Genomics of response to immune checkpoint therapies for cancer: implications for precision medicine

Proteome-based molecular subtyping and therapeutic target prediction in gastric cancer

Different molecular classifications for gastric cancer (GC) have been proposed based on multi-omics platforms with the long-term goal of improved precision treatment. However, the GC (phospho)proteome remains incompletely characterized, particularly at the level of tyrosine phosphorylation. In addition, previous multiomics-based stratification of patient cohorts has lacked identification of corresponding cell line models and comprehensive validation of broad or subgroup-selective therapeutic targets. To address these knowledge gaps, we applied a reverse approach, undertaking the most comprehensive (phospho)proteomic analysis of GC cell lines to date and cross-validating this using publicly available data. Mass spectrometry (MS)-based (phospho)proteomic and tyrosine phosphorylation datasets were subjected to individual or integrated clustering to identify subgroups that were subsequently characterized in terms of enriched molecular processes and pathways. Significant congruence was detected between cell line proteomic and specific patient-derived transcriptomic subclassifications. Many protein kinases exhibiting 'outlier' expression or phosphorylation in the cell line dataset exhibited genomic aberrations in patient samples and association with poor prognosis, with casein kinase I isoform delta/epsilon (CSNK1D/E) being experimentally validated as potential therapeutic targets. Src family kinases were predicted to be commonly hyperactivated in GC cell lines, consistent with broad sensitivity to the next-generation Src inhibitor eCF506. In addition, phosphoproteomic and integrative clustering segregated the cell lines into two subtypes, with epithelial-mesenchyme transition (EMT) and proliferation-associated processes enriched in one, designated the EMT subtype, and metabolic pathways, cell-cell junctions, and the immune response dominating the features of the other, designated the metabolism subtype. Application of kinase activity prediction algorithms and interrogation of gene dependency and drug sensitivity databases predicted that the mechanistic target of rapamycin kinase (mTOR) and dual specificity mitogen-activated protein kinase kinase 2 (MAP2K2) represented potential therapeutic targets for the EMT and metabolism subtypes, respectively, and this was confirmed using selective inhibitors. Overall, our study provides novel, in-depth insights into GC proteomics, kinomics, and molecular taxonomy and reveals potential therapeutic targets that could provide the basis for precision treatments.

Comparison of target agent treatment strategies for platinum-resistant recurrent ovarian cancer: A Bayesian network meta-analysis

BACKGROUND

We aimed to compare 7 newer immunotherapies and targeted therapies for platinum-resistant relapsed ovarian cancer.

METHODS

We conducted a comprehensive search of PubMed, EMBASE, and Cochrane Library electronic databases for phase III trials involving platinum-resistant recurrent ovarian cancer (PRrOC) patients treated with immunotherapy or targeted therapy in combination with chemotherapy. The quality of the included trials was assessed using the GRADE method. The primary outcome of comparison was progression-free survival, and secondary outcomes included overall survival and safety.

RESULTS

This analysis included 7 randomized phase III controlled trials, encompassing 2485 PRrOC patients. Combining bevacizumab plus chemotherapy and lurbinectedin demonstrated statistically significant differences in progression-free survival compared to all other regimens of interest. However, no statistically significant differences were observed in the overall survival. Nivolumab and mirvetuximab exhibited fewer serious adverse events than the other regimens of interest.

CONCLUSIONS

Our findings indicate that bevacizumab combined with chemotherapy and lurbinectedin monotherapy has significant efficacy in patients with PRrOC. For patients with PRrOC who have exhausted treatment options, nivolumab and mirvetuximab may be considered as alternatives because of their better safety profiles.

