Single-cell atlas of tumor cell evolution in response to therapy in hepatocellular carcinoma and intrahepatic cholangiocarcinoma

DKK1+ tumor cells inhibited the infiltration of CCL19+ fibroblasts and plasma cells contributing to worse immunotherapy response in hepatocellular carcinoma

Intra-tumor immune infiltration plays a pivotal role in the interaction with tumor cells in hepatocellular carcinoma (HCC). However, its phenotype and related spatial structure remained elusive. To address these limitations, we conducted a comprehensive study combining spatial data (38,191 spots from eight samples) and single-cell data (56,022 cells from 20 samples). Our analysis revealed two distinct infiltration patterns: immune exclusion and immune activation. Plasma cells emerged as the primary cell type within intra-tumor immune clusters. Notably, we observed the co-location of CCL19+ fibroblasts with plasma cells, which secrete chemokines and promote T-cell activation and leukocyte migration. Conversely, in immune-exclusion samples, this co-location was primarily observed in the adjacent normal area. This co-localization correlated with T cell infiltration and the formation of tertiary lymphoid structures, validated by multiplex immunofluorescence conducted on twenty HCC samples. Both CCL19+ fibroblasts and plasma cells were associated with favorable survival outcomes. In an immunotherapy cohort, HCC patients who responded favorably exhibited higher infiltration of CCL19+ fibroblasts and plasma cells. Additionally, we observed the accumulation of DKK1+ tumor cells within the tumor area in immune-exclusion samples, particularly at the tumor boundary, which inhibited the infiltration of CCL19+ fibroblasts and plasma cells into the tumor area. Furthermore, in immune-exclusion samples, the SPP1 signaling pathway demonstrated the highest activity in communication between tumor and immune clusters, and CCL19-CCR7 played a pivotal role in the self-communication of immune clusters. This study elucidates immune exclusion and immune activation patterns in HCC and identifies relevant factors contributing to immune resistance.

Single-cell RNA sequencing reveals anti-tumor potency of CD56+ NK cells and CD8+ T cells in humanized mice via PD-1 and TIGIT co-targeting

In solid tumors, the exhaustion of natural killer (NK) cells and cytotoxic T cells in the immunosuppressive tumor microenvironment poses challenges for effective tumor control. Conventional humanized mouse models of hepatocellular carcinoma patient-derived xenografts (HCC-PDX) encounter limitations in NK cell infiltration, hindering studies on NK cell immunobiology. Here, we introduce an improved humanized mouse model with restored NK cell reconstitution and infiltration in HCC-PDX, coupled with single-cell RNA sequencing (scRNA-seq) to identify potential anti-HCC treatments. A single administration of adeno-associated virus carrying human interleukin-15 reinstated persistent NK cell reconstitution and infiltration in HCC-PDX in humanized mice. scRNA-seq revealed NK cell and T cell subpopulations with heightened PDCD1 and TIGIT levels. Notably, combination therapy with anti-PD-1 and anti-TIGIT antibodies alleviated HCC burden in humanized mice, demonstrating NK cell-dependent efficacy. Bulk-RNA sequencing analysis also revealed significant alterations in the tumor transcriptome that may contribute to further resistance after combination therapy, warranting further investigations. As an emerging strategy, ongoing clinical trials with anti-PD-1 and anti-TIGIT antibodies provide limited data. The improved humanized mouse HCC-PDX model not only sheds light on the pivotal role of NK cells but also serves as a robust platform for evaluating safety and anti-tumor efficacy of combination therapies and other potential regimens, complementing clinical insights.

Effect of fibroblast heterogeneity on prognosis and drug resistance in high-grade serous ovarian cancer

Tumor heterogeneity is associated with poor prognosis and drug resistance, leading to therapeutic failure. Here, we used tumor evolution analysis to determine the intra- and intertumoral heterogeneity of high-grade serous ovarian cancer (HGSOC) and analyze the correlation between tumor heterogeneity and prognosis, as well as chemotherapy response, through single-cell and spatial transcriptomic analysis. We collected and curated 28 HGSOC patients' single-cell transcriptomic data from five datasets. Then, we developed a novel text-mining-based machine-learning approach to deconstruct the evolutionary patterns of tumor cell functions. We then identified key tumor-related genes within different evolutionary branches, characterized the microenvironmental cell compositions that various functional tumor cells depend on, and analyzed the intra- and intertumoral heterogeneity as well as the tumor microenvironments. These analyses were conducted in relation to the prognosis and chemotherapy response in HGSOC patients. We validated our findings in two spatial and seven bulk transcriptomic datasets (total: 1,030 patients). Using transcriptomic clusters as proxies for functional clonality, we identified a significant increase in tumor cell state heterogeneity that was strongly correlated with patient prognosis and treatment response. Furthermore, increased intra- and intertumoral functional clonality was associated with the characteristics of cancer-associated fibroblasts (CAFs). The spatial proximity between CXCL12-positive CAFs and tumor cells, mediated through the CXCL12/CXCR4 interaction, was highly positively correlated with poor prognosis and chemotherapy resistance in HGSOC. Finally, we constructed a panel of 24 genes through statistical modeling that correlate with CXCL12-positive fibroblasts and can predict both prognosis and the response to chemotherapy in HGSOC patients. Our study offers insights into the collective behavior of tumor cell communities in HGSOC, as well as potential drivers of tumor evolution in response to therapy. There was a strong association between CXCL12-positive fibroblasts and tumor progression, as well as treatment outcomes.

Cancer-associated fibroblasts derived fibronectin extra domain A promotes sorafenib resistance in hepatocellular carcinoma cells by activating SHMT1

Resistance to sorafenib, an effective first-line treatment for advanced hepatocellular carcinoma (HCC), greatly compromised the prognosis of patients. The extracellular matrix is one of the most abundant components of the tumor microenvironment. Beyond acting as a physical barrier, it remains unclear whether cell interactions and signal transduction mediated by the extracellular matrix contribute to sorafenib resistance. With the analysis of primary HCC organoid RNA-seq data combined with in vivo and in vitro experiments validation, we discovered that fibronectin extra domain A (FN-EDA) derived from cancer-associated fibroblasts played a critical role in sorafenib resistance. Mechanistically, FN-EDA stimulates the up-regulation of the key one-carbon metabolism enzyme SHMT1 in HCC cells via the TLR4/NF-κB signaling pathway, thereby countering the oxidative stress induced by sorafenib. Moreover, we reinforced the clinical significance of our discoveries by conducting in vivo assays with an immunodeficiency subcutaneous xenograft tumor model, which was established using primary cancer-associated fibroblasts derived from clinical HCC tissues, and through the analysis of HCC samples obtained from The Cancer Genome Atlas (TCGA) database. Our findings suggest that targeting the FN-EDA/SHMT1 pathway could be a potential strategy to improve sorafenib responsiveness in HCC patients.

Supercontinuum-tailoring multicolor imaging reveals spatiotemporal dynamics of heterogeneous tumor evolution

Tumor heterogeneity and tumor evolution contribute to cancer treatment failure. To understand how selective pressures drive heterogeneous tumor evolution, it would be useful to image multiple important components and tumor subclones in vivo. We propose a supercontinuum-tailoring two-photon microscope (SCT-TPM) and realize simultaneous observation of nine fluorophores with a single light beam, breaking through the 'color barrier' of intravital two-photon fluorescence imaging. It achieves excitation multiplexing only by modulating the phase of fiber supercontinuum (SC), allowing to capture rapid events of multiple targets with maintaining precise spatial alignment. We employ SCT-TPM to visualize the spatiotemporal dynamics of heterogeneous tumor evolution under host immune surveillance, particularly the behaviors and interactions of six tumor subclones, immune cells and vascular network, and thus infer the trajectories of tumor progression and clonal competition. SCT-TPM opens up the possibility of tumor lineage tracking and mechanism exploration in living biological systems.

Identification of molecular subtypes based on bile acid metabolism in cholangiocarcinoma

BACKGROUND

Cholangiocarcinoma is a highly heterogeneous tumor with bile acid metabolism involving in its development. The aim of this study was to characterize bile acid metabolism and identify specific subtypes to better stratify cholangiocarcinoma patients for individualized treatment and prognostic assessment.

METHODS

A total of 30 bile acids were quantified using the ultra-performance liquid chromatography tandem mass spectrometry. Using Consensus clustering, the molecular subtypes related to bile acid metabolism were identified. The prognosis, clinicopathologic characteristics, immune landscape, and therapeutic response were compared between these subtypes. The single-cell RNA sequencing (scRNA-seq) analysis and preliminary cell experiment were also conducted to verify our findings.

