Identification of a tumour immune barrier in the HCC microenvironment that determines the efficacy of immunotherapy

Exploring the role of the immune microenvironment in hepatocellular carcinoma: Implications for immunotherapy and drug resistance

Hepatocellular carcinoma (HCC), the most common type of liver tumor, is a leading cause of cancer-related deaths, and the incidence of liver cancer is still increasing worldwide. Curative hepatectomy or liver transplantation is only indicated for a small population of patients with early-stage HCC. However, most patients with HCC are not candidates for radical resection due to disease progression, leading to the choice of the conventional tyrosine kinase inhibitor drug sorafenib as first-line treatment. In the past few years, immunotherapy, mainly immune checkpoint inhibitors (ICIs), has revolutionized the clinical strategy for HCC. Combination therapy with ICIs has proven more effective than sorafenib, and clinical trials have been conducted to apply these therapies to patients. Despite significant progress in immunotherapy, the molecular mechanisms behind it remain unclear, and immune resistance is often challenging to overcome. Several studies have pointed out that the complex intercellular communication network in the immune microenvironment of HCC regulates tumor escape and drug resistance to immune response. This underscores the urgent need to analyze the immune microenvironment of HCC. This review describes the immunosuppressive cell populations in the immune microenvironment of HCC, as well as the related clinical trials, aiming to provide insights for the next generation of precision immunotherapy.

Spatial multiomics reveals a subpopulation of fibroblasts associated with cancer stemness in human hepatocellular carcinoma

BACKGROUND

Cancer-associated fibroblasts (CAFs) are the prominent cell type in the tumor microenvironment (TME), and CAF subsets have been identified in various tumors. However, how CAFs spatially coordinate other cell populations within the liver TME to promote cancer progression remains unclear.

METHODS

We combined multi-region proteomics (6 patients, 24 samples), 10X Genomics Visium spatial transcriptomics (11 patients, 25 samples), and multiplexed imaging (92 patients, 264 samples) technologies to decipher the expression heterogeneity, functional diversity, spatial distribution, colocalization, and interaction of fibroblasts. The newly identified CAF subpopulation was validated by cells isolated from 5 liver cancer patients and in vitro functional assays.

RESULTS

We identified a liver CAF subpopulation, marked by the expression of COL1A2, COL4A1, COL4A2, CTGF, and FSTL1, and named F5-CAF. F5-CAF is preferentially located within and around tumor nests and colocalizes with cancer cells with higher stemness in hepatocellular carcinoma (HCC). Multiplexed staining of 92 patients and the bulk transcriptome of 371 patients demonstrated that the abundance of F5-CAFs in HCC was associated with a worse prognosis. Further in vitro experiments showed that F5-CAFs isolated from liver cancer patients can promote the proliferation and stemness of HCC cells.

CONCLUSIONS

We identified a CAF subpopulation F5-CAF in liver cancer, which is associated with cancer stemness and unfavorable prognosis. Our results provide potential mechanisms by which the CAF subset in the TME promotes the development of liver cancer by supporting the survival of cancer stem cells.

Unveiling major histocompatibility complex-mediated pan-cancer immune features by integrated single-cell and bulk RNA sequencing

Immune checkpoint inhibitors (ICIs) have transformed cancer therapy, yet persistent challenges such as low response rate and significant heterogeneity necessitate attention. The pivotal role of the major histocompatibility complex (MHC) in ICI efficacy, its intricate impacts and potentials as a prognostic marker, warrants comprehensive exploration. This study integrates single-cell RNA sequencing (scRNA-seq), bulk RNA-seq, and spatial transcriptomic analyses to unveil pan-cancer immune characteristics governed by the MHC transcriptional feature (MHC.sig). Developed through scRNA-seq analysis of 663,760 cells across diverse cohorts and validated in 30 solid cancer types, the MHC.sig demonstrates a robust correlation between immune-related genes and infiltrating immune cells, highlighting its potential as a universal pan-cancer marker for anti-tumor immunity. Screening the MHC.sig for therapeutic targets using CRISPR data identifies potential genes for immune therapy synergy and validates its predictive efficacy for ICIs responsiveness across diverse datasets and cancer types. Finally, analysis of cellular communication patterns reveals interactions between C1QC+macrophages and malignant cells, providing insights into potential therapeutic agents and their sensitivity characteristics. This comprehensive analysis positions the MHC.sig as a promising marker for predicting immune therapy outcomes and guiding combinatorial therapeutic strategies.

Tumor-associated macrophage clusters linked to immunotherapy in a pan-cancer census

Transcriptional heterogeneity of tumor-associated macrophages (TAMs) has been investigated in individual cancers, but the extent to which these states transcend tumor types and represent a general feature of cancer remains unclear. We performed pan-cancer single-cell RNA sequencing analysis across nine cancer types and identified distinct monocyte/TAM composition patterns. Using spatial analysis from clinical study tissues, we assessed TAM functions in shaping the tumor microenvironment (TME) and influencing immunotherapy. Two specific TAM clusters (pro-inflammatory and pro-tumor) and four TME subtypes showed distinct immunological features, genomic profiles, immunotherapy responses, and cancer prognosis. Pro-inflammatory TAMs resided in immune-enriched niches with exhausted CD8+ T cells, while pro-tumor TAMs were restricted to niches associated with a T-cell-excluded phenotype and hypoxia. We developed a machine learning model to predict immune checkpoint blockade response by integrating TAMs and clinical data. Our study comprehensively characterizes the common features of TAMs and highlights their interaction with the TME.

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

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

Rhein‐based Pickering emulsion for hepatocellular carcinoma: Shaping the metabolic signaling and immunoactivation in transarterial chemoembolization

The efficacy of transarterial chemoembolization (TACE) has been limited by insufficient embolization and a high incidence of tumor recurrence. Herein, we identified that aberrant metabolic reprogramming and immunosuppression contribute to TACE refractoriness and Rhein, as a potential glycolytic metabolism inhibitor and immunoactivation inducer, was optimized to sensitize tumors to TACE therapy. To achieve efficient embolization, we developed an oil‐in‐water lipiodol embolic emulsion by stabilizing the self‐assembled Rhein nanogel. The assembled Rhein exhibited a nanofiber network, and its integration enhanced the mechanical stability and viscoelasticity of the lipiodol embolic agent. With the synergistic advantages of solid and liquid embolic agents, this carrier‐free Pickering emulsion exhibits efficient embolization and sustained drug release in models of unilateral renal artery embolization, rabbit ear tumor embolization, rabbit orthotopic liver cancer, and rat orthotopic liver cancer. Compared to conventional three‐way catheter mixing methods, multimodal imaging corroborates a marked enhancement in local drug retention and tumor suppression. Importantly, the incorporation of Rhein‐mediated synergistic immunoembolization in this strategy achieved efficient embolization while robustly activating anti‐tumor immune responses, including inducing immunogenic cell death, dendritic cell activation, and major histocompatibility complex class I presentation to CD8+ T cells for tumor killing. Together, these findings reveal a novel strategy for the application of self‐assembled Rhein nanofiber‐stabilized lipiodol emulsion to control metabolic signaling and immunoactivation in TACE.

The role of tumor-associated macrophages in hepatocellular carcinoma-from bench to bedside: A review

Hepatocellular carcinoma is one of the most common cancers worldwide. Despite progress in treatment, recurrence after radical treatment is common, and the prognosis remains poor for patients with advanced disease. Therefore, there is a need to identify prognostic and predictive factors for the response to therapy or more intensive surveillance or treatment. Because the tumor microenvironment plays a crucial role in the development of cancer and metastasis, it is a crucial need to understand processes that are involved in carcinogenesis. Within the microenvironment, several immune cells with different roles are present. One of the most important of these is tumor-associated macrophages. These cells may exert either antitumor or protumor roles. Several studies have suggested that tumor-associated macrophages can be used as prognostic markers. Furthermore, they may be involved in resistance to immunotherapy or systemic treatment. As they play an important role in cancer development, tumor-associated macrophages are also a good target for therapy. In this review, we briefly summarize recent progress on knowledge regarding the basic molecular characteristics, impact on prognosis and potential clinical implications of tumor-associated macrophages in hepatocellular carcinoma.

