PD-1/PD-L blockade in gastrointestinal cancers: lessons learned and the road toward precision immunotherapy

iMLGAM: Integrated Machine Learning and Genetic Algorithm-driven Multiomics analysis for pan-cancer immunotherapy response prediction

To address the substantial variability in immune checkpoint blockade (ICB) therapy effectiveness, we developed an innovative R package called integrated Machine Learning and Genetic Algorithm-driven Multiomics analysis (iMLGAM), which establishes a comprehensive scoring system for predicting treatment outcomes through advanced multi-omics data integration. Our research demonstrates that iMLGAM scores exhibit superior predictive performance across independent cohorts, with lower scores correlating significantly with enhanced therapeutic responses and outperforming existing clinical biomarkers. Detailed analysis revealed that tumors with low iMLGAM scores display distinctive immune microenvironment characteristics, including increased immune cell infiltration and amplified antitumor immune responses. Critically, through clustered regularly interspaced short palindromic repeats screening, we identified Centrosomal Protein 55 (CEP55) as a key molecule modulating tumor immune evasion, mechanistically confirming its role in regulating T cell-mediated antitumor immune responses. These findings not only validate iMLGAM as a powerful prognostic tool but also propose CEP55 as a promising therapeutic target, offering novel strategies to enhance ICB treatment efficacy. The iMLGAM package is freely available on GitHub (https://github.com/Yelab1994/iMLGAM), providing researchers with an innovative approach to personalized cancer immunotherapy prediction.

CXCR2P1 enhances the response of gastric cancer to PD-1 inhibitors through increasing the immune infiltration of tumors

Background

Recent years, immunotherapy has emerged as a pivotal approach in cancer treatment. However, the response of gastric cancer to immunotherapy exhibits significant heterogeneity. Therefore, the early identification of gastric cancer patients who are likely to benefit from immunotherapy and the discovery of novel therapeutic targets are of critical importance.

Materials and methods

We collected data from European Nucleotide Archive (ENA) and Gene Expression Omnibus (GEO) databases. In project PRJEB25780, we performed WGCNA analysis and Lasso regression and chose CXCR2P1 for the subsequent analysis. Then, we compared the expression difference of CXCR2P1 among different groups. Kaplan-Meier curve was used to analyze the prognostic value of CXCR2P1, which was validated by project IMvigor210 and GEO datasets. ESTIMATE and CIBERSORT algorithm were used to evaluate the reshaping effect of CXCR2P1 to immune microenvironment of tumor. Differentially expressed genes (DEG) analysis, enrichGO analysis, Gene Set Enrichment Analysis (GSEA) and co-expression analysis were used to explore the cell biological function and signaling pathway involved in CXCR2P1.

Results

WGCNA identified CXCR2P1 as a hub gene significantly associated with immune response to PD-1 inhibitors in gastric cancer. CXCR2P1 expression was elevated in responders and correlated with better prognosis. Functional analysis revealed its role in reshaping the tumor immune microenvironment by promoting immune cell infiltration, including M1 macrophages, activated CD4+ T cells, and follicular helper T cells. CXCR2P1 enhanced antigen presentation via the MHC-II complex, influenced key immune pathways, such as Toll-like receptor signaling and T-cell activation, which led to the up-regulation of expression of PD-L1. GSEA showed CXCR2P1 were correlated with microRNAs. Through DEG analysis and expression analysis, MIR215 was identified as a potential direct target of CXCR2P1.

Conclusion

High expression of CXCR2P1 is correlated with better response to PD-1 inhibitor. It reshapes the immune microenvironment by increasing immune infiltration and changing the fraction of immune cells. In tumor immune microenvironment, CXCR2P1 can promote inflammation, enhance antigen presentation and activate the PD-1/PD-L1-related signaling pathway, which might be achieved by CXCR2P1-MIR215 axis.

An Overview of Predictive Biomarkers and Detection Approaches for Immunotherapy Response in GI Malignancies

This review provides an in-depth exploration of the evolving role of immunotherapy in gastrointestinal (GI) cancers, with a particular focus on immune checkpoint inhibitors (ICIs) and their associated predictive biomarkers. We present a detailed analysis of established biomarkers, such as PD-L1, microsatellite instability (MSI), tumor mutational burden (TMB), and the tumor microenvironment (TME), as well as emerging biomarkers, including gut microbiota and Epstein-Barr virus (EBV). The predictive value of these biomarkers in guiding clinical decision-making and optimizing immunotherapy outcomes is thoroughly discussed. Additionally, we highlight recent advancements in biomarker evaluation technologies, including next-generation sequencing (NGS), multiplex immunohistochemistry, and artificial intelligence (AI)-driven models. These technologies are instrumental in advancing precision medicine by enhancing the accuracy and efficiency of biomarker detection and facilitating personalized treatment approaches. The integration of these predictive biomarkers with advanced detection technologies has significantly improved the clinical efficacy of immunotherapy in GI cancers by addressing challenges such as tumor heterogeneity, immune evasion, and variable patient responses. By providing a deeper understanding of tumor biology and patient-specific factors, these tools offer the potential to optimize patient selection, treatment regimens, and, ultimately, clinical outcomes. This review underscores the transformative impact of combining predictive biomarkers with cutting-edge technologies, marking a significant step forward in the field of precision oncology for GI cancer treatment.

Therapeutic strategies targeting CD47-SIRPα signaling pathway in gastrointestinal cancers treatment

Gastrointestinal (GI) cancers are prevalent globally, with leading incidence and mortality rates among malignant tumors. Despite notable advancements in surgical resection, radiotherapy, and chemotherapy, the overall survival rates remain low. Hence, it is imperative to explore alternative approaches that enhance patient outcomes. Cluster of differentiation 47 (CD47), serving as an early diagnostic marker, is predominantly overexpressed in GI cancers and associated with poor prognosis. Targeting the CD47-signal regulatory protein alpha (SIRPα) signaling pathway may provide a novel strategy for GI cancers treatment. This study summarizes current knowledge of the structure and function of CD47 and SIRPα, their roles in signaling pathways, the prognostic significance of CD47, therapeutic strategies targeting the CD47-SIRPα signaling pathway in GI cancer, and highlights key issues for future investigations.

Non-invasive assessment of programmed cell death ligand-1 expression using 18F-FDG PET-CT imaging in esophageal squamous cell carcinoma

Programmed cell death ligand-1 (PD-L1) is an ideal checkpoint for immunohistochemical detection. The method of obtaining PD-L1 expression through biopsy can impact the accurate assessment of PD-L1 expression due to the spatial and temporal heterogeneity of tumors. Because of the limited sample size, biopsies often give only a localized picture of the tumor. In this retrospective study, a total of 2,386 metabolic tumor volume (MTV) features were extracted from 18F-FDG PET-CT images. A radiomics model was developed to holistically and non-invasively assess PD-L1 expression in patients with esophageal squamous cell carcinoma by identifying seven independent factors through feature screening. The radiomics model shows effective discrimination, with an area under the receiver operating characteristic curve of 0.888 [95% confidence interval (CI): 0.831-0.945] and 0.889 (95% CI: 0.706-1.000) for the training and validation cohorts, respectively. The results of the decision curve analysis demonstrated that utilizing the radiation model to forecast PD-L1 expression levels yielded more net benefits at threshold probabilities below 0.669. The clinical impact curves demonstrate that when the threshold probability is less than 0.501, the loss-to-benefit ratio is less than one in all cases.

Deciphering lung adenocarcinoma prognosis and immunotherapy response through an AI-driven stemness-related gene signature

Lung adenocarcinoma (LUAD) is a leading cause of cancer-related deaths, and improving prognostic accuracy is vital for personalised treatment approaches, especially in the context of immunotherapy. In this study, we constructed an artificial intelligence (AI)-driven stemness-related gene signature (SRS) that deciphered LUAD prognosis and immunotherapy response. CytoTRACE analysis of single-cell RNA sequencing data identified genes associated with stemness in LUAD epithelial cells. An AI network integrating traditional regression, machine learning, and deep learning algorithms constructed the SRS based on genes associated with stemness. Subsequently, we conducted a comprehensive exploration of the connection between SRS and both intrinsic and extrinsic immune environments using multi-omics data. Experimental validation through siRNA knockdown in LUAD cell lines, followed by assessments of proliferation, migration, and invasion, confirmed the functional role of CKS1B, a top SRS gene. The SRS demonstrated high precision in predicting LUAD prognosis and likelihood of benefiting from immunotherapy. High-risk groups classified by the SRS exhibited decreased immunogenicity and reduced immune cell infiltration, indicating challenges for immunotherapy. Conversely, in vitro experiments revealed CKS1B knockdown significantly impaired aggressive cancer phenotypes like proliferation, migration, and invasion of LUAD cells, highlighting its pivotal role. These results underscore a close association between stemness and tumour immunity, offering predictive insights into the immune landscape and immunotherapy responses in LUAD. The newly established SRS holds promise as a valuable tool for selecting LUAD populations likely to benefit from future clinical stratification efforts.

