The Emerging Roles of Exosomes in the Chemoresistance of Hepatocellular Carcinoma

Autophagy-modulating biomembrane nanostructures: A robust anticancer weapon by modulating the inner and outer cancer environment

Recently, biomembrane nanostructures, such as liposomes, cell membrane-coated nanostructures, and exosomes, have demonstrated promising anticancer therapeutic effects. These nanostructures possess remarkable biocompatibility, multifunctionality, and low toxicity. However, their therapeutic efficacy is impeded by chemoresistance and radiotherapy resistance, which are closely associated with autophagy. Modulating autophagy could enhance the therapeutic sensitivity and effectiveness of these biomembrane nanostructures by influencing the immune system and the cancer microenvironment. For instance, autophagy can regulate the immunogenic cell death of cancer cells, antigen presentation of dendritic cells, and macrophage polarization, thereby activating the inflammatory response in the cancer microenvironment. Furthermore, combining autophagy-regulating drugs or genes with biomembrane nanostructures can exploit the targeting and long-term circulation properties of these nanostructures, leading to increased drug accumulation in cancer cells. This review explores the role of autophagy in carcinogenesis, cancer progression, metastasis, cancer immune responses, and resistance to treatment. Additionally, it highlights recent research advancements in the synergistic anticancer effects achieved through autophagy regulation by biomembrane nanostructures. The review also discusses the prospects and challenges associated with the future clinical translation of these innovative treatment strategies. In summary, these findings provide valuable insights into autophagy, autophagy-modulating biomembrane-based nanostructures, and the underlying molecular mechanisms, thereby facilitating the development of promising cancer therapeutics.

KIFC3 regulates progression of hepatocellular carcinoma via EMT and the AKT/mTOR pathway

INTRODUCTION

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related deaths worldwide. Despite an overall downward trend in cancer mortality, HCC-related mortality continues to increase. KIFC3 is involved in cell division and cancers. However, the role of KIFC3 in HCC has yet to be elucidated.

METHODS

A total of 36 cases of HCC tissues, 4 HCC cell lines, and TCGA databases were searched to explore the expression of KIFC3 in HCC. Subsequently, Western blot analysis, immunofluorescence, bioinformatic analysis, molecular docking, and Co-IP were performed to investigate the molecular mechanisms of KIFC3 in HCC.

RESULT

We found that the expression of KIFC3 was upregulated in HCC, and high KIFC3 expression was related to poor overall survival. In addition, the knockdown of KIFC3 inhibited the proliferation, migration, and invasion of HCC cells in vitro, and impeded the growth of HCC in vivo, while overexpression of KIFC3 in HCC cells revealed the opposite effect. Mechanistically, KIFC3 promotes the progression of HCC through the PI3K/AKT/mTOR signalling. And KIFC3 had slight effect on the protein expression of p-PI3K, p-AKT and p-mTOR in TRIP13-ablated or LY294002-treated HCC cells. The KIFC3 knockdown could further enhance the inhibitory effect of LY294002.

CONCLUSION

Our data revealed that KIFC3 is upregulated in HCC and may serve as a novel biomarker for predicting survival in HCC patients. Targeting KIFC3 may serve as a novel therapeutic strategy for HCC patients.

Cross-talk between cancer stem cells and immune cells: potential therapeutic targets in the tumor immune microenvironment

Ongoing research has revealed that the existence of cancer stem cells (CSCs) is one of the biggest obstacles in the current cancer therapy. CSCs make an influential function in tumor progression, recurrence and chemoresistance due to their typical stemness characteristics. CSCs are preferentially distributed in niches, and those niche sites exhibit characteristics typical of the tumor microenvironment (TME). The complex interactions between CSCs and TME illustrate these synergistic effects. The phenotypic heterogeneity within CSCs and the spatial interactions with the surrounding tumor microenvironment led to increased therapeutic challenges. CSCs interact with immune cells to protect themselves against immune clearance by exploiting the immunosuppressive function of multiple immune checkpoint molecules. CSCs also can protect themselves against immune surveillance by excreting extracellular vesicles (EVs), growth factors, metabolites and cytokines into the TME, thereby modulating the composition of the TME. Therefore, these interactions are also being considered for the therapeutic development of anti-tumor agents. We discuss here the immune molecular mechanisms of CSCs and comprehensively review the interplay between CSCs and the immune system. Thus, studies on this topic seem to provide novel ideas for reinvigorating therapeutic approaches to cancer.