Determinants of gastric cancer immune escape identified from non-coding immune-landscape quantitative trait loci

The landscape of non-coding mutations in cancer progression and immune evasion is largely unexplored. Here, we identify transcrptome-wide somatic and germline 3' untranslated region (3'-UTR) variants from 375 gastric cancer patients from The Cancer Genome Atlas. By performing gene expression quantitative trait loci (eQTL) and immune landscape QTL (ilQTL) analysis, we discover 3'-UTR variants with cis effects on expression and immune landscape phenotypes, such as immune cell infiltration and T cell receptor diversity. Using a massively parallel reporter assay, we distinguish between causal and correlative effects of 3'-UTR eQTLs in immune-related genes. Our approach identifies numerous 3'-UTR eQTLs and ilQTLs, providing a unique resource for the identification of immunotherapeutic targets and biomarkers. A prioritized ilQTL variant signature predicts response to immunotherapy better than standard-of-care PD-L1 expression in independent patient cohorts, showcasing the untapped potential of non-coding mutations in cancer.

Birinapant Reshapes the Tumor Immunopeptidome and Enhances Antigen Presentation

Birinapant, an antagonist of the inhibitor of apoptosis proteins, upregulates MHCs in tumor cells and displays a better tumoricidal effect when used in combination with immune checkpoint inhibitors, indicating that Birinapant may affect the antigen presentation pathway; however, the mechanism remains elusive. Based on high-resolution mass spectrometry and in vitro and in vivo models, we adopted integrated genomics, proteomics, and immunopeptidomics strategies to study the mechanism underlying the regulation of tumor immunity by Birinapant from the perspective of antigen presentation. Firstly, in HT29 and MCF7 cells, Birinapant increased the number and abundance of immunopeptides and source proteins. Secondly, a greater number of cancer/testis antigen peptides with increased abundance and more neoantigens were identified following Birinapant treatment. Moreover, we demonstrate the existence and immunogenicity of a neoantigen derived from insertion/deletion mutation. Thirdly, in HT29 cell-derived xenograft models, Birinapant administration also reshaped the immunopeptidome, and the tumor exhibited better immunogenicity. These data suggest that Birinapant can reshape the tumor immunopeptidome with respect to quality and quantity, which improves the presentation of CTA peptides and neoantigens, thus enhancing the immunogenicity of tumor cells. Such changes may be vital to the effectiveness of combination therapy, which can be further transferred to the clinic or aid in the development of new immunotherapeutic strategies to improve the anti-tumor immune response.

Aging-related biomarker discovery in the era of immune checkpoint inhibitors for cancer patients

Older patients with cancer, particularly those over 75 years of age, often experience poorer clinical outcomes compared to younger patients. This can be attributed to age-related comorbidities, weakened immune function, and reduced tolerance to treatment-related adverse effects. In the immune checkpoint inhibitors (ICI) era, age has emerged as an influential factor impacting the discovery of predictive biomarkers for ICI treatment. These age-linked changes in the immune system can influence the composition and functionality of tumor-infiltrating immune cells (TIICs) that play a crucial role in the cancer response. Older patients may have lower levels of TIICs infiltration due to age-related immune senescence particularly T cell function, which can limit the effectivity of cancer immunotherapies. Furthermore, age-related immune dysregulation increases the exhaustion of immune cells, characterized by the dysregulation of ICI-related biomarkers and a dampened response to ICI. Our review aims to provide a comprehensive understanding of the mechanisms that contribute to the impact of age on ICI-related biomarkers and ICI response. Understanding these mechanisms will facilitate the development of treatment approaches tailored to elderly individuals with cancer.

DLGAP5 promotes lung adenocarcinoma growth via upregulating PLK1 and serves as a therapeutic target

BACKGROUND

Human discs large-associated protein 5 (DLGAP5) is reported to play a pivotal role in regulating the cell cycle and implicate in tumorigenesis and progression of various cancers. Our current research endeavored to explore the prognostic value, immune implication, biological function and targeting strategy of DLGAP5 in LUAD through approaches including bioinformatics, network pharmacology analysis and experimental study.