Unravelling the role of intratumoral bacteria in digestive system cancers: current insights and future perspectives

Recently, research on the human microbiome, especially concerning the bacteria within the digestive system, has substantially advanced. This exploration has unveiled a complex interplay between microbiota and health, particularly in the context of disease. Evidence suggests that the gut microbiome plays vital roles in digestion, immunity and the synthesis of vitamins and neurotransmitters, highlighting its significance in maintaining overall health. Conversely, disruptions in these microbial communities, termed dysbiosis, have been linked to the pathogenesis of various diseases, including digestive system cancers. These bacteria can influence cancer progression through mechanisms such as DNA damage, modulation of the tumour microenvironment, and effects on the host's immune response. Changes in the composition and function within the tumours can also impact inflammation, immune response and cancer therapy effectiveness. These findings offer promising avenues for the clinical application of intratumoral bacteria for digestive system cancer treatment, including the potential use of microbial markers for early cancer detection, prognostication and the development of microbiome-targeted therapies to enhance treatment outcomes. This review aims to provide a comprehensive overview of the pivotal roles played by gut microbiome bacteria in the development of digestive system cancers. Additionally, we delve into the specific contributions of intratumoral bacteria to digestive system cancer development, elucidating potential mechanisms and clinical implications. Ultimately, this review underscores the intricate interplay between intratumoral bacteria and digestive system cancers, underscoring the pivotal role of microbiome research in transforming diagnostic, prognostic and therapeutic paradigms for digestive system cancers.

Potential therapeutic targets in myeloid cell therapy for overcoming chemoresistance and immune suppression in gastrointestinal tumors

In the tumor microenvironment (TME), myeloid cells play a pivotal role. Myeloid-derived immunosuppressive cells, including tumor-associated macrophages (TAMs) and myeloid-derived suppressor cells (MDSCs), are central components in shaping the immunosuppressive milieu of the tumor. Within the TME, a majority of TAMs assume an M2 phenotype, characterized by their pro-tumoral activity. These cells promote tumor cell growth, angiogenesis, invasion, and migration. In contrast, M1 macrophages, under appropriate activation conditions, exhibit cytotoxic capabilities against cancer cells. However, an excessive M1 response may lead to pro-tumoral inflammation. As a result, myeloid cells have emerged as crucial targets in cancer therapy. This review concentrates on gastrointestinal tumors, detailing methods for targeting macrophages to enhance tumor radiotherapy and immunotherapy sensitivity. We specifically delve into monocytes and tumor-associated macrophages' various functions, establishing an immunosuppressive microenvironment, promoting tumorigenic inflammation, and fostering neovascularization and stromal remodeling. Additionally, we examine combination therapeutic strategies.

GRIN2A mutation is a novel indicator of stratifying beneficiaries of immune checkpoint inhibitors in multiple cancers

Glutamate-NMDAR receptors (GRINs) have been reported to influence cancer immunogenicity; however, the relationship between GRIN alterations and the response to immune checkpoint inhibitors (ICIs) has not been determined. This study combined clinical characteristics and mutational profiles from multiple cohorts to form a discovery cohort (n = 901). The aim of this study was to investigate the correlation between the mutation status of the GRIN gene and the response to ICI therapy. Additionally, an independent ICI-treated cohort from the Memorial Sloan Kettering Cancer Center (MSKCC, N = 1513) was used for validation. Furthermore, this study explored the associations between GRIN2A mutations and intrinsic and extrinsic immunity using multiomics analysis. In the discovery cohort, patients with GRIN2A-MUTs had improved clinical outcomes, as indicated by a higher objective response rate (ORR: 36.8% vs 25.8%, P = 0.020), durable clinical benefit (DCB: 55.2% vs 38.7%, P = 0.005), prolonged progression-free survival (PFS: HR = 0.65; 95% CI 0.49 to 0.87; P = 0.003), and increased overall survival (OS: HR = 0.67; 95% CI 0.50 to 0.89; P = 0.006). Similar results were observed in the validation cohort, in which GRIN2A-MUT patients exhibited a significant improvement in overall survival (HR = 0.66; 95% CI = 0.49 to 0.88; P = 0.005; adjusted P = 0.045). Moreover, patients with GRIN2A-MUTs exhibited an increase in tumor mutational burden, high expression of costimulatory molecules, increased activity of antigen-processing machinery, and infiltration of various immune cells. Additionally, gene sets associated with cell cycle regulation and the interferon response were enriched in GRIN2A-mutated tumors. In conclusion, GRIN2A mutation is a novel biomarker associated with a favorable response to ICIs in multiple cancers.

Matrix metalloproteinase-2 inducing COL1A1 synthesis via integrin alpha Ⅴ promotes invasion and metastasis of cholangiocarcinoma cells

INTRODUCTION AND OBJECTIVES

Cholangiocarcinoma (CCA) is characterized by early distant invasion and metastasis, whereas the underlying mechanism is still obscure. Increasing evidence shows that collagen type Ι alpha 1 (COL1A1) is a gene associated with the progression of multiple diseases. Here, we attempted to investigate the role of COL1A1 in CCA.

MATERIALS AND METHODS

The expression of COL1A1 between tumor tissues and adjacent normal tissues obtained from CCA patients was detected by Western blot and immunofluorescence, followed by analysis of its clinical significance. Then, the biological effects of COL1A1 overexpression or knockdown on CCA cells were evaluated in vitro and in vivo. Finally, molecular mechanism of COL1A1 in regulating the invasion and metastasis of CCA cells was determined by a series of experiments.

RESULTS

COL1A1 expression was significantly higher in CCA pathological tissues than in corresponding adjacent normal tissues. Analysis of 83 CCA patients showed that higher expression of COL1A1 was correlated with poorer patient prognosis. Notably, overexpression or knockdown experiments revealed that COL1A1 contributed to the migration and invasion, as well as epithelial-to-mesenchymal transition (EMT), in CCA cells. Further investigations demonstrated that matrix metalloproteinase-2 (MMP2) promoted COL1A1 upregulation via the integrin alpha Ⅴ pathway, therefore affecting ECM remodelling and inducing EMT in CCA cells. Moreover, COL1A1 expression was positively related to PD-1 and PD-L1 in CCA, and COL1A1 increased PD-L1 expression by activating the NF-κB pathway.

CONCLUSIONS

COL1A1 plays an important role in regulating CCA progression and may act as a promising biomarker and therapeutic target for CCA.

Identification and validation of the association of Janus kinase 2 mutations with the response to immune checkpoint inhibitor therapy

BACKGROUND

Janus kinase 2 (JAK2) mutation plays an important role in T cell immunity. However, the effect of JAK2 mutation on immunotherapy is largely uncharacterized.

METHODS

In this study, we analyzed the effect of JAK2 mutation on the efficacy and outcomes of immune checkpoint inhibitor (ICI) therapy in the discovery cohort (n = 662) and the verification cohort (n = 1423). Furthermore, we explored the association of JAK2 mutation with the tumor immune microenvironment in a multiomics cohort.

RESULTS

In the discovery cohort (n = 662), JAK2 mutant-type patients had a better objective response rate (58.8% vs. 26.7%, P = 0.010), durable clinical benefit (64.7% vs. 38.9%, P = 0.043), progression-free survival (hazard ratio [HR] = 0.431, P = 0.015), and overall survival (HR = 0.378, P = 0.025), relative to JAK2 wild-type patients. Moreover, we further verified the prognostic significance of JAK2 mutation in an independent ICI treatment cohort with a larger sample size (n = 1423). In addition, we discovered that the JAK2 mutation was remarkably related to increased immunogenicity, such as a higher TMB, higher expression of costimulatory molecules and stimulation of antigen processing mechanisms. In addition, JAK2 mutation was positively correlated with activated anticancer immunity, such as infiltration of various immune cells and higher expression of chemokines.

CONCLUSION

Our study demonstrates that JAK2 mutation is a novel marker that can be used to effectively predict prognosis and response to ICI therapy.

Comprehensive molecular analysis identifies RET alterations association with response of ICIs in multi-immunotherapy cohorts

BACKGROUND

The RET gene, which is frequently mutated across many types of cancer, has been proven to be critically involved in tumorigenesis and tumour development; however, its prediction of the therapeutic efficacy of immune checkpoint inhibitor (ICI) therapy remains to be elucidated. The present research aims to investigate the association between RET mutations and the efficiency of ICI therapy.

METHOD

We analysed the role of RET mutations in predicting the prognosis of patients receiving ICIs therapy in the discovery cohort and validated it in the validation cohort. Then, multi-omics data from TCGA pan-cancer cohort was employed to propose the association between RET mutations and tumour inflamed anti-tumour immune response and tumour antigenicity.

RESULTS

Our study revealed that among 606 cases and across five types of cancer, RET mutation was associated with better clinical outcomes for ICIs therapy, including elevated response rate, longer progression-free survival PFS, and longer overall survival OS. Multivariate analysis showed that RET mutation could independently predict the prognosis of patients treated with ICIs, after adjusting cancer types. The predictive value of RET status for the OS of patients treated with ICIs immunotherapy was further validated in the validation cohort (n = 1,409). Subgroup analysis suggested that only the monotherapy group showed significant differences in OS(P < 0.05) and PFS(P < 0.05) between RET-wildtype tumours and RET-mutant tumours. Multi-omics data analysis revealed potential anti-tumour immunity mechanisms of RET mutations, suggesting that RET-mutant tumours have enhanced immunogenicity, higher expression of immune checkpoints and chemokines, and higher immune cell infiltration than those observed in RET-wildtype tumours; thus, potentially indicating a more favourable response to immunotherapy.

CONCLUSIONS

RET mutation may be a predictive biomarker of enhanced response to ICIs therapy. Extensive investigation of the underlying molecular mechanisms and prospective studies are needed in the future.

SPP1 is associated with adverse prognosis and predicts immunotherapy efficacy in penile cancer

BACKGROUND

The effect of SPP1 in squamous cell carcinoma of the penis (PSCC) remained unknown. We attempted to clarify the function of the SPP1 gene in PSCC.