Identification of three metabolic subtypes in gastric cancer and the construction of a metabolic pathway-based risk model that predicts the overall survival of GC patients

Gastric cancer (GC) is highly heterogeneous and GC patients have low overall survival rates. It is also challenging to predict the prognosis of GC patients. This is partly because little is known about the prognosis-related metabolic pathways in this disease. Hence, our objective was to identify GC subtypes and genes related to prognosis, based on changes in the activity of core metabolic pathways in GC tumor samples. Differences in the activity of metabolic pathways in GC patients were analyzed using Gene Set Variation Analysis (GSVA), leading to the identification of three clinical subtypes by non-negative matrix factorization (NMF). Based on our analysis, subtype 1 showed the best prognosis while subtype 3 exhibited the worst prognosis. Interestingly, we observed marked differences in gene expression between the three subtypes, through which we identified a new evolutionary driver gene, CNBD1. Furthermore, we used 11 metabolism-associated genes identified by LASSO and random forest algorithms to construct a prognostic model and verified our results using qRT-PCR (five matched clinical tissues of GC patients). This model was found to be both effective and robust in the GSE84437 and GSE26253 cohorts, and the results from multivariate Cox regression analyses confirmed that the 11-gene signature was an independent prognostic predictor (p < 0.0001, HR = 2.8, 95% CI 2.1-3.7). The signature was found to be relevant to the infiltration of tumor-associated immune cells. In conclusion, our work identified significant GC prognosis-related metabolic pathways in different GC subtypes and provided new insights into GC-subtype prognostic assessment.

Significance of exosomes in hepatocellular carcinoma

Among the most prevalent cancers in the world, hepatocellular carcinoma (HCC) has a high mortality rate. The diagnosis and management of HCC are presently hindered by difficulties in early detection and suboptimal treatment outcomes. Exosomes have been shown to play an important role in hepatocarcinogenesis and can also be used for diagnosis and treatment. In this review, we discussed the research progress on exosomes in hepatocarcinogenesis development, tumor microenvironment remodeling, treatment resistance, and immunosuppression. HCC can be diagnosed and treated by understanding the pathogenesis and identifying early diagnostic markers. This review will be a significant reference for scholars with an initial understanding of the field to fully understand the role of exosomes in the organism.

Novel Nanotechnology Approaches to Overcome Drug Resistance in the Treatment of Hepatocellular Carcinoma: Glypican 3 as a Useful Target for Innovative Therapies

Hepatocellular carcinoma (HCC) is the second most lethal tumor, with a 5-year survival rate of 18%. Early stage HCC is potentially treatable by therapies with curative intent, whereas chemoembolization/radioembolization and systemic therapies are the only therapeutic options for intermediate or advanced HCC. Drug resistance is a critical obstacle in the treatment of HCC that could be overcome by the use of targeted nanoparticle-based therapies directed towards specific tumor-associated antigens (TAAs) to improve drug delivery. Glypican 3 (GPC3) is a member of the glypican family, heparan sulfate proteoglycans bound to the cell surface via a glycosylphosphatidylinositol anchor. The high levels of GPC3 detected in HCC and the absence or very low levels in normal and non-malignant liver make GPC3 a promising TAA candidate for targeted nanoparticle-based therapies. The use of nanoparticles conjugated with anti-GPC3 agents may improve drug delivery, leading to a reduction in severe side effects caused by chemotherapy and increased drug release at the tumor site. In this review, we describe the main clinical features of HCC and the common treatment approaches. We propose the proteoglycan GPC3 as a useful TAA for targeted therapies. Finally, we describe nanotechnology approaches for anti-GPC3 drug delivery systems based on NPs for HCC treatment.

