Spatial transcriptomics elucidates trajectories associated with transformation in malignant peripheral nerve sheath tumors
Authors:
- Kanish MirchiaKMKanish Mirchia
- Abhishek BhattacharyaABAbhishek Bhattacharya
- Jonas Krag VikenJVJonas Krag Viken
- Grant EilersGEGrant Eilers
- Sixuan PanSPSixuan Pan
- Iowis ZhuIZIowis Zhu
- Daniel ZhangDZDaniel Zhang
- Ayesha SiddikaASAyesha Siddika
- Varun MongaVarun Monga
- Rosanna WustrackRWRosanna Wustrack
- Brian S NaBNBrian S Na
- Iain CarmichaelICIain Carmichael
Open Access
- 10 October 2026
- journal article
- Published by Oxford University Press (OUP) in Neuro-Oncology
Abstract
Background: Tumor invasion and malignant transformation are spatiotemporally coordinated processes that shape clinical behavior, diagnostic classification, and treatment response. Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive tumors that can arise sporadically or in people with neurofibromatosis type 1 (NF-1), yet how distinct spatial niches underlie MPNST intratumor heterogeneity, local invasion, or malignant transformation from benign precursors is not fully understood. Methods: We integrate spatial analysis of 50,896 transcriptomes from 15 human MPNSTs with deep learning image analysis to define the interplay between genetic alterations, the immune microenvironment, and epigenetic cell fate regulation in MPNST invasion and transformation. Results: Spatial transcriptomics reveal distinct infiltrating immune cells and immunomodulatory spatial clusters in sporadic compared to NF-1–associated MPNSTs. Local invasion is marked by spatially defined immunomodulatory and dedifferentiation programs. Analysis of 2 NF-1–associated MPNSTs with contiguous morphologically defined neurofibroma and MPNST components demonstrates that NF-1–associated tumors exhibit a similar malignant transformation process associated with dynamic immune infiltration, chromosome 9p loss, and dedifferentiation concomitant with increased cell proliferation. Finally, deep learning morphology encoders were trained on spatial transcriptomic data to predict spatial transcriptomic cluster identity and chromosome 9p loss from hematoxylin and eosin–stained images although the generalizability of such encoders remains a challenge. Conclusions: Our data provide a spatial framework for peripheral nerve sheath tumor transformation although the limited sample size of the present cohort will require additional validation of the proposed model.Keywords
Funding Information
- National Institutes of Health (R01 CA304081 and P50 CA097257)
- Francis Collins Scholar Award during the study period
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