In-situ-formed immunotherapeutic and hemostatic dual drug-loaded nanohydrogel for preventing postoperative recurrence of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a prevalent malignancy characterized by an exceedingly high recurrence rate post-surgery, significantly impairing the prognosis of HCC patients. However, a standard in-care strategy for postoperative therapy is still lacking. Although encouraging results have been obtained in a newly published clinical trial for postoperative therapy by targeting the vascular endothelial growth factor (VEGF) and programmed death ligand 1 (anti-PD-L1), its efficacy remains constrained. Combining a hemostatic hydrogel with a nanoparticle-based drug delivery system presents an opportunity to optimize the antitumor effect. Herein, we developed a nanoplatform, termed HMSN@Sor/aP@Gel, comprising a hemostatic fibrin hydrogel and functionalized hollow mesoporous silica nanoparticles (HMSNs) loaded with sorafenib and anti-PD-L1 for locally administered targeted-immunotherapy to prevent the postoperative recurrence and metastasis of HCC. The antitumor mechanism is grounded in dual inhibition of Ras/Raf/MEK/ERK (MAPK) and phosphatidylinositol-3-kinase (PI3K)/protein kinase B (AKT) pathways, synergistically complemented by PD-L1 blockade. HMSN@Sor/aP@Gel facilitates dendritic cell maturation, enhances cytotoxic T-lymphocyte infiltration, promotes the polarization of tumor-associated macrophages to M1 phenotype, induces tumor immunogenic cell death, reverses immunosuppression, and establishes immune memory to counter postoperative recurrence. Animal studies corroborate that HMSN@Sor/aP@Gel-mediated targeted immunotherapy significantly impedes primary and metastatic tumor growth and establishes immune memory to prevent recurrence post-surgery. This investigation presents a promising strategy for postoperative therapy with considerable potential for clinical translation.

The association between tumour heterogeneity and immune evasion mechanisms in hepatocellular carcinoma and its clinical implications

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality worldwide. The emergence of combination therapy, atezolizumab (anti-PDL1, immune checkpoint inhibitor) and bevacizumab (anti-VEGF) has revolutionised the management of HCC. Despite this breakthrough, the best overall response rate with first-line systemic therapy is only about 30%, owing to intra-tumoural heterogeneity, complex tumour microenvironment and the lack of predictive biomarkers. Many groups have attempted to classify HCC based on the immune microenvironment and have consistently observed better outcomes in immunologically "hot" HCC. We summarised possible mechanisms of tumour immune evasion based on the latest literature and the rationale for combination/sequential therapy to improve treatment response. Lastly, we proposed future strategies and therapies to overcome HCC immune evasion to further improve treatment outcomes of HCC.

CAFs and T cells interplay: The emergence of a new arena in cancer combat

The interaction between the immune system and the tumor matrix has a huge impact on the progression and treatment of cancer. This paper summarizes and discusses the crosstalk between T cells and cancer-associated fibroblasts (CAFs). CAFs can also produce inhibitors that counteract the function of T cells and promote tumor immune escape, while T cells can also engage in complex two-way interactions with CAFs through direct cell contact, the exchange of soluble factors such as cytokines, and the remodeling of the extracellular matrix. Precise targeted intervention can effectively reverse tumor-promoting crosstalk between T cells and CAFs, improve anti-tumor immune response, and provide a new perspective for cancer treatment. Therefore, it is important to deeply understand the mechanism of crosstalk between T cells and CAFs. This review aims to outline the underlying mechanisms of these interactions and discuss potential therapeutic strategies that may become fundamental tools in the treatment of cancer, especially hard-to-cure cancers.

Dissecting the tumor microenvironment in response to immune checkpoint inhibitors via single-cell and spatial transcriptomics

Cancer is a disease that undergoes selective pressure to evolve during its progression, becoming increasingly heterogeneous. Tumoral heterogeneity can dictate therapeutic response. Transcriptomics can be used to uncover complexities in cancer and reveal phenotypic heterogeneity that affects disease response. This is especially pertinent in the immune microenvironment, which contains diverse populations of immune cells, and whose dynamic properties influence disease response. The recent development of immunotherapies has revolutionized cancer therapy, with response rates of up to 50% within certain cancers. However, despite advances in immune checkpoint blockade specifically, there remains a significant population of non-responders to these treatments. Transcriptomics can be used to profile immune and other cell populations following immune-checkpoint inhibitor (ICI) treatment, generate predictive biomarkers of resistance or response, assess immune effector function, and identify potential immune checkpoints. Single-cell RNA sequencing has offered insight into mRNA expression within the complex and heterogeneous tumor microenvironment at single-cell resolution. Spatial transcriptomics has enabled measurement of mRNA expression while adding locational context. Here, we review single-cell sequencing and spatial transcriptomic research investigating ICI response within a variety of cancer microenvironments.

Density of tertiary lymphoid structures predicts clinical outcome in breast cancer brain metastasis

BACKGROUND

Patients with breast cancer brain metastases (BCBM) experience a rapid decline in their quality of life. Recently, tertiary lymphoid structures (TLSs), analogs of secondary lymphoid organs, have attracted extensive attention. However, the potential clinical implications of TLSs in BCBMs are poorly understood. In this study, we evaluated the density and composition of TLSs in BCBMs and described their prognostic value.

METHODS

Clinicopathological data were collected from 98 patients (2015-2021). TLSs were evaluated, and a TLS scoring system was constructed. Differences in progression-free survival (PFS) and overall survival (OS) between groups were calculated using the Kaplan-Meier method. Immunohistochemistry and multiplex immunofluorescence (mIF) were used to assess TLSs heterogeneity.

RESULTS

TLSs were identified in 47 patients with BCBM. High TLSs density indicated favorable survival (OS, p=0.003; PFS, p<0.001). TLS was positively associated with OS (p=0.0172) and PFS (p=0.0161) in the human epidermal growth factor receptor type 2-positive subtype, and with prolonged OS (p=0.0482) in the triple-negative breast cancer subtype. The mIF results showed significant differences in the percentages of T follicular helper (Tfh) cells, M2 macrophages, cytotoxic T lymphocytes, and CD8+TIM-3+ T lymphocytes between the groups of TLS scores 0-3 (cytotoxic T lymphocytes, p=0.044; Tfh, p=0.021; M2 macrophages, p=0.033; CD8+TIM-3+ T lymphocytes, p=0.018). Furthermore, novel nomograms incorporating the TLS scores and other clinicopathological predictors demonstrated prominent predictability of the 1-year, 3-year, and 5-year outcomes of BCBMs (area under the curve >0.800).

CONCLUSION

Our results highlight the impact of TLSs abundance on the OS and PFS of patients with BCBM. Additionally, we described the immune composition of TLSs and proposed novel nomograms to predict the prognosis of patients with BCBM.

Decoding the spatiotemporal heterogeneity of tumor-associated macrophages

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

POSTN+ cancer-associated fibroblasts determine the efficacy of immunotherapy in hepatocellular carcinoma

OBJECTIVE

Hepatocellular carcinoma (HCC) poses a significant clinical challenge because the long-term benefits of immune checkpoint blockade therapy are limited. A comprehensive understanding of the mechanisms underlying immunotherapy resistance in HCC is imperative for improving patient prognosis.

DESIGN

In this study, to systematically investigate the characteristics of cancer-associated fibroblast (CAF) subsets and the dynamic communication among the tumor microenvironment (TME) components regulated by CAF subsets, we generated an HCC atlas by compiling single-cell RNA sequencing (scRNA-seq) datasets on 220 samples from six datasets. We combined spatial transcriptomics with scRNA-seq and multiplexed immunofluorescence to identify the specific CAF subsets in the TME that determine the efficacy of immunotherapy in HCC patients.

RESULTS

Our findings highlight the pivotal role of POSTN+ CAFs as potent immune response barriers at specific tumor locations, as they hinder effective T-cell infiltration and decrease the efficacy of immunotherapy. Additionally, we elucidated the interplay between POSTN+ CAFs and SPP1+ macrophages, whereby the former recruits the latter and triggers increased SPP1 expression via the IL-6/STAT3 signaling pathway. Moreover, we demonstrated a spatial correlation between POSTN+ CAFs and SPP1+ macrophages, revealing an immunosuppressive microenvironment that limits the immunotherapy response. Notably, we found that patients with elevated expression levels of both POSTN+ CAFs and SPP1+ macrophages achieved less therapeutic benefit in an immunotherapy cohort.

CONCLUSION

Our research elucidates light on the role of a particular subset of CAFs in immunotherapy resistance, emphasizing the potential benefits of targeting specific CAF subpopulations to improve clinical responses to immunotherapy.

