An invasive zone in human liver cancer identified by Stereo-seq promotes hepatocyte-tumor cell crosstalk, local immunosuppression and tumor progression

FPR1 signaling aberrantly regulates S100A8/A9 production by CD14+FCN1hi macrophages and aggravates pulmonary pathology in severe COVID-19

Excessive alarmins S100A8/A9 escalate the inflammation and even exacerbate immune-driven thrombosis and multi-organ damage. However, the regulatory mechanisms of S100A8/A9 expression in infectious diseases remain unclear. In this study, high-dimensional transcriptomic data analyses revealed a high proportion of CD14+FCN1hi macrophages within the pulmonary niche post-severe SARS-CoV-2 infection. By constructing the S100-coexpression gene list and supervised module scoring, we found that CD14+FCN1hi macrophages presented the highest scores of alarmin S100, and possibly served as the trigger and amplifier of inflammation in severe COVID-19. These CD14+FCN1hi cells lacked the positive regulatory activity of transcription factor PPARγ, and lost their differentiation ability towards mature macrophages. Ex vivo experiments further validated that the epithelial cells with high ORF-3a expression promoted the expression and secretion of S100A8/A9 through ANXA1/SAA1-FPR1 signaling. S100A8/A9 heterodimers, as well as the co-localization of S100A8/A9 with microtubules, were both diminished by the FPR1 inhibitor. Phospho-kinase protein array indicated that STAT3 promoted transcription, and PLC-γ and ERK1/2 pathways were involved in the hetero-dimerization and unconventional secretion of S100A8/A9. Our study highlights the pivotal role of FPR1 signaling in the excessive production of S100A8/A9 and provides a promising target for the prevention and control of severe COVID-19 and post-acute COVID-19 sequelae.

Spatial oncology: Translating contextual biology to the clinic

Microscopic examination of cells in their tissue context has been the driving force behind diagnostic histopathology over the past two centuries. Recently, the rise of advanced molecular biomarkers identified through single cell profiling has increased our understanding of cellular heterogeneity in cancer but have yet to significantly impact clinical care. Spatial technologies integrating molecular profiling with microenvironmental features are poised to bridge this translational gap by providing critical in situ context for understanding cellular interactions and organization. Here, we review how spatial tools have been used to study tumor ecosystems and their clinical applications. We detail findings in cell-cell interactions, microenvironment composition, and tissue remodeling for immune evasion and therapeutic resistance. Additionally, we highlight the emerging role of multi-omic spatial profiling for characterizing clinically relevant features including perineural invasion, tertiary lymphoid structures, and the tumor-stroma interface. Finally, we explore strategies for clinical integration and their augmentation of therapeutic and diagnostic approaches.

Global research trends in the tumor microenvironment of hepatocellular carcinoma: insights based on bibliometric analysis

Objective

This study aimed to use visual mapping and bibliometric analysis to summarize valuable information on the tumor microenvironment (TME)-related research on hepatocellular carcinoma (HCC) in the past 20 years and to identify the research hotspots and trends in this field.

Methods

We screened all of the relevant literature on the TME of HCC in the Web of Science database from 2003 to 2023 and analysed the research hotspots and trends in this field via VOSviewer and CiteSpace.

Results

A total of 2,157 English studies were collected. According to the prediction, the number of papers that were published in the past three years will be approximately 1,394, accounting for 64.63%. China published the most papers (n=1,525) and had the highest total number of citations (n=32,253). Frontiers In Immunology published the most articles on the TME of HCC (n=75), whereas, Hepatology was the journal with the highest total number of citations (n=4,104) and average number of citations (n=91). The four clusters containing keywords such as "cancer-associated fibroblasts", "hepatic stellate cells", "immune cells", "immunotherapy", "combination therapy", "landscape", "immune infiltration", and "heterogeneity" are currently hot research topics in this field. The keywords "cell death", "ferroptosis", "biomarkers", and "prognostic features" have emerged relatively recently, and these research directions are becoming increasingly popular.

Conclusions

We identified four key areas of focus in the study of the TME in HCC: the main components and roles in the TME, immunotherapy, combination therapy, and the microenvironmental landscape. Moreover, the result of our study indicate that effect of ferroptosis on the TME in HCC may become a future research trend.

Single-cell and spatial omics unravel the spatiotemporal biology of tumour border invasion and haematogenous metastasis

Solid tumours exhibit a well-defined architecture, comprising a differentiated core and a dynamic border that interfaces with the surrounding tissue. This border, characterised by distinct cellular morphology and molecular composition, serves as a critical determinant of the tumour's invasive behaviour. Notably, the invasive border of the primary tumour represents the principal site for intravasation of metastatic cells. These cells, known as circulating tumour cells (CTCs), function as 'seeds' for distant dissemination and display remarkable heterogeneity. Advancements in spatial sequencing technology are progressively unveiling the spatial biological features of tumours. However, systematic investigations specifically targeting the characteristics of the tumour border remain scarce. In this comprehensive review, we illuminate key biological insights along the tumour body-border-haematogenous metastasis axis over the past five years. We delineate the distinctive landscape of tumour invasion boundaries and delve into the intricate heterogeneity and phenotype of CTCs, which orchestrate haematogenous metastasis. These insights have the potential to explain the basis of tumour invasion and distant metastasis, offering new perspectives for the development of more complex and precise clinical interventions and treatments.

A quartet of cancer stem cell niches in hepatocellular carcinoma

Hepatocellular Carcinoma (HCC), the most prevalent type of primary liver cancer, is known for its aggressive behavior and poor prognosis. The Cancer Stem Cell theory, which postulates the presence of a small population of self-renewing cells called Cancer Stem Cells (CSCs), provides insights into various clinical and molecular features of HCC such as tumor heterogeneity, metabolic adaptability, therapy resistance, and recurrence. These CSCs are nurtured in the tumor microenvironment (TME), where a mix of internal and external factors creates a tumor-supportive niche that is continuously evolving both spatially and temporally, thus enhancing the tumor's complexity. This review details the origins of hepatic CSCs (HCSCs) and the factors influencing their stem-like qualities. It highlights the reciprocal crosstalk between HCSCs and the TME (hypoxic, vascular, invasive, and immune niches), exploring the signaling pathways involved and how these interactions control the malignant traits of CSCs. Additionally, it discusses potential therapeutic approaches targeting the HCSC niche and their possible uses in clinical practice.