MiR-520a-5p/PPP5C regulation pattern is identified as the key to gemcitabine resistance in pancreatic cancer

Objective

To explore the effects of the expression level of miR-520-5p/PPP5C in pancreatic cancer cells and exosomes on cell viability, angiogenesis, autophagy, which involved in the mechanism of gemcitabine resistance in pancreatic cancer.

Methods

APSC-1 cell line was treated with gemcitabine, after which its exosomes were extracted for NTA assay. Subsequently, the drug resistance of APSC-1 cells was assayed using CCK8, as well as the activity of HUVEC cells treated with exosomes from each group of APSC-1 cells after drug resistance treatment as well as overexpression treatment. Five groups of HUVEC cells treated with exosomes were subjected to in vitro tubule formation assay. levels of PPP5C in each group of ASPC-1 cells and their exosomes, levels of overexpressed PPP5C, and related exosomal proteins were examined by WB. mRNA expression levels of PPP5C and levels of miR-520a were examined by qPCR The relationship between miR-520a-5p and PPP5C was investigated. After that, the autophagy of PPP5C was detected. Finally, it was analyzed by TCGA database for survival prognosis analysis.

Results

APSC-1 cells had an IC50 value of 227.1 μM for gemcitabine, elevated PPP5C expression, drug resistance, and enhanced HUVEC cell activity; exosomes CD9, CD63, and CD81 were significantly expressed in all groups; meanwhile, enhanced PPP5C expression not only promoted in vitro tubule formation but also increased autophagy levels; meanwhile, its relationship with miR-520-5p and There was a targeted inhibitory relationship between its level and miR-520-5p and PPP5C, and its elevated level also led to a decrease in the survival level of patients over 3-5 years.

Conclusion

PPP5C has a prognostic role in pancreatic cancer by promoting the value-added and invasion of pancreatic cancer cells, and a targeted inhibitory relationship between miR-520-5p and PPP5C was found.

Identification of the Immune Subtype of Hepatocellular Carcinoma for the Prediction of Disease-Free Survival Time and Prevention of Recurrence by Integrated Analysis of Bulk- and Single-Cell RNA Sequencing Data

Background

The main factors affecting the long-term prognosis of hepatocellular carcinoma (HCC) patients undergoing radical surgery are recurrence and metastasis. However, the methods for predicting disease-free survival (DFS) time and preventing postoperative recurrence of HCC are still very limited.

Methods

In this study, immune cell abundances in HCC samples were analyzed by single-sample gene set enrichment analysis (ssGSEA), while the prognostic values of immune cells for DFS time prediction were evaluated by the least absolute shrinkage and selection operator (LASSO) and subsequent univariate and multivariate Cox analyses. Next, a risk score was constructed based on the most prognostic immune cells and their corresponding coefficients. Interactions among prognostic immune cells and the specific targets for the prevention of recurrence were further identified by single-cell RNA (scRNA) sequencing data and CellMiner.

Results

A novel efficient T cell risk score (TCRS) was constructed based on data from the three most prognostic immune cell types (effector memory CD8 T cells, regulatory T cells and follicular helper T cells) for identifying an immune subtype of HCC patients with longer DFS times and inflammatory immune characteristics. Functional differences between the high- and low-score groups separated by TCRS were clarified, and the cell-cell communication among these immune cells was elucidated. Finally, fifteen hub genes that may be potential therapeutic targets for the prevention of recurrence were identified.

Conclusions

We constructed and verified a useful model for the prediction of DFS time of HCC after surgery. In addition, fifteen hub genes were identified as candidates for the prevention of recurrence, and a preliminarily investigation of potential drugs targeting these hub genes was carried out.

Identification of an Epithelial-Mesenchymal Transition-Related Long Non-coding RNA Prognostic Signature to Determine the Prognosis and Drug Treatment of Hepatocellular Carcinoma Patients

Introduction

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with poor prognosis. Epithelial–mesenchymal transition (EMT) is crucial for cancer progression and metastasis. Thus, we aimed to construct an EMT-related lncRNA signature for predicting the prognosis of HCC patients.