RESULTS

The altered bile acid profile and genetic variation of bile acid metabolism-related genes in cholangiocarcinoma were demonstrated. The cholangiocarcinoma was categorized into bile acid metabolism-active and -inactive subtypes with different prognoses, clinicopathologic characteristics, tumor microenvironments (TME) and therapeutic responses. This categorization was reproducible and predictable. Specifically, the bile acid metabolism-active subtype showed a poor prognosis with an immunosuppressive microenvironment and an inactive response to immunotherapy, while the bile acid metabolism-inactive subtype showed the opposite characteristics. Moreover, the scRNA-seq revealed that immunotherapy altered bile acid metabolism in TME of cholangiocarcinoma. Finally, a prognostic signature related to bile acid metabolism was developed, which exhibited strong power for prognostic assessment of cholangiocarcinoma. Consistently, these results were verified by immunohistochemistry, cell proliferation, migration, and apoptosis assays.

CONCLUSION

In conclusion, a novel cholangiocarcinoma classification based on bile acid metabolism was established. This classification was significant for the estimation of TME and prognosis.

CD34 as a potential prognostic indicator for camrelizumab response in advanced non-small-cell lung cancer: insights from digital spatial profiling

Background

Given that only a small subset of patients with advanced non-small-cell lung cancer (aNSCLC) benefit from immune checkpoint inhibitors (ICIs), the effectiveness of ICIs is often compromised by the complex interplay within the tumor microenvironment (TME).

Objectives

To identify predictive biomarkers associated with ICI resistance at a multi-omics spatial level.

Design

A total of eight aNSCLC patients who received first-line anti-programmed cell death protein-1 (PD-1) monoclonal antibody camrelizumab at Shandong Cancer Hospital and Institute between 2021 and 2022 were included in the discovery cohort. An additional validation cohort of 45 samples from camrelizumab-treated aNSCLC patients was also enrolled.

Methods

NanoString GeoMx® digital spatial profiling was conducted at the transcriptomic and proteomic level within pan-cytokeratin (panCK+), CD45+, and CD68+ compartments. For validation, multiplex immunofluorescence (mIF) staining was performed.

Results

Distinct spatial expression patterns and levels of immune infiltration were observed between tumor and leukocyte compartments. Higher CD34 expression in the macrophage compartment correlated with poorer prognosis and response to camrelizumab (p < 0.05). mIF validation confirmed the association of elevated CD34 expression level with reduced progression-free survival (PFS; hazard ratio (HR) = 5.011, 95% confidence interval: 1.057-23.752, p = 0.042), outperforming traditional tumor markers in predictive accuracy.

Conclusion

Our findings identify CD34 as a novel spatial biomarker for anti-PD-1 therapy efficacy, potentially guiding the selection of aNSCLC patients who are more likely to benefit from ICI treatment.

Trial registration

ChiCTR2000040416.

Characterization of cell states in biliary tract cancers identifies mechanisms of therapeutic resistance in a phase II trial of DKN-01/nivolumab

Biliary tract cancers demonstrate profound therapeutic resistance, and broadly effective therapies for refractory disease are lacking. We conducted a single-arm, second-line phase II trial combining DKN-01, a humanized monoclonal antibody targeting Dickkopf-1 (DKK-1), and nivolumab to treat patients with advanced biliary tract cancer (NCT04057365). No objective responses were seen. To identify mechanisms of treatment failure, we analyzed paired pre-treatment and on-treatment biopsies using scRNA-seq and constructed a detailed molecular classification of malignant and immune cells. We annotated five biliary tract cancer malignant cell states: classical, basal, mesenchymal, neural-like, and endothelial-like. Neural-like and endothelial-like states, which drive therapeutic resistance in other cancers, have not previously been described in BTC. Malignant cell states co-varied with distinct immune cell states, revealing diverse mechanisms of myeloid and T-cell mediated immune suppression, including M2 myeloid and terminally exhausted T cell programs that were induced by DKN-01/nivolumab. Here, we provide the first systematic classification of functionally annotated cell states in biliary tract cancer and provide new insight into resistance mechanisms to an immunotherapy combination that can inform the next generation of trials.

HCC spatial transcriptomic profiling reveals significant and potentially targetable cancer-endothelial interactions

BACKGROUND

HCC is a highly vascular tumor, and many effective drug regimens target the tumor blood vessels. Prior bulk HCC subtyping data used bulk transcriptomes, which contained a mixture of parenchymal and stromal contributions.

METHODS

We utilized computational deconvolution and cell-cell interaction analyses to cell type-specific (tumor-enriched and vessel-enriched) spatial transcriptomic data collected from 41 resected HCC tissue specimens.

RESULTS

We report that the prior Hoshida bulk transcriptional subtyping schema is driven largely by an endothelial fraction, show an alternative tumor-specific schema has potential prognostic value, and use spatially paired ligand-receptor analyses to identify known and novel (LGALS9 tumor-HAVCR2 vessel) signaling relationships that drive HCC biology in a subtype-specific and potentially targetable manner.

CONCLUSIONS

Our study leverages spatial gene expression profiling technologies to dissect HCC heterogeneity and identify heterogeneous signaling relationships between cancer cells and their endothelial cells. Future validation and expansion of these findings may validate novel cancer-endothelial cell interactions and related drug targets.

Single-cell transcriptome analysis reveals evolving tumour microenvironment induced by immunochemotherapy in nasopharyngeal carcinoma

BACKGROUND

Combinatory therapeutic strategy containing immunochemotherapy as part of induction therapy components is one of the current trends in the treatment of high-risk metastatic locally advanced nasopharyngeal carcinoma (NPC). However, the mechanism underlying the heterogeneity of response at the single-cell level has not been underexplored.

METHODS

18 bulks and 11 single-cell RNA sequencing from paired before-treatment and on-treatment samples in patients with treatment-naive high-risk metastatic locally advanced NPCs were obtained. Following quality control, a total of 87 191 cells were included in the subsequence bioinformatics analysis.

RESULTS

Immunochemotherapy was associated with on-treatment tumour microenvironment (TME) remodelling, including upregulation of anti-TMEs signatures, downregulation of pro-TMEs signatures, reversing CD8+ T exhaustion, and repolarizing proinflammatory TAMs. For the patients achieving a complete response, the cytotoxic activity of CD8+ T cells was stimulated and more interferon-gamma was provided, which would be the key for TAMs proinflammatory repolarization and eventually promote the CD8+ T cells maturation in turn. Among patients who did not reach complete response, differentiation and hypoxia signatures for endothelial cells were elevated after therapy. These patients exhibited higher levels of immune checkpoint genes in malignant cells at the baseline (before treatment), and decreased tumour antigen presentation activity, which may underlie the resistance mechanism to therapy.

CONCLUSIONS

This study pictures a map of TME modulation following immunochemotherapy-based combination induction therapy and provides potential future approaches.

HIGHLIGHTS

Immunochemotherapy remodeled T cell phenotypes. For the patients achieving complete response, more interferon gamma was provided by CD8+ T cells after therapy, which would be the key for TAMs pro-inflammatory repolarization and eventually promote the CD8+ T cells maturation in turns. Among patients who did not reach complete response, malignant cells exhibited higher level of immune checkpoint genes before therapy, and decreased tumor antigen presentation activity, which may underlie the resistance mechanism to therapy.

Spatial analysis reveals targetable macrophage-mediated mechanisms of immune evasion in hepatocellular carcinoma minimal residual disease

Hepatocellular carcinoma (HCC) frequently recurs from minimal residual disease (MRD), which persists after therapy. Here, we identified mechanisms of persistence of residual tumor cells using post-chemoembolization human HCC (n = 108 patients, 1.07 million cells) and a transgenic mouse model of MRD. Through single-cell high-plex cytometric imaging, we identified a spatial neighborhood within which PD-L1 + M2-like macrophages interact with stem-like tumor cells, correlating with CD8+ T cell exhaustion and poor survival. Further, through spatial transcriptomics of residual HCC, we showed that macrophage-derived TGFβ1 mediates the persistence of stem-like tumor cells. Last, we demonstrate that combined blockade of Pdl1 and Tgfβ excluded immunosuppressive macrophages, recruited activated CD8+ T cells and eliminated residual stem-like tumor cells in two mouse models: a transgenic model of MRD and a syngeneic orthotopic model of doxorubicin-resistant HCC. Thus, our spatial analyses reveal that PD-L1+ macrophages sustain MRD by activating the TGFβ pathway in stem-like cancer cells and targeting this interaction may prevent HCC recurrence from MRD.

scCrab: A Reference-Guided Cancer Cell Identification Method based on Bayesian Neural Networks

Cancer is a significant global public health concern, where early detection can greatly enhance curative outcomes. Therefore, the identification of cancer cells holds significant importance as the primary method for cancer diagnosis. The advancement of single-cell RNA sequencing (scRNA-seq) technology has made it possible to address the problem of cancer cell identification at the single-cell level more efficiently with computational methods, as opposed to the time-consuming and less reproducible manual identification methods. However, existing computational methods have shown suboptimal identification performance and a lack of capability to incorporate external reference data as prior information. Here, we propose scCrab, a reference-guided automatic cancer cell identification method, which performs ensemble learning based on a Bayesian neural network (BNN) with multi-head self-attention mechanisms and a linear regression model. Through a series of experiments on various datasets, we systematically validated the superior performance of scCrab in both intra- and inter-dataset predictions. Besides, we demonstrated the robustness of scCrab to dropout rate and sample size, and conducted ablation experiments to investigate the contributions of each component in scCrab. Furthermore, as a dedicated model for cancer cell identification, scCrab effectively captures cancer-related biological significance during the identification process.

