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

Vaccarin ameliorates osteoarthritis by suppressing the c-Jun N-terminal kinase (JNK)-serum amyloid A2 (SAA2) pathway mediating chondrocyte senescence

BACKGROUND

Osteoarthritis is a chronic degenerative joint disease marked by chondrocyte senescence and extracellular matrix degradation. Vaccarin, a flavonoid with anti-inflammatory and antioxidant properties, has not been previously investigated for its therapeutic potential in osteoarthritis.

PURPOSE

To evaluate the therapeutic potential of Vaccarin in osteoarthritis and elucidate its underlying mechanisms.

DESIGN AND METHOD

This study utilized in vitro chondrocyte cultures and RNA sequencing to identify relevant pathways, followed by validation at the genetic, protein, and metabolic levels using multiple approaches. Additionally, the therapeutic effects of Vaccarin were assessed in vivo using a destabilization of the medial meniscus (DMM)-induced osteoarthritis mouse model and human cartilage samples from osteoarthritis patients.

RESULTS

Vaccarin effectively ameliorated osteoarthritis both in vivo and in vitro. Transcriptomic sequencing indicated a significant downregulation of serum amyloid A2 (SAA2) expression following Vaccarin treatment. Multi-omics analysis, validated by human specimens, indicated that SAA2 is minimally secreted in healthy articular cartilage but serves as a crucial osteoarthritis biomarker in Asian populations. Mechanistically, Vaccarin inhibits c-Jun N-terminal kinase (JNK) phosphorylation, thereby reducing SAA2 expression and mitigating chondrocyte inflammation and senescence. Notably, inflammatory conditions upregulate SAA2 expression in chondrocytes via the JNK pathway. Elevated SAA2 levels contribute to mitochondrial dysfunction in chondrocytes, leading to increased reactive oxygen species (ROS) production and exacerbating osteoarthritis progression.

CONCLUSION

This study identifies SAA2 as a potential therapeutic target for osteoarthritis and suggests that Vaccarin presents a promising treatment avenue.

Panoramic spatial enhanced resolution proteomics (PSERP) reveals tumor architecture and heterogeneity in gliomas

The spatial proteomic profiling of complex tissues is essential for investigating cellular function in physiological and pathological states. However, the imbalance among resolution, protein coverage, and expense precludes their systematic application to analyze whole tissue sections in an unbiased manner and with high resolution. Here, we introduce panoramic spatial enhanced resolution proteomics (PSERP), a method that combines tissue expansion, automated sample segmentation, and tryptic digestion with high-throughput proteomic profiling. The PSERP approach facilitates rapid quantitative profiling of proteomic spatial variability in whole tissue sections at sub-millimeter resolution. We demonstrated the utility of this method for determining the streamlined large-scale spatial proteomic features of gliomas. Specifically, we profiled spatial proteomic features for nine glioma samples across three different mutation types (IDH1-WT/EGFR-mutant, IDH1-mutant, and IDH1/EGFR-double-WT gliomas) at sub-millimeter resolution (corresponding to a total of 2,230 voxels). The results revealed over 10,000 proteins identified in a single slide, which helps us to portray the diverse proteins and pathways with spatial abundance patterns in the context of tumor heterogeneity and cellular features. Our spatial proteomic data revealed distinctive proteomic features of malignant and non-malignant tumor regions and depicted the distribution of proteins from tumor centers to tumor borders and non-malignant tumor regions. Through integrative analysis with single-cell transcriptomic data, we elucidated the cellular composition and cell-cell communications in a spatial context. Our PSERP also includes a spatially resolved tumor-specific peptidome identification workflow that not only enables us to elucidate the spatial expression patterns of tumor-specific peptides in glioma samples with different genomic types but also provides us with opportunities to select combinations of tumor-specific mutational peptides whose expression could cover the maximum tumor regions for future immune therapies. We further demonstrated that combining tumor-specific peptides might enhance the efficacy of immunotherapy in both patient-derived cell (PDC) and patient-derived xenograft (PDX) models. PSERP efficiently retains precise spatial proteomic information within the tissue context and provides a deeper understanding of tissue biology and pathology at the molecular level.

Prediction of Ki-67 expression in hepatocellular carcinoma with machine learning models based on intratumoral and peritumoral radiomic features

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignant tumours of the digestive system worldwide. The expression of Ki-67 is crucial for the diagnosis, treatment, and prognostic evaluation of HCC.

AIM

To construct a machine learning model for the preoperative evaluation of Ki-67 expression in HCC and to assist in clinical decision-making.

METHODS

This study included 164 pathologically confirmed HCC patients. Radiomic features were extracted from the computed tomography images reconstructed by superresolution of the intratumoral and peritumoral regions. Features were selected via the intraclass correlation coefficient, t tests, Pearson correlation coefficients and least absolute shrinkage and selection operator regression methods, and models were constructed via various machine learning methods. The best model was selected, and the radiomics score (Radscore) was calculated. A nomogram incorporating the Radscore and clinical risk factors was constructed. The predictive performance of each model was evaluated via receiver operating characteristic (ROC) curves and calibration curves, and decision curve analysis was used to assess the clinical benefits.

RESULTS

In total, 164 HCC patients, namely, 104 patients with high Ki-67 expression and 60 with low Ki-67 expression, were included. Compared with the models in which only intratumoral or peritumoral features were used, the fusion model in which intratumoral and peritumoral features were combined demonstrated stronger predictive ability. Moreover, the clinical-radiomics model including the Radscore and clinical features had higher predictive performance than did the fusion model (area under the ROC curve = 0.848 vs 0.780 in the training group, area under the ROC curve = 0.830 vs 0.760 in the validation group). The calibration curve showed good consistency between the predicted probability and the actual probability, and the decision curve further confirmed its clinical benefit.

CONCLUSION

A machine learning model based on the radiomic features of the intratumoral and peritumoral regions on superresolution computed tomography in conjunction with clinical factors can accurately evaluate Ki-67 expression. The model provides valuable assistance in selecting treatment strategies for HCC patients and contributes to research on neoadjuvant therapy for liver cancer.

MTFR2-Mediated Fission Drives Fatty Acid and Mitochondrial Co-Transfer from Hepatic Stellate Cells to Tumor Cells Fueling Oncogenesis

The tumor margin of hepatocellular carcinoma (HCC) is a critical zone where cancer cells invade the surrounding stroma, exhibiting unique and more invasive metabolic and migratory features compared to the tumor center, driving tumor expansion beyond the primary lesion. Studies have shown that at this critical interface, HCC cells primarily rely on fatty acid oxidation to meet their energy demands, although the underlying mechanisms remain unclear. This study demonstrates that activated hepatic stellate cells (HSCs) at the tumor margin play a pivotal role in sustaining the metabolic needs of HCC cells. Specifically, it is discovered that mitochondrial fission regulator 2 (MTFR2) in HSCs interacts with dynamin-related protein 1 (DRP1, a known mitochondrial fission machinery), preventing its lysosomal degradation, which in turn promotes mitochondrial fission. This MTFR2-driven mitochondrial fission enhances the transfer of both fatty acids and mitochondria to HCC cells, supplying essential metabolic substrates and reinforcing the mitochondrial machinery critical for tumor growth. The findings suggest that targeting MTFR2-driven mitochondrial fission may offer a novel therapeutic avenue for interfering with the metabolic crosstalk between tumor cells and the stromal niche.