Methods

Cox regression analysis and LASSO regression method were used to build an EMT-related lncRNAs risk signature based on TCGA database. Kaplan-Meier survival analysis was conducted to compare the overall survival (OS) in different risk groups. ROC curves and Cox proportional-hazards analysis were performed to evaluate the performance of the risk signature. RT-qPCR was conducted in HCC cell lines and tissue samples to detect the expression of some lncRNAs in this risk model. Furthermore, a nomogram involving the risk score and clinicopathological features was built and validated with calibration curves and ROC curves. In addition, we explored the association between risk signature and tumor immunity, somatic mutations status, and drugs sensitivity.

Results

Twelve EMT-related lncRNAs were obtained to construct the prognostic risk signature for patients with HCC. The Kaplan-Meier curve analysis revealed that patients in the high-risk group had worse overall survival (OS) than those in low-risk group. ROC curves and Cox regression analysis suggested the risk signature could predict HCC survival exactly and independently. The prognostic value of the risk model was confirmed in the testing and entire groups. We also found AC099850.3 and AC092171.2 were highly expressed in HCC cells and HCC tissues. The nomogram could accurately predict survival probability of HCC patients. Gene set enrichment analysis (GSEA) and gene ontology (GO) analysis showed that cancer-related pathways and cell division activity were enriched in high-risk group. The SNPs showed that the prevalence of TP53 mutations was significantly different between high- and low-risk groups; the TP53 mutations and the high TMB were both associated with a worse prognosis in patients with HCC. We also observed widely associations between risk signature and drugs sensitivity in HCC.

Conclusion

A novel EMT-related lncRNAs risk signature, including 12 lncRNAs, was established and identified in patients with HCC, which can accurately predict the prognosis of HCC patients and may be used to guide individualized treatment in the clinical practice.

Immune cell responses in pancreatic cancer and their clinical application

Pancreatic cancer is one of the most lethal diseases around the world, for hardly detection and poor prognosis. Recent years, functions of the tumor microenvironment and immune cells attract people’s view and there is emerging evidence implicating some immune cells hold the key points in the metabolism, invasion, and metastasis in pancreatic cancer. In this review, we highlight some main immune cells, such as Tumor-associated neutrophils (TANs) and macrophages (TAMs), Pancreatic stellate cells (PSCs), Myeloid-derived suppressor cells (MDSCs), and Regulatory T cells (Tregs). Furthermore, we review current clinical applications and discuss potential values in future.

A Novel Epithelial-Mesenchymal Transition Gene Signature Correlated With Prognosis, and Immune Infiltration in Hepatocellular Carcinoma

Background: Although many genes related to epithelial-mesenchymal transition (EMT) have been explored in hepatocellular carcinoma (HCC), their prognostic significance still needs further analysis. Methods: Differentially expressed EMT-related genes were obtained through the integrated analysis of 4 Gene expression omnibus (GEO) datasets. The univariate Cox regression and Lasso Cox regression models are utilized to determine the EMT-related gene signature. Based on the results of multivariate Cox regression, a predictive nomogram is established. Time-dependent ROC curve and calibration curve are used to show the distinguishing ability and consistency of the nomogram. Finally, we explored the correlation between EMT risk score and immune immunity. Results: We identified a nine EMT-related gene signature to predict the survival outcome of HCC patients. Based on the EMT risk score's median, HCC patients in each dataset were divided into high and low-risk groups. The survival outcomes of HCC patients in the high-risk group were significantly worse than those in the low-risk group. The prediction nomogram based on the EMT risk score has better distinguishing ability and consistency. High EMT risk score was related to immune infiltration. Conclusion: The nomogram based on the EMT risk score can reliably predict the survival outcome of HCC patients, thereby providing benefits for medical decisions.

