Macrophage correlates with immunophenotype and predicts anti-PD-L1 response of urothelial cancer

M2-type tumor-associated macrophages upregulated PD-L1 expression in cervical cancer via the PI3K/AKT pathway

BACKGROUND AND PURPOSE

PD-1/PD-L1 inhibitors have become a promising therapy. However, the response rate is lower than 30% in patients with cervical cancer (CC), which is related to immunosuppressive components in tumor microenvironment (TME). Tumor-associated macrophages (TAMs), as one of the most important immune cells, are involved in the formation of tumor suppressive microenvironment. Therefore, it will provide a theoretical basis for curative effect improvement about the regulatory mechanism of TAMs on PD-L1 expression.

METHODS

The clinical data and pathological tissues of CC patients were collected, and the expressions of PD-L1, CD68 and CD163 were detected by immunohistochemistry. Bioinformatics was used to analyze the macrophage subtypes involved in PD-L1 regulation. A co-culture model was established to observe the effects of TAMs on the morphology, migration and invasion function of CC cells, and the regulatory mechanism of TAMs on PD-L1.

RESULTS

PD-L1 expression on tumor cells could predict the poor prognosis of patients. And there was a strong correlation between PD-L1 expression with CD163+TAMs infiltration. Similarly, PD-L1 expression was associated with M1/M2-type TAMs infiltration in bioinformatics analysis. The results of cell co-culture showed that M1/M2-type TAMs could upregulate PD-L1 expression, especially M2-type TAMs may elevate the PD-L1 expression via PI3K/AKT pathway. Meanwhile, M1/M2-type TAMs can affect the morphological changes, and enhance migration and invasion abilities of CC cells.

CONCLUSIONS

PD-L1 expression in tumor cells can be used as a prognostic factor and is closely related to CD163+TAMs infiltration. In addition, M2-type TAMs can upregulate PD-L1 expression in CC cells through PI3K/AKT pathway, enhance the migration and invasion capabilities, and affect the tumor progression.

Transcriptome Deconvolution Reveals Absence of Cancer Cell Expression Signature in Immune Checkpoint Blockade Response

Immune checkpoint therapy (ICB) has conferred significant and durable clinical benefit to some patients with cancer. However, most patients do not respond to ICB, and reliable biomarkers of ICB response are needed to improve patient stratification. Here, we performed a transcriptome-wide meta-analysis across 1,486 tumors from ICB-treated patients and tumors with expected ICB outcomes based on microsatellite status. Using a robust transcriptome deconvolution approach, we inferred cancer- and stroma-specific gene expression differences and identified cell-type specific features of ICB response across cancer types. Consistent with current knowledge, stromal expression of CXCL9, CXCL13, and IFNG were the top determinants of favorable ICB response. In addition, we identified a group of potential immune-suppressive genes, including FCER1A, associated with poor response to ICB. Strikingly, PD-L1 expression in stromal cells, but not cancer cells, is correlated with ICB response across cancer types. Furthermore, the unbiased transcriptome-wide analysis failed to identify cancer-cell intrinsic expression signatures of ICB response conserved across tumor types, suggesting that cancer cells lack tissue-agnostic transcriptomic features of ICB response.

SIGNIFICANCE

Our results challenge the prevailing dogma that cancer cells present tissue-agnostic molecular markers that modulate immune activity and ICB response, which has implications on the development of improved ICB diagnostics and treatments.

N6-methyladenosine methylation regulates the tumor microenvironment of Epstein-Barr virus-associated gastric cancer

BACKGROUND

N6-methyladenosine (m6A) methylation modification exists in Epstein-Barr virus (EBV) primary infection, latency, and lytic reactivation. It also modifies EBV latent genes and lytic genes. EBV-associated gastric cancer (EBVaGC) is a distinctive molecular subtype of GC. We hypothesized EBV and m6A methylation regulators interact with each other in EBVaGC to differentiate it from other types of GC.

AIM

To investigate the mechanisms of m6A methylation regulators in EBVaGC to determine the differentiating factors from other types of GC.

METHODS

First, The Cancer Gene Atlas and Gene Expression Omnibus databases were used to analyze the expression pattern of m6A methylation regulators between EBVaGC and EBV-negative GC (EBVnGC). Second, we identified Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment of m6A-related differentially expressed genes. We quantified the relative abundance of immune cells and inflammatory factors in the tumor microenvironment (TME). Finally, cell counting kit-8 cell proliferation test, transwell test, and flow cytometry were used to verify the effect of insulin-like growth factor binding protein 1 (IGFBP1) in EBVaGC cell lines.

RESULTS

m6A methylation regulators were involved in the occurrence and development of EBVaGC. Compared with EBVnGC, the expression levels of m6A methylation regulators Wilms tumor 1-associated protein, RNA binding motif protein 15B, CBL proto-oncogene like 1, leucine rich pentatricopeptide repeat containing, heterogeneous nuclear ribonucleoprotein A2B1, IGFBP1, and insulin-like growth factor 2 binding protein 1 were significantly downregulated in EBVaGC (P < 0.05). The overall survival rate of EBVaGC patients with a lower expression level of IGFBP1 was significantly higher (P = 0.046). GO and KEGG functional enrichment analyses showed that the immunity pathways were significantly activated and rich in immune cell infiltration in EBVaGC. Compared with EBVnGC, the infiltration of activated CD4+ T cells, activated CD8+ T cells, monocytes, activated dendritic cells, and plasmacytoid dendritic cells were significantly upregulated in EBVaGC (P < 0.001). In EBVaGC, the expression level of proinflammatory factors interleukin (IL)-17, IL-21, and interferon-γ and immunosuppressive factor IL-10 were significantly increased (P < 0.05). In vitro experiments demonstrated that the expression level of IGFBP1 was significantly lower in an EBVaGC cell line (SNU719) than in an EBVnGC cell line (AGS) (P < 0.05). IGFBP1 overexpression significantly attenuated proliferation and migration and promoted the apoptosis levels in SNU719. Interfering IGFBP1 significantly promoted proliferation and migration and attenuated the apoptosis levels in AGS.

CONCLUSION

m6A regulators could remodel the TME of EBVaGC, which is classified as an immune-inflamed phenotype and referred to as a “hot” tumor. Among these regulators, we demonstrated that IGFBP1 affected proliferation, migration, and apoptosis.

N6-methyladenosine methylation regulates the tumor microenvironment of Epstein-Barr virus-associated gastric cancer

BACKGROUND

N6-methyladenosine (m6A) methylation modification exists in Epstein-Barr virus (EBV) primary infection, latency, and lytic reactivation. It also modifies EBV latent genes and lytic genes. EBV-associated gastric cancer (EBVaGC) is a distinctive molecular subtype of GC. We hypothesized EBV and m6A methylation regulators interact with each other in EBVaGC to differentiate it from other types of GC.

AIM

To investigate the mechanisms of m6A methylation regulators in EBVaGC to determine the differentiating factors from other types of GC.

METHODS

First, The Cancer Gene Atlas and Gene Expression Omnibus databases were used to analyze the expression pattern of m6A methylation regulators between EBVaGC and EBV-negative GC (EBVnGC). Second, we identified Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment of m6A-related differentially expressed genes. We quantified the relative abundance of immune cells and inflammatory factors in the tumor microenvironment (TME). Finally, cell counting kit-8 cell proliferation test, transwell test, and flow cytometry were used to verify the effect of insulin-like growth factor binding protein 1 (IGFBP1) in EBVaGC cell lines.

RESULTS

m6A methylation regulators were involved in the occurrence and development of EBVaGC. Compared with EBVnGC, the expression levels of m6A methylation regulators Wilms tumor 1-associated protein, RNA binding motif protein 15B, CBL proto-oncogene like 1, leucine rich pentatricopeptide repeat containing, heterogeneous nuclear ribonucleoprotein A2B1, IGFBP1, and insulin-like growth factor 2 binding protein 1 were significantly downregulated in EBVaGC (P < 0.05). The overall survival rate of EBVaGC patients with a lower expression level of IGFBP1 was significantly higher (P = 0.046). GO and KEGG functional enrichment analyses showed that the immunity pathways were significantly activated and rich in immune cell infiltration in EBVaGC. Compared with EBVnGC, the infiltration of activated CD4+ T cells, activated CD8+ T cells, monocytes, activated dendritic cells, and plasmacytoid dendritic cells were significantly upregulated in EBVaGC (P < 0.001). In EBVaGC, the expression level of proinflammatory factors interleukin (IL)-17, IL-21, and interferon-γ and immunosuppressive factor IL-10 were significantly increased (P < 0.05). In vitro experiments demonstrated that the expression level of IGFBP1 was significantly lower in an EBVaGC cell line (SNU719) than in an EBVnGC cell line (AGS) (P < 0.05). IGFBP1 overexpression significantly attenuated proliferation and migration and promoted the apoptosis levels in SNU719. Interfering IGFBP1 significantly promoted proliferation and migration and attenuated the apoptosis levels in AGS.

CONCLUSION

m6A regulators could remodel the TME of EBVaGC, which is classified as an immune-inflamed phenotype and referred to as a "hot" tumor. Among these regulators, we demonstrated that IGFBP1 affected proliferation, migration, and apoptosis.

Identification and experimental validation of cuproptosis regulatory program in a sepsis immune microenvironment through a combination of single-cell and bulk RNA sequencing

Background

In spite of its high mortality rate and poor prognosis, the pathogenesis of sepsis is still incompletely understood. This study established a cuproptosis-based risk model to diagnose and predict the risk of sepsis. In addition, the cuproptosis-related genes were identified for targeted therapy.

Methods

Single-cell sequencing analyses were used to characterize the cuproptosis activity score (CuAS) and intercellular communications in sepsis. Differential cuproptosis-related genes (CRGs) were identified in conjunction with single-cell and bulk RNA sequencing. LASSO and Cox regression analyses were employed to develop a risk model. Three external cohorts were conducted to assess the model's accuracy. Differences in immune infiltration, immune cell subtypes, pathway enrichment, and the expression of immunomodulators were further evaluated in distinct groups. Finally, various in-vitro experiments, such as flow cytometry, Western blot, and ELISA, were used to explore the role of LST1 in sepsis.

Results

ScRNA-seq analysis demonstrated that CuAS was highly enriched in monocytes and was closely related to the poor prognosis of sepsis patients. Patients with higher CuAS exhibited prominent strength and numbers of cell-cell interactions. A total of five CRGs were identified based on the LASSO and Cox regression analyses, and a CRG-based risk model was established. The lower riskScore cohort exhibited enhanced immune cell infiltration, elevated immune scores, and increased expression of immune modulators, indicating the activation of an antibacterial response. Ultimately, in-vitro experiments demonstrated that LST1, a key gene in the risk model, was enhanced in the macrophage in response to LPS, which was closely related to the decrease of macrophage survival rate, the enhancement of apoptosis and oxidative stress injury, and the imbalance of the M1/M2 phenotype.