Morphomolecular Pathology and Genomic Insights into the Cells of Origin of Cholangiocarcinoma and Combined Hepatocellular-Cholangiocarcinoma

Cholangiocarcinomas are a highly heterogeneous group of malignancies that, despite recent progress in the understanding of their molecular pathogenesis and clinical management, continue to pose a major challenge to public health. The traditional view posits that cholangiocarcinomas derive from the neoplastic transformation of cholangiocytes lining the biliary tree. However, increasing genetic and experimental evidence has recently pointed to a more complex, and nuanced, scenario for the potential cell of origin of cholangiocarcinomas. Hepatocytes as well as hepatic stem/progenitor cells are being considered as additional potential sources, depending on microenvironmental contexts, including liver injury. The hypothesis of potentially diverse cells of origin for cholangiocarcinoma, albeit controversial, is certainly not surprising given the plasticity of the cells populating the liver as well as the existence of liver cancer subtypes with mixed histologic and molecular features. This review carefully examines the current pathologic, genomic, and experimental evidence supporting the existence of multiple cells of origin of liver and biliary tract cancers, with particular focus on cholangiocarcinoma and combined hepatocellular-cholangiocarcinoma.

RIG-I is an intracellular checkpoint that limits CD8+ T-cell antitumour immunity

Retinoic acid-inducible gene I (RIG-I) is a pattern recognition receptor involved in innate immunity, but its role in adaptive immunity, specifically in the context of CD8+ T-cell antitumour immunity, remains unclear. Here, we demonstrate that RIG-I is upregulated in tumour-infiltrating CD8+ T cells, where it functions as an intracellular checkpoint to negatively regulate CD8+ T-cell function and limit antitumour immunity. Mechanistically, the upregulation of RIG-I in CD8+ T cells is induced by activated T cells, and directly inhibits the AKT/glycolysis signalling pathway. In addition, knocking out RIG-I enhances the efficacy of adoptively transferred T cells against solid tumours, and inhibiting RIG-I enhances the response to PD-1 blockade. Overall, our study identifies RIG-I as an intracellular checkpoint and a potential target for alleviating inhibitory constraints on T cells in cancer immunotherapy, either alone or in combination with an immune checkpoint inhibitor.

Integrated analysis of tumor and adjacent non-tumor proteomic data reveals SERPINH1 as a recurrence biomarker and drug target in hepatocellular carcinoma

The high rate of postoperative recurrence contributes to the poor outcome in hepatocellular carcinoma (HCC), and effective strategies for managing recurrence are currently lacking. Based on seven pairs of tumors and non-tumor adjacent tissues (NATs) proteomic datasets across five cancer types, this study systematically investigates the stratified and therapeutic value of tumors and NATs for tumor recurrence. NATs exhibited stable and irreplaceable independent prognostic capabilities for recurrence, complementing clinical indicators and tumor characteristics. In comparison to tumor tissues, NATs exhibit higher enrichment levels of recurrence-related proteins in pathways such as immunity, extracellular matrix, and angiogenesis. Taking HCC as an example, we identified SERPINH1 as a recurrent biomarker with drug-targeting potential that applied to both tumors and NATs and then validated them through independent immunohistochemistry cohorts and animal experiments. Patients with high SERPINH1 expression in both tumors and NATs have the highest 5-year recurrence rates, even among clinically low recurrence risk groups. Targeting SERPINH1 can effectively delay tumor occurrence and progression. This study highlights the significant importance of NATs in recurrence prediction and postoperative management, proposing a recurrence management strategy that focuses on both tumors and NATs. SERPINH1 emerges as a valuable biomarker and drug target for addressing postoperative recurrence in HCC.

HKDC1 promotes liver cancer stemness under hypoxia through stabilizing β-catenin

BACKGROUND AND AIMS

Hexokinases (HKs), a group of enzymes catalyzing the first step of glycolysis, have been shown to play important roles in liver metabolism and tumorigenesis. Our recent studies identified hexokinase domain containing 1 (HKDC1) as a top candidate associated with liver cancer metastasis. We aimed to compare its cell-type specificity with other HKs upregulated in liver cancer and investigate the molecular mechanisms underlying its involvement in liver cancer metastasis.

APPROACH AND RESULTS

We found that, compared to HK1 and HK2, the other 2 commonly upregulated HKs in liver cancer, HKDC1 was most strongly associated with the metastasis potential of tumors and organoids derived from 2 liver cancer mouse models we previously established. RNA in situ hybridization and single-cell RNA-seq analysis revealed that HKDC1 was specifically upregulated in malignant cells in HCC and cholangiocarcinoma patient tumors, whereas HK1 and HK2 were widespread across various tumor microenvironment lineages. An unbiased metabolomic profiling demonstrated that HKDC1 overexpression in HCC cells led to metabolic alterations distinct from those from HK1 and HK2 overexpression, with HKDC1 particularly impacting the tricarboxylic acid cycle. HKDC1 was prometastatic in HCC orthotopic and tail vein injection mouse models. Molecularly, HKDC1 was induced by hypoxia and bound to glycogen synthase kinase 3β to stabilize β-catenin, leading to enhanced stemness of HCC cells.

CONCLUSIONS

Overall, our findings underscore HKDC1 as a prometastatic HK specifically expressed in the malignant compartment of primary liver tumors, thereby providing a mechanistic basis for targeting this enzyme in advanced liver cancer.

Effect of Sortilin1 on promoting angiogenesis and systemic metastasis in hepatocellular carcinoma via the Notch signaling pathway and CD133

Hepatocellular carcinoma (HCC) is known to be lethal disease. However, its prognosis remains poor, primarily because the precise oncogenic mechanisms underlying HCC progression remain elusive, thus hampering effective treatment. Here, we aimed to identify the potential oncogenes in HCC and elucidate the underlying mechanisms of their action. To identify potential candidate genes, an integrative analysis of eight publicly available genomic datasets was performed, and the functional implications of the identified genes were assessed in vitro and in vivo. Sortilin 1 (SORT1) was identified as a potential candidate oncogene in HCC, and its overexpression in HCC cells was confirmed by analyzing spatial transcriptomic and single-cell data. Silencing SORT1 in Huh-7 and Hep3B cells significantly reduced HCC progression in vitro and in vivo. Functional analyses of oncogenic pathways revealed that SORT1 expression regulated the Notch signaling pathway activation and CD133 expression. Furthermore, analysis of epigenetic regulation of the candidate gene and its clinical implications using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA LIHC) and our HCC cohort (AJOU_HCC cohort) data demonstrated an inverse correlation between the methylation status of the SORT1 promoter region, specifically at the cg16988986 site, and SORT1 mRNA expression, indicating the epigenetic regulation of SORT1 in HCC. In addition, the distinct methylation status of cg16988986 was significantly associated with patient survival. In conclusion, SORT1 plays a pivotal role in HCC by activating the Notch signaling pathway and increasing CD133 expression. These findings suggest SORT1 as a promising therapeutic target for HCC.

Single-cell transcriptomics reveals tumor microenvironment remodeling in hepatocellular carcinoma with varying tumor subclonal complexity

Introduction

The complexity of tumor cell subclonal structure has been extensively investigated in hepatocellular carcinoma. However, the role of subclonal complexity in reshaping the tumor microenvironment (TME) remains poorly understood.

Methods

We integrated single-cell transcriptome sequencing data from four independent HCC cohorts, involving 30 samples, to decode the associations between tumor subclonal complexity and the TME. We proposed a robust metric to accurately quantify the degree of subclonal complexity for each sample based on discrete copy number variations (CNVs) profiles.

Results

We found that tumor cells in the high-complexity group originated from the cell lineage with FGB overexpression and exhibited high levels of transcription factors associated with poor survival. In contrast, tumor cells in low-complexity patients showed activation of more hallmark signaling pathways, more active cell-cell communications within the TME and a higher immune activation status. Additionally, cytokines signaling activity analysis suggested a link between HMGB1 expressed by a specific endothelial subtype and T cell proliferation.

Discussion

Our study sheds light on the intricate relationship between the complexity of subclonal structure and the TME, offering novel insights into potential therapeutic targets for HCC.

Secreted PTEN binds PLXDC2 on macrophages to drive antitumor immunity and tumor suppression

Loss of phosphatase and tensin homolog (PTEN) has been linked to an immunosuppressive tumor microenvironment, but its underlying mechanisms remain largely enigmatic. Here, we report that PTEN can be secreted by the transmembrane emp24 domain-containing protein 10 (TMED10)-channeled protein secretion pathway. Inhibiting PTEN secretion from tumor cells contributes to immunosuppression and impairs the tumor-suppressive role of PTEN, while intratumoral injection of PTEN protein promotes antitumor immunity and suppresses tumor growth in mice. Mechanistically, extracellular PTEN binds to the plexin domain-containing protein 2 (PLXDC2) on macrophages, triggering subsequent activation of JAK2-STAT1 signaling, which switches tumor-associated macrophages (TAMs) from the immunosuppressive to inflammatory phenotype, leading to enhanced activation of CD8+ T and natural killer cells. Importantly, PTEN treatment also enhances the therapeutic efficacy of anti-PD-1 treatment in mice and reverses the immune-suppressive phenotype of patient-derived primary TAMs. These data identify a cytokine-like role of PTEN in immune activation and tumor suppression and demonstrate the therapeutic potential for extracellular administration of PTEN in cancer immunotherapy.

