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IDDF2024-ABS-0065 A dynamic molecular landscape at single-cell resolution and the importance of ligand-receptor genes through the progression of colorectal cancer
  1. Jianping Liu1,
  2. Jianwen Sheng2,
  3. Nianshuang Li1,
  4. Yuanhang Liao2,
  5. Yupeng Zhang2,
  6. Huan Chen2,
  7. Mengxian Tu2,
  8. Guping Zhong2,
  9. Chaoliang Xiong2,
  10. Pan Zheng1,
  11. Yuting Lei1,
  12. Zekun He2,
  13. Lei Wang3,
  14. Xiaolin Gao3,
  15. Yin Zhu1
  1. 1Department of Gastroenterology, The Affiliated Hospital of Yichun University, Jiangxi Province, China
  2. 2Department of Gastroenterology, Yichun People’s Hospital, Jiangxi Province, China
  3. 3College of Animal Science and Technology, Yunnan Agricultural University, Yunnan Province, China

Abstract

Background Colorectal cancer (CRC) is the third most common cancer and the leading cause of cancer-related death worldwide. The high mortality of CRC is largely due to the late diagnosis, incomplete molecular understanding of pathological progression, and limited treatment options for patients with advanced disease stages. Therefore, the identification of novel biomarkers at the early (pre-cancerous) phase, thorough elucidation of pathological mechanisms, and development of effective therapies are crucial for CRC diagnosis and treatment.

Methods As common precursors to colorectal cancer (CRC), polyps and adenomas in the large intestine may develop into malignancy over time through a cascade known as the ‘normal-polyp-adenoma-carcinoma’ sequence. To better understand the molecular mechanisms underlying the initiation and progression of CRC, we have utilized the 10× genomics scRNA-seq platform to perform a high-resolution transcriptomic analysis of three normal colorectal tissues, two samples with inflammatory polyps, two specimens with adenomatous polyps and three CRC samples (IDDF2024-ABS-0065 Figure 1. Sample collection and cell type identification).

Results By analyzing the scRNA-seq data of the ten samples, in combination with validation by immunofluorescence staining using expanded clinical samples, and together with verification using large-scale TCGA and Kaplan–Meier data, we provided a dynamic landscape of ten clinical colorectal samples covering these four pathological phases, showed the heterogeneity of (sub-) cell types and difference of the transcriptomic profiling across the four stages (IDDF2024-ABS-0065 Figure 2. T cells, IDDF2024-ABS-0065 Figure 3. Treg cells, IDDF2024-ABS-0065 Figure 4. Epithelial cells, IDDF2024-ABS-0065 Figure 5. Fibroblasts), and demonstrated that ligand-receptor genes (IDDF2024-ABS-0065 Figure 1. Sample collection and cell type identification (F-H)), transcription factors (IDDF2024-ABS-0065 Figure 2. T cells (G,H,L,M), IDDF2024-ABS-0065 Figure 4. Epithelial cells (J-L), IDDF2024-ABS-0065 Figure 5. Fibroblasts (J-L)) and genes encoding multiple immunoglobulins and heat shock proteins (IDDF2024-ABS-0065 Figure 2. T cells (C), IDDF2024-ABS-0065 Figure 5. Fibroblasts (G)) may play distinct roles in immunity and microenvironment during colorectal malignancy. More importantly and for the first time, in-depth analyses showed that the expression of ligand-receptor genes can be used to determine the cell (sub-)types isolated from colorectal tissues (IDDF2024-ABS-0065 Figure 1. Sample collection and cell type identification).

Abstract IDDF2024-ABS-0065 Figure 1

Sample collection and cell type identification

Abstract IDDF2024-ABS-0065 Figure 2

T cells

Abstract IDDF2024-ABS-0065 Figure 3

Treg cells

Abstract IDDF2024-ABS-0065 Figure 4

Epithelial cells

Abstract IDDF2024-ABS-0065 Figure 5

Fibroblasts

Conclusions Our transcriptome data provides valuable insights and a useful resource for better understanding the molecular pathological landscape in CRC to achieve more effective diagnosis and treatments.

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