ArticleCancers2023
Sialic Acids on Tumor Cells Modulate IgA Therapy by Neutrophils via Inhibitory Receptors Siglec-7 and Siglec-9.
Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Detection of Premalignant Cervical Lesions viaBiosensors · 2025Article
- Therapeutic potential of tumor-associated neutrophils: dual role and phenotypic plasticity.Signal transduction and targeted therapy · 2025Review
- The Efficacy of Targeted Monoclonal IgA Antibodies Against Pancreatic Ductal Adenocarcinoma.Cells · 2025Article
- Targeting immune checkpoints on myeloid cells: current status and future directions.Cancer immunology, immunotherapy : CII · 2025Review
- Sialylation inhibition improves macrophage mediated tumor cell phagocytosis of breast cancer cells triggered by therapeutic antibodies of different isotypes.Frontiers in oncology · 2024Article
- Disruption of the sialic acid/Siglec-9 axis improves antibody-mediated neutrophil cytotoxicity towards tumor cells.Frontiers in immunology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
Abstract
Immunotherapy with targeted therapeutic antibodies is often ineffective in long-term responses in cancer patients due to resistance mechanisms such as overexpression of checkpoint molecules. Similar to T lymphocytes, myeloid immune cells express inhibitory checkpoint receptors that interact with ligands overexpressed on cancer cells, contributing to treatment resistance. While CD47/SIRPα-axis inhibitors in combination with IgA therapy have shown promise, complete tumor eradication remains a challenge, indicating the presence of other checkpoints. We investigated hypersialylation on the tumor cell surface as a potential myeloid checkpoint and found that hypersialylated cancer cells inhibit neutrophil-mediated tumor killing through interactions with sialic acid-binding immunoglobulin-like lectins (Siglecs). To enhance antibody-dependent cellular cytotoxicity (ADCC) using IgA as therapeutic, we explored strategies to disrupt the interaction between tumor cell sialoglycans and Siglecs expressed on neutrophils. We identified Siglec-9 as the primary inhibitory receptor, with Siglec-7 also playing a role to a lesser extent. Blocking Siglec-9 enhanced IgA-mediated ADCC by neutrophils. Concurrent expression of multiple checkpoint ligands necessitated a multi-checkpoint-blocking approach. In certain cancer cell lines, combining CD47 blockade with desialylation improved IgA-mediated ADCC, effectively overcoming resistance that remained when blocking only one checkpoint interaction. Our findings suggest that a combination of CD47 blockade and desialylation may be necessary to optimize cancer immunotherapy, considering the upregulation of checkpoint molecules by tumor cells to evade immune surveillance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.