Unveiling contact-mediated cellular crosstalk

Cell-cell interactions orchestrate complex functions in multicellular organisms, forming a regulatory network for diverse biological processes. Their disruption leads to disease states. Recent advancements - including single-cell sequencing and spatial transcriptomics, coupled with powerful bioengineering and molecular tools - have revolutionized our understanding of how cells respond to each other. Notably, spatial transcriptomics allows us to analyze gene expression changes based on cell proximity, offering a unique window into the impact of cell-cell contact. Additionally, computational approaches are being developed to decipher how cell contact governs the symphony of cellular responses. This review explores these cutting-edge approaches, providing valuable insights into deciphering the intricate cellular changes influenced by cell-cell communication.

A genetic variant in the TAPBP gene enhances cervical cancer susceptibility by increasing m6A modification

Genetic variants can affect gene expression by altering the level of N6-methyladenosine (m6A) modifications. A better understanding of the association of these genetic variants with susceptibility to cervical cancer (CC) can promote advances in disease screening and treatment. Genome-wide identification of m6A-associated functional SNPs for CC was performed using the TCGA and JENGER databases, incorporating the data from RNA-seq and MeRIP-seq. The screened risk-associated SNP rs1059288 (A>G), which is located in the 3' UTR of TAPBP, was further validated in a case-control study involving 921 cases and 1077 controls. The results revealed a significant association between rs1059288 and the risk of CC (OR 1.48, 95% CI 1.13-1.92). Mechanistically, the presence of the risk G allele of rs1059288 was associated with increased m6A modification of TAPBP compared with the A allele. This modification was facilitated by the m6A methyltransferase METTL14 and the reading protein YTHDF2. Immunohistochemical staining of tissue microarrays containing 61 CC and 45 normal tissues showed an overexpression of TAPBP in CC. Furthermore, the upregulation of TAPBP promoted the growth and migration of CC cells as well as tumor-forming ability, inhibited apoptosis, and conferred increased resistance to commonly used chemotherapeutic drugs such as bleomycin, cisplatin, and doxorubicin. Knockdown of TAPBP inhibited the JAK/STAT/MICB signaling pathway in CC cells and upregulated certain immune genes including ISG15, IRF3, PTPN6, and HLA-A. These findings offer insights into the involvement of genetic variations in TAPBP in the development and progression of CC.

Next-generation spatial transcriptomics: unleashing the power to gear up translational oncology

The growing advances in spatial transcriptomics (ST) stand as the new frontier bringing unprecedented influences in the realm of translational oncology. This has triggered systemic experimental design, analytical scope, and depth alongside with thorough bioinformatics approaches being constantly developed in the last few years. However, harnessing the power of spatial biology and streamlining an array of ST tools to achieve designated research goals are fundamental and require real-world experiences. We present a systemic review by updating the technical scope of ST across different principal basis in a timeline manner hinting on the generally adopted ST techniques used within the community. We also review the current progress of bioinformatic tools and propose in a pipelined workflow with a toolbox available for ST data exploration. With particular interests in tumor microenvironment where ST is being broadly utilized, we summarize the up-to-date progress made via ST-based technologies by narrating studies categorized into either mechanistic elucidation or biomarker profiling (translational oncology) across multiple cancer types and their ways of deploying the research through ST. This updated review offers as a guidance with forward-looking viewpoints endorsed by many high-resolution ST tools being utilized to disentangle biological questions that may lead to clinical significance in the future.

SpaTopic: A statistical learning framework for exploring tumor spatial architecture from spatially resolved transcriptomic data

Tumor tissues exhibit a complex spatial architecture within the tumor microenvironment (TME). Spatially resolved transcriptomics (SRT) is promising for unveiling the spatial structures of the TME at both cellular and molecular levels, but identifying pathology-relevant spatial domains remains challenging. Here, we introduce SpaTopic, a statistical learning framework that harmonizes spot clustering and cell-type deconvolution by integrating single-cell transcriptomics and SRT data. Through topic modeling, SpaTopic stratifies the TME into spatial domains with coherent cellular organization, facilitating refined annotation of the spatial architecture with improved performance. We assess SpaTopic across various tumor types and show accurate prediction of tertiary lymphoid structures and tumor boundaries. Moreover, marker genes derived from SpaTopic are transferrable and can be applied to mark spatial domains in other datasets. In addition, SpaTopic enables quantitative comparison and functional characterization of spatial domains across SRT datasets. Overall, SpaTopic presents an innovative analytical framework for exploring, comparing, and interpreting tumor SRT data.

Pre-metastatic niche: formation, characteristics and therapeutic implication

Distant metastasis is a primary cause of mortality and contributes to poor surgical outcomes in cancer patients. Before the development of organ-specific metastasis, the formation of a pre-metastatic niche is pivotal in promoting the spread of cancer cells. This review delves into the intricate landscape of the pre-metastatic niche, focusing on the roles of tumor-derived secreted factors, extracellular vesicles, and circulating tumor cells in shaping the metastatic niche. The discussion encompasses cellular elements such as macrophages, neutrophils, bone marrow-derived suppressive cells, and T/B cells, in addition to molecular factors like secreted substances from tumors and extracellular vesicles, within the framework of pre-metastatic niche formation. Insights into the temporal mechanisms of pre-metastatic niche formation such as epithelial-mesenchymal transition, immunosuppression, extracellular matrix remodeling, metabolic reprogramming, vascular permeability and angiogenesis are provided. Furthermore, the landscape of pre-metastatic niche in different metastatic organs like lymph nodes, lungs, liver, brain, and bones is elucidated. Therapeutic approaches targeting the cellular and molecular components of pre-metastatic niche, as well as interventions targeting signaling pathways such as the TGF-β, VEGF, and MET pathways, are highlighted. This review aims to enhance our understanding of pre-metastatic niche dynamics and provide insights for developing effective therapeutic strategies to combat tumor metastasis.

Spatiotemporal metabolomic approaches to the cancer-immunity panorama: a methodological perspective

Metabolic reprogramming drives the development of an immunosuppressive tumor microenvironment (TME) through various pathways, contributing to cancer progression and reducing the effectiveness of anticancer immunotherapy. However, our understanding of the metabolic landscape within the tumor-immune context has been limited by conventional metabolic measurements, which have not provided comprehensive insights into the spatiotemporal heterogeneity of metabolism within TME. The emergence of single-cell, spatial, and in vivo metabolomic technologies has now enabled detailed and unbiased analysis, revealing unprecedented spatiotemporal heterogeneity that is particularly valuable in the field of cancer immunology. This review summarizes the methodologies of metabolomics and metabolic regulomics that can be applied to the study of cancer-immunity across single-cell, spatial, and in vivo dimensions, and systematically assesses their benefits and limitations.

