Mast cell marker gene signature: prognosis and immunotherapy response prediction in lung adenocarcinoma through integrated scRNA-seq and bulk RNA-seq

Background

Mast cells, comprising a crucial component of the tumor immune milieu, modulate neoplastic progression by secreting an array of pro- and antitumorigenic factors. Numerous extant studies have produced conflicting conclusions regarding the impact of mast cells on the prognosis of patients afflicted with lung adenocarcinoma (LUAD).

Methods

Employing single-cell RNA sequencing (scRNA-seq) analysis, mast cell-specific marker genes in LUAD were ascertained. Subsequently, a mast cell-related genes (MRGs) signature was devised to stratify LUAD patients into high- and low-risk cohorts based on the median risk value. Further investigations were conducted to assess the influence of distinct risk categories on the tumor microenvironment. The prognostic import and capacity to prognosticate immunotherapy benefits of the MRGs signature were corroborated using four external cohorts. Ultimately, the functional roles of SYAP1 were validated through in vitro experimentation.

Results

After scRNA-seq and bulk RNA-seq data analysis, we established a prognostic signature consisting of nine MRGs. This profile effectively distinguished favorable survival outcomes in both the training and validation cohorts. In addition, we identified the low-risk group as a population more effective for immunotherapy. In cellular experiments, we found that silencing SYAP1 significantly reduced the proliferation, invasion and migratory capacity of LUAD cells while increasing apoptosis.

Conclusion

Our MRGs signature offers valuable insights into the involvement of mast cells in determining the prognosis of LUAD and may prove instrumental as a navigational aid for immunotherapy selection, as well as a predictor of immunotherapy response in LUAD patients.

Breaking the Invisible Barriers: Unleashing the Full Potential of Immune Checkpoint Inhibitors in Oncogene-Driven Lung Adenocarcinoma

The rapid development of targeted therapy paved the way toward personalized medicine for advanced non-small cell lung cancer (NSCLC). Lung adenocarcinoma (ADC) harboring actionable genetic alternations including epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), Kirsten rat sarcoma virus (ALK) and c-ros oncogene 1 (ROS1) treated with tyrosine kinase inhibitors (TKIs) incurred lesser treatment toxicity but better therapeutic responses compared with systemic chemotherapy. Angiogenesis inhibitors targeting vascular endothelial growth factor (VEGF) have also shown an increase in overall survival (OS) for NSCLC patients. However, acquired resistance to these targeted therapies remains a major obstacle to long-term maintenance treatment for lung ADC patients. The emergence of immune checkpoint inhibitors (ICIs) against programmed cell death protein 1 (PD-1) or programmed cell death-ligand 1 (PD-L1) has changed the treatment paradigm for NSCLC tumors without actionable genetic alternations. Clinical studies have suggested, however, that there are no survival benefits with the combination of targeted therapy and ICIs. In this review, we will summarize and discuss the current knowledge on the tumor immune microenvironment and the dynamics of immune phenotypes, which could be crucial in extending the applicability of ICIs for this subpopulation of lung ADC patients.

Identification of m6A-related lncRNAs as prognostic signature within colon tumor immune microenvironment

BACKGROUND

The current study probed prognosis-related potential for m6A-related lncRNAs signatures within colon tumor immune microenvironment (TIM).

METHODS

After downloading transcriptomic datasets for colon cancer (CC) patients from The Cancer Genome Atlas (TCGA), they were divided, in a 1:1 ratio, within training or test datasets. m6A-related lncRNAs were then scrutinized across such dataset using Pearson correlation assessment before generating a m6A-related lncRNAs prognosis-related model using the training dataset. The latter was then validated with the test and the whole dataset. In addition, we compared the differences of TIM and the estimated IC50 of drug response between the high- and low-risk groups.

RESULTS

Overall survival (OS) resulted as linked with 11 m6A-related lncRNAs, while within the developed prognosis-related model, areas-under-curves were as follows: within training dataset, values at 3-, 4-, and 5-years were 0.777, 0.819, and 0.805, accordingly, and for test one, they were 0.697, 0.682, and 0.706, respectively. Finally, the values for the whole dataset were 0.675 (3-year), 0.682 (4-years), and 0.679 (5-years), accordingly. Moreover, CC cases categorized within low-risk cohort demonstrated enhanced OS (p < .0001), lower metastasis (p = 2e-06) and lower T stage (p = .0067), more instability for microsatellite status (p = .012), and downregulation for PD-L1, PD-1, CTLA-4, LAG3, and HAVCR2 (p < .05). In addition, risk scorings were significantly linked to the degree of infiltrative intensity for CD8 and CD4 (memory resting) T-cells, T-regulatory (Tregs), and Mast cells triggering (p < .05). Patients with low infiltrative propensity for CD4 T-cells also had better OS (p = .016). Moreover, six representative drugs were found to be sensitive for treating CC patients.

CONCLUSION

A robust m6A-related prognostic model with great performances was developed before exploring the TIM characteristics and its potential therapeutic drugs, which might improve the prognosis and therapeutic efficacy.

A senescence-associated signature refines the classification of different modification patterns and characterization of tumor immune microenvironment infiltration in triple-negative breast cancer

Background: Recent studies have found that senescence-associated genes play a significant role in cancer biological processes. We aimed to analyze the characteristics and role of senescence-associated genes in triple-negative breast cancer (TNBC). Methods: We systematically screened senescence-associated secretory phenotype (SASP) genes based on the gene expression information in the TCGA database. According to the expression levels of senescence-associated genes, TNBC was classified into two subtypes, namely, TNBCSASP1 and TNBCSASP2, using an unsupervised cluster algorithm. We then performed gene expression, enrichment pathway, immune infiltration, mutational profile characterization, drug sensitivity and prognostic value analyses for the two subtypes. The reliability and prognostic predictive utility of this classification model were validated. The most prognostically relevant gene, FAM3B, was comprehensively identified and validated by tissue microarray in TNBC. Results: TNBC was classified into two senescence-associated subtypes, TNBCSASP1 and TNBCSASP2, based on the set of senescence-associated secretory phenotype genes, among which the TNBCSASP1 subtype had a poor prognosis. The TNBCSASP1 subtype was immunosuppressed, with suppressed immune-related signaling pathways and low immune cell infiltration. The effect of the mutation on the TP53 and TGF-β pathways could be related to the poor prognosis of the TNBCSASP1 subtype. Drug sensitivity analysis showed that AMG.706, CCT007093, and CHIR.99021 were potential targeted drugs for the TNBCSASP1 subtype. Finally, FAM3B was a key biomarker affecting the prognosis of patients with triple-negative breast cancer. Compared to normal breast tissue, the expression of FAM3B was reduced in triple-negative breast cancer. Survival analysis showed that overall survival was significantly shorter in triple-negative breast cancer patients with high FAM3B expression. Conclusion: A senescence-associated signature with different modification patterns has critical potential for providing a better understanding of TNBC biological processes, and FAM3B might serve as an applicable target for TNBC therapy.

Characterization of anoikis-based molecular heterogeneity in pancreatic cancer and pancreatic neuroendocrine tumor and its association with tumor immune microenvironment and metabolic remodeling

Background

Accumulating evidence suggests that anoikis plays a crucial role in the onset and progression of pancreatic cancer (PC) and pancreatic neuroendocrine tumors (PNETs); nevertheless, the prognostic value and molecular characteristics of anoikis in cancers are yet to be determined.

Materials and methods

We gathered and collated the multi-omics data of several human malignancies using the TCGA pan-cancer cohorts. We thoroughly investigated the genomics and transcriptomics features of anoikis in pan-cancer. We then categorized a total of 930 patients with PC and 226 patients with PNETs into distinct clusters based on the anoikis scores computed through single-sample gene set enrichment analysis. We then delved deeper into the variations in drug sensitivity and immunological microenvironment between the various clusters. We constructed and validated a prognostic model founded on anoikis-related genes (ARGs). Finally, we conducted PCR experiments to explore and verify the expression levels of the model genes.

Results

Initially, we identified 40 differentially expressed anoikis-related genes (DE-ARGs) between pancreatic cancer (PC) and adjacent normal tissues based on the TCGA, GSE28735, and GSE62452 datasets. We systematically explored the pan-cancer landscape of DE-ARGs. Most DE-ARGs also displayed differential expression trends in various tumors, which were strongly linked to favorable or unfavorable prognoses of patients with cancer, especially PC. Cluster analysis successfully identified three anoikis-associated subtypes for PC patients and two anoikis-associated subtypes for PNETs patients. The C1 subtype of PC patients showed a higher anoikis score, poorer prognosis, elevated expression of oncogenes, and lower level of immune cell infiltration, whereas the C2 subtype of PC patients had the exact opposite characteristics. We developed and validated a novel and accurate prognostic model for PC patients based on the expression traits of 13 DE-ARGs. In both training and test cohorts, the low-risk subpopulations had significantly longer overall survival than the high-risk subpopulations. Dysregulation of the tumor immune microenvironment could be responsible for the differences in clinical outcomes between low- and high-risk groups.

Conclusions

These findings provide fresh insights into the significance of anoikis in PC and PNETs. The identification of subtypes and construction of models have accelerated the progress of precision oncology.

