Integrated multi-regional multiomic profiling of breast phyllodes tumours reveals peritumoural immune activation and stromal remodelling

Tian-Qi Gu , Lei Wang , Xiang-Rong Wu , Qiang Zheng , Fei-Lin Qu , Chao Chen , Gen-Hong Di , Zhi-Ming Shao , A-Yong Cao

Clinical and Translational Medicine ›› 2026, Vol. 16 ›› Issue (4) : e70644

PDF (4040KB)
Clinical and Translational Medicine ›› 2026, Vol. 16 ›› Issue (4) :e70644 DOI: 10.1002/ctm2.70644
RESEARCH ARTICLE
Integrated multi-regional multiomic profiling of breast phyllodes tumours reveals peritumoural immune activation and stromal remodelling
Author information +
History +
PDF (4040KB)

Abstract

Background: Breast malignant phyllodes tumours are rare fibroepithelial neoplasms arising from periductal stromal cells, characterized by rapid progression and a high recurrence rate. The poor prognosis largely stems from the lack of effective therapeutic strategies, underscoring the insufficient understanding of their molecular mechanisms and therapeutic targets. Moreover, most previous studies have mainly focused on the tumour core, while the molecular features of the surrounding peritumoural tissue remain insufficiently explored.

Methods: To address this problem, we collected 66 phyllodes tumour specimens from 22 patients, including benign, borderline and malignant subtypes. For each case, paired samples were obtained from the tumour core and peritumoural regions. Multi-regional genomic, transcriptomic and digital pathology analyses were performed to characterize spatial patterns of tumour evolution. In addition, multiplex immunofluorescence was applied to validate the spatial distribution of key cellular and molecular features.

Results: Malignant phyllodes tumours exhibited markedly enhanced proliferative activity compared with benign and borderline counterparts. Malignant tumours were also characterized by a distinctly immune activated peritumoural niche encasing an immune excluded tumour core. Specifically, the peritumoural regions displayed abundant lymphocyte infiltration and close immune cell clustering, whereas the intratumoral compartments were largely devoid of immune cells. Enhanced angiogenesis and collagen remodelling were observed in the peritumoural compartment. In malignant phyllodes tumour patients, a more pronounced spatial immune segregation phenotype may be associated with a lower risk of recurrence.

Conclusion: These results provide an integrated view of phyllodes tumour progression and identify immune exclusion as a defining feature of malignancy. The unique biological characteristics of the peritumoural region may serve as valuable therapeutic targets, offering potential for combined anti-angiogenesis agents and immunotherapy strategies to overcome the immune excluded microenvironment of malignant phyllodes tumours.

Keywords

angiogenesis / breast phyllodes tumour / extracellular matrix remodelling / immune exclusion / peritumoural microenvironment

Cite this article

Download citation ▾
Tian-Qi Gu, Lei Wang, Xiang-Rong Wu, Qiang Zheng, Fei-Lin Qu, Chao Chen, Gen-Hong Di, Zhi-Ming Shao, A-Yong Cao. Integrated multi-regional multiomic profiling of breast phyllodes tumours reveals peritumoural immune activation and stromal remodelling. Clinical and Translational Medicine, 2026, 16 (4) : e70644 DOI:10.1002/ctm2.70644

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Valenza C, De Pas TM, Gaeta A, et al. Primary malignant phyllodes tumors of the breast: a retrospective analysis from a referral center. Eur J Cancer. 2024; 196:113423.

[2]

Papas Y, Asmar AE, Ghandour F, Hajj I. Malignant phyllodes tumors of the breast: a comprehensive literature review. Breast J. 2020; 26: 240-244.

[3]

Li J, Ho W, Tsang JYS, Ni Y, Chan S, Tse GM. Expression of biomarkers in the AKT pathway correlates with malignancy and recurrence in phyllodes tumours of the breast. Histopathology. 2019; 74: 567-577.

[4]

Parkes A, Wang W, Patel S, et al. Outcomes of systemic therapy in metastatic phyllodes tumor of the breast. Breast Cancer Res Treat. 2021; 186: 871-882.

[5]

Mao Y, Xiong Z, Wu S, et al. The predictive value of magnetic resonance imaging-based texture analysis in evaluating histopathological grades of breast phyllodes tumor. J Breast Cancer. 2022; 25: 117-130.

[6]

Urbaniak A, Jousheghany F, Yuan Y, et al. The response of phyllodes tumor of the breast to anticancer therapy: an in vitro and ex vivo study. Oncol Lett. 2019; 18: 5097-5106.

[7]

Zhao W, Tian Q, Zhao A, et al. The role of adjuvant radiotherapy in patients with malignant phyllodes tumor of the breast: a propensity-score matching analysis. Breast Cancer. 2021; 28: 110-118.