Spatial resolved transcriptomics reveals distinct cross-talk between cancer cells and tumor-associated macrophages in intrahepatic cholangiocarcinoma

BACKGROUND

Multiple studies have shown that tumor-associated macrophages (TAMs) promote cancer initiation and progression. However, the reprogramming of macrophages in the tumor microenvironment (TME) and the cross-talk between TAMs and malignant subclones in intrahepatic cholangiocarcinoma (iCCA) has not been fully characterized, especially in a spatially resolved manner. Deciphering the spatial architecture of variable tissue cellular components in iCCA could contribute to the positional context of gene expression containing information pathological changes and cellular variability.

METHODS

Here, we applied spatial transcriptomics (ST) and digital spatial profiler (DSP) technologies with tumor sections from patients with iCCA.

RESULTS

The results reveal that spatial inter- and intra-tumor heterogeneities feature iCCA malignancy, and tumor subclones are mainly driven by physical proximity. Tumor cells with TME components shaped the intra-sectional heterogenetic spatial architecture. Macrophages are the most infiltrated TME component in iCCA. The protein trefoil factor 3 (TFF3) secreted by the malignant subclone can induce macrophages to reprogram to a tumor-promoting state, which in turn contributes to an immune-suppressive environment and boosts tumor progression.

CONCLUSIONS

In conclusion, our description of the iCCA ecosystem in a spatially resolved manner provides novel insights into the spatial features and the immune suppressive landscapes of TME for iCCA.

Spatial landscapes of cancers: insights and opportunities

Solid tumours comprise many different cell types organized in spatially structured arrangements, with substantial intratumour and intertumour heterogeneity. Advances in spatial profiling technologies over the past decade hold promise to capture the complexity of these cellular architectures to build a holistic view of the intricate molecular mechanisms that shape the tumour ecosystem. Some of these mechanisms act at the cellular scale and are controlled by cell-autonomous programmes or communication between nearby cells, whereas other mechanisms result from coordinated efforts between large networks of cells and extracellular molecules organized into tissues and organs. In this Review we provide insights into the application of single-cell and spatial profiling tools, with a focus on spatially resolved transcriptomic tools developed to understand the cellular architecture of the tumour microenvironment and identify opportunities to use them to improve clinical management of cancers.

Immunomodulatory molecules in colorectal cancer liver metastasis

Colorectal cancer (CRC) ranks as the third most common cancer and the second leading cause of cancer-related deaths. According to clinical diagnosis and treatment, liver metastasis occurs in approximately 50 % of CRC patients, indicating a poor prognosis. The unique immune tolerance of the liver fosters an immunosuppressive tumor microenvironment (TME). In the context of tumors, numerous membrane and secreted proteins have been linked to tumor immune evasion as immunomodulatory molecules, but much remains unknown about how these proteins contribute to immune evasion in colorectal cancer liver metastasis (CRLM). This article reviews recently discovered membrane and secreted proteins with roles as both immunostimulatory and immunosuppressive molecules within the TME that influence immune evasion in CRC primary and metastatic lesions, particularly their mechanisms in promoting CRLM. This article also addresses screening strategies for identifying proteins involved in immune evasion in CRLM and provides insights into potential protein targets for treating CRLM.

Spatiotemporal omics for biology and medicine

The completion of the Human Genome Project has provided a foundational blueprint for understanding human life. Nonetheless, understanding the intricate mechanisms through which our genetic blueprint is involved in disease or orchestrates development across temporal and spatial dimensions remains a profound scientific challenge. Recent breakthroughs in cellular omics technologies have paved new pathways for understanding the regulation of genomic elements and the relationship between gene expression, cellular functions, and cell fate determination. The advent of spatial omics technologies, encompassing both imaging and sequencing-based methodologies, has enabled a comprehensive understanding of biological processes from a cellular ecosystem perspective. This review offers an updated overview of how spatial omics has advanced our understanding of the translation of genetic information into cellular heterogeneity and tissue structural organization and their dynamic changes over time. It emphasizes the discovery of various biological phenomena, related to organ functionality, embryogenesis, species evolution, and the pathogenesis of diseases.

DAB2 + macrophages support FAP + fibroblasts in shaping tumor barrier and inducing poor clinical outcomes in liver cancer

Background: Cancer-associated fibroblasts (CAFs) are the key components of the immune barrier in liver cancer. Therefore, gaining a deeper understanding of the heterogeneity and intercellular communication of CAFs holds utmost importance in boosting immunotherapy effectiveness and improving clinical outcomes. Methods: A comprehensive analysis by combing single-cell, bulk, and spatial transcriptome profiling with multiplexed immunofluorescence was conducted to unravel the complexities of CAFs in liver cancer. Results: Through an integrated approach involving 235 liver cancer scRNA-seq samples encompassing over 1.2 million cells, we found that CAFs were particularly increased in hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). FAP + fibroblasts were identified as the dominant subtype of CAFs, and which were mainly involved in extracellular matrix organization and angiogenesis. These CAFs were enriched in the tumor boundary of HCC, but diffusely scattered within ICC. The DAB2 + and SPP1 + tumor-associated macrophages (TAMs) reinforce the function of FAP + CAFs through signals such as TGF-β, PDGF, and ADM. Notably, the interaction between DAB2 + TAMs and FAP + CAFs promoted the formation of immune barrier and correlated with poorer patient survival, non-response to immunotherapy in HCC. High FAP and DAB2 immunohistochemical scores predicted shorter survival and higher serum AFP concentration in a local clinical cohort of 90 HCC patients. Furthermore, this communication pattern might be applicable to other solid malignancies as well. Conclusions: The interaction between DAB2 + TAMs and FAP + CAFs appears crucial in shaping the immune barrier. Strategies aimed at disrupting this communication or inhibiting the functions of FAP + CAFs could potentially enhance immunotherapy effectiveness and improve clinical outcomes.