Conclusions

This study constructed a cuproptosis-related risk model to accurately predict the prognosis of sepsis. We further characterized the cuproptosis-related gene LST1 to provide a theoretical framework for sepsis therapy.

Longitudinal molecular profiling elucidates immunometabolism dynamics in breast cancer

Although metabolic reprogramming within tumor cells and tumor microenvironment (TME) is well described in breast cancer, little is known about how the interplay of immune state and cancer metabolism evolves during treatment. Here, we characterize the immunometabolic profiles of tumor tissue samples longitudinally collected from individuals with breast cancer before, during and after neoadjuvant chemotherapy (NAC) using proteomics, genomics and histopathology. We show that the pre-, on-treatment and dynamic changes of the immune state, tumor metabolic proteins and tumor cell gene expression profiling-based metabolic phenotype are associated with treatment response. Single-cell/nucleus RNA sequencing revealed distinct tumor and immune cell states in metabolism between cold and hot tumors. Potential drivers of NAC based on above analyses were validated in vitro. In summary, the study shows that the interaction of tumor-intrinsic metabolic states and TME is associated with treatment outcome, supporting the concept of targeting tumor metabolism for immunoregulation.

Comprehensive analysis of T-cell regulatory factors and tumor immune microenvironment in stomach adenocarcinoma

BACKGROUND

Gastric cancer (GC) is one of the most prevalent malignant tumors worldwide and is associated with high morbidity and mortality rates. However, the specific biomarkers used to predict the postoperative prognosis of patients with gastric cancer remain unknown. Recent research has shown that the tumor microenvironment (TME) has an increasingly positive effect on anti-tumor activity. This study aims to build signatures to study the effect of certain genes on gastric cancer.

METHODS

Expression profiles of 37 T cell-related genes and their TME characteristics were comprehensively analyzed. A risk signature was constructed and validated based on the screened T cell-related genes, and the roles of hub genes in GC were experimentally validated.

RESULTS

A novel T cell-related gene signature was constructed based on CD5, ABCA8, SERPINE2, ESM1, SERPINA5, and NMU. The high-risk group indicated lower overall survival (OS), poorer immune efficacy, and higher drug resistance, with SERPINE2 promoting GC cell proliferation, according to experiments. SERPINE2 and CXCL12 were significantly correlated, indicating poor OS via the Youjiang cohort.

CONCLUSIONS

This study identified T cell-related genes in patients with stomach adenocarcinoma (STAD) for prognosis estimation and proposed potential immunotherapeutic targets for STAD.

Identification of crucial genes through WGCNA in the progression of gastric cancer

Background: To explore the hub gene closely related to the progression of gastric cancer (GC), so as to provide a theoretical basis for revealing the therapeutic mechanism of GC. Methods: The gene expression profile and clinical data of GSE15459 in Gene Expression Omnibus (GEO) database were downloaded. The weighted gene co-expression network analysis (WGCNA) was used to screen the key modules related to GC progression. Survival analysis was used to assess the influence of hub genes on patients' outcomes. CIBERSORT analysis was used to predict the tissue infiltrating immune cells in patients. Immunohistochemical staining was conducted to further verify the expression of hub genes. Results: Through WGCNA, a total of 26 co-expression modules were constructed, in which salmon module and royalblue module had strong correlation with GC progression. The results of enrichment analysis showed that genes in the two modules were mainly involved in toll-like receptor signaling pathway, cholesterol metabolism and neuroactive ligand-receptor interaction. Six hub genes (C1QA, C1QB, C1QC, FCER1G, FPR3 and TYROBP) related to GC progression were screened. Survival analysis showed overall survival in the high expression group was significantly lower than that in the low expression group. CIBERSORT analysis revealed that immune characteristics difference between patients in early stage and advanced stage. Immunohistochemical results confirmed that C1QB, FCER1G, FPR3 and TYROBP were significantly associated with disease progression in GC. Conclusion: Our study identified that C1QB, FCER1G, FPR3 and TYROBP played important roles in the progression of GC, and their specific mechanisms are worth further study.

FAT1 upregulation is correlated with an immunosuppressive tumor microenvironment and predicts unfavorable outcome of immune checkpoint therapy in non-small cell lung cancer

Background

Previous studies found that FAT1 was recurrently mutated and aberrantly expressed in multiple cancers, and the loss function of FAT1 promoted the formation of cancer-initiating cells in several cancers. However, in some types of cancer, FAT1 upregulation could lead to epithelial-mesenchymal transition (EMT). The role of FAT1 in cancer progression, which appears to be cancer-type-specific, is largely unknown.

Methods

QRT-PCR and immunochemistry were used to verify the expression of FAT1 in non-small cell lung cancer (NSCLC). QRT-PCR and Western blot were used to detect the influence of siFAT1 knockdown on the expression of potential targets of FAT1 in NSCLC cell lines. GEPIA, KM-plotter, CAMOIP, and ROC-Plotter were used to evaluate the association between FAT1 and clinical outcomes based on expression and clinical data from TCGA and immune checkpoint inhibitors (ICI) treated cohorts.

Results

We found that FAT1 upregulation was associated with the activation of TGF-β and EMT signaling pathways in NSCLC. Patients with a high FAT1 expression level tend to have a poor prognosis and hard to benefit from ICI therapy. Genes involved in TGF-β/EMT signaling pathways (SERPINE1, TGFB1/2, and POSTN) were downregulated upon knockdown of FAT1. Genomic and immunologic analysis showed that high cancer-associated fibroblast (CAF) abundance, decreased CD8+ T cells infiltration, and low TMB/TNB were correlated with the upregulation of FAT1, thus promoting an immunosuppressive tumor microenvironment (TME) which influence the effect of ICI-therapy.

Conclusion

Our findings revealed the pattern of FAT1 upregulation in the TME of patients with NSCLC, and demonstrated its utility as a biomarker for unfavorable clinical outcomes, thereby providing a potential therapeutic target for NSCLC treatment.

Cdc42-driven endosomal cholesterol transport promotes collateral resistance in HER2-positive gastric cancer

Resistance to trastuzumab and the poor efficacy of subsequent chemotherapy have become major challenges for HER2-positive gastric cancer (GC). As resistance evolves, tumor cells may acquire a new drug susceptibility profile, profoundly impacting the subsequent treatment selection and patient survival. However, the interplay between trastuzumab and other types of drugs in HER2-positive GC remains elusive. In our study, we utilized resistant cell lines and tissue specimens to map the drug susceptibility profile of trastuzumab-resistant GC, discovering that resistance to trastuzumab induces collateral resistance to commonly used chemotherapeutic agents. Additionally, patients with collateral resistance distinguished by a 13-gene scoring model in HER2-positive GC cohorts are predicted to have a poor prognosis and may be sensitive to cholesterol-lowering drugs. Mechanistically, endosomal cholesterol transport is further confirmed to enrich cholesterol in the plasma membrane, contributing to collateral resistance through the Hedgehog-ABCB1 axis. As a driver for cholesterol, Cdc42 is activated by the formation of the NPC1-TβRI-Cdc42 complex to facilitate endosomal cholesterol transport. We demonstrated that inhibiting Cdc42 activation with ZCL278 reduces cholesterol levels in the plasma membrane and reverses collateral resistance between trastuzumab and chemotherapy in vitro and in vivo. Collectively, our findings verify the phenomena and mechanism of collateral resistance between trastuzumab and chemotherapy, and propose a potential therapeutic target and strategy in the second-line treatment for trastuzumab-resistant HER2-positive GC.

GDF10 and IDO1 as a thyroid cancer prognostic biomarker associated with immune infiltration

Objection

The aim of this work is to screen the immune-related genes to predict the prognosis and provide a new direction of treatment for patients with thyroid cancer (THCA).

Methods

The mRNA and clinical features of THCA patients were collected from the Cancer Genome Atlas (TCGA) databases. The immune-related genes were obtained from the ImmPort databases. The bio-information methods were performed to screen the differential expression genes (DEGs) and genes related to immunity between the THCA patients and normal individuals. On this basis, the hub prognosis immunity genes were screened by Veen. The related genes were obtained by constructing the protein-protein interaction network. The enrichment analyses were performed based on the protein and protein interaction (PPI) related genes. The hub immune checkpoint was screened by correlation analysis. Finally, the hub gene and the immunity checkpoint-miRNA (or transcription factor, drug) interaction network were constructed. A drug-sensitive analysis also was performed.

Results

The GDF10 was screened. The PPI genes were enriched in the TGF-beta signaling pathway, signaling pathways regulating, the pluripotency of stem cells, Cytokine-cytokine receptor interaction, and so on. The hub immunity checkpoint IDO1 was obtained. The joint indicator of two hub genes was positively related to the thyroid differentiation score. Three interaction factors were found to be related to the two hub genes, and 7 kinds of drugs screened act on the two hub genes at the same time.

Conclusion

This work indicated that immune-related gene GDF10 and immune checkpoint IDO1 are important for the prognosis prediction of THCA patients, and immunity is involved in the proliferation, and differentiation of tumor cells.

Copper-binding protein modelling by single-cell transcriptome and Bulk transcriptome to predict overall survival in lung adenocarcinoma patients

Background: Copper and copper-binding proteins are key components of tumour progression as they play an important role in tumour invasion and migration, and abnormal accumulation of copper (Cu) may be intimately linked to with lung adenocarcinoma (LUAD). Methods: Data on lung adenocarcinoma were sourced from the Cancer Genome Atlas (TCGA) database and the National Centre for Biotechnology Information (GEO). 10x scRNA sequencing, which is from Bischoff P et al, was used for down-sequencing clustering and subgroup identification using TSNE. The genes for Copper-binding proteins (CBP) were acquired from the MSigDB database. LASSO-Cox analysis was subsequently used to construct a model for copper-binding proteins (CBPRS), which was then compared to lung adenocarcinoma models developed by others. External validation was carried out in the GSE31210 and GSE50081 cohorts. The effectiveness of immunotherapy was evaluated using the TIDE algorithm and the IMvigor210, GSE78220, and TCIA cohorts. Furthermore, differences in mutational profiles and the immune microenvironment between different risk groups were investigated. The CBPRS's key regulatory genes were screened using ROC diagnostic and KM survival curves. The differential expression of these genes was then verified by RT-qPCR. Results: The six CBP genes were identified as highly predictive of LUAD prognosis and significantly correlated with it. Multivariate analysis showed that patients in the low-risk group had a higher overall survival rate than those in the high-risk group, indicating that the model was an independent predictor of LUAD. The CBPRS demonstrated superior predictive ability compared to 11 previously published models. We constructed a column-line graph that includes CBPRS and clinical characteristics, which exhibits high predictive performance. Additionally, we observed significant differences in biological functions, mutational landscapes, and immune cell infiltration in the tumour microenvironment between the high-risk and low-risk groups. It is noteworthy that immunotherapy was also significant in both the high- and low-risk groups. These results suggest that the model has good predictive efficacy. Conclusions: The CBP model demonstrated good predictive performance, revealing characteristics of the tumour microenvironment. This provides a new method for assessing the efficacy of pre-immunisation and offers a potential strategy for future treatment of lung adenocarcinoma.

