Immuno-Metabolism and Microenvironment in Cancer: Key Players for Immunotherapy

The roles of metabolic profiles and intracellular signaling pathways of tumor microenvironment cells in angiogenesis of solid tumors

Innate and adaptive immune cells patrol and survey throughout the human body and sometimes reside in the tumor microenvironment (TME) with a variety of cell types and nutrients that may differ from those in which they developed. The metabolic pathways and metabolites of immune cells are rooted in cell physiology, and not only provide nutrients and energy for cell growth and survival but also influencing cell differentiation and effector functions. Nowadays, there is a growing awareness that metabolic processes occurring in cancer cells can affect immune cell function and lead to tumor immune evasion and angiogenesis. In order to safely treat cancer patients and prevent immune checkpoint blockade-induced toxicities and autoimmunity, we suggest using anti-angiogenic drugs solely or combined with Immune checkpoint blockers (ICBs) to boost the safety and effectiveness of cancer therapy. As a consequence, there is significant and escalating attention to discovering techniques that target metabolism as a new method of cancer therapy. In this review, a summary of immune-metabolic processes and their potential role in the stimulation of intracellular signaling in TME cells that lead to tumor angiogenesis, and therapeutic applications is provided. Video abstract.

A pyroptosis-related gene model and its correlation with the microenvironment of lung adenocarcinoma: A bioinformatics analysis and experimental verification

Background: Non-small cell lung cancer, comprising lung adenocarcinoma (LUAD) and lung squamous cell carcinoma, is one of the leading causes of cancer-related mortality. Pyroptosis is a new form of programmed cell death involved in cancer development. The relationship between LUAD and pyroptosis is unclear. This research aims to investigate this relationship and develop a stratified clinical model based on pyroptosis-related genes (PRGs). Methods: We analyzed the data of LUAD from The Cancer Genome Atlas (TCGA) and evaluated the expression of 48 PRGs to identify the differentially expressed genes. Then, constructing the risk model using the least absolute shrinkage and selection operator and the Cox regression method to find the gene signatures. The functional enrichment, immune cell infiltration, tumor mutational burden (TMB), and expression of immune checkpoints were compared to investigate the potential mechanism. The IC50 of common drugs was evaluated and compared. The inflammasome activation assay and lactate dehydrogenase (LDH) assay of NLR-family CARD-containing protein 4 (NLRC4) were also performed to confirm the role of pyroptosis in LUAD. Results: The pyroptosis-related model accurately predicted the prognosis of patients with LUAD, with the low-risk group exhibiting a higher survival probability. The risk score was an independent prognostic factor for survival. The stratified patients exhibited distinct tumor microenvironments, TMB, and drug sensitivity. The validation experiments of NLRC4 confirmed its role in inducing pyroptosis via promoting IL-1 maturation. Conclusion: PRGs regulated the tumor microenvironment and influenced the outcome of LUAD. NLRC4 may function as a hub gene in the process of LUAD.

Prediction of hepatocellular carcinoma prognosis and immunotherapeutic effects based on tryptophan metabolism-related genes

Background

L-tryptophan (Trp) metabolism involved in mediating tumour development and immune suppression. However, comprehensive analysis of the role of the Trp metabolism pathway is still a challenge.

Methods

We downloaded Trp metabolism-related genes’ expression data from different public databases, including TCGA, Gene Expression Omnibus (GEO) and Hepatocellular Carcinoma Database (HCCDB). And we identified two metabolic phenotypes using the ConsensusClusterPlus package. Univariate regression analysis and lasso Cox regression analysis were used to establish a risk model. CIBERSORT and Tracking of Indels by DEcomposition (TIDE) analyses were adopted to assess the infiltration abundance of immune cells and tumour immune escape.

Results

We identified two metabolic phenotypes, and patients in Cluster 2 (C2) had a better prognosis than those in Cluster 1 (C1). The distribution of clinical features between the metabolic phenotypes showed that patients in C1 tended to have higher T stage, stage, grade, and death probability than those of patients in C2. Additionally, we screened 739 differentially expressed genes (DEGs) between the C1 and C2. We generated a ten-gene risk model based on the DEGs, and the area under the curve (AUC) values of the risk model for predicting overall survival. Patients in the low-risk subgroup tended to have a significantly longer overall survival than that of those in the high-risk group. Moreover, univariate analysis indicated that the risk model was significantly correlated with overall survival. Multivariate analysis showed that the risk model remained an independent risk factor in hepatocellular carcinoma (p < 0.0001).

Conclusions

We identified two metabolic phenotypes based on genes of the Trp metabolism pathway, and we established a risk model that could be used for predicting prognosis and guiding immunotherapy in patients with hepatocellular carcinoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02730-8.

CDCA3 Predicts Poor Prognosis and Affects CD8+ T Cell Infiltration in Renal Cell Carcinoma

Background

Cell division cycle associated 3 (CDCA3) mediates the ubiquitination WEE1 kinase at G2/M phase. However, its contribution to cancer immunity remains uncertain.

Methods

We first evaluated the effect of CDCA3 on the prognosis of patients with renal cell carcinoma (RCC). The results of bioinformatics analysis were verified by the tissue microarray, immunofluorescence (IF) staining, CCK-8 assay, colony formation, cell cycle, and Western blot.

Results

Bioinformatics analysis predicated CDCA3 was an independent predictor of poor prognosis in RCC and was associated with poor TNM stage and grade. CDCA3 was related to the infiltration of CD8⁺ T cells and Tregs. Tissue microarray demonstrated that CDCA3 was strongly associated with poor prognosis and positively relevant to CD8⁺ T infiltration. In vitro experiments showed that exgenomic interference of CDCA3 could attenuate cellular proliferation, arrest cell cycle, and blockade accumulation of CDK4, Bub3, and Cdc20 in mitosis process.

Conclusion

CDCA3 presents as a good biomarker candidate to predict the prognosis of RCC patients and potentiates the immune tumor microenvironment (TME) of RCC.

Comprehensive analysis of the prognostic signature and tumor microenvironment infiltration characteristics of cuproptosis-related lncRNAs for patients with colon adenocarcinoma

Background

Cuproptosis, a newly described method of regulatory cell death (RCD), may be a viable new therapy option for cancers. Long noncoding RNAs (lncRNAs) have been confirmed to be correlated with epigenetic controllers and regulate histone protein modification or DNA methylation during gene transcription. The roles of cuproptosis-related lncRNAs (CRLs) in Colon adenocarcinoma (COAD), however, remain unknown.

Methods

COAD transcriptome data was obtained from the TCGA database. Thirteen genes associated to cuproptosis were identified in published papers. Following that, correlation analysis was used to identify CRLs. The cuproptosis associated prognostic signature was built and evaluated using Lasso regression and COX regression analysis. A prognostic signature comprising six CRLs was established and the expression patterns of these CRLs were analyzed by qRT-PCR. To assess the clinical utility of prognostic signature, we performed tumor microenvironment (TME) analysis, mutation analysis, nomogram generation, and medication sensitivity analysis.

Results

We identified 49 prognosis-related CRLs in COAD and constructed a prognostic signature consisting of six CRLs. Each patient can be calculated for a risk score and the calculation formula is: Risk score =TNFRSF10A-AS1 * (-0.2449) + AC006449.3 * 1.407 + AC093382.1 *1.812 + AC099850.3 * (-0.0899) + ZEB1-AS1 * 0.4332 + NIFK-AS1 * 0.3956. Six CRLs expressions were investigated by qRT-PCR in three colorectal cancer cell lines. In three cohorts, COAD patients were identified with different risk groups, with the high-risk group having a worse prognosis than the low-risk group. Furthermore, there were differences in immune cell infiltration and tumor mutation burden (TMB) between the two risk groups. We also identified certain drugs that were more sensitive to the high-risk group: Paclitaxel, Vinblastine, Sunitinib and Elescloml.

Conclusions

Our findings may be used to further investigate RCD, comprehension of the prognosis and tumor microenvironment infiltration characteristics in COAD.

Construction of ceRNA network and identification of hub genes in aniridia-associated keratopathy using bioinformatics analysis

Aniridia-associated keratopathy (AAK) is characteristic at ocular surface of aniridia caused by haploinsufficiency of PAX6. Competing endogenous RNA (ceRNA) has been reported to play an important role in various diseases, whereas its function on AAK is unclear. The microarray data of 20 AAK patients and 20 healthy people were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed lncRNAs, miRNAs, and mRNAs were analyzed using “limma” packages and weighted gene co-expression network analysis (WGCNA). A ceRNA network was constructed by Cytoscape 3.9.1, and miR-224-5p, miR-30a-5p, and miR-204-5p were at the center of the network. CIBERSORTx algorithm and ssGSEA analyses revealed that AAK was associated with immune cell infiltration, showing that activated Mast cells increased while resting Mast cells decreased and NK cells decreased in AAK. Type II INF Response, CCR, parainflammation, T cell co-stimulation, and APC co-stimulation of AAK patients differed from healthy individuals. Additionally, the ROC curve of five genes, MITF(AUC = 0.988), RHOB(AUC = 0.973), JUN(AUC = 0.953), PLAUR (AUC = 0.925), and ARG2 (AUC = 0.915) with high confidence in predicting AAK were identified. Gene set enrichment analysis (GSEA) analysis of hub genes enriched in the IL-17 signaling pathway.