Remodeling of the immune and stromal cell compartment by PD-1 blockade in mismatch repair-deficient colorectal cancer

Immune checkpoint inhibitor (ICI) therapy can induce complete responses in mismatch repair-deficient and microsatellite instability-high (d-MMR/MSI-H) colorectal cancers (CRCs). However, the underlying mechanism for pathological complete response (pCR) to immunotherapy has not been completely understood. We utilize single-cell RNA sequencing (scRNA-seq) to investigate the dynamics of immune and stromal cells in 19 patients with d-MMR/MSI-H CRC who received neoadjuvant PD-1 blockade. We found that in tumors with pCR, there is a concerted decrease in CD8⁺ Trm-mitotic, CD4⁺ Tregs, proinflammatory IL1B⁺ Mono and CCL2⁺ Fibroblast following treatment, while the proportions of CD8⁺ Tem, CD4⁺ Th, CD20⁺ B, and HLA-DRA⁺ Endothelial cells increase. Proinflammatory features in the tumor microenvironment mediate the persistence of residual tumors by modulating CD8⁺ T cells and other response-associated immune cell populations. Our study provides valuable resources and biological insights into the mechanism of successful ICI therapy and potential targets for improving treatment efficacy.

Single-cell atlas reveals a distinct immune profile fostered by T cell-B cell crosstalk in triple negative breast cancer

BACKGROUND

Characterizing the unique immune microenvironment of each tumor is of great importance for better predicting prognosis and guiding cancer immunotherapy. However, the unique features of the immune microenvironment of triple negative breast cancer (TNBC) compared with other subtypes of breast cancer remain elusive. Therefore, we aimed to depict and compare the immune landscape among TNBC, human epidermal growth factor receptor 2-positive (HER2⁺ ) breast cancer, and luminal-like breast cancer.

METHODS

Single-cell RNA sequencing (scRNA-seq) was performed on CD45⁺ immune cells isolated from human normal breast tissues and primary breast tumors of various subtypes. By analyzing the scRNA-seq data, immune cell clusters were identified and their proportions as well as transcriptome features were compared among TNBC, human HER2⁺ breast cancer, and luminal-like breast cancer. Pseudotime and cell-cell communication analyses were also conducted to characterize the immune microenvironment.

RESULTS

ScRNA-seq data of 117,958 immune cells were obtained and 31 immune clusters were identified. A unique immunosuppressive microenvironment in TNBC was decoded as compared to that in HER2⁺ or luminal-like breast cancer, which was characterized by higher proportions of regulatory T cells (Tregs) and exhausted CD8⁺ T cells and accompanied by more abundant plasma cells. Tregs and exhausted CD8⁺ T cells in TNBC exhibited increased immunosuppression signature and dysfunctional scores. Pseudotime analyses showed that B cells tended to differentiate to plasma cells in TNBC. Cell-cell communication analyses indicated that these unique features are fostered by the diversified T cell-B cell crosstalk in TNBC. Based on the T cell-B cell crosstalk, a prognostic signature was established that could effectively predict the prognosis status for patients with TNBC. Additionally, it was found that TNBC had a higher proportion of cytotoxic natural killer (NK) cells, whereas HER2⁺ or luminal-like breast cancer lost this feature, suggesting that HER2⁺ or luminal-like breast cancer, but not TNBC, may benefit from NK-based immunotherapy.

CONCLUSIONS

This study identified a distinct immune feature fostered by T cell-B cell crosstalk in TNBC, which provides better prognostic information and effective therapeutic targets for breast cancer.

Immune cells in residual disease and recurrence

Tumor recurrence following potentially curative therapy constitutes a major obstacle to achieving cures in patients with cancer. Recurrent tumors frequently arise from a population of residual cancer cells - also referred to as minimal residual disease (RD) or persister cells - that survive therapy and persist for prolonged periods prior to tumor relapse. While there has been significant recent progress in deciphering tumor-cell-intrinsic pathways that regulate residual cancer cell survival and recurrence, much less is known about how the tumor microenvironment (TME) of residual tumors impacts persister cancer cells or tumor recurrence. In this review, we highlight recent studies exploring the regulation and function of immune cells in RD and discuss therapeutic opportunities to target immune cells in residual tumors.

HNRNPC suppresses tumor immune microenvironment by activating Treg cells promoting the progression of prostate cancer

Immune microenvironment could affect the biological progress in prostate cancer (PCa) through N6 methyl adenosine (m6A) methylation. The purpose of this study was to investigate the crosstalk between m6A methylation and immune microenvironment and explore potential biomarkers to improve the immunotherapeutic response. Firstly, according to 11 differentially expressed m6A genes between normal and tumor samples, PCa patients were divided into immune microenvironment subtype 1 (IMS1) and IMS2 based on m6A gene profiles extracted from The Cancer Genome Atlas (TCGA) database. IMS2 showed an immune "cold" phenotype with worse prognoses, and HNRNPC was identified as the biomarker of IMS2 by the protein-protein interaction network. Furthermore, through bioinformatics analyses and in vitro experiments, we found that HNRNPC-high patients showed a suppressive immune-infiltrating tumor microenvironment with a higher infiltration of regulatory T (Treg) cells. Finally, we cocultured transfected PCa cells with peripheral blood mononuclear cells (PBMC) and verified that HNRNPC inhibits tumor immunity by elevating the activation of Treg cells and suppression of effector CD8 T cell. In conclusion, we identified a "cold" immune phenotype in PCa, and HNRNPC regulating the activation of Treg cells. Activation of the immune microenvironment through targeting HNRNPC may be a potential therapeutic option for advanced PCa.

Construction of a prognostic model of acute myeloid leukemia associated with immunogenic cell death

BACKGROUND

Immunogenic cell death(ICD)is a kind of regulatory cell death, which causes a series of antigen-specific adaptive immune responses by generating and emitting some danger signals or damage-associated molecular patterns (DAMPs). At present, little is known about the prognostic value of ICD and its related processes in acute myeloid leukemia (AML). The aim of the study was to explore the relationship between ICD and tumor immune microenvironment changes in AML.

RESEARCH DESIGN & METHODS

In the study, AML samples were divided into two groups by consensus clustering analysis, and then gene enrichment analysis and GSEA analysis were performed on the ICD high expression group. Furthermore, CIBERSORT was used to analyze the tumor microenvironment and immune characteristics of AML. Finally, a prognostic model related to ICD was constructed by using univariate and multivariate regression analysis.

RESULTS

ICD was divided into two groups according to the level of ICD gene expression. The ICD high expression group was associated with good clinical results and high levels of immune cell infiltration.

CONCLUSIONS

The study constructed and verified the prognostic characteristics of AML related to ICD, which has important value in predicting the overall survival time of AML patients.

The Tumor Immune Microenvironment in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is a type of kidney cancer that arises from the cells lining the tubes of the kidney. The tumor immune microenvironment (TIME) of ccRCC is a complex interplay of various immune cells, cytokines, and signaling pathways. One of the critical features of the ccRCC TIME is the presence of infiltrating immune cells, including T cells, B cells, natural killer cells, dendritic cells, and myeloid-derived suppressor cells. Among these cells, CD8+ T cells are particularly important in controlling tumor growth by recognizing and killing cancer cells. However, the TIME of ccRCC is also characterized by an immunosuppressive environment that hinders the function of immune cells. Several mechanisms contribute to the immunosuppressive nature of the ccRCC TIME. For instance, ccRCC cells produce cytokines such as interleukin-10 (IL-10) and transforming growth factor-beta (TGF-β), which suppress immune cell activation and promote the differentiation of regulatory T cells (Tregs). Tregs, in turn, dampen the activity of effector T cells and promote tumor growth. In addition, ccRCC cells can express programmed death-ligand 1 (PD-L1), which interacts with the programmed cell death protein 1 (PD-1) receptor on T cells to inhibit their function. In addition, other immune checkpoint proteins, such as cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and lymphocyte activation gene 3 (LAG-3), also contribute to the immunosuppressive milieu of the ccRCC TIME. Finally, the hypoxic and nutrient-poor microenvironment of ccRCC can stimulate the production of immunosuppressive metabolites, such as adenosine and kynurenine, which further impair the function of immune cells. Understanding the complex interplay between tumor cells and the immune system in the ccRCC TIME is crucial for developing effective immunotherapies to treat this disease.

Dihydropyrimidine Dehydrogenase (DPD) as a Bridge between the Immune Microenvironment of Colon Cancers and 5-FU Resistance

BACKGROUND

The purpose of the present study was to investigate the role of the 5-Fluorouracil (5-FU) resistance-related factor dihydropyrimidine dehydrogenase (DPD) in tumor immunity and prognosis and to study the relationship between drug resistance and the immune microenvironment of colon cancer.

METHODS

Bioinformatics methods were used to analyze the expression of DPD associated with prognosis, immunity, microsatellite instability, and tumor mutational burden in colon cancer. Immunohistochemistry (IHC) was used to detect DPD, MLH1, MSH2, MSH6, and PMS2 in 219 colon cancer tissue samples. Additional IHC analyses were conducted to detect CD4, CD8, CD20, and CD163 in 30 colon cancer tissue samples with the most extensive immune infiltration. The significance of the correlations and clinical significance of DPD with immune infiltration, immune-related markers, microsatellite instability-related indicators, and prognosis were evaluated.

RESULTS

The major findings of the present study are as follows: (1) DPD was expressed in tumor and immune cells and associated with certain immune cell-related markers, particularly M2 macrophages that expressed CD163. (2) DPD expression significantly and positively correlated with immune cell markers and immune checkpoints PD-1 and PD-L1. High expression of DPD in immune cells, but not tumor cells, led to increased immune infiltration. (3) High expression of DPD in immune and tumor cells induced 5-FU resistance and was associated with unfavorable prognosis. (4) DPD expression closely correlated with microsatellite instability and tumor mutational burden and led to resistance to 5-FU in patients with microsatellite instability. (5) Bioinformatics analyses revealed that DPD was enriched in immune-related functions and pathways such as activation of T cells and macrophages.

CONCLUSIONS

DPD plays an important role in the immune microenvironment and drug resistance of colon cancers and their functional association.