Screening and molecular docking verification of feature genes related to phospholipid metabolism in hepatocarcinoma caused by hepatitis B

BACKGROUND

The progression of tumours is related to abnormal phospholipid metabolism. This study is anticipated to present a fresh perspective for disease therapy targets of hepatocarcinoma caused by hepatitis B virus in the future by screening feature genes related to phospholipid metabolism.

METHODS

This study analysed GSE121248 to pinpoint differentially expressed genes (DEGs). By examining the overlap between the metabolism-related genes and DEGs, the research focused on the genes involved in phospholipid metabolism. To find feature genes, functional enrichment studies were carried out and a network diagram was proposed. These findings were validated via data base of The Cancer Genome Atlas (TCGA). Further analyses included immune infiltration studies and metabolomics. Finally, the relationships between differentially abundant metabolites and feature genes were confirmed by molecular docking, providing a thorough comprehension of the molecular mechanisms.

RESULTS

The seven genes with the highest degree of connection (PTGS2, IGF1, SPP1, BCHE, NR1I2, NAMPT, and FABP1) were identified as feature genes. In the TCGA database, the seven feature genes also had certain diagnostic efficiency. Immune infiltration analysis revealed that feature genes regulate the infiltration of various immune cells. Metabolomics successfully identified the different metabolites of the phospholipid metabolism pathway between patients and normal individuals. The docking study indicated that different metabolites may play essential roles in causing disease by targeting feature genes.

CONCLUSIONS

In this study, for the first time, it reveals the possible involvement of genes linked to phospholipid metabolism-related genes using bioinformatics analysis. Identifying genes and probable therapeutic targets could provide clues for the further treatment of disease.

DNA methylation and gene expression profiling reveal potential association of retinol metabolism related genes with hepatocellular carcinoma development

Background

Aberrant DNA methylation patterns play a critical role in the development of hepatocellular carcinoma (HCC). However, the molecular mechanisms associated with these aberrantly methylated genes remain unclear. This study aimed to comprehensively investigate the methylation-driven gene expression alterations in HCC using a multi-omics dataset.

Methods

Whole genome bisulfite sequencing (WGBS) and RNA sequencing (RNA-seq) techniques were used to assess the methylation and gene expression profiles of HCC tissues (HCCs) and normal adjacent tissues (NATs). The candidate genes' potential function was further investigated using single-cell RNA sequencing (scRNA seq) data.

Results

We observed widespread hypomethylation in HCCs compared to NATs. Methylation levels in distinct genomic regions exhibited significant differences between HCCs and NATs. We identified 247,632 differentially methylated regions (DMRs) and 4,926 differentially expressed genes (DEGs) between HCCs and NATs. Integrated analysis of DNA methylation and RNA-seq data identified 987 methylation-driven candidate genes, with 970 showing upregulation and 17 showing downregulation. Four genes involved in the retinol metabolic pathway, namely ADH1A, CYP2A6, CYP2C8, and CYP2C19, were identified as hyper-downregulated genes. Their expression levels could stratify HCCs into three subgroups with distinct survival outcomes, immune cell infiltration, and tumor microenvironments. Validation of these findings in an independent dataset yielded similar outcomes, confirming the high concordance and potential prognostic value of these genes. ScRNA seq data revealed the low expression of these genes in immune cells, emphasizing their role in promoting malignant cell proliferation and migration. In conclusion, this study provides insights into the molecular characteristics of HCC, revealing the involvement of retinol metabolism-related genes in the development and progression of HCC. These findings have implications for HCC diagnosis, prognosis prediction, and the development of therapeutic targets.

Artificial intelligence applied to 'omics data in liver disease: towards a personalised approach for diagnosis, prognosis and treatment

Advancements in omics technologies and artificial intelligence (AI) methodologies are fuelling our progress towards personalised diagnosis, prognosis and treatment strategies in hepatology. This review provides a comprehensive overview of the current landscape of AI methods used for analysis of omics data in liver diseases. We present an overview of the prevalence of different omics levels across various liver diseases, as well as categorise the AI methodology used across the studies. Specifically, we highlight the predominance of transcriptomic and genomic profiling and the relatively sparse exploration of other levels such as the proteome and methylome, which represent untapped potential for novel insights. Publicly available database initiatives such as The Cancer Genome Atlas and The International Cancer Genome Consortium have paved the way for advancements in the diagnosis and treatment of hepatocellular carcinoma. However, the same availability of large omics datasets remains limited for other liver diseases. Furthermore, the application of sophisticated AI methods to handle the complexities of multiomics datasets requires substantial data to train and validate the models and faces challenges in achieving bias-free results with clinical utility. Strategies to address the paucity of data and capitalise on opportunities are discussed. Given the substantial global burden of chronic liver diseases, it is imperative that multicentre collaborations be established to generate large-scale omics data for early disease recognition and intervention. Exploring advanced AI methods is also necessary to maximise the potential of these datasets and improve early detection and personalised treatment strategies.

Building a learnable universal coordinate system for single-cell atlas with a joint-VAE model

A universal coordinate system that can ensemble the huge number of cells and capture their heterogeneities is of vital importance for constructing large-scale cell atlases as references for molecular and cellular studies. Studies have shown that cells exhibit multifaceted heterogeneities in their transcriptomic features at multiple resolutions. This nature of complexity makes it hard to design a fixed coordinate system through a combination of known features. It is desirable to build a learnable universal coordinate model that can capture major heterogeneities and serve as a controlled generative model for data augmentation. We developed UniCoord, a specially-tuned joint-VAE model to represent single-cell transcriptomic data in a lower-dimensional latent space with high interpretability. Each latent dimension can represent either discrete or continuous feature, and either supervised by prior knowledge or unsupervised. The latent dimensions can be easily reconfigured to generate pseudo transcriptomic profiles with desired properties. UniCoord can also be used as a pre-trained model to analyze new data with unseen cell types and thus can serve as a feasible framework for cell annotation and comparison. UniCoord provides a prototype for a learnable universal coordinate framework to enable better analysis and generation of cells with highly orchestrated functions and heterogeneities.

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.

DDX5 deficiency drives non-canonical NF-κB activation and NRF2 expression, influencing sorafenib response and hepatocellular carcinoma progression

In advanced hepatocellular carcinoma (HCC), RNA helicase DDX5 regulates the Wnt/β-catenin-ferroptosis axis, influencing the efficacy of the multi-tyrosine kinase inhibitor (mTKI) sorafenib. DDX5 inhibits Wnt/β-catenin signaling, preventing sorafenib-induced ferroptosis escape. Sorafenib/mTKIs reduce DDX5 expression, correlating with poor patient survival post-sorafenib treatment. Notably, DDX5-knockout in HCC cells activates Wnt/β-catenin signaling persistently. Herein, we investigate the mechanistic impact of Wnt/β-catenin activation resulting from DDX5 downregulation in the progression and treatment of HCC. RNAseq analyses identified shared genes repressed by DDX5 and upregulated by sorafenib, including Wnt signaling genes, NF-κB-inducing kinase (NIK) essential for non-canonical NF-κB (p52/RelB) activation, and cytoprotective transcription factor NRF2. We demonstrate, Wnt/β-catenin activation induced NIK transcription, leading to non-canonical NF-κB activation, which subsequently mediated NRF2 transcription. Additionally, DDX5 deficiency extended NRF2 protein half-life by inactivating KEAP1 through p62/SQSTM1 stabilization. In a preclinical HCC mouse model, NRF2 knockdown or DDX5 overexpression restricted tumor growth upon sorafenib treatment, via induction of ferroptosis. Importantly, DDX5-knockout HCC cells exhibited elevated expression of Wnt signaling genes, NIK, p52/RelB, and NRF2-regulated genes, regardless of sorafenib treatment. Transcriptomic analyses of HCCs from TCGA and the Stelic Animal Model (STAM) of non-alcoholic steatohepatitis revealed elevated expression of these interconnected pathways in the context of DDX5 downregulation. In conclusion, DDX5 deficiency triggers Wnt/β-catenin signaling, promoting p52/RelB and NRF2 activation, thereby enabling ferroptosis evasion upon sorafenib treatment. Similarly, independent of sorafenib, DDX5 deficiency in liver tumors enhances activation and gene expression of these interconnected pathways, underscoring the clinical relevance of DDX5 deficiency in HCC progression and therapeutic response.

