Immunotherapy in multiple myeloma

Identification of HIST1H2BH as the hub gene associated with multiple myeloma using integrated bioinformatics analysis

OBJECTIVES

Identifying the specific biomarkers and molecular signatures of MM might provide novel evidence for MM prognosis and targeted therapy.

METHODS

Bioinformatic analyses were performed through GEO and TCGA datasets. The differential expression of HIST1H2BH in MM sample was validated by the qRT-PCR. And the CCK-8 assay was performed to detect the proliferation activity of HIST1H2BH on MM cell lines.

RESULTS

A total of 793 DEGs were identified between bone marrow plasma cells from newly diagnosed myeloma and normal donors in GSE6477. Among them, four vital genes (HIST1H2AC, HIST1H2BH, CCND1 and TCF7L2) modeling were constructed. The increased HIST1H2BH expression was correlated with worse survival of MM based on TCGA datasets. The transcriptional expression of HIST1H2BH was significantly up-regulated in primary MM patients. And knockdown HIST1H2BH decreased the proliferation of MM cell lines.

CONCLUSIONS

We have identified up-regulated HIST1H2BH in MM patients associated with poor prognosis using integrated bioinformatical methods.

CAR T therapies in multiple myeloma: unleashing the future

In recent years, the field of cancer treatment has witnessed remarkable breakthroughs that have revolutionized the landscape of care for cancer patients. While traditional pillars such as surgery, chemotherapy, and radiation therapy have long been available, a cutting-edge therapeutic approach called CAR T-cell therapy has emerged as a game-changer in treating multiple myeloma (MM). This novel treatment method complements options like autologous stem cell transplants and immunomodulatory medications, such as proteasome inhibitors, by utilizing protein complexes or anti-CD38 antibodies with potent complement-dependent cytotoxic effects. Despite the challenges and obstacles associated with these treatments, the recent approval of the second FDA multiple myeloma CAR T-cell therapy has sparked immense promise in the field. Thus far, the results indicate its potential as a highly effective therapeutic solution. Moreover, ongoing preclinical and clinical trials are exploring the capabilities of CAR T-cells in targeting specific antigens on myeloma cells, offering hope for patients with relapsed/refractory MM (RRMM). These advancements have shown the potential for CAR T cell-based medicines or combination therapies to elicit greater treatment responses and minimize side effects. In this context, it is crucial to delve into the history and functions of CAR T-cells while acknowledging their limitations. We can strategize and develop innovative approaches to overcome these barriers by understanding their challenges. This article aims to provide insights into the application of CAR T-cells in treating MM, shedding light on their potential, limitations, and strategies employed to enhance their efficacy.

Immune Therapies in AL Amyloidosis-A Glimpse to the Future

Light-chain (AL) amyloidosis is a rare plasma cell disorder characterized by the deposition of misfolded immunoglobulin light chains in target organs, leading to multi-organ dysfunction. Treatment approaches have historically mirrored but lagged behind those of multiple myeloma (MM). Recent advancements in MM immunotherapy are gradually being evaluated and adopted in AL amyloidosis. This review explores the current state of immunotherapeutic strategies in AL amyloidosis, including monoclonal antibodies, antibody-drug conjugates, bispecific antibodies, and chimeric antigen receptor T-cell therapy. We discuss the unique challenges and prospects of these therapies in AL amyloidosis, including the exposure of frail AL amyloidosis patients to immune-mediated toxicities such as cytokine release syndrome (CRS) and immune effector-cell-associated neurotoxicity syndrome (ICANS), as well as their efficacy in promoting rapid and deep hematologic responses. Furthermore, we highlight the need for international initiatives and compassionate programs to provide access to these promising therapies and address critical unmet needs in AL amyloidosis management. Finally, we discuss future directions, including optimizing treatment sequencing and mitigating toxicities, to improve outcomes for AL amyloidosis patients.

