Biology subjects

Xi, F.

Publications and source records attributed to Xi, F..

6 recordsLinked to original sources

bioRxiv2026

FLASH X-rays preserve neutrophil chromatin to boost antitumor immunity

Ultrahigh dose-rate FLASH radiotherapy spares normal tissue while preserving antitumor activity, positioning it as a promising technology in radiation oncology, but its immunomodulatory mechanisms remain elusive. Here, using a bilateral subcutaneous tumor model in mice, we show that 8-Gy FLASH X-rays, versus an equal dose of conventional dose-rate (CONV) X-rays, elicit a robust abscopal antitumor effect with anti-PD-1 therapy. Single-cell transcriptome and T cell receptor (TCR) profiling reveal that FLASH X-rays plus anti-PD-1 enhance antitumor immune infiltration and TCR clonal expansion in both irradiated and abscopal tumor lesions. Mechanistically, the ultrashort temporal continuity of FLASH dose delivery conserves chromatin compaction in neutrophils during exposure and inhibits neutrophil extracellular trap (NET) formation, thereby dismantling NET-mediated CD8+ T-cell exclusion within primary tumors. Conversely, CONV or split-dose FLASH X-rays induce marked chromatin modifications prior to dose completion, leading to chromatin hyper-relaxation which promotes NETosis and consequently abrogates systemic antitumor immunity. Notably, this detrimental effect can be reversed by pharmacologically suppressing PARylation-mediated chromatin modification and decondensation in neutrophils. These findings identify radiation-induced aberrant chromatin relaxation in neutrophils as a critical determinant of radioimmunotherapy outcomes, providing a rationale for redefining the FLASH effect and advancing its clinical translation.

cancer biology↗

bioRxiv2025

ST-FFPE-mIF: Integrating Spatial Transcriptomics and Multiplex Immunofluorescence in Formalin-Fixed Paraffin-Embedded Tissues Using Stereo-seq

Stereo-seq is the state-of-the-art technique, which allows capturing of spatial transcriptomic data at sub-cellular resolution and in large scale of view. Stereo-seq FFPE technique is recently launched with the capability to obtain spatially resolved gene expression in FFPE tissue sections. However, the omic information is limited to transcriptome. To delineate spatial molecular hierarchy from transcriptome to phenome, we present the protocol that implements nine-plex immunofluorescence staining with detection of spatial transcriptomics in one FFPE tissue section (short for ST-FFPE-mIF). This protocol details the modified biochemistry procedure and also provides analytical framework to achieve single-cell resolution through nuclear or membrane staining-based cell segmentation. We demonstrated the application of ST-FFPE-mIF in colorectal cancer sample to illustrate how ST-FFPE-mIF facilitates a robust analysis of spatially resolved multi-omic data at the single-cell level.

biochemistry↗

bioRxiv2024

SCIITensor: A tensor decomposition based algorithm to construct actionable TME modules with spatially resolved intercellular communications

Advanced spatial transcriptomics (ST) technology has paved the way for elucidating the spatial architecture of the tumor microenvironment (TME) from multiple perspectives. However, available tools only focus on the static molecular and cellular composition of the TME when analyzing the high-throughput ST data, neglecting to uncover the in-depth spatial co-variation of intercellular communications arising from heterogeneous spatial TMEs. Here, we introduce SCIITensor, which decomposes TME modules from the perspective of spatially resolved intercellular communication by spatially quantifying the cellular and molecular interaction intensities between proximal cells within each domain. It then constructs a three-dimensional matrix, formulating the task as a matrix decomposition problem, and identifies biologically relevant spatial interactions and TME patterns using Non-Negative Tucker Decomposition (NTD). We evaluated the performance of SCIITensor on liver cancer datasets obtained from multiple ST platforms. At the research setting of a single-sample investigation, SCIITensor precisely identified a functional TME module indicating a tumor boundary structure specific domain with co-variant interaction contexts, which were involved in construction of immunosuppressive TME. Moreover, we also proved that SCIITensor was able to construct TME meta-modules across multiple samples and to further identify an immune-infiltration associated and sample-common meta-module. We demonstrate that SCIITensor is applicable for dissecting TME modules from a new perspective by constructing spatial interaction contexts using ST datasets of individual and multiple samples, providing new insights into tumor research and potential therapeutic targets.