Overcoming treatment resistance in cholangiocarcinoma: current strategies, challenges, and prospects

Significant advancements in our understanding and clinical treatment of cholangiocarcinoma (CCA) have been achieved over the past 5 years. Groundbreaking studies have illuminated the immune landscape and pathological characteristics of the tumor microenvironment in CCA. The development of immune- and metabolism-based classification systems has enabled a nuanced exploration of the tumor microenvironment and the origins of CCA, facilitating a detailed understanding of tumor progression modulation. Despite these insights, targeted therapies have not yet yielded satisfactory clinical results, highlighting the urgent need for innovative therapeutic strategies. This review delineates the complexity and heterogeneity of CCA, examines the current landscape of therapeutic strategies and clinical trials, and delves into the resistance mechanisms underlying targeted therapies. Finally, from a single-cell and spatial transcriptomic perspective, we address the challenge of therapy resistance, discussing emerging mechanisms and potential strategies to overcome this barrier and enhance treatment efficacy.

Immunosuppression and phenotypic plasticity in an atlas of human hepatocholangiocarcinoma

Background

Hepatocholangiocarcinoma (H-ChC) has the clinicopathological features of both hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA) and is a more aggressive subtype of primary hepatic carcinoma than HCC or iCCA.

Methods

We sequenced 91,112 single-cell transcriptomes from 16 human samples to elucidate the molecular mechanisms underlying the coexistence of HCC and iCCA components in H-ChC.

Results

We observed two molecular subtypes of H-ChC at the whole-transcriptome level (CHP and CIP), where a metabolically active tumour cell subpopulation enriched in CHP was characterized by a cellular pre-differentiation property. To define the heterogeneity of tumours and their associated microenvironments, we observe greater tumour diversity in H-ChC than HCC and iCCA. H-ChC exhibits weaker immune cell infiltration and greater CD8+ exhausted T cell (Tex) dysfunction than HCC and iCCA. Then we defined two broad cell states of 6,852 CD8+ Tex cells: GZMK+ CD8+ Tex cells and terminal CD8+ Tex cells. GZMK+ CD8+ Tex cells exhibited higher infiltration of after treatment in H-ChC, the effector scores and expression of the immune checkpoints of them greatly increased after immunotherapy, which indicated that H-ChC might be more sensitive than HCC or iCCA to immunotherapy.

Conclusions

In this paper, H-ChC was explored, hoping to contribute to the study of mixed tumours in other cancers.

SPP1 could be an immunological and prognostic biomarker: From pan-cancer comprehensive analysis to osteosarcoma validation

Secreted phosphoprotein 1 (SPP1), also known as osteopontin, is a phosphorylated protein. High SPP1 expression levels have been detected in multiple cancers and are associated with poor prognosis and reduced survival rates. However, only a few pan-cancer analyses have targeted SPP1. We conducted a comprehensive analysis using multiple public databases, including TIMER and TCGA, to investigate the expression levels of SPP1 in 33 different tumor types. In addition, we verified the effect of SPP1 on osteosarcoma. To assess the impact of SPP1 on patient outcomes, we employed univariate Cox regression and Kaplan-Meier survival analyses to analyze overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in these tumor patients. We also explored SPP1 gene alterations in various tumor tissues using cBioPortal. We then examined the relationship between SPP1 and clinical characteristics, TME, immune regulatory genes, immune checkpoints, TMB, and MSI using R language. In addition, we used GSEA to investigate the molecular mechanisms underlying the role of SPP1. Bioinformatics analysis indicated that SPP1 was upregulated in 17 tumors. Overexpression of SPP1 results in poor OS, DSS, and PFI in CESC, ESCA, GBM, LGG, LIHC, PAAD, PRAD, and skin cutaneous melanoma. SPP1 expression was positively associated with immunocyte infiltration, immune regulatory genes, immune checkpoints, TMB, MSI, and drug sensitivity in certain cancers. We found that high expression of SPP1 in osteosarcoma was related to drug resistance and metastasis and further demonstrated that SPP1 can stimulate osteosarcoma cell proliferation via CCND1 by activating the PI3K/Akt pathway. These findings strongly suggest that SPP1 is a potential prognostic marker and novel target for cancer immunotherapy.

The neurotransmitter calcitonin gene-related peptide shapes an immunosuppressive microenvironment in medullary thyroid cancer

Neurotransmitters are key modulators in neuro-immune circuits and have been linked to tumor progression. Medullary thyroid cancer (MTC), an aggressive neuroendocrine tumor, expresses neurotransmitter calcitonin gene-related peptide (CGRP), is insensitive to chemo- and radiotherapies, and the effectiveness of immunotherapies remains unknown. Thus, a comprehensive analysis of the tumor microenvironment would facilitate effective therapies and provide evidence on CGRP's function outside the nervous system. Here, we compare the single-cell landscape of MTC and papillary thyroid cancer (PTC) and find that expression of CGRP in MTC is associated with dendritic cell (DC) abnormal development characterized by activation of cAMP related pathways and high levels of Kruppel Like Factor 2 (KLF2), correlated with an impaired activity of tumor infiltrating T cells. A CGRP receptor antagonist could offset CGRP detrimental impact on DC development in vitro. Our study provides insights of the MTC immunosuppressive microenvironment, and proposes CGRP receptor as a potential therapeutic target.

Targeting CD73 limits tumor progression and enhances anti-tumor activity of anti-PD-1 therapy in intrahepatic cholangiocarcinoma

BACKGROUND & AIMS

Patients with intrahepatic cholangiocarcinoma (iCCA) respond poorly to immune checkpoint blockades (ICBs). In this study, we aimed to dissect the potential mechanisms underlying poor response to ICBs and explore a rational ICB-based combination therapy in iCCA.

METHODS

scRNA-seq dataset GSE151530 was analyzed to investigate the differentially expressed genes in malignant cells following ICBs therapy. RNA-seq analysis and western blot assays were performed to examine the upstream and downstream signaling pathways of CD73. Subcutaneous tumor xenograft models were utilized to investigate the impact of CD73 on iCCA growth. Plasmid AKT/NICD-induced spontaneous murine iCCAs were used to explore the therapeutic efficacy of CD73 enzymatic inhibitor AB680 combined with PD-1 blockade. Time-of-flight mass cytometry (CyTOF) was conducted to identify the tumor-infiltrating immune cell populations and their functional changes in murine iCCAs treated with AB680 in combination with PD-1 antibody.

RESULTS

scRNA-seq analysis identified elevated CD73 expression in malignant cells in response to ICBs therapy. Mechanistically, ICBs therapy upregulated CD73 expression in malignant cells via TNF-α/NF-κB signaling pathway. In vivo studies revealed that CD73 inhibition suppressed the growth of subcutaneous tumors, and achieved synergistic depression effects with gemcitabine and cisplatin (GC). Adenosine produced by CD73 activates AKT/GSK3β/β-catenin signaling axis in iCCA cells. CD73 inhibitor AB680 potentiates anti-tumor efficacy of PD-1 antibody in murine iCCAs. CyTOF analysis showed that AB680 combined with anti-PD-1 therapy promoted the infiltration of CD8+ T, CD4+ T cells, and NK cells in murine iCCAs, while simultaneously decreased the proportions of macrophages and neutrophils. Moreover, AB680 combined with anti-PD-1 significantly upregulated the expression of Granzyme B, Tbet and co-stimulatory molecule ICOS in infiltrating CD8+ T cells.

CONCLUSIONS

CD73 inhibitor AB680 limits tumor progression and potentiates therapeutic efficacy of GC chemotherapy or anti-PD-1 treatment in iCCA. AB680 combined with anti-PD-1 therapy effectively elicits anti-tumor immune response.

Commentary: Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in cholangiocarcinoma

Machine learning has made great progress in the field of medicine, especially in oncology research showing significant potential. In this paper, the application of machine learning in the study of cholangiocarcinoma was discussed. By developing a novel intra-tumor heterogeneity feature, the study successfully achieved accurate prediction of prognosis and immunotherapy effect in patients with cholangiocarcinoma. This study not only provides strong support for personalized treatment, but also provides key information for clinicians to develop more effective treatment strategies. This breakthrough marks the continuous evolution of machine learning in cancer research and brings new hope for the future development of the medical field. Our study lays a solid foundation for deepening the understanding of the biological characteristics of cholangiocarcinoma and improving the therapeutic effect, and provides a useful reference for more extensive cancer research.

Applications of single-cell multi-omics in liver cancer

Primary liver cancer, more specifically hepatocellular carcinoma (HCC), remains a significant global health problem associated with increasing incidence and mortality. Clinical, biological, and molecular heterogeneity are well-known hallmarks of cancer and HCC is considered one of the most heterogeneous tumour types, displaying substantial inter-patient, intertumoural and intratumoural variability. This heterogeneity plays a pivotal role in hepatocarcinogenesis, metastasis, relapse and drug response or resistance. Unimodal single-cell sequencing techniques have already revolutionised our understanding of the different layers of molecular hierarchy in the tumour microenvironment of HCC. By highlighting the cellular heterogeneity and the intricate interactions among cancer, immune and stromal cells before and during treatment, these techniques have contributed to a deeper comprehension of tumour clonality, hematogenous spreading and the mechanisms of action of immune checkpoint inhibitors. However, major questions remain to be elucidated, with the identification of biomarkers predicting response or resistance to immunotherapy-based regimens representing an important unmet clinical need. Although the application of single-cell multi-omics in liver cancer research has been limited thus far, a revolution of individualised care for patients with HCC will only be possible by integrating various unimodal methods into multi-omics methodologies at the single-cell resolution. In this review, we will highlight the different established single-cell sequencing techniques and explore their biological and clinical impact on liver cancer research, while casting a glance at the future role of multi-omics in this dynamic and rapidly evolving field.