Cooperative Role of Carbonic Anhydrase IX/XII in Driving Tumor Invasion and Metastasis: A Novel Targeted Therapeutic Strategy

Cancer invasion and metastasis are critical factors that influence patient prognosis. Carbonic anhydrase IX (CA IX) and carbonic anhydrase XII (CA XII) are key regulators of hypoxia and pH homeostasis in the tumor microenvironment (TME). It has been verified that both CA IX and CA XII play significant roles in promoting tumor metastasis in recent years, but most of the literature tends to treat them as separate entities rather than exploring their synergistic effects. This review provides a comprehensive overview of the roles of CA IX and CA XII in tumor invasion and metastasis, along with their clinical applications, including their spatial distribution characteristics, molecular mechanisms that facilitate tumor metastasis, and their potential for clinical translation. Moreover, this review incorporates the classical tumor core-invasive front model to propose a metabolic coupling model of CA IX and CA XII, offering a fresh perspective on precision therapies that target tumor metabolism. By emphasizing the metabolic coupling between these two molecules, this review offers new insights distinct from previous studies and highlights the clinical therapeutic potential of simultaneously targeting both during treatment. It sheds new light on future research and clinical applications, aiming to enhance the prognosis of cancer patients through innovative therapeutic strategies.

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.

CXCL6 Reshapes Lipid Metabolism and Induces Neutrophil Extracellular Trap Formation in Cholangiocarcinoma Progression and Immunotherapy Resistance

The chemokine CXCL6 is identified as a pivotal regulator of biological processes across multiple malignancies. However, its function in cholangiocarcinoma (CCA) is underexplored. Tumor profiling for CXCL6 is performed using a public database. Both in vitro and in vivo experiments are utilized to evaluate the oncogenic effects of CXCL6 on CCA. Additionally, RNA-Seq is employed to detect transcriptomic changes related to CXCL6 expression in CCA cells and neutrophils. Molecular docking, fluorescence colocalization, and Co-IP are used to elucidate a direct interaction between JAKs and CXCR1/2. Additionally, LC-MS lipidomics and explored the impact of CXCL6 on immunotherapy in vivo. CXCL6 is upregulated in CCA tissues and promoted the proliferation and metastasis of CCA. Mechanistically, CXCL6 regulated the CXCR1/2-JAK-STAT/PI3K axis in CCA via autocrine signaling, leading to lipid metabolic reprogramming, and promoted neutrophil extracellular traps (NETs) formation by activating the RAS/MAPK pathway in neutrophils. Eventually, NETs formation induced immunotherapy resistance in CCA by blocking CD8+T cell infiltration. CXCL6 modulates CCA progression through the CXCR1/2-JAK-STAT/PI3K axis and reshaping its lipid metabolism. CXCL6 also mediates immunotherapy resistance through NETs, which may be a potential therapeutic target and biomarker for CCA.

Impact of lymph node metastasis on immune microenvironment and prognosis in colorectal cancer liver metastasis: insights from multiomics profiling

BACKGROUND

This study aimed to investigate the prognostic impact of lymph node metastasis (LNM) on patients with colorectal cancer liver metastasis (CRLM) and elucidate the underlying immune mechanisms using multiomics profiling.

METHODS

We enrolled patients with CRLM from the US Surveillance, Epidemiology, and End Results (SEER) cohort and a multicenter Chinese cohort, integrating bulk RNA sequencing, single-cell RNA sequencing and proteomics data. The cancer-specific survival (CSS) and immune profiles of the tumor-draining lymph nodes (TDLNs), primary tumors and liver metastasis were compared between patients with and without LNM. Pathological evaluations were used to assess immune cell infiltration and histological features.

RESULTS

The CRLM patients with LNM had significantly shorter CSS than patients without LNM in two large cohorts. Our results showed that nonmetastatic TDLNs exhibited a greater abundance of immune cells, including CD4+ T cells, CD8+ T cells, and CD19+ B cells, whereas metastatic TDLNs were enriched with fibroblasts, endothelial cells, and macrophages. Immunohistochemical analysis confirmed elevated levels of CD3+ T cells, CD8+ T cells, and CD19+ B cells in nonmetastatic TDLNs. The presence of nonmetastatic TDLNs was associated with enhanced antitumor immune responses in primary tumors, characterized by a higher Klintrup-Makinen (KM) grade and the presence of tertiary lymphoid structures. Furthermore, liver metastasis in patients with nonmetastatic TDLNs were predominantly of the desmoplastic growth pattern (dHGP), while those with metastatic TDLNs were predominantly of the replacement growth pattern (rHGP).

CONCLUSIONS

This research highlights the adverse prognostic impact of LNM on patients with CRLM and reveals potential related mechanisms through multiomics analysis. Our research paves the way for further refinement of the AJCC TNM staging system for CRLM in clinical practice.

Alpha-fetoprotein combined with initial tumor shape irregularity in predicting the survival of patients with advanced hepatocellular carcinoma treated with immune-checkpoint inhibitors: a retrospective multi-center cohort study

BACKGROUND

Immune checkpoint inhibitors (ICIs) are playing a significant role in the treatment of hepatocellular carcinoma (HCC). This study aims to explore the prognostic value of alpha-fetoprotein (AFP) and initial tumor shape irregularity in patients treated with ICIs.

METHODS

In this retrospective, multi-center study, 296 HCC patients were randomly divided into the training set and the validation set in a 3:2 ratio. The training set was used to evaluate prognostic factors and to develop an easily applicable ATSI (AFP and Tumor Shape Irregularity) score, which was verified in the validation set.

RESULTS

The ATSI score was developed from two independent prognostic risk factors: baseline AFP ≥ 400 ng/ml (HR 1.73, 95% CI 1.01-2.96, P = 0.046) and initial tumor shape irregularity (HR 1.94, 95% CI 1.03-3.65, P = 0.041). The median overall survival (OS) was not reached (95% CI 28.20-NA) in patients who met no criteria (0 points), 25.8 months (95% CI 14.17-NA) in patients who met one criterion (1 point), and 17.03 months (95% CI 11.73-23.83) in patients who met two criteria (2 points) (P = 0.001). The median progression-free survival (PFS) was 10.83 months (95% CI 9.27-14.33) for 0 points, 8.03 months (95% CI 6.77-10.57) for 1 point, and 5.03 months (95% CI 3.83-9.67) for 2 points (P < 0.001). The validation set effectively verified these results (median OS, 37.43/24.27/14.03 months for 0/1/2 points, P = 0.028; median PFS, 13.93/8.30/4.90 months for 0/1/2 points, P < 0.001).

CONCLUSIONS

The ATSI score can effectively predict prognosis in HCC patients receiving ICIs.

Spatial transcriptomics reveals tryptophan metabolism restricting maturation of intratumoral tertiary lymphoid structures

Tertiary lymphoid structures (TLSs) are ectopic lymphoid aggregates found in numerous cancers, often linked to enhanced immunotherapy responses and better clinical outcomes. However, the factors driving TLS maturation are not fully understood. Using near single-cell spatial transcriptomic mapping, we comprehensively profile TLSs under various maturation stages and their microenvironment in hepatocellular carcinoma (HCC). Based on their developmental trajectories, we classify immature TLSs into two groups: conforming and deviating TLSs. Our findings indicate that conforming TLSs, similar to mature TLSs, possess a niche function for immunotherapy responses, while deviating TLSs do not. We discover that the tryptophan-enriched metabolic microenvironment shaped by malignant cells contributes to the deviation of TLS maturation. Inhibiting tryptophan metabolism promotes intratumoral TLS maturation and enhances tumor control, synergizing with anti-PD-1 treatments. Therefore, promoting TLS maturation represents a potential strategy to improve antitumor responses and immunotherapy outcomes.

Spatial multi-omics analysis of tumor-stroma boundary cell features for predicting breast cancer progression and therapy response

Background

The tumor boundary of breast cancer represents a highly heterogeneous region. In this area, the interactions between malignant and non-malignant cells influence tumor progression, immune evasion, and drug resistance. However, the spatial transcriptional profile of the tumor boundary and its role in the prognosis and treatment response of breast cancer remain unclear.