METHOD

Eight paired penile cancer specimens (including penile cancer tissue, paracancerous tissue, and positive lymph node tissue) subjected to whole transcriptome sequencing were analysed to identify differentially expressed genes. We used immunohistochemistry to detect the expression of SPP1 protein and immune cell related proteins in penile cancer tissue. Then, we performed weighted gene coexpression network analysis (WGCNA) to identify the genes related to SPP1 in penile cancer tissue and positive lymph node tissue. Based on the GSE57955 dataset, the CIBERSORT and ssGSEA algorithms were carried out to investigate the immune environment of PSCC. GSVA analysis was conducted to identify the signaling pathways related to SPP1 subgroups. Enzyme-linked immunosorbent assay (ELISA) method was adopted to detect SPP1 level in the serum of 60 patients with penile cancer.

RESULTS

Differential analysis indicated that SPP1 was the most differentially upregulated gene in both penile cancer tissues and positive lymph node tissues. Survival analysis suggested that the prognosis of the low-SPP1 group was significantly poorer than that of the high-SPP1 group. Subsequently, immune-related bioinformatics showed that SPP1 was significantly associated with B cells, CD8 + T cells, CD4 + T cells, macrophages, helper T cells, neutrophils and dendritic cells. The immunohistochemical results showed that the high-SPP1 group was characterized by relatively high expression of CD16 and relatively low expression of CD4. GSVA analysis indicated that high-SPP1 group was significantly associated with immune-related pathways such as PD-L1 expression and the PD-1 checkpoint pathway in cancer and the TNF signaling pathway. ELISA demonstrated that the serum level of SPP1 in patients with positive lymph node metastasis of penile cancer was significantly higher than that in patients with negative lymph node metastasis of penile cancer.

CONCLUSION

Our study shows that the SPP1 gene might be an effective biomarker for predicting the prognosis and the efficacy of immunotherapy in PSCC patients.

A Clinical Viewpoint on the Use of Targeted Therapy in Advanced Gastric Cancer

The development of therapies for advanced gastric cancer (GC) has made significant progress over the past few years. The identification of new molecules and molecular targets is expanding our understanding of the disease's intricate nature. The end of the classical oncology era, which relied on well-studied chemotherapeutic agents, is giving rise to novel and unexplored challenges, which will cause a significant transformation of the current oncological knowledge in the next few years. The integration of established clinically effective regimens in additional studies will be crucial in managing these innovative aspects of GC. This study aims to present an in-depth and comprehensive review of the clinical advancements in targeted therapy and immunotherapy for advanced GC.

POLD4 Promotes Glioma Cell Proliferation and Suppressive Immune Microenvironment: A Pan-Cancer Analysis Integrated with Experimental Validation

POLD4 plays a crucial part in the complex machinery of DNA replication and repair as a vital component of the DNA polymerase delta complex. In this research, we obtained original information from various publicly available databases. Using a blend of R programming and internet resources, we initiated an extensive examination into the correlation between POLD4 expression and the various elements of cancers. In addition, we performed knockdown experiments in glioma cell lines to authenticate its significant impact. We discovered that POLD4 is upregulated in various malignant tumors, demonstrating a significant correlation with poor patient survival prognosis. Using function analysis, it was uncovered that POLD4 exhibited intricate associations with signaling pathways spanning multiple tumor types. Subsequent investigations unveiled the close association of POLD4 with the immune microenvironment and the effectiveness of immunotherapy. Drugs like trametinib, saracatinib, and dasatinib may be used in patients with high POLD4. Using experimental analysis, we further confirmed the overexpression of POLD4 in gliomas, as well as its correlation with glioma recurrence, proliferation, and the suppressive immune microenvironment. Our research findings indicate that the expression pattern of POLD4 not only serves as a robust indicator of prognosis in cancer patients but also holds promising potential as a new focus for treatment.

Core fucosylation and its roles in gastrointestinal glycoimmunology

Glycosylation is a common post-translational modification in eukaryotic cells. It is involved in the production of many biologically active glycoproteins and the regulation of protein structure and function. Core fucosylation plays a vital role in the immune response. Most immune system molecules are core fucosylated glycoproteins such as complements, cluster differentiation antigens, immunoglobulins, cytokines, major histocompatibility complex molecules, adhesion molecules, and immune molecule synthesis-related transcription factors. These core fucosylated glycoproteins play important roles in antigen recognition and clearance, cell adhesion, lymphocyte activation, apoptosis, signal transduction, and endocytosis. Core fucosylation is dominated by fucosyltransferase 8 (Fut8), which catalyzes the addition of α-1,6-fucose to the innermost GlcNAc residue of N-glycans. Fut8 is involved in humoral, cellular, and mucosal immunity. Tumor immunology is associated with aberrant core fucosylation. Here, we summarize the roles and potential modulatory mechanisms of Fut8 in various immune processes of the gastrointestinal system.

Exploration of cuprotosis-related genes for predicting prognosis and immunological characteristics in acute myeloid leukaemia based on genome and transcriptome

BACKGROUND

Acute myeloid leukemia (AML) is a common hematologic malignancy with a generally unfavorable prognosis. Cuprotosis as a new form of programmed cell death has been shown to play an important role in tumorigenesis and progression; However, the relationship between cuprotosis and the prognosis of AML patients remains unclear.

METHODS

Transcriptomic and genomics data, along with clinical information, were obtained from the TCGA and GEO databases. Especially, unsupervised clustering and machining learning were used to identify molecular subtypes and cuprotosis-related risk scores respectively. Kaplan-Meier analysis, univariate and multivariate Cox regression, and Receiver Operator Characteristic curve (ROC) were performed to assess the prognosis based on cuprotosis-related genes (CRGs). Moreover, multiple algorithms were used to evaluate immunological heterogeneity among patients with different risk scores. For in vitro analysis, the expression of genes involved in CRGs was detected by Quantitative Reverse Transcription Polymerase (qRT-PCR) in AML patients.

RESULTS

Transcriptomic and genome data indicated the immense heterogeneity in the CRGs landscape of normal and tumor samples. Cuprotosis subtype A and cuprotosis regulatory subtype B in the genomics map and biological characteristics were significantly different from the other groups. Furthermore, these two subtypes had lower risk scores and longer survival times compared to other groups. Cox analyses indicated that risk score was an independent prognostic factor for AML patients. In addition, our risk score could be an indicator of survival outcomes in immunotherapy datasets.

CONCLUSIONS

Our study demonstrates the potential of CRGs in guiding the prognosis, treatment, and immunological characteristics of AML patients.

A Comparative Analysis of Optimization Algorithms for Gastrointestinal Abnormalities Recognition and Classification Based on Ensemble XcepNet23 and ResNet18 Features

Esophagitis, cancerous growths, bleeding, and ulcers are typical symptoms of gastrointestinal disorders, which account for a significant portion of human mortality. For both patients and doctors, traditional diagnostic methods can be exhausting. The major aim of this research is to propose a hybrid method that can accurately diagnose the gastrointestinal tract abnormalities and promote early treatment that will be helpful in reducing the death cases. The major phases of the proposed method are: Dataset Augmentation, Preprocessing, Features Engineering (Features Extraction, Fusion, Optimization), and Classification. Image enhancement is performed using hybrid contrast stretching algorithms. Deep Learning features are extracted through transfer learning from the ResNet18 model and the proposed XcepNet23 model. The obtained deep features are ensembled with the texture features. The ensemble feature vector is optimized using the Binary Dragonfly algorithm (BDA), Moth-Flame Optimization (MFO) algorithm, and Particle Swarm Optimization (PSO) algorithm. In this research, two datasets (Hybrid dataset and Kvasir-V1 dataset) consisting of five and eight classes, respectively, are utilized. Compared to the most recent methods, the accuracy achieved by the proposed method on both datasets was superior. The Q_SVM's accuracies on the Hybrid dataset, which was 100%, and the Kvasir-V1 dataset, which was 99.24%, were both promising.

Intracellular Adhesion Molecule-1 Improves Responsiveness to Immune Checkpoint Inhibitor by Activating CD8+ T Cells

Immune checkpoint inhibitor (ICI) clinically benefits cancer treatment. However, the ICI responses are only achieved in a subset of patients, and the underlying mechanisms of the limited response remain unclear. 160 patients with non-small cell lung cancer treated with anti-programmed cell death protein-1 (anti-PD-1) or anti-programmed death ligand-1 (anti-PD-L1) are analyzed to understand the early determinants of response to ICI. It is observed that high levels of intracellular adhesion molecule-1 (ICAM-1) in tumors and plasma of patients are associated with prolonged survival. Further reverse translational studies using murine syngeneic tumor models reveal that soluble ICAM-1 (sICAM-1) is a key molecule that increases the efficacy of anti-PD-1 via activation of cytotoxic T cells. Moreover, chemokine (CXC motif) ligand 13 (CXCL13) in tumors and plasma is correlated with the level of ICAM-1 and ICI efficacy, suggesting that CXCL13 might be involved in the ICAM-1-mediated anti-tumor pathway. Using sICAM-1 alone and in combination with anti-PD-1 enhances anti-tumor efficacy in anti-PD-1-responsive tumors in murine models. Notably, combinatorial therapy with sICAM-1 and anti-PD-1 converts anti-PD-1-resistant tumors to responsive ones in a preclinical study. These findings provide a new immunotherapeutic strategy for treating cancers using ICAM-1.

Immunological Role of TP53 Somatic Mutation Classification in Human Cancers

Background

TP53 is a very common tumor suppressor gene and has implicated in various cancers. A systematic immunological analysis of TP53 somatic mutation classification in multiple cancers is still lacking.