CCL19-producing fibroblasts promote tertiary lymphoid structure formation enhancing anti-tumor IgG response in colorectal cancer liver metastasis

Tertiary lymphoid structures (TLSs) are associated with enhanced immunity in tumors. However, their formation and functions in colorectal cancer liver metastasis (CRLM) remain unclear. Here, we reveal that intra- and peri-tumor mature TLSs (TLS+) are associated with improved clinical outcomes than TLS- tumors. Using single-cell-RNA-sequencing and spatial-enhanced-resolution-omics-sequencing (Stereo-seq), we reveal that TLS+ tumors are enriched with IgG+ plasma cells (PCs), while TLS- tumors are characterized with IgA+ PCs. By generating TLS-associated PC-derived monoclonal antibodies in vitro, we show that TLS-PCs secrete tumor-targeting antibodies. As the proof-of-concept, we demonstrate the anti-tumor activities of TLS-PC-mAb6 antibody in humanized mouse model of colorectal cancer. We identify a fibroblast lineage secreting CCL19 that facilitates lymphocyte trafficking to TLSs. CCL19 treatment promotes TLS neogenesis and prevents tumor growth in mice. Our data uncover the central role of CCL19+ fibroblasts in TLS formation, which in turn generates therapeutic antibodies to restrict CRLM.

Boundarics in Biomedicine

"Boundarics in Biomedicine" is a cutting-edge interdisciplinary discipline, which is of great significance for understanding the origin of life, the interaction between internal and external environments, and the mechanism of disease occurrence and evolution. Here, the definition of Boundarics in Biomedicine is first described, including its connotation, research object, research method, challenges, and future perspectives. "Boundarics in Biomedicine" is a cutting-edge interdisciplinary discipline involving multiple fields (e.g., bioscience, medicine, chemistry, materials science, and information science) dedicated to investigating and solving key scientific questions in the formation, identification, and evolution of living organism boundaries. Specifically, it encompasses 3 levels: (a) the boundary between the living organism and the external environment, (b) internal boundary within living organism, and (c) the boundary related to disease in living organism. The advancement of research in Boundarics in Biomedicine is of great scientific significance for understanding the origin of life, the interaction between internal and external environments, and the mechanism of disease occurrence and evolution, thus providing novel principles, technologies, and methods for early diagnosis and prevention of major diseases, personalized drug development, and prognosis assessment (Fig. 1).

Role of tumor-associated macrophages in hepatocellular carcinoma: impact, mechanism, and therapy

Hepatocellular carcinoma (HCC) is a highly frequent malignancy worldwide. The occurrence and progression of HCC is a complex process closely related to the polarization of tumor-associated macrophages (TAMs) in the tumor microenvironment (TME). The polarization of TAMs is affected by a variety of signaling pathways and surrounding cells. Evidence has shown that TAMs play a crucial role in HCC, through its interaction with other immune cells in the TME. This review summarizes the origin and phenotypic polarization of TAMs, their potential impacts on HCC, and their mechanisms and potential targets for HCC immunotherapy.

Immunosuppressive tumor microenvironment in the progression, metastasis, and therapy of hepatocellular carcinoma: from bench to bedside

Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy with high incidence, recurrence, and metastasis rates. The emergence of immunotherapy has improved the treatment of advanced HCC, but problems such as drug resistance and immune-related adverse events still exist in clinical practice. The immunosuppressive tumor microenvironment (TME) of HCC restricts the efficacy of immunotherapy and is essential for HCC progression and metastasis. Therefore, it is necessary to elucidate the mechanisms behind immunosuppressive TME to develop and apply immunotherapy. This review systematically summarizes the pathogenesis of HCC, the formation of the highly heterogeneous TME, and the mechanisms by which the immunosuppressive TME accelerates HCC progression and metastasis. We also review the status of HCC immunotherapy and further discuss the existing challenges and potential therapeutic strategies targeting immunosuppressive TME. We hope to inspire optimizing and innovating immunotherapeutic strategies by comprehensively understanding the structure and function of immunosuppressive TME in HCC.

Right eye metastasis of small‑cell lung carcinoma: A case report

The incidence of eye metastasis from primary malignant tumors is low. Predominantly, these primary malignant tumors consist of breast and lung carcinoma. Ocular metastatic carcinoma is often clinically overlooked. In clinical practice, it is rare for small-cell lung carcinoma (SCLC) to metastasize to the right eye. Early detection and treatment via the monitoring of clinical symptoms and auxiliary examinations of the eye are of great significance in preserving the patient's vision and improving their quality of life. Such treatments include radiotherapy or enucleation of the eyeball. A 54-year-old male patient with SCLC experienced a decline in vision and blurred vision during his systemic treatment using combined enverolumab and etoposide and cisplatin. Upon examination, including fundus photography, ocular B-scan and magnetic resonance imaging, a right eye metastasis was suspected. Within a short period of time, the patient experienced significant pain and blindness in the right eye, which required surgical removal of the right eyeball. Postoperative pathology confirmed metastasis. After six cycles of treatment, the primary lesion in the lung reduced in size. By reporting this case of SCLC metastasis to the right eye, we aim to provide a reference for the clinical diagnosis and treatment of ocular metastatic carcinoma.

Decoding the spatiotemporal heterogeneity of tumor-associated macrophages

Tumor-associated macrophages (TAMs) are pivotal in cancer progression, influencing tumor growth, angiogenesis, and immune evasion. This review explores the spatial and temporal heterogeneity of TAMs within the tumor microenvironment (TME), highlighting their diverse subtypes, origins, and functions. Advanced technologies such as single-cell sequencing and spatial multi-omics have elucidated the intricate interactions between TAMs and other TME components, revealing the mechanisms behind their recruitment, polarization, and distribution. Key findings demonstrate that TAMs support tumor vascularization, promote epithelial-mesenchymal transition (EMT), and modulate extracellular matrix (ECM) remodeling, etc., thereby enhancing tumor invasiveness and metastasis. Understanding these complex dynamics offers new therapeutic targets for disrupting TAM-mediated pathways and overcoming drug resistance. This review underscores the potential of targeting TAMs to develop innovative cancer therapies, emphasizing the need for further research into their spatial characteristics and functional roles within the TME.

Open-ST: High-resolution spatial transcriptomics in 3D

Spatial transcriptomics (ST) methods unlock molecular mechanisms underlying tissue development, homeostasis, or disease. However, there is a need for easy-to-use, high-resolution, cost-efficient, and 3D-scalable methods. Here, we report Open-ST, a sequencing-based, open-source experimental and computational resource to address these challenges and to study the molecular organization of tissues in 2D and 3D. In mouse brain, Open-ST captured transcripts at subcellular resolution and reconstructed cell types. In primary head-and-neck tumors and patient-matched healthy/metastatic lymph nodes, Open-ST captured the diversity of immune, stromal, and tumor populations in space, validated by imaging-based ST. Distinct cell states were organized around cell-cell communication hotspots in the tumor but not the metastasis. Strikingly, the 3D reconstruction and multimodal analysis of the metastatic lymph node revealed spatially contiguous structures not visible in 2D and potential biomarkers precisely at the 3D tumor/lymph node boundary. All protocols and software are available at https://rajewsky-lab.github.io/openst.

