A merged microarray meta-dataset for transcriptionally profiling colorectal neoplasm formation and progression

Rohr, Michael; Beardsley, Jordan M.; Nakkina, Sai Preethi; Zhu, Xiang; Aljabban, Jihad; Hadley, Dexter; Altomare, Deborah A.

doi:10.1038/s41597-021-00998-5

Cited by 10 publications

(13 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A decreased mRNA expression of VIP in colorectal samples was mentioned, which is also in parallel with our results since we observed down-regulated profile of VIP in polyp samples. Another study highlighted IGF1 as one of the drivers in the transition between adenoma and colorectal cancer, IGF1 was also identified in our study with a decreased expression profile in polyps [44]. Comparison of cancer free and cancer adjacent polyp samples presented several molecular changes between two polyp types [46].…”

Section: Plos Onesupporting

confidence: 71%

“…Therefore, the expression changes in favor of EMT support the idea that colon adenomas could initiate to advance both invasive and metastatic features in pre-malignant period. Several studies endorse this proposition as they also discuss that EMT related pathways would involve in polyp formation [44,68,75]. Enrichment analysis illuminates that MSX1 upregulation, on one hand, induces EMT, on the other hand, hinders cell growth.…”

Section: Plos Onementioning

confidence: 95%

“…For the differentiation of polyp subtypes, the gene expression differences between two different polyp groups were defined by several technologies [43]. In a meta-analysis study, normal colon, polyp and colon cancer gene expression data were integrated with the Combat method; DEG and pathway analysis were applied to explain the mechanisms of polyp and cancer formation [44]. In another study, DEG and pathway analysis were performed for normal, polyp and colon cancer samples; a marker gene cluster was revealed [45].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

In silico identification of novel biomarkers for key players in transition from normal colon tissue to adenomatous polyps

et al. 2022

View full text Add to dashboard Cite

Adenomatous polyps of the colon are the most common neoplastic polyps. Although most of adenomatous polyps do not show malign transformation, majority of colorectal carcinomas originate from neoplastic polyps. Therefore, understanding of this transformation process would help in both preventive therapies and evaluation of malignancy risks. This study uncovers alterations in gene expressions as potential biomarkers that are revealed by integration of several network-based approaches. In silico analysis performed on a unified microarray cohort, which is covering 150 normal colon and adenomatous polyp samples. Significant gene modules were obtained by a weighted gene co-expression network analysis. Gene modules with similar profiles were mapped to a colon tissue specific functional interaction network. Several clustering algorithms run on the colon-specific network and the most significant sub-modules between the clusters were identified. The biomarkers were selected by filtering differentially expressed genes which also involve in significant biological processes and pathways. Biomarkers were also validated on two independent datasets based on their differential gene expressions. To the best of our knowledge, such a cascaded network analysis pipeline was implemented for the first time on a large collection of normal colon and polyp samples. We identified significant increases in TLR4 and MSX1 expressions as well as decrease in chemokine profiles with mostly pro-tumoral activities. These biomarkers might appear as both preventive targets and biomarkers for risk evaluation. As a result, this research proposes novel molecular markers that might be alternative to endoscopic approaches for diagnosis of adenomatous polyps.

show abstract

Section: Plos Onesupporting

confidence: 71%

Section: Plos Onementioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

In silico identification of novel biomarkers for key players in transition from normal colon tissue to adenomatous polyps

et al. 2022

View full text Add to dashboard Cite

show abstract

“…The dataset E-MTAB-10089 ( Rohr et al, 2021 ) was used to compare gene expression in normal tissue, adenoma and colorectal cancer. One-way ANOVA test was used to determine significant differences with Benjamini-Hochberg correction for multiple comparisons.…”

Section: Methodsmentioning

confidence: 99%

Multikinase inhibitors modulate non-constitutive proteasome expression in colorectal cancer cells

Burov,

Grigorieva,

Lebedev

et al. 2024

Front. Mol. Biosci.

View full text Add to dashboard Cite

Introduction: Proteasomes are multi-subunit protein complexes responsible for protein degradation in cells. Immunoproteasomes and intermediate proteasomes (together non-constitutive proteasomes) are specific forms of proteasomes frequently associated with immune response, antigen presentation, inflammation and stress. Expression of non-constitutive proteasome subunits has a prognostic value in several types of cancer. Thus, factors that modulate non-constitutive proteasome expression in tumors are of particular interest. Multikinase inhibitors (MKIs) demonstrate promising results in treatment of cancer. At the same time, their immunomodulatory properties and effects on non-constitutive proteasome expression in colorectal cancer cells are poorly investigated.Methods: Proteasome subunit expression in colorectal cancer was evaluated by bioinformatic analysis of available datasets. Two colorectal cancer cell lines, expressing fluorescent non-constitutive proteasomes were treated with multikinase inhibitors: regorafenib and sorafenib. The proteasome subunit expression was assessed by real-time PCR, Western blotting and flow cytometry. The proteasome activity was studied using proteasome activity-based probe and fluorescent substrates. Intracellular proteasome localization was revealed by confocal microscopy. Reactive oxygen species levels following treatment were determined in cells. Combined effect of proteasome inhibition and treatment with MKIs on viability of cells was estimated.Results: Expression of non-constitutive proteasomes is increased in BRAF-mutant colorectal tumors. Regorafenib and sorafenib stimulated the activity and synthesis of non-constitutive proteasomes in examined cell lines. MKIs induced oxidative stress and redistribution of proteasomes within cells. Sorafenib stimulated formation of cytoplasmic aggregates, containing proteolyticaly active non-constitutive proteasomes, while regorafenib had no such effect. MKIs caused no synergistic action when were combined with the proteasome inhibitor.Discussion: Obtained results indicate that MKIs might affect the crosstalk between cancer cells and immune cells via modulation of intracellular proteasome pool. Observed phenomenon should be considered when MKI-based therapy is applied.

show abstract

“…A variety of ‘omics’ studies and other bioinformatics-only investigations are yielding increasingly larger numbers of novel potential markers and molecular targets of CRC (reviewed in [ 20 , 21 , 22 ]) and of breast cancer [ 23 ], lung cancer [ 24 ], and of other cancers [ 25 ]. These studies usually aim to identify differentially expressed genes (DEG) and/or disease-related proteins using a variety of sequencing, microarrays, bead arrays and qPCR approaches or proteomics-based studies.…”

Section: Introductionmentioning

confidence: 99%

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

Kamel

Schneider

Nisar

et al. 2022

Cancers

View full text Add to dashboard Cite

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

show abstract

A merged microarray meta-dataset for transcriptionally profiling colorectal neoplasm formation and progression

Cited by 10 publications

References 57 publications

In silico identification of novel biomarkers for key players in transition from normal colon tissue to adenomatous polyps

In silico identification of novel biomarkers for key players in transition from normal colon tissue to adenomatous polyps

Multikinase inhibitors modulate non-constitutive proteasome expression in colorectal cancer cells

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

Contact Info

Product

Resources

About