High S100A9+ cell density predicts a poor prognosis in hepatocellular carcinoma patients after curative resection

HNRNPL facilitates ferroptosis in hepatocellular carcinoma cells by promoting S100A9 expression

OBJECTIVE

This study probed into the effect of HNRNPL on ferroptosis in hepatocellular carcinoma (HCC) cells and related molecular mechanisms.

METHODS

Expression patterns of HNRNPL, Recombinant S100 Calcium Binding Protein A9 (S100A9) were analyzed in HCC tissues or cells. Following transfection, HCC cell activity was analyzed, followed by detection of levels of ROS, iron content, LPO, MDA, and GSH as well as the expression of ferroptosis-related proteins. For molecular mechanism, RIP, RNA pull-down assay and actinomycin D assay were implemented to verify the binding relationship between HNRNPL and S100A9. Finally, in vivo nude mouse xenograft tumor experiments were performed for further validate the crucial role of HNENPL expression in HCC.

RESULTS

HNRNPL and S100A9 were significantly overexpressed in HCC. sh-HNRNPL treatment led to a significant decrease in cellular activity, GSH content, and expression of GPX4 and SLC7A11, and a significant increase in iron content, LPO level, MDA, ROS content, and expression of ACSL4 and TFR1. In addition, after sh-HNRNPL was combined with oe-S100A9 or Fer-1, a ferroptosis inhibitor, both oe-S100A9 and Fer-1 reversed the promotional effect of sh-HNRNPL on ferroptosis of HCC cells when sh-HNRNPL acted alone. Mechanically, HNRNPL promoted S100A9 mRNA stability and expression through RBP. Furthermore, low expression of HNRNPL in vivo delayed the growth of xenograft tumors and the expression of ferroptosis-related proteins.

CONCLUSION

HNRNPL promotes S100A9 mRNA stability and expression through RBP action, thereby promoting ferroptosis in HCC cells.

FAP is a prognostic marker, but not a viable therapeutic target for clinical translation in HNSCC

PURPOSE

PD-1 targeted immunotherapy has imparted a survival benefit to advanced head and neck squamous cell carcinoma (HNSCC), but less than 20% patients produce a durable response to this therapy. Here we aimed to investigate the potential biomarkers for predicting the clinical outcome and resistance to PD-1 targeted immunotherapy in HNSCC patients, and to examine the involvement of FAP+ cancer-associated fibroblasts (CAFs).

METHODS

Bioinformatics methods were applied to analyze multiple datasets and explore the role of PD-1 and FAP in HNSCC. Immunohistochemistry was used to detect the expression of FAP protein. Fap gene knockout mice (Fap-/-) and L929 cells with different levels of Fap overexpression (L929-Fap-Low/High) were established to demonstrate the role of FAP+ CAFs in tumor development and immune checkpoint blockade (ICB) resistance.

RESULTS

The expression level of PD-1 gene was positively correlated with better overall survival and therapeutic response to PD-1 blockade in HNSCC, but not all tumors with high expression of both PD-1 and PD-L1 were responsive. Moreover, FAP gene was overexpressed in pan-cancer tissues, and could serve as a prognostic biomarker for several cancers, including HNSCC. However, FAP protein was undetectable in mouse MTCQ1 tumors and barely expressed in human HNSCC tumors. Furthermore, FAP+ CAFs did not promote tumor growth or enhance the resistance to PD-1 inhibitor treatment.

CONCLUSION

Although FAP+ CAFs have attracted increasing attention for their role in cancer, the feasibility and efficacy of FAP-targeting therapies for HNSCC remain doubtful.