Method

Utilizing the Cottrazm algorithm, we reconstructed the intricate boundaries and identified differentially expressed genes (DEGs) associated with these regions. Cell-cell co-positioning analysis was conducted using SpaCET, which revealed key interactions between tumor-associated macrophage (TAMs) and cancer-associated fibroblasts (CAFs). Additionally, Lasso regression analysis was employed to develop a malignant body signature (MBS), which was subsequently validated using the TCGA dataset for prognosis prediction and treatment response assessment.

Results

Our research indicates that the tumor boundary is characterized by a rich reconstruction of the extracellular matrix (ECM), immunomodulatory regulation, and the epithelial-to-mesenchymal transition (EMT), underscoring its significance in tumor progression. Spatial colocalization analysis reveals a significant interaction between CAFs and M2-like tumor-associated macrophage (TAM), which contributes to immune exclusion and drug resistance. The MBS score effectively stratifies patients into high-risk groups, with survival outcomes for patients exhibiting high MBS scores being significantly poorer. Furthermore, drug sensitivity analysis demonstrates that high-MB tumors had poor response to chemotherapy strategies, highlighting the role of the tumor boundary in modulating therapeutic efficacy.

Conclusion

Collectively, we investigate the spatial transcription group and bulk data to elucidate the characteristics of tumor boundary molecules in breast cancer. The CAF-M2 phenotype emerges as a critical determinant of immunosuppression and drug resistance, suggesting that targeting this interaction may improve treatment responses. Furthermore, the MBS serves as a novel prognostic tool and offers potential strategies for guiding personalized treatment approaches in breast cancer.

Molecular pathways and diagnosis in spatially resolved Alzheimer's hippocampal atlas

We employed Stereo-seq combined with single-nucleus RNA sequencing (snRNA-seq) to investigate the gene expression and cell composition changes in human hippocampus with or without Alzheimer's disease (AD). The transcriptomic map, with single-cell precision, unveiled AD-associated alterations with spatial specificity, which include the following: (1) elevated synapse pruning gene expression in the fimbria of AD, with disrupted microglia-astrocyte communication likely leading to disorganized synaptic structure; (2) a globally increased energy generation in the cornu ammonis (CA) region, with varying degrees across its subregions; (3) a significant reduction in the number of CA1 neurons in AD, while CA4 neurons remained largely unaffected, potentially due to gene alterations in CA4 conferring resilience to AD; and (4) aggravated amyloid-beta (Aβ) plaques in CA1 and stratum lucidum, radiatum, and moleculare (SLRM), and integration of Stereo-seq map with Aβ staining revealed a sequential enrichment of microglia and astrocytes around Aβ plaques. Finally, reduced brain-derived extracellular vesicles carrying cholecystokinin (CCK) and peripheral myelin protein 2 (PMP2) in AD plasma highlighted their diagnostic potential for clinical applications.

MuCST: restoring and integrating heterogeneous morphology images and spatial transcriptomics data with contrastive learning

Spatially resolved transcriptomics (SRT) simultaneously measure spatial location, histology images, and transcriptional profiles of cells or regions in undissociated tissues. Integrative analysis of multi-modal SRT data holds immense potential for understanding biological mechanisms. Here, we present a flexible multi-modal contrastive learning for the integration of SRT data (MuCST), which joins denoising, heterogeneity elimination, and compatible feature learning. MuCST accurately identifies spatial domains and is applicable to diverse datasets platforms. Overall, MuCST provides an alternative for integrative analysis of multi-modal SRT data ( https://github.com/xkmaxidian/MuCST ).

Liver Metastasis in Cancer: Molecular Mechanisms and Management

Liver metastasis is a leading cause of mortality from malignant tumors and significantly impairs the efficacy of therapeutic interventions. In recent years, both preclinical and clinical research have made significant progress in understanding the molecular mechanisms and therapeutic strategies of liver metastasis. Metastatic tumor cells from different primary sites undergo highly similar biological processes, ultimately achieving ectopic colonization and growth in the liver. In this review, we begin by introducing the inherent metastatic-friendly features of the liver. We then explore the panorama of liver metastasis and conclude the three continuous, yet distinct phases based on the liver's response to metastasis. This includes metastatic sensing stage, metastatic stress stage, and metastasis support stage. We discuss the intricate interactions between metastatic tumor cells and various resident and recruited cells. In addition, we emphasize the critical role of spatial remodeling of immune cells in liver metastasis. Finally, we review the recent advancements and the challenges faced in the clinical management of liver metastasis. Future precise antimetastatic treatments should fully consider individual heterogeneity and implement different targeted interventions based on stages of liver metastasis.

Single-cell analyses reveal metastasis mechanism and microenvironment remodeling of lymph node in intrahepatic cholangiocarcinoma

Background & Aims

Lymph node metastasis (LNM) is a major determinant of recurrence and prognosis in intrahepatic cholangiocarcinoma (iCCA). LNM disrupts T cell-mediated cytotoxicity, promotes tumor-specific immune tolerance, and facilitates distant metastasis. Despite its importance, extensive research on LMN in iCCA is lacking. This study aimed to systematically explore the heterogeneity of the LNM-associated microenvironment in iCCA by integrating single-cell and multi-omics analyses, identifying metastasis-associated cell subgroups, and validating these findings through multiple cohorts.

Methods

We analyzed single-cell transcriptomics data from primary tumors, cancer-adjacent liver tissues, and tumor-draining lymph nodes of four patients with iCCA who underwent radical surgery. Additionally, we collected 81 tumor and matched lymph node tissue sections from patients with iCCA. We performed single-cell RNA sequencing and multiplex immunohistochemistry, followed by differential gene expression analysis, functional enrichment analysis, single-cell copy number variation assessment, and pseudotime analysis.

Results

Our analysis revealed the complex heterogeneity of the iCCA LNM-associated microenvironment. We found a significant increase in stromal and mature immune cells in the metastatic lymph nodes. T cells constitute the predominant component, with diverse functional subtypes. We identified CD36+ macrophages and SAA1+ tumor cells as key players in the metastatic process. The SAA1-CD36 receptor‒ligand pair may be crucial in forming the LNM-associated microenvironment.

Conclusions

We identified several metastasis-associated cell subgroups. These findings provide new insights into the mechanisms underlying LNM in iCCA and lay the groundwork for the development of novel therapeutic strategies. Our study highlights the importance of single-cell technologies in understanding tumor microenvironment complexity and offers valuable resources for future research.

Impact and implications

The lack of single-cell transcriptome analysis of intrahepatic cholangiocarcinoma (iCCA) lymph node metastases has prevented us from understanding the underlying mechanisms of disease progression. To fill this knowledge gap, we elucidated the unique ecosystem of iCCA lymph node metastases, which is an important advance in clarifying the impact of the immune environment on the development of this disease. The results of this study identified several LNM-related therapeutic targets, which will not only be helpful to basic researchers, but also provide potential diagnostic and treatment ideas for physicians, thereby helping patients and their caregivers develop more personalized treatment plans. This finding is highly important for improving the prognosis of patients with advanced iCCA in the future.

Prognostic Value of Ki-67 in the Invasive Zone of Oral Squamous Cell Carcinoma

BACKGROUND

The molecular profile of cells within the tumor invasive zone, where tumor cells interact with surrounding non-tumor cells, plays a crucial role in defining tumor malignant characteristics, such as the pattern of invasion (POI). Therefore, evaluating the diagnostic value of the proliferation index molecule, Ki-67, in both tumor cells and adjacent non-tumor cells at the invasive zone with different POIs, holds significant clinical importance for oral squamous cell carcinoma (OSCC).