Immunotherapies Targeting Tumor-Associated Macrophages (TAMs) in Cancer

Tumor-associated macrophages (TAMs) are one of the most plentiful immune compositions in the tumor microenvironment, which are further divided into anti-tumor M1 subtype and pro-tumor M2 subtype. Recent findings found that TAMs play a vital function in the regulation and progression of tumorigenesis. Moreover, TAMs promote tumor vascularization, and support the survival of tumor cells, causing an impact on tumor growth and patient prognosis. Numerous studies show that reducing the density of TAMs, or modulating the polarization of TAMs, can inhibit tumor growth, indicating that TAMs are a promising target for tumor immunotherapy. Recently, clinical trials have found that treatments targeting TAMs have achieved encouraging results, and the U.S. Food and Drug Administration has approved a number of drugs for use in cancer treatment. In this review, we summarize the origin, polarization, and function of TAMs, and emphasize the therapeutic strategies targeting TAMs in cancer treatment in clinical studies and scientific research, which demonstrate a broad prospect of TAMs-targeted therapies in tumor immunotherapy.

Advances in spatial transcriptomics and its applications in cancer research

Malignant tumors have increasing morbidity and high mortality, and their occurrence and development is a complicate process. The development of sequencing technologies enabled us to gain a better understanding of the underlying genetic and molecular mechanisms in tumors. In recent years, the spatial transcriptomics sequencing technologies have been developed rapidly and allow the quantification and illustration of gene expression in the spatial context of tissues. Compared with the traditional transcriptomics technologies, spatial transcriptomics technologies not only detect gene expression levels in cells, but also inform the spatial location of genes within tissues, cell composition of biological tissues, and interaction between cells. Here we summarize the development of spatial transcriptomics technologies, spatial transcriptomics tools and its application in cancer research. We also discuss the limitations and challenges of current spatial transcriptomics approaches, as well as future development and prospects.

Spatial proteomic landscape of primary and relapsed hepatocellular carcinoma reveals immune escape characteristics in early relapse

BACKGROUND AND AIMS

Surgical resection serves as the principal curative strategy for HCC, yet the incidence of postoperative recurrence remains alarmingly high. However, the spatial molecular structural alterations contributing to postoperative recurrence in HCC are still poorly understood.

APPROACH AND RESULTS

We employed imaging mass cytometry to profile the in situ expression of 33 proteins within 358,729 single cells of 92 clinically annotated surgical specimens from 46 patients who were treated with surgical resections for primary and relapsed tumors. We revealed the recurrence progression of HCC was governed by the dynamic spatial distribution and functional interplay of diverse cell types across adjacent normal, tumor margin, and intratumor regions. Our exhaustive analyses revealed an aggressive, immunosuppression-related spatial ecosystem in relapsed HCC. Additionally, we illustrated the prominent implications of the tumor microenvironment of tumor margins in association with relapse HCC. Moreover, we identified a novel subpopulation of dendritic cells (PDL1 + CD103 + DCs) enriched in the peritumoral area that correlated with early postoperative recurrence, which was further validated in an external cohort. Through the analysis of single-cell RNA sequencing data, we found the interaction of PDL1 + CD103 + DCs with regulatory T cells and exhausted T cells enhanced immunosuppression and immune escape through multiple ligand-receptor pathways.

CONCLUSIONS

We comprehensively depicted the spatial landscape of single-cell dynamics and multicellular architecture within primary and relapsed HCC. Our findings highlight spatial organization as a prominent determinant of HCC recurrence and provide valuable insight into the immune evasion mechanisms driving recurrence.

Spatial omics techniques and data analysis for cancer immunotherapy applications

In-depth profiling of cancer cells/tissues is expanding our understanding of the genomic, epigenomic, transcriptomic, and proteomic landscape of cancer. However, the complexity of the cancer microenvironment, particularly its immune regulation, has made it difficult to exploit the potential of cancer immunotherapy. High-throughput spatial omics technologies and analysis pipelines have emerged as powerful tools for tackling this challenge. As a result, a potential revolution in cancer diagnosis, prognosis, and treatment is on the horizon. In this review, we discuss the technological advances in spatial profiling of cancer around and beyond the central dogma to harness the full benefits of immunotherapy. We also discuss the promise and challenges of spatial data analysis and interpretation and provide an outlook for the future.

Plasma proteomics analysis of Chinese HIV-1 infected individuals focusing on the immune and inflammatory factors afford insight into the viral control mechanism

Background

Long-term non-progressors (LTNPs) with HIV infection can naturally control viral replication for up to a decade without antiretroviral therapy (ART), but the underlying mechanisms of this phenomenon remain elusive.

Methods

To investigate the relevant immune and inflammatory factors associated with this natural control mechanism, we collected plasma samples from 16 LTNPs, 14 untreated viral progressors (VPs), 17 successfully ART-treated patients (TPs), and 16 healthy controls (HCs). The OLINK immune response panel and inflammation panel were employed to detect critical proteins, and the plasma neutralizing activity against a global panel of pseudoviruses was assessed using TZM-bl cells.

Results

The combination of IL17C, IL18, DDX58, and NF2 contributed to discriminating LTNPs and VPs. IL18 and CCL25 were positively associated with CD4+ T cell counts but negatively correlated with viral load. Furthermore, CXCL9 and CXCL10 emerged as potential supplementary diagnostic markers for assessing the efficacy of antiretroviral therapy (ART). Finally, TNFRSF9 displayed positive correlations with neutralization breadth and Geometry Median Titer (GMT) despite the lack of significant differences between LTNPs and VPs.

Conclusion

In summary, this study identified a set of biomarkers in HIV-infected individuals at different disease stages. These markers constitute a potential network for immune balance regulation in HIV infection, which is related to the long-term control of HIV by LTNPs. It provides important clues for further exploring the immune regulatory mechanism of HIV.