Cancer cell genetics shaping of the tumor microenvironment reveals myeloid cell-centric exploitable vulnerabilities in hepatocellular carcinoma

Myeloid cells are abundant and plastic immune cell subsets in the liver, to which pro-tumorigenic, inflammatory and immunosuppressive roles have been assigned in the course of tumorigenesis. Yet several aspects underlying their dynamic alterations in hepatocellular carcinoma (HCC) progression remain elusive, including the impact of distinct genetic mutations in shaping a cancer-permissive tumor microenvironment (TME). Here, in newly generated, clinically-relevant somatic female HCC mouse models, we identify cancer genetics' specific and stage-dependent alterations of the liver TME associated with distinct histopathological and malignant HCC features. Mitogen-activated protein kinase (MAPK)-activated, NrasG12D-driven tumors exhibit a mixed phenotype of prominent inflammation and immunosuppression in a T cell-excluded TME. Mechanistically, we report a NrasG12D cancer cell-driven, MEK-ERK1/2-SP1-dependent GM-CSF secretion enabling the accumulation of immunosuppressive and proinflammatory monocyte-derived Ly6Clow cells. GM-CSF blockade curbs the accumulation of these cells, reduces inflammation, induces cancer cell death and prolongs animal survival. Furthermore, GM-CSF neutralization synergizes with a vascular endothelial growth factor (VEGF) inhibitor to restrain HCC outgrowth. These findings underscore the profound alterations of the myeloid TME consequential to MAPK pathway activation intensity and the potential of GM-CSF inhibition as a myeloid-centric therapy tailored to subsets of HCC patients.

Integration of single-cell and bulk RNA-sequencing to analyze the heterogeneity of hepatocellular carcinoma and establish a prognostic model

BACKGROUND

The highly heterogeneous nature of hepatocellular carcinoma (HCC) results in different responses and prognoses to the same treatment in patients with similar clinical stages.

AIMS

Thus, it is imperative to investigate the association between HCC tumor heterogeneity and treatment response and prognosis.

METHODS AND RESULTS

At first, we downloaded scRNA-seq, bulk RNA-seq, and clinical data from TCGA and GEO databases. We conducted quality control, normalization using SCTransform, dimensionality reduction using PCA, batch effect removal using Harmony, dimensionality reduction using UMAP, and cell annotation-based marker genes on the scRNA-seq data. We recognized tumor cells, identified tumor-related genes (TRGs), and performed cell communication analysis. Next, we developed a prognostic model using univariable Cox, LASSO, and multivariate Cox analyses. The signature was evaluated using survival analysis, ROC curves, C-index, and nomogram. Last, we studied the predictability of the signature in terms of prognosis and immunotherapeutic response for HCC, assessed a variety of drugs for clinical treatment, and used the qRT-PCR analysis to validate the mRNA expression levels of prognostic TRGs.

CONCLUSION

To conclude, this study expounded upon the influence of tumor cell heterogeneity on the prediction of treatment outcomes and prognosis in HCC. This, in turn, enhances the predictive ability of the TNM staging system and furnishes novel perspectives on the prognostic assessment and therapy of HCC.

Comprehensive scRNA-seq Analysis and Identification of CD8_+T Cell Related Gene Markers for Predicting Prognosis and Drug Resistance of Hepatocellular Carcinoma

BACKGROUND

Tumor heterogeneity of immune infiltration of cells plays a decisive role in hepatocellular carcinoma (HCC) therapy response and prognosis. This study investigated the effect of different subtypes of CD8+T cells on the HCC tumor microenvironment about its prognosis.

METHODS

Single-cell RNA sequencing, transcriptome, and single-nucleotide variant data from LUAD patients were obtained based on the GEO, TCGA, and HCCD18 databases. CD8+ T cells-associated subtypes were identified by consensus clustering analysis, and genes with the highest correlation with prognostic CD8+ T cell subtypes were identified using WGCNA. The ssGSEA and ESTIMATE algorithms were used to calculate pathway enrichment scores and immune cell infiltration levels between different subtypes. Finally, the TIDE algorithm, CYT score, and tumor responsiveness score were utilized to predict patient response to immunotherapy.

