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. 2025 Jan 27:16:1497004.
doi: 10.3389/fimmu.2025.1497004. eCollection 2025.

Immune microenvironment features underlying the superior efficacy of neoadjuvant immunochemotherapy over chemotherapy in local advanced gastric cancer

Affiliations

Immune microenvironment features underlying the superior efficacy of neoadjuvant immunochemotherapy over chemotherapy in local advanced gastric cancer

Ning Zhang et al. Front Immunol. .

Abstract

Background: The therapeutic efficacy of neoadjuvant immunotherapy combined with chemotherapy (Io+Chemo) is superior than chemotherapy alone (Chemo). However, the mechanism of Io+Chemo superiority remains to be further elucidated.

Methods: The study included 128 patients with resectable stage II-III gastric cancer, in which 63 were given neoadjuvant Io+Chemo, and 65 Chemo alone. Patients given Io+Chemo were treated with 2-4 cycles of PD-(L)1 inhibitor (Pembrolizumab, Sintililimab or Nivolumab) with S-1 and oxaliplatin (SOX) or capecitabine and oxaliplatin (XELOX) before surgical resection. Patients given Chemo were treated with 2-4 cycles of SOX or XELOX before surgical resection. Tumor tissues were evaluated for tumor-infiltrating immune cells (TIICs) using immunohistochemistry and QuPath software quantitative analysis, for detecting T, B, NK, plasma cells, and macrophages. The relationship between TIICs and different neoadjuvant treatment regimens and pathological responses was also explored.

Results: Compared with Chemo, Io+Chemo induced higher rates of pathological complete response (33.3 vs. 9.2%, p=0.001) and major pathological response (MPR) (49.2 vs. 30.8%, p=0.033). Compared with Chemo group, density of CD4+(1904.8 vs. 1530), CD8+(1982.9 vs. 1124.4), CD20+(1115.6 vs. 574), CD38+(1580.4 vs. 1128), CD138+(1237.2 vs. 496.4), and CD56+ (596.8 vs. 159) cells was increased 24.5%, 76.4%, 94.4%, 40.1%, and 149.2% respectively, whereas CD163+ macrophages (994.4 vs. 1706) was decreased 41.7% in Io+Chemo group.

Conclusions: Our study favors neoadjuvant Io+Chemo over Chemo and reveals Io+Chemo can induce the formation of an immune-activated microenvironment that make Io+Chemo superior to Chemo.

Keywords: gastric cancer; immunochemotherapy; neoadjuvant therapy; tumor immune microenvironment; tumor-infiltrating immune cells.

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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
Study design examining effects of neoadjuvant therapies on resectable LAGC patients. (A) Study flow chart depicting the study protocol. According to our inclusion and exclusion criteria, a total of 128 patients with gastric cancer who underwent surgical resection after neoadjuvant therapy were included in the trial, of which 63 received Io+Chemo and 65 received Chemo. Their pathological response and TIICs of tumor, stromal, and total (tumor + stroma) were evaluated. All samples have been evaluated TIICs in stroma. Due to 27 patients achieved pCR, i.e., no tumor cells remained, TIICs were only evaluated in stroma of these samples. (B) The endpoints explored and sample details in each analysis. ① Evaluated the pathological response of patients received neoadjuvant Io+Chemo and Chemo; ② Evaluate the effect of neoadjuvant Io+Chemo and Chemo on TIICs; ③ Evaluated the relationship between pathological response and TIICs in different treatment subgroups. LAGC, local advanced gastric cancer; TIICs, Tumor infiltrating immune cells; NAT, neoadjuvant therapy; pCR, pathological complete response; MPR, major pathological response; Io+Chemo, immunochemotherapy; Chemo, chemotherapy.
Figure 2
Figure 2
Import scanned slides into QuPath software and (A) Create annotations for tumor and stroma. (B) Separating stains, check “Estimate stain vectors” for better cell detection. (C) Select five suitable sections in each of the tumor and stroma, each with an area of 500 × 500 μm, and add annotations for them. (D) Select "Analyze" →"cell detection"→"positive detection"→check "Single threshold". (E) Select "show annotation measurements" to export the data which contains percentage and density. (F) Select "Analyze" →"cell detection"→"positive detection"→uncheck "Single threshold". (G) Select "show annotation measurements" to export the data which contains H-score values.
Figure 3
Figure 3
Comparison of TIIC subsets in patients treated with neoadjuvant Io+Chemo versus Chemo. The scatter plot was shown as median. The density and percentage of CD3 (A), CD4 (B), CD8 (C), CD20 (D), CD38 (E), CD138 (F), CD56 (G), CD68 (H), CD163 (I) were statistical different in responders and non-responders. Figure was created with R. *p<0.05; **p<0.01; ***p<0.001; ns, no statistical significance.
Figure 4
Figure 4
Comparison of TIIC between Io+Chemo and Chemo by immunohistochemistry. HE: the more immune cells in Io+Chemo specimens (A) than in Chemo specimens (B). CD4: the density of Io+Chemo specimens (C) was higher than Chemo specimens (D). CD8: the density of Io+Chemo specimens (E) was higher than Chemo specimens (F) CD20: the density of Io+Chemo specimens (G) was higher than Chemo specimens (H). CD163: the density of Io+Chemo specimens (I) was lower than Chemo specimens (J).

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