Digital pathology and spatial omics in steatohepatitis: Clinical applications and discovery potentials

Steatohepatitis with diverse etiologies is the most common histological manifestation in patients with liver disease. However, there are currently no specific histopathological features pathognomonic for metabolic dysfunction-associated steatotic liver disease, alcohol-associated liver disease, or metabolic dysfunction-associated steatotic liver disease with increased alcohol intake. Digitizing traditional pathology slides has created an emerging field of digital pathology, allowing for easier access, storage, sharing, and analysis of whole-slide images. Artificial intelligence (AI) algorithms have been developed for whole-slide images to enhance the accuracy and speed of the histological interpretation of steatohepatitis and are currently employed in biomarker development. Spatial biology is a novel field that enables investigators to map gene and protein expression within a specific region of interest on liver histological sections, examine disease heterogeneity within tissues, and understand the relationship between molecular changes and distinct tissue morphology. Here, we review the utility of digital pathology (using linear and nonlinear microscopy) augmented with AI analysis to improve the accuracy of histological interpretation. We will also discuss the spatial omics landscape with special emphasis on the strengths and limitations of established spatial transcriptomics and proteomics technologies and their application in steatohepatitis. We then highlight the power of multimodal integration of digital pathology augmented by machine learning (ML)algorithms with spatial biology. The review concludes with a discussion of the current gaps in knowledge, the limitations and premises of these tools and technologies, and the areas of future research.

Spaco: A comprehensive tool for coloring spatial data at single-cell resolution

Understanding tissue architecture and niche-specific microenvironments in spatially resolved transcriptomics (SRT) requires in situ annotation and labeling of cells. Effective spatial visualization of these data demands appropriate colorization of numerous cell types. However, current colorization frameworks often inadequately account for the spatial relationships between cell types. This results in perceptual ambiguity in neighboring cells of biological distinct types, particularly in complex environments such as brain or tumor. To address this, we introduce Spaco, a potent tool for spatially aware colorization. Spaco utilizes the Degree of Interlacement metric to construct a weighted graph that evaluates the spatial relationships among different cell types, refining color assignments. Furthermore, Spaco incorporates an adaptive palette selection approach to amplify chromatic distinctions. When benchmarked on four diverse datasets, Spaco outperforms existing solutions, capturing complex spatial relationships and boosting visual clarity. Spaco ensures broad accessibility by accommodating color vision deficiency and offering open-accessible code in both Python and R.

Artificial tumor matrices and bioengineered tools for tumoroid generation

The tumor microenvironment (TME) is critical for tumor growth and metastasis. The TME contains cancer-associated cells, tumor matrix, and tumor secretory factors. The fabrication of artificial tumors, so-called tumoroids, is of great significance for the understanding of tumorigenesis and clinical cancer therapy. The assembly of multiple tumor cells and matrix components through interdisciplinary techniques is necessary for the preparation of various tumoroids. This article discusses current methods for constructing tumoroids (tumor tissue slices and tumor cell co-culture) for pre-clinical use. This article focuses on the artificial matrix materials (natural and synthetic materials) and biofabrication techniques (cell assembly, bioengineered tools, bioprinting, and microfluidic devices) used in tumoroids. This article also points out the shortcomings of current tumoroids and potential solutions. This article aims to promotes the next-generation tumoroids and the potential of them in basic research and clinical application.

Heterogeneity and tumoral origin of medulloblastoma in the single-cell era

Medulloblastoma is one of the most common malignant pediatric brain tumors derived from posterior fossa. The current treatment includes maximal safe surgical resection, radiotherapy, whole cranio-spinal radiation and adjuvant with chemotherapy. However, it can only limitedly prolong the survival time with severe side effects and relapse. Defining the intratumoral heterogeneity, cellular origin and identifying the interaction network within tumor microenvironment are helpful for understanding the mechanisms of medulloblastoma tumorigenesis and relapse. Due to technological limitations, the mechanisms of cellular heterogeneity and tumor origin have not been fully understood. Recently, the emergence of single-cell technology has provided a powerful tool for achieving the goal of understanding the mechanisms of tumorigenesis. Several studies have demonstrated the intratumoral heterogeneity and tumor origin for each subtype of medulloblastoma utilizing the single-cell RNA-seq, which has not been uncovered before using conventional technologies. In this review, we present an overview of the current progress in understanding of cellular heterogeneity and tumor origin of medulloblastoma and discuss novel findings in the age of single-cell technologies.

Serum amyloid A promotes glycolysis of neutrophils during PD-1 blockade resistance in hepatocellular carcinoma

The response to programmed death-1 (PD-1) blockade varies in hepatocellular carcinoma (HCC). We utilize a panel of 16 serum factors to show that a circulating level of serum amyloid A (SAA) > 20.0 mg/L has the highest accuracy in predicting anti-PD-1 resistance in HCC. Further experiments show a correlation between peritumoral SAA expression and circulating SAA levels in patients with progressive disease after PD-1 inhibition. In vitro experiments demonstrate that SAA induces neutrophils to express PD-L1 through glycolytic activation via an LDHA/STAT3 pathway and to release oncostatin M, thereby attenuating cytotoxic T cell function. In vivo, genetic or pharmacological inhibition of STAT3 or SAA eliminates neutrophil-mediated immunosuppression and enhances antitumor efficacy of anti-PD-1 treatment. This study indicates that SAA may be a critical inflammatory cytokine implicated in anti-PD-1 resistance in HCC. Targeting SAA-induced PD-L1+ neutrophils through STAT3 or SAA inhibition may present a potential approach for overcoming anti-PD1 resistance.

Precision treatment in advanced hepatocellular carcinoma

The past decade has witnessed significant advances in the systemic treatment of advanced hepatocellular carcinoma (HCC). Nevertheless, the newly developed treatment strategies have not achieved universal success and HCC patients frequently exhibit therapeutic resistance to these therapies. Precision treatment represents a paradigm shift in cancer treatment in recent years. This approach utilizes the unique molecular characteristics of individual patient to personalize treatment modalities, aiming to maximize therapeutic efficacy while minimizing side effects. Although precision treatment has shown significant success in multiple cancer types, its application in HCC remains in its infancy. In this review, we discuss key aspects of precision treatment in HCC, including therapeutic biomarkers, molecular classifications, and the heterogeneity of the tumor microenvironment. We also propose future directions, ranging from revolutionizing current treatment methodologies to personalizing therapy through functional assays, which will accelerate the next phase of advancements in this area.