LINC01094/SPI1/CCL7 Axis Promotes Macrophage Accumulation in Lung Adenocarcinoma and Tumor Cell Dissemination

Objective

Infiltration of tumor-associated macrophages is closely linked to the malignant development of human cancers. This research studies the function of C-C motif chemokine ligand 7 (CCL7) in the macrophage accumulation in lung adenocarcinoma (LUAD) and the underpinning mechanism.

Methods

The expression profile of CCL7 in LUAD and its correlations with patient's prognosis and macrophage infiltration were predicted via bioinformatics systems. Artificial up- or downregulation of CCL7 was induced in LUAD cells to explore its function in the mobility, EMT of cancer cells, and migration of M2 macrophages. Cancer cells were implanted in NOD/SCID mice to induce xenograft tumors. The CCL7-related transcription factors or factors were predicted by bioinformatic tools, and the molecular interactions were confirmed by immunoprecipitation or luciferase assays.

Results

CCL7 was highly expressed in LUAD and linked to increased TAM infiltration. Knockdown of CCL7 suppressed the chemotaxis and M2 skewing of macrophages, and it blocked the EMT and mobility of LUAD cells. CCL7 downregulation also suppressed macrophage infiltration in xenograft tumors in mice. Spi-1 proto-oncogene (SPI1) was confirmed as an upstream factor activating CCL7 transcription, and LINC01094 was found to bind to SPI1 to promote its nuclear translocation. Upregulation of SPI1 restored the chemotactic migration and M2 polarization of macrophages in LUAD cells.

Conclusion

This paper reveals that LINC01094 binds to SPI1 to promote its nuclear translocation, which further activates CCL7 transcription by binding to its promoter, leading to M2 macrophage accumulation and dissemination of tumor cells.

Pan-cancer analysis reveals interleukin-17 family members as biomarkers in the prediction for immune checkpoint inhibitor curative effect

Background

The interleukin-17 (IL-17) family contains six homologous genes, IL-17A to IL-17F. Growing evidence indicates that dysregulated IL-17 family members act as major pathogenic factors in the early and late stages of cancer development and progression. However, the prevalence and predictive value of IL-17 for immune checkpoint inhibitor (ICI) therapeutic effectiveness in multiple tumor types remain largely unknown, and the associations between its expression levels and immunotherapy-associated signatures also need to be explored.

Methods

The pan-cancer dataset in The Cancer Genome Atlas (TCGA) was downloaded from UCSC Xena (http://xena.ucsc.edu/). The immunotherapeutic cohorts included IMvigor210, which were obtained from the Gene Expression Omnibus database and included in a previously published study. Other datasets, namely, the GEO dataset and PRECOG, GEO, and METABRIC databases, were also included. In 33 TCGA tumor types, a pan-cancer analysis was carried out including their expression map, clinical risk assessment, and immune subtype analysis, along with their association with the stemness indices, tumor microenvironment (TME) in pan-cancer, immune infiltration analysis, ICI-related immune indicators, and drug sensitivity. RT-PCR was also carried out to verify the gene expression levels among MCF-10A and MCF-7 cell lines.

Results

The expression of the IL-17 family is different between tumor and normal tissue in most cancers, and consistency has been observed between gene activity and gene expression. RT-PCR results show that the expression differences in the IL-17 family of human cell (MCF-10A and MCF-7) are consistent with the bioinformatics differential expression analysis. Moreover, the expression of the IL-17 family can be a sign of patients’ survival prognosis in some tumors and varies in different immune subtypes. Moreover, the expression of the IL-17 family presents a robust correlation with immune cell infiltration, ICI-related immune indicators, and drug sensitivity. High expression of the IL-17 family is significantly related to immune-relevant pathways, and the low expression of IL-17B means a better immunotherapeutic response in BLCA.

Conclusion

Collectively, IL-17 family members may act as biomarkers in predicting the prognosis of the tumor and the therapeutic effects of ICIs, which provides new guidance for cancer treatment.

Adenosinergic axis and immune checkpoint combination therapy in tumor: A new perspective for immunotherapy strategy

There are two figures and one table in this review, the review consists of 5823 words, without the description of figures and table, but including references.

Tumor cells escape anti-tumor immune responses in various ways, including functionally shaping the microenvironment through the secretion of various chemokines and, cytokines. Adenosine is a powerful immunosuppressive metabolite, that is frequently elevated in the extracellular tumor microenvironment (TME). Thus, it has recently been proposed as a novel antitumor immunoassay for targeting adenosine- generating enzymes, such as CD39, CD73, and adenosine receptors. In recent years, the discovery of the immune checkpoints, such as programmed cell death 1(PD-1) and cytotoxic T lymphocyte antigen 4 (CTLA-4), has also greatly changed treatment methods and ideas for malignant tumors. Malignant tumor immunotherapy has been developed from point-to-point therapy targeting immune checkpoints, combining different points of different pathways to create a therapy based on the macroscopic immune regulatory system network. This article reviews the theoretical basis of the adenosine energy axis and immune checkpoint combined therapy for malignant tumors and the latest advances in malignant tumors.

Exploration of shared TF-miRNA‒mRNA and mRNA-RBP-pseudogene networks in type 2 diabetes mellitus and breast cancer

Type 2 diabetes mellitus (T2DM) has been confirmed to be closely associated with breast cancer (BC). However, the shared mechanisms between these diseases remain unclear. By comparing different datasets, we identified shared differentially expressed (DE) RNAs in T2DM and BC, including 427 mRNAs and 6 miRNAs from the GEO(Gene Expression Omnibus) database. We used databases to predict interactions to construct two critical networks. The transcription factor (TF)-miRNA‒mRNA network contained 236 TFs, while the RNA binding protein (RBP)-pseudogene-mRNA network showed that the pseudogene S-phase kinase associated protein 1 pseudogene 1 (SKP1P1) might play a key role in regulating gene expression. The shared mRNAs between T2DM and BC were enriched in cytochrome (CYP) pathways, and further analysis of CPEB1 and COLEC12 expression in cell lines, single cells and other cancers showed that they were strongly correlated with the survival and prognosis of patients with BC. This result suggested that patients with T2DM presenting the downregulation of CPEB1 and COLEC12 might have a higher risk of developing BC. Overall, our work revealed that high expression of CYPs in patients with T2DM might be a susceptibility factor for BC and identified novel gene candidates and immune features that are promising targets for immunotherapy in patients with BC.

A cohesin-associated gene score may predict immune checkpoint blockade in hepatocellular carcinoma

Stromal antigen 1 (STAG1), a component of cohesion, is overexpressed in various cancers, but it is unclear whether it has a role in the transcriptional regulation of hepatocellular carcinoma (HCC). To test this hypothesis, here, we screened global HCC datasets and performed multiscale embedded gene co-expression network analysis to identify the potential functional modules of differentially expressed STAG1 co-expressed genes. The putative transcriptional targets of STAG1 were identified using chromatin immunoprecipitation followed by high-throughput DNA sequencing. The cohesin-associated gene score (CAGS) was quantified using the The Cancer Genome Atlas HCC cohort and single-sample gene set enrichment analysis. Distinct cohesin-associated gene patterns were identified by calculating the euclidean distance of each patient. We assessed the potential ability of the CAGS in predicting immune checkpoint blockade (ICB) treatment response using IMvigor210 and GSE78220 cohorts. STAG1 was upregulated in 3313 HCC tissue samples compared with 2692 normal liver tissue samples (standard mean difference = 0.54). A total of three cohesin-associated gene patterns were identified, where cluster 2 had a high TP53 mutated rate and a poor survival outcome. Low CAGS predicted a significant survival advantage but presaged poor immunotherapy response. Differentially expressed STAG1 co-expression genes were enriched in the mitotic cell cycle, lymphocyte activation, and blood vessel development. PDS5A and PDGFRA were predicted as the downstream transcriptional targets of STAG1. In summary, STAG1 is significantly upregulated in global HCC tissue samples and may participate in blood vessel development and the mitotic cell cycle. A cohesin-associated gene scoring system may have potential to predict the ICB response.

