Evaluation of MGP gene expression in colorectal cancer

Caiado, Helena; Conceição, Natércia; Tiago, Daniel M.; Marreiros, Ana; Vicente, S.; Enriquez, Jose Luis; Vaz, Ana; Antunes, Artur; Guerreiro, Horácio; Caldeira, Paulo; Cancela, M. Leonor

doi:10.1016/j.gene.2019.144120

Cited by 20 publications

(17 citation statements)

References 45 publications

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“…Another factor instead displays a unique expression profile of markers previously shown to be dysregulated in various tumor types (e.g. MGP, S100, TFF3 ) [ 14 – 16 ]. Factor_7 on the other hand is concentrated to a small region between tumor areas with a strong signature for the presence and regulation of T and B cells (CCL19, TRBC2, CD52, MS4A1, TRAC), possibly forming a tertiary lymphoid structure [ 17 ].…”

Section: Resultsmentioning

confidence: 99%

Seamless integration of image and molecular analysis for spatial transcriptomics workflows

Bergenstråhle¹,

Larsson²,

Lundeberg³

2020

BMC Genomics

191

162

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Background Recent advancements in in situ gene expression technologies constitute a new and rapidly evolving field of transcriptomics. With the recent launch of the 10x Genomics Visium platform, such methods have started to become widely adopted. The experimental protocol is conducted on individual tissue sections collected from a larger tissue sample. The two-dimensional nature of this data requires multiple consecutive sections to be collected from the sample in order to construct a comprehensive three-dimensional map of the tissue. However, there is currently no software available that lets the user process the images, align stacked experiments, and finally visualize them together in 3D to create a holistic view of the tissue. Results We have developed an R package named STUtility that takes 10x Genomics Visium data as input and provides features to perform standardized data transformations, alignment of multiple tissue sections, regional annotation, and visualizations of the combined data in a 3D model framework. Conclusions STUtility lets the user process, analyze and visualize multiple samples of spatially resolved RNA sequencing and image data from the 10x Genomics Visium platform. The package builds on the Seurat framework and uses familiar APIs and well-proven analysis methods. An introduction to the software package is available at https://ludvigla.github.io/STUtility_web_site/ .

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Section: Resultsmentioning

confidence: 99%

Seamless integration of image and molecular analysis for spatial transcriptomics workflows

Bergenstråhle¹,

Larsson²,

Lundeberg³

2020

BMC Genomics

191

162

View full text Add to dashboard Cite

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“…POSTN, the most well-characterized Gla-protein family member, was shown to be a major determinant in proliferation for a number of aggressive, advanced solid tumors with poor prognosis (22). MGP is much less known than POSTN, but is gradually emerging as a determinant in cancer progression, exhibiting increased expression in colorectal, glioblastoma, breast, cervical, osteosarcoma and skin cancers with unfavorable prognosis (93)(94)(95)(96)(97). SPARC has been reported to mediate a variety of signaling pathways.…”

Section: Expression Of Mcps In Cancermentioning

confidence: 99%

The Matrix Revolution: Matricellular Proteins and Restructuring of the Cancer Microenvironment

et al. 2020

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The extracellular matrix (ECM) surrounding cells is indispensable for regulating their behavior. The dynamics of ECM signaling are tightly controlled throughout growth and development. During tissue remodeling, matricellular proteins (MCPs) are secreted into the ECM. These factors do not serve classical structural roles, but rather regulate matrix proteins and cell-matrix interactions to influence normal cellular functions. In the tumor microenvironment, it is becoming increasingly clear that aberrantly expressed MCPs can support multiple hallmarks of carcinogenesis by interacting with various cellular components that are coupled to an array of downstream signals. Moreover, MCPs also reorganize the biomechanical properties of the ECM to accommodate metastasis and tumor colonization. This realization is stimulating new research on MCPs as reliable and accessible biomarkers in cancer, as well as effective and selective therapeutic targets. Research.

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“…Recently, MGP was reported to be upregulated in a variety of tumors, including ovarian, breast, urogenital and skin cancer. However, in colon and lung cancers, an inverse correlation between MGP expression and survival was observed (57).…”

Section: Positivementioning

confidence: 99%

Comprehensive genomic analysis contrasting primary colorectal cancer and matched liver metastases

et al. 2021

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Recent studies have revealed that colorectal cancer (CRC) displays intratumor genetic heterogeneity, and that the cancer microenvironment plays an important role in the proliferation, invasion and metastasis of CRC. The present study performed genomic analysis on paired primary CRC and synchronous colorectal liver metastasis (CRLM) tissues collected from 22 patients using whole-exome sequencing, cancer gene panels and microarray gene expression profiling. In addition, immunohistochemical analysis was used to confirm the protein expression levels of genes identified as highly expressed in CRLM by DNA microarray analysis. The present study identified 10 genes that were highly expressed in CRLM compared with in CRC, from 36,022 probes obtained from primary CRC, CRLM and normal liver tissues by gene expression analysis with DNA microarrays. Of the 10 genes identified, five were classified as encoding 'matricellular proteins' [(osteopontin, periostin, thrombospondin-2, matrix Gla protein (MGP) and glycoprotein nonmetastatic melanoma protein B (GPNMB)] and were selected for immunohistochemical analysis. Osteopontin was strongly expressed in CRLM (6 of 22 cases: 27.3%), but not in CRC (0 of 22: 0%; P=0.02). Periostin also exhibited strong immunoreactivity in CRLM (17 of 22: 68.2%) compared with in CRC (7 of 22: 31.8%; P=0.006). Thrombospondin-2 exhibited strong immunoreactivity in both CRC and CRLM (54.5% in CRC, 45.5% in CRLM; P=0.55). GPNMB and MGP were rarely positive for both CRC and CRLM. A comparison of immunoreactive positive factors for these five genes revealed the complexities of gene expression in CRLM. Of the cases examined, 16 (72.7%) cases of CRC showed zero or only one positive immunoreactive factor. By contrast, CRLM showed more frequent and multiple immunoreactive factors; for example, 16 cases (72.7%) shared two or more factors, which was statistically more frequent than in CRC (P=0.007). The present study revealed the genomic heterogeneity between paired primary CRC and CRLM, in terms of cancer cell microenvironment. This finding may lead to novel diagnostic and therapeutic targets in the era of genome-guided personalized cancer treatment.

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Evaluation of MGP gene expression in colorectal cancer

Cited by 20 publications

References 45 publications

Seamless integration of image and molecular analysis for spatial transcriptomics workflows

Seamless integration of image and molecular analysis for spatial transcriptomics workflows

The Matrix Revolution: Matricellular Proteins and Restructuring of the Cancer Microenvironment

Comprehensive genomic analysis contrasting primary colorectal cancer and matched liver metastases

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