Single-cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancers

BACKGROUND

The encoding of cell intrinsic drug resistance states in breast cancer reflects the contributions of genomic and non-genomic variations and requires accurate estimation of clonal fitness from co-measurement of transcriptomic and genomic data. Somatic copy number (CN) variation is the dominant mutational mechanism leading to transcriptional variation and notably contributes to platinum chemotherapy resistance cell states. Here, we deploy time series measurements of triple negative breast cancer (TNBC) single-cell transcriptomes, along with co-measured single-cell CN fitness, identifying genomic and transcriptomic mechanisms in drug-associated transcriptional cell states.

RESULTS

We present scRNA-seq data (53,641 filtered cells) from serial passaging TNBC patient-derived xenograft (PDX) experiments spanning 2.5 years, matched with genomic single-cell CN data from the same samples. Our findings reveal distinct clonal responses within TNBC tumors exposed to platinum. Clones with high drug fitness undergo clonal sweeps and show subtle transcriptional reversion, while those with weak fitness exhibit dynamic transcription upon drug withdrawal. Pathway analysis highlights convergence on epithelial-mesenchymal transition and cytokine signaling, associated with resistance. Furthermore, pseudotime analysis demonstrates hysteresis in transcriptional reversion, indicating generation of new intermediate transcriptional states upon platinum exposure.

CONCLUSIONS

Within a polyclonal tumor, clones with strong genotype-associated fitness under platinum remained fixed, minimizing transcriptional reversion upon drug withdrawal. Conversely, clones with weaker fitness display non-genomic transcriptional plasticity. This suggests CN-associated and CN-independent transcriptional states could both contribute to platinum resistance. The dominance of genomic or non-genomic mechanisms within polyclonal tumors has implications for drug sensitivity, restoration, and re-treatment strategies.

Establishing an oxidative stress mitochondria-related prognostic model in hepatocellular carcinoma based on multi-omics characteristics and machine learning computational framework

Hepatocellular carcinoma (HCC) has high incidence and mortality rates worldwide. Damaged mitochondria are characterized by the overproduction of reactive oxygen species (ROS), which can promote cancer development. The prognostic value of the interplay between mitochondrial function and oxidative stress in HCC requires further investigation. Gene expression data of HCC samples were collected from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and International Cancer Genome Consortium (ICGC). We screened prognostic oxidative stress mitochondria-related (OSMT) genes at the bulk transcriptome level. Based on multiple machine learning algorithms, we constructed a consensus oxidative stress mitochondria-related signature (OSMTS), which contained 26 genes. In addition, we identified six of these genes as having a suitable prognostic value for OSMTS to reduce the difficulty of clinical application. Univariate and multivariate analyses verified the OSMTS as an independent prognostic factor for overall survival (OS) in HCC patients. The OSMTS-related nomogram demonstrated to be a powerful tool for the clinical diagnosis of HCC. We observed differences in biological function and immune cell infiltration in the tumor microenvironment between the high- and low-risk groups. The highest expression of the OSMTS was detected in hepatocytes at the single-cell transcriptome level. Hepatocytes in the high- and low-risk groups differed significantly in terms of biological function and intercellular communication. Moreover, at the spatial transcriptome level, high expression of OSMTS was mainly in regions enriched in hepatocytes and B cells. Potential drugs targeting specific risk subgroups were identified. Our study revealed that the OSMTS can serve as a promising tool for prognosis prediction and precise intervention in HCC patients.

Developing an advanced diagnostic model for hepatocellular carcinoma through multi-omics integration leveraging diverse cell-death patterns

Introduction

Hepatocellular carcinoma (HCC), representing more than 80% of primary liver cancer cases, lacks satisfactory etiology and diagnostic methods. This study aimed to elucidate the role of programmed cell death-associated genes (CDRGs) in HCC by constructing a diagnostic model using single-cell RNA sequencing (scRNA-seq) and RNA sequencing (RNA-seq) data.

Methods

Six categories of CDRGs, including apoptosis, necroptosis, autophagy, pyroptosis, ferroptosis, and cuproptosis, were collected. RNA-seq data from blood-derived exosomes were sourced from the exoRBase database, RNA-seq data from cancer tissues from the TCGA database, and scRNA-seq data from the GEO database. Subsequently, we intersected the differentially expressed genes (DEGs) of the HCC cohort from exoRBase and TCGA databases with CDRGs, as well as DEGs obtained from single-cell datasets. Candidate biomarker genes were then screened using clinical indicators and a machine learning approach, resulting in the construction of a seven-gene diagnostic model for HCC. Additionally, scRNA-seq and spatial transcriptome sequencing (stRNA-seq) data of HCC from the Mendeley data portal were used to investigate the underlying mechanisms of these seven key genes and their association with immune checkpoint blockade (ICB) therapy. Finally, we validated the expression of key molecules in tissues and blood-derived exosomes through quantitative Polymerase Chain Reaction (qPCR) and immunohistochemistry experiments.

Results

Collectively, we obtained a total of 50 samples and 104,288 single cells. Following the meticulous screening, we established a seven-gene diagnostic model for HCC, demonstrating high diagnostic efficacy in both the exoRBase HCC cohort (training set: AUC = 1; testing set: AUC = 0.847) and TCGA HCC cohort (training set: AUC = 1; testing set: AUC = 0.976). Subsequent analysis revealed that HCC cluster 3 exhibited a higher stemness index and could serve as the starting point for the differentiation trajectory of HCC cells, also displaying more abundant interactions with other cell types in the microenvironment. Notably, key genes TRIB3 and NQO1 displayed elevated expression levels in HCC cells. Experimental validation further confirmed their elevated expression in both tumor tissues and blood-derived exosomes of cancer patients. Additionally, stRNA analysis not only substantiated these findings but also suggested that patients with high TRIB3 and NQO1 expression might respond more favorably to ICB therapy.

Conclusions

The seven-gene diagnostic model demonstrated remarkable accuracy in HCC screening, with TRIB3 emerging as a promising diagnostic tool and therapeutic target for HCC.

Spatial Dissection of the Immune Landscape of Solid Tumors to Advance Precision Medicine

Chemotherapeutics, radiation, targeted therapeutics, and immunotherapeutics each demonstrate clinical benefits for a small subset of patients with solid malignancies. Immune cells infiltrating the tumor and the surrounding stroma play a critical role in shaping cancer progression and modulating therapy response. They do this by interacting with the other cellular and molecular components of the tumor microenvironment. Spatial multi-omics technologies are rapidly evolving. Currently, such technologies allow high-throughput RNA and protein profiling and retain geographical information about the tumor microenvironment cellular architecture and the functional phenotype of tumor, immune, and stromal cells. An in-depth spatial characterization of the heterogeneous tumor immune landscape can improve not only the prognosis but also the prediction of therapy response, directing cancer patients to more tailored and efficacious treatments. This review highlights recent advancements in spatial transcriptomics and proteomics profiling technologies and the ways these technologies are being applied for the dissection of the immune cell composition in solid malignancies in order to further both basic research in oncology and the implementation of precision treatments in the clinic.

Advances and challenges of exosome-derived noncoding RNAs for hepatocellular carcinoma diagnosis and treatment

Exosomes, also termed extracellular vesicles (EVs), are an important component of the tumor microenvironment (TME) and exert versatile effects on the molecular communications in the TME of hepatocellular carcinoma (HCC). Exosome-mediated intercellular communication is closely associated with the tumorigenesis and development of HCC. Exosomes can be extracted through ultracentrifugation and size exclusion, followed by molecular analysis through sequencing. Increasing studies have confirmed the important roles of exosome-derived ncRNAs in HCC, including tumorigenesis, progression, immune escape, and treatment resistance. Due to the protective membrane structure of exosomes, the ncRNAs carried by exosomes can evade degradation by enzymes in body fluids and maintain good expression stability. Thus, exosome-derived ncRNAs are highly suitable as biomarkers for the diagnosis and prognostic prediction of HCC, such as exosomal miR-21-5p, miR-221-3p and lncRNA-ATB. In addition, substantial studies revealed that the up-or down-regulation of exosome-derived ncRNAs had an important impact on HCC progression and response to treatment. Exosomal biomarkers, such as miR-23a, lncRNA DLX6-AS1, miR-21-5p, lncRNA TUC339, lncRNA HMMR-AS1 and hsa_circ_0004658, can reshape immune microenvironment by regulating M2-type macrophage polarization and then promote HCC development. Therefore, by controlling exosome biogenesis and modulating exosomal ncRNA levels, HCC may be inhibited or eliminated. In this current review, we summarized the recent findings on the role of exosomes in HCC progression and analyzed the relationship between exosome-derived ncRNAs and HCC diagnosis and treatment.