METHODS

Multiple databases, including TCGA, GEO, CPTAC and Human Protein Atlas, were utilized to explore the expression and clinical significance of DLGAP5 in LUAD. The genetic alterations of DLGAP5 were assessed through cBioPortal and COSMIC databases. The relationship between DLGAP5 expression and genetic abnormalities of driver genes in LUAD was analyzed through TIMER2.0 database. CancerSEA database was utilized to explore the function of DLGAP5 in 14 different states in LUAD at single-cell resolution. GDSC database was utilized to analyze the impact of DLGAP5 on IC50 of frequently-used anti-LUAD drugs. CIBERSORT method and TIMER2.0 database was utilized to explore the relationship between DLGAP5 and tumor immune infiltration. Network pharmacology was applied to screen potential DLGAP5 inhibitor. In vitro and in vivo experiments were utilized to evaluate biological function and downstream targets of DLGAP5, and the effect of screened DLGAP5 inhibitor on LUAD growth.

RESULTS

High DLGAP5 expression was commonly observed in LUAD and associated with mutation of major driver genes, poor prognosis, high IC50 values of frequently-used anti-LUAD drugs, increasing immune infiltration and elevated immune checkpoint blockade-related genes in LUAD. PLK1 was revealed as a potential DLGAP5 downstream target in LUAD. DLGAP5 overexpression or knockdown significantly promoted or inhibited LUAD cell proliferation and PLK1 expression. PLK1 overexpression well rescued DLGAP5 knockdown-induced cell proliferation inhibition, or vice versa. Furthermore, by virtual screening of an investigational drug library from the DrugBank database, AT9283 was screened and identified as a novel DLGAP5 inhibitor. AT9283 effectively suppressed growth of LUAD cells both in vitro and in vivo. DLGAP5 overexpression significantly reversed AT9283-induced proliferation inhibition. Moreover, AT9283 significantly suppressed DLGAP5 and PLK1 expression, while DLGAP5 overexpression significantly reversed AT9283-induced PLK1 suppression.

CONCLUSION

Our research has demonstrated that DLGAP5 is upregulated in LUAD and exhibits a strong correlation with unfavorable prognosis. Furthermore, DLGAP5 assumes a significant function in the regulation of tumor immunity and treatment outcome of immune checkpoint inhibitors. Of note, we found that DLGAP5 promotes cell proliferation of LUAD via upregulating PLK1. Targeting DLGAP5 by AT9283, our newly identified DLGAP5 inhibitor, suppresses LUAD growth. DLGAP5 may become a promising prognostic biomarker and therapeutic target for patients with LUAD.

A Large-Scale Meta-Analysis Reveals Positive Feedback between Macrophages and T Cells That Sensitizes Tumors to Immunotherapy

Although considerable efforts have been dedicated to identifying predictive signatures for immune checkpoint inhibitor (ICI) treatment response, current biomarkers suffer from poor generalizability and reproducibility across different studies and cancer types. The integration of large-scale multiomics studies holds great promise for discovering robust biomarkers and shedding light on the mechanisms of immune resistance. In this study, we conducted the most extensive meta-analysis involving 3,037 ICI-treated patients with genetic and/or transcriptomics profiles across 14 types of solid tumor. The comprehensive analysis uncovered both known and novel reliable signatures associated with ICI treatment outcomes. The signatures included tumor mutational burden (TMB), IFNG and PDCD1 expression, and notably, interactions between macrophages and T cells driving their activation and recruitment. Independent data from single-cell RNA sequencing and dynamic transcriptomic profiles during the ICI treatment provided further evidence that enhanced cross-talk between macrophages and T cells contributes to ICI response. A multivariable model based on eight nonredundant signatures significantly outperformed existing models in five independent validation datasets representing various cancer types. Collectively, this study discovered biomarkers predicting ICI response that highlight the contribution of immune cell networks to immunotherapy efficacy and could help guide patient treatment.

SIGNIFICANCE

Identification of robust immunogenomic connections, particularly macrophage T-cell interactions, in a large-scale pan-cancer meta-analysis and development of a predictive model for immunotherapy response that outperformed existing models could facilitate clinical decision-making.

Aggrephagy-related gene signature correlates with survival and tumor-associated macrophages in glioma: Insights from single-cell and bulk RNA sequencing

BACKGROUND

Aggrephagy is a lysosome-dependent process that degrades misfolded protein condensates to maintain cancer cell homeostasis. Despite its importance in cellular protein quality control, the role of aggrephagy in glioma remains poorly understood.