LncRNA00978 contributes to growth and metastasis of hepatocellular carcinoma cells via mediating microRNA-125b-5p/SOX12 pathway

As a malignant tumor, HCC (hepatocellular carcinoma) is featured by a high recurrence rate with a poor prognosis. Increasing evidence supports an important role of lincRNAs in HCC. Here, the purpose of the study was to explore the function of LINC00978 (long non-coding RNA00978) in HCC and the underlying mechanisms. LINC00978 expression and its association with the progression of HCC were analyzed using HCC TCGA datasets. LINC00978 expression in tissues was measured using real-time PCR. Then, we knocked down LINC00978 in HCC cells to explore its effect on cellular invasion, proliferation, and migration. Finally, we investigated the potential molecular mechanism of LINC00978 by dual Luciferase reporter assay, FISH (fluorescence in situ hybridization) and RIP (RNA immunoprecipitation). LINC00978 expression was remarkably increased in HCC. A high level of LINC00978 was associated with poor prognosis of HCC. Additionally, LINC00978 silencing could repress the growth and metastasis of HCC cells. Mechanistically, it was revealed that LINC00978 could sponge microRNA-125b-5p and identified SOX12 (SRY-Box Transcription Factor 12) as a direct target gene of microRNA-125b-5p. More importantly, the suppressed effect of LINC00978 silencing on the metastasis and growth of HCC cells could be rescued by miR-125b-5p inhibition and overexpressed SOX12. LINC00978/microRNA-125b-5p/SOX12 axis promoted liver cancer migration, invasion, and proliferation, which could be used as a possible therapeutic target for the treatment of hepatocellular carcinoma.

ASF1B is a Promising Prognostic Biomarker and Correlates With Immunotherapy Efficacy in Hepatocellular Carcinoma

Background: Anti-silencing function 1B (ASF1B), a histone H3-H4 chaperone, is crucial for S-phase progression and cell proliferation. Recent studies have shown that ASF1B may be used as a new proliferation marker for cancer prognosis. However, the prognostic value and effect of ASF1B on tumor cells and the immune microenvironment in hepatocellular carcinoma (HCC) remain unclear.

Methods: We analyzed the expression of ASF1B and its prognostic value using The Cancer Genome Atlas (TCGA) database (as a training set) and other databases, and we validated the findings by immunohistochemistry in our clinical database, containing 141 HCC patients (as a validation set). Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were performed to probe the tumor-associated biological processes of ASF1B in HCC. The interrelationships between ASF1B expression and tumor immunological characteristics were analyzed by multiple databases. The Imvigor210 cohort was retrieved to assess the ability of ASF1B to predict immunotherapy efficacy.

Results: ASF1B was highly expressed in tumor tissue compared to paracancerous tissue. High ASF1B expression was associated with worse overall survival (OS) and progression-free survival (PFS) in the training set (p = 0.005, p < 0.001) and validation set (p < 0.001, p < 0.001). Multivariate analysis revealed that ASF1B was an independent prognostic factor associated with OS and PFS. GSEA and GSVA suggested that ASF1B was involved in tumor-associated biological processes, including the cell cycle, DNA replication, base excision repair, mismatch repair, RNA degradation, ubiquitin-mediated proteolysis, and nucleotide excision repair. Further analysis revealed that the levels of ASF1B were positively correlated with the immune cells infiltration of B cells, CD8⁺ T cells, CD4⁺ T cells, neutrophils, and dendritic cells. However, ASF1B was positively correlated with Treg cell infiltration and inhibitory immune checkpoints in exhausted T cells. Patients who received anti-PD-L1 immunotherapy with high ASF1B expression had a higher objective response.

Conclusion: The ASF1B level is an independent prognostic factor and may serve as a potential immunotherapeutic target.

A Comprehensive Pan-Cancer Analysis for Pituitary Tumor-Transforming Gene 1

Pituitary tumor-transforming gene 1 (PTTG1) encodes a multifunctional protein that is involved in many cellular processes. However, the potential role of PTTG1 in tumor formation and its prognostic function in human pan-cancer is still unknown. The analysis of gene alteration, PTTG1 expression, prognostic function, and PTTG1-related immune analysis in 33 types of tumors was performed based on various databases such as The Cancer Genome Atlas database, the Genotype-Tissue Expression database, and the Human Protein Atlas database. Additionally, PTTG1-related gene enrichment analysis was performed to investigate the potential relationship and possible molecular mechanisms between PTTG1 and tumors. Overexpression of PTTG1 may lead to tumor formation and poor prognosis in various tumors. Consequently, PTTG1 acts as a potential oncogene in most tumors. Additionally, PTTG1 is related to immune infiltration, immune checkpoints, tumor mutational burden, and microsatellite instability. Thus, PTTG1 could be potential biomarker for both prognosis and outcomes of tumor treatment and it could also be a promising target in tumor therapy.

