Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Jun 24:15:1407995.
doi: 10.3389/fimmu.2024.1407995. eCollection 2024.

Decoding immune-related gene-signatures in colorectal neoplasia

Affiliations

Decoding immune-related gene-signatures in colorectal neoplasia

Thura Akrem Omran et al. Front Immunol. .

Abstract

Background: Colorectal cancer (CRC) is a significant health issue, with notable incidence rates in Norway. The immune response plays a dual role in CRC, offering both protective effects and promoting tumor growth. This research aims to provide a detailed screening of immune-related genes and identify specific genes in CRC and adenomatous polyps within the Norwegian population, potentially serving as detection biomarkers.

Methods: The study involved 69 patients (228 biopsies) undergoing colonoscopy, divided into CRC, adenomatous polyps, and control groups. We examined the expression of 579 immune genes through nCounter analysis emphasizing differential expression in tumor versus adjacent non-tumorous tissue and performed quantitative reverse transcription polymerase chain reaction (RT-qPCR) across patient categories.

Results: Key findings include the elevated expression of CXCL1, CXCL2, IL1B, IL6, CXCL8 (IL8), PTGS2, and SPP1 in CRC tissues. Additionally, CXCL1, CXCL2, IL6, CXCL8, and PTGS2 showed significant expression changes in adenomatous polyps, suggesting their early involvement in carcinogenesis.

Conclusions: This study uncovers a distinctive immunological signature in colorectal neoplasia among Norwegians, highlighting CXCL1, CXCL2, IL1B, IL6, CXCL8, PTGS2, and SPP1 as potential CRC biomarkers. These findings warrant further research to confirm their role and explore their utility in non-invasive screening strategies.

Keywords: Norway; adenomatous polyps; biomarker potential; colorectal cancer (CRC); gene expression; immunology.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The schematic represents the study design. The study began with the collection of samples from CRC patients, including both tumor and adjacent non-neoplastic tissue. Utilizing the nCounter NanoString technology, the expression levels of 579 immune-related genes were quantitatively measured. From this comprehensive analysis, eight genes were identified as being most highly expressed. To validate these findings, we expanded the study to include healthy controls, polyp patients, and CRC patients, taking samples from various regions of the colon. The eight identified genes underwent further RT-qPCR analysis across these groups, confirming their elevated expression in CRC. Created with BioRender.com.
Figure 2
Figure 2
Differential gene expression of immune-related genes in CRC. The MDS plot (A) and heatmap (B) illustrate similarities in the mRNA expression of 579 immune-related genes in 25 cancer samples and 25 paired adjacent non-neoplastic tissue samples. (A) Cancer samples are depicted in violet, and adjacent non-neoplastic samples are depicted in green. Selected samples are annotated with sample ID (number) and type of tissue (T, cancer; M, adjacent non-neoplastic tissue). (B) The columns represent the samples, where cancer samples are colored blue and non-neoplastic samples are colored orange in the dendrogram on top. The rows represent individual genes. The color scale indicates the relative expression levels of each gene, where dark blue represents low expression and dark orange represents high expression.
Figure 3
Figure 3
Comparison of mRNA expression of individual genes in paired cancer and adjacent non-neoplastic samples. The volcano plot shows the Wilcoxon test results, comparing mRNA expression in paired cancerous and non-neoplastic samples.
Figure 4
Figure 4
Gene expression analysis in the outliers-subgroups. (A) Heatmap clusters gene expression levels, highlighting a subgroup with increased immune gene expression. (B) The MDS plot differentiates the subgroup of highly inflamed tumors from ‘Regular’ samples, emphasizing their distinct expression patterns.
Figure 5
Figure 5
Distribution of Inflammatory Gene Expression Across Colorectal Tissues. This figure presents box plots showing the mRNA expression levels of nine genes (CXCL1, CXCL2, CXCL9, IL1B, IL6, CXCL8, PTGS2, SPP1, and TGFB1) measured by RT-qPCR and normalized against endogenous control genes GAPDH and POLR2A across different colorectal tissue samples. The samples include healthy controls from the ascending colon (Control AC) and sigmoid colon (Control CS), polyp patients with tissues from the ascending colon (Polyp AC), adenomas polyp (Polyp TU), adjacent non-neoplastic tissue (Polyp NN), and sigmoid colon (Polyp CS), and CRC patients with tissues from the ascending colon (Cancer AC), tumor (Cancer TU), adjacent non-neoplastic tissue (Cancer NN), and sigmoid colon (Cancer CS). Box plots indicate the median (line inside the box), interquartile range (box), and range (whiskers), with outliers shown as individual points outside the whiskers. The statistical significance of the comparisons is indicated within the plots with black lines: polyp TU vs. polyp NN, cancer TU vs. cancer NN, and polyp TU vs. cancer TU. P-values are displayed above the comparison lines.

Similar articles

Cited by

References

    1. Norway CRo . Cancer incidence, mortality, survival and prevalence in Norway. Oslo: Cancer in Norway; (2022).
    1. Aran V, Victorino AP, Thuler LC, Ferreira CG. Colorectal cancer: epidemiology, disease mechanisms and interventions to reduce onset and mortality. Clin Colorectal Cancer. (2016) 15:195–203. doi: 10.1016/j.clcc.2016.02.008 - DOI - PubMed
    1. Simon K. Colorectal cancer development and advances in screening. Clin Interv Aging. (2016) 11:967–76. doi: 10.2147/CIA - DOI - PMC - PubMed
    1. Xu W, He Y, Wang Y, Li X, Young J, Ioannidis JPA, et al. . Risk factors and risk prediction models for colorectal cancer metastasis and recurrence: an umbrella review of systematic reviews and meta-analyses of observational studies. BMC Med. (2020) 18:172. doi: 10.1186/s12916-020-01618-6 - DOI - PMC - PubMed
    1. Fearon ER. Molecular genetics of colorectal cancer. Annu Rev Pathol. (2011) 6:479–507. doi: 10.1146/annurev-pathol-011110-130235 - DOI - PubMed

Substances