The role of tumor metabolism in modulating T-Cell activity and in optimizing immunotherapy

Immunotherapy has revolutionized cancer treatment and revitalized efforts to harness the power of the immune system to combat a variety of cancer types more effectively. However, low clinical response rates and differences in outcomes due to variations in the immune landscape among patients with cancer continue to be major limitations to immunotherapy. Recent efforts to improve responses to immunotherapy have focused on targeting cellular metabolism, as the metabolic characteristics of cancer cells can directly influence the activity and metabolism of immune cells, particularly T cells. Although the metabolic pathways of various cancer cells and T cells have been extensively reviewed, the intersections among these pathways, and their potential use as targets for improving responses to immune-checkpoint blockade therapies, are not completely understood. This review focuses on the interplay between tumor metabolites and T-cell dysfunction as well as the relationship between several T-cell metabolic patterns and T-cell activity/function in tumor immunology. Understanding these relationships could offer new avenues for improving responses to immunotherapy on a metabolic basis.

Synergistic Target of Intratumoral Microbiome and Tumor by Metronidazole-Fluorouridine Nanoparticles

Clinical and experimental evidence confirmed bacterial infiltration in a variety of tumors, which is related to the progression and therapeutic effects of the tumors. Although the administration of antibiotics inhibits the growth of bacteria inside the tumor, systemic distribution of antibiotics induces an imbalance of other microbiomes in the body, which in turn leads to the development of new diseases. To address this clinical challenge, we nanonized an antibiotic in this study. Metronidazole, an antibiotic against broad anaerobes, was linked to fluorouridine to form an amphiphilic small molecule, metronidazole-fluorouridine, which further autoassembled as metronidazole-fluorouridine nanoparticles (MTI-FDU) in a hydrophilic solution. The disulfide bond in the linker cleaves in response to high levels of glutathione (GSH) in the tumor microenvironment. The synergistic antitumor effect of MTI-FDU was observed in two animal models of gut cancer with intratumoral bacteria. Analysis revealed that metronidazole delivered by nanoparticles attacked bacteria inside the tumor, while it had minimal effect on gut microbial homeostasis. Further experiments at the cellular and molecular levels disclosed that MTI-FDU shaped the tumor immune microenvironment through clearance of bacteria and bacterial products. In conclusion, we achieved a synergistic antitumor effect by a dual target of both the intratumoral microbiome and tumor cells. Antibiotic-composed nanoparticles have a clinical advantage in the treatment of tumors with bacteria infiltration, which kill pro-tumor bacteria efficiently as well as keep a balanced microbiota of the patient.

Copper and cuproptosis-related genes in hepatocellular carcinoma: therapeutic biomarkers targeting tumor immune microenvironment and immune checkpoints

Background

Hepatocellular carcinoma (HCC), one of the most common cancers worldwide, exhibits high immune heterogeneity and mortality. Emerging studies suggest that copper (Cu) plays a key role in cell survival. However, the relationship between Cu and tumor development remains unclear.

Methods

We investigated the effects of Cu and cuproptosis-related genes (CRGs) in patients with HCC in the TCGA-LIHC (The Cancer Genome Atlas-Liver cancer, n = 347) and ICGC-LIRI-JP (International Cancer Genome Consortium-Liver Cancer-Riken-Japan, n = 203) datasets. Prognostic genes were identified by survival analysis, and a least absolute shrinkage and selection operator (Lasso) regression model was constructed using the prognostic genes in the two datasets. Additionally, we analyzed differentially expressed genes and signal pathway enrichment. We also evaluated the effects of CRGs on tumor immune cell infiltration and their co-expression with immune checkpoint genes (ICGs) and performed validation in different tumor immune microenvironments (TIMs). Finally, we performed validation using clinical samples and predicted the prognosis of patients with HCC using a nomogram.

Results

A total of 59 CRGs were included for analysis, and 15 genes that significantly influenced the survival of patients in the two datasets were identified. Patients were grouped by risk scores, and pathway enrichment analysis suggested that immune-related pathways were substantially enriched in both datasets. Tumor immune cell infiltration analysis and clinical validation revealed that PRNP (Prion protein), SNCA (Synuclein alpha), and COX17 (Cytochrome c oxidase copper chaperone COX17) may be closely correlated with immune cell infiltration and ICG expression. A nomogram was constructed to predict the prognosis of patients with HCC using patients' characteristics and risk scores.

Conclusion

CRGs may regulate the development of HCC by targeting the TIM and ICGs. CRGs such as PRNP, SNCA, and COX17 could be promising targets for HCC immune therapy in the future.

Heterogeneity in the immune microenvironment of bone metastasis in driver-positive non-small cell lung cancer

Mutations in epidermal growth factor receptor and anaplastic lymphoma kinase are common driver events in non-small cell lung cancer (NSCLC), which are associated with a high frequency of bone metastases (BMs). While the bone marrow represents a specialized immune microenvironment, the immune repertoire of BMs remains unknown. Considering the higher incidence of BMs in driver gene-positive NSCLCs, and the unique biology of the bone, herein, we assessed the infiltrating immune cells and T cell receptor (TCR) profile of BMs in driver-positive NSCLCs. Immune profile of BMs in driver gene-positive NSCLC were assessed in 10 patients, where 6 had driver gene-positive mutation. TCR and bulk RNA sequencing were performed on malignant bone samples. The diversity and clonality of the TCR repertoire were analyzed. The cellular components were inferred from bulk gene expression profiles computationally by CIBERSORT. Although BMs were generally regarded as immune-cold tumors, immune cell composition analyses showed co-existence of cytotoxic and suppressor immune cells in driver-positive BM samples, as compared to primary lung. Analysis of the TCR repertoire indicated a trend of higher diversity and similar clonality in the driver-positive compared with the driver-negative subsets. In addition, we identified two cases that showed the opposite response to immune checkpoint blockade. A comparison of these two patients' BM samples showed more highly amplified clones, fewer M2 macrophages and more activated natural killer cells in the responder. In summary, BMs in NSCLC are heterogeneous in their immune microenvironment, which might be related to differential clinical outcomes to immune checkpoint blockade.

Integrated analysis based on vesicle trafficking-related genes identifying CNIH4 as a novel therapeutic target for glioma

BACKGROUND

Vesicle trafficking is a highly important process in numerous human diseases, especially in the central nervous system dysfunctions. However, as a key component of vesicle trafficking-related genes (VRGs), Cornichon family AMPA receptor auxiliary protein 4 (CNIH4) has not been systematically elucidated in glioma so far.

METHODS

Differentially expressed VRGs were selected using molecular signatures database (MSigDB), The Cancer Genome Atlas (TCGA), and Genotype-Tissue Expression (GTEx) mRNA expression profiles. Further exploration of CNIH4 was determined using LASSO-Cox regression algorithms. Then Kaplan-Meier (K-M) plotter, receiver operating characteristic (ROC) curves, and multivariate Cox regression analyses were utilized to assess the independent significance of CNIH4 in the CGGA validation cohort. Functional exploration was performed with Gene Set Enrichment Analysis (GSEA) and then verified using a series of functional experiments in glioma cells. Finally, the consensus clustering algorithm was applied to identify clusters in glioma samples. After that, differences in prognosis, the tumor immune microenvironment (TIME), and therapy response were evaluated between clusters.

RESULTS

CNIH4 was shown to be overexpressed in malignant glioma variants and was frequently observed in GCSs and TMZ-resistant cell lines. Higher CNIH4 levels were significantly related to poor outcomes and positively correlated with adverse clinicopathological characteristics. Survival analyses revealed CNIH4 as an independent risk factor that outperformed traditional measures. Enrichment analysis indicated that overactive CNIH4 significantly gathered in stem cell processes. Furthermore, functional assays of silencing CNIH4 expression suppressed stem cell-like properties in vitro and inhibited tumorigenicity in vivo. Finally, the CNIH4-enriched subgroup negatively modulated immunotherapeutic response and reflected lower chemotherapy sensitivity for glioma patients.

CONCLUSION

Our study identified CNIH4 as a potential VRG that regulates tumor stemness, microenvironment immunity, and chemotherapy sensitivity. It may serve as a novel prognostic factor and a promising target against glioma therapy.

Understanding the landscape of immunotherapy in thymic epithelial tumors

Thymic epithelial tumors (TETs) are a rare group of malignancies arising from the thymus. Surgery remains the foundation of treatment for patients with early-stage disease. Limited treatment options are available for the treatment of unresectable, metastatic, or recurrent TETs and are associated with modest clinical efficacy. The emergence of immunotherapies in the treatment of solid tumors has generated significant interest in understanding their role in TET treatment. However, the high rates of comorbid paraneoplastic autoimmune disorders, particularly in thymoma, have tempered expectations regarding the role of immune-based therapies. Clinical studies of immune checkpoint blockade (ICB) in thymoma and thymic carcinoma have revealed higher frequencies of immune-related adverse events (IRAEs) and limited efficacy. Despite these setbacks, the growing understanding of the thymic tumor microenvironment and systemic immune system has advanced the understanding of these diseases and provided opportunities for novel immunotherapy modalities. Ongoing studies are evaluating numerous immune-based treatments in TETs with the goal of improving clinical efficacy and mitigating IRAE risk. This review will provide insight into the current understanding of the thymic immune microenvironment, outcomes of previous ICB studies, and review treatments currently being explored for the management of TET.

Investigation of Diagnostic and Prognostic Value of CLEC4M of Non-Small Cell Lung Carcinoma Associated with Immune Microenvironment

Purpose

C-type lectin domain family 4 member M (CLEC4M) has been found to be involved in the occurrence and development of cancer, but its role in NSCLC remains to be fully explored. Our work aims to evaluate the diagnostic and prognostic value of CLEC4M in NSCLC and to investigate the underlying mechanisms of CLEC4M in the immune microenvironment of NSCLC.