[8]

Tan J, Ong CK, Lim WK, et al. Genomic landscapes of breast fibroepithelial tumors. Nat Genet. 2015; 47: 1341-1345.

[9]

Gong C, Nie Y, Qu S, et al. miR-21 induces myofibroblast differentiation and promotes the malignant progression of breast phyllodes tumors. Cancer Res. 2014; 74: 4341-4352.

[10]

Nie Y, Chen J, Huang D, et al. Tumor-associated macrophages promote malignant progression of breast phyllodes tumors by inducing myofibroblast differentiation. Cancer Res. 2017; 77: 3605-3618.

[11]

Zhu B, Tapinos A, Koka H, et al. Genomes and epigenomes of matched normal and tumor breast tissue reveal diverse evolutionary trajectories and tumor-host interactions. Am J Hum Genet. 2024; 111: 2773-2788.

[12]

Trujillo KA, Heaphy CM, Mai M, et al. Markers of fibrosis and epithelial to mesenchymal transition demonstrate field cancerization in histologically normal tissue adjacent to breast tumors. Int J Cancer. 2011; 129: 1310-1321.

[13]

Aran D, Camarda R, Odegaard J, et al. Comprehensive analysis of normal adjacent to tumor transcriptomes. Nat Commun. 2017; 8: 1077.

[14]

Cheng C, Nguyen TT, Tang M, et al. Immune infiltration in tumor and adjacent non-neoplastic regions codetermines patient clinical outcomes in early-stage lung cancer. J Thorac Oncol. 2023; 18: 1184-1198.

[15]

Kim J, Kim H, Lee M, et al. Transcriptomes of the tumor-adjacent normal tissues are more informative than tumors in predicting recurrence in colorectal cancer patients. J Transl Med. 2023; 21: 209.

[16]

Rosenberger LH, Thomas SM, Nimbkar SN, et al. Contemporary multi-institutional cohort of 550 cases of phyllodes tumors (2007-2017) demonstrates a need for more individualized margin guidelines. J Clin Oncol. 2021; 39: 178-189.

[17]

Nie Y, Huang H, Guo M, et al. Breast phyllodes tumors recruit and repolarize tumor-associated macrophages via secreting CCL5 to promote malignant progression, which can be inhibited by CCR5 inhibition therapy. Clin Cancer Res. 2019; 25: 3873-3886.

[18]

Chen J, Xu Q, Liu D, et al. CD146 promotes malignant progression of breast phyllodes tumor through suppressing DCBLD2 degradation and activating the AKT pathway. Cancer Commun (Lond). 2023; 43: 1244-1266.

[19]

Gong Y, Ji P, Yang Y, et al. Metabolic-pathway-based subtyping of triple-negative breast cancer reveals potential therapeutic targets. Cell Metab. 2021; 33: 51-64.e59.

[20]

Borella F, Porpiglia M, Gallio N, et al. Borderline phyllodes breast tumors: a comprehensive review of recurrence, histopathological characteristics, and treatment modalities. Curr Oncol. 2025; 32: 66.

[21]

Freitas KA, Belk JA, Sotillo E, et al. Enhanced T cell effector activity by targeting the mediator kinase module. Science. 2022; 378:eabn5647.

[22]

Tang Y, Tang S, Yang W, et al. MED12 loss activates endogenous retroelements to sensitise immunotherapy in pancreatic cancer. Gut. 2024; 73: 1999-2011.

[23]

Shi WY, Liu KJ, Esfahani MS, et al. Field-effect-informed urine liquid biopsy for bladder cancer. Cell. 2026; 189: 1024-1038.e1029.

[24]

Zhao S, Chen D, Fu T, et al. Single-cell morphological and topological atlas reveals the ecosystem diversity of human breast cancer. Nat Commun. 2023; 14: 6796.

[25]

Ma D, Dai L, Wu X, et al. Spatial determinants of antibody-drug conjugate SHR-A1811 efficacy in neoadjuvant treatment for HER2-positive breast cancer. Cancer Cell. 2025; 43: 1061-1075.e1067.

[26]

Punovuori K, Bertillot F, Miroshnikova YA, et al. Multiparameter imaging reveals clinically relevant cancer cell-stroma interaction dynamics in head and neck cancer. Cell. 2024; 187: 7267-7284.e7220.

[27]

Schweizer L, Kenny HA, Krishnan R, et al. Spatial proteo-transcriptomic profiling reveals the molecular landscape of borderline ovarian tumors and their invasive progression. Cancer Cell. 2025; 43: 1495-1511.e1497.