RESULTS

We defined 3 CD8+T cell clusters (CD8_0, CD8_1, CD8_2) based on the scRNA- seq dataset (GSE149614). Among, CD8_2 was prognosis-related risk factor with HCC. We screened 30 prognosis genes from CD8_2, and identified 3 molecular subtypes (clust1, clust2, clust3). Clust1 had better survival outcomes, higher gene mutation, and enhanced immune infiltration. Furthermore, we identified a 12 genes signature (including CYP7A1, SPP1, MSC, CXCL8, CXCL1, GCNT3, TMEM45A, SPP2, ME1, TSPAN13, S100A9, and NQO1) with excellent prediction performance for HCC prognosis. In addition, High-score patients with higher immune infiltration benefited less from immunotherapy. The sensitivity of low-score patients to multiple drugs including Parthenolide and Shikonin was significantly higher than that of high-score patients. Moreover, high-score patients had increased oxidative stress pathways scores, and the RiskScore was closely associated with oxidative stress pathways scores. And the nomogram had good clinical utility.

CONCLUSION

To predict the survival outcome and immunotherapy response for HCC, we developed a 12-gene signature based on the heterogeneity of the CD8+ T cells.

Targeting S100A9 protein affects mTOR-ER stress signaling and increases venetoclax sensitivity in Acute Myeloid Leukemia

Acute Myeloid Leukemia (AML) is a heterogeneous disease with limited treatment options and a high demand for novel targeted therapies. Since myeloid-related protein S100A9 is abundantly expressed in AML, we aimed to unravel the therapeutic impact and underlying mechanisms of targeting both intracellular and extracellular S100A9 protein in AML cell lines and primary patient samples. S100A9 silencing in AML cell lines resulted in increased apoptosis and reduced AML cell viability and proliferation. These therapeutic effects were associated with a decrease in mTOR and endoplasmic reticulum stress signaling. Comparable results on AML cell proliferation and mTOR signaling could be observed using the clinically available S100A9 inhibitor tasquinimod. Interestingly, while siRNA-mediated targeting of S100A9 affected both extracellular acidification and mitochondrial metabolism, tasquinimod only affected the mitochondrial function of AML cells. Finally, we found that S100A9-targeting approaches could significantly increase venetoclax sensitivity in AML cells, which was associated with a downregulation of BCL-2 and c-MYC in the combination group compared to single agent therapy. This study identifies S100A9 as a novel molecular target to treat AML and supports the therapeutic evaluation of tasquinimod in venetoclax-based regimens for AML patients.

Viral nanoparticle vaccines against S100A9 reduce lung tumor seeding and metastasis

Metastatic cancer accounts for 90% of all cancer-related deaths and continues to be one of the toughest challenges in cancer treatment. A growing body of data indicates that S100A9, a major regulator of inflammation, plays a central role in cancer progression and metastasis, particularly in the lungs, where S100A9 forms a premetastatic niche. Thus, we developed a vaccine against S100A9 derived from plant viruses and virus-like particles. Using multiple tumor mouse models, we demonstrate the effectiveness of the S100A9 vaccine candidates in preventing tumor seeding within the lungs and outgrowth of metastatic disease. The elicited antibodies showed high specificity toward S100A9 without cross-reactivity toward S100A8, another member of the S100A family. When tested in metastatic mouse models of breast cancer and melanoma, the vaccines significantly reduced lung tumor nodules after intravenous challenge or postsurgical removal of the primary tumor. Mechanistically, the vaccines reduce the levels of S100A9 within the lungs and sera, thereby increasing the expression of immunostimulatory cytokines with antitumor function [(interleukin) IL-12 and interferonγ] while reducing levels of immunosuppressive cytokines (IL-10 and transforming growth factorβ). This also correlated with decreased myeloid-derived suppressor cell populations within the lungs. This work has wide-ranging impact, as S100A9 is overexpressed in multiple cancers and linked with poor prognosis in cancer patients. The data presented lay the foundation for the development of therapies and vaccines targeting S100A9 to prevent metastasis.