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.

Integrated bulk and single-cell RNA sequencing identifies an aneuploidy-based gene signature to predict sensitivity of lung adenocarcinoma to traditional chemotherapy drugs and patients' prognosis

Background

Patients with lung adenocarcinoma (LUAD) often develop a poor prognosis. Currently, researches on prognostic and immunotherapeutic capacity of aneuploidy-related genes in LUAD are limited.

Methods

Genes related to aneuploidy were screened based on bulk RNA sequencing data from public databases using Spearman method. Next, univariate Cox and Lasso regression analyses were performed to establish an aneuploidy-related riskscore (ARS) model. Results derived from bioinformatics analysis were further validated using cellular experiments. In addition, typical LUAD cells were identified by subtype clustering, followed by SCENIC and intercellular communication analyses. Finally, ESTIMATE, ssGSEA and CIBERSORT algorithms were employed to analyze the potential relationship between ARS and tumor immune environment.

Results

A five-gene ARS signature was developed. These genes were abnormally high-expressed in LUAD cell lines, and in particular the high expression of CKS1B promoted the proliferative, migratory and invasive phenotypes of LUAD cell lines. Low ARS group had longer overall survival time, higher degrees of inflammatory infiltration, and could benefit more from receiving immunotherapy. Patients in low ASR group responded more actively to traditional chemotherapy drugs (Erlotinib and Roscovitine). The scRNA-seq analysis annotated 17 cell subpopulations into seven cell clusters. Core transcription factors (TFs) such as CREB3L1 and CEBPD were enriched in high ARS cell group, while TFs such as BCLAF1 and UQCRB were enriched in low ARS cell group. CellChat analysis revealed that high ARS cell groups communicated with immune cells via SPP1 (ITGA4-ITGB1) and MK (MDK-NCl) signaling pathways.

Conclusion

In this research, integrative analysis based on the ARS model provided a potential direction for improving the diagnosis and treatment of LUAD.

Advances in spatial transcriptomics and its applications in cancer research

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

Prediction of Efficacy for Atezolizumab/Bevacizumab in Unresectable Hepatocellular Carcinoma with Hepatobiliary-Phase Gadolinium Ethoxybenzyl-Diethylenetriaminepentaacetic Acid MRI

BACKGROUND

This study aimed to examine whether the coefficient of variation (CV) in the hepatobiliary-phase (HBP) of Gd-EOB-DTPA-MRI could be an independent predictive factor for tumor progression.

METHODS

Patients who underwent Gd-EOB-DTPA-MRI before Atezolizumab/bevacizumab therapy at six affiliated institutions between 2018 and 2022 were included. CV for each patient was calculated as the mean value for up to five tumors larger than 10 mm, and CV of the whole tumor was calculated using LIFEx software. The tumor response was evaluated within 6-10 weeks. The primary endpoint was to investigate the predictive factors, including CV, related to tumor progression using logistic regression analysis. The secondary endpoints were tumor response rate and progression-free survival (PFS) based on CV.

RESULTS

Of the 46 enrolled patients, 13 (28.3%) underwent early progressive disease. Multivariate analysis revealed that a high CV (≥0.22) was an independent predictive factor for tumor progression (p = 0.043). Patients with a high CV had significantly frequent PD than those with a low CV (43.5 vs. 13.0%, p = 0.047). Patients with a high CV tended to have shorter PFS than those with a low CV (3.5 vs. 6.7 months, p = 0.071).

CONCLUSION

Quantitative analysis using CV in the HBP of Gd-EOB-DTPA-MRI may be useful for predicting tumor progression for atezolizumab/bevacizumab therapy.

IFIT1 + neutrophil is a causative factor of immunosuppressive features of poorly cohesive carcinoma (PCC)

The importance of the immune microenvironment in poorly cohesive carcinoma (PCC) has been highlighted due to its limited response rate to conventional therapy and emerging treatment resistance. A combination of clinical cohorts, bioinformatics analyses, and functional/molecular experiments revealed that high infiltration of Interferon Induced Protein with Tetratricopeptide Repeats 1 (IFIT1) + tumor-associated neutrophils (TANs) is a distinguishing feature of PCC patients. Upregulation of IFIT1 + TANs promote migration and invasion of gastric cancer (GC) cell lines (MKN45 and MKN74) and stimulates the growth of cell-derived xenograft models. Besides, by promoting macrophage secreted phosphoprotein 1 (SPP1) expression and facilitating cancer-associated fibroblast and endothelial cell recruitment and activation through TANs, IFIT1 promotes a mesenchymal phenotype, which is associated with a poor prognosis. Importantly, compared to non-PCC (NPCC), PCC tumors is more immunosuppressive. Mechanistically, IFIT1 can be stimulated by IFN-γ and contributes to the expression of Programmed Cell Death 1 Ligand (PDL1) in TANs. We demonstrated in mouse models that IFIT1 + PDL1 + TANs can induce acquired resistance to anti-PD-1 immunotherapy, which may be responsible for the difficulty of PCC patients to benefit from immunotherapy. This work highlights the role of IFIT1 + TANs in mediating the remodeling of the tumor immune microenvironment and immunotherapeutic resistance and introduces IFIT1 + TANs as a promising target for precision therapy of PCC.

The high expression of ADRM1 in hepatocellular carcinoma is closely related to tumor immune infiltration and is regulated by miR-891a-5p

Liver cancer is one of the most common malignant tumors worldwide. Although some progress has been made in the diagnosis and treatment of Hepatocellular carcinoma (HCC), the diagnosis and treatment of HCC is still facing great challenges because of the high mortality rate and poor prognosis of HCC. The purpose of this study was to explore the relationship between adhesion-regulating molecule1 (ADRM1), and liver cancer, and the relationship between prognoses. ADRM1 is highly expressed in tumors and is closely associated with the prognosis of patients with liver cancer. In our previous study, we found that ADRM1 was highly expressed in HCC and was closely related to tumor immune and immune checkpoint levels in HCC. We validated the immune expression of ADRM1 in liver cancer cells using flow cytometry. In hepatocellular carcinoma tissues, miR-891a-5p regulates ADRM1. Upregulation of miR-891a-5p upregulates ADRM1, and downregulation of miR-891a-5p downregulates ADRM1. It is suggested that ADRM1 plays a key role in the occurrence and development of hepatocellular carcinoma. This study is expected to provide new ideas for the research and development of anti-HCC drugs targeting miR-891a-5p/ADRM1. However, further trials are needed to confirm these results and explore the actual results in patients with HCC.

T cell-related ubiquitination genes as prognostic indicators in hepatocellular carcinoma

BACKGROUND

T lymphocytes, integral to the adaptive immune system, wield pivotal influence in bolstering anti-tumor responses, and are strictly regulated by ubiquitination modification. The objective of this investigation was to devise a novel prognostic and immunotherapeutic efficacy predictor for hepatocellular carcinoma patients utilizing T cell-related ubiquitination genes (TCRUG).

METHOD

The single-cell RNA sequencing (scRNA-seq) data and bulk RNA data of HCC patients are derived from the GEO database and TCGA database. Based on the processing of scRNA-seq, T cell marker genes are obtained and TCRUG is obtained. Further combined with WGCNA, differential analysis, univariate Cox regression analysis, LASSO analysis, and multivariate Cox regression analysis to filter and screen TCRUG. Finally construct a riskscore for predicting the prognosis of HCC patients, the predictive effect of which is validated in the GEO dataset. In addition, we also studied the correlation between riskscore and immunotherapy efficacy. Finally, the oncogenic role of UBE2E1 in HCC was explored through various in vitro experiments.

RESULT

Based on patients' scRNA-seq data, we finally obtained 3050 T cell marker genes. Combined with bulk RNA data and clinical data from the TCGA database, we constructed a riskscore that accurately predicts the prognosis of HCC patients. This riskscore is an independent prognostic factor for HCC and is used to construct a convenient column chart. In addition, we found that the high-risk group is more suitable for immunotherapy. Finally, the proliferation, migration, and invasion abilities of HCC cells significantly decreased after UBE2E1 expression reduction.