METHODS

This retrospective study included 133 primary OSCC samples, and the spatial pattern of Ki-67 in the tumor invasive zone was analyzed by immunohistochemistry (IHC). The prognostic value of tumor cells and stroma proliferative capacity in different POIs were assessed.

RESULTS

Ki-67 was widely expressed in tumor cells and stroma cells within the invasive zone, and cells in high-invasiveness POIs exhibit higher proliferation. Elevated Ki-67 expression in tumor cells was associated with poor overall survival (OS) and disease-free survival (DFS) in patients, which is independent of POIs. In our study, we identified the expression level of Ki-67 in tumor cells across high-invasiveness POIs as an independent risk factor for OS and DFS in OSCC patiens. Additionally, Ki-67 expression in surrounding non-tumor cells did not significantly correlate with patient survival.

CONCLUSION

The remarkable proliferation characteristic of tumor cells in high-invasiveness POIs of OSCC tumors plays a crucial role in the prognosis of patients.

NFE2-driven neutrophil polarization promotes pancreatic cancer liver metastasis progression

Pancreatic cancer liver metastasis is an important factor leading to dismal prognoses. The details of adaptive immune remodeling in liver metastasis, especially the role of neutrophils, remain elusive. Here, combined single-cell sequencing with spatial transcriptomics results revealed that liver metastases exhibit more aggressive transcriptional characteristics and higher levels of immunosuppression compared with the primary tumor. We identified neutrophils_S100A12 (S100 calcium binding protein A12) cells as the pivotal pro-metastatic cluster, specifically distributed at the invasive front of the metastatic lesions. Mechanistically, our findings indicated that nuclear factor erythroid 2 (NFE2) is a key transcription factor regulating neutrophil phenotypic polarization. Metastatic tumors produce transforming growth factor β to activate the SMAD3 pathway within neutrophils, inducing NFE2-driven polarization. NFE2 promotes the transcription of peptidylarginine deiminase 4 by binding to its promoter, leading to the generation of neutrophil extracellular traps at the invasive front. Collectively, our data demonstrate that NFE2-driven neutrophil polarization is a potential target for anti-metastatic therapy.

Inferring cell trajectories of spatial transcriptomics via optimal transport analysis

The integration of cell transcriptomics and spatial position to organize differentiation trajectories remains a challenge. Here, we introduce SpaTrack, which leverages optimal transport to reconcile both gene expression and spatial position from spatial transcriptomics into the transition costs, thereby reconstructing cell differentiation. SpaTrack can construct detailed spatial trajectories that reflect the differentiation topology and trace cell dynamics across multiple samples over temporal intervals. To capture the dynamic drivers of differentiation, SpaTrack models cell fate as a function of expression profiles influenced by transcription factors over time. By applying SpaTrack, we successfully disentangle spatiotemporal trajectories of axolotl telencephalon regeneration and mouse midbrain development. Diverse malignant lineages expanding within a primary tumor are uncovered. One lineage, characterized by upregulated epithelial mesenchymal transition, implants at the metastatic site and subsequently colonizes to form a secondary tumor. Overall, SpaTrack efficiently advances trajectory inference from spatial transcriptomics, providing valuable insights into differentiation processes.

Integration of single-cell and spatial transcriptomics reveals fibroblast subtypes in hepatocellular carcinoma: spatial distribution, differentiation trajectories, and therapeutic potential

BACKGROUND

Cancer-associated fibroblasts (CAFs) are key components of the hepatocellular carcinoma (HCC) tumor microenvironment (TME). regulating tumor proliferation, metastasis, therapy resistance, immune evasion via diverse mechanisms. A deeper understanding of the l diversity of CAFs is essential for predicting patient prognosis and guiding treatment strategies.

METHODS

We examined the diversity of CAFs in HCC by integrating single-cell, bulk, and spatial transcriptome analyses.

RESULTS

Using a training cohort of 88 HCC single-cell RNA sequencing (scRNA-seq) samples and a validation cohort of 94 samples, encompassing over 1.2 million cells, we classified three fibroblast subpopulations in HCC: HLA-DRB1 + CAF, MMP11 + CAF, and VEGFA + CAF based on highly expressed genes of which, which are primarily located in normal tissue, tumor boundaries, and tumor interiors, respectively. Cell trajectory analysis revealed that VEGFA + CAFs are at the terminal stage of differentiation, which, notably, is tumor-specific. VEGFA + CAFs were significantly associated with patient survival, and the hypoxic microenvironment was found to be a major factor inducing VEGFA + CAFs. Through cellular communication with capillary endothelial cells (CapECs), VEGFA + CAFs promoted intra-tumoral angiogenesis, facilitating tumor progression and metastasis. Additionally, a machine learning model developed using high-expression genes from VEGFA + CAFs demonstrated high accuracy in predicting prognosis and sorafenib response in HCC patients.

CONCLUSIONS

We characterized three fibroblast subpopulations in HCC and revealed their distinct spatial distributions within the tumor. VEGFA + CAFs, which was induced by hypoxic TME, were associated with poorer prognosis, as they promote tumor angiogenesis through cellular communication with CapECs. Our findings provide novel insights and pave the way for individualized therapy in HCC patients.

Immune microenvironment spatial landscapes of tertiary lymphoid structures in gastric cancer

BACKGROUND

Tertiary lymphoid structures (TLS) correlate with tumour prognosis and immunotherapy responses in gastric cancer (GC) studies. However, understanding the complex and diverse immune microenvironment within TLS requires comprehensive analysis.

METHODS

We examined the prognostic impact of TLS within the tumour core (TC) of 59 GC patients undergoing immunotherapy. Multispectral fluorescence imaging was employed to evaluate variations in immune cell infiltration across different TLS sites among 110 GC patients, by quantifying immune cell density and spatial characteristics. We also generated a single-cell transcriptomic atlas of TLS-positive (n = 4) and TLS-negative (n = 8) microenvironments and performed spatial transcriptomics (ST) analysis on two samples.

RESULTS

TLS presence in the TC significantly correlated with improved immune-related overall survival (P = 0.049). CD8+LAG-3-PD-1+TIM-3-, CD4+PD-L1+, and CD4+FoxP3- T cell densities were significantly higher in the TLS within TC compared to tumour and stromal regions. Immune cells within TLS exhibited closer intercellular proximity than those outside TLS. Five key density and spatial characteristics of immune cells within TLS in the TC were selected to develop the Density and Spatial Score risk model. Single-cell RNA sequencing revealed strong intercellular interactions in the presence of TLS within the microenvironment. However, TLS-absent environment facilitated tumour cell interactions with immune cells through MIF- and galectin-dependent pathways, recruiting immunosuppressive cells. ST analysis confirmed that T and B cells co-localise within TLS, enhancing immune response activation compared to cancer nests and exerting a strong anti-tumour effect.

CONCLUSIONS

TLS presence facilitates frequent cell-to-cell communication, forming an active immune microenvironment, highlighting the prognostic value of TLS.