Identification and validation of a novel prognostic model of inflammation-related gene signature of lung adenocarcinoma

Previous literatures have suggested the importance of inflammatory response during lung adenocarcinoma (LUAD) development. This study aimed at exploring the inflammation-related genes and developing a prognostic signature for predicting the prognosis of LUAD. Survival‑associated inflammation-related genes were identified by univariate Cox regression analysis in the dataset of The Cancer Genome Atlas (TCGA). The least absolute shrinkage and selection operator (LASSO) penalized Cox regression model was used to derive a risk signature which is significantly negatively correlated with OS and divide samples into high-, medium- and low-risk group. Univariate and multivariate Cox analyses suggested that the level of risk group was an independent prognostic factor of the overall survival (OS). Time-dependent receiver operating characteristic (ROC) curve indicated the AUC of 1-, 3- and 5-years of the risk signature was 0.715, 0.719, 0.699 respectively. A prognostic nomogram was constructed by integrating risk group and clinical features. The independent dataset GSE30219 of Gene Expression Omnibus (GEO) was used for verification. We further explored the differences among risk groups in Gene set enrichment analysis (GSEA), tumor mutation and tumor microenvironment. Furthermore, Single Sample Gene Set Enrichment Analysis (ssGSEA) and the results of Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) suggested the status of immune cell infiltration was highly associated with risk groups. We demonstrated the prediction effect of CTLA-4 and PD-1/PD-L1 inhibitors in the low-risk group was better than that in the high-risk group using two methods of immune score include immunophenoscore from The Cancer Immunome Atlas (TCIA) and TIDE score from Tumor Immune Dysfunction and Exclusion (TIDE). In addition, partial targeted drugs and chemotherapy drugs for lung cancer had higher drug sensitivity in the high-risk group. Our findings provide a foundation for future research targeting inflammation-related genes to predictive prognosis and some reference significance for the selection of immunotherapy and drug regimen for lung adenocarcinoma.

PRR7-AS1 Correlates with Immune Cell Infiltration and Is a Diagnostic and Prognostic Marker for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a highly aggressive malignant disease, and numerous studies have shown that certain functional long noncoding RNAs (lncRNAs) are implicated in the progression of several cancers. The purpose of the research was to determine, using a database, bioinformatics, and statistical analysis, whether or not lncRNA PRR7-AS1 (PRR7-AS1) was related to HCC. TCGA datasets were used to conduct research on the PRR7-AS1 expression pattern in HCC. In order to evaluate the efficacy of GIHCG as a prognostic tool, both survival and Cox regression analyses were carried out. Furthermore, an investigation of the connection between the expression of PRR7-AS1 and immune infiltration in HCC was carried out. In this study, we identified 125 lncRNAs that were significantly dysregulated in HCC and were associated with long-term survival. Among the above 125 lncRNAs, our attention focused on PRR7-AS1. We found that PRR7-AS1 expressions were distinctly overexpressed in HCC samples compared with nontumor samples. ROC assays revealed that PRR7-AS1 effectively differentiated HCC specimens from normal tissues with an AUC of 0.875 (95% CI: 0.840 to 0.911). Moreover, the high PRR7-AS1 expression was associated with advanced clinical stage and poor prognosis of HCC patients. Importantly, the multivariate Cox proportional hazards model suggested that up-expression of PRR7-AS1 was an independent prognostic marker indicating shorter overall survival and disease-specific survival for HCC patients. Finally, we found that PRR7-AS1 expression was associated with the expression of NK CD56bright cells, Th2 cells, TFH, macrophages, Th1 cells, aDC, T helper cells, cytotoxic cells, DC, Tgd, neutrophils, and Th17 cells. Overall, the results of our study show that PRR7-AS1 was a biomarker that could be utilized to predict the prognosis of HCC patients and was linked to the infiltration of immune cells in HCC.

Tumor associated macrophages-derived exosomes facilitate hepatocellular carcinoma malignance by transferring lncMMPA to tumor cells and activating glycolysis pathway

BACKGROUND

Tumor-associated macrophages (TAMs), which form a large part of the tumor microenvironment, are normally regulated by metabolic reprogramming. However, the potential mechanisms of the immune-metabolism interaction between hepatocellular carcinoma (HCC) cells and TAMs remain unclear.

METHODS

The candidate long non-coding RNAs (lncRNAs) were screened by Smart-seq based scRNA-seq method and then validated by qPCR. Immunostaining analysis was done to examine the levels of markers for TAMs and glycolysis. Exosomes from primary TAMs of human HCC tissues were isolated by centrifugation, and their internalization with lncRNAs was confirmed by immunofluorescence. The underlying mechanism of TAMs-derived exosomal lncRNA to HCC was confirmed by luciferase reporter assay and RNA immunoprecipitation. Metabolism regulation was evaluated through glucose consumption, lactate productions and extracellular acidification rates (ECARs). Mouse xenograft models were used to elucidate the in vivo effect of candidate lncRNAs on tumor growth.

RESULTS

TAMs augment the aerobic glycolysis in HCC cells and their proliferation by the extracellular exosome transmission of a myeloid-derived lncRNA, M2 macrophage polarization associated lncRNA (lncMMPA). Mechanistically, lncMMPA not only could polarize M2 macrophage, but also could act as an microRNA sponge to interact with miR-548 s and increase the mRNA level of ALDH1A3, then further promote glucose metabolism and cell proliferation in HCC. Moreover, lncMMPA increased HCC cell multiplication through interacting with miR-548 s in vivo. Clinically, lncMMPA expression associates with glycolysis in TAMs and reduced survival of HCC patients.

CONCLUSION

LncMMPA plays an important role in regulating HCC malignancy and metabolic reprogramming of miR-548 s/ALDH1A3 pathway.

New Immuno-oncology Targets and Resistance Mechanisms

OPINION STATEMENT

Immune checkpoint inhibition (ICI) has revolutionized the field of non-small cell lung cancer (NSCLC); currently, most patients with advanced disease receive upfront ICI either alone or in combination with chemotherapy. These advances have recently extended into early-stage NSCLC, with ICI incorporation into neoadjuvant and adjuvant treatment regimens. However, despite these successes, immunotherapy (IO) resistance remains a fundamental challenge in NSCLC, introducing a central quandary of how to precisely select the appropriate IO therapy or IO combination therapy for each individual patient. To address this vital need in the field, there has been an explosion of research in immuno-oncology to identify mechanisms of resistance, ranging from genomic alterations in the tumor to immunosuppressive conditions in the tumor microenvironment (TME). There remain many questions about how this complex interplay between the tumor and the immune microenvironment translates into clinical phenotypes of primary and acquired resistance. In NSCLC, a number of novel therapeutics are being developed to prevent and overcome resistance to ICI. Particular promise has been shown with therapeutics targeting novel T cell immune checkpoint inhibitors and targeting innate immune cells in the TME, chief among these cells are natural killer cells, neutrophils, and macrophages. Further research into tissue-based and non-invasive biomarkers that can be prospectively integrated into therapeutic trial design will be critical to advance the field's understanding of individual resistance patterns and enable the ultimate goal of precision immuno-oncology.

Anaplastic lymphoma kinase-special immunity and immunotherapy

Alterations in the anaplastic lymphoma kinase (ALK) gene play a key role in the development of various human tumors, and targeted therapy has transformed the treatment paradigm for these oncogene-driven tumors. However, primary or acquired resistance remains a challenge. ALK gene variants (such as gene rearrangements and mutations) also play a key role in the tumor immune microenvironment. Immunotherapy targeting the ALK gene has potential clinical applications. Here, we review the results of recent studies on the immunological relevance of ALK-altered tumors, which provides important insights into the development of tumor immunotherapies targeting this large class of tumors.

Holliday Cross-Recognition Protein HJURP: Association With the Tumor Microenvironment in Hepatocellular Carcinoma and With Patient Prognosis

Background: Hepatocellular carcinoma is the most common type of primary liver cancer, and it is associated with poor prognosis. It often fails to respond to immunotherapy, highlighting the need to identify genes that are associated with the tumor microenvironment and may be good therapeutic targets. We and others have shown that the Holliday cross-recognition protein HJURP can promote the proliferation, migration, and invasion by hepatocellular carcinoma cells, and that HJURP overexpression is associated with poor survival. Here we explored the potential relationship between HJURP and the tumor microenvironment in hepatocellular carcinoma.

Methods: We used the Immuno-Oncology-Biological-Research (IOBR) software package to analyze the potential roles of HJURP in the tumor microenvironment. Using single-cell RNA sequencing data, we identified the cell clusters expressing abundant HJURP, then linked some of these clusters to certain bioprocesses using Gene Set Enrichment Analysis (GSEA). We validated the differential expression of HJURP in tumor-infiltrating CD8⁺ T cells, sorted by flow cytometry into populations based on the expression level of PD-1. We used weighted gene co-expression network analysis (WGCNA) to identify immunity-related genes whose expression strongly correlated with that of HJURP. The function of these genes was validated based on enrichment in Gene Ontology (GO) terms, and they were used to establish a prognosis prediction model.

Results: IOBR analysis suggested that HJURP is significantly related to the immunosuppressive tumor microenvironment and was significantly related to T cells, dendritic cells, and B cells. Based on single-cell RNA sequencing, HJURP was strongly expressed in T cells, erythrocytes, and B cells from normal liver tissues, as well as in CD8⁺ T cells, dendritic cells, and one cluster of hepatocytes in hepatocellular carcinoma tissues. Malignant hepatocytes strongly expressing HJURP were associated with the downregulation of immune bioprocesses. HJURP expression was significantly higher in CD8⁺ T cells strongly expressing PD-1 than in those expressing no or intermediate levels of PD1. WGCNA identified two module eigengenes (comprising 397 and 84 genes) related to the tumor microenvironment. We identified 24 hub genes and confirmed that they were related to immune regulation. A prognostic risk score model based on expression of HJURP, PPT1, PML, and CLEC7A showed moderate ability to predict survival.

