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. 2021 Apr;25(7):3622-3633.
doi: 10.1111/jcmm.16467. Epub 2021 Mar 14.

Two novel qualitative transcriptional signatures robustly applicable to non-research-oriented colorectal cancer samples with low-quality RNA

Jun Cheng  1   2   3 , Yating Guo  2   3 , Guoxian Guan  4 , Haiyan Huang  2   3 , Fengle Jiang  2   3 , Jun He  2   3 , Junling Wu  2   3 , Zheng Guo  2   3 , Xing Liu  4 , Lu Ao  2   3
Affiliations

Two novel qualitative transcriptional signatures robustly applicable to non-research-oriented colorectal cancer samples with low-quality RNA

Jun Cheng et al. J Cell Mol Med. 2021 Apr.

Abstract

Currently, due to the low quality of RNA caused by degradation or low abundance, the accuracy of gene expression measurements by transcriptome sequencing (RNA-seq) is very challenging for non-research-oriented clinical samples, majority of which are preserved in hospitals or tissue banks worldwide with complete pathological information and follow-up data. Molecular signatures consisting of several genes are rarely applied to such samples. To utilize these resources effectively, 45 stage II non-research-oriented samples which were formalin-fixed paraffin-embedded (FFPE) colorectal carcinoma samples (CRC) using RNA-seq have been analysed. Our results showed that although gene expression measurements were significantly affected, most cancer features, based on the relative expression orderings (REOs) of gene pairs, were well preserved. We then developed two REO-based signatures, which consisted of 136 gene pairs for early diagnosis of CRC, and 4500 gene pairs for predicting post-surgery relapse risk of stage II and III CRC. The performance of our signatures, which included hundreds or thousands of gene pairs, was more robust for non-research-oriented clinical samples, compared to that of two published concise REO-based signatures. In conclusion, REO-based signatures with relatively more gene pairs could be robustly applied to non-research-oriented CRC samples.

Keywords: colorectal cancer; low-quality RNA; non-research-oriented clinical samples; relative expression orderings; transcriptional signature.

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Conflict of interest statement

The authors confirm that there are no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Evaluation of the REO‐based cancer features in non‐research‐oriented clinical samples using the 177 122 stable opposite gene pairs (A) or the 43 439 977 significant opposite gene pairs (B) which were selected between 77 FF tumour and 51 FF normal samples. The retention rates of gene pairs with the specific cancer pattern (Gi > Gj) in the public FF CRCs (green), in‐house FFPE CRCs (blue) and normal FF samples (red) were shown
FIGURE 2
FIGURE 2
The flow chart for the development of the REO‐based signatures for the early diagnosis of CRC (A) or predicting post‐surgery relapse risk of stage II and III CRC (B), respectively
FIGURE 3
FIGURE 3
The predictive performance of the 4500 gene pair signature. A‐C, Kaplan‐Meier curves of DFI for patients with stage II and III CRC. D‐F, Kaplan‐Meier curves of DFI for patients with stage II CRC. G‐I, Kaplan‐Meier curves of DFI for patients with stage III CRC
FIGURE 4
FIGURE 4
The predictive performances of the 4500 gene pairs signature (A) and 44 gene pairs signature (B) in the non‐research‐oriented clinical samples
FIGURE 5
FIGURE 5
The function analysis of the common DEGs. A, KEGG function enrichment analysis with the 499 DEGs. B, The largest sub‐network in PPI analysis
See this image and copyright information in PMC

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