Role of Immune Cells and Immunotherapy in Multiple Myeloma

The clinical signs of multiple myeloma, a plasma cell (PC) dyscrasia, include bone loss, renal damage, and paraproteinemia. It can be defined as the uncontrolled growth of malignant PCs within the bone marrow. The distinctive bone marrow milieu that regulates the progression of myeloma disease involves interactions between plasma and stromal cells, and myeloid and lymphoid cells. These cells affect the immune system independently or because of a complicated web of interconnections, which promotes disease development and immune evasion. Due to the importance of these factors in the onset of disease, various therapeutic strategies have been created that either target or improve the immunological processes that influence disease progression. The immune system has a role in the mechanism of action of multiple myeloma treatments. The main contributions of immune cells to the bone marrow microenvironment, as well as how they interact and how immune regulation might lead to therapeutic effects, are covered in this study.

Efficacy of PD-1 Inhibitors in First-Line Treatment for Advanced Gastroesophageal Junction and Gastric Cancer by Subgroups: A Systematic Review and Meta-Analysis

BACKGROUND

PD-1 inhibitors have been approved for the first-line treatment of patients with advanced gastric cancer, gastroesophageal junction cancer, or esophageal adenocarcinoma. However, the results of several clinical trials are not entirely consistent, and the dominant population of first-line immunotherapy for advanced gastric/gastroesophageal junction cancer still needs to be precisely determined.

OBJECTIVE

This objective of this study is to evaluate the efficacy of anti-PD-1/PD-L1 therapy in advanced gastric/gastroesophageal junction adenocarcinoma patients through a systematic review and meta-analysis of relevant clinical trials.

METHOD

The PubMed, Embase, and Cochrane Library electronic databases were searched up to August 1, 2022, for clinical trials of anti-PD-1/PD-L1 immunotherapy for the first-line treatment of advanced gastroesophageal cancer. Hazard ratios and 95% confidence intervals for overall survival, progression-free survival, and objective response rates were extracted and pooled for meta-analysis. Prespecified subgroups included the following: agent type, PD-L1 expression, and high microsatellite instability.

RESULTS

This study analyzed 5 RCTs involving 3,355 patients. Compared with the chemotherapy group, the combined immunotherapy group had a significantly higher objective response rate (OR = 0.63, 95% CI: 0.55-0.72, p < 0.00001) and prolonged overall survival (HR = 0.82, 95% CI: 0.76-0.88, p < 0.00001) and progression-free survival (HR = 0.75, 95% CI: 0.69-0.82, p < 0.00001). The combination of immunotherapy and chemotherapy prolonged OS in both MSI-H (HR = 0.38, p = 0.002) and MSS (HR = 0.78, p < 0.00001) populations, but there was a significant difference between groups (p = 0.02). However, in improving ORR, the benefit of ICI combined with chemotherapy in the MSS group and MSI-H group was not significantly different between groups (p = 0.52). Combination therapy with ICIs was more effective than chemotherapy alone in prolonging OS in the subgroup with a high CPS, regardless of the CPS cutoff for PD-L1. However, when the cutoff of CPS was 1, the difference between subgroups did not reach statistical significance (p = 0.12), while the benefit ratio of the MSI-H group was higher when the cutoff was 10 (p = 0.004) than when the cutoff value was 5 (p = 0.002).

CONCLUSIONS

For first-line treatment of advanced gastroesophageal cancer, an ICI combination strategy is more effective than chemotherapy. The subgroup of patients with a CPS ≥10 has a more significant benefit, and CPS ≥10 has the potential to be used as an accurate marker of the dominant population of immuno-combined therapy.

Estrogen-related genes influence immune cell infiltration and immunotherapy response in Hepatocellular Carcinoma

Background

Immunotherapy has been the first-line treatment option in advanced Hepatocellular Carcinoma(HCC); but now, there are no established molecular markers that can predict immunotherapy response. Estrogen has a crucial role in the development of a variety of liver illnesses, including liver fibrosis, Nonalcoholic fatty liver disease (NAFLD), and HCC. Nonetheless, the significance of estrogen-related genes in HCC immunotherapy and the underlying molecular mechanisms are not yet fully understood.