Conclusion:HJURP is associated with tumor-infiltrating immune cells, immune checkpoints, and immune suppression in hepatocellular carcinoma. HJURP-related genes involved in immune responses may be useful for predicting patient prognosis.

Single-Cell RNA-seq Analysis Reveals Dysregulated Cell-Cell Interactions in a Tumor Microenvironment Related to HCC Development

The heterogeneity of tumor microenvironment (TME) of hepatocellular carcinoma (HCC) may relate to cell-cell interaction event (CCE) dysregulation and would affect therapeutic responses and clinical outcomes. To reveal the differentiation of CCEs in the liver tissue from healthy donors (HD) to HCC, scRNA-seq data of ~62000 cells from HD, paracancerous nontumor tissue (NT), and HCC were analyzed. The microenvironmental CCE landscape was constructed. Dysregulated cell types and changed molecular functions were identified with CCE alterations in HCC. Dysregulated CCEs which function as pivotal roles in tumorigenesis and development of HCC included SPP1-CD44, MIF-TNFRSF14, and VEGFA-NRP1. A CCE-based immune regulatory network was extracted to illustrate the mechanism of TME dysregulation. A prognostic signature based on CCE genes was identified and validated in independent datasets. Our study provided insights into the characteristics of the cross-talk between tumor cells and microenvironment in HCC and established a workflow strategy for CCE analyses based on scRNA-seq data.

Angiogenic Factor-Based Signature Predicts Prognosis and Immunotherapy Response in Non-Small-Cell Lung Cancer

Non-small-cell lung cancer (NSCLC) is one of the most common malignancies, and specific molecular targets are still lacking. Angiogenesis plays a central regulatory role in the growth and metastasis of malignant tumors and angiogenic factors (AFs) are involved. Although there are many studies comparing AFs and cancer, a prognostic risk model for AFs and cancer in humans has not been reported in the literature. This study aimed to identify the key AFs closely related to the process of NSCLC development, and four genes have been found, C1QTNF6, SLC2A1, PTX3, and FSTL3. Then, we constructed a novel prognostic risk model based on these four genes in non-small-cell lung cancer (NSCLC) and fully analyzed the relationship with clinical features, immune infiltration, genomes, and predictors. This model had good discrimination and calibration and will perform well in predicting the prognosis of treatment in clinical practice.

PI3K/AKT/mTOR Pathway-Associated Genes Reveal a Putative Prognostic Signature Correlated with Immune Infiltration in Hepatocellular Carcinoma

Background

The dysregulated PI3K/AKT/mTOR pathway acts as the main regulator of tumorigenesis in hepatocellular carcinoma (HCC).

Aim

Here, we identify the prognostic significance of PI3K/AKT/mTOR pathway-associated genes (PAGs) as well as their putative signature based on PAGs in an HCC patient's cohort.

Methods

The transcriptomic data and clinical feature sets were queried to extract the putative prognostic signature.

Results

We identified nine PAGs with different expressions. GO and KEGG indicated that these differentially expressed genes were associated with various carcinogenic pathways. Based on the signature-computed median risk score, we categorized the patients into groups of low risk and high risk. The survival time for the low-risk group is longer than that of the high-risk group in Kaplan-Meier (KM) curves. The prognostic value of risk score (ROC = 0.736) of receiver operating characteristic (ROC) curves performed better in comparison to that of other clinicopathological features. In both the GEO database and ICGC database, these outcomes were verified. The predictions of the overall survival rates in HCC patients of 1 year, 3 years, and 5 years can be obtained separately from the nomogram. The risk score was associated with the immune infiltrations of CD8 T cells, activated CD4 memory T cells, and follicular helper T cells, and the expression of immune checkpoints (PD-1, TIGIT, TIM-3, BTLA, LAG-3, and CTLA4) was positively relevant to the risk score. The sensitivity to several chemotherapeutic drugs can also be revealed by the signature. CDK1, PITX2, PRKAA2, and SFN were all upregulated in the tumor tissue of clinical samples.

Conclusion

A putative and differential dataset-validated prognostic signature on the basis of integrated bioinformatic analysis was established in our study, providing the immunotherapeutic targets as well as the personalized treatment in HCC with neoteric insight.

An Ex Vivo 3D Tumor Microenvironment-Mimicry Culture to Study TAM Modulation of Cancer Immunotherapy

Tumor-associated macrophages (TAMs) accumulate in the solid tumor microenvironment (TME) and have been shown to promote tumor growth and dampen antitumor immune responses. TAM-mediated suppression of T-cell antitumor reactivity is considered to be a major obstacle for many immunotherapies, including immune checkpoint blockade and adoptive T/CAR-T-cell therapies. An ex vivo culture system closely mimicking the TME can greatly facilitate the study of cancer immunotherapies. Here, we report the development of a 3D TME-mimicry culture that is comprised of the three major components of a human TME, including human tumor cells, TAMs, and tumor antigen-specific T cells. This TME-mimicry culture can readout the TAM-mediated suppression of T-cell antitumor reactivity, and therefore can be used to study TAM modulation of T-cell-based cancer immunotherapy. As a proof-of-principle, the studies of a PD-1/PD-L1 blockade therapy and a MAO-A blockade therapy were performed and validated.

The oncogenic role of tubulin alpha-1c chain in human tumours

Tubulin alpha-1c chain (TUBA1C), a subtype of α-tubulin, has been shown to be involved in cell proliferation and cell cycle progression in several cancers and to influence cancer development and prognosis. However, a pancancer analysis of TUBA1C to reveal its immunological and prognostic roles has not been performed. In this study, we first downloaded raw data on TUBA1C expression in cancers from The Cancer Genome Atlas (TCGA) database and multiple other databases and analysed these data with R software to investigate the prognostic and immunological value of TUBA1C in cancers. Immunohistochemical analysis was performed in gliomas to further validate our findings. Overall, TUBA1C was overexpressed in most cancers, and overexpression of TUBA1C was linked to poor prognosis and higher tumour grade in patients. In addition, TUBA1C expression was associated with tumour mutation burden (TMB), microsatellite instability (MSI), the tumour microenvironment (TME) and the infiltration of immune cells. TUBA1C was also coexpressed with most immune-related genes and influenced immune-related pathways. Immunohistochemical analysis showed that TUBA1C expression was highest in glioblastoma (GBM) tissues, second highest in low-grade glioma (LGG) tissues and lowest in normal tissues. Our study indicated that TUBA1C might be a biomarker for predicting the immune status and prognosis of cancers, offering new ideas for cancer treatment.

A Novel Necroptosis-Associated lncRNA Signature Can Impact the Immune Status and Predict the Outcome of Breast Cancer

Breast cancer (BRCA) is one of the leading causes of death among women worldwide, and drug resistance often leads to a poor prognosis. Necroptosis is a type of programmed cell death (PCD) and exhibits regulatory effects on tumor progression, but few studies have focused on the relationships between necroptosis-associated lncRNAs and BRCA. In this study, we established a signature basis of 7 necroptosis-related lncRNAs associated with prognosis and divided BRCA patients into high- and low-risk groups. Kaplan-Meier curves all showed an adverse prognosis for patients in the high-risk group. Cox assays confirmed that risk score was an independent prognostic factor for BRCA patients. The receiver operating characteristic (ROC) curve proved the predictive accuracy of the signature and the area under the curve (AUC) values of the risk score reached 0.722. The nomogram relatively accurately predicted the prognosis of the patients. GSEA analysis suggested that the related signaling pathways and biological processes enriched in the high- and low-risk groups may influence the tumor microenvironment (TME) of BRCA. ssGSEA showed the difference in immune cell infiltration, immune pathway activation, and immune checkpoint expression between the two risk groups, with the low-risk group more suitable for immunotherapy. According to the significant difference in IC50 between risk groups, patients can be guided for an individualized treatment plan. Overall, the authors established a prognostic signature consisting of 7 necroptosis-associated lncRNAs that can independently predict the clinical outcome of BRCA patients. The difference in the tumor immune microenvironment between the low- and high-risk populations may be the reason for the resistance to immunotherapy in some patients.

An Insight into the Novel Immunotherapy and Targeted Therapeutic Strategies for Hepatocellular Carcinoma and Cholangiocarcinoma

Hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA) constitute highly malignant forms of primary liver cancers. Hepatocellular and bile duct carcinogenesis is a multiplex process, caused by various genetic and epigenetic alterations, the influence of environmental factors, as well as the implication of the gut microbiome, which was undervalued in the previous years. The molecular and immunological analysis of the above malignancies, as well as the identification of the crucial role of intestinal microbiota for hepatic and biliary pathogenesis, opened the horizon for novel therapeutic strategies, such as immunotherapy, and enhanced the overall survival of cancer patients. Some of the immunotherapy strategies that are either clinically applied or under pre-clinical studies include monoclonal antibodies, immune checkpoint blockade, cancer vaccines, as well as the utilization of oncolytic viral vectors and Chimeric antigen, receptor-engineered T (CAR-T) cell therapy. In this current review, we will shed light on the recent therapeutic modalities for the above primary liver cancers, as well as on the methods for the enhancement and optimization of anti-tumor immunity.