CONCLUSION

This study developed a riskscore based on TCRUG that can accurately and stably predict the prognosis of HCC patients. This riskscore is also effective in predicting the immune therapy response of HCC patients.

Osteopontin/SPP1: a potential mediator between immune cells and vascular calcification

Vascular calcification (VC) is considered a common pathological process in various vascular diseases. Accumulating studies have confirmed that VC is involved in the inflammatory response in heart disease, and SPP1+ macrophages play an important role in this process. In VC, studies have focused on the physiological and pathological functions of macrophages, such as pro-inflammatory or anti-inflammatory cytokines and pro-fibrotic vesicles. Additionally, macrophages and activated lymphocytes highly express SPP1 in atherosclerotic plaques, which promote the formation of fatty streaks and plaque development, and SPP1 is also involved in the calcification process of atherosclerotic plaques that results in heart failure, but the crosstalk between SPP1-mediated immune cells and VC has not been adequately addressed. In this review, we summarize the regulatory effect of SPP1 on VC in T cells, macrophages, and dendritic cells in different organs' VC, which could be a potential therapeutic target for VC.

A Bibliometric Analysis of the Spatial Transcriptomics Literature from 2006 to 2023

In recent years, spatial transcriptomics (ST) research has become a popular field of study and has shown great potential in medicine. However, there are few bibliometric analyses in this field. Thus, in this study, we aimed to find and analyze the frontiers and trends of this medical research field based on the available literature. A computerized search was applied to the WoSCC (Web of Science Core Collection) Database for literature published from 2006 to 2023. Complete records of all literature and cited references were extracted and screened. The bibliometric analysis and visualization were performed using CiteSpace, VOSviewer, Bibliometrix R Package software, and Scimago Graphica. A total of 1467 papers and reviews were included. The analysis revealed that the ST publication and citation results have shown a rapid upward trend over the last 3 years. Nature Communications and Nature were the most productive and most co-cited journals, respectively. In the comprehensive global collaborative network, the United States is the country with the most organizations and publications, followed closely by China and the United Kingdom. The author Joakim Lundeberg published the most cited paper, while Patrik L. Ståhl ranked first among co-cited authors. The hot topics in ST are tissue recognition, cancer, heterogeneity, immunotherapy, differentiation, and models. ST technologies have greatly contributed to in-depth research in medical fields such as oncology and neuroscience, opening up new possibilities for the diagnosis and treatment of diseases. Moreover, artificial intelligence and big data drive additional development in ST fields.

Safety and Preliminary Efficacy of Pembrolizumab Following Transarterial Chemoembolization for Hepatocellular Carcinoma: The PETAL Phase Ib Study

PURPOSE

Transarterial chemoembolization (TACE) may prime adaptive immunity and enhance immunotherapy efficacy. PETAL evaluated safety, preliminary activity of TACE plus pembrolizumab and explored mechanisms of efficacy.

PATIENTS AND METHODS

Patients with liver-confined hepatocellular carcinoma (HCC) were planned to receive up to two rounds of TACE followed by pembrolizumab 200 mg every 21 days commencing 30 days post-TACE until disease progression or unacceptable toxicity for up to 1 year. Primary endpoint was safety, with assessment window of 21 days from pembrolizumab initiation. Secondary endpoints included progression-free survival (PFS) and evaluation of tumor and host determinants of response.

RESULTS

Fifteen patients were included in the safety and efficacy population: 73% had nonviral cirrhosis; median age was 72 years. Child-Pugh class was A in 14 patients. Median tumor size was 4 cm. Ten patients (67%) received pembrolizumab after one TACE; 5 patients after two (33%). Pembrolizumab yielded no synergistic toxicity nor dose-limiting toxicities post-TACE. Treatment-related adverse events occurred in 93% of patients, most commonly skin rash (40%), fatigue, and diarrhea (27%). After a median follow-up of 38.5 months, objective response rate 12 weeks post-TACE was 53%. PFS rate at 12 weeks was 93% and median PFS was 8.95 months [95% confidence interval (CI): 7.30-NE (not estimable)]. Median duration of response was 7.3 months (95% CI: 6.3-8.3). Median overall survival was 33.5 months (95% CI: 11.6-NE). Dynamic changes in peripheral T-cell subsets, circulating tumor DNA, serum metabolites, and in stool bacterial profiles highlight potential mechanisms of action of multimodal therapy.

CONCLUSIONS

TACE plus pembrolizumab was tolerable with no evidence of synergistic toxicity, encouraging further clinical development of immunotherapy alongside TACE.

Proteomic, single-cell and bulk transcriptomic analysis of plasma and tumor tissues unveil core proteins in response to anti-PD-L1 immunotherapy in triple negative breast cancer

BACKGROUND

Anti-PD-1/PD-L1 treatment has achieved durable responses in TNBC patients, whereas a fraction of them showed non-sensitivity to the treatment and the mechanism is still unclear.

METHODS

Pre- and post-treatment plasma samples from triple negative breast cancer (TNBC) patients treated with immunotherapy were measured by tandem mass tag (TMT) mass spectrometry. Public proteome data of lung cancer and melanoma treated with immunotherapy were employed to validate the findings. Blood and tissue single-cell RNA sequencing (scRNA-seq) data of TNBC patients treated with or without immunotherapy were analyzed to identify the derivations of plasma proteins. RNA-seq data from IMvigor210 and other cancer types were used to validate plasma proteins in predicting response to immunotherapy.

RESULTS

A random forest model constructed by FAP, LRG1, LBP and COMP could well predict the response to immunotherapy. The activation of complement cascade was observed in responders, whereas FAP and COMP showed a higher abundance in non-responders and negative correlated with the activation of complements. scRNA-seq and bulk RNA-seq analysis suggested that FAP, COMP and complements were derived from fibroblasts of tumor tissues.

CONCLUSIONS

We constructe an effective plasma proteomic model in predicting response to immunotherapy, and find that FAP+ and COMP+ fibroblasts are potential targets for reversing immunotherapy resistance.

Study on the mechanism of heterogeneous tumor-associated macrophages in three subtypes of breast cancer through the integration of single-cell RNA sequencing and in vitro experiments

BACKGROUND

Tumor-associated macrophages (TAM) exert a significant influence on the progression and heterogeneity of various subtypes of breast cancer (BRCA). However, the roles of heterogeneous TAM within BRCA subtypes remain unclear. Therefore, this study sought to elucidate the role of TAM across the following three BRCA subtypes: triple-negative breast cancer, luminal, and HER2.

MATERIALS AND METHODS

This investigation aimed to delineate the variations in marker genes, drug sensitivity, and cellular communication among TAM across the three BRCA subtypes. We identified specific ligand-receptor (L-R) pairs and downstream mechanisms regulated by VEGFA-VEGFR1, SPP1-CD44, and SPP1-ITGB1 L-R pairs. Experimental verification of these pairs was conducted by co-culturing macrophages with three subtypes of BRCA cells.

RESULTS

Our findings reveal the heterogeneity of macrophages within the three BRCA subtypes, evidenced by variations in marker gene expression, composition, and functional characteristics. Notably, heterogeneous TAM were found to promote invasive migration and epithelial-mesenchymal transition (EMT) in MDA-MB-231, MCF-7, and SKBR3 cells, activating NF-κB pathway via P38 MAPK, TGF-β1, and AKT, respectively, through distinct VEGFA-VEGFR1, SPP1-CD44, and SPP1-ITGB1 L-R pairs. Inhibition of these specific L-R pairs effectively reversed EMT, migration, and invasion of each cancer cells. Furthermore, we observed a correlation between ligand gene expression and TAM sensitivity to anticancer drugs, suggesting a potential strategy for optimizing personalized treatment guidance.

CONCLUSION

Our study highlights the capacity of heterogeneous TAM to modulate biological functions via distinct pathways mediated by specific L-R pairs within diverse BRCA subtypes. This study might provide insights into precision immunotherapy of different subtypes of BRCA.

Multi-omic profiling reveals potential biomarkers of hepatocellular carcinoma prognosis and therapy response among mitochondria-associated cell death genes in the context of 3P medicine

Background

Cancer cell growth, metastasis, and drug resistance are major challenges in treating liver hepatocellular carcinoma (LIHC). However, the lack of comprehensive and reliable models hamper the effectiveness of the predictive, preventive, and personalized medicine (PPPM/3PM) strategy in managing LIHC.