Method

In this study, we constructed a novel estrogen-related gene prognostic signature (ERGPS) by analyzing bulk RNA sequencing data from 365 HCC patients. Based on the median risk score, we divided 365 HCC patients into low- and high-risk groups. Tumor mutation burden (TMB), Microsatellite instability (MSI), T cell receptor (TCR) richness, B cell receptor (BCR) richness, single-nucleotide variants (SNV) Neoantigens, Cancer Testicular Antigens (CTA) scores, and Tumour Immune Dysfunction and Exclusion (TIDE) scores were used to evaluate the magnitude of immunotherapy response. Multiple external datasets validate the validity and robustness of the prognostic signature. Real-time quantitative polymerase chain reaction (qRT-PCR) was used to validate estrogen-related gene overexpression in HCC tissue samples.

Results

ERGPS is an independent risk factor affecting the prognosis of HCC patients and is superior to other clinical variables in predicting patient survival and immunotherapy response. Multiple independent external datasets confirmed the superior predictive efficacy of the prognostic signature. The prognostic signature was positively correlated with TMB score, MSI score, TCR richness, BCR richness, SNV Neoantigens score, CTA score, expression levels of immune checkpoint-related genes, and TIDE score. Patients with HCC in the high-risk group identified by the prognostic signature were likely to be more responsive to immunotherapy and more suitable for immunotherapy. qRT-PCR confirmed that estrogen-related genes of the construct signature were highly expressed in HCC tumor tissues.

Conclusion

Estrogen-related genes are overexpressed in HCC tissues. Our novel prognostic signature can accurately predict not only the prognosis but also the immunotherapy response of HCC patients. In the future, prognostic signatures will be a useful tool for clinicians to screen patients with HCC who are suitable for immunotherapy.

Gamma Delta T Cells: Role in Immunotherapy of Hepatocellular Carcinoma

The most typical type of liver cancer or hepatocellular carcinoma (HCC) develops from hepatocyte loss. Non-alcoholic fatty liver disease (NAFLD), viral hepatitis C and cirrhosis are the leading causes of HCC. With the Hepatitis B vaccine and medicines, there are several treatments for HCC, including liver resection, ablation, transplantation, immunotherapy, gene therapy, radiation embolization, and targeted therapy. Currently, a wide range of studies are carried out on gene therapy to identify biomarkers and pathways, which help us identify the exact stage of the disorder and reduce its effects. γδT cells have recently received much interest as a potential cancer treatment method in adaptive immunotherapy. γδT cells can quickly form connections between receptor and ligand activation. They can clonally expand and are a significant source of cytokines and chemokines. The present review provides a comprehensive understanding on the function of γδT cells in immunotherapies and how they are used to treat HCC.

m5C Regulator-mediated methylation modification clusters contribute to the immune microenvironment regulation of multiple myeloma

Background: Multiple myeloma (MM) is a hematological malignancy in which plasma cells proliferate abnormally. 5-methylcytosine (m5C) methylation modification is the primary epigenetic modification and is involved in regulating the occurrence, development, invasion, and metastasis of various tumors; however, its immunological functions have not been systematically described in MM. Thus, this study aimed to clarify the significance of m5C modifications and how the immune microenvironment is linked to m5C methylation in MM.

Method: A total of 483 samples (60 healthy samples, 423 MM samples) from the Gene Expression Omnibus dataset were acquired to assess the expression of m5C regulators. A nomogram model was established to predict the occurrence of MM. We investigated the impact of m5C modification on immune microenvironment characteristics, such as the infiltration of immunocytes and immune response reactions. We then systematically evaluated three different m5C expression patterns to assess immune characteristics and metabolic functional pathways and established m5C-related differentially expressed genes (DEGs). In addition, biological process analysis was performed and an m5C score was constructed to identify potentially significant immunological functions in MM.

Result: Differential expressions of m5C regulators were identified between healthy and MM samples. The nomogram revealed that m5C regulators could predict higher disease occurrence of MM. We identified three distinct m5C clusters with unique immunological and metabolic characteristics. Among the three different m5C clusters, cluster C had more immune characteristics and more metabolism-related pathways than clusters A and B. We analyzed 256 m5C-related DEGs and classified the samples into three different m5C gene clusters. Based on the m5C and m5C gene clusters, we calculated m5C scores and classified each patient into high- and low-m5C score groups.