Recent Advances and Next Breakthrough in Immunotherapy for Cancer Treatment

With the huge therapeutic potential, cancer immunotherapy is expected to become the mainstream of cancer treatment. In the current field of cancer immunotherapy, there are mainly five types. Immune checkpoint blockade therapy is one of the most promising directions. Adoptive cell therapy is an important component of cancer immunotherapy. The therapy with the cancer vaccine is promising cancer immunotherapy capable of cancer prevention. Cytokine therapy is one of the pillars of cancer immunotherapy. Oncolytic immunotherapy is a promising novel component of cancer immunotherapy, which with significantly lower incidence of serious adverse reactions. The recent positive results of many clinical trials with cancer immunotherapy may herald good clinical prospects. But there are still many challenges in the broad implementation of immunotherapy. Such as the immunotherapy cannot act on all tumors, and it has serious adverse effects including but not limited to nonspecific and autoimmunity inflammation. Here, we center on recent progress made within the last 5 years in cancer immunotherapy. And we discuss the theoretical background, as well as the opportunities and challenges of cancer immunotherapy.

Immunological Classification of Tumor Types and Advances in Precision Combination Immunotherapy

Immunity is an important physiological function acquired throughout evolution as a defense system against the invasion of pathogenic microorganisms. The immune system also eliminates senescent cells and maintains homeostasis, monitoring cell mutations and preventing tumor development via the action of the immune cells and molecules. Immunotherapy often relies on the interaction of immune cells with the tumor microenvironment (TME). Based on the distribution of the number of lymphocytes (CD3 and CD8) in the center and edge of the tumor and the expression level of B7-H1/PD-L1, tumors are divided into hot tumors, cold tumors, and intermediate tumors (including immune-suppressed and isolated). This review focuses on the advances in precision combination immunotherapy, which has been widely explored in recent years, and its application in different tumor types.

Systematic evaluation of the prognostic and immunological role of PDLIM2 across 33 cancer types

The protein PDLIM2 regulates the stability of various transcription factors and is required for polarized cell migration. However, the clinical relevance and immune infiltration of PDLIM2 in cancer are not well-understood. We utilized The Cancer Genome Atlas and Genotype-Tissue Expression database to characterize alterations in PDLIM2 in pan-cancer. TIMER was used to explore PDLIM2 expression and immune infiltration levels. We assessed the correlation between PDLIM2 expression and immune-associated gene expression, immune score, tumor mutation burden, and DNA microsatellite instability. PDLIM2 significantly affected the prognosis of various cancers. Increased expression of PDLIM2 was significantly correlated with the tumor grade in seven types of tumors. The expression level of PDLIM2 was positively correlated with immune infiltrates, including B cells, CD8+ T cells, CD4+ T cells, neutrophils, macrophages, and dendritic cells in bladder urothelial, kidney renal papillary cell, and colon adenocarcinoma. High expression levels of PDLIM2 tended to be associated with higher immune and stromal scores. PDLIM2 expression was associated with the tumor mutation burden in 12 cancer types and microsatellite instability in 5 cancer types. PDLIM2 levels were strongly correlated with diverse immune-related genes. PDLIM2 can act as a prognostic-related therapeutic target and is correlated with immune infiltrates in pan-cancer.

Anlotinib Enhances the Antitumor Activity of High-Dose Irradiation Combined with Anti-PD-L1 by Potentiating the Tumor Immune Microenvironment in Murine Lung Cancer

Background. Radioimmunotherapy has become one of the most promising strategies for cancer treatment. Preclinical and clinical studies have demonstrated that antiangiogenic therapy can improve the efficacy of immunotherapy and sensitize radiotherapy through a variety of mechanisms. However, it is undefined whether angiogenesis inhibitors can enhance the effect of radioimmunotherapy. In this study, we aim to explore the role of anlotinib (AL3818) on the combination of radiotherapy and immune checkpoint inhibitors in Lewis lung carcinoma mouse. Methods. C57BL/6 mouse subcutaneous tumor model was used to evaluate the ability of different treatment regimens in tumor growth control. Immune response and immunophenotyping including the quantification and activation were determined by flow cytometry, multiplex immunofluorescence, and multiplex immunoassay. Results. Triple therapy (radiotherapy combined with anti-PD-L1 and anlotinib) increased tumor-infiltrating lymphocytes and reversed the immunosuppressive effect of radiation on the tumor microenvironment in mouse model. Compared with radioimmunotherapy, the addition of anlotinib also boosted the infiltration of CD8+ T cells and M1 cells and caused a decrease in the number of MDSCs and M2 cells in mice. The levels of IFN-gamma and IL-18 were the highest in the triple therapy group, while the levels of IL-23, IL-13, IL-1 beta, IL-2, IL-6, IL-10, and Arg-1 were significantly reduced. NF-κB, MAPK, and AKT pathways were downregulated in triple therapy compared with radioimmunotherapy. Thus, the tumor immune microenvironment was significantly improved. As a consequence, triple therapy displayed greater benefit in antitumor efficacy. Conclusion. Our findings indicate that anlotinib might be a potential synergistic treatment for radioimmunotherapy to achieve better antitumor efficacy in NSCLC patients by potentiating the tumor immune microenvironment.

Association of a Novel Prognosis Model with Tumor Mutation Burden and Tumor-Infiltrating Immune Cells in Thyroid Carcinoma

Although immunotherapy has recently demonstrated a substantial promise in treating advanced thyroid carcinoma (THCA), it is not appropriate for all THCA patients. As a result, this study aims to identify biomarkers for predicting immunotherapy efficacy and prognosis in THCA patients based on a constructed prognostic model. The transcriptomic and corresponding clinical data of THCA patients were obtained from the Cancer Genome Atlas (TCGA) database. We identified differentially expressed genes (DEGs) between THCA and normal samples and performed an intersection analysis of DEGs with immune-related genes (IRGs) downloaded from the ImmPort database. Functional enrichment analysis was performed on the chosen immune-related DEGs. Subsequently, Cox and LASSO regression analyses were conducted to obtain three hub immune-related DEGs, including PPBP, SEMA6B, and GCGR. Following that, a prognostic risk model was established and validated based on PPBP, SEMA6B, and GCGR genes to predict immunotherapy efficacy and THCA prognosis. Finally, we investigated the association between the constructed risk model and tumor mutational burden (TMB), abundance of tumor-infiltrating immune cells (TICs) as well as immunotherapeutic targets (PDL-1, PD-1, and CTLA4) in THCA. THCA patients in the high-risk score (RS) group showed higher TMB levels and worse prognosis than the low RS group. Patients in the high-RS group had higher proportions of monocytes, M2 macrophages, and activated dendritic cells, whereas those in the low-RS group exhibited higher numbers of M1 macrophages and dendritic resting cells. Our data implied that the constructed THCA prognostic model was sound and we concluded that the THCA patients having high TMB and low PD-L1 expression levels might respond poorly to immunotherapy. Taken together, we constructed a novel prognostic model for THCA patients to predict their prognosis and immunotherapy efficacy, providing a viable option for the future management of THCA patients in the clinic.

Improving the ability of CAR-T cells to hit solid tumors: Challenges and strategies

Chimeric antigen receptor T cell (CAR-T) therapy is a late-model of immune cell therapy that has been shown to be effective in refractory/recurrent B-cell leukemia and lymphoma. Compared with the traditional anti-tumor methods, CAR-T cell therapy has the advantages of higher specificity, stronger lethality and longer-lasting efficacy. Although CAR-T cells have made significant progress in the treatment of hematologic malignancies, diverse difficulties remain in the treatment of solid tumors, including immune escape due to tumor antigen heterogeneity, preventing entry or limiting the persistence of CAR-T cells by physical or cytokine barriers and along with other immunosuppressive molecule and cells in the tumor microenvironment (TME). Otherwise, the intracellular signaling of CAR also impact on CAR-T cells persistence. Appropriate modification of intracellular costimulatory molecular signal in the structure of CAR or coexpression of CAR and cytokines can provide a way to enhance CAR-T cells activity. Additionally, CAR-T cells dysfunction due to T cell exhaustion is associated with multi-factors, especially transcription factors, such as c-Jun, NR4A. Engineering CAR-T cells to coexpress or knockout transcription factors in favor of T_CM memory CAR-T cells differentiation was proved to prolonged the survival of CAR-T cells. Finally, combination of CAR-T cells with oncolytic viruses, nanoparticles or immune checkpoint inhibitors provides an effective measure to improve CAR-T cells function. Here, we discuss all of these advances and challenges and review promising strategies for treating solid tumors. In particular, we also highlight that CAR-T cells have enormous potential to be used in combination with other immunotherapies.

