Effects of polyunsaturated fatty acids on gastric cancer immunity and immunotherapy

Abstract

Although immunotherapy has been predominant for advanced gastric cancer treatment, it still has limitations. Polyunsaturated fatty acids (PUFAs) are associated with inflammation while their roles in tumor immune microenvironment (TIME) are unclear. This study explores PUFAs' impacts on gastric cancer immunity and immunotherapy efficacy. Bioinformatics analysis was conducted to identify differential expressions of PUFAs metabolic genes and their immune correlations. Clinical data of advanced gastric cancer patients receiving immunotherapy at Zhongda Hospital (2020-2024), whose serum PUFAs were measured by mass spectrometry (MS), were collected and analyzed. Bioinformatics analysis revealed differential expression of half of PUFAs metabolic genes in gastric cancer. PUFAs metabolism towards Omega-3 (ω-3) tended to increase infiltration of active anti-tumor cells and up-regulate multiple immune checkpoints expressions, while metabolism towards Omega-6 (ω-6) led to opposite TIME outcomes. The clinical study demonstrated that lower serum ω-6/ω-3 ratio, arachidonic acid/eicosapentaenoic acid (AA/EPA) ratio, linoleic acid/alpha-linolenic acid (LA/ALA) ratio and higher EPA were associated with better six-month progression-free survival rate (6-month PFS) and one-year overall survival rate (1-year OS). This study deepens our understandings of TIME in gastric cancer. It clearly demonstrates that maintaining appropriate PUFAs ratios or values is promising in improving prognosis.

Keywords: Bioinformatics analysis; Gastric cancer; Immunotherapy; Mass spectrometry; PUFAs; Tumor immune microenvironment.

Fig. 1

The network of polyunsaturated fatty acids. It presents main PUFAs’ downstream metabolites and their inflammation correlations. ω-6 PUFAs metabolites like leukotrienes (LT), prostaglandins (PG) and thromboxanes (TX) generally lead to chronic inflammation and carcinogenesis, while ω-3 PUFAs produce resolvins, protectins and maresins which are involved in resolving acute inflammation.

Fig. 2

DEGs and enrichemnt (a) Combined PUFAs related genes heatmap of two datasets. (b) Expression volcano plot of DEGs of GSE13911 and GSE118916, respectively. (c) Enrichment degree of all categories of fatty acids metabolism related genes in GO:BP. Highlighted entries are related to PUFAs metabolism and blue entries are other top 9 significantly enriched biological processes. (d) Enrichment degree of polyunsaturated fatty acids related genes in KEGG. Red entries are related to PUFAs metabolism and blue entries are other top 10 enriched pathways ranked by significance. (e) Chord plot of crosstalk between PUFAs related genes, inflammation and cellular signaling.

Fig. 3

PUFAs and immune infiltration (a, b) ω-3 and ω-6/ω-3 PUFAs metabolism score and immune cell infiltration, respectively. Infiltration scales are transformed by log10 calculation. Significance markers: “*”: P < 0.05; “**”: P < 0.01; “***”: P < 0.001. (c) Relations between ω-3, ω-6 and ω-6/ω-3 PUFAs metabolism score and immune checkpoints expressions in gastric cancer TME, respectively. (d) PPI network of protein Interactions between PUFAs metabolic enzymes and four inflammation pathways (NF-κB, ras-raf-MAPK, PI3K-AKT and JAK-STAT).

Fig. 4

PUFAs and immunotherapy (a) correlation heatmap of determined unsaturated poly fatty acids from 70 patients. Considering multicollinearity (multicollinearity test, VIF > 10, P < 0.05), the source substrates of the two metabolic directions, LA and ALA, were separately analyzed. (b) High and low serum PUFAs level groups and therapeutic efficacy. Only those whose significance less than 0.05 are presented. (c) Survival curves based on PFS of high groups and low groups. (d) ROC curves of PUFAs’ predictive values on immunotherapy efficacy and survival. Only those whose significance less than 0.05 are presented.