Conclusion: Our study demonstrated that m5C modification is involved in and contributes to the diversity and complexity of the immune microenvironment, which offers promise for the development of accurate therapeutic strategies.

EMT-Related Gene Signature Predicts the Prognosis in Uveal Melanoma Patients

Background. Uveal melanoma (UVM) is the most common primary intraocular malignancy in adults. Epithelial-mesenchymal transition (EMT) is an essential regulator of the UVM’s immune microenvironment. However, the precise role of EMT in UVM remains to be explored and the development of a related treatment strategy is urgently needed. Methods. Multiomics data and clinical information for TCGA-UVM were used to identify the EMT subtypes and analyze their regulatory role in the immune microenvironment in UVM. A machine-learning method based on the identified subtypes was utilized to construct the EMT feature-based prognostic model. External validation cohorts GSE84976 and GSE22138 were employed to validate the model’s robustness. Immunotherapy cohort IMvigor210 was used to explore the model’s potential to predict immunotherapy responsiveness. Results. Two EMT subtypes were identified in UVM. The role of EMT in shaping the immune microenvironment and regulating cancer-immunity circle of UVM was analyzed. A robust prognostic model was presented and validated to predict patient prognosis. The model also predicted patient’s immune features and immunotherapy responsiveness. Conclusion. The EMT-mediated immune features in UVM were illustrated, providing a reliable model to facilitate precise UVM treatment. This research may assist in decision-making during clinical UVM therapy.

Identification of a Novel Risk Model: A Five-Gene Prognostic Signature for Pancreatic Cancer

Objective. Biomarkers for pancreatic cancer (PCa) prognosis provide evidence for improving the survival outcome of this disease. This study aimed to identify a prognostic risk model based on gene expression profiling of microarray bioinformatics analysis. Methods. Prognostic immune genes in the TCGA-PAAD cohort were identified using the univariate Cox regression and Kaplan–Meier survival analysis. Multivariate Cox regression (stepAIC) was used to identify prognostic genes from the top 20 hub genes in the protein-protein interaction (PPI) network. A prognostic risk model was established and its performance in predicting the overall survival in PCa was validated in GSE62452. Gene mutations and infiltration immune cells in PCa tumors were analyzed using online databases. Results. Univariate Cox regression and Kaplan–Meier survival analyses identified 128 prognostic genes. Multivariate Cox regression (stepAIC) identified five prognostic genes (PLCG1, MET, TNFSF10, CXCL9, and TLR3) out of the 20 hub genes in the PPI network. A prognostic risk model was established using the signature of five genes. This model had moderate to high accuracies (AUC > 0.700) in predicting 3-year and 5-year overall survival in TCGA and GSE62452 cohorts. The Kaplan–Meier survival analysis showed that high-risk scores were correlated with poor survival outcomes in PCa ( $p<0.05$ ). Also, mutations in the five genes were related to poor survival. The five genes were related to multiple immune cells. Conclusions. The prognostic risk model was significantly correlated with the survival in PCa patients. This model modulated PCa tumor progression and prognosis by regulating immune cell infiltration.

Which role for predictors of response to immune checkpoint inhibitors in hepatocellular carcinoma?

INTRODUCTION

Hepatocellular carcinoma (HCC) remains a frequently diagnosed malignancy worldwide, still representing an important cause of cancer-related death. Recent years have seen the emergence of novel systemic treatments for HCC patients, including immune checkpoint inhibitors (ICIs). Nonetheless, several questions regarding HCC immunotherapy remain unanswered, especially in terms of biochemical predictors of response.

AREAS COVERED

In the current paper, we will discuss available evidence regarding predictive biomarkers of response to HCC immunotherapy. A literature search was conducted in January 2022 of Pubmed/Medline, Cochrane library, and Scopus databases.

EXPERT OPINION

The identification of predictive biomarkers represents an unmet need in HCC patients receiving ICIs. The HCC medical community is called to further efforts aimed to elucidate the effective role of PD-L1 expression, TMB, MSI, gut microbiota, and other emerging biomarkers.