Unraveling the role of M1 macrophage and CXCL9 in predicting immune checkpoint inhibitor efficacy through multicohort analysis and single-cell RNA sequencing

The exact function of M1 macrophages and CXCL9 in forecasting the effectiveness of immune checkpoint inhibitors (ICIs) is still not thoroughly investigated. We investigated the potential of M1 macrophage and C-X-C Motif Chemokine Ligand 9 (CXCL9) as predictive markers for ICI efficacy, employing a comprehensive approach integrating multicohort analysis and single-cell RNA sequencing. A significant correlation between high M1 macrophage and improved overall survival (OS) and objective response rate (ORR) was found. M1 macrophage expression was most pronounced in the immune-inflamed phenotype, aligning with increased expression of immune checkpoints. Furthermore, CXCL9 was identified as a key marker gene that positively correlated with M1 macrophage and response to ICIs, while also exhibiting associations with immune-related pathways and immune cell infiltration. Additionally, through exploring RNA epigenetic modifications, we identified Apolipoprotein B MRNA Editing Enzyme Catalytic Subunit 3G (APOBEC3G) as linked to ICI response, with high expression correlating with improved OS and immune-related pathways. Moreover, a novel model based on M1 macrophage, CXCL9, and APOBEC3G-related genes was developed using multi-level attention graph neural network, which showed promising predictive ability for ORR. This study illuminates the pivotal contributions of M1 macrophages and CXCL9 in shaping an immune-active microenvironment, correlating with enhanced ICI efficacy. The combination of M1 macrophage, CXCL9, and APOBEC3G provides a novel model for predicting clinical outcomes of ICI therapy, facilitating personalized immunotherapy.

Identification of T-cell exhaustion-related genes and prediction of their immunotherapeutic role in lung adenocarcinoma

Background: Lung adenocarcinoma ranks as the second most widespread form of cancer globally, accompanied by a significant mortality rate. Several studies have shown that T cell exhaustion is associated with immunotherapy of tumours. Consequently, it is essential to comprehend the possible impact of T cell exhaustion on the tumor microenvironment. The purpose of this research was to create a TEX-based model that would use single-cell RNA-seq (scRNA-seq) and bulk-RNA sequencing to explore new possibilities for assessing the prognosis and immunotherapeutic response of LUAD patients. Methods: RNA-seq data from LUAD patients was downloaded from the Cancer Genome Atlas (TCGA) database and the National Center for Biotechnology Information (GEO). 10X scRNA sequencing data, as reported by Bischoff P et al., was utilized for down-sampling clustering and subgroup identification using TSNE. TEX-associated genes were identified through gene set variance analysis (GSVA) and weighted gene correlation network analysis (WGCNA). We utilized LASSO-Cox analysis to establish predicted TEX features. External validation was conducted in GSE31210 and GSE30219 cohorts. Immunotherapeutic response was assessed in IMvigor210, GSE78220, GSE35640 and GSE100797 cohorts. Furthermore, we investigated differences in mutational profiles and immune microenvironment between various risk groups. We then screened TEXRS key regulatory genes using ROC diagnostic curves and KM survival curves. Finally, we verified the differential expression of key regulatory genes through RT-qPCR. Results: Nine TEX genes were identified as highly predictive of LUAD prognosis and strongly correlated with disease outcome. Univariate and multivariate analysis revealed that patients in the low-risk group had significantly better overall survival rates compared with those in the high-risk group, highlighting the model's ability to independently predict LUAD prognosis. Our analysis revealed significant variation in the biological function, mutational landscape, and immune cell infiltration within the tumor microenvironment of both high-risk and low-risk groups. Additionally, immunotherapy was found to have a significant impact on both groups, indicating strong predictive efficacy of the model. Conclusions: The TEX model showed good predictive performance and provided a new perspective for evaluating the efficacy of preimmunization, which provides a new strategy for the future treatment of lung adenocarcinoma.

Update on current and new potential immunotherapies in breast cancer, from bench to bedside

Impressive advances have been seen in cancer immunotherapy during the last years. Although breast cancer (BC) has been long considered as non-immunogenic, immunotherapy for the treatment of BC is now emerging as a new promising therapeutic approach with considerable potential. This is supported by a plethora of completed and ongoing preclinical and clinical studies in various types of immunotherapies. However, a significant gap between clinical oncology and basic cancer research impairs the understanding of cancer immunology and immunotherapy, hampering cancer therapy research and development. To exploit the accumulating available data in an optimal way, both fundamental mechanisms at play in BC immunotherapy and its clinical pitfalls must be integrated. Then, clinical trials must be critically designed with appropriate combinations of conventional and immunotherapeutic strategies. While there is room for major improvement, this updated review details the immunotherapeutic tools available to date, from bench to bedside, in the hope that this will lead to rethinking and optimizing standards of care for BC patients.

Targeting metabolic sensing switch GPR84 on macrophages for cancer immunotherapy

INTRODUCTION

As one of the major components of the tumor microenvironment, tumor-associated macrophages (TAMs) possess profound inhibitory activity against T cells and facilitate tumor escape from immune checkpoint blockade therapy. Converting this pro-tumorigenic toward the anti-tumorigenic phenotype thus is an important strategy for enhancing adaptive immunity against cancer. However, a plethora of mechanisms have been described for pro-tumorigenic differentiation in cancer, metabolic switches to program the anti-tumorigenic property of TAMs are elusive.

MATERIALS AND METHODS

From an unbiased analysis of single-cell transcriptome data from multiple tumor models, we discovered that anti-tumorigenic TAMs uniquely express elevated levels of a specific fatty acid receptor, G-protein-coupled receptor 84 (GPR84). Genetic ablation of GPR84 in mice leads to impaired pro-inflammatory polarization of macrophages, while enhancing their anti-inflammatory phenotype. By contrast, GPR84 activation by its agonist, 6-n-octylaminouracil (6-OAU), potentiates pro-inflammatory phenotype via the enhanced STAT1 pathway. Moreover, 6-OAU treatment significantly retards tumor growth and increases the anti-tumor efficacy of anti-PD-1 therapy.

CONCLUSION

Overall, we report a previously unappreciated fatty acid receptor, GPR84, that serves as an important metabolic sensing switch for orchestrating anti-tumorigenic macrophage polarization. Pharmacological agonists of GPR84 hold promise to reshape and reverse the immunosuppressive TME, and thereby restore responsiveness of cancer to overcome resistance to immune checkpoint blockade.

Prognostic stratification of sepsis through DNA damage response based RiskScore system: insights from single-cell RNA-sequencing and transcriptomic profiling

Background

A novel risk scoring system, predicated on DNA damage response (DDR), was developed to enhance prognostic predictions and potentially inform the creation of more effective therapeutic protocols for sepsis.

Methods

To thoroughly delineate the expression profiles of DDR markers within the context of sepsis, an analytical approach utilizing single-cell RNA-sequencing (scRNA-seq) was implemented. Our study utilized single-cell analysis techniques alongside weighted gene co-expression network analysis (WGCNA) to pinpoint the genes that exhibit the most substantial associations with DNA damage response (DDR). Through Cox proportional hazards LASSO regression, we distinguished DDR-associated genes and established a risk model, enabling the stratification of patients into high- and low-risk groups. Subsequently, we carried out an analysis to determine our model's predictive accuracy regarding patient survival. Moreover, we examined the distinct biological characteristics, various signal transduction routes, and immune system responses in sepsis patients, considering different risk categories and outcomes related to survival. Lastly, we conducted experimental validation of the identified genes through in vivo and in vitro assays, employing RT-PCR, ELISA, and flow cytometry.

Results

Both single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic analyses have demonstrated a strong correlation between DNA damage response (DDR) levels and sepsis prognosis. Specific cell subtypes, including monocytes, megakaryocytes, CD4+ T cells, and neutrophils, have shown elevated DDR activity. Cells with increased DDR scores exhibited more robust and numerous interactions with other cell populations. The weighted gene co-expression network analysis (WGCNA) and single-cell analyses revealed 71 DDR-associated genes. We developed a four-gene risk scoring system using ARL4C, CD247, RPL7, and RPL31, identified through univariate COX, LASSO COX regression, and log-rank (Mantel-Cox) tests. Nomograms, calibration plots, and decision curve analyses (DCA) regarding these specific genes have provided significant clinical benefits for individuals diagnosed with sepsis. The study suggested that individuals categorized as lower-risk demonstrated enhanced infiltration of immune cells, upregulated expression of immune regulators, and a more prolific presence of immune-associated functionalities and pathways. RT-qPCR analyses on a sepsis rat model revealed differential gene expression predominantly in the four targeted genes. Furthermore, ARL4C knockdown in sepsis model in vivo and vitro caused increased inflammatory response and a worse prognosis.

Conclusion

The delineated DDR expression landscape offers insights into sepsis pathogenesis, whilst our riskScore model, based on a robust four-gene signature, could underpin personalized sepsis treatment strategies.

Development of a stemness-related prognostic index to provide therapeutic strategies for bladder cancer

Bladder cancer (BC) is a heterogeneous disease with varying clinical outcomes. Recent evidence suggests that cancer progression involves the acquisition of stem-like signatures, and assessing stemness indices help uncover patterns of intra-tumor molecular heterogeneity. We used the one-class logistic regression algorithm to compute the mRNAsi for each sample in BLCA cohort. We subsequently classified BC patients into two subtypes based on 189 mRNAsi-related genes, using the unsupervised consensus clustering. Then, we identified nine hub genes to construct a stemness-related prognostic index (SRPI) using Cox regression, LASSO regression and Random Forest methods. We further validated SRPI using two independent datasets. Afterwards, we examined the molecular and immune characterized of SRPI. Finally, we conducted multiply drug screening and experimental approaches to identify and confirm the most proper agents for patients with high SRPI. Based on the mRNAsi-related genes, BC patients were classified into two stemness subtypes with distinct prognosis, functional annotations, genomic variations and immune profiles. Using the SRPI, we identified a specific subgroup of BC patients with high SRPI, who had a poor response to immunotherapy, and were less sensitive to commonly used chemotherapeutic agents, FGFR inhibitors, and EGFR inhibitors. We further identified that dasatinib was the most promising therapeutic agent for this subgroup of patients. This study provides further insights into the stemness classification of BC, and demonstrates that SRPI is a promising tool for predicting prognosis and therapeutic opportunities for BC patients.