Single-Cell and Spatial Transcriptomics Delineate the Microstructure and Immune Landscape of Intrahepatic Cholangiocarcinoma in the Leading-Edge Area

Intrahepatic cholangiocarcinoma (ICC) tumor cells and their interactions with the immune microenvironment, particularly at the leading-edge area, have been underexplored. This study employs single-cell RNA sequencing (scRNA-seq) and spatial transcriptome (ST) analysis on samples from the tumor core, adjacent non-tumorous tissue, and the leading-edge area of nine ICC patients. These findings indicate that tumor cells at the leading-edge area demonstrate enhanced proliferation and are tightly associated with the stroma, including endothelial cells and POSTN+ FAP+ fibroblasts. Notably, CD8+ T cells in this region exhibit a naive phenotype with low cytotoxicity and signs of exhaustion, likely due to compromised antigen presentation by antigen-presenting cells (APCs). The predominant CD8+ T cell subset, mucosal-associated invariant T (MAIT) cells, recruits SPP1+ macrophages within the stroma. This interaction, along with the presence of POSTN+ cancer-associated fibroblasts (CAFs) and endothelial cells, forms a unique "triad structure" that fosters tumor growth and ICC progression. The research highlights the intricate characteristics and interactions of ICC tumor cells in the leading-edge area, offering insights into potential therapeutic targets for intervention.

Spatial‒temporal heterogeneities of liver cancer and the discovery of the invasive zone

Solid tumours are intricate and highly heterogeneous ecosystems, which grow in and invade normal organs. Their progression is mediated by cancer cells' interaction with different cell types, such as immune cells, stromal cells and endothelial cells, and with the extracellular matrix. Owing to its high incidence, aggressive growth and resistance to local and systemic treatments, liver cancer has particularly high mortality rates worldwide. In recent decades, spatial heterogeneity has garnered significant attention as an unfavourable biological characteristic of the tumour microenvironment, prompting extensive research into its role in liver tumour development. Advances in spatial omics have facilitated the detailed spatial analysis of cell types, states and cell‒cell interactions, allowing a thorough understanding of the spatial and temporal heterogeneities of tumour microenvironment and informing the development of novel therapeutic approaches. This review illustrates the latest discovery of the invasive zone, and systematically introduced specific macroscopic spatial heterogeneities, pathological spatial heterogeneities and tumour microenvironment heterogeneities of liver cancer.

Tertiary Lymphoid Structures are Linked to Enhanced Antitumor Immunity and Better Prognosis in Muscle-Invasive Bladder Cancer

The prognosis for muscle-invasive bladder cancer (MIBC) remains poor, and reliable prognostic markers have yet to be identified. Tertiary lymphoid structures (TLS) have been associated with favorable outcomes in certain cancers. However, the relationship between TLS and MIBC remains unclear. A multi-omics approach is utilized, leveraging single-cell RNA sequencing, spatial transcriptomics, bulk RNA sequencing, and immunohistochemistry, to investigate the roles of B cells and TLS in MIBC. These findings indicate that elevated levels of B cells and TLS correlate with improved prognoses in patients with MIBC, aligning with the robust antitumor immune responses observed in the TLS region. From a mechanistic perspective, CXCL13 serves as a critical cytokine for TLS formation in MIBC, primarily secreted by clonally expanded CXCL13+ T cells. This cytokine interacts with the CXCR5 receptor on NR4A2+ B cells, promoting TLS development. Plasma cells arising within the TLS microenvironment predominantly produce the IGHG antibody, potentially enhancing the phagocytic capabilities of C1QC+ macrophages. From an application standpoint, a TLS-specific gene signature is developed that effectively predicts outcomes in MIBC and other cancers. This study highlights the prognostic potential of TLS in MIBC and reveals immune mechanisms, offering insights for personalized treatment strategies.

Habitat radiomics based on CT images to predict survival and immune status in hepatocellular carcinoma, a multi-cohort validation study

BACKGROUND AND OBJECTIVE

Though several clinicopathological features are identified as prognostic indicators, potentially prognostic radiomic models are expected to preoperatively and noninvasively predict survival for HCC. Traditional radiomic models are lacking in a consideration for intratumoral regional heterogeneity. The study aimed to establish and validate the predictive power of multiple habitat radiomic models in predicting prognosis of hepatocellular carcinoma (HCC).

METHODS

A total of 232 HCC patients were retrospectively included, including a training/validation cohort and two external testing cohorts from 4 centers. For habitat radiomics, intratumoral habitat partitioning based on CT images was first performed by using Otsu thresholding method. Second, a total of 350 habitat radiomic models were constructed to select the optimal model. Then, both ROC curve analyses and Kaplan-Meier survival curve analyses were applied to assess the predictive performances. Ultimately, an immune status profiling was conducted based on bioinformatic analyses and multiplex immunohistochemistry (mIHC) assays to reveal the potential mechanisms.

RESULTS

A total of 4 habitats were segmented, and the corresponding habitat radiomic models were constructed based on each habitat and an integration of all the four habitats. Generally, habitat radiomic models outperformed traditional radiomic models in stratifying prognosis for HCC. The habitat radiomic model based on the segmented habitat 4 involving decision tree (DT) screening and random forest (RF) classifier was identified as the optimal model with an AUCmean of 0.806. Distinct resting natural killer (NK) cell infiltrations significantly contributed to the prognosis stratification of HCC by the optimal habitat radiomic model.

CONCLUSIONS

The habitat radiomic model based on CT images was potentially predictive of overall survival for HCC, with a superiority over the traditional radiomic model. The prognostic power of the habitat radiomic model was partly attributed to the distinct immune status captured in the CT images.

Stromal architecture and fibroblast subpopulations with opposing effects on outcomes in hepatocellular carcinoma

Dissecting the spatial heterogeneity of cancer-associated fibroblasts (CAFs) is vital for understanding tumor biology and therapeutic design. By combining pathological image analysis with spatial proteomics, we revealed two stromal archetypes in hepatocellular carcinoma (HCC) with different biological functions and extracellular matrix compositions. Using paired single-cell RNA and epigenomic sequencing with Stereo-seq, we revealed two fibroblast subsets CAF-FAP and CAF-C7, whose spatial enrichment strongly correlated with the two stromal archetypes and opposing patient prognosis. We discovered two functional units, one is the intratumor inflammatory hub featured by CAF-FAP plus CD8_PDCD1 proximity and the other is the marginal wound-healing hub with CAF-C7 plus Macrophage_SPP1 co-localization. Inhibiting CAF-FAP combined with anti-PD-1 in orthotopic HCC models led to improved tumor regression than either monotherapy. Collectively, our findings suggest stroma-targeted strategies for HCC based on defined stromal archetypes, raising the concept that CAFs change their transcriptional program and intercellular crosstalk according to the spatial context.

VCP downstream metabolite glycerol-3-phosphate (G3P) inhibits CD8+T cells function in the HCC microenvironment

CD8+T cells within the tumor microenvironment (TME) are often functionally impaired, which limits their ability to mount effective anti-tumor responses. However, the molecular mechanisms behind this dysfunction remain incompletely understood. Here, we identified valosin-containing protein (VCP) as a key regulator of CD8+T cells suppression in hepatocellular carcinoma (HCC). Our findings reveal that VCP suppresses the activation, expansion, and cytotoxic capacity of CD8+T cells both in vitro and in vivo, significantly contributing to the immunosuppressive nature of the TME. Mechanistically, VCP stabilizes the expression of glycerol-3-phosphate dehydrogenase 1-like protein (GPD1L), leading to the accumulation of glycerol-3-phosphate (G3P), a downstream metabolite of GPD1L. The accumulated G3P diffuses into the TME and directly interacts with SRC-family tyrosine kinase LCK, a critical component of the T-cell receptor (TCR) signaling pathway in CD8+T cells. This interaction heightens the phosphorylation of Tyr505, a key inhibitory residue, ultimately reducing LCK activity and impairing downstream TCR signaling. Consequently, CD8+T cells lose their functional capacity, diminishing their ability to fight against HCC. Importantly, we demonstrated that targeting VCP in combination with anti-PD1 therapy significantly suppresses HCC tumor growth and restores the anti-tumor function of CD8+T cells, suggesting synergistic therapeutic potential. These findings highlight a previously unrecognized mechanism involving VCP and G3P in suppressing T-cell-mediated immunity in the TME, positioning VCP as a promising upstream target for enhancing immunotherapy in HCC.