Methods

To assess the immunological value of TP53 somatic mutation classification in various cancers, we integrated a series of bioinformatics methods to analyze the role of TP53 gene across the public databases, such as UCSC Xena, Cancer Cell Line Encyclopedia (CCLE), Ensembl, and Genotype-Tissue Expression (GTEx).

Results

The results revealed that the TP53 expression level had significant difference in tumor tissues and normal tissues, and it had a high expression level in most malignant tumors. Moreover, the missense mutation is the most common type of TP53 mutation in most cancers. In addition, the Cox proportional hazards model analysis and Kaplan-Meier (KM) survival analysis demonstrated that the TP53 expression is a high-risk factor in brain lower-grade glioma (LGG), prostate adenocarcinoma (PRAD), and uterine carcinosarcoma (UCS), which is opposite in uterine corpus endometrial carcinoma (UCEC). Besides, compared to the TP53 nontruncating mutation classification samples, we found that TP53 truncating mutation samples had lower TP53 expression levels in certain types of cancer. Notably, TP53 was associated with the mismatch repair (MMR) gene in some cancers which contained truncating or nontruncating mutation. Based on the classification of truncating or nontruncating mutation, we also discovered that TP53 expression was positively or negatively correlated with the immune score, stromal score, and the levels of immune cell infiltration in different cancers.

Conclusions

Our research reveals an overarching landscape of immunological value on TP53 status in various malignant tumors. According to our results, we demonstrate that TP53 also plays an immunological role in various cancers.

Comprehensive analysis of the correlation of the pan-cancer gene HAUS5 with prognosis and immune infiltration in liver cancer

Liver hepatocellular carcinoma (LIHC) is one of the most common malignancies and places a heavy burden on patients worldwide. HAUS augmin-like complex subunit 5 (HAUS5) is involved in the occurrence and development of various cancers. However, the functional role and significance of HAUS5 in LIHC remain unclear. The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE) and Gene Expression Omnibus (GEO) databases were used to analyze the mRNA expression of HAUS5. The value of HAUS5 in predicting LIHC prognosis and the relationship between HAUS5 and clinicopathological features were assessed by the Kaplan-Meier plotter and UALCAN databases. Functional enrichment analyses and nomogram prediction model construction were performed with the R packages. The LinkedOmics database was searched to reveal co-expressed genes associated with HAUS5. The relationship between HAUS5 expression and immune infiltration was explored by searching the TISIDB database and single-sample gene set enrichment analysis (ssGSEA). The Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the Human Protein Atlas (HPA) databases were used to evaluate HAUS5 protein expression. Finally, the effect of HAUS5 on the proliferation of hepatoma cells was verified by CCK-8, colony formation and EdU assays. HAUS5 is aberrantly expressed and associated with a poor prognosis in most tumors, including LIHC. The expression of HAUS5 is significantly correlated with clinicopathological indicators in patients with LIHC. Functional enrichment analysis showed that HAUS5 was closely related to DNA replication, cell cycle and p53 signaling pathway. HAUS5 may serve as an independent risk factor for LIHC prognosis. The nomogram based on HAUS5 had area under the curve (AUC) values of 0.74 and 0.77 for predicting the 3-year and 5-year overall survival (OS) of LIHC patients. Immune correlation analysis showed that HAUS5 was significantly associated with immune infiltration. Finally, the results of in vitro experiments showed that when HAUS5 was knocked down, the proliferation of hepatoma cells was significantly decreased. The pan-oncogene HAUS5 is a positive regulator of LIHC progression and is closely associated with a poor prognosis in LIHC. Moreover, HAUS5 is involved in immune infiltration in LIHC. HAUS5 may be a new prognostic marker and therapeutic target for LIHC patients.

Prognosis and personalized medicine prediction by integrated whole exome and transcriptome sequencing of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a clinically and genetically heterogeneous disease. To better describe the clinical value of the main driver gene mutations of HCC, we analyzed the whole exome sequencing data of 125 patients, and combined with the mutation data in the public database, 14 main mutant genes were identified. And we explored the correlation between the main mutation genes and clinical features. Consistent with the results of previous data, we found that TP53 and LRP1B mutations were related to the prognosis of our patients by WES data analysis. And we further explored the associated characteristics of TP53 and LRP1B mutations. However, it is of great clinical significance to tailor a unique prediction method and treatment plan for HCC patients according to the mutation of TP53. For TP53 wild-type HCC patients, we proposed a prognostic risk model based on 11 genes for better predictive value. According to the median risk score of the model, HCC patients with wild-type TP53 were divided into high-risk and low-risk groups. We found significant transcriptome changes in the enrichment of metabolic-related pathways and immunological characteristics between the two groups, suggesting the predictability of HCC immunotherapy by using this model. Through the CMap database, we found that AM580 had potential therapeutic significance for high-risk TP53 wild-type HCC patients.

High concordance rate of capillary electrophoresis workflow for microsatellite instability analysis and mismatch repair (MMR) immunostaining in colorectal carcinoma

Microsatellite instability (MSI) is the primary predictive biomarker for therapeutic efficacies of cancer immunotherapies. Establishment of the MSI detection methods with high sensitivity and accessibility is important. Because MSI is mainly caused by defects in DNA mismatch repair (MMR), immunohistochemical (IHC) staining for the MMR proteins has been widely employed to predict the responses to immunotherapies. Thus, due to the high sensitivity of PCR, the MSI-PCR analysis has also been recommended as the primary approach as MMR IHC. This study aimed to develop a sensitive and convenient platform for daily MSI-PCR services. The routine workflow used a non-labeling QIAxcel capillary electrophoresis system which did not need the fluorescence labeling of the DNA products or usage of a multi-color fluorescence reader. Furthermore, the 15 and 1000 bp size alignment markers were used to precisely detect the size of the DNA product. A cohort of 336 CRC cases was examined by MSI-PCR on the five mononucleotide MSI markers recommended by ESMO. The PCR products were analyzed in the screening gels, followed by high-resolution gel electrophoresis for confirmation if needed. In the MSI-PCR tests, 90.1% (303/336) cases showed clear major shift patterns in the screening gels, and only 33 cases had to be re-examined using the high-resolution gels. The cohort was also analyzed by MMR IHC is, which revealed 98.5% (331/336) concordance with MSI-PCR. In the five discordant cases, 4 (3 MSI-L and 1 MSS) showed MSH6 loss. Besides, one case exhibited MSI-H but no loss in the MMR IHC. Further NGS analysis, in this case, found that missense and frameshift mutations in the PMS2 and MSH6 genes occurred, respectively. In conclusion, the non-labeling MSI-PCR capillary electrophoresis revealed high concordance with the MMR IHC analysis and is cost- and time-effective. Therefore, it shall be highly applicable in clinical laboratories.

Co-expression of receptor tyrosine kinases and CD8 T-lymphocyte genes is associated with distinct prognoses, immune cell infiltration patterns and immunogenicity in cancers

Tumor angiogenesis and the immune microenvironment are 2 essential aspects of the tumor microenvironment (TME). The combination of receptor tyrosine kinase (RTK) inhibitor (TKI)-mediated antiangiogenic therapy and CD8 T-lymphocyte-mediated immunotherapy has become an important focus of cancer treatment, with good results for many tumor types. However, the complex regulatory interactions between these 2 treatment strategies have not been elucidated. Therefore, we systematically investigated the association between the RTKs and CD8 T-lymphocyte genes (CD8Ts) across cancers. We comprehensively evaluated alterations in RTK genes across cancers and examined the co-expression of RTKs and CD8Ts using a weighted gene co-expression network analysis. We found that RTKs exhibited extensive genetic alterations across cancers and were significantly related to the activity of cancer hallmark-related pathways. We identified co-expression between the RTKs and CD8Ts. The low co-expression score subtype was associated with significant better clinical benefits and was characterized by a hot immune microenvironment, including more infiltrating immune cells, higher chemokine expression, and stronger immunogenicity, such as the tumor mutation burden and neoantigens. Two immunotherapy cohorts confirmed that patients with low co-expression scores had an inflamed TME phenotype and significant therapeutic advantages. Then, 4 co-expression patterns were identified, with different patterns reflecting different prognoses and immune microenvironments. The RTK^lowCD8T^high group was associated with the best prognosis and immune-activated microenvironment. In summary, the present study indicates co-expression of RTKs and CD8Ts, which supports the potential application of the combination of inhibiting RTKs activity via TKI-targeted therapy and increasing CD8 T cell activity via immunotherapy in the treatment of cancer.

Identification and Validation of RELN Mutation as a Response Indicator for Immune Checkpoint Inhibitor Therapy in Melanoma and Non-Small Cell Lung Cancer

Remarkable clinical benefits in several advanced cancers are observed under the treatment of immune checkpoint inhibitor (ICI) agents. However, only a smaller proportion of patients respond to the treatments. Reelin (RELN) is frequently mutated in the cancer genome. In this study, the RELN mutation association with ICI treatment efficacy in melanoma and non-small cell lung cancer (NSCLC) was elucidated. Data from 631 melanoma and 109 NSCLC patients with both ICI treatment data and pre-treatment mutational profiles were collected. In addition, from the Cancer Genome Atlas (TCGA) project, we also obtained both tumors to explore the immunologic features behind RELN mutations. Melanoma patients with RELN mutations exhibited a favorable ICI survival benefit when compared with wild-type patients (HR: 0.66, 95% CI: 0.51-0.87, p = 0.003). A higher response rate was also noticed in RELN-mutated patients (38.9% vs. 28.3%, p = 0.017). The association of RELN mutations with a preferable immunotherapy outcome and response was further confirmed in NSCLC. Further exploration demonstrated that favorable immunocyte infiltration and immune response signaling pathways were found in patients with RELN mutations. In this study, RELN mutations were identified to connect with a better immune microenvironment and an improved ICI efficacy in melanoma and NSCLC, which provides a potential biomarker for immunological feature evaluation and immunotherapeutic outcome prediction at the molecular level.

