Spatial transcriptomics reveals a new cluster of fibroblasts to promote the progression of lung adenocarcinoma
Liyang Li , Xiaoxia Liu , Yifei Liu , Xuanqi Liu , Wanxin Duan , Yujia Jiang , Jian Chen , Tianxiang Chen , Gang Chen , Ao Chen , Duojiao Wu , Dongli Song , Yuanlin Song
Clinical and Translational Discovery ›› 2026, Vol. 6 ›› Issue (3) : e70131
Methods: Our study applied spatio-temporal enhanced resolution omics-sequencing (Stereo-seq) to investigate the interactions between fibroblasts and lung cancer cells. A co-culture system of A549 lung cancer cells and HFL1 fibroblasts was established to validate the functional roles of identified fibroblast subtypes. Gene knockdown, proliferation, migration, invasion, and ELISA assays were conducted to investigate underlying mechanisms.
Results: Spatial transcriptomics revealed significant heterogeneity in LUAD tissues, with identification of a novel fibroblast cluster (C0) characterized by high expression of POSTN, THY1, BGN, and COL1A1, which co-localized with malignant epithelial cells (C5) in high-malignancy regions. Public dataset analysis confirmed C0 as CAFs, enriched in LUAD and associated with poor prognosis. Ligand-receptor analysis highlighted collagen I- and fibronectin 1-mediated interactions between C0 and C5. In vitro, co-culture with A549 induced differentiation of HFL1 into CAFs, with upregulation of COL1A1, COL1A2, and CAF markers. Knockdown of COL1A1 or COL1A2 in fibroblasts significantly reduced collagen I secretion and attenuated cancer cell proliferation, migration, and invasion, while exerting minimal effects on angiogenesis.
Conclusions: These findings not only provide a molecular map of lung cancer tissues for further study but also illustrate a novel co-location relationship between fibroblasts and cancer cells within the TME. Our results highlight the potential of CAFs as a promising therapeutic target, complementing existing approaches targeting genetic mutations and immune cells.
cancer-associated fibroblasts / lung adenocarcinoma / spatial transcriptomics
| [1] |
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| [2] |
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| [3] |
|
| [4] |
|
| [5] |
|
| [6] |
|
| [7] |
|
| [8] |
|
| [9] |
|
| [10] |
|
| [11] |
|
| [12] |
|
| [13] |
|
| [14] |
|
| [15] |
|
| [16] |
|
| [17] |
|
| [18] |
|
| [19] |
|
| [20] |
|
| [21] |
|
| [22] |
|
| [23] |
|
| [24] |
|
| [25] |
|
| [26] |
|
| [27] |
|
| [28] |
|
| [29] |
|
| [30] |
|
| [31] |
|
| [32] |
|
| [33] |
|
| [34] |
|
| [35] |
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2026 The Author(s). Clinical and Translational Discovery published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.
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