OBJECTIVE

To investigate the expression of aggrephagy-related genes (ARGs) in glioma and in different cell types of gliomas and to develop an ARGs-based prognostic signature to predict the prognosis, tumor microenvironment, and immunotherapy response of gliomas.

METHODS

ARGs were identified by searching the Reactome database. We developed the ARGs-based prognostic signature (ARPS) using data from the Cancer Genome Atlas (TCGA, n = 669) by Lasso-Cox regression. We validated the robustness of the signature in clinical subgroups and CGGA cohorts (n = 970). Gene set enrichment analysis (GSEA) was used to identify the pathways enriched in ARPS subgroups. The correlations between ARGs and macrophages were also investigated at single cell level.

RESULTS

A total of 44 ARGs showed heterogeneous expression among different cell types of gliomas. Five ARGs (HSF1, DYNC1H1, DYNLL2, TUBB6, TUBA1C) were identified to develop ARPS, an independent prognostic factor. GSEA showed gene sets of patients with high-ARPS were mostly enriched in cell cycle, DNA replication, and immune-related pathways. High-ARPS subgroup had higher immune cell infiltration states, particularly macrophages, Treg cells, and neutrophils. APRS had positive association with tumor mutation burden (TMB) and immunotherapy response predictors. At the single cell level, we found ARGs correlated with macrophage development and identified ARGs-mediated macrophage subtypes with distinct communication characteristics with tumor cells. VIM+ macrophages were identified as pro-inflammatory and had higher interactions with malignant cells.

CONCLUSION

We identified a novel signature based on ARGs for predicting glioma prognosis, tumor microenvironment, and immunotherapy response. We highlight the ARGs-mediated macrophages in glioma exhibit classical features.

Computational Quantification of Cancer Immunoediting

The remarkable success of cancer immunotherapy has revolutionized cancer treatment, emphasizing the importance of tumor-immune interactions in cancer evolution and treatment. Cancer immunoediting describes the dual effect of tumor-immune interactions: inhibiting tumor growth by destroying tumor cells and facilitating tumor escape by shaping tumor immunogenicity. To better understand tumor-immune interactions, it is critical to develop computational methods to measure the extent of cancer immunoediting. In this review, we provide a comprehensive overview of the computational methods for quantifying cancer immunoediting. We focus on describing the basic ideas, computational processes, advantages, limitations, and influential factors. We also summarize recent advances in quantifying cancer immunoediting studies and highlight future research directions. As the methods for quantifying cancer immunoediting are continuously improved, future research will further help define the role of immunity in tumorigenesis and hopefully provide a basis for the design of new personalized cancer immunotherapy strategies.

A novel cuproptosis pattern and tumor immune microenvironment characterization in urothelial carcinoma of the bladder

Background

Urothelial carcinoma of the bladder (UCB) is the most prevalent malignant tumor of the urinary system worldwide, which has a significant recurrence rate despite multiple treatment options available. As a unique and novel copper-dependent programmed cell death mechanism, the comprehensive impact of cuproptosis on the tumor immune microenvironment, clinicopathological characteristics and the prognosis of patients remains largely unclear.

Methods

A total of 568 UCB samples were thoroughly examined for cuproptosis patterns using data downloaded from TCGA and GEO, based on 10 cuproptosis-related genes reported previously. Then, the univariate COX regression analysis was performed on the genes that differed across the various patterns. To measure individual cuproptosis pattern, a cuproptosis score system was constructed using a principal component analysis algorithm. To validate the scoring system, immunohistochemical staining was performed on tumor tissues with different pathological grades, and experiments in vitro were conducted about the differentially expressed genes related to prognosis. Finally, the capacity of scoring system to predict the response to immunotherapy was verified by using data from IMvigor 210 cohort.