Plasma extracellular vesicle derived protein profile predicting and monitoring immunotherapeutic outcomes of gastric cancer

Immune checkpoint inhibitor (ICI)-based immunotherapy brought new hope for gastric cancer (GC) treatment. However, due to the lack of proper biomarkers, patient selection and outcome prediction for GC's immunotherapy remain unsatisfying. In this study, through applying an extracellular vesicle (EV) protein expression array, we assessed the correlation of plasma EV-derived protein spectrum with outcomes of ICI-related therapeutic combinations. Plasma from 112 GC patients received ICI-related therapies were investigated retrospectively/prospectively as three cohorts. We identified four plasma EV-derived proteins (ARG1/CD3/PD-L1/PD-L2) from 42 crucial candidate proteins and combined them as an EV-score that robustly predicting immunotherapeutic outcomes at baseline and dynamically monitoring disease progression along with treatment. High EV-score reflected microenvironmental features of stronger antitumour immunity, characterized by more activated CD8+ T/NK cells, higher TH1/TH2 ratio and higher expressions of IFN-γ/perforin/granzymes in paired peripheral blood, which were verified by dataset analysis and in vivo experiments. EV-score≥1 GC received more therapeutic benefits from ICIs, while EV-score < 1 GC potentially benefited more from ICIs combining HER2-targeted therapies. Collectively, through proposing a plasma EV-score on protein level that powerfully predicting and monitoring GC's immunotherapeutic outcomes, our work facilitated clinical patient selection and decision-makings, and provided mechanistical insights for immunotherapy-related microenvironmental changes and improvements for current ICI-regimens.

Tubulin Alpha 1b Is Associated with the Immune Cell Infiltration and the Response of HCC Patients to Immunotherapy

Tubulin alpha 1b (TUBA1B) is an important microtubule isoform that is involved in the formation of the cytoskeleton. The objective of our study was to explore the potential of TUBA1B in predicting the prognosis of HCC and patients’ response to immunotherapy. Raw data was extracted from TCGA and GEO databases, and then HCCDB, TIMER, HPA, and GEPIA websites, as well as R software, were used to perform bioinformatics analysis to investigate the potential of TUBA1B as a prognostic and immunotherapeutic marker for hepatocellular carcinoma (HCC). We found that both TUBA1B mRNA and protein were highly expressed in HCC. TUBA1B was proved to be an independent prognostic predictor of HCC. Additionally, TUBA1B expression was associated with the infiltration of several immune cells in HCC. Moreover, TUBA1B was coexpressed with immune-related genes and immune checkpoints. Patients expressing high TUBA1B responded better to immune checkpoint inhibitor (ICI) therapy. GO and KEGG analyses revealed that TUBA1B may be involved in the processes of cell cycle, spliceosome, and DNA replication. In conclusion, TUBA1B is expected to be a prognostic and immunotherapeutic marker for HCC.

A mutation-based gene set predicts survival benefit after immunotherapy across multiple cancers and reveals the immune response landscape

BACKGROUND

Immune checkpoint inhibitor (ICI) therapy has revolutionized the treatment of many cancers. However, the limited population that benefits from ICI therapy makes it necessary to screen predictive biomarkers for stratifying patients. Currently, many biomarkers, such as tumor mutational burden (TMB), have been used in the clinic as indicative biomarkers. However, some high-TMB patients with mutations in genes that are closely related to immunotherapeutic resistance are not sensitive to ICI therapy. Thus, there is a need to move beyond TMB and identify specific genetic determinants of the response to ICI therapy. In this study, we established a comprehensive mutation-based gene set across different tumor types to predict the efficacy of ICI therapy.

METHODS

We constructed and validated a mutational signature to predict the prognosis of patients treated with ICI therapy. Then, the underlying immune response landscapes of different subtypes were investigated with multidimensional data.

RESULTS

This study included genomic and clinical data for 12,647 patients. An eleven-gene mutation-based gene set was generated to divide patients into a high-risk group and a low-risk group in a training cohort (1572 patients with 9 types of cancers who were treated with ICI therapy). Validation was performed in a validation cohort (932 patients with 5 types of cancers who were treated with ICI therapy). Mutations in these 11 genes were associated with a better response to ICI therapy. In addition, the mutation-based gene set was demonstrated to be an independent prognostic factor after ICI therapy. We further explored the role of the immune context in determining the benefits of immunotherapy in 10,143 patients with 33 types of cancers and found distinct immune landscapes for the high- and low-risk groups.

CONCLUSIONS

The mutation-based gene set developed in this study can be used to reliably predict survival benefit across cancers in patients receiving ICI therapy. The close interplay between the extrinsic and intrinsic immune landscapes in the identified patient subgroups and the subgroups' differing responses to ICI therapy could guide immunotherapy treatment decisions for cancer patients.

Constructing a Novel Signature Based on Immune-Related lncRNA to Improve Prognosis Prediction of Cervical Squamous Cell Carcinoma Patients

We downloaded gene expression data, clinical data, and somatic mutation data of cervical squamous cell carcinoma (CSCC) patients from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Predictive lncRNAs were screened using univariate analysis and least absolute shrinkage and selection operator (LASSO) regression, and risk scores were calculated for each patient according to the expression levels of lncRNAs and regression coefficients to establish a risk model that could be a novel signature. We assessed the correlation between immune infiltration status, chemotherapeutics sensitivity, immune checkpoint proteins (ICP), and the signature. Therefore, we selected 11 immune-related lncRNAs (WWC2,AS2, STXBP5.AS1, ERICH6.AS1, USP30.AS1, LINC02073, RBAKDN, IL21R.AS1, LINC02078, DLEU1, LINC00426, BOLA3.AS1) to construct the risk model. Patients who were in the high-risk group had a shorter survival time than those in the low-risk group (p < 0.001). Risk scores in the signature were negatively correlated with macrophage M1, macrophage M2, and T cell CD8 + ; what's more, T cell CD8 + was higher in the low-risk group. The expression levels of ICP such as PD-L1, PD-1, CTLA-4, TIGIT, LAG-3, and TIM-3 were substantially higher in the low-risk group. For chemotherapeutic agents, high-risk scores were associated with higher half-inhibitory concentrations (IC50) of cisplatin. These findings suggested that the risk model can be a novel signature for predicting CSCC patients' prognosis, and it also can be used to formulate clinical treatment plans for CSCC patients.

Prognostic Value and Immunological Role of KIFC1 in Hepatocellular Carcinoma

As one of the members of the kinesin family, the role and potential mechanism of kinesin family member C1 (KIFC1) in the development of liver hepatocellular carcinoma (LIHC), especially in the immune infiltration, have not been fully elucidated. In this study, multiple databases and immunohistochemistry were employed to analyze the role and molecular mechanism including the immune infiltration of KIFC1 in LIHC. Generally, KIFC1 mRNA expression was overexpressed in LIHC tissues than normal tissues, and its protein was also highly expressed in the LIHC. KIFC1 mRNA expression was correlated with tumor grade and TNM staging, which was negatively correlated with overall survival and disease-free survival. Moreover, univariable and multivariate Cox analysis revealed that upregulated KIFC1 mRNA is an independent prognostic factor for LIHC. The KIFC1 promoter methylation level was negatively associated with KIFC1 mRNA expression and advanced stages and grade in LIHC. The different methylation sites of KIFC1 had a different effect on the prognosis of LIHC. Specifically, the KIFC1 mRNA expression level showed intense correlation with tumor immunity, such as tumor-infiltrating immune cells and immune scores as well as multiple immune-related genes. Moreover, KIFC1 co-expressed with some immune checkpoints and related to the responses to immune checkpoint blockade (ICB) and chemotherapies. Significant GO analysis showed that genes correlated with KIFC1 served as catalytic activity, acting on DNA, tubulin binding, histone binding, ATPase activity, and protein serine/threonine kinase activity. KEGG pathway analysis showed that these genes related to KIFC1 are mainly enriched in signal pathways such as cell cycle, spliceosome, pyrimidine metabolism, and RNA transport. Conclusively, KIFC1 was upregulated and displayed a prognostic value in LIHC. Moreover, KIFC1 may be involved in the LIHC progression partially through immune evasion and serve as a predictor of ICB therapies and chemotherapies.

Bromodomain and extra-terminal inhibitors emerge as potential therapeutic avenues for gastrointestinal cancers

Gastrointestinal (GI) cancers, including colorectal cancer, pancreatic cancer, liver cancer and gastric cancer, are severe social burdens due to high incidence and mortality rates. Bromodomain and extra-terminal (BET) proteins are epigenetic readers consisting of four conserved members (BRD2, BRD3, BRD4 and BRDT). BET family perform pivotal roles in tumorigenesis through transcriptional regulation, thereby emerging as potential therapeutic targets. BET inhibitors, disrupting the interaction between BET proteins and acetylated lysines, have been reported to suppress tumor initiation and progression in most of GI cancers. In this review, we will demonstrate how BET proteins participate in the GI cancers progression and highlight the therapeutic potential of targeting BET proteins for GI cancers treatment.