Machine learning for the identification of neoantigen-reactive CD8 + T cells in gastrointestinal cancer using single-cell sequencing

BACKGROUND

It appears that tumour-infiltrating neoantigen-reactive CD8 + T (Neo T) cells are the primary driver of immune responses to gastrointestinal cancer in patients. However, the conventional method is very time-consuming and complex for identifying Neo T cells and their corresponding T cell receptors (TCRs).

METHODS

By mapping neoantigen-reactive T cells from the single-cell transcriptomes of thousands of tumour-infiltrating lymphocytes, we developed a 26-gene machine learning model for the identification of neoantigen-reactive T cells.

RESULTS

In both training and validation sets, the model performed admirably. We discovered that the majority of Neo T cells exhibited notable differences in the biological processes of amide-related signal pathways. The analysis of potential cell-to-cell interactions, in conjunction with spatial transcriptomic and multiplex immunohistochemistry data, has revealed that Neo T cells possess potent signalling molecules, including LTA, which can potentially engage with tumour cells within the tumour microenvironment, thereby exerting anti-tumour effects. By sequencing CD8 + T cells in tumour samples of patients undergoing neoadjuvant immunotherapy, we determined that the fraction of Neo T cells was significantly and positively linked with the clinical benefit and overall survival rate of patients.

CONCLUSION

This method expedites the identification of neoantigen-reactive TCRs and the engineering of neoantigen-reactive T cells for therapy.

Exploring potential predictive biomarkers through historical perspectives on the evolution of systemic therapies into the emergence of neoadjuvant therapy for the treatment of hepatocellular carcinoma

Hepatocellular carcinoma (HCC), a type of liver cancer, ranks as the sixth most prevalent cancer globally and represents the third leading cause of cancer-related deaths. Approximately half of HCC patients miss the opportunity for curative treatment and are then limited to undergoing systemic therapies. Currently, systemic therapy has entered the era of immunotherapy, particularly with the advent of immune-checkpoint inhibitors (ICIs), which have significantly enhanced outcomes for patients with advanced HCC. Neoadjuvant treatment for HCC has become a possibility-findings from the IMbrave 050 trial indicated that ICIs offer the benefit of recurrence-free survival for high-risk HCC patients post-resection or local ablation. However, only a small fraction of individuals benefit from systemic therapy. Consequently, there is an urgent need to identify predictive biomarkers for treatment response and outcome assessment. This study reviewed the historical progression of systemic therapy for HCC, highlighting notable therapeutic advancements. This study examined the development of systemic therapies involving conventional drugs and clinical trials utilized in HCC treatment, as well as potential predictive biomarkers for advanced and/or locally advanced HCC. Various studies have revealed potential biomarkers in the context of HCC treatment. These include the association of dendritic cells (DCs) with a favorable response to neoadjuvant therapy, the presence of enriched T effector cells and tertiary lymphoid structures, the identification of CD138+ plasma cells, and distinct spatial arrangements of B cells in close proximity to T cells among responders with locally advanced HCC receiving neoadjuvant cabozantinib and nivolumab treatment. Furthermore, pathological response has been associated with intratumoral cellular triads consisting of progenitor CD8+ T cells and CXCL13+ CD4+ T helper cells surrounding mature DCs in patients receiving neoadjuvant cemiplimab for resectable HCC. Despite no widely recognized predictive biomarkers for HCC individualized treatment, we believe neoadjuvant trials hold the most promise in identifying and validating them. This is because they can collect multiple samples from resectable HCC patients across stages, especially with multi-omics, bridging preclinical and clinical gaps.

S100A16 is a potential target for reshaping the tumor microenvironment in the hypoxic context of liver cancer

BACKGROUND

The research on the S100 family has garnered significant attention; however, there remains a dearth of understanding regarding the precise role of S100A16 in the tumor microenvironment of liver cancer.

METHOD

Comprehensive analysis was conducted on the expression of S100A16 in tumor tissues and its correlation with hypoxia genes. Furthermore, an investigation was carried out to examine the association between S100A16 and infiltration of immune cells in tumors as well as immunotherapy. Relevant findings were derived from the analysis of single cell sequencing data, focusing on the involvement of S100A16 in both cellular differentiation and intercellular communication. Finally, we validated the expression of S100A16 in liver cancer by Wuhan cohort and multiplexed immunofluorescence to investigate the correlation between S100A16 and hypoxia.

RESULT

Tumor tissues displayed a notable increase in the expression of S100A16. A significant correlation was observed between S100A16 and genes associated with hypoxic genes. Examination of immune cell infiltration revealed an inverse association between T cell infiltration and the level of S100A16 expression. The high expression group of S100A16 exhibited a decrease in the expression of genes related to immune cell function. Single-cell sequencing data analysis revealed that non-immune cells predominantly expressed S100A16, and its expression levels increased along with the trajectory of cell differentiation. Additionally, there were significant variations observed in hypoxia genes as cells underwent differentiation. Cellular communication identified non-immune cells interacting with immune cells through multiple signaling pathways. The Wuhan cohort verified that S100A16 expression was increased in liver cancer. The expression of S100A16 and HIF was simultaneously elevated in endothelial cells.

CONCLUSION

The strong association between S100A16 and immune cell infiltration is observed in the context of hypoxia, indicating its regulatory role in shaping the hypoxic tumor microenvironment in liver cancer.

CD63 + tumor-associated macrophages drive the progression of hepatocellular carcinoma through the induction of epithelial-mesenchymal transition and lipid reprogramming

BACKGROUND

Tumor-associated macrophages (TAMs) constitute a substantial part of human hepatocellular carcinoma (HCC). The present study was devised to explore TAM diversity and their roles in HCC progression.

METHODS

Through the integration of multiple 10 × single-cell transcriptomic data derived from HCC samples and the use of consensus nonnegative matrix factorization (an unsupervised clustering algorithm), TAM molecular subtypes and expression programs were evaluated in detail. The roles played by these TAM subtypes in HCC were further probed through pseudotime, enrichment, and intercellular communication analyses. Lastly, vitro experiments were performed to validate the relationship between CD63, which is an inflammatory TAM expression program marker, and tumor cell lines.

RESULTS

We found that the inflammatory expression program in TAMs had a more obvious interaction with HCC cells, and CD63, as a marker gene of the inflammatory expression program, was associated with poor prognosis of HCC patients. Both bulk RNA-seq and vitro experiments confirmed that higher TAM CD63 expression was associated with the growth of HCC cells as well as their epithelial-mesenchymal transition, metastasis, invasion, and the reprogramming of lipid metabolism.

CONCLUSIONS

These analyses revealed that the TAM inflammatory expression program in HCC is closely associated with malignant tumor cells, with the hub gene CD63 thus representing an ideal target for therapeutic intervention in this cancer type.

Plasma exosomes from patients with active thyroid-associated orbitopathy induce inflammation and fibrosis in orbital fibroblasts

BACKGROUND

The pathogenesis of thyroid-associated orbitopathy (TAO) remains incompletely understand. The interaction between immunocytes and orbital fibroblasts (OFs) play a critical role in orbital inflammatory and fibrosis. Accumulating reports indicate that a significant portion of plasma exosomes (Pla-Exos) are derived from immune cells; however, their impact upon OFs function is unclear.

METHODS

OFs were primary cultured from inactive TAO patients. Exosomes isolated from plasma samples of patients with active TAO and healthy controls (HCs) were utilized for functional and RNA cargo analysis. Functional analysis in thymocyte differentiation antigen-1+ (Thy-1+) OFs measured expression of inflammatory and fibrotic markers (mRNAs and proteins) and cell activity in response to Pla-Exos. RNA cargo analysis was performed by RNA sequencing and RT-qPCR. Thy-1+ OFs were transfected with miR-144-3p mimics/inhibitors to evaluate its regulation of inflammation, fibrosis, and proliferation.

RESULTS

Pla-Exos derived from active TAO patients (Pla-ExosTAO-A) induced stronger production of inflammatory cytokines and hyaluronic acid (HA) in Thy-1+ OFs while inhibiting their proliferation. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and single sample gene set enrichment analysis (ssGSEA) suggested that the difference in mRNA expression levels between Pla-ExosTAO-A and Pla-ExosHC was closely related to immune cells. Differential expression analysis revealed that 62 upregulated and 45 downregulated miRNAs in Pla-ExosTAO-A, with the elevation of miR-144-3p in both Pla-Exos and PBMCs in active TAO group. KEGG analysis revealed that the target genes of differentially expressed miRNA and miR-144-3p enriched in immune-related signaling pathways. Overexpression of the miR-144-3p mimic significantly upregulated the secretion of inflammatory cytokines and HA in Thy-1+ OFs while inhibiting their proliferation.

