Abstract 6552: Siglec1 expression on the tumor-associated macrophage in breast cancer

Abstract Breast cancer is a common malignant tumor with four distinct subtypes, based on the presence of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 (HER2): luminal A, luminal B, HER2-enriched, and triple-negative. There is currently no effective immune checkpoint blockade (ICB) against breast cancer. The tumor microenvironment comprises not only cancer cells, but also fibroblast and tumor-infiltrating immune cells. Macrophages are the largest subset of tumor-infiltrating immune cells, called tumor-associated macrophages (TAMs). It has been reported that Siglec1 is a selective marker of TAM. Siglec1 is also known as CD169 Sialoadhesin, and is typically found on the surface of monocytes and macrophages. Macrophages can be divided into two groups: M1- and M2-like. Although Siglec1 does not belong to either of these, macrophages that express Siglec1 have been associated with immunosuppressive functions, which can facilitate tumor progression. Given the observed differences in Siglec1 mRNA expression among breast cancer subtypes, we postulated that Siglec1 protein expression would also vary between subtypes, resulting in different prognoses. We also evaluated the impact of ICB on Siglec1 expression in an immune co-culture system utilizing patient-derived organoids (PDOs). Formalin-fixed paraffin-embedded blocks were prepared from fresh frozen surgical tissues. Using them, hematoxylin and eosin staining and immunohistochemistry (IHC) were conducted, and the percentage of Siglec1+ cells was obtained from the slides. The relationship between Siglec1 expression and patient baseline characteristics, including age, hormone receptor status, HER2 status, Ki67 level, subtype, histologic grade, and TNM stage, was examined. To evaluate the impact of ICB on Siglec1 expression, PDOs were co-cultured with their own peripheral blood mononuclear cells (PBMCs) and cytokines in minimum medium. Following a 24-hour and 10- to 14-day incubation period, the immune cells were analyzed by flow cytometry. In clinicopathological analyses, no correlation was identified between Siglec1 expression and subtype, but Siglec1 expression was significantly associated with tumor stage. Furthermore, survival analysis revealed a correlation between Siglec1 expression and recurrence and/or mortality. In the co-culture system, Siglec1 was expressed in both M1- and M2-like subsets, and the ratio of Siglec1+ macrophages was decreased when PBMCs were cultured with PDOs. Administration of anti-PD-1 in the models has been observed to alter the proportion of Siglec1+ macrophages compared to the control. In conclusion, the results demonstrated that Siglec1 may be related to both subsets of macrophages and be associated with large tumors and prognosis. Anti-PD-1 treatment may influence the expression of Siglec1+ macrophages. Further investigation is required to ascertain the impact of ICB on Siglec1+ macrophages. Citation Format: Shinyoung Park, Chul Hwa Hong, Won-Ji Ryu, Jeong Dong Lee, Ja Seung Koo, Min Hwan Kim, Joo Hyuk Sohn, Hyung Seok Park. Siglec1 expression on the tumor-associated macrophage in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6552.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-6552
Primary Topic
Ferroptosis and cancer prognosis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 6552: Siglec1 expression on the tumor-associated macrophage in breast cancer

Joohyuk Sohn, Won‐Ji Ryu, Ja Seung Koo, Hyung Seok Park et al.
1 links
Cancer Research
Ferroptosis and cancer prognosis
article

Abstract 6552: Siglec1 expression on the tumor-associated macrophage in breast cancer

Joohyuk Sohn, Won‐Ji Ryu, Ja Seung Koo, Hyung Seok Park, Jeong Dong Lee, Min Hwan Kim, Shinyoung Park, C HONG
article en

Abstract

Abstract Breast cancer is a common malignant tumor with four distinct subtypes, based on the presence of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 (HER2): luminal A, luminal B, HER2-enriched, and triple-negative. There is currently no effective immune checkpoint blockade (ICB) against breast cancer. The tumor microenvironment comprises not only cancer cells, but also fibroblast and tumor-infiltrating immune cells. Macrophages are the largest subset of tumor-infiltrating immune cells, called tumor-associated macrophages (TAMs). It has been reported that Siglec1 is a selective marker of TAM. Siglec1 is also known as CD169 Sialoadhesin, and is typically found on the surface of monocytes and macrophages. Macrophages can be divided into two groups: M1- and M2-like. Although Siglec1 does not belong to either of these, macrophages that express Siglec1 have been associated with immunosuppressive functions, which can facilitate tumor progression. Given the observed differences in Siglec1 mRNA expression among breast cancer subtypes, we postulated that Siglec1 protein expression would also vary between subtypes, resulting in different prognoses. We also evaluated the impact of ICB on Siglec1 expression in an immune co-culture system utilizing patient-derived organoids (PDOs). Formalin-fixed paraffin-embedded blocks were prepared from fresh frozen surgical tissues. Using them, hematoxylin and eosin staining and immunohistochemistry (IHC) were conducted, and the percentage of Siglec1+ cells was obtained from the slides. The relationship between Siglec1 expression and patient baseline characteristics, including age, hormone receptor status, HER2 status, Ki67 level, subtype, histologic grade, and TNM stage, was examined. To evaluate the impact of ICB on Siglec1 expression, PDOs were co-cultured with their own peripheral blood mononuclear cells (PBMCs) and cytokines in minimum medium. Following a 24-hour and 10- to 14-day incubation period, the immune cells were analyzed by flow cytometry. In clinicopathological analyses, no correlation was identified between Siglec1 expression and subtype, but Siglec1 expression was significantly associated with tumor stage. Furthermore, survival analysis revealed a correlation between Siglec1 expression and recurrence and/or mortality. In the co-culture system, Siglec1 was expressed in both M1- and M2-like subsets, and the ratio of Siglec1+ macrophages was decreased when PBMCs were cultured with PDOs. Administration of anti-PD-1 in the models has been observed to alter the proportion of Siglec1+ macrophages compared to the control. In conclusion, the results demonstrated that Siglec1 may be related to both subsets of macrophages and be associated with large tumors and prognosis. Anti-PD-1 treatment may influence the expression of Siglec1+ macrophages. Further investigation is required to ascertain the impact of ICB on Siglec1+ macrophages. Citation Format: Shinyoung Park, Chul Hwa Hong, Won-Ji Ryu, Jeong Dong Lee, Ja Seung Koo, Min Hwan Kim, Joo Hyuk Sohn, Hyung Seok Park. Siglec1 expression on the tumor-associated macrophage in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6552.

Cancer ResearchVol. 85(8_Supplement_1)
Yonsei University (KR), Seoul National University Hospital (KR)
Openalex Percentile: Top 87%
Ferroptosis and cancer prognosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.