Establishment of nucleic acid sensing pathways-based model in predicting response to immunotherapy and targeted drug in hepatitis virus-related hepatocellular carcinoma

Hepatocellular carcinoma (HCC) accounts for 80% of liver cancers, while 70%-80% of HCC developed from chronic liver disease with hepatitis B virus (HBV) and hepatitis C virus (HCV) infection as the major etiology. Immunotherapy is assuming a role as a pillar of HCC treatment, but the remarkable immune-mediated responses are restricted in a minority of patients. Nucleic acid sensing (NAS) pathways are the central pathway of the innate immune system and antiviral immune response to viral infection, but their role in hepatitis virus-related HCC remains undetermined. In our study, we performed a comprehensive bioinformatics analysis based on transcriptomic data of hepatitis virus related-HCC tissues collected from multiple public data sets. Two subgroups were validated based on NAS-related genes in virus-related HCC patients, which were defined as NAS-activated subgroups and NAS-suppressed subgroups based on the expression of NAS-related genes. On this basis, a NAS-related risk score (NASRS) predictive model was established for risk stratification and prognosis prediction in the hepatitis virus-related HCC (TCGA-LIHC and ICGC cohorts). The predictive values of the NASRS in prognosis and immunotherapy were also verified in multiple data sets. A nomogram was also established to facilitate the clinical use of NASRS and demonstrate its effectiveness through different approaches. Additionally, six potential drugs binding to the core target of the NAS signature were predicted via molecular docking strategy. We subsequently evaluated the cytotoxic capabilities of potential drug in vitro and in vivo. Based on these results, we conclude that the NASRS model could serve as a power prognostic biomarker and predict responses to immunotherapy, which is meaningful in clinical decision-making of hepatitis virus-related HCC patients.

Association between the expression levels of ADAMTS16 and BMP2 and tumor budding in hepatocellular carcinoma

Tumor budding (TB) has become a crucial factor for predicting the malignancy grade and prognostic outcome for multiple types of solid cancer. Studies have investigated the prognostic value of TB in hepatocellular carcinoma (HCC). However, its molecular mechanism in HCC remains unclear. To the best of our knowledge, the present study was the first to compare the expression of differentially expressed genes (DEGs) between TB-positive (TB-pos) and TB-negative HCC tissues. In the present study, total RNA was extracted from 40 HCC tissue specimens and then sequenced. According to Gene Ontology (GO) functional annotation, upregulated DEGs were markedly associated with embryonic kidney development-related GO terms, which suggested that the TB process may at least partly mimic the process of embryonic kidney development. Subsequently, two genes, a disintegrin and metalloproteinase domain with thrombospondin motifs 16 (ADAMTS16) and bone morphogenetic protein 2 (BMP2), were screened and verified through immunohistochemical analysis of HCC tissue microarrays. According to the immunohistochemical results, ADAMTS16 and BMP2 were upregulated in TB-pos HCC samples, and BMP2 expression was increased in budding cells compared with the tumor center. Additionally, through cell culture experiments, it was demonstrated that ADAMTS16 and BMP2 may promote TB of liver cancer, thus promoting the malignant progression of liver cancer. Further analysis revealed that ADAMTS16 expression was associated with necrosis and cholestasis, and BMP2 expression was associated with the Barcelona Clinic Liver Cancer stage and the vessels encapsulating tumor clusters. Overall, the findings of the present study provided insights into the possible mechanisms of TB in HCC and revealed potential anti-HCC therapeutic targets.

In-depth serum proteomics reveals the trajectory of hallmarks of cancer in hepatitis B virus-related liver diseases