Why may citrate sodium significantly increase the effectiveness of transarterial chemoembolization in hepatocellular carcinoma?

Hepatocellular carcinoma (HCC) represents the third cause of cancer death in men worldwide, and its increasing incidence can be explained by the increasing occurrence of non-alcoholic steatohepatitis (NASH). HCC prognosis is poor, as its 5-year overall survival is approximately 18 % and most cases are diagnosed at an inoperable advanced stage. Moreover, tumor sensitivity to conventional chemotherapeutics (particularly to cisplatin-based regimen), trans-arterial chemoembolization (cTACE), tyrosine kinase inhibitors, anti-angiogenic molecules and immune checkpoint inhibitors is limited. Oncogenic signaling pathways, such as HIF-1α and RAS/PI3K/AKT, may provoke drug resistance by enhancing the aerobic glycolysis ("Warburg effect") in cancer cells. Indeed, this metabolism, which promotes cancer cell development and aggressiveness, also induces extracellular acidity. In turn, this acidity promotes the protonation of drugs, hence abrogating their internalization, since they are most often weakly basic molecules. Consequently, targeting the Warburg effect in these cancer cells (which in turn would reduce the extracellular acidification) could be an effective strategy to increase the delivery of drugs into the tumor. Phosphofructokinase-1 (PFK1) and its activator PFK2 are the main regulators of glycolysis, and they also couple the enhancement of glycolysis to the activation of key signaling cascades and cell cycle progression. Therefore, targeting this "Gordian Knot" in HCC cells would be of crucial importance. Here, we suggest that this could be achieved by citrate administration at high concentration, because citrate is a physiologic inhibitor of PFK1 and PFK2. As shown in various in vitro studies, including HCC cell lines, administration of high concentrations of citrate inhibits PFK1 and PFK2 (and consequently glycolysis), decreases ATP production, counteracts HIF-1α and PI3K/AKT signaling, induces apoptosis, and sensitizes cells to cisplatin treatment. Administration of high concentrations of citrate in animal models (including Ras-driven tumours) has been shown to effectively inhibit cancer growth, reverse cell dedifferentiation, and neutralize intratumor acidity, without apparent toxicity in animal studies. Citrate may also induce a rapid secretion of pro-inflammatory cytokines by macrophages, and it could favour the destruction of cancer stem cells (CSCs) sustaining tumor recurrence. Consequently, this "citrate strategy" could improve the tumor sensitivity to current treatments of HCC by reducing the extracellular acidity, thus enhancing the delivery of chemotherapeutic drugs into the tumor. Therefore, we propose that this strategy should be explored in clinical trials, in particular to enhance cTACE effectiveness.

LAMC2 promotes the proliferation of cancer cells and induce infiltration of macrophages in non-small cell lung cancer

Background

Non-small-cell lung cancer (NSCLC) is the most prevalent cancer worldwide. Tumor microenvironment (TME) plays a very important role in the cancer development. Thus, it is urgent to find the change of TME that contributes to NSCLC carcinogenesis and progression.

Methods

The bioinformatics analysis approach was applied to evaluate the change of TME and screen the differentially immune cells in NSCLC tissue based on The Cancer Genome Atlas (TCGA) data. Meanwhile, the association of differentially immune cells with tumor stage and prognosis of NSCLC was evaluated. Then, we screen the different expression genes between macrophages infiltration high group and low group. After that, the expression of LAMC2 was detected in 48 cases of NSCLC tissues and paired normal tissues. The function of LAMC2 was detected through cell experiments in vitro. Immunohistochemistry assay was used to detect the correlation between LAMC2 expression and macrophages infiltration in NSCLC tissue. LAMC2-related pathways were identified by gene set enrichment analysis.

Results

Compared with early stage, middle-advanced stage of NSCLC exhibited lower immune score. Macrophages were the main component of different immune cells and correlated with poor outcome. The results of immunohistochemistry indicated that the expression of LAMC2 in NSCLC tissues was higher than paired normal tissues. Down-regulation of LAMC2 inhibited the proliferation, migration and invasion of NSCLC cells in vitro. Overexpression of LAMC2 was positively associated with macrophages infiltration in NSCLC tissues. Inhibition of LAMC2 expression in NSCLC cells could reduce THP-1 infiltration, and LAMC2 protein could promote the infiltration of THP-1. The Gene Set Enrichment Analysis results showed that high expression of LAMC2 was correlated with focal adhesion and extracellular matrix receptor interaction.

Conclusions

Immune suppression and macrophages infiltration were correlated with poor outcomes in NSCLC. LAMC2 promoted macrophages infiltration and extracellular matrix remolding in NSCLC. Our studies suggested an oncogenic role of LAMC2 in NSCLC progression and it perhaps serve as a potential immune therapy target for NSCLC.

The Predictive Role of Immune Related Subgroup Classification in Immune Checkpoint Blockade Therapy for Lung Adenocarcinoma

Background: In lung adenocarcinoma (LUAD), the predictive role of immune-related subgroup classification in immune checkpoint blockade (ICB) therapy remains largely incomplete. Methods: Transcriptomics analysis was performed to evaluate the association between immune landscape and ICB therapy in lung adenocarcinoma and the associated underlying mechanism. First, the least absolute shrinkage and selection operator (LASSO) algorithm and K-means algorithm were used to identify immune related subgroups for LUAD cohort from the Cancer Genome Atlas (TCGA) database (n = 572). Second, the immune associated signatures of the identified subgroups were characterized by evaluating the status of immune checkpoint associated genes and the immune cell infiltration. Then, potential responses to ICB therapy based on the aforementioned immune related subgroup classification were evaluated via tumor immune dysfunction and exclusion (TIDE) algorithm analysis, and survival analysis and further Cox proportional hazards regression analysis were also performed for LUAD. In the end, gene set enrichment analysis (GSEA) was performed to explore the metabolic mechanism potentially responsible for immune related subgroup clustering. Additionally, two LUAD cohorts from the Gene Expression Omnibus (GEO) database were used as validation cohort. Results: A total of three immune related subgroups with different immune-associated signatures were identified for LUAD. Among them, subgroup 1 with higher infiltration scores for effector immune cells and immune checkpoint associated genes exhibited a potential response to IBC therapy and a better survival, whereas subgroup 3 with lower scores for immune checkpoint associated genes but higher infiltration scores for suppressive immune cells tended to be insensitive to ICB therapy and have an unfavorable prognosis. GSEA revealed that the status of glucometabolic reprogramming in LUAD was potentially responsible for the immune-related subgroup classification. Conclusion: In summary, immune related subgroup clustering based on distinct immune associated signatures will enable us to screen potentially responsive LUAD patients for ICB therapy before treatment, and the discovery of metabolism associated mechanism is beneficial to comprehensive therapeutic strategies making involving ICB therapy in combination with metabolism intervention for LUAD.

Immunological Markers, Prognostic Factors and Challenges Following Curative Treatments for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortalities worldwide. Patients with early-stage HCC are eligible for curative treatments, such as surgical resection, liver transplantation (LT) and percutaneous ablation. Although curative treatments provide excellent long-term survival, almost 70-80% of patients experience HCC recurrence after curative treatments. Tumor-related factors, including tumor size, number and differentiation, and underlying liver disease, are well-known risk factors for recurrence following curative therapies. Moreover, the tumor microenvironment (TME) also plays a key role in the recurrence of HCC. Many immunosuppressive mechanisms, such as an increase in regulatory T cells and myeloid-derived suppressor cells with a decrease in cytotoxic T cells, are implicated in HCC recurrence. These suppressive TMEs are also modulated by several factors and pathways, including mammalian target of rapamycin signaling, vascular endothelial growth factor, programmed cell death protein 1 and its ligand 1. Based on these mechanisms and the promising results of immune checkpoint blockers (ICBs) in advanced HCC, there have been several ongoing adjuvant studies using a single or combination of ICB following curative treatments in HCC. In this review, we strive to provide biologic and immunological markers, prognostic factors, and challenges associated with clinical outcomes after curative treatments, including resection, LT and ablation.