Cancer Stem Cells and Their Vesicles, Together with Other Stem and Non-Stem Cells, Govern Critical Cancer Processes: Perspectives for Medical Development

Stem cells, identified several decades ago, started to attract interest at the end of the nineties when families of mesenchymal stem cells (MSCs), concentrated in the stroma of most organs, were found to participate in the therapy of many diseases. In cancer, however, stem cells of high importance are specific to another family, the cancer stem cells (CSCs). This comprehensive review is focused on the role and the mechanisms of CSCs and of their specific extracellular vesicles (EVs), which are composed of both exosomes and ectosomes. Compared to non-stem (normal) cancer cells, CSCs exist in small populations that are preferentially distributed to the niches, such as minor specific tissue sites corresponding to the stroma of non-cancer tissues. At niches and marginal sites of other cancer masses, the tissue exhibits peculiar properties that are typical of the tumor microenvironment (TME) of cancers. The extracellular matrix (ECM) includes components different from non-cancer tissues. CSCs and their EVs, in addition to effects analogous to those of MSCs/EVs, participate in processes of key importance, specific to cancer: generation of distinct cell subtypes, proliferation, differentiation, progression, formation of metastases, immune and therapy resistance, cancer relapse. Many of these, and other, effects require CSC cooperation with surrounding cells, especially MSCs. Filtered non-cancer cells, especially macrophages and fibroblasts, contribute to collaborative cancer transition/integration processes. Therapy developments are mentioned as ongoing preclinical initiatives. The preliminary state of clinical medicine is presented in terms of both industrial development and future treatments. The latter will be administered to specific patients together with known drugs, with the aim of eradicating their tumor growth and metastases.

Epigenetic and Immune-Cell Infiltration Changes in the Tumor Microenvironment in Hepatocellular Carcinoma

Background

Epigenetics regulate gene expression without altering the DNA sequence. Epigenetics targeted chemotherapeutic approach can be used to overcome treatment resistance and low response rate in HCC. However, a comprehensive review of genomic data was carried out to determine the role of epigenesis in the tumor microenvironment (TME), immune cell-infiltration characteristics in HCC is still insufficient.

Methods

The association between epigenetic-related genes (ERGs), inflammatory response-related genes (IRRGs) and CRISPR genes was determined by merging genomic and CRISPR data. Further, characteristics of immune-cell infiltration in the tumor microenvironment was evaluated.

Results

Nine differentially expressed genes (ANP32B, ASF1A, BCORL1, BMI1, BUB1, CBX2, CBX3, CDK1, and CDK5) were shown to be independent prognostic factors based on lasso regression in the TCGA-LIHC and ICGC databases. In addition, the results showed significant differences in expression of PDCD-1 (PD-1) and CTLA4 between the high- and low-epigenetic score groups. The CTRP and PRISM-derived drug response data yielded four CTRP-derived compounds (SB-743921, GSK461364, gemcitabine, and paclitaxel) and two PRISM-derived compounds (dolastatin-10 and LY2606368). Patients with high ERGs benefited more from immune checkpoint inhibitor (ICI) therapy than patients with low ERGs. In addition, the high ERGs subgroup had a higher T cell exclusion score, while the low ERGs subgroup had a higher T cell dysfunction. However, there was no difference in microsatellite instability (MSI) score among the two subgroups. Further, genome-wide CRISPR-based loss-of function screening derived from DepMap was conducted to determine key genes leading to HCC development and progression. In total, 640 genes were identified to be essential for survival in HCC cell lines. The protein-protein interaction (PPI) network demonstrated that IRRGs PSEN1 was linked to most ERGs and CRISPR genes such as CDK1, TOP2A, CBX2 and CBX3.

Conclusion

Epigenetic alterations of cancer-related genes in the tumor microenvironment play a major role in carcinogenesis. This study showed that epigenetic-related novel biomarkers could be useful in predicting prognosis, clinical diagnosis, and management in HCC.