Cancer Progression Mediated by CAFs Relating to HCC and Identification of Genetic Characteristics Influencing Prognosis

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignancies, and although there are several treatment options, the overall results are not satisfactory. Cancer-associated fibroblasts (CAFs) can promote cancer progression through various mechanisms.

METHODS

HCC-associated mRNA data were sourced from The Cancer Genome Atlas database (TCGA) and International Cancer Genome Consortium (ICGC) database. First, the differentially expressed CAF-related genes (CAF-DEGs) were acquired by difference analysis and weighted gene coexpression network analysis (WGCNA). Moreover, a CAF-related risk model was built by Cox analysis. Kaplan-Meier (K-M) curves and receiver operating characteristic (ROC) curves were utilized to evaluate the validity of this risk model. Furthermore, enrichment analysis of differentially expressed genes (DEGs) between the high- and low-risk groups was executed to explore the functions relevant to the risk model. Furthermore, this study compared the differences in immune infiltration, immunotherapy, and drug sensitivity between the high- and low-risk groups. Finally, we verified the mRNA expression levels of selected prognostic genes by quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

107 CAF-DEGs were identified in the HCC samples, and five prognosis-related genes (ACTA2, IGJ, CTHRC1, CXCL12, and LAMB1) were obtained by Cox analysis and utilized to build a CAF-related risk model. K-M analysis illustrated a low survival in the high-risk group, and ROC curves revealed that the risk model could accurately predict the 1-, 3-, and 5-year overall survival (OS) of HCC patients. In addition, Cox analysis demonstrated that the risk score was an independent prognostic factor. Enrichment analysis illustrated that DEGs between the high- and low-risk groups were related to immune response, amino acid metabolism, and fatty acid metabolism. Furthermore, risk scores were correlated with the tumor microenvironment, CAF scores, and TIDE scores, and CAF-related marker genes were positively correlated with all five model genes. Notably, the risk model was relevant to the sensitivity of chemotherapy drugs. Finally, the results of qRT-PCR demonstrated that the expression levels of 5 model genes were in accordance with the analysis.

CONCLUSION

A CAF-related risk model based on ACTA2, IGJ, CTHRC1, CXCL12, and LAMB1 was built and could be utilized to predict the prognosis and treatment of HCC.

USH2A Mutation is Associated With Tumor Mutation Burden and Antitumor Immunity in Patients With Colon Adenocarcinoma

Colon adenocarcinoma (COAD) is one of the diseases with the highest morbidity and mortality in the world. At present, immunotherapy has become a valuable method for the treatment of COAD. Tumor mutational burden (TMB) is considered to be the most common biomarker for predicting immunotherapy. According to reports, the mutation rate of COAD ranks third. However, whether these gene mutations are related to TMB and immune response is still unknown. Here, COAD somatic mutation data were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Bioinformatics methods were used to study the relationships among gene mutations, COAD survival prognosis, and tumor immune response. A total of 22 of the top 40 mutations in TCGA and ICGC databases were the same. Among them, the USH2A mutation was associated with high TMB and poor clinical prognosis. According to Gene Set Enrichment Analysis (GSEA) and the CIBERSORT algorithm, we determined that the USH2A mutation upregulates signaling pathways involved in the immune system and the antitumor immune response. In cases with a USH2A mutation, the immune score and MSI score of TCGA samples increased, the expression of immune checkpoint genes decreased significantly, and the TIDE score decreased significantly. Dependent on the presence or absence of a USH2A mutation, TCGA COAD samples were analyzed for differentially expressed genes, 522 of which were identified. Using a univariate Cox analysis and LASSO COX analysis of these differential genes, a prediction model was established, which established significant differences in the infiltration of immune cells, immune checkpoint gene expression, immune score, MSI score, TMB, and TIDE in patients in high- and low-risk groups. In conclusion, mutation of USH2A is frequent in COAD and is related to an increase in TMB and the antitumor immunity. The differential genes screened by USH2A mutation allowed the construction of a risk model for predicting the survival and prognosis of cancer patients, in addition to providing new ideas for COAD immunotherapy.

SLAMF8 expression predicts the efficacy of anti-PD1 immunotherapy in gastrointestinal cancers

Objectives

Epstein–Barr virus (EBV) infection is associated with a better response to anti‐PD1 immunotherapy. We hypothesised that genetic alterations induced by EBV infection are responsible for the activation of key immune responses and hence are predictive of anti‐PD1 efficacy.

Methods

With transcriptome data of gastric cancer (GC), we explored differentially expressed genes (DEGs) specific for EBV infection and performed coexpression network analysis using the DEGs to identify the consistent coexpression genes (CCGs) between EBV‐positive and EBV‐negative GC tissues. We selected the tag genes of the CCGs and validated them using RNA sequencing and immunohistochemistry. We established murine models and collected tissues from clinical patients to test the value of SLAMF8 in predicting anti‐PD1 treatment. The location and expression of SLAMF8 were characterised by multiplex immunofluorescence and quantitative PCR. Moreover, exogenous overexpression and RNA‐sequencing analysis were used to test the potential function of SLAMF8.

Results

We identified 290 CCGs and validated the tag gene SLAMF8 in transcriptome data of gastrointestinal cancer (GI). We observed that the T‐cell activation pathway was significantly enriched in high‐expression SLAMF8 GI cancers. Higher SLAMF8 expression was positively associated with CD8 expression and a better response to anti‐PD1 treatment. We further observed dynamically increased expression of SLAMF8 in murine models relatively sensitive to anti‐PD1 treatment. SLAMF8 was mainly expressed on the surface of macrophages. Exogenous overexpression of SLAMF8 in macrophages resulted in enrichment of positive regulation of multiple immune‐related pathways.

Conclusion

Higher SLAMF8 expression may predict better anti‐PD1 immunotherapy efficacy in GI cancer.

Faecal microbiota transplantation enhances efficacy of immune checkpoint inhibitors therapy against cancer

Even though immune checkpoint inhibitors (ICIs) are effective on multiple cancer types, there are still many non-responding patients. A possible factor put forward that may influence the efficacy of ICIs is the gut microbiota. Additionally, faecal microbiota transplantation may enhance efficacy of ICIs. Nevertheless, the data available in this field are insufficient, and relevant scientific work has just commenced. As a result, the current work reviewed the latest research on the association of gut microbiota with ICI treatments based on anti-programmed cell death protein 1 antibody and anti- cytotoxic T-lymphocyte-associated protein 4 antibody and explored the therapeutic potential of faecal microbiota transplantation in combination with ICI therapy in the future.

Advances in radiotherapy in bone metastases in the context of new target therapies and ablative alternatives: A critical review

In patients with bone metastases (BM), radiotherapy (RT) is used to alleviate symptoms, reduce the risk of fracture, and improve quality of life (QoL). However, with the emergence of concepts like oligometastases, minimal invasive surgery, ablative therapies such as stereotactic ablative RT (SABR), radiosurgery (SRS), thermal ablation, and new systemic anticancer therapies, there have been a paradigm shift in the multidisciplinary approach to BM with the aim of preserving mobility and function survival. Despite guidelines on using single-dose RT in uncomplicated BM, its use remains relatively low. In uncomplicated BM, single-fraction RT produces similar overall and complete response rates to RT with multiple fractions, although it is associated with a higher retreatment rate of 20% versus 8%. Complicated BM can be characterised as the presence of impending or existing pathologic fracture, a major soft tissue component, existing spinal cord or cauda equina compression and neuropathic pain. The rate of complicated BM is around 35%. Unfortunately, there is a lack of prospective trials on RT in complicated BM and the best dose/fractionation regimen is not yet established. There are contradictory outcomes in studies reporting BM pain control rates and time to pain reduction when comparing SABR with Conventional RT. While some studies showed that SABR produces a faster reduction in pain and higher pain control rates than conventional RT, other studies did not show differences. Moreover, the local control rate for BM treated with SABR is higher than 80% in most studies, and the rate of grade 3 or 4 toxicity is very low. The use of SABR may be preferred in three circumstances: reirradiation, oligometastatic disease, and radioresistant tumours. Local ablative therapies like SABR can delay change or use of systemic therapy, preserve patients' Qol, and improve disease-free survival, progression-free survival and overall survival. Moreover, despite the potential benefit of SABR in oligometastatic disease, there is a need to establish the optial indication, RT dose fractionation, prognostic factors and optimal timing in combination with systemic therapies for SABR. This review evaluates the role of RT in BM considering these recent treatment advances. We consider the definition of complicated BM, use of single and multiple fractions RT for both complicated and uncomplicated BM, reirradiation, new treatment paradigms including local ablative treatments, oligometastatic disease, systemic therapy, physical activity and rehabilitation.

Identification of NOTCH4 mutation as a response biomarker for immune checkpoint inhibitor therapy

BACKGROUND

Immune checkpoint inhibitor (ICI) therapy elicits durable antitumor responses in patients with many types of cancer. Genomic mutations may be used to predict the clinical benefits of ICI therapy. NOTCH homolog-4 (NOTCH4) is frequently mutated in several cancer types, but its role in immunotherapy is still unclear. Our study is the first to study the association between NOTCH4 mutation and the response to ICI therapy.

METHODS

We tested the predictive value of NOTCH4 mutation in the discovery cohort, which included non-small cell lung cancer, melanoma, head and neck squamous cell carcinoma, esophagogastric cancer, and bladder cancer patients, and validated it in the validation cohort, which included non-small cell lung cancer, melanoma, renal cell carcinoma, colorectal cancer, esophagogastric cancer, glioma, bladder cancer, head and neck cancer, cancer of unknown primary, and breast cancer patients. Then, the relationships between NOTCH4 mutation and intrinsic and extrinsic immune response mechanisms were studied with multiomics data.