[28]

Kanchanawong P, Calderwood DA. Organization, dynamics and mechanoregulation of integrin-mediated cell-ECM adhesions. Nat Rev Mol Cell Biol. 2023; 24: 142-161.

[29]

Yun J, Heo W, Lee E, et al. An integrative approach for exploring the nature of fibroepithelial neoplasms. Br J Cancer. 2023; 128: 626-637.

[30]

Li X, Yu X, Bi J, et al. Integrating single-cell and spatial transcriptomes reveals COL4A1/2 facilitates the spatial organisation of stromal cells differentiation in breast phyllodes tumours. Clin Transl Med. 2024; 14:e1611.

[31]

Lin H, Hua J, Wang Y, et al. Prognostic and predictive values of a multimodal nomogram incorporating tumor and peritumor morphology with immune status in resectable lung adenocarcinoma. J Immunother Cancer. 2025; 13:e010723.

[32]

Wang D, Lei Q, Yang L, et al. Tumor exosomal HIF2A induce peritumoral M2 macrophages accumulation to facilitate intestinal invasion in colorectal cancer. Theranostics. 2025; 15: 7709-7725.

[33]

Nozad S, Sheehan CE, Gay LM, et al. Comprehensive genomic profiling of malignant phyllodes tumors of the breast. Breast Cancer Res Treat. 2017; 162: 597-602.

[34]

Wang F, Dong J, Xu Y, et al. Turning attention to tumor-host interface and focus on the peritumoral heterogeneity of glioblastoma. Nat Commun. 2024; 15:10885.

[35]

Gu L, Zhu Y, Lee M, et al. Angiotensin II receptor inhibition ameliorates liver fibrosis and enhances hepatocellular carcinoma infiltration by effector T cells. Proc Natl Acad Sci U S A. 2023; 120:e2300706120.

[36]

Fercana GR, Yerneni S, Billaud M, et al. Perivascular extracellular matrix hydrogels mimic native matrix microarchitecture and promote angiogenesis via basic fibroblast growth factor. Biomaterials. 2017; 123: 142-154.

[37]

Zhang S, Regan K, Najera J, Grinstaff MW, Datta M, Nia HT. The peritumor microenvironment: physics and immunity. Trends Cancer. 2023; 9: 609-623.

[38]

Wan M, Mei J, Cai Y, et al. Targeting IGF1R overcomes armored and cold tumor microenvironment and boosts immune checkpoint blockade in triple-negative breast cancer. Adv Sci (Weinh). 2025; 12:e01341.

[39]

Khan KA, Caunt Mitzner M, Cruz-Munoz W, et al. Modulation of fibronectin extracellular matrix enhances anti-tumor efficacy of immune checkpoint blockade. Cell Rep Med. 2025; 6:102322.

[40]

Jiang Y, Ma D, Jin X, et al. Integrated multiomic profiling of breast cancer in the Chinese population reveals patient stratification and therapeutic vulnerabilities. Nat Cancer. 2024; 5: 673-690.

[41]

Hänzelmann S, Castelo R, Guinney J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinformatics. 2013; 14: 7.

[42]

Racle J, Gfeller D. EPIC: a tool to estimate the proportions of different cell types from bulk gene expression data. Methods Mol Biol. 2020; 2120: 233-248.

[43]

Becht E, Giraldo NA, Lacroix L, et al. Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression. Genome Biol. 2016; 17: 218.

[44]

Finotello F, Mayer C, Plattner C, et al. Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data. Genome Med. 2019; 11: 34.

[45]

Aran D, Hu Z, Butte AJ. xCell: digitally portraying the tissue cellular heterogeneity landscape. Genome Biol. 2017; 18: 220.

[46]

Abkevich V, Iliev D, Timms KM, et al. Computational method for estimating DNA copy numbers in normal samples, cancer cell lines, and solid tumors using array comparative genomic hybridization. J Biomed Biotechnol. 2010; 2010:386870.

[47]

Graham S, Vu QD, Raza SEA, et al. Hover-Net: simultaneous segmentation and classification of nuclei in multi-tissue histology images. Med Image Anal. 2019; 58:101563.

[48]

Zhou Y, Graham S, Koohbanani NA, Shaban M, Heng PA, Rajpoot N, CGC-Net: Cell Graph Convolutional Network for Grading of Colorectal Cancer Histology Images. in 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW). 2019.

[49]

Wang J, Chen RJ, Lu MY, Baras A, Mahmood F, in 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). 239-243 (IEEE).

RIGHTS & PERMISSIONS

2026 The Author(s). Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.

PDF (4040KB)

2

Accesses

0

Citation

Detail

Sections
Recommended

/