Hepatocellular carcinoma (HCC) is a prevalent cancer in China, with chronic hepatitis B (CHB) and liver cirrhosis (LC) being high-risk factors for developing HCC. Here, we determined the serum proteomes (762 proteins) of 125 healthy controls and Hepatitis B virus-infected CHB, LC, and HCC patients and constructed the first cancerous trajectory of liver diseases. The results not only reveal that the majority of altered biological processes were involved in the hallmarks of cancer (inflammation, metastasis, metabolism, vasculature, coagulation), but also identify potential therapeutic targets in cancerous pathways (i.e., IL17 signaling pathway). Notably, the biomarker panels for detecting HCC in CHB and LC high-risk populations were further developed using machine learning in two cohorts comprised of 200 samples (discovery cohort=125, validation cohort=75). The protein signatures significantly improved the area under the receiver operating characteristic curve (AUC) of HCC (CHB discovery and validation cohort = 0.953 and 0.891, respectively; LC discovery and validation cohort = 0.966 and 0.818, respectively) compared to using the traditional biomarker, alpha-fetoprotein (AFP), alone. Finally, selected biomarkers were validated with parallel reaction monitoring (PRM) mass spectrometry in an additional cohort (n=120). Altogether, our results provide fundamental insights into the continuous changes of cancer biology processes in liver diseases and identify candidate protein targets for early detection and intervention.

S100A9 promotes tumor-associated macrophage for M2 macrophage polarization to drive human liver cancer progression: An in vitro study

Tumor-associated macrophages (TAMs) and M2 macrophage polarization have been documented for their implication in various malignancies, but their implication in liver cancer remains to be determined. This study is intended to explore the effect of S100A9 regulated TAMs and macrophage polarization in liver cancer progression. THP-1 cells were induced to differentiate into M1 and M2 macrophages, which were then cultured in liver cancer cell conditioned culture medium before the M1 and M2 macrophages were identified by measuring biomarkers using real-time polymerase chain reaction. The differential expressed genes in macrophages in Gene Expression Omnibus (GEO) databases were screened. S100A9 overexpression and knockdown plasmid were transfected into macrophages to determine the effect of S100A9 on M2 macrophage polarization of TAMs and on proliferation ability of liver cancer cells. The proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) abilities of liver cancer co-cultured with TAMs. M1 and M2 macrophages were successfully induced and liver cancer cell conditioned culture medium can increase polarization of macrophages into M2 macrophages, in which elevated expression of S100A9 was detected. Data in GEO database showed that tumor microenvironment (TME) upregulated S1000A9 expression. Suppression on S1000A9 can significantly suppress M2 macrophage polarization. TAM can provide the necessary microenvironment for liver cancer cells, HepG2 and MHCC97H by increasing cell proliferation, migration, and invasion ability, while suppression on S1000A9 can reverse this expression pattern. Suppression on S100A9 expression can regulate M2 macrophage polarization of TAMs to suppress the progression of liver cancer.

Immune-related gene signature to predict TACE refractoriness in patients with hepatocellular carcinoma based on artificial neural network

Background: Transarterial chemoembolization (TACE) is the standard treatment option for intermediate-stage hepatocellular carcinoma (HCC), while response varies among patients. This study aimed to identify novel immune-related genes (IRGs) and establish a prediction model for TACE refractoriness in HCC patients based on machine learning methods. Methods: Gene expression data were downloaded from GSE104580 dataset of Gene Expression Omnibus (GEO) database, differential analysis was first performed to screen differentially expressed genes (DEGs). The least absolute shrinkage and selection operator (LASSO) regression analysis was performed to further select significant DEGs. Weighted gene co-expression network analysis (WGCNA) was utilized to build a gene co-expression network and filter the hub genes. Final signature genes were determined by the intersection of LASSO analysis results, WGCNA results and IRGs list. Based on the above results, the artificial neural network (ANN) model was constructed in the training cohort and verified in the validation cohort. Receiver operating characteristics (ROC) analysis was used to assess the prediction accuracy. Correlation of signature genes with tumor microenvironment scores, immune cells and immune checkpoint molecules were further analyzed. The tumor immune dysfunction and exclusion (TIDE) score was used to evaluate the response to immunotherapy. Results: One hundred and forty-seven samples were included in this study, which was randomly divided into the training cohort (n = 103) and validation cohort (n = 44). In total, 224 genes were identified as DEGs. Further LASSO regression analysis screened out 25 genes from all DEGs. Through the intersection of LASSO results, WGCNA results and IRGs list, S100A9, TREM1, COLEC12, and IFIT1 were integrated to construct the ANN model. The areas under the curves (AUCs) of the model were .887 in training cohort and .765 in validation cohort. The four IRGs also correlated with tumor microenvironment scores, infiltrated immune cells and immune checkpoint genes in various degrees. Patients with TACE-Response, lower expression of COLEC12, S100A9, TREM1 and higher expression of IFIT1 had better response to immunotherapy. Conclusion: This study constructed and validated an IRG signature to predict the refractoriness to TACE in patients with HCC, which may have the potential to provide insights into the TACE refractoriness in HCC and become the immunotherapeutic targets for HCC patients with TACE refractoriness.