CONCLUSION

Pla-Exos derived from patients with active TAO were immune-active, which may be a long-term stimulus casual for inflammatory and fibrotic progression of TAO. Our finding suggests that Pla-Exos could be used as biomarkers or treatment targets in TAO patients.

An Immunohistochemical Analysis of Osteopontin and S100 Calcium-binding Protein P is Useful for Subclassifying Large- and Small-duct Type Intrahepatic Cholangiocarcinomas

Intrahepatic cholangiocarcinoma (iCCA) has been newly subclassified into two different subtypes: large-duct (LD) type and small-duct (SD) type. However, many cases are difficult to subclassify, and there is no consensus regarding subclassification criteria. LD type expresses the highly sensitive diagnostic marker S100 calcium-binding protein P (S100P), while SD type lacks sensitive markers. We identified osteopontin (OPN) as a highly sensitive marker for SD type. This study aimed to develop new subclassification criteria for LD-type and SD-type iCCA. We retrospectively investigated 74 patients with iCCA and subclassified them based on whole-section immunostaining of S100P and OPN. Of the 74 cases, 41 were subclassified as LD type, 32 as SD type, and one was indeterminate. Notably, all S100P-negative cases had OPN positivity. Seventy-three of the 74 cases (98.6%) were clearly and easily subclassified as LD or SD type using only these 2 markers. We also determined the value of immunohistochemistry in cases that were difficult to diagnose based on hematoxylin-eosin and Alcian blue-periodic acid-Schiff staining. Furthermore, we analyzed the clinicopathological characteristics and prognoses of these 2 subtypes. LD type was a poor prognostic factor on univariate analysis; it had significantly worse overall survival ( P = 0.007) and recurrence-free survival ( P < 0.001) than the SD type. In conclusion, we propose new subclassification criteria for iCCA based on immunostaining of S100P and OPN. These criteria may help pathologists to diagnose subtypes of iCCA, supporting future clinical trials and the development of medications for these 2 subtypes as distinct cancers.

Reconstructing developmental trajectories using latent dynamical systems and time-resolved transcriptomics

The snapshot nature of single-cell transcriptomics presents a challenge for studying the dynamics of cell fate decisions. Metabolic labeling and splicing can provide temporal information at single-cell level, but current methods have limitations. Here, we present a framework that overcomes these limitations: experimentally, we developed sci-FATE2, an optimized method for metabolic labeling with increased data quality, which we used to profile 45,000 embryonic stem (ES) cells differentiating into neural tube identities. Computationally, we developed a two-stage framework for dynamical modeling: VelvetVAE, a variational autoencoder (VAE) for velocity inference that outperforms all other tools tested, and VelvetSDE, a neural stochastic differential equation (nSDE) framework for simulating trajectory distributions. These recapitulate underlying dataset distributions and capture features such as decision boundaries between alternative fates and fate-specific gene expression. These methods recast single-cell analyses from descriptions of observed data to models of the dynamics that generated them, providing a framework for investigating developmental fate decisions.

HCCDB v2.0: Decompose Expression Variations by Single-cell RNA-seq and Spatial Transcriptomics in HCC

Large-scale transcriptomic data are crucial for understanding the molecular features of hepatocellular carcinoma (HCC). Integrated 15 transcriptomic datasets of HCC clinical samples, the first version of HCC database (HCCDB v1.0) was released in 2018. Through the meta-analysis of differentially expressed genes and prognosis-related genes across multiple datasets, it provides a systematic view of the altered biological processes and the inter-patient heterogeneities of HCC with high reproducibility and robustness. With four years having passed, the database now needs integration of recently published datasets. Furthermore, the latest single-cell and spatial transcriptomics have provided a great opportunity to decipher complex gene expression variations at the cellular level with spatial architecture. Here, we present HCCDB v2.0, an updated version that combines bulk, single-cell, and spatial transcriptomic data of HCC clinical samples. It dramatically expands the bulk sample size by adding 1656 new samples from 11 datasets to the existing 3917 samples, thereby enhancing the reliability of transcriptomic meta-analysis. A total of 182,832 cells and 69,352 spatial spots are added to the single-cell and spatial transcriptomics sections, respectively. A novel single-cell level and 2-dimension (sc-2D) metric is proposed as well to summarize cell type-specific and dysregulated gene expression patterns. Results are all graphically visualized in our online portal, allowing users to easily retrieve data through a user-friendly interface and navigate between different views. With extensive clinical phenotypes and transcriptomic data in the database, we show two applications for identifying prognosis-associated cells and tumor microenvironment. HCCDB v2.0 is available at http://lifeome.net/database/hccdb2.

Fibroblast-Derived Lysyl Oxidase Increases Oxidative Phosphorylation and Stemness in Cholangiocarcinoma

BACKGROUND & AIMS

Metabolic and transcriptional programs respond to extracellular matrix-derived cues in complex environments, such as the tumor microenvironment. Here, we demonstrate how lysyl oxidase (LOX), a known factor in collagen crosslinking, contributes to the development and progression of cholangiocarcinoma (CCA).

METHODS

Transcriptomes of 209 human CCA tumors, 143 surrounding tissues, and single-cell data from 30 patients were analyzed. The recombinant protein and a small molecule inhibitor of the LOX activity were used on primary patient-derived CCA cultures to establish the role of LOX in migration, proliferation, colony formation, metabolic fitness, and the LOX interactome. The oncogenic role of LOX was further investigated by RNAscope and in vivo using the AKT/NICD genetically engineered murine CCA model.

RESULTS

We traced LOX expression to hepatic stellate cells and specifically hepatic stellate cell-derived inflammatory cancer-associated fibroblasts and found that cancer-associated fibroblast-driven LOX increases oxidative phosphorylation and metabolic fitness of CCA, and regulates mitochondrial function through transcription factor A, mitochondrial. Inhibiting LOX activity in vivo impedes CCA development and progression. Our work highlights that LOX alters tumor microenvironment-directed transcriptional reprogramming of CCA cells by facilitating the expression of the oxidative phosphorylation pathway and by increasing stemness and mobility.

CONCLUSIONS

Increased LOX is driven by stromal inflammatory cancer-associated fibroblasts and correlates with diminished survival of patients with CCA. Modulating the LOX activity can serve as a novel tumor microenvironment-directed therapeutic strategy in bile duct pathologies.

Heterogeneity in Liver Cancer Immune Microenvironment: Emerging Single-Cell and Spatial Perspectives

Primary liver cancer is a solid malignancy with a high mortality rate. The success of immunotherapy has shown great promise in improving patient care and highlights a crucial need to understand the complexity of the liver tumor immune microenvironment (TIME). Recent advances in single-cell and spatial omics technologies, coupled with the development of systems biology approaches, are rapidly transforming the landscape of tumor immunology. Here we review the cellular landscape of liver TIME from single-cell and spatial perspectives. We also discuss the cellular interaction networks within the tumor cell community in regulating immune responses. We further highlight the challenges and opportunities with implications for biomarker discovery, patient stratification, and combination immunotherapies.

Immunotherapy and drug sensitivity predictive roles of a novel prognostic model in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most significant causes of cancer-related deaths in the worldwide. Currently, predicting the survival of patients with HCC and developing treatment drugs still remain a significant challenge. In this study, we employed prognosis-related genes to develop and externally validate a predictive risk model. Furthermore, the correlation between signaling pathways, immune cell infiltration, immunotherapy response, drug sensitivity, and risk score was investigated using different algorithm platforms in HCC. Our results showed that 11 differentially expressed genes including UBE2C, PTTG1, TOP2A, SPP1, FCN3, SLC22A1, ADH4, CYP2C8, SLC10A1, F9, and FBP1 were identified as being related to prognosis, which were integrated to construct a prediction model. Our model could accurately predict patients' overall survival using both internal and external datasets. Moreover, a strong correlation was revealed between the signaling pathway, immune cell infiltration, immunotherapy response, and risk score. Importantly, a novel potential drug candidate for HCC treatment was discovered based on the risk score and also validated through ex vivo experiments. Our finds offer a novel perspective on prognosis prediction and drug exploration for cancer patients.

Identification and validation of a lactate metabolism-related six-gene prognostic signature in intrahepatic cholangiocarcinoma

PURPOSE

Intrahepatic cholangiocarcinoma (iCCA) is a highly malignant and fatal liver tumor with increasing incidence worldwide. Lactate metabolism has been recently reported as a crucial contributor to tumor progression and immune regulation in the tumor microenvironment. However, it remains poorly identified about the biological functions of lactate metabolism in iCCA, which hinders the development of prognostic tools and therapeutic interventions.

METHODS

The univariate Cox regression analysis and Boruta algorithm were utilized to identify key lactate metabolism-related genes (LMRGs), and a prognostic signature was constructed based on LMRG scores. Genomic variations and immune cell infiltration were evaluated in the high and low LMRG score groups. Finally, the biological functions of key LMRGs were verified with in vitro and in vivo experiments.