Methods

Integrating publicly accessible data and clinical tissue samples to verify the expression of CLEC4M in NSCLC. The diagnostic value of CLEC4M was determined by receiver operating characteristic (ROC) curve. Kaplan-Meier survival analysis, nomogram plot, univariate and multivariate Cox regression models were performed to evaluate the prognostic impact of CLEC4M on NSCLC patients. The correlation between CLEC4M and tumor immune infiltration was estimated using TIMER and UALCAN databases. Functional assessments including GO, KEGG pathway and GSEA analyses were implemented to illustrate the potential mechanisms of CLEC4M in NSCLC.

Results

CLEC4M was significantly downregulated in NSCLC tissue, as confirmed by immunohistochemistry of clinical tissues. The high AUC value of ROC curves demonstrated the diagnostic accuracy of CLEC4M in NSCLC. Additionally, low CLEC4M expression was associated with poor survival in NSCLC patients. Furthermore, CLEC4M was found to be significantly associated with tumor immune infiltration, and CLEC4M may be involved in immune activation and proliferation inhibition through the functional assessment, suggesting that CLEC4M may be a therapeutic target for NSCLC patients.

Conclusion

Our findings reveal CLEC4M is significantly downregulated in NSCLC tissues, and illustrate the diagnostic and prognostic value of CLEC4M in NSCLC, as well as its potential serve as an immune-related therapeutic target.

Senescence-Related lncRNA Signature Predicts Prognosis, Response to Immunotherapy and Chemotherapy in Skin Cutaneous Melanoma

Skin cutaneous melanoma (SKCM) is a highly malignant and aggressive cancer. Previous studies have shown that cellular senescence is a promising therapeutic strategy to limit melanoma cell progression. However, models to predict the prognosis of melanoma based on senescence-related lncRNAs and the efficacy of immune checkpoint therapy remain undefined. In this study, we developed a predictive signature consisting of four senescence-related lncRNAs (AC009495.2, U62317.1, AATBC, MIR205HG), and we then classified patients into high- and low-risk groups. GSEA (Gene set enrichment analysis) showed different activation of immune-related pathways in two groups. In addition, there were significant differences between the scores of tumor immune microenvironment, tumor burden mutation, immune checkpoint expression, and chemotherapeutic drug sensitivity between the two groups of patients. It provides new insights to guide more personalized treatment for patients with SKCM.

High baseline tumor burden-associated macrophages promote an immunosuppressive microenvironment and reduce the efficacy of immune checkpoint inhibitors through the IGFBP2-STAT3-PD-L1 pathway

BACKGROUND

Several clinical studies have uncovered a negative correlation between baseline tumor burden and the efficacy of immune checkpoint inhibitor (ICI) treatment. This study aimed to uncover the specific mechanisms underlying the difference in sensitivity to ICI treatment between tumors with high (HTB) and low (LTB) tumor burden.

METHODS

For in vivo studies, several mouse models of subcutaneous tumors were established, and transcriptome sequencing, immunohistochemistry, and flow cytometry assays were used to detect the immune status in these subcutaneous tumors. For in vitro experiments, co-culture models, cytokine antibody arrays, western blotting, flow cytometry, and enzyme-linked immunosorbent assays were used to explore the underlying molecular mechanisms RESULTS: We found that MC38 or B16 subcutaneous tumors from the HTB group did not show any response to anti-programmed cell death protein-1 (PD-1) therapy. Through flow cytometry assays, we found that the infiltration with CD8⁺ T cells was significantly decreased whereas M2-like macrophages were enriched in subcutaneous tumors of HTB groups compared with those of LTB group. These changes were not affected by the initial number of injected tumor cells or tumor age, nor could they be reversed by surgical tumor reduction. Intraperitoneal colony-stimulating factor 1 receptor (CSF-1R) inhibitor PLX3397 injection at different time points of tumor growth only had an effect when administered in the early tumor stage to maintain the "heat" of the tumor microenvironment during the process of tumor growth, thereby achieving a response to ICI treatment when the tumor grew to a large size. Mechanistically, we found that insulin-like growth factor binding protein 2 (IGFBP2) expression levels were significantly elevated in HTB tumor tissues. IGFBP2 promoted the programmed death-ligand 1 (PD-L1) expression in M2-like macrophages by activating signal transducer and activator of transcription 3 (STAT3), and PD-L1⁺ M2-like macrophages exerted an immunosuppressive effect by inhibiting the proliferation and activation of CD8⁺ T cells in a PD-L1-dependent fashion.

CONCLUSIONS

This study suggested that the low efficacy of ICI treatment in HTB tumors is mainly attributed to the intratumoral accumulation of PD-L1⁺ M2-like macrophages via the IGFBP2-STAT3-PD-L1 signaling pathway and their substantial inhibitory effects on T cell proliferation and activation.

Methylation Signature Implicated in Immuno-Suppressive Activities in Tubo-Ovarian High-Grade Serous Carcinoma

BACKGROUND

Better understanding of prognostic factors in tubo-ovarian high-grade serous carcinoma (HGSC) is critical, as diagnosis confers an aggressive disease course. Variation in tumor DNA methylation shows promise predicting outcome, yet prior studies were largely platform-specific and unable to evaluate multiple molecular features.

METHODS

We analyzed genome-wide DNA methylation in 1,040 frozen HGSC, including 325 previously reported upon, seeking a multi-platform quantitative methylation signature that we evaluated in relation to clinical features, tumor characteristics, time to recurrence/death, extent of CD8+ tumor-infiltrating lymphocytes (TIL), gene expression molecular subtypes, and gene expression of the ATP-binding cassette transporter TAP1.

RESULTS

Methylation signature was associated with shorter time to recurrence, independent of clinical factors (N = 715 new set, hazard ratio (HR), 1.65; 95% confidence interval (CI), 1.10-2.46; P = 0.015; N = 325 published set HR, 2.87; 95% CI, 2.17-3.81; P = 2.2 × 10-13) and remained prognostic after adjustment for gene expression molecular subtype and TAP1 expression (N = 599; HR, 2.22; 95% CI, 1.66-2.95; P = 4.1 × 10-8). Methylation signature was inversely related to CD8+ TIL levels (P = 2.4 × 10-7) and TAP1 expression (P = 0.0011) and was associated with gene expression molecular subtype (P = 5.9 × 10-4) in covariate-adjusted analysis.

CONCLUSIONS

Multi-center analysis identified a novel quantitative tumor methylation signature of HGSC applicable to numerous commercially available platforms indicative of shorter time to recurrence/death, adjusting for other factors. Along with immune cell composition analysis, these results suggest a role for DNA methylation in the immunosuppressive microenvironment.

IMPACT

This work aids in identification of targetable epigenome processes and stratification of patients for whom tailored treatment may be most beneficial.

Prognostic value of RILPL2 and its correlation with tumor immune microenvironment and glycolysis in non-small cell lung cancer

Rab-interacting lysosomal protein - like 2 (RILPL2) has been reported to be associated with prognosis and tumor biological functions in breast cancer and endometrial carcinoma. However, its expression and functional role in non-small cell lung cancer (NSCLC) remain unclear. The expression and clinical data of lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC) were downloaded from the TCGA database. The expression of RILPL2 in NSCLC cell lines was verified by the Western blot. We used online databases and bioinformatics analysis tools to explore its prognostic value, potential biological functions, and correlations with tumor immune microenvironment.The expression of RILPL2 was significantly lower in NSCLC compared with adjacent normal tissues. Low RILPL2 expression was associated with worse overall survival (OS) in NSCLC. The GO analysis showed RILPL2 was comprehensively involved in immune activity. RILPL2 expression was significantly positively correlated with the infiltration levels of B cells, CD8+T cells, CD4+T cells, macrophages, neutrophils, dendritic cells (P < 0.001), and it was also significantly positively correlated with programmed cell death ligand 1 (PD-L1/CD274) (P < 0.001). High RILPL2 expression could predict better immunotherapy response and prognosis in the immunotherapy cohort. The GSEA analysis showed low RILPL2 expression was associated with glycolysis process in LUAD, which was verified in vitro.These results showed RILPL2 expression was correlated with prognosis, tumor microenvironment, and immunotherapy response in NSCLC. Besides, RILPL2 may regulate glycolysis in LUAD.

Anti-tumor effects of miR-34a by regulating immune cells in the tumor microenvironment

Malignant tumors pose a serious threat to human health. The development of malignant tumors is characterized by uncontrolled cell division and immune evasion. The micro-ribonucleic acid-34a (miR-34a) is a small noncoding single-stranded ribonucleic acid that is ubiquitously present in normal human tissues. However, it has been confirmed to be dysregulated in a variety of tumor cells. Numerous research have revealed the importance of miR-34a in the treatment of various malignancies. MiR-34a deletion can hasten the growth of tumors whereas miR-34a overexpression suppresses the proliferation, invasion, and migration of cancer cells. Moreover, more recent studies have highlighted its role in immunity and investigated its applicability to particular tumors. Through various immune cells, factors, and other mechanisms, miR-34a can inhibit tumor carcinogenesis. In view of the important role of miR-34a in tumors, this research reviewed the aspects of miR-34a regulation of tumor immune microenvironment to exert anti-tumor effects in order to clarify the potential immunotherapy value of miR-34a in tumors.