Methods

Leveraging seven distinct patterns of mitochondrial cell death (MCD), we conducted a multi-omic screening of MCD-related genes. A novel machine learning framework was developed, integrating 10 machine learning algorithms with 67 different combinations to establish a consensus mitochondrial cell death index (MCDI). This index underwent rigorous evaluation across training, validation, and in-house clinical cohorts. A comprehensive multi-omics analysis encompassing bulk, single-cell, and spatial transcriptomics was employed to achieve a deeper insight into the constructed signature. The response of risk subgroups to immunotherapy and targeted therapy was evaluated and validated. RT-qPCR, western blotting, and immunohistochemical staining were utilized for findings validation.

Results

Nine critical differentially expressed MCD-related genes were identified in LIHC. A consensus MCDI was constructed based on a 67-combination machine learning computational framework, demonstrating outstanding performance in predicting prognosis and clinical translation. MCDI correlated with immune infiltration, Tumor Immune Dysfunction and Exclusion (TIDE) score and sorafenib sensitivity. Findings were validated experimentally. Moreover, we identified PAK1IP1 as the most important gene for predicting LIHC prognosis and validated its potential as an indicator of prognosis and sorafenib response in our in-house clinical cohorts.

Conclusion

This study developed a novel predictive model for LIHC, namely MCDI. Incorporating MCDI into the PPPM framework will enhance clinical decision-making processes and optimize individualized treatment strategies for LIHC patients.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00362-8.

A novel prognostic model for predicting patient survival and immunotherapy responsiveness in hepatocellular carcinoma: insights into the involvement of T-cell proliferation

BACKGROUND

The cancer-associated biological mechanisms and the implementation of immunotherapy are heavily impacted by the activities of T cells, consequently influencing the effectiveness of therapeutic interventions. Nevertheless, the mechanistic actions of T-cell proliferation in response to immunotherapy and the overall prognosis of individuals diagnosed with hepatocellular carcinoma (HCC) remains insufficiently understood. The present work seeks to present a comprehensive analysis immune landscape in the context of HCC.

METHODS

To achieve this objective, both clinical data and RNA sequencing data were acquired from authoritative databases such as The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO).

RESULTS

Through the utilization of consensus clustering techniques, distinct molecular subtypes associated with T-cell proliferation were delineated. Following this, seven genes of prognostic significance were identified via a combination of Cox and Lasso regression analyses. By integrating these genes into a prognostic signature, the predictive capability of the model was verified through an examination of internal and external datasets. Moreover, immunohistochemistry and qRT-PCR tests have verified the reliability of prognostic markers. Notably, the high-risk group exhibited elevated expression of immune checkpoint genes as well as higher benefit in terms of drug sensitivity testing, as determined by the Chi-square test (P < 0.001). The risk score derived from the prognostic signature depicted considerable efficacy in predicting the survival outcomes of HCC cases.

CONCLUSIONS

Overall, prognostic markers may become valuable predictive tool for individuals diagnosed with HCC, allowing for the prediction of their prognosis as well as the assessment of their immunological condition and response to immunotherapy.

Mgp High-Expressing MSCs Orchestrate the Osteoimmune Microenvironment of Collagen/Nanohydroxyapatite-Mediated Bone Regeneration

Activating autologous stem cells after the implantation of biomaterials is an important process to initiate bone regeneration. Although several studies have demonstrated the mechanism of biomaterial-mediated bone regeneration, a comprehensive single-cell level transcriptomic map revealing the influence of biomaterials on regulating the temporal and spatial expression patterns of mesenchymal stem cells (MSCs) is still lacking. Herein, the osteoimmune microenvironment is depicted around the classical collagen/nanohydroxyapatite-based bone repair materials via combining analysis of single-cell RNA sequencing and spatial transcriptomics. A group of functional MSCs with high expression of matrix Gla protein (Mgp) is identified, which may serve as a pioneer subpopulation involved in bone repair. Remarkably, these Mgp high-expressing MSCs (MgphiMSCs) exhibit efficient osteogenic differentiation potential and orchestrate the osteoimmune microenvironment around implanted biomaterials, rewiring the polarization and osteoclastic differentiation of macrophages through the Mdk/Lrp1 ligand-receptor pair. The inhibition of Mdk/Lrp1 activates the pro-inflammatory programs of macrophages and osteoclastogenesis. Meanwhile, multiple immune-cell subsets also exhibit close crosstalk between MgphiMSCs via the secreted phosphoprotein 1 (SPP1) signaling pathway. These cellular profiles and interactions characterized in this study can broaden the understanding of the functional MSC subpopulations at the early stage of biomaterial-mediated bone regeneration and provide the basis for materials-designed strategies that target osteoimmune modulation.

Cancer-associated fibroblasts in pancreatic ductal adenocarcinoma therapy: Challenges and opportunities

Pancreatic ductal adenocarcinoma (PDAC) is a solid organ malignancy with a high mortality rate. Statistics indicate that its incidence has been increasing as well as the associated deaths. Most patients with PDAC show poor response to therapies making the clinical management of this cancer difficult. Stromal cells in the tumor microenvironment (TME) contribute to the development of resistance to therapy in PDAC cancer cells. Cancer-associated fibroblasts (CAFs), the most prevalent stromal cells in the TME, promote a desmoplastic response, produce extracellular matrix proteins and cytokines, and directly influence the biological behavior of cancer cells. These multifaceted effects make it difficult to eradicate tumor cells from the body. As a result, CAF-targeting synergistic therapeutic strategies have gained increasing attention in recent years. However, due to the substantial heterogeneity in CAF origin, definition, and function, as well as high plasticity, majority of the available CAF-targeting therapeutic approaches are not effective, and in some cases, they exacerbate disease progression. This review primarily elucidates on the effect of CAFs on therapeutic efficiency of various treatment modalities, including chemotherapy, radiotherapy, immunotherapy, and targeted therapy. Strategies for CAF targeting therapies are also discussed.

Hepatocellular Carcinoma LINC01116 Outcompetes T Cells for Linoleic Acid and Accelerates Tumor Progression

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer with a highly immunosuppressive tumor microenvironment and a typical pattern of disturbances in hepatic lipid metabolism. Long non-coding RNAs are shown to play an important role in the regulation of gene expression, but much remains unknown between tumor microenvironment and lipid metabolism as a bridging molecule. Here, long intergenic nonprotein coding RNA 01116 (LINC01116) acts as this molecular which is frequently upregulated in HCC patients and associated with HCC progression in vitro and in vivo is identified. Mechanistically, LINC01116 stabilizes EWS RNA-binding protein 1 (EWSR1) by preventing RAD18 E3 Ubiquitin Protein Ligase (RAD18) -mediated ubiquitination. The enhanced EWSR1 protein upregulates peroxisome proliferator activated receptor alpha (PPARA) and fatty acid binding protein1 (FABP1) expression, a long-chain fatty acid (LCFA) transporter, and thus cancer cells outcompete T cells for LCFAs, especially linoleic acid, for seeding their own growth, leading to T cell malfunction and HCC malignant progression. In a preclinical animal model, the blockade of LINC01116 leads to enhanced efficacy of anti-PD1 treatment accompanied by increased cytotoxic T cell and decreased exhausted T cell infiltration. Collectively, LINC01116 is an immunometabolic lncRNA and the LINC01116-EWSR1-PPARA-FABP1 axis may be targetable for cancer immunotherapy.

IFRD1 promotes tumor cells "low-cost" survival under glutamine starvation via inhibiting histone H1.0 nucleophagy

Glutamine addiction represents a metabolic vulnerability of cancer cells; however, effective therapeutic targeting of the pathways involved remains to be realized. Here, we disclose the critical role of interferon-related developmental regulator 1 (IFRD1) in the adaptive survival of hepatocellular carcinoma (HCC) cells during glutamine starvation. IFRD1 is induced under glutamine starvation to inhibit autophagy by promoting the proteasomal degradation of the key autophagy regulator ATG14 in a TRIM21-dependent manner. Conversely, targeting IFRD1 in the glutamine-deprived state increases autophagy flux, triggering cancer cell exhaustive death. This effect largely results from the nucleophilic degradation of histone H1.0 and the ensuing unchecked increases in ribosome and protein biosynthesis associated with globally enhanced chromatin accessibility. Intriguingly, IFRD1 depletion in preclinical HCC models synergizes with the treatment of the glutaminase-1 selective inhibitor CB-839 to potentiate the effect of limiting glutamine. Together, our findings reveal how IFRD1 supports the adaptive survival of cancer cells under glutamine starvation, further highlighting the potential of IFRD1 as a therapeutic target in anti-cancer applications.