RESULTS

Patients in the high LMRG score group exhibit a poor prognosis compared to those in the low LMRG score group, with a high frequency of TP53 and KRAS mutations. Moreover, the infiltration and function of NK cells were compromised in the high LMRG score group, consistent with the results from two independent single-cell RNA sequencing datasets and immunohistochemistry of tissue microarrays. Experimental data revealed that lactate dehydrogenase A (LDHA) knockdown inhibited proliferation and migration in iCCA cell lines and tumor growth in immunocompetent mice.

CONCLUSION

Our study revealed the biological roles of LDHA in iCCA and developed a reliable lactate metabolism-related prognostic signature for iCCA, offering promising therapeutic targets for iCCA in the clinic.

Spatial proximity of tumor-immune interactions predicts patient outcome in hepatocellular carcinoma

BACKGROUND AND AIMS

The fitness and viability of a tumor ecosystem are influenced by the spatial organization of its cells. We aimed to study the structure, architecture, and cell-cell dynamics of the heterogeneous liver cancer tumor microenvironment using spatially resolved multiplexed imaging.

APPROACH AND RESULTS

We performed co-detection by indexing multiplexed immunofluorescence imaging on 68 HCC biopsies from Thai patients [(Thailand Initiative in Genomics and Expression Research for Liver Cancer (TIGER-LC)] as a discovery cohort, and then validated the results in an additional 190 HCC biopsies from Chinese patients [Liver Cancer Institute (LCI)]. We segmented and annotated 117,270 and 465,632 cells from the TIGER-LC and LCI cohorts, respectively. We observed 4 patient groups of TIGER-LC (IC1, IC2, IC3, and IC4) with distinct tumor-immune cellular interaction patterns. In addition, patients from IC2 and IC4 had much better overall survival than those from IC1 and IC3. Noticeably, tumor and CD8 + T-cell interactions were strongly enriched in IC2, the group with the best patient outcomes. The close proximity between the tumor and CD8 + T cells was a strong predictor of patient outcome in both the TIGER-LC and the LCI cohorts. Bulk transcriptomic data from 51 of the 68 HCC cases were used to determine tumor-specific gene expression features of our classified subtypes. Moreover, we observed that the presence of immune spatial neighborhoods in HCC as a measure of overall immune infiltration is linked to better patient prognosis.

CONCLUSIONS

Highly multiplexed imaging analysis of liver cancer reveals tumor-immune cellular heterogeneity within spatial contexts, such as tumor and CD8 + T-cell interactions, which may predict patient survival.

SIMarker: Cellular similarity detection and its application to diagnosis and prognosis of liver cancer

BACKGROUND

The emergence of single-cell technology offers a unique opportunity to explore cellular similarity and heterogeneity between precancerous diseases and solid tumors. However, there is lacking a systematic study for identifying and characterizing similarities at single-cell resolution.

METHODS

We developed SIMarker, a computational framework to detect cellular similarities between precancerous diseases and solid tumors based on gene expression at single-cell resolution. Taking hepatocellular carcinoma (HCC) as a case study, we quantified the cellular and molecular connections between HCC and cirrhosis. Core analysis modules of SIMarker is publicly available at https://github.com/xmuhuanglab/SIMarker ("SIM" means "similarity" and "Marker" means "biomarkers).

RESULTS

We found PGA5+ hepatocytes in HCC showed cirrhosis-like characteristics, including similar transcriptional programs and gene regulatory networks. Consequently, the genes constituting the gene expression program of these cirrhosis-like subpopulations were designated as cirrhosis-like signatures (CLS). Strikingly, our utilization of CLS enabled the development of diagnosis and prognosis biomarkers based on within-sample relative expression orderings of gene pairs. These biomarkers achieved high precision and concordance compared with previous studies.

CONCLUSIONS

Our work provides a systematic method to investigate the clinical translational significance of cellular similarities between HCC and cirrhosis, which opens avenues for identifying similar paradigms in other categories of cancers and diseases.

THBS1+ myeloid cells expand in SLD hepatocellular carcinoma and contribute to immunosuppression and unfavorable prognosis through TREM1

Hepatocellular carcinoma (HCC) is an inflammation-associated cancer arising from viral or non-viral etiologies including steatotic liver diseases (SLDs). Expansion of immunosuppressive myeloid cells is a hallmark of inflammation and cancer, but their heterogeneity in HCC is not fully resolved and might underlie immunotherapy resistance. Here, we present a high-resolution atlas of innate immune cells from patients with HCC that unravels an SLD-associated contexture characterized by influx of inflammatory and immunosuppressive myeloid cells, including a discrete population of THBS1+ regulatory myeloid (Mreg) cells expressing monocyte- and neutrophil-affiliated genes. THBS1+ Mreg cells expand in SLD-associated HCC, populate fibrotic lesions, and are associated with poor prognosis. THBS1+ Mreg cells are CD163+ but distinguished from macrophages by high expression of triggering receptor expressed on myeloid cells 1 (TREM1), which contributes to their immunosuppressive activity and promotes HCC tumor growth in vivo. Our data support myeloid subset-targeted immunotherapies to treat HCC.

Deciphering cancer cell state plasticity with single-cell genomics and artificial intelligence

Cancer stem cell plasticity refers to the ability of tumour cells to dynamically switch between states-for example, from cancer stem cells to non-cancer stem cell states. Governed by regulatory processes, cells transition through a continuum, with this transition space often referred to as a cell state landscape. Plasticity in cancer cell states leads to divergent biological behaviours, with certain cell states, or state transitions, responsible for tumour progression and therapeutic response. The advent of single-cell assays means these features can now be measured for individual cancer cells and at scale. However, the high dimensionality of this data, complex relationships between genomic features, and a lack of precise knowledge of the genomic profiles defining cancer cell states have opened the door for artificial intelligence methods for depicting cancer cell state landscapes. The contribution of cell state plasticity to cancer phenotypes such as treatment resistance, metastasis, and dormancy has been masked by analysis of 'bulk' genomic data-constituted of the average signal from millions of cells. Single-cell technologies solve this problem by producing a high-dimensional cellular landscape of the tumour ecosystem, quantifying the genomic profiles of individual cells, and creating a more detailed model to investigate cancer plasticity (Genome Res 31:1719, 2021; Semin Cancer Biol 53: 48-58, 2018; Signal Transduct Target Ther 5:1-36, 2020). In conjunction, rapid development in artificial intelligence methods has led to numerous tools that can be employed to study cancer cell plasticity.

Immunosuppressive CD29+ Treg accumulation in the liver in mice on checkpoint inhibitor therapy

OBJECTIVE

Liver metastases are often resistant to immune checkpoint inhibitor therapy (ICI) and portend a worse prognosis compared with metastases to other locations. Regulatory T cells (Tregs) are one of several immunosuppressive cells implicated in ICI resistance of liver tumours, but the role played by Tregs residing within the liver surrounding a tumour is unknown.

DESIGN

Flow cytometry and single-cell RNA sequencing were used to characterise hepatic Tregs before and after ICI therapy.

RESULTS

We found that the murine liver houses a Treg population that, unlike those found in other organs, is both highly proliferative and apoptotic at baseline. On administration of αPD-1, αPD-L1 or αCTLA4, the liver Treg population doubled regardless of the presence of an intrahepatic tumour. Remarkably, this change was not due to the preferential expansion of the subpopulation of Tregs that express PD-1. Instead, a subpopulation of CD29+ (Itgb1, integrin β1) Tregs, that were highly proliferative at baseline, doubled its size in response to αPD-1. Partial and full depletion of Tregs identified CD29+ Tregs as the prominent niche-filling subpopulation in the liver, and CD29+ Tregs demonstrated enhanced suppression in vitro when derived from the liver but not the spleen. We identified IL2 as a critical modulator of both CD29+ and CD29- hepatic Tregs, but expansion of the liver Treg population with αPD-1 driven by CD29+ Tregs was in part IL2-independent.

CONCLUSION

We propose that CD29+ Tregs constitute a unique subpopulation of hepatic Tregs that are primed to respond to ICI agents and mediate resistance.

Lineage and ecology define liver tumor evolution in response to treatment

A tumor ecosystem constantly evolves over time in the face of immune predation or therapeutic intervention, resulting in treatment failure and tumor progression. Here, we present a single-cell transcriptome-based strategy to determine the evolution of longitudinal tumor biopsies from liver cancer patients by measuring cellular lineage and ecology. We construct a lineage and ecological score as joint dynamics of tumor cells and their microenvironments. Tumors may be classified into four main states in the lineage-ecological space, which are associated with clinical outcomes. Analysis of longitudinal samples reveals the evolutionary trajectory of tumors in response to treatment. We validate the lineage-ecology-based scoring system in predicting clinical outcomes using bulk transcriptomic data of additional cohorts of 716 liver cancer patients. Our study provides a framework for monitoring tumor evolution in response to therapeutic intervention.