Spatial cancer systems biology resolves heterotypic interactions and identifies disruption of spatial hierarchy as a pathological driver event

Spatially annotated single-cell datasets provide unprecedented opportunities to dissect cell-cell communication in development and disease. Heterotypic signaling includes interactions between different cell types and is well established in tissue development and spatial organization. Epithelial organization requires several different programs that are tightly regulated. Planar cell polarity (PCP) is the organization of epithelial cells along the planar axis, orthogonal to the apical-basal axis. Here, we investigate PCP factors and explore the implications of developmental regulators as malignant drivers. Utilizing cancer systems biology analysis, we derive a gene expression network for WNT-ligands (WNT) and their cognate frizzled (FZD) receptors in skin cutaneous melanoma. The profiles supported by unsupervised clustering of multiple-sequence alignments identify ligand-independent signaling and implications for metastatic progression based on the underpinning developmental spatial program. Omics studies and spatial biology connect developmental programs with oncological events and explain key spatial features of metastatic aggressiveness. Dysregulation of prominent PCP factors such as specific representatives of the WNT and FZD families in malignant melanoma recapitulates the development program of normal melanocytes but in an uncontrolled and disorganized fashion.

Tumor immune microenvironment changes are associated with response to neoadjuvant chemotherapy and long-term survival benefits in advanced epithelial ovarian cancer: A pilot study

Little is known about the association between efficacy of neoadjuvant chemotherapy (NACT)/survival and the dynamic change of tumor immune environment (TIME) during treatment in epithelial ovarian cancer (EOC). This study investigated the TIME landscape of treatment-naive EOC tumors using multiplex immunofluorescence and associated the TIME before and after platinum-based NACT with treatment efficacy and prognosis in 33 patients with advanced EOC. NACT significantly increased the density of CD8+ T cells (P = 0.033), CD20+ B cells (P = 0.023), CD56 NK cells (P = 0.041), PD-1+ cells (P = 0.042), and PD-L1+CD68+ macrophages (P = 0.005) in the tissue specimens. Response to NACT was evaluated using CA125 response and chemotherapy response score (CRS). Compared with the non-responders, the responders displayed a larger proportion of tumors showing increase in the infiltration of CD20+ cells (P = 0.046) and in the M1/M2 ratio (P = 0.038) as well as fewer tumors showing increase in the infiltration of CD56bright cells (P = 0.041). No association was found between pre-NACT TIME and response to NACT. Density of pre-NACT CD8+ cells was positively associated with longer progression-free survival (PFS) (P = 0.011) and overall survival (OS) (P = 0.048). Post-NACT CD20+ and CD163+ macrophages (M2) infiltrates were associated with prolonged (P = 0.005) and shortened PFS (P = 0.021), respectively. Increase in the density of CD4+ T cells was predictive for longer PFS (P = 0.022) and OS (P = 0.023). In the multivariate analysis, high density of CD8+ cells pre-NACT (P = 0.042) were independently associated with improved OS.

Characterization of immune cell populations in syngeneic murine tumor models

Immunocompetent murine models are important tools for preclinical evaluation of immunotherapies. Here, six different immunocompetent tumor models based on four different cell lines were characterized, including metastatic lung cancer (CMT 167), triple-negative breast cancer (4T1), pancreatic cancer (KPCY), and colon cancer (MC38). The tumors were implanted subcutaneously or orthotopically before the animals were treated with anti-PD1 checkpoint inhibitor. A range of innate and adaptive immune cells were then quantified by flow cytometry of single-cell suspensions from the tumors. Furthermore, confocal laser scanning microscopy was used to quantify the density and distribution of T-cells in frozen sections. A model-dependent cellular immune landscape was observed, with variable responsiveness toward anti-PD1, ranging from the most responsive MC38 colon cancer model to the least responsive 4T1 breast cancer model. The study provides an overview of the immune landscape of these tumor models, and a foundation for further elucidation of pro-tumor and anti-tumor mechanisms behind heterogeneous responses towards immunotherapies.

Integrative analysis to screen novel pyroptosis-related LncRNAs for predicting clinical outcome of glioma and validation in tumor tissue

BACKGROUND

Pyroptosis, also known as inflammatory necrosis, is a programmed cell death that manifests itself as a continuous swelling of cells until the cell membrane breaks, leading to the liberation of cellular contents, which triggers an intense inflammatory response. Pyroptosis might be a panacea for a variety of cancers, which include immunotherapy and chemotherapy-insensitive tumors such as glioma. Several findings have observed that long non-coding RNAs (lncRNAs) modulate the bio-behavior of tumor cells by binding to RNA, DNA and protein. Nevertheless, there are few studies reporting the effect of lncRNAs in pyroptosis processes in glioma.

METHODS

The principal goal of this study was to identify pyroptosis-related lncRNAs (PRLs) utilizing bioinformatic algorithm and to apply PCR techniques for validation in human glioma tissues. The second goal was to establish a prognostic model for predicting the overall survival patients with glioma. Predict algorithm was used to construct prognosis model with good diagnostic precision for potential clinical translation.

RESULTS

Noticeably, molecular subtypes categorized by the PRLs were not distinct from any previously published subtypes of glioma. The immune and mutation landscapes were obviously different from previous subtypes of glioma. Analysis of the sensitivity (IC50) of patients to 30 chemotherapeutic agents identified 22 agents as potential therapeutic agents for patients with low riskscores.

CONCLUSIONS

We established an exact prognostic model according to the expression profile of PRLs, which may facilitate the assessment of patient prognosis and treatment patterns and could be further applied to clinical.

Attenuating Metabolic Competition of Tumor Cells for Favoring the Nutritional Demand of Immune Cells by a Branched Polymeric Drug Delivery System

Tumor cells are dominant in the nutritional competition in the tumor microenvironment, and their metabolic abnormalities often lead to microenvironmental acidosis and nutrient deprivation, thereby impairing the function of immune cells and diminishing the antitumor therapeutic effect. Herein, a branched polymeric conjugate and its efficacy in attenuating the metabolic competition of tumor cells are reported. Compared with the control nanoparticles prepared from its linear counterpart, the branched-conjugate-based nanoparticles can more efficiently accumulate in the tumor tissue and interfere with the metabolic processes of tumor cells to increase the concentration of essential nutrients and reduce the level of immunosuppressive metabolites in the TME, thus creating a favorable environment for infiltrated immune cells. Its combined treatment with an immune checkpoint inhibitor (ICI) achieves an enhanced antitumor effect. The work presents a promising approach for targeting metabolic competition in the TME to enhance the chemo-immunotherapeutic effect against cancers.

An autophagy-related gene prognostic index predicting biochemical recurrence, metastasis, and drug resistance for prostate cancer

Given the dual role of autophagy presenting in tumorigenesis and inhibition, we established an autophagy-related gene prognostic index (ARGPI) with validation to well predict the biochemical recurrence (BCR), metastasis, as well as chemoresistance for patients with prostate cancer (PCa) who underwent radical radiotherapy or prostatectomy. Then, Lasso and COX regression was used to develop the ARGPI. We performed the whole analyses through R packages (version 3.6.3). Secreted phosphoprotein 1 (SPP1), single-minded 2 (SIM2), serine protease inhibitor b5 (SERPINB5), aldehyde dehydrogenase 2 (ALDH2), and acyl-CoA synthetase long-chain 3 (ACSL3) were eventually used to establish the ARGPI score. Patients were divided into two different-risk groups based on the median ARGPI score, high-risk patients with a higher risk of BCR than low-risk patients (hazard ratio [HR]: 5.46, 95% confidence interval [CI]: 3.23-9.24). The risk of metastasis of high-risk patients was higher than low-risk patients (HR: 11.31, 95% CI: 4.89-26.12). In The Cancer Genome Atlas (TCGA) dataset, we observed similar prognostic value of ARGPI in terms of BCR-free survival (HR: 1.79, 95% CI: 1.07-2.99) and metastasis-free survival (HR: 1.80, 95% CI: 1.16-2.78). ARGPI score showed a diagnostic accuracy of 0.703 for drug resistance. Analysis of gene set enrichment analysis (GSEA) indicated that patients in the high-risk group were significantly positively related to interleukin (IL)-18 signaling pathway. Moreover, ARGPI score was significantly related to cancer-related fibroblasts (CAFs; r = 0.36), macrophages (r = 0.28), stromal score (r = 0.38), immune score (r = 0.35), estimate score (r = 0.39), as well as tumor purity (r = -0.39; all P < 0.05). Drug analysis showed that PI-103 was the common sensitive drug and cell line analysis indicated that PC3 was the common cell line of PI-103 and the definitive gene. In conclusion, we found that ARGPI could predict BCR, metastasis, and chemoresistance in PCa patients who underwent radical radiotherapy or prostatectomy.

Tumor immune microenvironment in therapy-naive esophageal adenocarcinoma could predict the nodal status

BACKGROUND

Currently, preoperative staging of esophageal adenocarcinoma (EAC) has modest reliability and accuracy for pT and pN stages prediction, which heavily affects overall survival. The interplay among immune checkpoints, oncogenes, and intratumoral and peritumoral immune infiltrating cells could be used to predict loco-regional metastatic disease in early EAC.

METHODS

We prospectively evaluated immune markers expression and oncogenes status as well as intratumoral and peritumoral immune infiltrating cells populations in esophageal mucosa samples obtained from neoadjuvant therapy-naïve patients who had esophagectomy for EAC.

RESULTS

Vascular invasion and high infiltration of lamina propria mononuclear cells resulted associated with nodal metastasis. Low infiltration of activated CD8⁺ CD28⁺ T cells was observed in both intratumoral and peritumoral mucosa of patients with nodal metastasis. Low levels of CD69, MYD88, and TLR4 transcripts were detected in the intratumoral specimen of patients with lymph node involvement. Receiver operating characteristic curve analysis showed good accuracy for detecting nodal metastasis for all the markers tested. Significant lower infiltration of CD8 T cells and M1 macrophages and a lower expression of CD8A, CD8B, and TBX21 were found also in Esophageal Adenocarcinoma TCGA panCancer Atlas in the normal tissue of patients with nodal metastasis.

CONCLUSIONS

Our data suggest that immune surveillance failure is the main driver of nodal metastasis onset. Moreover, nodal metastasis containment also involves the immune microenvironment of the peritumoral healthy tissue.