Results

Four unique cuproptosis clusters and two gene clusters were finally found by the investigation. The clinical features and prognosis of patients, as well as the mRNA transcriptome, pathway enrichment, and immune cell infiltration in TME, varied dramatically between various cuproptosis clusters and gene clusters. To identify individual cuproptosis patterns in UCB patients, we also established a cuproptosis scoring system. After validation with multiple methods, it was indicated that the score system could predict the prognosis of UCB patients and was significantly connected to clinical features such TNM category, tumor grade, molecular type and ultimate survival status. The clinical outcomes of UCB patients were predicted effectively according to the tumor mutation burden in conjunction with the scoring system. Furthermore, we found that the cuproptosis score had a significant correlation with the response to immunotherapy and the sensitivity to chemotherapy.

Conclusion

This study revealed the potential impact of cuproptosis on the UCB tumor immune microenvironment and clinical pathological characteristics. The cuproptosis score system could effectively predict the prognosis of patients and the response to chemotherapy and immunotherapy.

Plasma D-dimer and interleukin-6 are associated with treatment response and progression-free survival in advanced NSCLC patients on anti-PD-1 therapy

BACKGROUND/AIMS

Response to therapy after using immune checkpoint inhibitors (ICIs) is unpredictable due to significant interindividual variation in efficacy among advanced non-small cell lung cancer (NSCLC) patients. The current study centered on the identification of perivascular blood biomarkers for predicting the effectiveness of anti-programmed cell death protein 1 (anti-PD-1) treatment and progression-free survival (PFS) in advanced NSCLC patients, that could be applied to help determine how to change treatment plans therapeutic regimens for optimizing clinical benefits.

METHODS

A comprehensive review of 100 advanced or recurrent NSCLC patients receiving anti-PD-1 therapy (Camrelizumab, pembrolizumab, sintilimab, or nivolumab) was conducted between January 2018 and April 2021 in Tianjin Medical University Cancer Hospital. The cutoff values of D-dimer were selected from rom our previous study, and interleukin-6 (IL-6) was divided according to the median. Using computed tomography, tumor response was evaluated in accordance with the Response Assessment Criteria in Solid Tumors, version 1.1.

RESULTS

High IL-6 level in advanced NSCLC patients was predictive of low efficacy and a short PFS duration after anti-PD-1 therapy. An increased D-dimer value of 981 ng/mL was significantly predictive of disease progression in NSCLC patients treated with anti-PD-1 and high D-dimer expression predictive of short duration of PFS. Further studies on the correlation between IL-6, D-dimer, and anti-PD-1 efficacy in NSCLC patients stratified by gender revealed that D-dimer and IL-6 levels were significantly associated with the risk of PFS in male patients.

CONCLUSIONS

High IL-6 content in peripheral blood in patients with advanced non-small cell lung cancer may contribute to poor anti-PD-1 efficacy and short duration of PFS through inducing alterations in the tumor microenvironment. D-dimer in peripheral blood is predictive of hyperfibrinolysis and contributes to the release of tumor-driven specific factors, leading to poor effects of anti-PD-1 therapy.

POTEE mutation as a potential predictive biomarker for immune checkpoint inhibitors in lung adenocarcinoma

Precise selection of patients who could benefit from immune checkpoint inhibitors (ICIs) is an important challenge for immunotherapy in lung cancer. POTEE (POTE Ankyrin Domain Family Member E) is a member of one primate-specific gene family which have been identified as cancer-related antigens and potential target for immunotherapy of cancer. Here, we investigated the correlation between POTEE mutation and the clinical outcome of ICIs treatment in non-small cell lung cancer (NSCLC). We merged three NSCLC cohorts (n = 165) to assess predictive value of POTEE mutation of immunotherapy efficacy in NSCLC. The prognostic analysis and the potential molecular mechanism exploration were conducted based on the data from The Cancer Genome Atlas (TCGA) database. In the merged cohort, patients with POTEE-mutation (POTEE-Mut) had a significantly higher objective response rate (ORR) (100% vs 27.7%; P < 0.001) and longer progression-free survival (PFS) (P = 0.001; HR 0.08; 95% CI 0.01 - 0.54) compared to patients with POTEE wild-type (POTEE-WT) in NSCLC. Also, patients with POTEE-Mut showed higher ORR (100% vs 27.2%; P < 0.001) and longer PFS (P = 0.001; HR 0.07; 95% CI 0.01 - 0.52) in lung adenocarcinoma (LUAD). POTEE mutation was significantly associated with higher tumor mutational burden (TMB) and higher neoantigen load (NAL), but not with PD-L1 expression in LUAD. Gene set enrichment analyses (GSEA) analysis revealed prominent enrichment of signatures related to DNA repair in POTEE-Mut group (P < 0.001) in LUAD. Our results indicate that POTEE mutation could serve as a potential predictive biomarker for ICIs in LUAD. However, prospective cohort studies are still needed for further validation.