The oncogenic mechanisms of the Janus kinase-signal transducer and activator of transcription pathway in digestive tract tumors

Digestive tract tumors are heterogeneous and involve the dysregulation of multiple signaling pathways. The Janus kinase-signal transducer and activator of transcription (JAK-STAT) pathway plays a notable role in the oncogenesis of digestive tract tumors. Typically activated by pro-inflammatory cytokines, it regulates important biological processes, such as cell growth, differentiation, apoptosis, immune responses, and inflammation. The aberrant activation of this pathway manifests in different forms, including mutations in JAKs, overexpression of cytokine receptors, and sustained STAT activation, and contributes to promoting the malignant characteristics of cancer cells, including uncontrolled proliferation, resistance to apoptosis, enhanced invasion and metastasis, angiogenesis, acquisition of stem-like properties, and drug resistance. Numerous studies have shown that aberrant activation of the JAK-STAT pathway is closely related to the development and progression of digestive tract tumors, contributing to tumor survival, angiogenesis, changes in the tumor microenvironment, and even immune escape processes. In addition, this signaling pathway also affects the sensitivity of digestive tract tumors to chemotherapy and targeted therapy. Therefore, it is crucial to comprehensively understand the oncogenic mechanisms underlying the JAK-STAT pathway in order to develop effective therapeutic strategies against digestive tract tumors. Currently, several JAK-STAT inhibitors are undergoing clinical and preclinical trials as potential treatments for various human diseases. However, further investigation is required to determine the role of this pathway, as well as the effectiveness and safety of its inhibitors, especially in the context of digestive tract tumors. In this review, we provide an overview of the structure, classic activation, and negative regulation of the JAK-STAT pathway. Furthermore, we discuss the pathogenic mechanisms of JAK-STAT signaling in different digestive tract tumors, with the aim of identifying potential novel therapeutic targets. Video Abstract.

spatiAlign: an unsupervised contrastive learning model for data integration of spatially resolved transcriptomics

BACKGROUND

Integrative analysis of spatially resolved transcriptomics datasets empowers a deeper understanding of complex biological systems. However, integrating multiple tissue sections presents challenges for batch effect removal, particularly when the sections are measured by various technologies or collected at different times.

FINDINGS

We propose spatiAlign, an unsupervised contrastive learning model that employs the expression of all measured genes and the spatial location of cells, to integrate multiple tissue sections. It enables the joint downstream analysis of multiple datasets not only in low-dimensional embeddings but also in the reconstructed full expression space.

CONCLUSIONS

In benchmarking analysis, spatiAlign outperforms state-of-the-art methods in learning joint and discriminative representations for tissue sections, each potentially characterized by complex batch effects or distinct biological characteristics. Furthermore, we demonstrate the benefits of spatiAlign for the integrative analysis of time-series brain sections, including spatial clustering, differential expression analysis, and particularly trajectory inference that requires a corrected gene expression matrix.

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

BACKGROUND

Spatial transcriptome (ST) technologies are emerging as powerful tools for studying tumor biology. However, existing tools for analyzing ST data are limited, as they mainly rely on algorithms developed for single-cell RNA sequencing data and do not fully utilize the spatial information. While some algorithms have been developed for ST data, they are often designed for specific tasks, lacking a comprehensive analytical framework for leveraging spatial information.

RESULTS

In this study, we present StereoSiTE, an analytical framework that combines open-source bioinformatics tools with custom algorithms to accurately infer the functional spatial cell interaction intensity (SCII) within the cellular neighborhood (CN) of interest. We applied StereoSiTE to decode ST datasets from xenograft models and found that the CN efficiently distinguished different cellular contexts, while the SCII analysis provided more precise insights into intercellular interactions by incorporating spatial information. By applying StereoSiTE to multiple samples, we successfully identified a CN region dominated by neutrophils, suggesting their potential role in remodeling the immune tumor microenvironment (iTME) after treatment. Moreover, the SCII analysis within the CN region revealed neutrophil-mediated communication, supported by pathway enrichment, transcription factor regulon activities, and protein-protein interactions.

CONCLUSIONS

StereoSiTE represents a promising framework for unraveling the mechanisms underlying treatment response within the iTME by leveraging CN-based tissue domain identification and SCII-inferred spatial intercellular interactions. The software is designed to be scalable, modular, and user-friendly, making it accessible to a wide range of researchers.

Deciphering spatial domains from spatially resolved transcriptomics with Siamese graph autoencoder

BACKGROUND

Cell clustering is a pivotal aspect of spatial transcriptomics (ST) data analysis as it forms the foundation for subsequent data mining. Recent advances in spatial domain identification have leveraged graph neural network (GNN) approaches in conjunction with spatial transcriptomics data. However, such GNN-based methods suffer from representation collapse, wherein all spatial spots are projected onto a singular representation. Consequently, the discriminative capability of individual representation feature is limited, leading to suboptimal clustering performance.

RESULTS

To address this issue, we proposed SGAE, a novel framework for spatial domain identification, incorporating the power of the Siamese graph autoencoder. SGAE mitigates the information correlation at both sample and feature levels, thus improving the representation discrimination. We adapted this framework to ST analysis by constructing a graph based on both gene expression and spatial information. SGAE outperformed alternative methods by its effectiveness in capturing spatial patterns and generating high-quality clusters, as evaluated by the Adjusted Rand Index, Normalized Mutual Information, and Fowlkes-Mallows Index. Moreover, the clustering results derived from SGAE can be further utilized in the identification of 3-dimensional (3D) Drosophila embryonic structure with enhanced accuracy.

CONCLUSIONS

Benchmarking results from various ST datasets generated by diverse platforms demonstrate compelling evidence for the effectiveness of SGAE against other ST clustering methods. Specifically, SGAE exhibits potential for extension and application on multislice 3D reconstruction and tissue structure investigation. The source code and a collection of spatial clustering results can be accessed at https://github.com/STOmics/SGAE/.

