Indoleamine 2, 3-Dioxygenase 1 and CD8 Expression Profiling Revealed an Immunological Subtype of Colon Cancer With a Poor Prognosis

Chemo-immunotherapy by nanoliposomal epacadostat and docetaxel combination to IDO1 inhibition and tumor microenvironment suppression

The over-activation of tryptophan (Trp) metabolism to kynurenine (Kyn) catalyzed by Indoleamine 2,3-dioxygenase-1 (IDO1) enzyme, is one of the main metabolic pathways involved in tumor microenvironment (TME) immune escape and cancer treatment failure. The most efficient of IDO1 inhibitors is Epacadostat (EPA). Since monotherapy with single-agent IDO1 inhibitor regimen has led to an insufficient anti-tumor activity, we examined the efficacy of simultaneous treatment by Liposomal epacadostat (Lip-EPA) as a potent IDO inhibitor, in combination with docetaxel (DTX) as a complement immunogenic cell death (ICD) agent against B16F10 model. First, the in vitro combination index (CI) of epacadostat (EPA) and DTX was investigated by using the unified theory. Then, the in vivo efficacy of the combination therapy was assessed. Results indicated the synergestic cytotoxic effect of the combination on B16F10 compared to normal fibroblast cells (NIH). The immune profiling demonstrated a significant increase in the percentage of infiltrated T lymphocytes and IFN-γ release, a significant decrease in the percentage of regulatory T cells (Treg) population and the subsequent low levels of IL-10 generation in mice treated with Lip-EPA + DTX. Further, a significant tumor growth delay (TGD = 69.15 %) and an increased life span (ILS > 47.83 %) was observed with the combination strategy. Histopathology analysis revealed a remarkable increase in the Trp concentration following combination treatment, while Kyn levels significantly decreased. Results showed that the nano-liposomal form of IDO1 inhibitor in combination with chemotherapy could significantly improve the imunity response and dominate the tumor immuno-suppressive micro-environment, which merits further investigations.

Harnessing CD8+ T cell dynamics in hepatitis B virus-associated liver diseases: Insights, therapies and future directions

Hepatitis B virus (HBV) infection playsa significant role in the etiology and progression of liver-relatedpathologies, encompassing chronic hepatitis, fibrosis, cirrhosis, and eventual hepatocellularcarcinoma (HCC). Notably, HBV infection stands as the primary etiologicalfactor driving the development of HCC. Given the significant contribution ofHBV infection to liver diseases, a comprehensive understanding of immunedynamics in the liver microenvironment, spanning chronic HBV infection,fibrosis, cirrhosis, and HCC, is essential. In this review, we focused on thefunctional alterations of CD8+ T cells within the pathogenic livermicroenvironment from HBV infection to HCC. We thoroughly reviewed the roles ofhypoxia, acidic pH, metabolic reprogramming, amino acid deficiency, inhibitory checkpointmolecules, immunosuppressive cytokines, and the gut-liver communication in shapingthe dysfunction of CD8+ T cells in the liver microenvironment. Thesefactors significantly impact the clinical prognosis. Furthermore, we comprehensivelyreviewed CD8+ T cell-based therapy strategies for liver diseases,encompassing HBV infection, fibrosis, cirrhosis, and HCC. Strategies includeimmune checkpoint blockades, metabolic T-cell targeting therapy, therapeuticT-cell vaccination, and adoptive transfer of genetically engineered CD8+ T cells, along with the combined usage of programmed cell death protein-1/programmeddeath ligand-1 (PD-1/PD-L1) inhibitors with mitochondria-targeted antioxidants.Given that targeting CD8+ T cells at various stages of hepatitis Bvirus-induced hepatocellular carcinoma (HBV + HCC) shows promise, we reviewedthe ongoing need for research to elucidate the complex interplay between CD8+ T cells and the liver microenvironment in the progression of HBV infection toHCC. We also discussed personalized treatment regimens, combining therapeuticstrategies and harnessing gut microbiota modulation, which holds potential forenhanced clinical benefits. In conclusion, this review delves into the immunedynamics of CD8+ T cells, microenvironment changes, and therapeuticstrategies within the liver during chronic HBV infection, HCC progression, andrelated liver diseases.