Classification of bladder cancer based on immune cell infiltration and construction of a risk prediction model for prognosis

OBJECTIVES

To classify bladder cancer based on immune cell infiltration score and to construct a prognosis assessment model of patients with bladder cancer.

METHODS

The transcriptome data and clinical data of breast cancer patients were obtained from the The Cancer Genome Atlas (TCGA) database. Single sample gene set enrichment analysis was used to calculate the infiltration scores of 16 immune cells. The classification of breast cancer patients was achieved by unsupervised clustering, and the sensitivity of patients with different types to immunotherapy and chemotherapy was analyzed. The key modules significantly related to the infiltration of key immune cells were identified by weighted correlation network analysis (WGCNA), and the key genes in the modules were identified. A risk scoring model and a nomogram for prognosis assessment of bladder cancer patients were constructed and verified.

RESULTS

B cells, mast cells, neutrophils, T helper cells and tumor infiltrating lymphocytes were determined to be the key immune cells of bladder cancer. The patients were clustered into two groups (Cluster 1 ´ and Custer 2) based on immune cell infiltration scores. Compared with patients with Cluster 1 ´, patients with Cluster 2 were more likely to benefit from immunotherapy (P<0.05), and patients with Cluster 2 were more sensitive to Enbeaten, Docetaxel, Cyclopamine, and Akadixin (P<0.05). 35 genes related to key immune cells were screened out by WGCNA and 4 genes (GPR171, HOXB3, HOXB5 and HOXB6) related to the prognosis of bladder cancer were further screened by LASSO Cox regression. The areas under the ROC curve (AUC) of the bladder cancer prognosis risk scoring model based on these 4 genes to predict the 1-, 3- and 5-year survival of patients were 0.735, 0.765 and 0.799, respectively. The nomogram constructed by combining risk score and clinical parameters has high accuracy in predicting the 1-, 3-, and 5-year overall survival of bladder cancer patients.

CONCLUSIONS

According to the immune cell infiltration score, bladder cancer patients can be classified. Furthermore, bladder cancer prognosis risk scoring model and nomogram based on key immune cell-related genes have high accuracy in predicting the prognosis of bladder cancer patients.

A novel m7G regulator-based methylation patterns in head and neck squamous cell carcinoma

Abnormal RNA N7-methylguanosine (m7G) modification is known to contribute to effects on tumor occurrence and development. Nevertheless, the mechanisms of its function in immunoregulation, tumor microenvironment (TME) modulation, and tumor promotion remain largely unknown. A series of computer-aided bioinformatic analyses were conducted based on transcriptomic, single-cell sequence, and spatial transcriptomic data to determine the m7G modification patterns in head and neck squamous cell carcinoma (HNSCC). Consensus clustering approach was employed according to the expressions of 33 m7G regulators. ESTIMATE, CIBERSORT, and single sample gene set enrichment analysis algorithms were adopted to investigate the immune cell infiltration features. A prognostic model named m7Gscore was established. Seurat, SingleR, and Monocle2 were used to analyze the single-cell sequence profiling. STUtility was used to integrate multiple spatial transcriptomic datasets. Quantitative reverse transcription polymerase chain reaction, transwell, and wound-healing assay were performed to verify the oncogenes. Here, three different m7G modification patterns were highlighted in HNSCC patients, which were also related to various clinical manifestations and three representative immunophenotypes: immune-excluded, immune-desert, and inflamed, separately. Patients with lower m7Gscore were highlighted by higher immune cell infiltrations, better overall survival rates, lesser tumor mutation burden (TMB), lower sensitivities to target inhibitors therapies, and better immunotherapeutic response. Moreover, DCPS, EIF4E, EIF4E2, LSM1, NCBP2, NUDT1, and NUDT5 were identified to play critical roles in T-cell differentiation. Knockdown of LSM1/NUDT5 could restrain the malignancy of HNSCC cells. Collectively, quantitative assessment of m7G modification patterns in individual HNSCC patients could contribute to identifying more efficient immunotherapeutic approaches and improve the clinical outcome of HNSCC.

Tumor microenvironment heterogeneity in bladder cancer identifies biologically distinct subtypes predicting prognosis and anti-PD-L1 responses

Bladder cancer (BCa) is heterogeneous in the tumour microenvironment (TME). However, the role of the TME in BCa in modulating the response to immunotherapy has not been fully explored. We therefore analysed fractions of immune cells using CIBERSORTx and clustered BCa into subtypes. We also analyzed weighted correlation networks to generate immunotherapy-related hub genes that we used to construct a prediction model using multivariate Cox and LASSO regression analyses. We found that BCa comprised three subtypes (C1‒C3). The prognosis of the patients was the most favourable and the response rate to anti-programmed death ligand 1 (PD-L1) was the highest in C1 among the three subtypes. Immune cells, including CD8+, CD4+ memory activated, and follicular helper T cells, activated NK cells, and M1 macrophages infiltrated the C1 subtype. The C2 subtype was enriched in M0 macrophages and activated mast cells, and the C3 subtype was enriched in B and resting immune cells. Mechanistically, the enhanced immunogenicity of subtypes C1 and C2 correlated positively with a higher response rate, whereas the dysregulated ECM-related pathways in the C2 subtype and glycolytic and fatty acid metabolic pathways in the C3 subtype impaired the responses of patients to anti-PD-L1 therapy. We also constructed a TME-related signature based on 18 genes that performed well in terms of overall survival. In conclusion, we determined prognoses and anti-PD-L1 responses by analysing TME heterogeneity in BCa.

The therapeutic potential of PD-1/PD-L1 pathway on immune-related diseases: Based on the innate and adaptive immune components

Currently, immunotherapy targeting programmed cell death 1 (PD-1) or programmed death ligand 1 (PD-L1) has revolutionized the treatment strategy of human cancer patients. Meanwhile, PD-1/PD-L1 pathway has also been implicated in the pathogenesis of many immune-related diseases, such as autoimmune diseases, chronic infection diseases and adverse pregnancy outcomes, by regulating components of the innate and adaptive immune systems. Given the power of the new therapy, a better understanding of the regulatory effects of PD-1/PD-L1 pathway on innate and adaptive immune responses in immune-related diseases will facilitate the discovery of novel biomarkers and therapeutic drug targets. Targeting this pathway may successfully halt or potentially even reverse these pathological processes. In this review, we discuss recent major advances in PD-1/PD-L1 axis regulating innate and adaptive immune components in immune-related diseases. We reveal that the impact of PD-1/PD-L1 axis on the immune system is complex and manifold and multi-strategies on the targeted PD-1/PD-L1 axis are taken in the treatment of immune-related diseases. Consequently, targeting PD-1/PD-L1 pathway, alone or in combination with other treatments, may represent a novel strategy for future therapeutic intervention on immune-related diseases.

Pan-cancer analysis identifies RNF43 as a prognostic, therapeutic and immunological biomarker

BACKGROUND

RING finger protein 43 (RNF43), an E3 ubiquitin ligase, is a homologous gene mutated in several cancers. However, the pan-cancer panoramic picture of RNF43 and its predictive value for tumor immune phenotypes and immunotherapeutic efficacy are still largely unclear. Our study aims to clarify the functions of RNF43 in predicting the prognosis, immune signature, and immunotherapeutic efficacy in pan-cancer.

METHODS

By using RNA-seq, mutation, and clinical data from the TCGA database, the expression levels and prognostic significance of RNF43 in pan-cancer were analyzed. The genetic alteration characteristics of RNF43 were displayed by the cBioPortal database. Gene Set Enrichment Analysis (GSEA) was performed to investigate the potential biological functions and signaling pathways modulated by RNF43 in cancers. The relationship of RNF43 expression with immune cell infiltration, and immune modulators expression was interpreted by the ESTIMATE algorithm, CIBERSORT algorithm, and TISIDB database. The correlations between RNF43, microsatellite instability (MSI), and tumor mutation burden (TMB) were also investigated. Furthermore, the predictive value of RNF43 for immunotherapeutic efficacy and drug sensitivity was further illustrated. Besides, immunohistochemistry (IHC) was employed to validate the expression of the RNF43 in different cancer types by our clinical cohorts, including patients with lung cancer, sarcoma, breast cancer, and kidney renal clear cell carcinoma.

RESULTS

The results demonstrated that RNF43 was abnormally expressed in multiple cancers, and RNF43 is a critical prognosis-related factor in several cancers. RNF43 was frequently mutated in several cancers with a high frequency of 4%, and truncating mutation was the most frequent RNF43 mutation type. RNF43 expression was linked to the abundance of several immune cell types, including CD8+ T cells, B cells, and macrophages within the tumor immune microenvironment. Furthermore, RNF43 expression was significantly correlated with the efficacy of anti-PD-1/PD-L1 treatment, and it could predict the sensitivity of various anti-cancer drugs. Finally, IHC explored and validated the different expression levels of RNF43 in different cancers by our clinical samples.

CONCLUSION

Our results first present the expression pattern and the mutation signature of RNF43, highlighting that RNF43 is an important prognostic biomarker in pan-cancer. Furthermore, RNF43 seems to be a critical modulator in the tumor immune microenvironment and can function as a promising biomarker for predicting the immunotherapeutic efficacy of anti-PD-1/PD-L1 treatment, and drug sensitivity in cancer treatment.

Phase II trial of hypomethylating agent combined with nivolumab for acute myeloid leukaemia relapse after allogeneic haematopoietic cell transplantation-Immune signature correlates with response

Acute myeloid leukaemia (AML) relapse after allogeneic haematopoietic cell transplantation (allo-HCT) is often driven by immune-related mechanisms and associated with poor prognosis. Immune checkpoint inhibitors combined with hypomethylating agents (HMA) may restore or enhance the graft-versus-leukaemia effect. Still, data about using this combination regimen after allo-HCT are limited. We conducted a prospective, phase II, open-label, single-arm study in which we treated patients with haematological AML relapse after allo-HCT with HMA plus the anti-PD-1 antibody nivolumab. The response was correlated with DNA-, RNA- and protein-based single-cell technology assessments to identify biomarkers associated with therapeutic efficacy. Sixteen patients received a median number of 2 (range 1-7) nivolumab applications. The overall response rate (CR/PR) at day 42 was 25%, and another 25% of the patients achieved stable disease. The median overall survival was 15.6 months. High-parametric cytometry documented a higher frequency of activated (ICOS+ , HLA-DR+ ), low senescence (KLRG1- , CD57- ) CD8+ effector T cells in responders. We confirmed these findings in a preclinical model. Single-cell transcriptomics revealed a pro-inflammatory rewiring of the expression profile of T and myeloid cells in responders. In summary, the study indicates that the post-allo-HCT HMA/nivolumab combination induces anti-AML immune responses in selected patients and could be considered as a bridging approach to a second allo-HCT. Trial-registration: EudraCT-No. 2017-002194-18.