Whole genome and RNA sequencing analyses for 254 Taiwanese hepatocellular carcinomas

BACKGROUND

Comprehensive and integrative analysis of hepatocellular carcinoma (HCC) is important. In this study, we explored Taiwanese HCCs using multi-omics analyses.

METHODS

We analyzed 254 HCCs by whole genome sequencing and total RNA sequencing, and then used bioinformatic tools to analyze genomic and transcriptomic alterations in coding and non-coding sequences to explore the clinical importance of each sequence.

RESULTS

The frequencies of the five most commonly mutated cancer-related genes were TERT, TP53, CTNNB1, RB1, and ARID1A. Genetic alteration frequencies influenced the etiology of HCC; some alterations were also correlated with clinicopathological conditions. Many cancer-related genes had copy number alterations (CNAs) and structure variants (SVs) that changed according to etiology and exhibited potential associations with survival. We also identified several alterations in histone-related genes, HCC-related long non-coding RNAs, and non-coding driver genes that may contribute to the onset and progression of HCC. Transcriptomic analysis revealed that 229 differentially expressed and 148 novel alternative splicing (AS) genes, as well as the presence of fusion genes, were associated with patient survival. Moreover, somatic mutations, CNAs, and SVs were associated with immune checkpoint gene expression and tumor microenvironment. Finally, we identified relationships among AS, immune checkpoint gene expression and tumor microenvironment.

CONCLUSIONS

This study shows that genomic alterations are associated with survival, including DNA-based and RNA-based data. Moreover, genomic alterations and their associations with immune checkpoint genes and the tumor microenvironment may provide novel insights for the diagnosis and treatment of HCC.

Chemical Complementarity of Breast Cancer Resident, T-Cell Receptor CDR3 Domains and the Cancer Antigen, ARMC3, is Associated With Higher Levels of Survival and Granzyme Expression

Introduction

One of the most pressing goals for cancer immunotherapy at this time is the identification of actionable antigens.

Methods

This study relies on the following considerations and approaches to identify potential breast cancer antigens: (i) the significant role of the adaptive immune receptor, complementarity determining region-3 (CDR3) in antigen binding, and the existence cancer testis antigens (CTAs); (ii) chemical attractiveness; and (iii) informing the relevance of the integration of items (i) and (ii) with patient outcome and tumor gene expression data.

Results

We have assessed CTAs for associations with survival, based on their chemical complementarity with tumor resident T-cell receptor (TCR), CDR3s. Also, we have established gene expression correlations with the high TCR CDR3-CTA chemical complementarities, for Granzyme B, and other immune biomarkers.

Conclusions

Overall, for several independent TCR CDR3 breast cancer datasets, the CTA, ARMC3, stood out as a completely novel, candidate antigen based on multiple algorithms with highly consistent approaches. This conclusion was facilitated by use of the recently constructed Adaptive Match web tool.

TMBserval: a statistical explainable learning model reveals weighted tumor mutation burden better categorizing therapeutic benefits