Oxaliplatin facilitates tumor-infiltration of T cells and natural-killer cells for enhanced tumor immunotherapy in lung cancer model

Platinum is reported to have adjuvant immune properties, whether oxaliplatin (OXA) could be utilized to synergize with anti-programmed cell death-1 (PD-1) antibody or anti-NKG2D (natural-killer group 2, member D) antibody is investigated. Subcutaneous A549 lung cancer and murine Lewis lung carcinoma (LLC) models were constructed, which were further intravenously injected with platinum-based drugs or concomitant administrated with anti-PD-1 antibody and or anti-NKG2D antibody. The tumor volume and the proportion of myeloid cells (CD45⁺CD11b⁺), CD3⁺T cells and NK (NK1.1⁺) cells were detected. The relative expression of chemokine (C-X-C motif) ligand 9 (CXCL9), CXCL10 and CXCL11 and C-X-C motif chemokine receptor 3 (CXCR3) was detected with the ELISA, western blot and flow cytometry. The three platinum drugs (cisplatin, DDP; carboplatin, CBP; OXA) showed similar effects to inhibit A549 tumor growth in immune-deficient mice. While OXA exhibited better antitumor efficacy in wild-type mice bearing LLC with downregulated myeloid cells proportion, upregulated concentration of CXCL9, CXCL10 and CXCL11, and upregulated proportion and CXCR3 expression on T cells and NK cells. OXA combined with anti-PD1 or anti-NKG2D synergistically improved tumor growth inhibition and survival. The combination of OXA to anti-PD1 and anti-NKG2D antibodies will provide the most appropriate treatment benefit. Oxaliplatin promotes T cells and NK cells infiltration through the CXCL9/10/11-CXCR3 axis to enhance anti-PD1 or anti-NKG2D immunotherapy in lung cancer.

PI3K/Akt Pathway: The Indestructible Role of a Vintage Target as a Support to the Most Recent Immunotherapeutic Approaches

Simple Summary

PI3K/Akt pathway has an impressive story as tumor marker. PI3K-dependent solid tumors have been studied for several years in order to inhibit the pathway at different levels along the signaling. Despite the highly satisfactory results obtained in vitro and in xenograft mouse tumor models, the use of PI3K/Akt inhibitors in clinical trials resulted in being not as efficient as expected. With the emerging role of the tumor microenvironment in the response to therapy and the awareness, increasing in recent years, of the necessity to army the immune system against the tumor, new opportunities have emerged for PI3K/Akt inhibitors. Here, we show that PI3K/Akt, in addition to its function as tumor marker, exerts a pivotal role as an immunomodulator. Recent studies demonstrate that PI3K/Akt pathway is crucial for the regulation of the immune system and that its inhibition in combination with immunomodulatory agents may provide a new therapeutic approach for cancer.

Abstract

Pathologic activation of PI3Ks and the subsequent deregulation of its downstream signaling pathway is among the most frequent events associated with cellular transformation, cancer, and metastasis. PI3Ks are also emerging as critical factors in regulating anti-tumor immunity by either promoting an immunosuppressive tumor microenvironment or by controlling the activity and the tumor infiltration of cells involved in the immune response. For these reasons, significant pharmaceutical efforts are dedicated to inhibiting the PI3K pathway, with the main goal to target the tumor and, at the same time, to enhance the anti-tumor immunity. Recent immunotherapeutic approaches involving the use of adoptive cell transfer of autologous genetically modified T cells or immune check-point inhibitors showed high efficacy. However, mechanisms of resistance to these kinds of therapy are emerging, due in part to the inhibition of effector T cell functions exerted by the immunosuppressive tumor microenvironment. Here, we first describe how inhibition of PI3K/Akt pathway contribute to enhance anti-tumor immunity and further discuss how inhibitors of the pathway are used in combination with different immunomodulatory and immunotherapeutic agents to improve anti-tumor efficacy.

Phytochemicals in Cancer Immune Checkpoint Inhibitor Therapy

The interaction of immune checkpoint molecules in the tumor microenvironment reduces the anti-tumor immune response by suppressing the recognition of T cells to tumor cells. Immune checkpoint inhibitor (ICI) therapy is emerging as a promising therapeutic option for cancer treatment. However, modulating the immune system with ICIs still faces obstacles with severe immunogenic side effects and a lack of response against many cancer types. Plant-derived natural compounds offer regulation on various signaling cascades and have been applied for the treatment of multiple diseases, including cancer. Accumulated evidence provides the possibility of efficacy of phytochemicals in combinational with other therapeutic agents of ICIs, effectively modulating immune checkpoint-related signaling molecules. Recently, several phytochemicals have been reported to show the modulatory effects of immune checkpoints in various cancers in in vivo or in vitro models. This review summarizes druggable immune checkpoints and their regulatory factors. In addition, phytochemicals that are capable of suppressing PD-1/PD-L1 binding, the best-studied target of ICI therapy, were comprehensively summarized and classified according to chemical structure subgroups. It may help extend further research on phytochemicals as candidates of combinational adjuvants. Future clinical trials may validate the synergetic effects of preclinically investigated phytochemicals with ICI therapy.

Recent advances in the role of Th17/Treg cells in tumor immunity and tumor therapy

Th17 and Treg cells play an important role in regulating tissue inflammation and maintaining the stability of the immune system. They regulate inflammatory responses, participate in the occurrence and development of autoimmune diseases and tumors, and determine the disease progress. Malignant tumor is one of the diseases with the highest mortality rate in the world. However, the efficacy of traditional treatment is limited, so it is necessary to find safe and efficient treatment methods. Studies have shown that the balance of Th17/Treg cells plays a critical role in tumor progression. In this paper, we review the antitumor and tumor-suppressing effects of Th17/Treg cells, and new strategies for tumor therapy, combined with new research hotspots such as immune checkpoint therapy, miRNA-related gene therapy, and metabolic pathway regulation of Th17/Treg cell differentiation and tumor generation. The synergistic therapy is expected to be widely used in the future clinical practice, providing a new choice for the prevention and treatment of malignant tumors.

Discovery of IACS-9779 and IACS-70465 as Potent Inhibitors Targeting Indoleamine 2,3-Dioxygenase 1 (IDO1) Apoenzyme

Indoleamine 2,3-dioxygenase 1 (IDO1), a heme-containing enzyme that mediates the rate-limiting step in the metabolism of l-tryptophan to kynurenine, has been widely explored as a potential immunotherapeutic target in oncology. We developed a class of inhibitors with a conformationally constrained bicyclo[3.1.0]hexane core. These potently inhibited IDO1 in a cellular context by binding to the apoenzyme, as elucidated by biochemical characterization and X-ray crystallography. A SKOV3 tumor model was instrumental in differentiating compounds, leading to the identification of IACS-9779 (62) and IACS-70465 (71). IACS-70465 has excellent cellular potency, a robust pharmacodynamic response, and in a human whole blood assay was more potent than linrodostat (BMS-986205). IACS-9779 with a predicted human efficacious once daily dose below 1 mg/kg to sustain >90% inhibition of IDO1 displayed an acceptable safety margin in rodent toxicology and dog cardiovascular studies to support advancement into preclinical safety evaluation for human development.

Hypoxia in Lung Cancer Management: A Translational Approach

Simple Summary

Hypoxia is a common feature of lung cancers. Nonetheless, no guidelines have been established to integrate hypoxia-associated biomarkers in patient management. Here, we discuss the current knowledge and provide translational novel considerations regarding its clinical detection and targeting to improve the outcome of patients with non-small-cell lung carcinoma of all stages.

Abstract

Lung cancer represents the first cause of death by cancer worldwide and remains a challenging public health issue. Hypoxia, as a relevant biomarker, has raised high expectations for clinical practice. Here, we review clinical and pathological features related to hypoxic lung tumours. Secondly, we expound on the main current techniques to evaluate hypoxic status in NSCLC focusing on positive emission tomography. We present existing alternative experimental approaches such as the examination of circulating markers and highlight the interest in non-invasive markers. Finally, we evaluate the relevance of investigating hypoxia in lung cancer management as a companion biomarker at various lung cancer stages. Hypoxia could support the identification of patients with higher risks of NSCLC. Moreover, the presence of hypoxia in treated tumours could help clinicians predict a worse prognosis for patients with resected NSCLC and may help identify patients who would benefit potentially from adjuvant therapies. Globally, the large quantity of translational data incites experimental and clinical studies to implement the characterisation of hypoxia in clinical NSCLC management.

First-Line Treatment Options for PD-L1-Negative Non-Small Cell Lung Cancer: A Bayesian Network Meta-Analysis

Background

First-line treatment strategies for programmed death-ligand 1 (PD-L1) negative non-small cell lung cancer (NSCLC) patients include chemotherapy and combination with anti-angiogenesis drugs and/or immune checkpoint inhibitor. We conducted a Bayesian network meta-analysis to evaluate the efficacy of these therapeutic options.

Methods

We included phase III randomized controlled trials comparing two or more treatments in the first-line setting for NSCLC, including data in PD-L1–negative patients. First-line strategies were compared and ranked based on the effectiveness in terms of overall survival (OS) and progression-free survival (PFS). A rank was assigned to each treatment after Markov Chain Monte Carlo analyses.

Results

Fourteen trials involving 14 regimens matched our eligibility criteria. For OS, none of the treatment were significantly more effective than chemotherapy. Nivolumab plus ipilimumab plus chemotherapy was probably the best option based on analysis of the treatment ranking (probability = 30.1%). For PFS, nivolumab plus chemotherapy plus bevacizumab, atezolizumab plus chemotherapy plus bevacizumab, and atezolizumab plus chemotherapy were statistically superior to chemotherapy in pairwise comparison. Nivolumab plus chemotherapy plus bevacizumab was likely to be the preferred option based on the analysis of the treatment ranking (probability = 72.9%).