Interorgan communication with the liver: novel mechanisms and therapeutic targets

The liver is a multifunctional organ that plays crucial roles in numerous physiological processes, such as production of bile and proteins for blood plasma, regulation of blood levels of amino acids, processing of hemoglobin, clearance of metabolic waste, maintenance of glucose, etc. Therefore, the liver is essential for the homeostasis of organisms. With the development of research on the liver, there is growing concern about its effect on immune cells of innate and adaptive immunity. For example, the liver regulates the proliferation, differentiation, and effector functions of immune cells through various secreted proteins (also known as "hepatokines"). As a result, the liver is identified as an important regulator of the immune system. Furthermore, many diseases resulting from immune disorders are thought to be related to the dysfunction of the liver, including systemic lupus erythematosus, multiple sclerosis, and heart failure. Thus, the liver plays a role in remote immune regulation and is intricately linked with systemic immunity. This review provides a comprehensive overview of the liver remote regulation of the body's innate and adaptive immunity regarding to main areas: immune-related molecules secreted by the liver and the liver-resident cells. Additionally, we assessed the influence of the liver on various facets of systemic immune-related diseases, offering insights into the clinical application of target therapies for liver immune regulation, as well as future developmental trends.

Targeting the mechano-microenvironment and liver cancer stem cells: a promising therapeutic strategy for liver cancer

Over the past 2 decades, cancer stem cells (CSCs) have been identified as the root cause of cancer occurrence, progression, chemoradioresistance, recurrence, and metastasis. Targeting CSCs is a novel therapeutic strategy for cancer management and treatment. Liver cancer (LC) is a malignant disease that can endanger human health. Studies are increasingly suggesting that changes in the liver mechanical microenvironment are a primary driver triggering the occurrence and development of liver cancer. In this review, we summarize current understanding of the roles of the liver mechano-microenvironment and liver cancer stem cells (LCSCs) in liver cancer progression. We also discuss the relationship between the mechanical heterogeneity of liver cancer tissues and LCSC recruitment and metastasis. Finally, we highlight potential mechanosensitive molecules in LCSCs and mechanotherapy in liver cancer. Understanding the roles and regulatory mechanisms of the mechano-microenvironment and LCSCs may provide fundamental insights into liver cancer progression and aid in further development of novel therapeutic strategies.

Unveiling the Role of Tumor-Infiltrating T Cells and Immunotherapy in Hepatocellular Carcinoma: A Comprehensive Review

Hepatocellular carcinoma (HCC) is a rapidly rising global health concern, ranking as the third-leading cause of cancer-related mortality. Despite medical advancements, the five-year survival rate remains a dismal 18%, with a daunting 70% recurrence rate within a five-year period. Current systematic treatments, including first-line sorafenib, yield an overall response rate (ORR) below 10%. In contrast, immunotherapies have shown promise by improving ORR to approximately 30%. The IMbravel150 clinical trial demonstrates that combining atezolizumab and bevacizumab surpasses sorafenib in terms of median progression-free survival (PFS) and overall survival (OS). However, the therapeutic efficacy for HCC patients remains unsatisfactory, highlighting the urgent need for a comprehensive understanding of antitumor responses and immune evasion mechanisms in HCC. In this context, understanding the immune landscape of HCC is of paramount importance. Tumor-infiltrating T cells, including cytotoxic T cells, regulatory T cells, and natural killer T cells, are key components in the antitumor immune response. This review aims to shed light on their intricate interactions within the immunosuppressive tumor microenvironment and explores potential strategies for revitalizing dysfunctional T cells. Additionally, current immune checkpoint inhibitor (ICI)-based trials, ICI-based combination therapies, and CAR-T- or TCR-T-cell therapies for HCC are summarized, which might further improve OS and transform the management of HCC in the future.

Increased co-expression of PD1 and TIM3 is associated with poor prognosis and immune microenvironment heterogeneity in gallbladder cancer

BACKGROUND

The effectiveness of immune checkpoint inhibitors in treating gallbladder cancer (GBC) remains unsatisfactory. Recently, several new immune checkpoints have been identified. However, investigations exploring these immune checkpoints in GBC are limited. In this study, we aim to investigate the expression patterns and clinical implications of various immune checkpoints, and further characterize the spatial and quantitative heterogeneity of immune components in GBC.

METHODS

We employed single and multiplex immunohistochemistry to evaluate the expression of five immune checkpoint markers and four immune cell markers in the primary tumor core, hepatic invasion margin, and liver metastasis. Subsequently, we analyzed their interrelationships and their prognostic significance.

RESULTS

We observed a robust positive correlation between PD1/TIM3 expression in GBC (R = 0.614, P < 0.001). The co-expression of PD1/TIM3 exhibited a synergistic effect in predicting poor prognosis among postoperative GBC patients. Further analysis revealed that the prognostic significance of PD1/TIM3 was prominent in the subgroup with high infiltration of CD8 + T cells (P < 0.001). Multiplex immunohistochemistry reveals that PD1 + TIM3 + FOXP3 + cells constitute a significant proportion of FOXP3 + TILs in GBC tissue. Moreover, the co-high expression of PD1 and TIM3 is positively correlated with the accumulation of CD8 + TILs at the hepatic invasion margin. Lastly, our findings indicated reduced expression levels of immune checkpoints and diminished immune cell infiltration in liver metastases compared to primary tumors.

CONCLUSIONS

Increased co-expression of PD1/TIM3 is associated with poor prognosis in GBC patients and is related to the heterogeneity of immune microenvironment between GBC primary tumor and its hepatic invasion margin or liver metastases, which may be a potential target for future immunotherapy of GBC.

Spatial transcriptomics in development and disease

The proper functioning of diverse biological systems depends on the spatial organization of their cells, a critical factor for biological processes like shaping intricate tissue functions and precisely determining cell fate. Nonetheless, conventional bulk or single-cell RNA sequencing methods were incapable of simultaneously capturing both gene expression profiles and the spatial locations of cells. Hence, a multitude of spatially resolved technologies have emerged, offering a novel dimension for investigating regional gene expression, spatial domains, and interactions between cells. Spatial transcriptomics (ST) is a method that maps gene expression in tissue while preserving spatial information. It can reveal cellular heterogeneity, spatial organization and functional interactions in complex biological systems. ST can also complement and integrate with other omics methods to provide a more comprehensive and holistic view of biological systems at multiple levels of resolution. Since the advent of ST, new methods offering higher throughput and resolution have become available, holding significant potential to expedite fresh insights into comprehending biological complexity. Consequently, a rapid increase in associated research has occurred, using these technologies to unravel the spatial complexity during developmental processes or disease conditions. In this review, we summarize the recent advancement of ST in historical, technical, and application contexts. We compare different types of ST methods based on their principles and workflows, and present the bioinformatics tools for analyzing and integrating ST data with other modalities. We also highlight the applications of ST in various domains of biomedical research, especially development and diseases. Finally, we discuss the current limitations and challenges in the field, and propose the future directions of ST.