A pyroptosis-related lncRNA signature in bladder cancer

PURPOSE

Pyroptosis, a type of programmed cell death, is implicated in the tumorigenesis, development and migration of cancer, which can be regulated by long non-coding RNAs (lncRNAs). Our research aimed to investigate the prognostic role of pyroptosis-related lncRNAs and the relationship to the tumor immune microenvironment through bioinformatics analysis.

METHODS

The clinical and RNA-sequencing data of bladder cancer patients were downloaded from The Cancer Genome Atlas (TCGA). And 412 bladder cancer subjects with clinical information were divided into training and testing cohort. And 52 reported pyroptosis-related genes were used to screen pyroptosis-related lncRNAs. A pyroptosis-related lncRNA signature was constructed based on Cox regression analyses.

RESULTS

A 9-pyroptosis-related-lncRNA signature was identified to separate patients with bladder cancer into two groups. The prognosis of bladder cancer patients in the high-risk group was significantly inferior compared with those in the low-risk group. Risk scores were validated to develop an independent prognostic indicator based on multivariate Cox regression analysis. Receiver operating characteristic curve (ROC) analysis examined the signature on overall survival. The area under time-dependent ROC curve (AUC) at 1-, 3, and 5-years measured 0.747, 0.783, and 0.768, respectively. Analysis of the immune landscape and PD-L1 expression showed that PD-L1 is upregulated in the high-risk group. The immunocyte subtypes of the two groups were different.

CONCLUSION

A novel pyroptosis-related lncRNA signature was identified with prognostic value for bladder cancer patients. Pyroptosis-related lncRNAs have a potential role in cancer immunology and may serve as prognostic or therapeutic targets.

Senescence-related genes define prognosis, immune contexture, and pharmacological response in gastric cancer

As one of the prevalent tumors worldwide, gastric cancer (GC) has obtained sufficient attention in its clinical management and prognostic stratification. Senescence-related genes are involved in the tumorigenesis and progression of GC. A machine learning algorithm-based prognostic signature was developed from six senescence-related genes including SERPINE1, FEN1, PDGFRB, SNCG, TCF3, and APOC3. The TCGA-STAD cohort was utilized as a training set while the GSE84437 and GSE13861 cohorts were analyzed for validation. Immune cell infiltration and immunotherapy efficacy were investigated in the PRJEB25780 cohort. Data from the genomics of drug sensitivity in cancer (GDSC) database revealed pharmacological response. The GSE13861 and GSE54129 cohorts, single-cell dataset GSE134520, and The Human Protein Atlas (THPA) database were utilized for localization of the key senescence-related genes. Association of a higher risk-score with worse overall survival (OS) was identified in the training cohort (TCGA-STAD, P<0.001; HR = 2.03, 95% CI, 1.45-2.84) and the validation cohorts (GSE84437, P = 0.005; HR = 1.48, 95% CI, 1.16-1.95; GSE13861, P = 0.03; HR = 2.23, 95% CI, 1.07-4.62). The risk-score was positively correlated with densities of tumor-infiltrating immunosuppressive cells (P < 0.05) and was lower in patients who responded to pembrolizumab monotherapy (P = 0.03). Besides, patients with a high risk-score had higher sensitivities to the inhibitors against the PI3K-mTOR and angiogenesis (P < 0.05). Expression analysis verified the promoting roles of FEN1, PDGFRB, SERPINE1, and TCF3, and the suppressing roles of APOC3 and SNCG in GC, respectively. Immunohistochemistry staining and single-cell analysis revealed their location and potential origins. Taken together, the senescence gene-based model may potentially change the management of GC by enabling risk stratification and predicting response to systemic therapy.

Tumor microenvironment-mediated immune evasion in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and is the third leading cause of tumor-related mortality worldwide. In recent years, the emergency of immune checkpoint inhibitor (ICI) has revolutionized the management of HCC. Especially, the combination of atezolizumab (anti-PD1) and bevacizumab (anti-VEGF) has been approved by the FDA as the first-line treatment for advanced HCC. Despite great breakthrough in systemic therapy, HCC continues to portend a poor prognosis owing to drug resistance and frequent recurrence. The tumor microenvironment (TME) of HCC is a complex and structured mixture characterized by abnormal angiogenesis, chronic inflammation, and dysregulated extracellular matrix (ECM) remodeling, collectively contributing to the immunosuppressive milieu that in turn prompts HCC proliferation, invasion, and metastasis. The tumor microenvironment coexists and interacts with various immune cells to maintain the development of HCC. It is widely accepted that a dysfunctional tumor-immune ecosystem can lead to the failure of immune surveillance. The immunosuppressive TME is an external cause for immune evasion in HCC consisting of 1) immunosuppressive cells; 2) co-inhibitory signals; 3) soluble cytokines and signaling cascades; 4) metabolically hostile tumor microenvironment; 5) the gut microbiota that affects the immune microenvironment. Importantly, the effectiveness of immunotherapy largely depends on the tumor immune microenvironment (TIME). Also, the gut microbiota and metabolism profoundly affect the immune microenvironment. Understanding how TME affects HCC development and progression will contribute to better preventing HCC-specific immune evasion and overcoming resistance to already developed therapies. In this review, we mainly introduce immune evasion of HCC underlying the role of immune microenvironment, describe the dynamic interaction of immune microenvironment with dysfunctional metabolism and the gut microbiome, and propose therapeutic strategies to manipulate the TME in favor of more effective immunotherapy.

Tumor Mutational Burden for Predicting Prognosis and Therapy Outcome of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC), the primary hepatic malignancy, represents the second-highest cause of cancer-related death worldwide. Many efforts have been devoted to finding novel biomarkers for predicting both patients' survival and the outcome of pharmacological treatments, with a particular focus on immunotherapy. In this regard, recent studies have focused on unravelling the role of tumor mutational burden (TMB), i.e., the total number of mutations per coding area of a tumor genome, to ascertain whether it can be considered a reliable biomarker to be used either for the stratification of HCC patients in subgroups with different responsiveness to immunotherapy, or for the prediction of disease progression, particularly in relation to the different HCC etiologies. In this review, we summarize the recent advances on the study of TMB and TMB-related biomarkers in the HCC landscape, focusing on their feasibility as guides for therapy decisions and/or predictors of clinical outcome.

Lithium in Cancer Therapy: Friend or Foe?

Lithium, a trace element important for fetal health and development, is considered a metal drug with a well-established clinical regime, economical production process, and a mature storage system. Several studies have shown that lithium affects tumor development by regulating inositol monophosphate (IMPase) and glycogen synthase kinase-3 (GSK-3). Lithium can also promote proliferation and programmed cell death (PCD) in tumor cells through a number of new targets, such as the nuclear receptor NR4A1 and Hedgehog-Gli. Lithium may increase cancer treatment efficacy while reducing side effects, suggesting that it can be used as an adjunctive therapy. In this review, we summarize the effects of lithium on tumor progression and discuss the underlying mechanisms. Additionally, we discuss lithium's limitations in antitumor clinical applications, including its narrow therapeutic window and potential pro-cancer effects on the tumor immune system.

Pan-cancer integrated bioinformatics analysis reveals cuproptosis related gene FDX1 is a potential prognostic and immunotherapeutic biomarker for lower-grade gliomas

FDX1 participates in cuproptosis, a copper-dependent cell death mode, which might influence tumor progressions like ferroptosis and pyroptosis. However, the role of FDX1 in tumors remains to be explored. This study investigated FDX1 expression features, and correlations to prognosis, tumor stages, immune microenvironment, and cuproptosis from a pan-cancer perspective based on integrated bioinformatics. FDX1 mRNA and clinical data were obtained from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Broad Institute Cancer Cell Line Encyclopedia (CCLE) databases. Differential expression of FDX1 in tumor stages was performed on GEPIA2.0. Cox proportional hazard regression and survival curve were used to analyze the prognostic value of FDX1. The relationships between FDX1 expression and immune infiltration, immune cells, immune checkpoints, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), and DNA methyltransferase (DNMT) were explored. GSEA was utilized to find the biological function of FDX1 in LGG. Results showed that FDX1 was abnormally expressed in multiple tumor types and demonstrated variability in various tumor stages. Survival analysis revealed FDX1 predicted poor prognosis in glioma (GBMLGG), brain lower-grade glioma (LGG), and good prognosis in the pan-kidney cohort (KIPAN), and kidney renal clear cell carcinoma (KIRC). Immune correlation analysis suggested FDX1 showed positive correlations to StromalScore, ImmuneScore, ESTIMATEScore in LGG and negative correlation in KIRC. Additionally, positive correlations were observed between FDX1 and immune cells infiltration, immune checkpoints, tumor stemness, homologous recombination deficiency (HRD), and TMB in LGG in the pan-cancer analysis. Validation with CGGA suggested prognostic value and immune correlation of FDX1 in LGG. Specifically, high expression of FDX1 was accompanied by high expression of immune checkpoints such as CD276 (B7-H3), CD274 (PD-L1), PDCD1LG2 (PD-L2), CTLA4, and HAVCR2. These findings illustrated that FDX1 might be considered a potential poor prognosis biomarker and immunotherapy predictor in LGG.

A novel Cuprotosis-related signature predicts the prognosis and selects personal treatments for melanoma based on bioinformatics analysis

Background

Melanoma is a common and aggressive cutaneous malignancy characterized by poor prognosis and a high fatality rate. Recently, due to the application of Immune-checkpoint inhibitors (ICI) in melanoma treatment, melanoma patients' prognosis has been tremendously improved. However, the treatment effect varies quite differently from patient to patient. In this study, we aim to construct and validate a Cuproptosis-related risk model to improve outcome prediction of ICIs in melanoma and divide patients into subtypes with different Cuproptosis-related genes.

