Identification of lactylation-associated fibroblast subclusters predicting prognosis and cancer immunotherapy response in colon cancer.

Abstract

Background: Lactylation plays an important role in tumor progression. This study aimed to clarify the impact of lactylation on cancer-associated fibroblasts(CAFs).

Methods: Single-cell and bulk RNA sequence data, along with survival information, were obtained from TCGA and GEO datasets. Significant lactylation-associated genes were acquired by differential analysis and used to construct a prognostic model via Cox and LASSO regression analyses. Next, single-cell analysis, enrichment and pathway analysis, pseudotemporal trajectory and survival analysis were used to identify significant lactylation-associated fibroblast subclusters in colon cancer. IMvigor210 and PRJEB23709 cohorts were applied to assess the response to immunotherapy. In vitro experiments were conducted to explore how lactylation affect fibroblasts.

Results: We established a lactylation-associated prognostic model with 17 risk genes in TCGA and further validated it in GEO datasets. Single-cell analysis revealed the lactylation level of fibroblasts in colon cancer was greater than that in normal tissues. Moreover, five lactylation-associated fibroblast subclusters were identified via the NMF algorithm. Patients with lower scores of FB_2_CALD1, FB_3_TPM4 and FB_4_AHNAK subclusters had better clinical prognosis in colon cancer and were more likely to benefit from immunotherapy. Further experiments demonstrated that lactylation could enhance the proliferation, migration and invasion ability of fibroblasts and up-regulate the expression of COL1A1, which was similar to the effect of colon cancer cells.

Conclusion: This study identified key fibroblast subclusters with prognostic value and implied that lactylation might help transform fibroblasts into CAFs in colon cancer for the first time, which provides new paths for understanding the evolution of CAFs and cancer therapeutic strategies.