Cracking the "Cold Tumor" Barrier in Liver Cancer: How SeekSpace™ Unlocked the Spatial Code of TLS Formation
Release date : Aug 19,2026
Classification : Blog
Publication Spotlight · Journal of Hepatology · IF 40.1 How does a "cold" tumor learn to fight back? A Shanghai team mapped the complete signaling axis that builds tertiary lymphoid structures inside liver cancer — evidence no spot-based spatial platform could have produced.
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Hepatocellular carcinoma is a prototypical "immune-cold" tumor, with immunotherapy response rates that remain stubbornly low. Whether mature tertiary lymphoid structures — miniature immune hubs — form inside the tumor is a critical determinant of patient outcome. But a basic question had gone unanswered:
How do TLS actually form inside an HCC tumor?
Mainstream spot-based platforms use capture spots — often 55µm across — that typically contain dozens of mixed cells. That single design choice creates two problems that stand directly in the way of a TLS study.
01 · Localization Inference, not measurement Every spot's cell composition has to be computationally deconvoluted against an external scRNA-seq reference. TLS are built from rare B cells and dendritic cells — exactly where deconvolution error is largest. You never really know if B cells occupy the TLS core, or if the algorithm just smoothed the data into looking that way. | 02 · Origin Mixed signals, lost origin When a spot captures tumor and immune cells together, the transcriptome becomes a mixed average. You may detect CXCL12 — but not whether it came from a tumor cell, a hepatocyte, or a fibroblast. Biologically, those are entirely different stories. |
The approach One nucleus. One barcode. No inference. SeekSpace™ takes a fundamentally different approach: tissue sections undergo in-situ spatial barcoding of individual nuclei, followed by single-cell sequencing. Every SeekSpace data point corresponds to one real, physically mapped single nucleus.
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| 01 | TLS high-score regions — only in Setdb1-knockout tumors architecture Two independent TLS gene signatures scored the SeekSpace data, and the result was unequivocal: TLS hotspots appeared only in Setdb1-knockout tumors. SeekSpace directly resolved the canonical TLS architecture — B cells and dendritic cells in the core, T cells and myeloid cells at the periphery — confirming functional TLS formation after SETDB1 deletion. |
| 02 | Tracing the recruitment signal: hepatocytes secrete CXCL12 cell-of-origin CXCL12 is the critical B-cell chemoattractant — but which cell produces it is unanswerable with conventional spatial data. SeekSpace precisely localized CXCL12 to hepatocytes, cholangiocytes, fibroblasts, and tumor cells. Distance quantification showed B cells sitting significantly closer to CXCL12-positive hepatocytes in Setdb1-depleted samples, directly demonstrating that hepatocyte-secreted CXCL12 recruits B cells. |
| 03 | ERV neoantigens drive B cell maturation in situ colocalization Proving that ERV-derived neoantigens activate B cells required spatial colocalization. SeekSpace showed ERV overexpression in tumor cells surrounding TLS areas, with immunoglobulin gene signatures tightly overlapping ERV-expressing regions — direct spatial evidence that ERV neoantigens drive B cell maturation. |
This study establishes the first complete SETDB1 → cGAS–STING → CXCL12/ZBP1 → ERV regulatory axis in HCC. All of the core spatial evidence was generated exclusively by SeekSpace — physical single-cell resolution instead of algorithmic inference, direct cell-origin tracing of key signaling molecules, and robust capture even in necrotic microenvironments.
Facing similar challenges in your own tissue? If spatial resolution, rare cell detection, or cell-origin tracing is standing between you and a definitive finding, we're here to help. |
Shen SJ, Zhou K, Wang CY, et al. Setdb1 represses anti-tumor immunity and tertiary lymphoid structures in hepatocellular carcinoma. J Hepatol. 2026. DOI: 10.1016/j.jhep.2026.100123
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