Conclusions

Nivolumab plus chemotherapy, in combination with angiogenesis inhibition or anti-cytotoxic T-lymphocyte–associated antigen 4 (CTLA-4), had maximal benefits for NSCLC patient of PD-L1–negative expression. These findings may facilitate individualized treatment strategies. Safety at an individual patient level should be considered in decision making. Further validation is warranted.

Metabolic regulation in the immune response to cancer

Metabolic reprogramming in tumor‐immune interactions is emerging as a key factor affecting pro‐inflammatory carcinogenic effects and anticancer immune responses. Therefore, dysregulated metabolites and their regulators affect both cancer progression and therapeutic response. Here, we describe the molecular mechanisms through which microenvironmental, systemic, and microbial metabolites potentially influence the host immune response to mediate malignant progression and therapeutic intervention. We summarized the primary interplaying factors that constitute metabolism, immunological reactions, and cancer with a focus on mechanistic aspects. Finally, we discussed the possibility of metabolic interventions at multiple levels to enhance the efficacy of immunotherapeutic and conventional approaches for future anticancer treatments.

A prognostic model based on seven immune-related genes predicts the overall survival of patients with hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC such as progression, recurrence, and metastasis, and some have discussed using it as a weapon against a variety of cancers. However, the impact of immune-related genes (IRGs) on the prognosis of HCC remains unclear.

METHODS

Based on The Cancer Gene Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort) datasets, we integrated the ribonucleic acid (RNA) sequencing profiles of 424 HCC patients with IRGs to calculate immune-related differentially expressed genes (DEGs). Survival analysis was used to establish a prognostic model of survival- and immune-related DEGs. Based on genomic and clinicopathological data, we constructed a nomogram to predict the prognosis of HCC patients. Gene set enrichment analysis further clarified the signalling pathways of the high-risk and low-risk groups constructed based on the IRGs in HCC. Next, we evaluated the correlation between the risk score and the infiltration of immune cells, and finally, we validated the prognostic performance of this model in the GSE14520 dataset.

RESULTS

A total of 100 immune-related DEGs were significantly associated with the clinical outcomes of patients with HCC. We performed univariate and multivariate least absolute shrinkage and selection operator (Lasso) regression analyses on these genes to construct a prognostic model of seven IRGs (Fatty Acid Binding Protein 6 (FABP6), Microtubule-Associated Protein Tau (MAPT), Baculoviral IAP Repeat Containing 5 (BIRC5), Plexin-A1 (PLXNA1), Secreted Phosphoprotein 1 (SPP1), Stanniocalcin 2 (STC2) and Chondroitin Sulfate Proteoglycan 5 (CSPG5)), which showed better prognostic performance than the tumour/node/metastasis (TNM) staging system. Moreover, we constructed a regulatory network related to transcription factors (TFs) that further unravelled the regulatory mechanisms of these genes. According to the median value of the risk score, the entire TCGA cohort was divided into high-risk and low-risk groups, and the low-risk group had a better overall survival (OS) rate. To predict the OS rate of HCC, we established a gene- and clinical factor-related nomogram. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve showed that this model had moderate accuracy. The correlation analysis between the risk score and the infiltration of six common types of immune cells showed that the model could reflect the state of the immune microenvironment in HCC tumours.

CONCLUSION

Our IRG prognostic model was shown to have value in the monitoring, treatment, and prognostic assessment of HCC patients and could be used as a survival prediction tool in the near future.

Metabolic Factors Affecting Tumor Immunogenicity: What Is Happening at the Cellular Level?

Immunotherapy has changed the treatment paradigm in multiple solid and hematologic malignancies. However, response remains limited in a significant number of cases, with tumors developing innate or acquired resistance to checkpoint inhibition. Certain "hot" or "immune-sensitive" tumors become "cold" or "immune-resistant", with resultant tumor growth and disease progression. Multiple factors are at play both at the cellular and host levels. The tumor microenvironment (TME) contributes the most to immune-resistance, with nutrient deficiency, hypoxia, acidity and different secreted inflammatory markers, all contributing to modulation of immune-metabolism and reprogramming of immune cells towards pro- or anti-inflammatory phenotypes. Both the tumor and surrounding immune cells require high amounts of glucose, amino acids and fatty acids to fulfill their energy demands. Thus, both compete over one pool of nutrients that falls short on needs, obliging cells to resort to alternative adaptive metabolic mechanisms that take part in shaping their inflammatory phenotypes. Aerobic or anaerobic glycolysis, oxidative phosphorylation, tryptophan catabolism, glutaminolysis, fatty acid synthesis or fatty acid oxidation, etc. are all mechanisms that contribute to immune modulation. Different pathways are triggered leading to genetic and epigenetic modulation with consequent reprogramming of immune cells such as T-cells (effector, memory or regulatory), tumor-associated macrophages (TAMs) (M1 or M2), natural killers (NK) cells (active or senescent), and dendritic cells (DC) (effector or tolerogenic), etc. Even host factors such as inflammatory conditions, obesity, caloric deficit, gender, infections, microbiota and smoking status, may be as well contributory to immune modulation, anti-tumor immunity and response to immune checkpoint inhibition. Given the complex and delicate metabolic networks within the tumor microenvironment controlling immune response, targeting key metabolic modulators may represent a valid therapeutic option to be combined with checkpoint inhibitors in an attempt to regain immune function.

Is There a Place for Immune Checkpoint Inhibitors in Vulvar Neoplasms? A State of the Art Review

Vulvar cancer (VC) is a rare neoplasm, usually arising in postmenopausal women, although human papilloma virus (HPV)-associated VC usually develop in younger women. Incidences of VCs are rising in many countries. Surgery is the cornerstone of early-stage VC management, whereas therapies for advanced VC are multimodal and not standardized, combining chemotherapy and radiotherapy to avoid exenterative surgery. Randomized controlled trials (RCTs) are scarce due to the rarity of the disease and prognosis has not improved. Hence, new therapies are needed to improve the outcomes of these patients. In recent years, improved knowledge regarding the crosstalk between neoplastic and tumor cells has allowed researchers to develop a novel therapeutic approach exploiting these molecular interactions. Both the innate and adaptive immune systems play a key role in anti-tumor immunesurveillance. Immune checkpoint inhibitors (ICIs) have demonstrated efficacy in multiple tumor types, improving survival rates and disease outcomes. In some gynecologic cancers (e.g., cervical cancer), many studies are showing promising results and a growing interest is emerging about the potential use of ICIs in VC. The aim of this manuscript is to summarize the latest developments in the field of VC immunoncology, to present the role of state-of-the-art ICIs in VC management and to discuss new potential immunotherapeutic approaches.

A novel immune-related genes prognosis biomarker for hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is closely associated with the immune microenvironment. To identify the effective population before administering treatment, the establishment of prognostic immune biomarkers is crucial for early HCC diagnosis and treatment.

RESULTS

A total of 335 IRGs identified from 788 overlapping IRGs were associated with the survival of HCC. A prognostic immunoscore model was identified. The Kaplan-Meier survival curves and time-dependent ROC analysis revealed a powerful prognostic performance of immunoscore signature via multi validation. Besides, the immunoscore signature exhibited a better predictive power compared to other prognostic signatures. Gene set enrichment analysis showed multiple signaling differences between the high and low immunoscore group. Furthermore, immunoscore was significantly associated with multiple immune cells and immune infiltration in the tumor microenvironment.

CONCLUSIONS

We identified the immunoscore as a robust marker for predicting HCC patient survival.

METHODS

Three sets of immune-related genes (IRGs) were integrated to identify the overlapping IRGs. Weighted gene co-expression network analysis was performed to obtain the survival-related IRGs. Further, the prognostic immunoscore model was constructed via LASSO-penalized Cox regression analysis. Then the prognostic performance of immunoscore was evaluated. In addition, ESTIMATE and CIBERSORT algorithms were applied to explore the relationship between immunoscore and tumor immune microenvironment.

Development and Validation of a Novel 8 Immune Gene Prognostic Signature Based on the Immune Expression Profile for Hepatocellular Carcinoma

Background

The immune microenvironment plays a vital role in the development of hepatocellular carcinoma (HCC). This study explored novel immune-related biomarkers to predict the prognosis of patients with HCC.

Methods

RNA-Seq data were downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression was used to identify prognosis-related genes; the Lasso method was used to construct the prognosis risk model. Validation was performed on the International Cancer Genome Consortium (ICGC) cohort, and the C-index was calculated to evaluate its overall predictive performance. Western blots were conducted to evaluate the expression of genes.

Results

There were 320 immune-related genes, 40 of which were significantly related to prognosis. Eight immune gene signatures (CKLF, IL12A, CCL20, PRELID1, GLMN, ACVR2A, CD7, and FYN) were established by Lasso Cox regression analysis. This immune signature performed well in different cohorts and can be an independent risk factor for prognosis. In addition, the overall predictive performance of this model was higher than the other models reported previously.

Conclusion

The predictive immune model will enable patients with HCC to be more accurately managed in immunotherapy.