RESULTS

We collected an ICI-treated cohort (n = 662) and found that patients with NOTCH4 mutation had better clinical benefits in terms of objective response rate (ORR: 42.9% vs 25.9%, P = 0.007), durable clinical benefit (DCB: 54.0% vs 38.1%, P = 0.021), progression-free survival (PFS, hazard ratio [HR] = 0.558, P < 0.001), and overall survival (OS, HR = 0.568, P = 0.006). In addition, we validated the prognostic value of NOTCH4 mutation in an independent ICI-treated cohort (n = 1423). Based on multiomics data, we found that NOTCH4 mutation is significantly associated with enhanced immunogenicity, including a high tumor mutational burden, the expression of costimulatory molecules, and activation of the antigen-processing machinery, and NOTCH4 mutation positively correlates activated antitumor immunity, including infiltration of diverse immune cells and various immune marker sets.

CONCLUSIONS

Our findings indicated that NOTCH4 mutation serves as a novel biomarker correlated with a better response to ICI therapy.

Immune Subtypes Based on Immune-Related lncRNA: Differential Prognostic Mechanism of Pancreatic Cancer

Pancreatic cancer consists one of tumors with the highest degree of malignancy and the worst prognosis. To date, immunotherapy has become an effective means to improve the prognosis of patients with pancreatic cancer. Long non-coding RNAs (lncRNAs) have also been associated with the immune response. However, the role of immune-related lncRNAs in the immune response of pancreatic cancer remains unclear. In this study, we identified immune-related lncRNA pairs through a new combinatorial algorithm, and then clustered and deeply analyzed the immune characteristics and functional differences between subtypes. Subsequently, the prognostic model of 3 candidate lncRNA pairs was determined by multivariate COX analysis. The results showed significant prognostic differences between the C1 and C2 subtypes, which may be due to the differential infiltration of CTL and NK cells and the activation of tumor-related pathways. The prognostic model of the 3 lncRNA pairs (AC244035.1_vs._AC063926.1, AC066612.1_vs._AC090124.1, and AC244035.1_vs._LINC01885) was established, which exhibits stable and effective prognostic prediction performance. These 3 lncRNA pairs may regulate the anti-tumor effect of immune cells through ion channel pathways. In conclusion, our research demonstrated the panoramic differences in immune characteristics between subtypes and stable prognostic models, and identified new potential targets for immunotherapy.

A novel ferroptosis phenotype-related clinical-molecular prognostic signature for hepatocellular carcinoma

Ferroptosis is a newly identified cell death mechanism and potential biomarker for hepatocellular carcinoma (HCC) therapy; however, its clinical relevance and underlying mechanism remain unclear. In this study, transcriptome and methylome data from 374 HCC cases were investigated for 41 ferroptosis-related genes to identify ferroptosis activity-associated subtypes. These subtypes were further investigated for associations with clinical and pathological variables, gene mutation landscapes, deregulated pathways and tumour microenvironmental immunity. A gene expression signature and predictive model were developed and validated using an additional 232 HCC cases from another independent cohort. Two distinct ferroptosis phenotypes (Ferroptosis-H and Ferroptosis-L) were identified according to ferroptosis gene expression and methylation in the patients with HCC. Patients with the Ferroptosis-H had worse overall and disease-specific survival, and the molecular subtypes were significantly associated with different clinical characteristics, mRNA expression patterns, tumour mutation profiles and microenvironmental immune status. Furthermore, a 15-gene ferroptosis-related prognostic model (FPM) for HCC was developed and validated which demonstrated accurate risk stratification ability. A nomogram included the FPM risk score, ECOG PS and hepatitis B status was developed for eventual clinical translation. Our results suggest that HCC subtypes defined by ferroptosis gene expression and methylation may be used to stratify patients for clinical decision-making.

A seven-nuclear receptor-based prognostic signature in breast cancer

BACKGROUND

Breast cancer (BRCA) is a malignant cancer that threatened the life of female with unsatisfactory prognosis. The aim of this study was to identify prognostic nuclear receptors (NRs) signature of BRCA.

METHODS

BRCA patient samples were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Consensus clustering analysis, univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis were performed to evaluate, select NRs as prognostic factors and build Risk Score model. GSEA analysis was explored to check signaling differences between High- and Low-Risk group. Nomogram model basing on age and Risk Score was established to predict the 1-, 3- and 5-year survival. Model performance was assessed by a time-dependent receiver operating characteristic (ROC) curve and calibration plot. CIBERSORT, ESTIMATE and TIMER algorithm were introduced to evaluate the immune landscape.

RESULTS

NR3C1, NR4A3, THRA, RXRG, NR2F6, NR1D2 and RORB were optimized as a prognostic signature for BRCA. This seven-NR-based Risk Score could effectively predict overall survival status. The area under the curve (AUC) of 1-, 3- and 5-year overall survival are 0.702, 0.734 and 0.722 in TCGA training cohort, and 0.630, 0.721 and 0.823 in GEO validation cohort, respectively. Calibration plot demonstrated satisfactory agreement between predictive and observed outcomes. Nomogram model worked well on predicting survival probabilities. Multiple cancer-related pathways were highly enriched in High-Risk group. High- and Low-Risk groups showed significant differed immune cell infiltration. There exists an obvious connection between Risk Score and immune checkpoints LAG3, PD1 and TIM3.

CONCLUSION

The seven-NR-based Risk Score represents a promising signature for estimating overall survival in patients with BRCA, and is correlated with the immune microenvironment.

Managing toxicities associated with immune checkpoint inhibitors

ABSTRACT

Recent development of immunotherapy has led to remarkable advancement in cancer therapy. Drugs that inhibit the cytotoxic T-lymphocyte-associated protein (CTLA-4) and programmed death-1 (PD-1) immune checkpoint pathways have shown improved patient survival. However, by altering the immune response to fight cancer, a new class of adverse reactions has emerged, known as immune-related adverse events. These adverse events are due to overactivation of the immune system in almost any organ of the body, can occur at any point in a patient's treatment course, and may become life-threatening. This article describes how to promptly recognize and manage these toxicities.

Systemic Immune-Inflammation Index and Changes of Neutrophil-Lymphocyte Ratio as Prognostic Biomarkers for Patients With Pancreatic Cancer Treated With Immune Checkpoint Blockade

The efficacy of current treatment regimens for pancreatic cancer (PC) remains unsatisfactory. In recent years, immune checkpoint blockade (ICB) therapy has shown promising anti-tumor outcomes in many malignancies, including PC. Inexpensive and readily available biomarkers which predict therapeutic responses and prognosis are in critical need. Systemic immune-inflammation index (SII) and neutrophil-lymphocyte ratio (NLR) are emerging predictors for prognosis of various tumors. We aim to investigate the prognostic significance of baseline SII, NLR, and their changes in PC patients treated with ICB. Our retrospective analysis included PC patients treated with ICB therapy in the Chinese PLA General Hospital. All demographic, biological, and clinical data were extracted from medical records. Relative changes of SII after two doses of ICB were defined as ΔSII% and calculated as (SII_{after 2 doses}-SII_baseline)/SII_baseline, and so was the case for ΔNLR%. Overall survival (OS) and progression-free survival (PFS) were compared using Kaplan-Meier curves. The prognostic significance of baseline SII, NLR, and their changes was assessed in univariate and multivariate analyses using the Cox proportional hazard regression model. In total, 122 patients with PC treated with ICB were included in the present analysis. Elevated baseline SII (HR=3.28; 95% CI:1.98–5.27; P=0.03) and ΔNLR% (HR=2.21; 95% CI:1.03–4.74; P=0.04) were significantly correlated with an increased risk of death. For PC patients receiving ICB combined with chemotherapies or radiotherapies as the first-line treatment, increased baseline SII was a negative predictor for both OS (HR=8.06; 95% CI:1.71–37.86; P=0.01) and PFS (HR=2.84; 95%CI:1.37–10.38; P=0.04). Our study reveals the prognostic value of baseline SII and NLR changes in PC patients receiving ICB therapy. The clinical utility of these prognostic biomarkers needs to be further studied in prospective studies.

Programmed cell death 1 as prognostic marker and therapeutic target in upper gastrointestinal cancers

Gastrointestinal (GIs) cancers are among the most common causes of cancer related death, and hence the importance for the identification of novel prognostic/predictive biomarkers for detection of patients at an early stage, and for using these to identify novel targeted therapies to improve the efficacy of existing chemotherapeutic regimens. Programmed cell death 1 has been reported as a potential target in several malignancies, and targeting agents are being developed, some already approved by FDA, such as: pembrolizumab, Atezolizumab, Nivolumab. Pembrolizumab that have been approved for the treatment of metastatic non-small cell lung cancer. Here we provide an overview of the mechanism of action PD-1/PD-L1, prognostic value and current progress in clinical trials using PD-1/PD-L1 inhibitors, and the resistant mechanisms at underlie the inhibitory effect of these agents in the treatment of gastrointestinal cancers.

Identification of a two-gene prognostic model associated with cytolytic activity for colon cancer

Background

Increasing evidence has shown that cytolytic activity (CYT) is a new immunotherapy biomarker that characterises the antitumour immune activity of cytotoxic T cells and macrophages. In this study, we established a prognostic model associated with CYT.