Case Report: Complete pathological remission of human chorionic gonadotrophin-producing gallbladder carcinoma with multiple liver metastases after treatment with chemotherapy plus an immune checkpoint inhibitor

Background

Gallbladder carcinoma (GBC) producing human chorionic gonadotrophin (HCG) is an extremely rare and highly invasive tumor with a poor prognosis. This unfavorable clinical outcome is partly due to the aggressive nature of the tumor and its insensitivity to chemotherapy.

Case presentation

We herein report a case of primary GBC producing HCG with liver metastases in a 58-year-old woman. The patient presented with a markedly elevated β-HCG level and a mass in the gallbladder with multiple liver metastases. A definitive diagnosis was obtained after a needle biopsy of the liver metastases, showing poorly differentiated carcinoma with large-scale necrosis and strong positivity of immunostaining for HCG in tumor cells. The patient received chemotherapy (gemcitabine plus capecitabine) combined with carrellizumab, an immune checkpoint inhibitor (ICI). Pathological complete response was achieved after eight courses of combined therapy, which was confirmed by pathological analysis of resected specimens. After surgery, two courses of chemotherapy plus ICIs were adopted again. Complete response remained for approximately 1 year up to the present. Tumor tissue was collected to perform immunostaining of PD-L1, whole-exome sequencing, and RNA-seq. Low-TMB (1.51 mut/Mb), MSS, and high PD-L1 expression (TPS ≥ 50%) were observed in the tumor. Besides, the dominant types of infiltrating immune cells were macrophage and CD4+ T cells. Compared to other gallbladder adenocarcinoma without HCG, the proportion of M1 macrophage was at a higher level and the gene sets of MYC targets v1 and PI3K/AKT/mTOR signaling were highly expressed in our case. To the best of our knowledge, this is the first case report of complete remission of HCG-producing gallbladder carcinoma with liver metastases after chemotherapy combined with an immune checkpoint inhibitor. Furthermore, this is also the first report that described the tumor genetic feature and tumor immune microenvironment atlas of HCG-producing GBC.

Conclusion

chemotherapy plus an immune checkpoint inhibitor may provide a potentially curative option for gallbladder carcinoma with HCG production.

Investigating the potential mechanism of quercetin against cervical cancer

BACKGROUND

Cervical cancer is emerging as a potential target of increased susceptibility to coronavirus disease-2019 (COVID-19), leading to compromised survival rates. Despite this critical link, efficacious anti-cervical cancer/COVID-19 interventions remain limited. Quercetin, known for its efficacy against both cancer and viral infections, holds promise as a therapeutic agent. This study aims to elucidate quercetin's anti-cervical cancer/COVID-19 mechanisms and potential targets.

METHODS

We initiated our investigation with differential gene expression analysis using cervical cancer transcriptome data from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx), focusing on intersections with COVID-19-related genes. Network pharmacology was employed to identify the shared targets between cervical cancer/COVID-19 DEGs and quercetin's targets. Subsequently, Cox proportional hazards analyses were employed to establish a risk score based on these genes. Molecular docking techniques were applied to predict quercetin's therapeutic targets and mechanisms for mitigating cervical cancer and COVID-19.

RESULTS

Our findings unveiled 45 potential quercetin targets with anti-cervical cancer/COVID-19 actions. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses highlighted significant enrichment in immune pathways and COVID-19-related pathways. A refined risk score model, comprising PLA2G7, TNF, TYK2, F2, and NRP1, effectively stratified cervical cancer patients into distinct risk groups. Importantly, molecular docking analyses illuminated quercetin's remarkable binding affinity to the primary protease of the coronavirus.

CONCLUSIONS

In summation, our study suggests that quercetin holds promise as a potential therapeutic agent for mitigating coronavirus function, specifically through its interaction with the primary protease. This research offers novel insights into exploring COVID-19 susceptibility and enhancing survival in cervical cancer patients.

Integrated multiomics analysis and machine learning refine molecular subtypes and prognosis for muscle-invasive urothelial cancer

Muscle-invasive urothelial cancer (MUC), characterized by high aggressiveness and significant heterogeneity, is currently lacking highly precise individualized treatment options. We used a computational pipeline to synthesize multiomics data from MUC patients using 10 clustering algorithms, which were then combined with 10 machine learning algorithms to identify molecular subgroups of high resolution and develop a robust consensus machine learning-driven signature (CMLS). Through multiomics clustering, we identified three cancer subtypes (CSs) that are related to prognosis, with CS2 exhibiting the most favorable prognostic outcome. Subsequent screening enabled identification of 12 hub genes that constitute a CMLS with robust predictive power for prognosis. The low-CMLS group exhibited a more favorable prognosis and greater responsiveness to immunotherapy and was more likely to exhibit the "hot tumor" phenotype. The high-CMLS group had a poor prognosis and lower likelihood of benefitting from immunotherapy, but dasatinib and romidepsin may serve as promising treatments for them. Comprehensive analysis of multiomics data can offer important insights and further refine the molecular classification of MUC. Identification of CMLS represents a valuable tool for early prediction of patient prognosis and for screening potential candidates likely to benefit from immunotherapy, with broad implications for clinical practice.

Development and validation of a kidney renal clear cell carcinoma prognostic model relying on pyroptosis-related LncRNAs-A multidimensional comprehensive bioinformatics exploration

BACKGROUND

Renal cell carcinoma (RCC) is a malignant tumour that may develop in the kidney. RCC is one of the most common kinds of tumours of this sort, and its most common pathological subtype is kidney renal clear cell carcinoma (KIRC). However, the aetiology and pathogenesis of RCC still need to be clarified. Exploring the internal mechanism of RCC contributes to diagnosing and treating this disease. Pyroptosis is a critical process related to cell death. Recent research has shown that pyroptosis is a critical factor in the initiation and progression of tumour formation. Thus far, researchers have progressively uncovered evidence of the regulatory influence that long noncoding RNAs (lncRNAs) have on pyroptosis.

METHODS

In this work, a comprehensive bioinformatics approach was used to produce a predictive model according to pyroptosis-interrelated lncRNAs for the purpose of predicting the overall survival and molecular immune specialties of patients diagnosed with KIRC. This model was verified from multiple perspectives.

RESULTS

First, we discovered pyroptosis-associated lncRNAs in KIRC patients using the TCGA database and a Sankey diagram. Then, we developed and validated a KIRC patient risk model based on pyroptosis-related lncRNAs. We demonstrated the grouping power of PLnRM through PCA and used PLnRM to assess the tumour immune microenvironment and response to immunotherapy. Immunological and molecular traits of diverse PLnRM subgroups were evaluated, as were clinical KIRC patient characteristics and predictive risk models. On this basis, a predictive nomogram was developed and analyzed, and novel PLnRM candidate compounds were identified. Finally, we investigated possible medications used by KIRC patients.

CONCLUSIONS

The results demonstrate that the model generated has significant value for KIRC in clinical practice.

Adhesion-regulating molecule 1 (ADRM1) can be a potential biomarker and target for bladder cancer

Adhesion-regulating molecule 1 (ADRM1) has been implicated in tumor development, yet its specific role in bladder cancer (BC) remains undefined. This study aimed to elucidate the function of ADRM1 in BC through a combination of bioinformatics analysis and immunohistochemical analysis (IHC). Utilizing R version 3.6.3 and relevant packages, we analyzed online database data. Validation was conducted through IHC data, approved by the Institutional Ethics Committee (Approval No. K20220830). In both paired and unpaired comparisons, ADRM1 expression was significantly elevated in BC tissues compared to adjacent tissues, as evidenced by the results of TCGA dataset and IHC data. Patients with high ADRM1 expression had statistically worse overall survival than those with low ADRM1 expression in TCGA dataset, GSE32548 dataset, GSE32894 dataset, and IHC data. Functional analysis unveiled enrichment in immune-related pathways, and a robust positive correlation emerged between ADRM1 expression and pivotal immune checkpoints, including CD274, PDCD1, and PDCD1LG2. In tumor microenvironment, samples with the high ADRM1 expression contained statistical higher proportion of CD8 + T cells and Macrophage infiltration. Meanwhile, these high ADRM1-expressing samples displayed elevated tumor mutation burden scores and stemness indices, implying potential benefits from immunotherapy. Patients with low ADRM1 expression were sensitive to cisplatin, docetaxel, vinblastine, mitomycin C, and methotrexate. According to the findings from bioinformatics and IHC analyses, ADRM1 demonstrates prognostic significance for BC patients and holds predictive potential for both immunotherapy and chemotherapy responses. This underscores its role as a biomarker and therapeutic target in BC.

Characterization of the metabolic alteration-modulated tumor microenvironment mediated by TP53 mutation and hypoxia

BACKGROUND

TP53 mutation and hypoxia play an essential role in cancer progression. However, the metabolic reprogramming and tumor microenvironment (TME) heterogeneity mediated by them are still not fully understood.

METHODS

The multi-omics data of 32 cancer types and immunotherapy cohorts were acquired to comprehensively characterize the metabolic reprogramming pattern and the TME across cancer types and explore immunotherapy candidates. An assessment model for metabolic reprogramming was established by integration of multiple machine learning methods, including lasso regression, neural network, elastic network, and survival support vector machine (SVM). Pharmacogenomics analysis and in vitro assay were conducted to identify potential therapeutic drugs.

RESULTS

First, we identified metabolic subtype A (hypoxia-TP53 mutation subtype) and metabolic subtype B (non-hypoxia-TP53 wildtype subtype) in hepatocellular carcinoma (HCC) and showed that metabolic subtype A had an "immune inflamed" microenvironment. Next, we established an assessment model for metabolic reprogramming, which was more effective compared to the traditional prognostic indicators. Then, we identified a potential targeting drug, teniposide. Finally, we performed the pan-cancer analysis to illustrate the role of metabolic reprogramming in cancer and found that the metabolic alteration (MA) score was positively correlated with tumor mutational burden (TMB), neoantigen load, and homologous recombination deficiency (HRD) across cancer types. Meanwhile, we demonstrated that metabolic reprogramming mediated a potential immunotherapy-sensitive microenvironment in bladder cancer and validated it in an immunotherapy cohort.