Methods

Here, according to differentially expressed genes from four melanoma datasets in GEO (Gene Expression Omnibus), and one in TCGA (The Cancer Genome Atlas) database, a novel signature was developed through LASSO and Cox regression analysis. We used 781 melanoma samples to examine the molecular subtypes associated with Cuproptosis-related genes and studied the related gene mutation and TME cell infiltration. Patients with melanoma can be divided into at least three subtypes based on gene expression profile. Survival pan-cancer analysis was also conducted for melanoma patients.

Results

The Cuproptosis risk score can predict tumor immunity, subtype, survival, and drug sensitivity for melanoma. And Cuproptosis-associated subtypes can help predict therapeutic outcomes.

Conclusion

Cuproptosis risk score is a promising potential biomarker in cancer diagnosis, molecular subtypes determination, TME cell infiltration characteristics, and therapy response prediction in melanoma patients.

Construction and comprehensive analysis of a novel prognostic signature associated with pyroptosis molecular subtypes in patients with pancreatic adenocarcinoma

Background

Treatment of cancer with pyroptosis is an emerging strategy. Molecular subtypes based on pyroptosis-related genes(PRGs) seem to be considered more conducive to individualized therapy. It is meaningful to construct a pyroptosis molecular subtypes-related prognostic signature (PMSRPS) to predict the overall survival (OS) of patients with pancreatic adenocarcinoma(PAAD) and guide treatment.

Methods

Based on the transcriptome data of 23 PRGs, consensus clustering was applied to divide the TCGA and GSE102238 combined cohort into three PRGclusters. Prognosis-related differentially expressed genes(DEGs) among PRGclusters were subjected to LASSO Cox regression analysis to determine a PMSRPS. External cohort and in vitro experiments were conducted to verify this PMSRPS. The CIBERSORT algorithm, the ESTIMATE algorithm and the Immunophenoscore (IPS) were used to analyze the infiltrating abundance of immune cells, the tumor microenvironment (TME), and the response to immunotherapy, respectively. Wilcoxon analysis was used to compare tumor mutational burden (TMB) and RNA stemness scores (RNAss) between groups. RT-qPCR and in vitro functional experiments were used for evaluating the expression and function of SFTA2.

Results

Based on three PRGclusters, 828 DEGs were obtained and a PMSRPS was subsequently constructed. In internal and external validation, patients in the high-risk group had significantly lower OS than those in the low-risk group and PMSRPS was confirmed to be an independent prognostic risk factor for patients with PAAD with good predictive performance. Immune cell infiltration abundance and TME scores indicate patients in the high-risk group have typical immunosuppressive microenvironment characteristics. Analysis of IPS suggests patients in the high-risk group responded better to novel immune checkpoint inhibitors (ICIs) than PD1/CTLA4. The high-risk group had higher TMB and RNAss. In addition, 10 potential small-molecule compounds were screened out. Finally, we found that the mRNA expression of SFTA2 gene with the highest risk coefficient in PMSRPS was significantly higher in PAAD than in paracancerous tissues, and knockdown of it significantly delayed the progression of PAAD.

Conclusions

PMSRPS can well predict the prognosis, TME and immunotherapy response of patients with PAAD, identify potential drugs, and provide treatment guidance based on individual needs.

Identification and verification of m7G-Related genes as biomarkers for prognosis of sarcoma

Background: Increasing evidence indicates a crucial role for N7-methylguanosine (m7G) methylation modification in human disease development, particularly cancer, and aberrant m7G levels are closely associated with tumorigenesis and progression via regulation of the expression of multiple oncogenes and tumor suppressor genes. However, the role of m7G in sarcomas (SARC) has not been adequately evaluated. Materials and methods: Transcriptome and clinical data were gathered from the TCGA database for this study. Normal and SARC groups were compared for the expression of m7G-related genes (m7GRGs). The expression of m7GRGs was verified using real-time quantitative PCR (RT-qPCR) in SARC cell lines. Then, differentially expressed genes (DEGs) were identified between high and low m7GRGs expression groups in SARC samples, and GO enrichment and KEGG pathways were evaluated. Next, prognostic values of m7GRGs were evaluated by Cox regression analysis. Subsequently, a prognostic model was constructed using m7GRGs with good prognostic values by Lasso regression analysis. Besides, the relationships between prognostic m7GRGs and immune infiltration, clinical features, cuproptosis-related genes, and antitumor drugs were investigated in patients with SARC. Finally, a ceRNA regulatory network based on m7GRGs was constructed. Results: The expression of ten m7GRGs was higher in the SARC group than in the control group. DEGs across groups with high and low m7GRGs expression were enriched for adhesion sites and cGMP-PKG. Besides, we constructed a prognostic model that consists of EIF4A1, EIF4G3, NCBP1, and WDR4 m7GRGs for predicting the survival likelihood of sarcoma patients. And the elevated expression of these four prognostic m7GRGs was substantially associated with poor prognosis and elevated expression in SARC cell lines. Moreover, we discovered that these four m7GRGs expressions were negatively correlated with CD4⁺ T cell levels, dendritic cell level and tumor purity, and positively correlated with tumor mutational burden, microsatellite instability, drug sensitivity and cuproptosis-related genes in patients with sarcomas. Then, a triple regulatory network of mRNA, miRNA, and lncRNA was established. Conclusion: The current study identified EIF4A1, EIF4G3, NCBP1, and WDR4 as prognostic genes for SARC that are associated with m7G.These findings extend our knowledge of m7G methylation in SARC and may guide the development of innovative treatment options.

Treatment of HCC with claudin-1-specific antibodies suppresses carcinogenic signaling and reprograms the tumor microenvironment

BACKGROUND & AIMS

Despite recent approvals, the response to treatment and prognosis of patients with advanced hepatocellular carcinoma (HCC) remain poor. Claudin-1 (CLDN1) is a membrane protein that is expressed at tight junctions, but it can also be exposed non-junctionally, such as on the basolateral membrane of the human hepatocyte. While CLDN1 within tight junctions is well characterized, the role of non-junctional CLDN1 and its role as a therapeutic target in HCC remains unexplored.

METHODS

Using humanized monoclonal antibodies (mAbs) specifically targeting the extracellular loop of human non-junctional CLDN1 and a large series of patient-derived cell-based and animal model systems we aimed to investigate the role of CLDN1 as a therapeutic target for HCC.

RESULTS

Targeting non-junctional CLDN1 markedly suppressed tumor growth and invasion in cell line-based models of HCC and patient-derived 3D ex vivo models. Moreover, the robust effect on tumor growth was confirmed in vivo in a large series of cell line-derived xenograft and patient-derived xenograft mouse models. Mechanistic studies, including single-cell RNA sequencing of multicellular patient HCC tumorspheres, suggested that CLDN1 regulates tumor stemness, metabolism, oncogenic signaling and perturbs the tumor immune microenvironment.

CONCLUSIONS

Our results provide the rationale for targeting CLDN1 in HCC and pave the way for the clinical development of CLDN1-specific mAbs for the treatment of advanced HCC.

IMPACT AND IMPLICATIONS

Hepatocellular carcinoma (HCC) is associated with high mortality and unsatisfactory treatment options. Herein, we identified the cell surface protein Claudin-1 as a treatment target for advanced HCC. Monoclonal antibodies targeting Claudin-1 inhibit tumor growth in patient-derived ex vivo and in vivo models by modulating signaling, cell stemness and the tumor immune microenvironment. Given the differentiated mechanism of action, the identification of Claudin-1 as a novel therapeutic target for HCC provides an opportunity to break the plateau of limited treatment response. The results of this preclinical study pave the way for the clinical development of Claudin-1-specific antibodies for the treatment of advanced HCC. It is therefore of key impact for physicians, scientists and drug developers in the field of liver cancer and gastrointestinal oncology.

Targets of Immune Escape Mechanisms in Cancer: Basis for Development and Evolution of Cancer Immune Checkpoint Inhibitors

Immune checkpoint blockade (ICB) has emerged as a novel therapeutic tool for cancer therapy in the last decade. Unfortunately, a small number of patients benefit from approved immune checkpoint inhibitors (ICIs). Therefore, multiple studies are being conducted to find new ICIs and combination strategies to improve the current ICIs. In this review, we discuss some approved immune checkpoints, such as PD-L1, PD-1, and CTLA-4, and also highlight newer emerging ICIs. For instance, HLA-E, overexpressed by tumor cells, represents an immune-suppressive feature by binding CD94/NKG2A, on NK and T cells. NKG2A blockade recruits CD8+ T cells and activates NK cells to decrease the tumor burden. NKG2D acts as an NK cell activating receptor that can also be a potential ICI. The adenosine A2A and A2B receptors, CD47-SIRPα, TIM-3, LAG-3, TIGIT, and VISTA are targets that also contribute to cancer immunoresistance and have been considered for clinical trials. Their antitumor immunosuppressive functions can be used to develop blocking antibodies. PARPs, mARTs, and B7-H3 are also other potential targets for immunosuppression. Additionally, miRNA, mRNA, and CRISPR-Cas9-mediated immunotherapeutic approaches are being investigated with great interest. Pre-clinical and clinical studies project these targets as potential immunotherapeutic candidates in different cancer types for their robust antitumor modulation.

By integrating single-cell RNA-seq and bulk RNA-seq in sphingolipid metabolism, CACYBP was identified as a potential therapeutic target in lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is a heterogeneous disease with a dismal prognosis for advanced tumors. Immune-associated cells in the microenvironment substantially impact LUAD formation and progression, which has gained increased attention in recent decades. Sphingolipids have a profound impact on tumor formation and immune infiltration. However, few researchers have focused on the utilization of sphingolipid variables in the prediction of LUAD prognosis. The goal of this work was to identify the major sphingolipid-related genes (SRGs) in LUAD and develop a valid prognostic model based on SRGs.