High indoleamine 2,3-dioxygenase transcript levels predict better outcome after front-line cancer immunotherapy

Indoleamine 2,3-dioxygenase 1 (IDO1), which catabolizes tryptophan, is a potential target to unlock the immunosuppressive tumor microenvironment. Correlations between IDO1 and immune checkpoint inhibitor (ICI) efficacy remain unclear. Herein, we investigated IDO1 transcript expression across cancers and clinical outcome correlations. High IDO1 transcripts were more frequent in uterine (54.2%) and ovarian cancer (37.2%) but varied between and within malignancies. High IDO1 RNA expression was associated with high expression of PD-L1 (immune checkpoint ligand), CXCL10 (an effector T cell recruitment chemokine), and STAT1 (a component of the JAK-STAT pathway) (all multivariable p < 0.05). PIK3CA and CTCF alterations were more frequent in the high IDO1 group. High IDO1 expression was an independent predictor of progression-free survival (adjusted HR = 0.44, 95% CI 0.20-0.99, p = 0.049) and overall survival (adjusted HR = 0.31, 95% CI 0.11-0.87, p = 0.026) after front-line ICIs. IDO1 expression warrants further exploration as a predictive biomarker for immunotherapy. Moreover, co-expressed immunoregulatory molecules merit exploration for co-targeting.

Validation of a Proteomic-Based Prognostic Model for Breast Cancer and Immunological Analysis

Breast cancer (BC) has emerged as an extremely destructive malignancy, causing significant harm to female patients and society at large. Proteomic research holds great promise for early diagnosis and treatment of diseases, and the integration of proteomics with genomics can offer valuable assistance in the early diagnosis, treatment, and improved prognosis of BC patients. In this study, we downloaded breast cancer protein expression data from The Cancer Genome Atlas (TCGA) and combined proteomics with genomics to construct a proteomic-based prognostic model for BC. This model consists of nine proteins (HEREGULIN, IDO, PEA15, MERIT40_pS29, CIITA, AKT2, CD171 DVL3, and CABL9). The accuracy of the model in predicting the survival prognosis of BC patients was further validated through risk curve analysis, survival curve analysis, and independent prognostic analysis. We further confirmed the impact of differential expression of these nine key proteins on overall survival in BC patients, and the differential expression of the key proteins and their encoding genes was validated using immunohistochemical staining. Enrichment analysis revealed functional associations primarily related to PPAR signaling pathway, steroid hormone metabolism, chemokine signaling pathway, DNA conformation changes, immunoglobulin production, and immunoglobulin complex in the high- and low-risk groups. Immune infiltration analysis revealed differential expression of immune cells between the high- and low-risk groups, providing a theoretical basis for subsequent immunotherapy. The model constructed in this study can predict the survival of BC patients, and the identified key proteins may serve as biomarkers to aid in the early diagnosis of BC. Enrichment analysis and immune infiltration analysis provide a necessary theoretical basis for further exploration of the molecular mechanisms and subsequent immunotherapy.

Novel targets for immune-checkpoint inhibition in cancer

Immune-checkpoint inhibitors have revolutionized cancer therapy, yet many patients either do not derive any benefit from treatment or develop a resistance to checkpoint inhibitors. Intrinsic resistance can result from neoantigen depletion, defective antigen presentation, PD-L1 downregulation, immune-checkpoint ligand upregulation, immunosuppression, and tumor cell phenotypic changes. On the other hand, extrinsic resistance involves acquired upregulation of inhibitory immune-checkpoints, leading to T-cell exhaustion. Current data suggest that PD-1, CTLA-4, and LAG-3 upregulation limits the efficacy of single-agent immune-checkpoint inhibitors. Ongoing clinical trials are investigating novel immune-checkpoint targets to avoid or overcome resistance. This review provides an in-depth analysis of the evolving landscape of potentially targetable immune-checkpoints in cancer. We highlight their biology, emphasizing the current understanding of resistance mechanisms and focusing on promising strategies that are under investigation. We also summarize current results and ongoing clinical trials in this crucial field that could once again revolutionize outcomes for cancer patients.

Infiltration of a Unique CD8+CD274+ Cell Subgroup in Hepatocellular Carcinoma is Associated with Poor Clinical Outcomes

Introduction

Immune checkpoint (IC) inhibitor-related immunotherapies have attracted considerable attention in hepatocellular carcinoma (HCC). High IC expression and high tumor infiltrating lymphocyte levels are the current indicators of sensitivity to IC inhibitors. Thus, it is imperative to apply precision medicine strategies for patient selection.

Methods

Six independent HCC cohorts were used for analysis at the single-cell and tissue levels. Multiplex immunofluorescence and immunochemistry staining assays were used to validate our results. A series of methodologies were used for immune-related evaluations.