CONCLUSION

Metabolic alteration mediated by hypoxia and TP53 mutation is associated with TME modulation and tumor progression across cancer types. In this study, we analyzed the role of metabolic alteration in cancer and propose a predictive model for cancer prognosis and immunotherapy responsiveness. We also explored a potential therapeutic drug, teniposide.

Association of ERCC family mutations with prognosis and immune checkpoint inhibitors response in multiple cancers

The proteins encoded by the excision repair cross-complementing (ERCC) family are pivotal in DNA damage repair and maintaining genome stability. However, the precise role of the ERCC family in tumor prognosis and the effectiveness of immune checkpoint inhibitors (ICI) therapy remain uncertain. This study aimed to explore the connection between ERCC mutations and prognosis as well as the response to ICI. We observed that patients with ERCC mutations exhibited enhanced progression-free survival (PFS) and overall survival (OS) in two independent pan-cancer cohorts. Furthermore, this mutant subgroup showed higher tumor mutation burden (TMB) compared to the wild-type subgroup. Notably, ERCC mutations were associated with better OS (HR 0.54, 95% CI 0.42-0.70; P < 0.001) in pan-cancer patients who underwent ICI therapy (N = 1661). These findings were validated in a separate cohort, where patients in the ERCC mutant subgroup demonstrated improved clinical outcomes (HR 0.56, 95% CI 0.37-0.84; P = 0.03) and higher response rates (51.9% vs. 26.8%) than the wild-type subgroup. Further analysis revealed that patients with ERCC mutations displayed elevated tumor neoantigen burden (TNB) levels and increased infiltration of immune-response cells. Our study suggests that ERCC mutations are linked to enhanced immunogenicity and improved ICI efficacy, thus potentially serving as a biomarker for ICI therapy.

Therapeutic implications for localized prostate cancer by multiomics analyses of the ageing microenvironment landscape

Background: Numerous studies have substantiated the association between aging and the progression of malignant tumors in humans, notably prostate cancer (PCa). Nevertheless, to the best of our knowledge, no studies have comprehensively elucidated the intricate characteristics of the aging microenvironment (AME) in PCa. Methods: AME regulatory patterns were determined using the NMF algorithm. Then an ageing microenvironment index (AMI) was constructed, with excellent prognostic and immunotherapy prediction ability, and its' clinical relevance was surveyed through spatial transcriptomics. Further, the drug response was analysed using the Genomics of Drug Sensitivity in Cancer (GDSC), the Connectivity Map (CMap) and CellMiner database for patients with PCa. Finally, the AME was studied using in vitro and vivo experiments. Results: Three different AME regulatory patterns were identified across 813 PCa patients, associated with distinct clinical prognosis and physiological pathways. Based on the AMI, patients with PCa were divided into the high-score and low-score subsets. Higher AMI score was significantly infiltrated with more immune cells, higher rate of biochemical recurrence (BCR) and worse response to immunotherapy, antiandrogen therapy and chemotherapy in PCa. In addition, we found that the combination of bicalutamide and embelin was capable of suppressing tumor growth of PCa. Besides, as the main components of AMI, COL1A1 and BGLAP act as oncogenes and were verified via in vivo and in vitro experiments. Conclusions: AME regulation is significantly associated with the diversity and complexity of TME. Quantitative evaluation of the AME regulatory patterns may provide promising novel molecular markers for individualised therapy in PCa.

m5C regulator-mediated methylation modification phenotypes characterized by distinct tumor microenvironment immune heterogenicity in colorectal cancer

The RNA 5-methylcytosine (m5C) modification has been demonstrated to be an important epigenetic regulator and to impact colorectal cancer (CRC) progression. However, the potential roles of m5C modification in immune cell infiltration in the CRC tumor microenvironment (TME) remain unknown. The m5C modification phenotypes were comprehensively evaluated based on 14 m5C regulators in a meta-CRC cohort of 1792 patients and systematically correlated with the m5C modification phenotypes, immune cell infiltration characteristics and known biological processes. The m5Cscore model was constructed by principal component analysis (PCA) algorithms to quantify the m5C modification phenotypes of individual CRC samples and was used to predict the immunotherapy response. We identified three m5C modification phenotypes associated with distinct clinical outcomes and biological processes among the 1792 meta-CRC patients. Three phenotypes with a highly consistent TME landscape and characteristics were revealed: immune excluded, immune desert and immune inflammation. The meta-CRC patients were divided into high and low m5Cscore subgroups based on the m5Cscore. The m5Cscore was confirmed to have a negative correlation with infiltrating immune cells and PD-L1 expression and a positive correlation with tumor mutation burden (TMB), mutation rate and microsatellite instability (MSI) score. Moreover, patients in the low m5Cscore group had better immunotherapy responses and significant durable survival benefits in independent anti-PD-1/L1 immunotherapy cohorts for the immune checkpoint inhibitor (ICI) therapeutic strategy. This study revealed that m5C modification plays a crucial role in TME composition and complexity. Comprehensive evaluation of the m5C modification phenotypes of individual patients will enhance our understanding of TME characteristics and promote the application of more appropriate and personalized treatment strategies.

Case report: durable complete response to pembrolizumab plus lenvatinib in a metastatic upper tract urothelial carcinoma patient with high tumor mutational burden and an immune-active tumor microenvironment

Immune checkpoint inhibitors (ICIs) have been approved as an emerging first-line treatment option for advanced and metastatic urothelial carcinoma whose tumors express programmed death-ligand 1 (PD-L1). However, the efficacy of immunotherapy in PD-L1-negative urothelial carcinoma patients remains unclear, and biomarkers beyond PD-L1 expression to predict response to immunotherapy need investigation. Here, we report a metastatic renal pelvis urothelial carcinoma patient with PD-L1 negative expression that responded dramatically to first-line pembrolizumab plus lenvatinib. By the recent follow-up in March 2022, the patient had a complete radiological response for 3.4 years, with no recurrence even during the 23-month drug-withdrawal period. The results of the next-generation sequencing using the tumor sample revealed a high tumor mutational burden (TMB), which may be independently driven by the pathogenic mutation in TP53 , TERT , NCOR1 , and TSC2 genes. Besides, the tumor microenvironment exhibited an immune-active signature with relatively abundant CD8+ cells and M1 tumor-associated macrophages but scarce regulatory T cells may also explain the great benefit of the combination therapy. Our case provides a direction for identifying biomarkers beyond PD-L1 expression to screen urothelial carcinoma patients who benefit from ICI as well as ICI-based therapy.

ITGA3 acts as a purity-independent biomarker of both immunotherapy and chemotherapy resistance in pancreatic cancer: bioinformatics and experimental analysis

Contribution of integrin superfamily genes to treatment resistance remains uncertain. Genome patterns of thirty integrin superfamily genes were analyzed of using bulk and single-cell RNA sequencing, mutation, copy number, methylation, clinical information, immune cell infiltration, and drug sensitivity data. To select the integrins that are most strongly associated with treatment resistance in pancreatic cancer, a purity-independent RNA regulation network including integrins were constructed using machine learning. The integrin superfamily genes exhibit extensive dysregulated expression, genome alterations, epigenetic modifications, immune cell infiltration, and drug sensitivity, as evidenced by multi-omics data. However, their heterogeneity varies among different cancers. After constructing a three-gene (TMEM80, EIF4EBP1, and ITGA3) purity-independent Cox regression model using machine learning, ITGA3 was identified as a critical integrin subunit gene in pancreatic cancer. ITGA3 is involved in the molecular transformation from the classical to the basal subtype in pancreatic cancer. Elevated ITGA3 expression correlated with a malignant phenotype characterized by higher PD-L1 expression and reduced CD8+ T cell infiltration, resulting in unfavorable outcomes in patients receiving either chemotherapy or immunotherapy. Our findings suggest that ITGA3 is an important integrin in pancreatic cancer, contributing to chemotherapy resistance and immune checkpoint blockade therapy resistance.

Cuproptosis combines immune landscape providing prognostic biomarker in head and neck squamous carcinoma

Head and neck squamous carcinomas (HNSC) are the seventh most common cancer around the world. Treatment options available today have considerable limitations in terms of efficacy. Identifying novel therapeutic targets for HNSC is, therefore, urgently needed. As a novel determined regulated cell death (RCD), Cuproptosis is correlated with the development, treatment response, and prognosis of various cancer. However, the potential role of Cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) of HNSC remains unclear. To figure out whether TME cells and Cuproptosis could better predict prognosis, in this study, we analyzed the expression, mutation status, and other clinical information of 502 HNSC patients by dividing them into four clusters based on their CRGs and TME cell expression. Utilizing the LASSO-Cox method and bootstrap, we established Prognostic Cuproptosis and TME classifier, which were significantly associated with prognosis, pathways, clinical features, and immune cell infiltration in TME of HNSC. To go further, the subgroup Cup low/TMEhigh displayed a better prognosis than any others. Two GEO datasets demonstrated the proposed risk model's clinical applicability. Our GO enrichment analyses proved the conjoint effect of Cuproptosis and TME on tumor angiogenesis, proliferation, and so on. Single-cell analysis and Immunotherapy profile then provided a foundation for determining the molecular mechanisms. It revealed the prognostic risk score positively correlated with T cell activation and natural killer (NK) recruiting. As far as we know, this study is the first time to explore the involvement of CRGs regulation in the TME of HNSC. In a word, it is vital to use these findings to develop new therapeutic strategies.

The combined signatures of the tumour microenvironment and nucleotide metabolism-related genes provide a prognostic and therapeutic biomarker for gastric cancer

The tumour microenvironment (TME) is vital to tumour development and influences the immunotherapy response. Abnormal nucleotide metabolism (NM) not only promotes tumour cell proliferation but also inhibits immune responses in the TME. Therefore, this study aimed to determine whether the combined signatures of NM and the TME could better predict the prognosis and treatment response in gastric cancer (GC). 97 NM-related genes and 22 TME cells were evaluated in TCGA-STAD samples, and predictive NM and TME characteristics were determined. Subsequent correlation analysis and single-cell data analysis illustrated a link between NM scores and TME cells. Thereafter, NM and TME characteristics were combined to construct an NM-TME classifier. Patients in the NMlow/TMEhigh group exhibited better clinical outcomes and treatment responses, which could be attributed to the differences in immune cell infiltration, immune checkpoint genes, tumour somatic mutations, immunophenoscore, immunotherapy response rate and proteomap. Additionally, the NMhigh/TMElow group benefited more from Imatinib, Midostaurin and Linsitinib, while patients in the NMlow/TMEhigh group benefited more from Paclitaxel, Methotrexate and Camptothecin. Finally, a highly reliable nomogram was developed. In conclusion, the NM-TME classifier demonstrated a pretreatment predictive value for prognosis and therapeutic responses, which may offer novel strategies for strategizing patients with optimal therapies.