A Capillary-Force-Driven, Single-Cell Transfer Method for Studying Rare Cells

The characterization of individual cells within heterogeneous populations (e.g., rare tumor cells in healthy blood cells) has a great impact on biomedical research. To investigate the properties of these specific cells, such as genetic biomarkers and/or phenotypic characteristics, methods are often developed for isolating rare cells among a large number of background cells before studying their genetic makeup and others. Prior to using real-world samples, these methods are often evaluated and validated by spiking cells of interest (e.g., tumor cells) into a sample matrix (e.g., healthy blood) as model samples. However, spiking tumor cells at extremely low concentrations is challenging in a standard laboratory setting. People often circumvent the problem by diluting a solution of high-concentration cells, but the concentration becomes inaccurate after series dilution due to the fact that a cell suspension solution can be inhomogeneous, especially when the cell concentration is very low. We report on an alternative method for low-cost, accurate, and reproducible low-concentration cell spiking without the use of external pumping systems. By inducing a capillary force from sudden pressure drops, a small portion of the cellular membrane was aspirated into the reservoir tip, allowing for non-destructive single-cell transfer. We investigated the surface membrane tensions induced by cellular aspiration and studied a range of tip/tumor cell diameter combinations, ensuring that our method does not affect cell viability. In addition, we performed single-cell capture and transfer control experiments using human acute lymphoblastic leukemia cells (CCRF-CEM) to develop calibrated data for the general production of low-concentration samples. Finally, we performed affinity-based tumor cell isolation using this method to generate accurate concentrations ranging from 1 to 15 cells/mL.

Macrophage-coated tumor cluster aggravates hepatoma invasion and immunotherapy resistance via generating local immune deprivation

Immune checkpoint inhibitors (ICIs) represent a promising treatment for hepatocellular carcinoma (HCC) due to their capacity for abundant lymphocyte infiltration. However, some patients with HCC respond poorly to ICI therapy due to the presence of various immunosuppressive factors in the tumor microenvironment. Our research reveals that a macrophage-coated tumor cluster (MCTC) signifies a unique spatial structural organization in HCC correlating with diminished recurrence-free survival and overall survival in a total of 572 HCC cases from 3 internal cohorts and 2 independent external validation cohorts. Mechanistically, tumor-derived macrophage-associated lectin Mac-2 binding protein (M2BP) induces MCTC formation and traps immunocompetent cells at the edge of MCTCs to induce intratumoral cytotoxic T cell exclusion and local immune deprivation. Blocking M2BP with a Mac-2 antagonist might provide an effective approach to prevent MCTC formation, enhance T cell infiltration, and thereby improve the efficacy of ICI therapy in HCC.

HIF2A mediates lineage transition to aggressive phenotype of cancer-associated fibroblasts in lung cancer brain metastasis

Brain metastasis is the most devasting form of lung cancer. Recent studies highlight significant differences in the tumor microenvironment (TME) between lung cancer brain metastasis (LCBM) and primary lung cancer, which contribute significantly to tumor progression and drug resistance. Cancer-associated fibroblasts (CAFs) are the major component of pro-tumor TME with high plasticity. However, the lineage composition and function of CAFs in LCBM remain elusive. By reanalyzing single-cell RNA sequencing (scRNA-seq) data (GSE131907) from lung cancer patients with different stages of metastasis comprising primary lesions and brain metastasis, we found that CAFs undergo distinctive lineage transition during LCBM under a hypoxic situation, which is directly driven by hypoxia-induced HIF-2α activation. Transited CAFs enhance angiogenesis through VEGF pathways, trigger metabolic reprogramming, and promote the growth of tumor cells. Bulk RNA sequencing data was utilized as validation cohorts. Multiplex immunohistochemistry (mIHC) assay was performed on four paired samples of brain metastasis and their primary lung cancer counterparts to validate the findings. Our study revealed a novel mechanism of lung cancer brain metastasis featuring HIF-2α-induced lineage transition and functional alteration of CAFs, which offers potential therapeutic targets.

QL1604 combined with bevacizumab as an innovative first-line treatment for HCC patient with extensive metastasis who showed remarkable effect: a case report

Hepatocellular carcinoma (HCC) is a common and highly malignant tumor with poor outcomes, especially when it metastasizes. In this report, we present the case of a 64-year-old male patient diagnosed with recurrence and multiple metastases of HCC 7 years after surgery. As the tumor invaded the spinal canal and pressed on the spinal cord, the patient experienced paralysis in the lower limbs. After undergoing surgical resection for spinal decompression, the patient chose an innovative regimen: QL1604 200 mg every 3 weeks plus bevacizumab 675 mg every 3 weeks as first-line treatment. From July 2022 to February 2024, the patient has regularly received the treatment. During the treatment, the paralysis symptoms of the patient gradually improved, and the motor function of the lower limbs completely returned to normal. When re-evaluated his spinal cord injury, the Frankel grade of the patient was downgraded from C to E. The tumor shrank to reach a state of PR and lasted for one and a half years. QL1604 combined with bevacizumab demonstrated excellent efficacy and minimal side effects in this patient. This new combined therapy holds potential as a first-line treatment strategy.

LARS1 is a Prognostic Biomarker and Exhibits a Correlation with Immune Infiltrates in Hepatocellular Carcinoma

Purpose

To study the relationship between LARS1 expression and immune infiltration and prognosis in hepatocellular carcinoma (HCC).

Patients and Methods

The clinical characteristics together with LARS1 expression levels were obtained from the TCGA database. Immunohistochemistry confirmed LARS1 expression levels in paraneoplastic and tumor tissues. To investigate LARS1-related downstream molecules, a network of protein-protein interactions (PPIs) and the Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) were built. Furthermore, gene set enrichment analysis (GSEA) was used to analyze the pathways associated with LARS1 expression, whereas Single-sample GSEA (ssGSEA) was applied to perform an association study between immune infiltration and LARS1 gene expression. The TISCH Database and the TISIDB database were used to compare the difference of LARS1 expression in hepatocellular carcinoma and immunomodulators.

Results

In comparison to that in normal tissues, the LARS1 expression level was elevated in tumor tissues. LARS1 expression exhibited substantial correlation with AFP, Histologic grade, pathologic stage, Residual tumor, and Vascular invasion in HCC. Higher LARS1 expression in HCC was linked to lower progression-free survival (PFS), disease-specific survival (DSS), and overall survival (OS). According to the GO/KEGG study, the important biological process (neutral lipid metabolic process), cellular component (triglyceride-rich plasma lipoprotein), molecular functions (lipase inhibitor activity), and KEGG pathway (cholesterol metabolism) could be a probable function mechanism in promoting HCC. Various pathways as per GSEA revealed that they were enriched in samples with elevated LARS1 expression. The expression level of LARS1 in malignant tumor cells after immunotherapy was significantly higher than that before immunotherapy. LARS1 was also remarkably linked to the infiltration level and the immunomodulators.

Conclusion

LARS1 can be used as a biomarker of HCC, which is associated to immune infiltration of HCC.

Single-cell and spatial transcriptomics reveal metastasis mechanism and microenvironment remodeling of lymph node in osteosarcoma

BACKGROUND

Osteosarcoma (OS) is the most common primary malignant bone tumor and is highly prone to metastasis. OS can metastasize to the lymph node (LN) through the lymphatics, and the metastasis of tumor cells reestablishes the immune landscape of the LN, which is conducive to the growth of tumor cells. However, the mechanism of LN metastasis of osteosarcoma and remodeling of the metastatic lymph node (MLN) microenvironment is not clear.

METHODS

Single-cell RNA sequencing of 18 samples from paracancerous, primary tumor, and lymph nodes was performed. Then, new signaling axes closely related to metastasis were identified using bioinformatics, in vitro experiments, and immunohistochemistry. The mechanism of remodeling of the LN microenvironment in tumor cells was investigated by integrating single-cell and spatial transcriptomics.