Comprehensive Analysis to Identify the Epithelial-Mesenchymal Transition-Related Immune Signatures as a Prognostic and Therapeutic Biomarkers in Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is a highly heterogeneous disease with the high rates of the morbidity and mortality due to the lack of the effective prognostic model for prediction.

Aim: To construct a risk model composed of the epithelial–mesenchymal transition (EMT)-related immune genes for the assessment of the prognosis, immune infiltration status, and chemosensitivity.

Methods: We obtained the transcriptome and clinical data of the HCC samples from The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC) databases. The Pearson correlation analysis was applied to identify the differentially expressed EMT-related immune genes (DE-EMTri-genes). Subsequently, the univariate Cox regression was introduced to screen out the prognostic gene sets and a risk model was constructed based on the least absolute shrinkage and selection operator-penalized Cox regression. Additionally, the receiver operating characteristic (ROC) curves were plotted to compare the prognostic value of the newly established model compared with the previous model. Furthermore, the correlation between the risk model and survival probability, immune characteristic, and efficacy of the chemotherapeutics were analyzed by the bioinformatics methods.

Results: Six DE-EMTri-genes were ultimately selected to construct the prognostic model. The area under the curve (AUC) values for 1-, 2-, and 3- year were 0.773, 0.721, and 0.673, respectively. Stratified survival analysis suggested that the prognosis of the low-score group was superior to the high-score group. Moreover, the univariate and multivariate analysis indicated that risk score [hazard ratio (HR) 5.071, 95% CI 3.050, 8.432; HR 4.396, 95% CI 2.624, 7.366; p < 0.001] and stage (HR 2.500, 95% CI 1.721, 3.632; HR 2.111, 95% CI 1.443, 3.089; p < 0.001) served as an independent predictive factors in HCC. In addition, the macrophages, natural killer (NK) cells, and regulatory T (Treg) cells were significantly enriched in the high-risk group. Finally, the patients with the high-risk score might be more sensitive to cisplatin, doxorubicin, etoposide, gemcitabine, and mitomycin C.

Conclusion: We established a reliable EMTri-genes-based prognostic signature, which may hold promise for the clinical prediction.

Development of a Toll-Like Receptor-Based Gene Signature That Can Predict Prognosis, Tumor Microenvironment, and Chemotherapy Response for Hepatocellular Carcinoma

Objective: Emerging evidence highlights the implications of the toll-like receptor (TLR) signaling pathway in the pathogenesis and therapeutic regimens of hepatocellular carcinoma (HCC). Herein, a prognostic TLR-based gene signature was conducted for HCC.

Methods: HCC-specific TLRs were screened in the TCGA cohort. A LASSO model was constructed based on prognosis-related HCC-specific TLRs. The predictive efficacy, sensitivity, and independency of this signature was then evaluated and externally verified in the ICGC, GSE14520, and GSE76427 cohorts. The associations between this signature and tumor microenvironment (stromal/immune score, immune checkpoint expression, and immune cell infiltrations) and chemotherapy response were assessed in HCC specimens. The expression of TLRs in this signature was verified in HCC and normal liver tissues by Western blot. Following si-MAP2K2 transfection, colony formation and apoptosis of Huh7 and HepG2 cells were examined.

Results: Herein, we identified 60 HCC-specific TLRs. A TLR-based gene signature (MAP2K2, IRAK1, RAC1, TRAF3, MAP3K7, and SPP1) was conducted for HCC prognosis. High-risk patients exhibited undesirable outcomes. ROC curves confirmed the well prediction performance of this signature. Multivariate Cox regression analysis demonstrated that the signature was an independent prognostic indicator. Also, high-risk HCC was characterized by an increased immune score, immune checkpoint expression, and immune cell infiltration. Meanwhile, high-risk patients displayed higher sensitivity to gemcitabine and cisplatin. The dysregulation of TLRs in the signature was confirmed in HCC. MAP2K2 knockdown weakened colony formation and elevated apoptosis of Huh7 and HepG2 cells.

Conclusion: Collectively, this TLR-based gene signature might assist clinicians to select personalized therapy programs for HCC patients.