Results

Herein, we uncovered a unique CD8⁺CD274⁺ cell subpopulation that is associated with tumor progression and poor survival in HCC at the single-cell level. We assessed this subset at the tissue level and found that the prognostic significance of CD274 is dependent on CD8A expression in HCC. Subsequently, we identified a unique high-risk subpopulation that showed high CD8A expression coupled with intense CD274 expression in multiple HCC cohorts. CD8A^HighCD274^High* subgroup was correlated with malignant indexes and remained an independent prognostic factor when considering the influence of these indexes. Molecular characteristic analyses showed that the CD8A^HighCD274^High* subgroup harbored more mutations, had higher immune response activity and presented enrichment of cancer-related biological processes. Moreover, this high-risk subpopulation in HCC was characterized by high immune cell infiltration, low tumor purity, and enrichment of cancer-related signatures. Finally, cases with this phenotype demonstrated higher immunomodulator and IC levels and greater sensitivity to IC inhibitors.

Conclusion

Our findings illustrate that some HCC patients may have a poor prognosis despite high CD8⁺ T-cell infiltration. These patients would probably benefit from IC inhibitor-based combination treatment.

Indoleamine-2,3 dioxygenase: a fate-changer of the tumor microenvironment

Indoleamine-2,3 dioxygenase is a rate-limiting enzyme in the tryptophan catabolism in kynurenine pathways that has an immunosuppressive effect and supports cancer cells to evade the immune system in different cancer types. Diverse cytokines and pathways upregulate the production of indoleamine-2,3 dioxygenase enzymes in the tumor microenvironment and cause more production and activity of this enzyme. Ultimately, this situation results in anti-tumor immune suppression which is in favor of tumor growth. Several inhibitors such as 1-methyl-tryptophan have been introduced for indoleamine-2,3 dioxygenase enzyme and some of them are widely utilized in pre-clinical and clinical trials. Importantly at the molecular level, indoleamine-2,3 dioxygenase is positioned in a series of intricate signaling and molecular networks. Here, the main objective is to provide a focused view of indoleamine-2,3 dioxygenase enhancer pathways and propose further studies to cover the gap in available information on the function of indoleamine-2,3 dioxygenase enzyme in the tumor microenvironment.

Tumors of the Digestive System: Comprehensive Review of Ancillary Testing and Biomarkers in the Era of Precision Medicine

Immunotherapy has remained at the vanguard of promising cancer therapeutic regimens due to its exceptionally high specificity for tumor cells and potential for significantly improved treatment-associated quality of life compared to other therapeutic approaches such as surgery and chemoradiation. This is especially true in the digestive system, where high rates of mutation give rise to a host of targetable tumor-specific antigens. Many patients, however, do not exhibit measurable improvements under immunotherapy due to intrinsic or acquired resistance, making predictive biomarkers necessary to determine which patients will benefit from this line of treatment. Many of these biomarkers are assessed empirically by pathologists according to nuanced scoring criteria and algorithms. This review serves to inform clinicians and pathologists of extant and promising upcoming biomarkers predictive of immunotherapeutic efficacy among digestive system malignancies and the ancillary testing required for interpretation by pathologists according to tumor site of origin.

Partners in crime: The feedback loop between metabolic reprogramming and immune checkpoints in the tumor microenvironment

The tumor microenvironment (TME) is a complex and constantly changing cellular system composed of heterogeneous populations of tumor cells and non-transformed stromal cells, such as stem cells, fibroblasts, endothelial cells, pericytes, adipocytes, and innate and adaptive immune cells. Tumor, stromal, and immune cells consume available nutrients to sustain their proliferation and effector functions and, as a result of their metabolism, produce a wide array of by-products that gradually alter the composition of the milieu. The resulting depletion of essential nutrients and enrichment of by-products work together with other features of the hostile TME to inhibit the antitumor functions of immune cells and skew their phenotype to promote tumor progression. This review briefly describes the participation of the innate and adaptive immune cells in recognizing and eliminating tumor cells and how the gradual metabolic changes in the TME alter their antitumor functions. In addition, we discuss the overexpression of the immune checkpoints and their ligands as a result of nutrient deprivation and by-products accumulation, as well as the amplification of the metabolic alterations induced by the immune checkpoints, which creates an immunosuppressive feedback loop in the TME. Finally, the combination of metabolic and immune checkpoint inhibitors as a potential strategy to treat cancer and enhance the outcome of patients is highlighted.