Recent Advances in Studies of Serum Amyloid A: Implications in Inflammation, Immunity and Tumor Metastasis

Research on serum amyloid A (SAA) has seen major advancement in recent years with combined approaches of structural analysis and genetically altered mice. Initially identified as an acute-phase reactant, SAA is now recognized as a major player in host defense, inflammation, lipid metabolism and tumor metastasis. SAA binding and the neutralization of LPS attenuate sepsis in mouse models. SAA also displays immunomodulatory functions in Th17 differentiation and macrophage polarization, contributing to a pro-metastatic tumor microenvironment. In spite of the progress, the regulatory mechanisms for these diverse functions of SAA remain unclear. This review provides a brief summary of recent advances in SAA research on immunity, inflammation, tumor microenvironment and in vivo models.

Exploring the cellular and molecular basis of murine cardiac development through spatiotemporal transcriptome sequencing

BACKGROUND

Spatial transcriptomics is a powerful tool that integrates molecular data with spatial information, thereby facilitating a deeper comprehension of tissue morphology and cellular interactions. In our study, we utilized cutting-edge spatial transcriptome sequencing technology to explore the development of the mouse heart and construct a comprehensive spatiotemporal cell atlas of early murine cardiac development.

RESULTS

Through the analysis of this atlas, we elucidated the spatial organization of cardiac cellular lineages and their interactions during the developmental process. Notably, we observed dynamic changes in gene expression within fibroblasts and cardiomyocytes. Moreover, we identified critical genes, such as Igf2, H19, and Tcap, as well as transcription factors Tcf12 and Plagl1, which may be associated with the loss of myocardial regeneration ability during early heart development. In addition, we successfully identified marker genes, like Adamts8 and Bmp10, that can distinguish between the left and right atria.

CONCLUSION

Our study provides novel insights into murine cardiac development and offers a valuable resource for future investigations in the field of heart research, highlighting the significance of spatial transcriptomics in understanding the complex processes of organ development.

Spatial-Omics Methods and Applications

Traditional tissue profiling approaches have evolved from bulk studies to single-cell analysis over the last decade; however, the spatial context in tissues and microenvironments has always been lost. Over the last 5 years, spatial technologies have emerged that enabled researchers to investigate tissues in situ for proteins and transcripts without losing anatomy and histology. The field of spatial-omics enables highly multiplexed analysis of biomolecules like RNAs and proteins in their native spatial context-and has matured from initial proof-of-concept studies to a thriving field with widespread applications from basic research to translational and clinical studies. While there has been wide adoption of spatial technologies, there remain challenges with the standardization of methodologies, sample compatibility, throughput, resolution, and ease of use. In this chapter, we discuss the current state of the field and highlight technological advances and limitations.

Challenges and Opportunities in the Clinical Translation of High-Resolution Spatial Transcriptomics

Pathology has always been fueled by technological advances. Histology powered the study of tissue architecture at single-cell resolution and remains a cornerstone of clinical pathology today. In the last decade, next-generation sequencing has become informative for the targeted treatment of many diseases, demonstrating the importance of genome-scale molecular information for personalized medicine. Today, revolutionary developments in spatial transcriptomics technologies digitalize gene expression at subcellular resolution in intact tissue sections, enabling the computational analysis of cell types, cellular phenotypes, and cell-cell communication in routinely collected and archival clinical samples. Here we review how such molecular microscopes work, highlight their potential to identify disease mechanisms and guide personalized therapies, and provide guidance for clinical study design. Finally, we discuss remaining challenges to the swift translation of high-resolution spatial transcriptomics technologies and how integration of multimodal readouts and deep learning approaches is bringing us closer to a holistic understanding of tissue biology and pathology.

Roles of Cellular Neighborhoods in Hepatocellular Carcinoma Pathogenesis

The development of hepatocellular carcinoma (HCC) involves an intricate interplay among various cell types within the liver. Unraveling the orchestration of these cells, particularly in the context of various etiologies, may hold the key to deciphering the underlying mechanisms of this complex disease. The advancement of single-cell and spatial technologies has revolutionized our ability to determine cellular neighborhoods and understand their crucial roles in disease pathogenesis. In this review, we highlight the current research landscape on cellular neighborhoods in chronic liver disease and HCC, as well as the emerging computational approaches applicable to delineate disease-associated cellular neighborhoods, which may offer insights into the molecular mechanisms underlying HCC pathogenesis and pave the way for effective disease interventions.

Envafolimab Inhibits the Growth of Gastric Cancer Cells with Low PD-L1 Expression through the DDX20/NF-κB/TNF-α Signaling Pathway

BACKGROUND

The mechanism of action of envafolimab (also known as KN035), a programmed death ligand 1 (PD-L1) inhibitor, in gastric adenocarcinoma patients with low PD-L1 expression is not well understood.

OBJECTIVES

The objective of this study was to explore the underlying mechanism of envafolimab in gastric cancer with low PD-L1 expression.

METHODS

Cytotoxicity and proliferation were evaluated by a CCK8 assay. Transwell assays were used to detect the migration and invasion ability of gastric cancer cells. The effect of envafolimab on the apoptosis of gastric cancer cells was detected by flow cytometry. The effect of envafolimab on gastric cancer cells with low PD-L1 expression was investigated via proteomics and bioinformatics analysis.

RESULTS

A total of 19 patients with advanced gastric adenocarcinoma who received envafolimab monotherapy or combination therapy were reviewed. Among them, 4 patients had low PD-L1 expression, the objective response rate (ORR) was 75% (3/4), and the disease control rate (DCR) was 100% (4/4). In vitro experiments showed that envafolimab inhibited the proliferation, invasion, and migration of gastric cancer cells with low expression of PD-L1 and induced cell apoptosis. DDX20 may be the target of envafolimab in gastric cancer cells, and it is related to the NF-κB signaling pathway. Western blot results showed that the protein expressions of DDX20, NF-κB p65, and TNF-α in gastric cancer cells were decreased after adding envafolimab. Furthermore, the DDX20 gene was silenced by small interfering RNA to further study the effect of DDX20 on PDL1 low expression in gastric cancer cells.

CONCLUSION

This study confirmed that envafolimab could inhibit the growth of gastric cancer cells with low PD-L1 expression by down-regulating DDX20 expression and regulating the NF- κB/TNF-α signaling pathway.

Spatial transcriptomics reveals unique metabolic profile and key oncogenic regulators of cervical squamous cell carcinoma

BACKGROUND

As a prevalent and deadly malignant tumor, the treatment outcomes for late-stage patients with cervical squamous cell carcinoma (CSCC) are often suboptimal. Previous studies have shown that tumor progression is closely related with tumor metabolism and microenvironment reshaping, with disruptions in energy metabolism playing a critical role in this process. To delve deeper into the understanding of CSCC development, our research focused on analyzing the tumor microenvironment and metabolic characteristics across different regions of tumor tissue.

METHODS

Utilizing spatial transcriptomics (ST) sequencing technology, we conducted a study on FFPE (formalin-fixed paraffin-embedded) tumor samples from CSCC patients. Coupled with single-cell RNA sequencing (scRNA-seq) data after deconvolution, we described spatial distribution maps of tumor leading edge and core regions in detail. Tumor tissues were classified into hypermetabolic and hypometabolic regions to analyze the metabolism profiles and tumor differentiation degree across different spatial areas. We also employed The Cancer Genome Atlas (TCGA) database to examine the analysis results of ST data.