Identification and validation of tumor-infiltrating lymphocyte-related prognosis signature for predicting prognosis and immunotherapeutic response in bladder cancer

Background

It has been discovered that tumor-infiltrating lymphocytes (TILs) are essential for the emergence of bladder cancer (BCa). This study aimed to research TIL-related genes (TILRGs) and create a gene model to predict BCa patients' overall survival.

Methods

The RNA sequencing and clinical data were downloaded from the TGCA and GEO databases. Using Pearson correlation analysis, TILRGs were evaluated. Moreover, hub TILRGs were chosen using a comprehensive analysis. By dividing the TCGA-BCa patients into different clusters based on hub TILRGs, we were able to explore the immune landscape between different clusters.

Results

Here, we constructed a model with five hub TILRGs and split all of the patients into two groups, each of which had a different prognosis and clinical characteristics, TME, immune cell infiltration, drug sensitivity, and immunotherapy responses. Better clinical results and greater immunotherapy sensitivity were seen in the low-risk group. Based on five hub TILRGs, unsupervised clustering analysis identify two molecular subtypes in BCa. The prognosis, clinical outcomes, and immune landscape differed in different subtypes.

Conclusions

The study identifies a new prediction signature based on genes connected to tumor-infiltrating lymphocytes, providing BCa patients with a new theoretical target.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-023-05241-z.

Characterization of glycometabolism and tumor immune microenvironment for predicting clinical outcomes in gastric cancer

Recent evidence demonstrates that the reprogramming of energy metabolism can interact with the tumor immune microenvironment, thereby participating in the progression of cancer. In this study, multi-omics data of 2471 gastric cancer samples were used to identify tumor glycometabolism and its correlation with tumor immune microenvironment. A series of bioinformatic approaches were performed to establish a scoring system to predict the survival and response of chemotherapy and immunotherapy. Three glycometabolic subtypes and two immune clustering subgroups of gastric cancer were determined. We further established a Gluco-Immune Scoring system to quantify the cancer glycometabolic status and immune infiltration of individual patients. Patients with low Gluco-Immune Score were sensitive to adjuvant chemotherapy, while patients with high Gluco-Immune Score may benefit from immunotherapy. Our results indicate that in gastric cancer, the assessment of tumor glucose metabolism and immune microenvironment has application value for the prediction of curative effects and the formulation of combined treatment strategies.

A Comprehensive Analysis of Programmed Cell Death-Associated Genes for Tumor Microenvironment Evaluation Promotes Precise Immunotherapy in Patients with Lung Adenocarcinoma

Immune checkpoint inhibitors (ICIs) represent a new hot spot in tumor therapy. Programmed cell death has an important role in the prognosis. We explore a programmed cell death gene prognostic model associated with survival and immunotherapy prediction via computational algorithms. Patient details were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. We used LASSO algorithm and multiple-cox regression to establish a programmed cell death-associated gene prognostic model. Further, we explored whether this model could evaluate the sensitivity of patients to anti-PD-1/PD-L1. In total, 1342 patients were included. We constructed a programmed cell death model in TCGA cohorts, and the overall survival (OS) was significantly different between the high- and low-risk score groups (HR 2.70; 95% CI 1.94–3.75; p < 0.0001; 3-year OS AUC 0.71). Specifically, this model was associated with immunotherapy progression-free survival benefit in the validation cohort (HR 2.42; 95% CI 1.59–3.68; p = 0.015; 12-month AUC 0.87). We suggest that the programmed cell death model could provide guidance for immunotherapy in LUAD patients.

Liquid Biopsies, Novel Approaches and Future Directions

Cancer is among the leading causes of death worldwide. Early diagnosis and prognosis are vital to improve patients' outcomes. The gold standard of tumor characterization leading to tumor diagnosis and prognosis is tissue biopsy. Amongst the constraints of tissue biopsy collection is the sampling frequency and the incomplete representation of the entire tumor bulk. Liquid biopsy approaches, including the analysis of circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), circulating miRNAs, and tumor-derived extracellular vesicles (EVs), as well as certain protein signatures that are released in the circulation from primary tumors and their metastatic sites, present a promising and more potent candidate for patient diagnosis and follow up monitoring. The minimally invasive nature of liquid biopsies, allowing frequent collection, can be used in the monitoring of therapy response in real time, allowing the development of novel approaches in the therapeutic management of cancer patients. In this review we will describe recent advances in the field of liquid biopsy markers focusing on their advantages and disadvantages.

Prediction of immune infiltration and prognosis for patients with urothelial bladder cancer based on the DNA damage repair-related genes signature

Objectives

To analyze the correlations between the expression and effect of DNA damage repair genes and the immune status and clinical outcomes of urothelial bladder cancer (BLCA) patients. In addition, we evaluate the efficacy and value of utilizing the DNA damage repair genes signature as a prognosis model for BLCA.

Methods

Two subtype groups (C1 and C2) were produced based on the varied expression of DNA damage repair genes. Significantly differentiated genes and predicted enriched gene pathways were obtained between the two subtypes. Seven key genes were obtained from the DNA damage repair-related genes and a 7-gene signature prognosis model was established based on the key genes. The efficacy and accuracy of this model in prognosis prediction was evaluated and verified in two independent databases. Also, the difference in biological functions, drug sensitivity, immune infiltration and affinity between the high-risk group and low-risk group was analyzed.

Results

The DNA damage repair gene signature could significantly differentiate the BLCA into two molecular subgroups with varied genetic expression and enriched gene pathways. Seven key genes were screened out from the 232 candidate genes for prognosis prediction and a 7-gene signature prognosis model was established based on them. Two independent patient cohorts (TCGA cohort and GEO cohort) were utilized to validate the efficacy of the prognosis model, which demonstrated an effective capability to differentiate and predict the overall survival of BLCA patients. Also, the high-risk group and low-risk group derived from the 7-gene model exhibited significantly differences in drug sensitivity, immune infiltration status and biological pathways enrichment.

Conclusions

Our established 7-gene signature model based on the DNA damage repair genes could serve as a novel prognosis predictive tool for BLCA. The differentiation of BLCA patients based on the 7-gene signature model may be of great value for the appropriate selection of specific chemotherapy agents and immune-checkpoint blockade therapy administration.

Characterization of cuproptosis identified immune microenvironment and prognosis in acute myeloid leukemia

BACKGROUND

Recent studies have reported that cuproptosis, a novel cell death pathway, strongly correlates with mitochondrial metabolism. In addition, the studies reported that cuproptosis plays a role in the development of several cancers and is regulated by protein lipoylation. During cuproptosis, copper binds to the lipoylated proteins and mediates cancer progression. However, the role of cuproptosis in acute myeloid leukemia (AML) patients is yet to be explored.

METHODS

This study curated seven cuproptosis-related-genes (CRGs): FDX1, DLAT, PDHB, PDHA1, DLD, LIAS, and LIPT1 to determine cuproptosis modification patterns and the CRGs signature in AML. The CIBERSORT and ssGSEA algorithms were utilized to evaluate the infiltration levels of different immune cell subtypes. A cuproptosis score system based on differentially expressed genes (DEGs) was constructed using the least absolute shrinkage and selection operator (LASSO) regression analysis. The developed cuproptosis score system was validated using two immunotherapy datasets, IMvigor210 and GSE78220.

RESULTS

Three distinct cuproptosis regulation patterns were identified using the Beat AML cohort. The results demonstrated that the three cuproptosis regulation patterns were correlated with various biological pathways and clinical outcomes. Tumor microenvironment (TME) characterization revealed that the identified cuproptosis regulation patterns were consistent with three immune profiles: immune-desert, immune-inflamed, and immune-excluded. The AML patients were grouped into low- and high-score groups based on the cuproptosis score system abstracted from 486 cuproptosis-related DEGs. Patients with lower cuproptosis scores were characterized by longer survival time and attenuated immune infiltration. It was found that lower cuproptosis scores were strongly correlated with lower somatic mutation frequency. Moreover, patients with lower cuproptosis scores presented more favorable immune responses and dual clinical benefits among external validation cohorts.

CONCLUSIONS

Cuproptosis phenotypes are significantly correlated with immune microenvironment complexity and variety. Cuprotopsis regulates the response of cancer cells to the immune system. Quantitatively assessing cuproptosis phenotypes in AML improves the understanding and knowledge regarding immune microenvironment characteristics and promotes the development of therapeutic interventions.

Macrophage and monocyte subsets as new therapeutic targets in cancer immunotherapy

The introduction of immune checkpoint inhibitors (ICIs) for the treatment of solid cancers dramatically turned the tables in clinical routine. However, therapy success is still limited with up to 70% of non-responders in patients with ICI treatment. Traditionally, most immunotherapy approaches aim at directly stimulating anti-tumor T cell responses. More recently, tumor-associated macrophages have come into focus due to their predominance in solid tumors. Intensive cross-talk with tumor cells and immune as well as stromal cells within the tumor microenvironment can drive either pro- or anti-tumorigenic macrophage phenotypes. In turn, tumor-associated macrophages strongly shape cytokine and metabolite levels in the tumor microenvironment and thus are central players in anti-tumor immunity. Thus, ambivalent macrophage populations exist which raises therapeutic possibilities to either enhance or diminish their functionality. However, molecular signals controlling tumor-associated macrophage polarization are incompletely understood. Gaining in-depth understanding of monocyte/macrophage properties both in circulation and within distinct tumor microenvironments would (i) allow the development of new therapeutic approaches, and (ii) could additionally aid our understanding of underlying mechanisms limiting current therapy with the option of combinatorial therapies to increase efficacy. In this review, we summarize recent data addressing heterogeneity of tumor-associated macrophage populations and we discuss strategies to target macrophages using known molecular pathways with the potential for straight-forward clinical application.