Methods

The most significant genes for sphingolipid metabolism (SM) were identified using the AUCell and WGCNA algorithms in conjunction with single-cell and bulk RNA-seq. LASSO and COX regression analysis was used to develop risk models, and patients were divided into high-and low-risk categories. External nine provided cohorts evaluated the correctness of the models. Differences in immune infiltration, mutation landscape, pathway enrichment, immune checkpoint expression, and immunotherapy were also further investigated in distinct subgroups. Finally, cell function assay was used to verify the role of CACYBP in LUAD cells.

Results

A total of 334 genes were selected as being most linked with SM activity for further investigation, and a risk model consisting of 11 genes was established using lasso and cox regression. According to the median risk value, patients were split into high- and low-risk groups, and the high-risk group had a worse prognosis. The low-risk group had more immune cell infiltration and higher expression of immune checkpoints, which illustrated that the low-risk group was more likely to benefit from immunotherapy. It was verified that CACYBP could increase the ability of LUAD cells to proliferate, invade, and migrate.

Conclusion

The eleven-gene signature identified in this research may help physicians create individualized care plans for LUAD patients. CACYBP may be a new therapeutic target for patients with advanced LUAD.

Role of gene signature regulation in tumor immune microenvironment on the mechanism of uveal melanoma metastasis

BACKGROUND

Uveal melanoma (UM) is a rare but deadly cancer. The main cause of death from UM is liver metastasis. Though the metastasis mechanism remains unclear, it is closely related to the immune microenvironment and gene expression.

OBJECTIVE

This study aimed to identify the prognostic genes in primary and metastatic UM and their relationship with the immune microenvironment.

METHODS

Primary and metastatic UM data from the GEO database included GSE22138 and GSE44295 datasets. Kaplan-Meier analysis, Cox regression models, and ROC analysis were applied to screen genes in GSE22138. TIMER2.0 was employed to analyze the immune microenvironment from gene expression. Prognostic immune gene correlation was tested by Spearman. The results were validated in the independent dataset of cohort GSE44295.

RESULTS

Metastasis and primary differential gene analysis showed 107 significantly different genes associated with prognosis, and 11 of them were immune-related. ROC analysis demonstrated that our signature was predictive for UM prognosis (AUC > 0.8). Neutrophil and myeloid dendritic cells were closely associated with metastasis with scores that significantly divided patients into high-risk and low-risk groups (log-rank p< 0.05). Of these 11 genes, FABP5 and SHC4 were significantly associated with neutrophils in metastatic tumors, while ROBO1 expression was significantly correlated with myeloid dendritic cells in the primary tumors.

CONCLUSIONS

The present study constructed an 11-gene signature and established a model for risk stratification and prediction of overall survival in metastatic UM. Since FABP5 and SHC4 are related to neutrophil infiltration in metastatic UM, FABP5 and neutrophil regulation might be crucial in metastatic UM.

GAPDH Is a Novel Ferroptosis-Related Marker and Correlates with Immune Microenvironment in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is a prevalent form of lung cancer with high morbidity and fatality rates. Ferroptosis is a type of programmed cell death that is iron-dependent. Recent findings have suggested that ferroptosis inducers have promising prospects for the therapy of LUAD. However, ferroptosis-related gene expression in LUAD and its relationship with the tumor prognosis and tumor immune microenvironment remain unknown. We identified a total of 638 ferroptosis-related genes, built a LUAD ferroptosis-related risk model (FRRM) with the help of Least Absolute Shrinkage Selection Operator (LASSO) regression analysis based on The Cancer Genome Atlas (TCGA) database, split LUAD patients into high- and low-risk clusters, and verified the model utilizing the Gene Expression Omnibus (GEO) database. The results of the FRRM's principal component analysis (PCA) demonstrated its strong predictive power. Further, univariate and multivariate Cox and AUC curve analyses demonstrated that the model was independent of other clinical traits and served as an independent prognostic factor. The nomogram demonstrated strong predictive power for overall survival, according to calibration plots. We also explored variations in clinical characteristics, immune cell infiltration, immune-related function, and functional pathways between the high- and low-risk groups. Additionally, we used a protein-protein interaction (PPI) network of various genes in the two groups to search for potential target genes. GAPDH was then chosen for a follow-up investigation. An analysis was performed on the relationship between GAPDH and variations in survival prognosis, clinical traits, immune cell infiltration, immune checkpoints, and immunotherapy. In vitro tests further supported the probable functions of GAPDH as a ferroptosis marker in LUAD. In conclusion, a novel ferroptosis-related prognostic gene, GAPDH, was discovered, whose expression was connected to the tumor immune microenvironment. The combination of immunotherapy and the targeting of GAPDH to induce ferroptosis in LUAD may provide a novel therapeutical option.

Exosomes as smart drug delivery vehicles for cancer immunotherapy

Exosomes (Exos) as drug delivery vehicles have been widely used for cancer immunotherapy owing to their good biocompatibility, low toxicity, and low immunogenicity. Some Exos-based cancer immunotherapy strategies such as tuning of immunosuppressive tumor microenvironment, immune checkpoint blockades, and cancer vaccines have also been investigated in recent years, which all showed excellent therapeutic effects for malignant tumor. Furthermore, some Exos-based drug delivery systems (DDSs) for cancer immunotherapy have also undergone clinic trails, indicating that Exos are a promising drug delivery carrier. In this review, in order to promote the development of Exos-based DDSs in cancer immunotherapy, the biogenesis and composition of Exos, and Exos as drug delivery vehicles for cancer immunotherapy are summarized. Meanwhile, their clinical translation and challenges are also discussed. We hope this review will provide a good guidance for Exos as drug delivery vehicles for cancer immunotherapy.

Cuproptosis-related lncRNA signatures: Predicting prognosis and evaluating the tumor immune microenvironment in lung adenocarcinoma

Background

Cuproptosis, a unique kind of cell death, has implications for cancer therapy, particularly lung adenocarcinoma (LUAD). Long non-coding RNAs (lncRNAs) have been demonstrated to influence cancer cell activity by binding to a wide variety of targets, including DNA, RNA, and proteins.

Methods

Cuproptosis-related lncRNAs (CRlncRNAs) were utilized to build a risk model that classified patients into high-and low-risk groups. Based on the CRlncRNAs in the model, Consensus clustering analysis was used to classify LUAD patients into different subtypes. Next, we explored the differences in overall survival (OS), the tumor immune microenvironment (TIME), and the mutation landscape between different risk groups and molecular subtypes. Finally, the functions of LINC00592 were verified through in vitro experiments.

Results

Patients in various risk categories and molecular subtypes showed statistically significant variations in terms of OS, immune cell infiltration, pathway activity, and mutation patterns. Cell experiments revealed that LINC00592 knockdown significantly reduced LUAD cell proliferation, invasion, and migration ability.

Conclusion

The development of a trustworthy prediction model based on CRlncRNAs may significantly aid in the assessment of patient prognosis, molecular features, and therapeutic modalities and may eventually be used in clinical applications.

Innate immunity in pancreatic cancer: Lineage tracing and function

Increasingly, patients with gastrointestinal tumors can benefit from immunotherapy, but not patients with pancreatic cancer. While this lack of benefit has been attributed to lower T-cell infiltration in pancreatic cancer, other studies have demonstrated the presence of numerous T cells in pancreatic cancer, suggesting another mechanism for the poor efficacy of immunotherapy. Single-cell RNA sequencing studies on the pancreatic cancer immune microenvironment have demonstrated the predominance of innate immune cells (e.g., macrophages, dendritic cells, mast cells, and innate immune lymphoid cells). Therefore, in-depth research on the source and function of innate immune lymphocytes in pancreatic cancer could guide pancreatic cancer immunotherapy.

Exosomes and cancer immunotherapy: A review of recent cancer research

As phospholipid extracellular vesicles (EVs) secreted by various cells, exosomes contain non-coding RNA (ncRNA), mRNA, DNA fragments, lipids, and proteins, which are essential for intercellular communication. Several types of cells can secrete exosomes that contribute to cancer initiation and progression. Cancer cells and the immune microenvironment interact and restrict each other. Tumor-derived exosomes (TDEs) have become essential players in this balance because they carry information from the original cancer cells and express complexes of MHC class I/II epitopes and costimulatory molecules. In the present study, we aimed to identify potential targets for exosome therapy by examining the specific expression and mechanism of exosomes derived from cancer cells. We introduced TDEs and explored their role in different tumor immune microenvironment (TIME), with a particular emphasis on gastrointestinal cancers, before briefly describing the therapeutic strategies of exosomes in cancer immune-related therapy.

Advanced development of biomarkers for immunotherapy in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common liver cancer and one of the leading causes of cancer-related deaths in the world. Mono-immunotherapy and combination therapy with immune checkpoint inhibitors (ICIs) and multitargeted tyrosine kinase inhibitors (TKIs) or anti-vascular endothelial growth factor (anti-VEGF) inhibitors have become new standard therapies in advanced HCC (aHCC). However, the clinical benefit of these treatments is still limited. Thus, proper biomarkers which can predict treatment response to immunotherapy to maximize clinical benefit while sparing unnecessary toxicity are urgently needed. Contrary to other malignancies, up until now, no acknowledged biomarkers are available to predict resistance or response to immunotherapy for HCC patients. Furthermore, biomarkers, which are established in other cancer types, such as programmed death ligand 1 (PD-L1) expression and tumor mutational burden (TMB), have no stable predictive effect in HCC. Thus, plenty of research focusing on biomarkers for HCC is under exploration. In this review, we summarize the predictive and prognostic biomarkers as well as the potential predictive mechanism in order to guide future research direction for biomarker exploration and clinical treatment options in HCC.