Methods

A prognostic model based on CYT-related genes was developed. Furthermore, aberrant expression of genes of the model in colon cancer (CC) was identified by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) assays. Next, the correlation between the model and T-cell infiltration in the CC microenvironment was analysed. The Tumour Immune Dysfunction and Exclusion (TIDE) algorithm and subclass mapping were used to predict clinical responses to immune checkpoint inhibitors.

Results

In total, 280 of the 1418 genes were differentially expressed based on CYT. A prognostic model (including HOXC8 and MS4A2) was developed based on CYT-related genes. The model was validated using the testing set, the whole set and a Gene Expression Omnibus (GEO) cohort (GSE41258). Gene set enrichment analysis (GSEA) and other analyses showed that the levels of immune infiltration and antitumour immune activation in low-risk-score tumours were greater than those in high-risk-score tumours. CC patients with a low-risk-score showed more promise in the response to anti-immune checkpoint therapy.

Conclusions

Overall, our model may precisely predict the overall survival of CC and reflect the strength of antitumour immune activity in the CC microenvironment. Furthermore, the model may be a predictive factor for the response to immunotherapy.

A TP53-based immune prognostic model for muscle-invasive bladder cancer

BACKGROUND

Muscle-invasive bladder cancer (MIBC) patients are subject to unfavorable treatment options and a high recurrence rate. The status of TP53 mutations played an essential role in the progression and the prognosis of MIBC. The present study proposed to investigate the association between TP53 mutations and immunophenotype in MIBC.

RESULTS

We established an immune prognostic model (IPM) ground on the immune-associated genes derived from variation analysis between wild-type TP53 and mutated TP53 TCGA-MIBC patients, and validated in another cohort from GEO database. Based on IPM, we divided MIBC patients into low and high risk subgroups. The high risk MIBC patients had higher proportions of macrophages M1, and lower proportions of T cells regulatory (Tregs) and activated dendritic cells than the low risk MIBC patients. Moreover, the expression of immune checkpoints genes (PD1, CTLA4, LAG3, HAVCR2 and TIGIT) was higher in the high risk patients than the low risk patients. In clinical application, IPM exhibited better survival prediction than conventional clinical characteristics.

CONCLUSIONS

Our investigation presented practical prognostic significance for MIBC patients and displayed the overarching landscape of the immune response in the MIBC microenvironment.

METHODS

Data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) analysis between the TP53 mutated and wild-type MIBC patients was conducted. The CIBERSORT algorithm was performed to evaluate the proportion of immune cell types. Gene expression profiles from the TCGA and GEO were used as training and testing cohorts to build and validate an immune-related prognostic model (IPM). Genes in the IPM model were first screened by univariate Cox analysis, then filtered by the least absolute shrinkage and selection operator (LASSO) Cox regression. A nomogram was finally established and evaluated by combining both the IPM and other clinical factors.

Clinical implications of plasma ctDNA features and dynamics in gastric cancer treated with HER2-targeted therapies

BACKGROUND

Gastric cancer (GC) is confronted with limited options for precision medicine. Human epidermal growth factor receptor 2 (HER2) is the principal druggable target of GC, yet proper biomarkers for response/resistance prediction remain unveiled.

METHODS

From 40 GC patients received HER2-targeted therapy, a total of 327 peripheral blood plasma specimens was collected including baseline and treatment time points. Circulating tumor DNA (ctDNA) was extracted and sequenced with a target panel of 425 genes. Experimental validation of resistant mutations was carried out in NIH-3T3 cell line.

RESULTS

Genomic features, including ERBB2 copy number variation (CNV), total copy number load, and tumor mutation burdens (TMBs), dynamically changed along with the treatment process and correlated with disease progression. Plasma ctDNA-based diagnosis was more sensitive than conventional computed tomography scanning in 40% of investigated patients, gaining additional time for clinical management. Compared to baseline, new gene alterations were emerged in 12 patients who developed drug resistance during treatment. ERBB2 mutations potentially related to Pyrotinib resistance were identified in plasma ctDNA of one patient and functional analysis of their downstream signaling pathways was carried out in NIH-3T3 cell line. TMB exhibited more power than ERBB2 CNV in predicting treatment responses and prognosis for HER2-targeted therapy in GC patients. Interestingly, survival analysis indicated that patients harboring both HER2 (ERBB2) positivity and high TMB might gain more therapeutic benefits from immune checkpoint inhibitors instead of HER2-targeted regimens that required further studies and validations CONCLUSIONS: Our work showed that the dynamic surveillance of plasma ctDNA genomic features provided instructive information for the precision medication of GC patients.

Transcriptional landscape of cholangiocarcinoma revealed by weighted gene coexpression network analysis

Cholangiocarcinoma (CCA) is a type of cancer with limited treatment options and a poor prognosis. Although some important genes and pathways associated with CCA have been identified, the relationship between coexpression and phenotype in CCA at the systems level remains unclear. In this study, the relationships underlying the molecular and clinical characteristics of CCA were investigated by employing weighted gene coexpression network analysis (WGCNA). The gene expression profiles and clinical features of 36 patients with CCA were analyzed to identify differentially expressed genes (DEGs). Subsequently, the coexpression of DEGs was determined by using the WGCNA method to investigate the correlations between pairs of genes. Network modules that were significantly correlated with clinical traits were identified. In total, 1478 mRNAs were found to be aberrantly expressed in CCA. Seven coexpression modules that significantly correlated with clinical characteristics were identified and assigned representative colors. Among the 7 modules, the green and blue modules were significantly related to tumor differentiation. Seventy-eight hub genes that were correlated with tumor differentiation were found in the green and blue modules. Survival analysis showed that 17 hub genes were prognostic biomarkers for CCA patients. In addition, we found five new targets (ISM1, SULT1B1, KIFC1, AURKB and CCNB1) that have not been studied in the context of CCA and verified their differential expression in CCA through experiments. Our results not only promote our understanding of the relationship between the transcriptome and clinical data in CCA but will also guide the development of targeted molecular therapy for CCA.

Construction of a prognostic model based on nine immune-related genes and identification of small molecule drugs for hepatocellular carcinoma (HCC)

This study aimed to develop a prognostic model for hepatocellular carcinoma (HCC) based on immune-related genes and to identify new potential small-molecule drugs. A differential gene expression analysis of high-throughput microarray data from The Cancer Genome Atlas (TCGA) was performed to identify immune-related genes. By comparison with an immune-related genome, nine genes with important prognostic value for HCC were identified. The prognostic characteristics were established based on univariate and multivariate COX and Lasso regression analyzes. Subsequently, immune-related HCC risk signatures were constructed based on these identified nine immune-related genes and patients were classified as being at high or low risk according to these signatures. The overall survival (OS) time of high-risk patients was significantly shorter than that of low-risk patients. When studied as an independent prognostic factor of HCC, the significant prognostic value of this feature can be seen in the stratified cohorts. For clinical application, it was developed a nomogram that includes nine clinical risk factors and the prognostic model built based on the identified immune-related genes. Internal and external verification on 243 HCC tissues through International Cancer Genome Consortium (ICGC) database were performed to make this model more accurate and reliable. In addition, it was observed a positive regulation between the identified immune-related genes and their transcription factors found in HCC patients. Moreover, physiological function and signaling pathway of identified immune-related genes were studied by GO and KEGG enrichment analysis. Finally, several new small molecular drugs with potential for the treatment of HCC have been identified in the CMap database.

Construction and validation of a TP53-associated immune prognostic model for gastric cancer

Increasing evidence indicates that TP53 mutation impacts the patients' prognosis by regulating the gastric cancer (GC) immunophenotype. An immune prognostic signature (IPS) was constructed based on TP53 status. The effects of the IPS on the immune microenvironment of GC were analyzed. We also constructed a nomogram integrating the IPS and other clinical factors. An IPS was constructed in the TCGA cohort and validated in the meta-GEO cohort. TP53 mutation resulted in the downregulation of the immune response in GC. Concretely, high-risk patients were characterized by increased monocyte, macrophage M0 and T cell follicular helper infiltration; increased stromal score, ESTIMATE score and immune score; higher TIM3 and BTLA expression; and decreased dendritic cell and T cell CD4 memory-activated infiltration and tumor purity. The nomogram also showed good predictive performance. These results suggest that the IPS is an effective prognostic indicator for GC patients, which might provide a theoretical foundation for immunotherapy.

Gene Therapy for Hepatocellular Carcinoma Using Adenoviral Vectors Delivering a Gene Encoding IL-17A-Neutralizing Antibody Fragments

High interleukin 17A (IL-17A) expression in hepatocellular carcinoma (HCC) tissue promotes HCC development. This study explores a method to inhibit HCC growth by neutralizing IL-17A in the HCC microenvironment. A novel type 5 adenoviral vector (Ad5) that carries DNA sequences encoding specific neutralizing IL-17A recombinant antibody fragments was developed in this research. After locally injecting into tumor tissues, the Ad5 transduced into tumor cells. This leads to the expression of the anti-IL-17A recombinant antibody fragments in the HCC tissue and consequently to an inhibition of HCC growth by neutralizing IL-17A. The stability of the antibody fragments was optimized by different structures design. Stable HCC cell lines that secrete IL-17A continuously were constructed, which showed stronger invasion and migration ability than control HCC cell lines. In addition, the enhanced migration and invasion ability were partially reversed by applying the adenoviral vectors. These results suggest that IL-17A might promote HCC growth by enhancing the invasion and migration ability of hepatoma cells. The antibody fragments from Ad5 neutralized IL-17A locally, in turn inhibiting the growth of HCC tumors. In conclusion, the local administration of Ad5 vectors encoding IL-17A-neutralizing antibody fragments provides a new option for HCC immunotherapy.