RESULTS

Our findings indicated a more complex tumor microenvironment in hypermetabolic regions. Cell-cell communication analysis showed that various cells in tumor microenvironment were influenced by the signalling molecule APP released by cancer cells and higher expression of APP was observed in hypermetabolic regions. Furthermore, our results revealed the correlation between APP and the transcription factor TRPS1. Both APP and TRPS1 demonstrated significant effects on cancer cell proliferation, migration, and invasion, potentially contributing to tumor progression.

CONCLUSIONS

Utilizing ST, scRNA-seq, and TCGA database, we examined the spatial metabolic profiles of CSCC tissues, including metabolism distribution, metabolic variations, and the relationship between metabolism and tumor differentiation degree. Additionally, potential cancer-promoting factors were proposed, offering a valuable foundation for the development of more effective treatment strategies for CSCC.

Integrated Single-Cell and Spatial Transcriptome Reveal Metabolic Gene SLC16A3 as a Key Regulator of Immune Suppression in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most lethal cancers, usually diagnosed at an advanced stage. Metabolic reprogramming plays a significant role in HCC progression, probably related to immune evasion, yet the key gene is unclear. In this study, six metabolism-related genes with prognostic implications were screened. Correlation analysis between the key genes and immune cell subtypes was conducted, and a prominent gene strongly associated with immunosuppression, SLC16A3, was identified. Overexpression of SLC16A3 is associated with the loss of T-cell function and might lead to the upregulation of several immunosuppressive proteins. Gene function enrichment analysis showed genes correlated with SLC16A3 primarily involved in cell adhesion. Single-cell analysis showed that the SLC16A3 gene was mainly expressed in macrophages, especially some tumour-promoting macrophages. Further analysis of spatial transcriptome data indicated that SLC16A3 was enriched at the tumour invasion front. The mIHC revealed that patients with high SLC16A3 expression exhibited significantly reduced infiltration of GZMB+ cells. And SLC16A3 inhibitors significantly suppressed the proliferation of HCC, while simultaneously enhancing T-cell cytotoxicity and reducing exhaustion. These results reveal the phenomenon of immune escape mediated by metabolic reprogramming and suggest that SLC16A3 may serve as a novel target for intervention.

Intra- and Peri-tumoral Radiomics Based on Dynamic Contrast Enhanced-MRI to Identify Lymph Node Metastasis and Prognosis in Intrahepatic Cholangiocarcinoma

BACKGROUND

Lymph node metastasis (LNM) in patients with intrahepatic cholangiocarcinoma (iCCA) affects treatment strategies and prognosis. However, preoperative imaging is not reliable enough for identifying LNM.

PURPOSE

To develop and validate a radiomics nomogram based on dynamic contrast enhanced (DCE)-MR images for identifying LNM and prognosis in iCCA.

STUDY TYPE

Retrospective.

SUBJECTS

Two hundred four patients with pathologically proven iCCA who underwent curative-intent resection and lymphadenectomy (training cohort: N = 107, internal test cohort: N = 46, and external test cohort: N = 51).

FIELD STRENGTH/SEQUENCE

T1- and T2-weighted imaging, diffusion-weighted imaging and DCE imaging at 1.5 T or 3.0 T.

ASSESSMENT

Radiomics features were extracted from intra- and peri-tumoral regions on preoperative DCE-MR images. Imaging features were evaluated by three radiologists, and significant variables in univariable and multivariable regression analysis were included in clinical model. The best-performing radiomics signature and clinical characteristics (intrahepatic duct dilatation, MRI-reported LNM) were combined to build a nomogram. Patients were divided into high-risk and low-risk groups based on their nomogram scores (cutoff = 0.341). Patients were followed up for 1-102 months (median 12) after surgery, the overall survival (OS) and recurrence-free survival (RFS) were calculated.

STATISTICAL TESTS

Receiver operating characteristic (ROC) curve, calibration, decision curve, Delong test, Kaplan-Meier curves, log rank test. Two tailed P < 0.05 was considered statistically significant.

RESULTS

The nomogram incorporating intra- and peri-tumoral radiomics features, intrahepatic duct dilatation and MRI-reported LNM obtained the best discrimination for LNM, with areas under the ROC curves of 0.946, 0.913, and 0.859 in the training, internal, and external test cohorts. In the entire cohort, high-risk patients had significantly lower RFS and OS than low-risk patients. High-risk of LNM was an independent factor of unfavorable OS and RFS.

DATA CONCLUSION

The nomogram integrating intra- and peri-tumoral radiomics signatures has potential to identify LNM and prognosis in iCCA.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

Spatial multi-omics characterizes GPR35-relevant lipid metabolism signatures across liver zonation in MASLD

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a metabolic disease that can progress to metabolic dysfunction-associated steatohepatitis (MASH), cirrhosis, and cancer. The zonal distribution of biomolecules in the liver is implicated in mediating the disease progression. Recently, G-protein-coupled receptor 35 (GPR35) has been highlighted to play a role in MASLD, but the precise mechanism is not fully understood, particularly, in a liver-zonal manner. Here, we aimed to identify spatially distributed specific genes and metabolites in different liver zonation that are regulated by GPR35 in MASLD, by combining lipid metabolomics, spatial transcriptomics (ST), and spatial metabolomics (SM). We found that GPR35 influenced lipid accumulation, inflammatory and metabolism-related factors in specific regions, notably affecting the anti-inflammation factor ELF4 (E74 like E-twenty six (ETS) transcription factor 4), lipid homeostasis key factor CIDEA (cell death-inducing DNA fragmentation factor alpha (DFFA)-like effector A), and the injury response-related genes SAA1/2/3 (serum amyloid A1/2/3), thereby impacting MASLD progression. Furthermore, SM elucidated specific metabolite distributions across different liver regions, such as C10H11N4O7P (3',5'-cyclic inosine monophosphate (3',5'-IMP)) for the central vein, and this metabolite significantly decreased in the liver zones of GPR35-deficient mice during MASLD progression. Taken together, GPR35 regulates hepatocyte damage repair, controls inflammation, and prevents MASLD progression by influencing phospholipid homeostasis and gene expression in a zonal manner.

YAP1 Inhibition Induces Phenotype Switching of Cancer-Associated Fibroblasts to Tumor Suppressive in Prostate Cancer

Prostate cancer rarely responds to immune-checkpoint blockade (ICB) therapies. Cancer-associated fibroblasts (CAF) are critical components of the immunologically "cold" tumor microenvironment and are considered a promising target to enhance the immunotherapy response. In this study, we aimed to reveal the mechanisms regulating CAF plasticity to identify potential strategies to switch CAFs from protumorigenic to antitumor phenotypes and to enhance ICB efficacy in prostate cancer. Integration of four prostate cancer single-cell RNA sequencing datasets defined protumorigenic and antitumor CAFs, and RNA-seq, flow cytometry, and a prostate cancer organoid model demonstrated the functions of two CAF subtypes. Extracellular matrix-associated CAFs (ECM-CAF) promoted collagen deposition and cancer cell progression, and lymphocyte-associated CAFs (Lym-CAF) exhibited an antitumor phenotype and induced the infiltration and activation of CD8+ T cells. YAP1 activity regulated the ECM-CAF phenotype, and YAP1 silencing promoted switching to Lym-CAFs. NF-κB p65 was the core transcription factor in the Lym-CAF subset, and YAP1 inhibited nuclear translocation of p65. Selective depletion of YAP1 in ECM-CAFs in vivo promoted CD8+ T-cell infiltration and activation and enhanced the therapeutic effects of anti-PD-1 treatment on prostate cancer. Overall, this study revealed a mechanism regulating CAF identity in prostate cancer and highlighted a therapeutic strategy for altering the CAF subtype to suppress tumor growth and increase sensitivity to ICB. Significance: YAP1 regulates cancer-associated fibroblast phenotypes and can be targeted to switch cancer-associated fibroblasts from a protumorigenic subtype that promotes extracellular matrix deposition to a tumor-suppressive subtype that stimulates antitumor immunity and immunotherapy efficacy.