Recent progress in molecular mechanisms of postoperative recurrence and metastasis of hepatocellular carcinoma

Hepatectomy is currently considered the most effective option for treating patients with early and intermediate hepatocellular carcinoma (HCC). Unfortunately, the postoperative prognosis of patients with HCC remains unsatisfactory, predominantly because of high postoperative metastasis and recurrence rates. Therefore, research on the molecular mechanisms of postoperative HCC metastasis and recurrence will help develop effective intervention measures to prevent or delay HCC metastasis and recurrence and to improve the long-term survival of HCC patients. Herein, we review the latest research progress on the molecular mechanisms underlying postoperative HCC metastasis and recurrence to lay a foundation for improving the understanding of HCC metastasis and recurrence and for developing more precise prevention and intervention strategies.

Metastatic Colon Cancer Treatment Using S100A9-Targeted Cowpea Mosaic Virus Nanoparticles

Peritoneal metastases (PMs) occur due to the metastasis of gynecological and gastrointestinal cancers such as ovarian, colon, pancreatic, or gastric tumors. PM outgrowth is often fatal, and patients with PMs have a median survival of 6 months. Cowpea mosaic virus (CPMV) has been shown, when injected intratumorally, to act as an immunomodulator reversing the immunosuppressive tumor microenvironment, therefore turning cold tumors hot and priming systemic antitumor immunity. However, not all tumors are injectable, and PMs especially will require targeted treatments to direct CPMV toward the disseminated tumor nodules. Toward this goal, we designed and tested a CPMV nanoparticle targeted to S100A9, a key immune mediator for many cancer types indicated in cancer growth, invasiveness, and metastasis. Here, we chose to use an intraperitoneal (IP) colon cancer model, and analysis of IP gavage fluid demonstrates that S100A9 is upregulated following IP challenge. S100A9-targeted CPMV particles displaying peptide ligands specific for S100A9 homed to IP-disseminated tumors, and treatment led to improved survival and decreased tumor burden. Targeting CPMV to S100A9 improves preclinical outcomes and harbors the potential of utilizing CPMV for the treatment of IP-disseminated diseases.

Neutrophils as potential therapeutic targets in hepatocellular carcinoma

The success of atezolizumab plus bevacizumab treatment contributed to a shift in systemic therapies for hepatocellular carcinoma (HCC) towards combinations that include cancer immunotherapeutic agents. Thus far, the principal focus of cancer immunotherapy has been on interrupting immune checkpoints that suppress antitumour lymphocytes. As well as lymphocytes, the HCC environment includes numerous other immune cell types, among which neutrophils are emerging as an important contributor to the pathogenesis of HCC. A growing body of evidence supports neutrophils as key mediators of the immunosuppressive environment in which some cancers develop, as well as drivers of tumour progression. If neutrophils have a similar role in HCC, approaches that target or manipulate neutrophils might have therapeutic benefits, potentially including sensitization of tumours to conventional immunotherapy. Several neutrophil-directed therapies for patients with HCC (and other cancers) are now entering clinical trials. This Review outlines the evidence in support of neutrophils as drivers of HCC and details their mechanistic roles in development, progression and metastasis, highlighting the reasons that neutrophils are well worth investigating despite the challenges associated with studying them. Neutrophil-modulating anticancer therapies entering clinical trials are also summarized.