Prognostic significance of absolute monocyte count and lymphocyte to monocyte ratio in mucosa-associated lymphoid tissue (MALT) lymphoma

To investigate the prognostic significance of peripheral blood absolute monocyte count (AMC) and lymphocyte to monocyte ratio (LMR) in mucosa-associated lymphoid tissue (MALT) lymphoma, we retrospectively analyzed 316 newly diagnosed patients with MALT lymphoma. The best cut-off value of AMC was 0.6 × 10⁹/L and LMR was 1.8 by x-tile according to progression-free survival (PFS). Multivariate analysis showed that MALT-IPI (p < 0.001), Eastern Cooperative Oncology Group performance status (ECOG PS) (p = 0.010), and LMR (p = 0.003) have independent prognostic significance for PFS, MALT-International Prognostic Index (MALT-IPI) (p = 0.018), β2-microglobulin (β2-MG) (p = 0.015), and LMR (p = 0.029) predicted poor overall survival (OS). Receiver-operator characteristic (ROC) curves were used to compare the prognostic prediction capability of MALT-IPI and MALT-IPI-M (MALT-IPI combined with LMR); area under the curves (AUCs) for MALT-IPI-M were larger than that for MALT-IPI both PFS (0.682 vs 0.654) and OS (0.804 vs 0.788). Our results indicated that that low level LMR at diagnosis was associated with inferior prognosis. The new prognostic index, MALT-IPI-M, enabled the risk stratification capability for MALT lymphoma survival.

Identification of angiogenesis-related subtypes, the development of prognostic models, and the landscape of tumor microenvironment infiltration in colorectal cancer

Background: Angiogenesis is one of the most prominent markers of cancer progression and contributes to tumor metastasis and prognosis. Anti-angiogenic drugs have proven effective in treating metastatic colorectal cancer. However, there is some uncertainty regarding the potential role of angiogenesis-related genes in the tumor microenvironment. Methods: We analyzed 1,214 colorectal cancer samples to identify alterations in angiogenesis-related genes (ARGs), and then correlated angiogenesis with clinical features, prognosis, and TME. The ARGs expression profiles in colorectal cancer were analyzed using three computational methods (CIBERSORT, ssGSEA, and MCPcounter) and provided a systematic immune landscape. Patients with CRC were classified into two subtypes based on consensus clustering analysis of angiogenesis-related genes. The revealed differentially expressed genes between the two subtypes were used to create and validate ARGscore prognostic models. In addition, we collected eight colorectal cancer patient specimens and performed RT-qPCR to validate the signature gene expression. Results: We assessed the expression patterns of ARGs in colorectal cancer. We identified two molecular subtypes and confirmed that the expression of ARGs was associated with prognosis and TME characteristics. Based on differentially expressed genes between subtypes, we constructed ARGscore and evaluated their predictive power for the survival of colorectal cancer patients. We also developed an accurate nomogram to make the ARGscore more clinically useful. In addition, ARGscore was significantly correlated with microsatellite instability, cancer stem cells, and chemotherapeutic drug sensitivity. Patients with ARGscore-low characterized by immune activation and microsatellite instability high had a better prognosis. Conclusion: ARGs expression influenced the prognosis, clinicopathological features, and tumor stromal immune microenvironment in colorectal cancer. We developed a new risk model, ARGscore, for the treatment and prognosis of CRC patients and validated its promising predictive power. These findings will enable us to understand colorectal cancer better, assess prognoses, and develop more effective treatment options.

Pharmaceutical targeting Th2-mediated immunity enhances immunotherapy response in breast cancer

BACKGROUND

Breast cancer is a complex disease with a highly immunosuppressive tumor microenvironment, and has limited clinical response to immune checkpoint blockade (ICB) therapy. T-helper 2 (Th2) cells, an important component of the tumor microenvironment (TME), play an essential role in regulation of tumor immunity. However, the deep relationship between Th2-mediated immunity and immune evasion in breast cancer remains enigmatic.

METHODS

Here, we first used bioinformatics analysis to explore the correlation between Th2 infiltration and immune landscape in breast cancer. Suplatast tosilate (IPD-1151 T, IPD), an inhibitor of Th2 function, was then employed to investigate the biological effects of Th2 blockade on tumor growth and immune microenvironment in immunocompetent murine breast cancer models. The tumor microenvironment was analyzed by flow cytometry, mass cytometry, and immunofluorescence staining. Furthermore, we examined the efficacy of IPD combination with ICB treatment by evaluating TME, tumor growth and mice survival.

RESULTS

Our bioinformatics analysis suggested that higher infiltration of Th2 cells indicates a tumor immunosuppressive microenvironment in breast cancer. In three murine breast cancer models (EO771, 4T1 and EMT6), IPD significantly inhibited the IL-4 secretion by Th2 cells, promoted Th2 to Th1 switching, remodeled the immune landscape and inhibited tumor growth. Remarkably, CD8⁺ T cell infiltration and the cytotoxic activity of cytotoxic T lymphocyte (CTL) in tumor tissues were evidently enhanced after IPD treatment. Furthermore, increased effector CD4⁺ T cells and decreased myeloid-derived suppressor cells and M2-like macrophages were also demonstrated in IPD-treated tumors. Importantly, we found IPD reinforced the therapeutic response of ICB without increasing potential adverse effects.

CONCLUSIONS

Our findings demonstrate that pharmaceutical inhibition of Th2 cell function improves ICB response via remodeling immune landscape of TME, which illustrates a promising combinatorial immunotherapy.

The Interface of Tumour-Associated Macrophages with Dying Cancer Cells in Immuno-Oncology

Tumour-associated macrophages (TAMs) are essential players in the tumour microenvironment (TME) and modulate various pro-tumorigenic functions such as immunosuppression, angiogenesis, cancer cell proliferation, invasion and metastasis, along with resistance to anti-cancer therapies. TAMs also mediate important anti-tumour functions and can clear dying cancer cells via efferocytosis. Thus, not surprisingly, TAMs exhibit heterogeneous activities and functional plasticity depending on the type and context of cancer cell death that they are faced with. This ultimately governs both the pro-tumorigenic and anti-tumorigenic activity of TAMs, making the interface between TAMs and dying cancer cells very important for modulating cancer growth and the efficacy of chemo-radiotherapy or immunotherapy. In this review, we discuss the interface of TAMs with cancer cell death from the perspectives of cell death pathways, TME-driven variations, TAM heterogeneity and cell-death-inducing anti-cancer therapies. We believe that a better understanding of how dying cancer cells influence TAMs can lead to improved combinatorial anti-cancer therapies, especially in combination with TAM-targeting immunotherapies.

Pan-cancer analysis of DEPDC1 as a candidate prognostic biomarker and associated with immune infiltration

Background

DEP domain containing 1 (DEPDC1) gene is upregulated in several malignancies and contributes to tumorigenesis. Although the role of DEPDC1 in tumor is becoming increasingly popular, the function of DEPDC1 in pan-cancer still needs to be systematically elucidated.

Methods

Data were downloaded from Genotype-Tissue Expression Data (GTEx), The Cancer Genome Atlas (TCGA) TIMER2.0, TISIDB, STRING, and CancerSEA databases and analyzed to determine the functionality of the DEPDC1. The results were visualized using tools provided by the databases and the R language.

Results

The results showed that DEPDC1 was significantly upregulated in 29 of the 33 human cancers analyzed. In addition, there were significant differences in DEPDC1 expression among cancer immune and molecular subtypes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that DEPDC1 was mainly involved in the cell cycle, and CancerSEA analysis showed that DEPDC1 promoted cell cycle, DNA repair, DNA damage, and proliferation in pan-cancer. Receiver operating characteristic (ROC) curve analysis showed high predictive accuracy for pan-cancer. DEPDC1 expression was positively correlated with activated CD4⁺ T helper 2 cells and common lymphoid progenitor cells, and negatively correlated with natural killer (NK) T cells, CD4⁺ central memory T cells, and CD4⁺ effector memory T cells. Furthermore, DEPDC1 was significantly positively correlated with T cell exhaustion marker genes, such as CD274, transforming growth factor beta receptor 1 (TGFBR1), kinase insert domain receptor (KDR), programmed cell death 1 ligand 2 (PDCD1LG2), granzyme B (GZMB), and granulysin (LAG2). Additionally, DEPDC1 was associated with overall survival (OS), disease-specific survival (DSS), and progress-free interval (PFI) prognosis in multiple tumor types. The ROC analysis showed high predictive accuracy for pan-cancer.

Conclusions

Collectively, DEPDC1 is aberrantly expressed and plays an immune-oncogenic role in pan-cancer, and DEPDC1 may serve as a biomarker for cancer diagnosis and therapy.

A pan-cancer analysis of the oncogenic role of ribonucleotide reductase subunit M2 in human tumors

Background

Recent studies have identified ribonucleotide reductase subunit M2 (RRM2) as a putative promoter of tumors. However, no systematic analysis of its carcinogenicity has been conducted.

Methods

The potential functions of RRM2 in various tumor types were investigated using data from the Genotype-Tissue Expression (GTEx), the Clinical Proteomic Tumor Analysis Consortium (CPTAC), the Cancer Genome Atlas (TCGA), the Human Protein Atlas (HPA), cBioPortal, GEPIA, String, and Gene Set Enrichment Analysis (GSEA). We analyzed the difference in mRNA and protein expression, pathological stage, survival, mutation, tumor microenvironment (TME), and immune cell infiltration in relation to RRM2. Meanwhile, using TCGA and the Tumor Immune Estimation Resource 2 (TIMER 2), the associations between RRM2 expression, immune infiltration, and immune-related genes were assessed. Additionally, CCK-8, Edu and RT-PCR assays were used to validate that RRM2 acts as an oncogene in liver cancer cells and its association with HBx. A cohort of liver hepatocellular carcinoma (LIHC) patients (n=154) from Huashan Hospital was analyzed for the expression of RRM2 and the association between RRM2 and immune infiltration.

Results

Using the GTEx and TCGA databases, we discovered that 28 tumors expressed RRM2 at significantly higher levels than the corresponding normal tissues. Increased RRM2 expression may be predictive of a poor overall survival (OS) in patients with seven different cancers. GO, KEGG, and GSEA analyses revealed that the biological process of RRM2 was associated with the regulation of carcinogenic processes and immune pathways in a variety of tumor types. The expression of RRM2 was highly correlated with maker genes involved in immune activation and immunosuppression, immune checkpoints, DNA mismatch repair system (MMR), and the infiltration levels of Tregs and macrophages (TAMs), suggesting that the carcinogenic effect of RRM2 may be achieved by regulating immune related genes. Moreover, as demonstrated by CCK-8 and Edu assays, RRM2 was an oncogene in liver cancer cells. We confirmed for the first time that RRM2 was significantly upregulated by HBx, suggesting that RRM2 may be a key regulator of LIHC induced by HBV. IHC analysis validated the upregulated expression of RRM2 protein and its correlation with immune infiltration makers in a LIHC patient cohort.

Conclusion

RRM2 may be a valuable molecular biomarker for predicting prognosis and immunotherapeutic efficacy in pan-cancer, particularly in LIHC.