bioinformatics↗

bioRxiv2024

StereoMM: A Graph Fusion Model for Integrating Spatial Transcriptomic Data and Pathological Images

Spatially resolved omics technologies generating multimodal and high-throughput data lead to the urgent need for advanced analysis to allow the biological discoveries by comprehensively utilizing information from multi-omics data. The H&E image and spatial transcriptomic data indicate abundant features which are different and complementary to each other. AI algorithms can perform nonlinear analysis on these aligned or unaligned complex datasets to decode tumoral heterogeneity for detecting functional domain. However,the interpretability of AI-generated outcomes for human experts is a problem hindering application of multi-modal analysis in clinic. We presented a machine learning based toolchain called StereoMM, which is a graph fusion model that can integrate gene expression, histological images, and spatial location. StereoMM firstly performs information interaction on transcriptomic and imaging features through the attention module, guaranteeing explanations for its decision-making processes. The interactive features are input into the graph autoencoder together with the graph of spatial position, so that multimodal features are fused in a self-supervised manner. Here, StereoMM was subjected to mouse brain tissue, demonstrating its capability to discern fine tissue architecture, while highlighting its advantage in computational speed. Utilizing data from Stereo-seq of human lung adenosquamous carcinoma and 10X Visium of human breast cancer, we showed its superior performance in spatial domain recognition over competing software and its ability to reveal tumor heterogeneity. The fusion approach for imaging and gene expression data within StereoMM aids in the more accurate identification of domains, unveils critical molecular features, and elucidates the connections between different domains, thereby laying the groundwork for downstream analysis.

bioinformatics↗

bioRxiv2022

StereoSiTE: A framework to spatially and quantitatively profile the cellular neighborhood organized iTME

With emerging of Spatial Transcriptomics (ST) technology, a powerful algorithmic framework to quantitatively evaluate the active cell-cell interactions in the bio-function associated iTME unit will pave the ways to understand the mechanism underlying tumor biology. This study provides the StereoSiTE incorporating open source bioinformatics tools with the self-developed algorithm, SCII, to dissect a cellular neighborhood (CN) organized iTME based on cellular compositions, and to accurately infer the functional cell-cell communications with quantitatively defined interaction intensity in ST data. We applied StereoSiTE to deeply decode ST data of the xenograft models receiving immunoagonist. Results demonstrated that the neutrophils dominated CN5 might attribute to iTME remodeling after treatment. To be noted, SCII analyzed the spatially resolved interaction intensity inferring a neutrophil leading communication network which was proved to actively function by analysis of Transcriptional Factor Regulon and Protein-Protein Interaction. Altogether, StereoSiTE is a promising framework for ST data to spatially reveal tumoribiology mechanisms.

cancer biology↗

bioRxiv2019

Calcium/calmodulin-dependent protein kinase II regulates mammalian axon growth by affecting F-actin length in growth cone

While axon regeneration is a key determinant of functional recovery of the nervous system after injury, it is often poor in the mature nervous system. Influx of extracellular calcium (Ca2+) is one of the first phenomena that occur following axonal injury, and calcium/calmodulin-dependent protein kinase (CaMKII), a target protein for calcium ions, regulates the status of cytoskeletal proteins such as F-actin. Herein, we found that peripheral axotomy activates CaMKII in dorsal root ganglion (DRG) sensory neurons, and inhibition of CaMKII impairs axon growth in both the peripheral and central nervous systems (PNS and CNS, respectively). Most importantly, we also found that activation of CaMKII promotes PNS and CNS axon growth, and regulatory effects of CaMKII on axon growth occur via affecting the length of the F-actin. Thus, we believe our findings provide clear evidence that CaMKII is a critical modulator of mammalian axon regeneration.

neuroscience↗