Fasting as an Adjuvant Therapy for Cancer: Mechanism of Action and Clinical Practice

The fundamental biological characteristics of tumor cells are characterized by irregularities in signaling and metabolic pathways, which are evident through increased glucose uptake, altered mitochondrial function, and the ability to evade growth signals. Interventions such as fasting or fasting-mimicking diets represent a promising strategy that can elicit distinct responses in normal cells compared to tumor cells. These dietary strategies can alter the circulating levels of various hormones and metabolites, including blood glucose, insulin, glucagon, growth hormone, insulin-like growth factor, glucocorticoids, and epinephrine, thereby potentially exerting an anticancer effect. Additionally, elevated levels of insulin-like growth factor-binding proteins and ketone bodies may increase tumor cells' dependence on their own metabolites, ultimately leading to their apoptosis. The combination of fasting or fasting-mimicking diets with radiotherapy or chemotherapeutic agents has demonstrated enhanced anticancer efficacy. This paper aims to classify fasting, elucidate the mechanisms that underlie its effects, assess its impact on various cancer types, and discuss its clinical applications. We will underscore the differential effects of fasting on normal and cancer cells, the mechanisms responsible for these effects, and the imperative for clinical implementation.

Comprehensive mapping of somatotroph pituitary neuroendocrine tumour heterogeneity using spatial and single-cell transcriptomics

BACKGROUND

Pituitary neuroendocrine tumours (PitNETs) are common intracranial tumours that are highly heterogeneous with unpredictable growth patterns. The driver genes and mechanisms that are crucial for tumour progression in somatotroph PitNETs are poorly understood.

METHODS

In this study, we performed integrative spatial transcriptomics (ST) and single-cell RNA sequencing (scRNA-seq) analysis on somatotroph tumours and normal pituitary samples to comprehensively characterize the differences in cellular characteristics.

RESULTS

By analyzing combined copy number variations (CNVs), tumour tissues were divided into two regions, which included the CNVhigh and CNVlow areas. The protumour genes DLK1 and RCN1 were highly expressed in the CNVhigh area, which might be related to tumour progression and could be targeted for precision therapy. We also found that the transforming growth factor beta signalling pathway participated in tumour progression and identified heterogeneity in the expression profiles of key genes. We assessed the intertumoral and intratumoral heterogeneity in somatotroph PitNETs and emphasized the importance of individualized treatment.

CONCLUSION

In summary, we visualized the cellular distribution and transcriptional differences in normal pituitary and somatotroph PitNETs by ST and scRNA-seq for the first time. This study provides a strong theoretical foundation to comprehensively understand the crucial mechanisms involved in tumour progression and develop new strategies to treat somatotroph PitNETs.

KEY POINTS

The first-ever visualization of cellular distributions in normal and tumor pituitary tissues. The inter- and intra-tumoral transcriptomic heterogeneity of somatotroph PitNETs was comprehensively revealed. Identification of potential protumor factors and critical signaling pathways, opening new avenues for therapeutic intervention.

Spatial mapping of the HCC landscape identifies unique intratumoral perivascular-immune neighborhoods

BACKGROUND

HCC develops in the context of chronic inflammation; however, the opposing roles the immune system plays in both the development and control of tumors are not fully understood. Mapping immune cell interactions across the distinct tissue regions could provide greater insight into the role individual immune populations have within tumors.

METHODS

A 39-parameter imaging mass cytometry panel was optimized with markers targeting immune cells, stromal cells, endothelial cells, hepatocytes, and tumor cells. We mapped the immune landscape of tumor, invasive margin, and adjacent nontumor regions across 16 resected tumors comprising 144 regions of interest. X-shift clustering and manual gating were used to characterize cell subsets, and Spectre quantified the spatial environment to identify cellular neighborhoods. Ligand-receptor communication was quantified on 2 single-cell RNA-sequencing data sets and 1 spatial transcriptomic data set.

RESULTS

We show immune cell densities remain largely consistent across these 3 regions, except for subsets of monocyte-derived macrophages, which are enriched within the tumors. Mapping cellular interactions across these regions in an unbiased manner identifies immune neighborhoods comprised of tissue-resident T cells, dendritic cells, and various macrophage populations around perivascular spaces. Importantly, we identify multiple immune cells within these neighborhoods interacting with VEGFA+ perivascular macrophages. VEGFA was further identified as a ligand for communication between perivascular macrophages and CD34+ endothelial cells.

CONCLUSIONS

Immune cell neighborhood interactions, but not cell densities, differ between intratumoral and adjacent nontumor regions in HCC. Unique intratumoral immune neighborhoods around the perivascular space point to an altered landscape within tumors. Enrichment of VEGFA+ perivascular macrophages within these tumors could play a key role in angiogenesis and vascular permeability.

Cancer metabolic reprogramming and precision medicine-current perspective

Despite the advanced technologies and global attention on cancer treatment strategies, cancer continues to claim lives and adversely affects socio-economic development. Although combination therapies were anticipated to eradicate this disease, the resilient and restorative nature of cancers allows them to proliferate at the expense of host immune cells energetically. This proliferation is driven by metabolic profiles specific to the cancer type and the patient. An emerging field is exploring the metabolic reprogramming (MR) of cancers to predict effective treatments. This mini-review discusses the recent advancements in cancer MR that have contributed to predictive, preventive, and precision medicine. Current perspectives on the mechanisms of various cancer types and prospects for MR and personalized cancer medicine are essential for optimizing metabolic outputs necessary for personalized treatments.

Evaluation of a three-gene methylation model for correlating lymph node metastasis in postoperative early gastric cancer adjacent samples

Background

Lymph node metastasis (LNM) has a profound impact on the treatment and prognosis of early gastric cancer (EGC), yet the existing evaluation methods lack accuracy. Recent research has underscored the role of precancerous lesions in tumor progression and metastasis. The objective of this study was to utilize the previously developed EGC LNM prediction model to further validate and extend the analysis in paired adjacent tissue samples.

Methods

We evaluated the model in a monocentric study using Methylight, a methylation-specific PCR technique, on postoperative fresh-frozen EGC samples (n = 129) and paired adjacent tissue samples (n = 129).

Results

The three-gene methylation model demonstrated remarkable efficacy in both EGC and adjacent tissues. The model demonstrated excellent performance, with areas under the curve (AUC) of 0.85 and 0.82, specificities of 85.1% and 80.5%, sensitivities of 83.3% and 73.8%, and accuracies of 84.5% and 78.3%, respectively. It is noteworthy that the model demonstrated superior performance compared to computed tomography (CT) imaging in the adjacent tissue group, with an area under the curve (AUC) of 0.86 compared to 0.64 (p < 0.001). Furthermore, the model demonstrated superior diagnostic capability in these adjacent tissues (AUC = 0.82) compared to traditional clinicopathological features, including ulceration (AUC = 0.65), invasional depth (AUC = 0.66), and lymphovascular invasion (AUC = 0.69). Additionally, it surpassed traditional models based on these features (AUC = 0.77).

Conclusion

The three-gene methylation prediction model for EGC LNM is highly effective in both cancerous and adjacent tissue samples in a postoperative setting, providing reliable diagnostic information. This extends its clinical utility, particularly when tumor samples are scarce, making it a valuable tool for evaluating LNM status and assisting in treatment planning.

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.