Autophagy, an accomplice or antagonist of drug resistance in HCC?

Hepatocellular carcinoma (HCC) is a highly lethal malignancy characterized by poor prognosis and a low 5-year survival rate. Drug treatment is proving to be effective in anti-HCC. However, only a small number of HCC patients exhibit sensitive responses, and drug resistance occurs frequently in advanced patients. Autophagy, an evolutionary process responsible for the degradation of cellular substances, is closely associated with the acquisition and maintenance of drug resistance for HCC. This review focuses on autophagic proteins and explores the intricate relationship between autophagy and cancer stem cells, tumor-derived exosomes, and noncoding RNA. Clinical trials involved in autophagy inhibition combined with anticancer drugs are also concerned.

Adipose Mesenchymal Stem Cell-Derived Exosomal microRNA-1236 Reduces Resistance of Breast Cancer Cells to Cisplatin by Suppressing SLC9A1 and the Wnt/β-Catenin Signaling

BACKGROUND

Emerging evidence has noted the versatile functions of mesenchymal stem cell-derived exosomes (MSC-Exos) in cancer control. This work aims to probe to function of adipose MSC-Exos (adMSC-Exos) in drug-resistance of breast cancer (BC) cells to cisplatin (DDP) and the molecules involved.

METHODS

Parental and DDP-resistant BC cell lines MCF-7 and MDA-MB-231 were used. All cells were pre-treated with adMSC-Exos. Then, the viability and apoptosis of cells after DDP treatment were determined. Differentially expressed miRNAs after adMSC-exo treatment were screened out. Rescue experiments were conducted by pre-transfecting miR-1236 inhibitor into adMSCs, and the role of miR-1236 in DDP sensitivity was determined. Targeting mRNAs of miR-1236 were predicted by bioinformatics analysis. Altered SLC9A1 expression was administrated to evaluate its function in DDP resistance.

RESULTS

The adMSC-Exos notably increased the sensitivity of either parental or DDP-resistant BC cells to DDP. SLC9A1 was notably highly expressed in DDP-resistant cells but inhibited following adMSC-exo administration. Importantly, miR-1236, which could directly bind to SLC9A1 and suppress its expression, was confirmed as an enriched miRNA in adMSC-Exos. Either inhibition of miR-1236 or upregulation of SLC9A1 blocked the pro-sensitize roles of adMSC-Exos. In addition, the Wnt/β-catenin pathway activity was suppressed by adMSC-Exos but recovered by SLC9A1.

CONCLUSION

This study evidenced that adMSC-Exos carry miR-1236 to increase sensitivity of BC cells to DDP with the involvement of SLC9A1 downregulation and Wnt/β-catenin inactivation. This finding may offer novel insights into treatment for drug-resistant BC.

Glucose Metabolism and Oxidative Stress in Hepatocellular Carcinoma: Role and Possible Implications in Novel Therapeutic Strategies

Hepatocellular carcinoma (HCC) metabolism is redirected to glycolysis to enhance the production of metabolic compounds employed by cancer cells to produce proteins, lipids, and nucleotides in order to maintain a high proliferative rate. This mechanism drives towards uncontrolled growth and causes a further increase in reactive oxygen species (ROS), which could lead to cell death. HCC overcomes the problem generated by ROS increase by increasing the antioxidant machinery, in which key mechanisms involve glutathione, nuclear factor erythroid 2-related factor 2 (Nrf2), and hypoxia-inducible transcription factor (HIF-1α). These mechanisms could represent optimal targets for innovative therapies. The tumor microenvironment (TME) exerts a key role in HCC pathogenesis and progression. Various metabolic machineries modulate the activity of immune cells in the TME. The deregulated metabolic activity of tumor cells could impair antitumor response. Lactic acid-lactate, derived from the anaerobic glycolytic rate of tumor cells, as well as adenosine, derived from the catabolism of ATP, have an immunosuppressive activity. Metabolic reprogramming of the TME via targeted therapies could enhance the treatment efficacy of anti-cancer immunotherapy. This review describes the metabolic pathways mainly involved in the HCC pathogenesis and progression. The potential targets for HCC treatment involved in these pathways are also discussed.