Developing an m5C regulator-mediated RNA methylation modification signature to predict prognosis and immunotherapy efficacy in rectal cancer

Background

Currently, a very small number of patients with colorectal cancer (CRC) respond to immune checkpoint inhibitor (ICI) treatment. Therefore, there is an urgent need to investigate effective biomarkers to determine the responsiveness to ICI treatment. Recently, aberrant 5-methylcytosine (m⁵C) RNA modification has emerged as a key player in the pathogenesis of cancer. Thus, we aimed to explore the predictive signature based on m⁵C regulator-related genes for characterizing the immune landscapes and predicting the prognosis and response to therapies.

Methods

The Cancer Genome Atlas (TCGA) cohort was used as the training set, while GEO data sets, real-time quantitative PCR (RT-qPCR) analysis from paired frozen tissues, and immunohistochemistry (IHC) data from tissue microarray (TMA) were used for validation. We constructed a novel signature based on three m⁵C regulator-related genes in patients with rectal adenocarcinoma (READ) using a least absolute shrinkage and selection operator (LASSO)-Cox regression and unsupervised consensus clustering analyses. Additionally, we correlated the three-gene signature risk model with the tumor immune microenvironment, immunotherapy efficiency, and potential applicable drugs.

Results

The m⁵C methylation-based signature was an independent prognostic factor, where low-risk patients showed a stronger immunoreactivity phenotype and a superior response to ICI therapy. Conversely, the high-risk patients had enriched pathways of cancer hallmarks and presented immune-suppressive state, which demonstrated that they are more insensitive to immunotherapy. Additionally, the signature markedly correlated with drug susceptibility.

Conclusions

We developed a reliable m⁵C regulator-based risk model to predict the prognosis, clarify the molecular and tumor microenvironment status, and identify patients who would benefit from immunotherapy or chemotherapy. Our study could provide vital guidance to improve prognostic stratification and optimize personalized therapeutic strategies for patients with rectal cancer.

A novel high-risk subpopulation identified by CTSL and ZBTB7B in gastric cancer

BACKGROUND

Gastric cancer (GC) is characterised by a heterogeneous tumour microenvironment (TME) that is closely associated with the response to treatment, especially immunotherapies. However, most previous GC molecular subtyping systems need complex gene signatures and examination methods, restricting their clinical applications. Thus, we developed a new TME-based molecular subtype using only two genes.

METHODS

Nine independent GC cohorts at the tissue- or single-cell level with more than 2000 patients were used in this study, including data we examined by single-cell sequencing, quantitative RT-PCR and immunochemistry/immunofluorescence staining. Nine different methods, five existing molecular subtypes and a series of signatures were used to evaluate the TME and molecular characteristics of GC.

RESULTS

We established a CTSL/ZBTB7B subtyping system and uncovered the novel CTSLHighZBTB7BLow high-risk subgroup, but characterised by relative higher immune cell infiltration and lower tumour purity. This subgroup demonstrate higher levels of immune checkpoints and more enrichment of cancer-related pathways compared with other cases.

CONCLUSIONS

We identified a high-risk subpopulation with unique TME features based on expressions of CTSL and ZBTB7B, suggesting a counterbalancing phenotype between immunostimulatory and immunosuppressive mechanisms. This subtyping system could be used to select treatment and management strategies for GC.

Comprehensive Analysis of a Cancer-Immunity Cycle-Based Signature for Predicting Prognosis and Immunotherapy Response in Patients With Colorectal Cancer

Immune checkpoint blockade (ICB) has been recognized as a promising immunotherapy for colorectal cancer (CRC); however, most patients have little or no clinical benefit. This study aimed to develop a novel cancer-immunity cycle–based signature to stratify prognosis of patients with CRC and predict efficacy of immunotherapy. CRC samples from The Cancer Genome Atlas (TCGA) were used as the training set, while the RNA data from Gene Expression Omnibus (GEO) data sets and real-time quantitative PCR (RT-qPCR) data from paired frozen tissues were used for validation. We built a least absolute shrinkage and selection operator (LASSO)-Cox regression model of the cancer-immunity cycle–related gene signature in CRC. Patients who scored low on the risk scale had a better prognosis than those who scored high. Notably, the signature was an independent prognostic factor in multivariate analyses, and to improve prognostic classification and forecast accuracy for individual patients, a scoring nomogram was created. The comprehensive results revealed that the low-risk patients exhibited a higher degree of immune infiltration, a higher immunoreactivity phenotype, stronger expression of immune checkpoint–associated genes, and a superior response to ICB therapy. Furthermore, the risk model was closely related to the response to multiple chemotherapeutic drugs. Overall, we developed a reliable cancer-immunity cycle–based risk model to predict the prognosis, the molecular and immune status, and the immune benefit from ICB therapy, which may contribute greatly to accurate stratification and precise immunotherapy for patients with CRC.