age, parity, and BRCA2 germline mutation. Of particular interest is a subset of alveolar cells termed basal-luminal (BL) cells, which exhibit poor transcriptional lineage fidelity, accumulate with age, and carry a gene signature associated with basal-like breast cancer. We further utilize a medium-depletion approach to identify molecular factors regulating cell-subtype proportion in organoids. Together, these data are a rich resource to elucidate diverse mammary cell states.
| S-EPMC9202341 | biostudies-literature
Project description:BackgroundThe proteome is a major source of therapeutic targets. We conducted a proteome-wide Mendelian randomization (MR) study to identify candidate protein markers and therapeutic targets for colorectal cancer (CRC).MethodsProtein quantitative trait loci (pQTLs) were derived from seven published genome-wide association studies (GWASs) on plasma proteome, and summary-level data were extracted for 4853 circulating protein markers. Genetic associations with CRC were obtained from a large-scale GWAS meta-analysis (16,871 cases and 26,328 controls), the FinnGen cohort (4957 cases and 304,197 controls), and the UK Biobank (9276 cases and 477,069 controls). Colocalization and summary-data-based MR (SMR) analyses were performed sequentially to verify the causal role of candidate proteins. Single cell-type expression analysis, protein-protein interaction (PPI), and druggability evaluation were further conducted to detect the specific cell type with enrichment expression and prioritize potential therapeutic targets.ResultsCollectively, genetically predicted levels of 13 proteins were associated with CRC risk. Elevated levels of two proteins (GREM1, CHRDL2) and decreased levels of 11 proteins were associated with an increased risk of CRC, among which four (GREM1, CLSTN3, CSF2RA, CD86) were prioritized with the most convincing evidence. These protein-coding genes are mainly expressed in tissue stem cells, epithelial cells, and monocytes in colon tumor tissue. Two interactive pairs of proteins (GREM1 and CHRDL2; MMP2 and TIMP2) were identified to be involved in osteoclast differentiation and tumorigenesis pathways; four proteins (POLR2F, CSF2RA, CD86, MMP2) have been targeted for drug development on autoimmune diseases and other cancers, with the potentials of being repurposed as therapeutic targets for CRC.ConclusionsThis study identified several protein biomarkers to be associated with CRC risk and provided new insights into the etiology and promising targets for the development of screening biomarkers and therapeutic drugs for CRC.
| S-EPMC10508028 | biostudies-literature
Project description:Colorectal cancer (CRC) is the third most common cancer worldwide and has poor prognosis. To identify the oncofetal proteins involved in CRC carcinogenesis, differentially expressed proteins among fetal colorectal tissues, CRC, and the paired tumor-adjacent normal colorectal tissues were investigated by a two-dimensional gel electrophoresis and MALDI-TOF/TOF-based proteomics approach. 42 protein spots were differentially expressed among these tissues, and 22 proteins were identified by MS analysis. Desmin and zinc finger protein 829 were found to be elevated in CRC tissue and fetal colorectal tissue compared with normal colorectal tissue. The elevated expression of desmin in CRC tissue and different developmental stages of fetus colon was confirmed by RT-PCR and Western blot analysis. Immunohistochemical analysis showed that the elevated expression of desmin was correlated with the severity and differentiation of CRC and decreased survival rate of CRC patients. Finally by developing a highly sensitive immunoassay, desmin could be detected in human serum and was significantly elevated in CRC patients compared with healthy volunteers. We propose that desmin be considered a potential oncofetal serum tumor marker for CRC that may have significance in the detection of patients with CRC.
| S-EPMC2722764 | biostudies-literature