RESULTS

From 18 single-cell sequencing samples, we obtained 117,964 cells. The pseudotime analysis revealed that osteoblast(OB) cells may follow a differentiation path from paracancerous tissue (PC) → primary tumor (PT) → MLN or from PC → PT, during the process of LN metastasis. Next, in combination of bioinformatics, in vitro and in vivo experiments, and immunohistochemistry, we determined that ETS2/IBSP, a new signal axis, might promote LN metastasis. Finally, single-cell and spatial dissection uncovered that OS cells could reshape the microenvironment of LN by interacting with various cell components, such as myeloid, cancer-associated fibroblasts (CAFs), and NK/T cells.

CONCLUSIONS

Collectively, our research revealed a new molecular mechanism of LN metastasis and clarified how OS cells influenced the LN microenvironment, which might provide new insight for blocking LN metastasis.

Macrophages Orchestrate the Liver Tumor Microenvironment

Liver cancer is one of the leading causes of cancer-related mortality. Hepatocellular carcinoma and cholangiocarcinoma are the most common types, and despite numerous advances, therapeutic options still remain poor for these cancer patients. Tumor development and progression strictly depend on a supportive tumor microenvironment (TME). Tumor-associated macrophages (TAMs) are the most abundant immune cells population within a tumorigenic liver; they sustain cancer cells' growth and invasiveness, and their presence is correlated with a poor prognosis. Furthermore, TAM cross-talk with cells and components of the TME promotes immunosuppression, a desmoplastic response, and angiogenesis. In this review, we summarize the latest advances in understanding TAM heterogeneity and function, with a particular focus on TAM modulation of the TME. We also discuss the potential of targeting macrophage subpopulations and how this is now being exploited in current clinical trials for the treatment of liver cancer.

Emerging Roles of Spatial Transcriptomics in Liver Research

Spatial transcriptomics, leveraging sequencing- and imaging-based techniques, has emerged as a groundbreaking technology for mapping gene expression within the complex architectures of tissues. This approach provides an in-depth understanding of cellular and molecular dynamics across various states of healthy and diseased livers. Through the integration of sophisticated bioinformatics strategies, it enables detailed exploration of cellular heterogeneity, transitions in cell states, and intricate cell-cell interactions with remarkable precision. In liver research, spatial transcriptomics has been particularly revelatory, identifying distinct zonated functions of hepatocytes that are crucial for understanding the metabolic and detoxification processes of the liver. Moreover, this technology has unveiled new insights into the pathogenesis of liver diseases, such as the role of lipid-associated macrophages in steatosis and endothelial cell signals in liver regeneration and repair. In the domain of liver cancer, spatial transcriptomics has proven instrumental in delineating intratumor heterogeneity, identifying supportive microenvironmental niches and revealing the complex interplay between tumor cells and the immune system as well as susceptibility to immune checkpoint inhibitors. In conclusion, spatial transcriptomics represents a significant advance in hepatology, promising to enhance our understanding and treatment of liver diseases.

Overcoming Resistance to Immune Checkpoint Blockade in Liver Cancer with Combination Therapy: Stronger Together?

Primary liver cancer, represented mainly by hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (CCA), is one of the most common and deadliest tumors worldwide. While surgical resection or liver transplantation are the best option in early disease stages, these tumors often present in advanced stages and systemic treatment is required to improve survival time. The emergence of immune checkpoint inhibitor (ICI) therapy has had a positive impact especially on the treatment of advanced cancers, thereby establishing immunotherapy as part of first-line treatment in HCC and CCA. Nevertheless, low response rates reflect on the usually cold or immunosuppressed tumor microenvironment of primary liver cancer. In this review, we aim to summarize mechanisms of resistance leading to tumor immune escape with a special focus on the composition of tumor microenvironment in both HCC and CCA, also reflecting on recent important developments in ICI combination therapy. Furthermore, we discuss how combination of ICIs with established primary liver cancer treatments (e.g. multikinase inhibitors and chemotherapy) as well as more complex combinations with state-of-the-art therapeutic concepts may reshape the tumor microenvironment, leading to higher response rates and long-lasting antitumor immunity for primary liver cancer patients.

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.

Immunosuppressive tumor microenvironment and immunotherapy of hepatocellular carcinoma: current status and prospectives

Hepatocellular carcinoma (HCC) is a major health concern worldwide, with limited therapeutic options and poor prognosis. In recent years, immunotherapies such as immune checkpoint inhibitors (ICIs) have made great progress in the systemic treatment of HCC. The combination treatments based on ICIs have been the major trend in this area. Recently, dual immune checkpoint blockade with durvalumab plus tremelimumab has also emerged as an effective treatment for advanced HCC. However, the majority of HCC patients obtain limited benefits. Understanding the immunological rationale and exploring novel ways to improve the efficacy of immunotherapy has drawn much attention. In this review, we summarize the latest progress in this area, the ongoing clinical trials of immune-based combination therapies, as well as novel immunotherapy strategies such as chimeric antigen receptor T cells, personalized neoantigen vaccines, oncolytic viruses, and bispecific antibodies.

Pan-cancer analysis implicates novel insights of lactate metabolism into immunotherapy response prediction and survival prognostication

BACKGROUND

Immunotherapy has emerged as a potent clinical approach for cancer treatment, but only subsets of cancer patients can benefit from it. Targeting lactate metabolism (LM) in tumor cells as a method to potentiate anti-tumor immune responses represents a promising therapeutic strategy.

METHODS

Public single-cell RNA-Seq (scRNA-seq) cohorts collected from patients who received immunotherapy were systematically gathered and scrutinized to delineate the association between LM and the immunotherapy response. A novel LM-related signature (LM.SIG) was formulated through an extensive examination of 40 pan-cancer scRNA-seq cohorts. Then, multiple machine learning (ML) algorithms were employed to validate the capacity of LM.SIG for immunotherapy response prediction and survival prognostication based on 8 immunotherapy transcriptomic cohorts and 30 The Cancer Genome Atlas (TCGA) pan-cancer datasets. Moreover, potential targets for immunotherapy were identified based on 17 CRISPR datasets and validated via in vivo and in vitro experiments.

RESULTS

The assessment of LM was confirmed to possess a substantial relationship with immunotherapy resistance in 2 immunotherapy scRNA-seq cohorts. Based on large-scale pan-cancer data, there exists a notably adverse correlation between LM.SIG and anti-tumor immunity as well as imbalance infiltration of immune cells, whereas a positive association was observed between LM.SIG and pro-tumorigenic signaling. Utilizing this signature, the ML model predicted immunotherapy response and prognosis with an AUC of 0.73/0.80 in validation sets and 0.70/0.87 in testing sets respectively. Notably, LM.SIG exhibited superior predictive performance across various cancers compared to published signatures. Subsequently, CRISPR screening identified LDHA as a pan-cancer biomarker for estimating immunotherapy response and survival probability which was further validated using immunohistochemistry (IHC) and spatial transcriptomics (ST) datasets. Furthermore, experiments demonstrated that LDHA deficiency in pancreatic cancer elevated the CD8+ T cell antitumor immunity and improved macrophage antitumoral polarization, which in turn enhanced the efficacy of immunotherapy.

CONCLUSIONS

We unveiled the tight correlation between LM and resistance to immunotherapy and further established the pan-cancer LM.SIG, holds the potential to emerge as a competitive instrument for the selection of patients suitable for immunotherapy.

Crosstalk between T lymphocyte and extracellular matrix in tumor microenvironment

The extracellular matrix (ECM) is a complex three-dimensional structure composed of proteins, glycans, and proteoglycans, constituting a critical component of the tumor microenvironment. Complex interactions among immune cells, extracellular matrix, and tumor cells promote tumor development and metastasis, consequently influencing therapeutic efficacy. Hence, elucidating these interaction mechanisms is pivotal for precision cancer therapy. T lymphocytes are an important component of the immune system, exerting direct anti-tumor effects by attacking tumor cells or releasing lymphokines to enhance immune effects. The ECM significantly influences T cells function and infiltration within the tumor microenvironment, thereby impacting the behavior and biological characteristics of tumor cells. T cells are involved in regulating the synthesis, degradation, and remodeling of the extracellular matrix through the secretion of cytokines and enzymes. As a result, it affects the proliferation and invasive ability of tumor cells as well as the efficacy of immunotherapy. This review discusses the mechanisms underlying T lymphocyte-ECM interactions in the tumor immune microenvironment and their potential application in immunotherapy. It provides novel insights for the development of innovative tumor therapeutic strategies and drug.