A high tumor mutation burden (TMB) is known to drive the response to immune checkpoint inhibitors (ICI) and is associated with favorable prognoses. However, because it is a one-dimensional numerical representation of non-synonymous genetic alterations, TMB suffers from clinical challenges due to its equal quantification. Since not all mutations elicit the same antitumor rejection, the effect on immunity of neoantigens encoded by different types or locations of somatic mutations may vary. In addition, other typical genomic features, including complex structural variants, are not captured by the conventional TMB metric. Given the diversity of cancer subtypes and the complexity of treatment regimens, this paper proposes that tumor mutations capable of causing various degrees of immunogenicity should be calculated separately. TMB should therefore, be segmented into more exact, higher dimensional feature vectors to exhaustively measure the foreignness of tumors. We systematically reviewed patients' multifaceted efficacy based on a refined TMB metric, investigated the association between multidimensional mutations and integrative immunotherapy outcomes, and developed a convergent categorical decision-making framework, TMBserval (Statistical Explainable machine learning with Regression-based VALidation). TMBserval integrates a multiple-instance learning concept with statistics to create a statistically interpretable model that addresses the broad interdependencies between multidimensional mutation burdens and decision endpoints. TMBserval is a pan-cancer-oriented many-to-many nonlinear regression model with discrimination and calibration power. Simulations and experimental analyses using data from 137 actual patients both demonstrated that our method could discriminate between patient groups in a high-dimensional feature space, thereby rationally expanding the beneficiary population of immunotherapy.

The landscape of objective response rate of anti-PD-1/L1 monotherapy across 31 types of cancer: a system review and novel biomarker investigating

BACKGROUND

Immune checkpoint inhibitors (ICIs) have dramatically changed the landscape of cancer treatment. However, only a few patients respond to ICI treatment. Thus, uncovering clinically accessible ICI biomarkers would help identify which patients will respond well to ICI treatment. A comprehensive objective response rate (ORR) data of anti-PD-1/PD-L1 monotherapy in pan-cancer would offer the original data to explore the new biomarkers for ICIs.

METHODS

We systematically searched PubMed, Cochrane, and Embase for clinical trials on July 1, 2021, limited to the years 2017-2021, from which we obtained studies centering around anti-PD-1/PD-L1 monotherapy. Finally, 121 out of 3099 publications and 143 ORR data were included. All of the 31 tumor types/subtypes can be found in the TCGA database. The gene expression profiles and mutation data were downloaded from TCGA. A comprehensive genome-wide screening of ORR highly correlated mutations among 31 cancers was conducted by Pearson correlation analysis based on the TCGA database.

RESULTS

According to the ORR, we classified 31 types of cancer into high, medium, and low response types. Further analysis uncovered that "high response" cancers had more T cell infiltration, more neoantigens, and less M2 macrophage infiltration. A panel of 28 biomarkers reviewed from recent articles were investigated with ORR. We also found the TMB as a traditional biomarker had a high correlation coefficient with ORR in pan-cancer, however, the correlation between ITH and ORR was low across pan-cancer. Moreover, we primarily identified 1044 ORR highly correlated mutations through a comprehensive screening of TCGA data, among which USH2A, ZFHX4 and PLCO mutations were found to be highly correlated to strengthened tumor immunogenicity and inflamed antitumor immunity, as well as improved outcomes for ICIs treatment among multiple immunotherapy cohorts.

CONCLUSION

Our study provides comprehensive data on ORR of anti-PD-1/PD-L1 monotherapy across 31 tumor types/subtypes and an essential reference of ORR to explore new biomarkers. We also screened out a list of 1044 immune response related genes and we showed that USH2A, ZFHX4 and PLCO mutations may act as good biomarkers for predicting patient response to anti-PD-1/PD-L1 ICIs.

Distinct cellular composition between normal surgical margins and tumor tissues in oral squamous cell carcinoma

BACKGROUND

Adequate resection of normal surgical margins is important. However, the clear distinction between the normal surgical margins and tumor tissues is still difficult.

OBJECTIVE

Here, this study analyzed the variety of cell types in tumors and the normal surgical margins using a computational approach.

METHODS

The composition of cell types was compared between the two tissues by statistical and machine learning approaches.

RESULTS

The results showed the distinct cellular composition between tumor-adjacent and tumor tissues. In particular, endothelial cells were highly represented and macrophages were underrepresented at the normal surgical margin. Moreover, the normal surgical margin and tumor tissues could be discriminated using a machine learning algorithm.

CONCLUSION

The results will help to understand cellular differences between normal surgical margins and tumor tissues and to provide potentials for tumor detection and treatment.

Clinical implication and immunological landscape analyses of ANLN in pan-cancer: A new target for cancer research

BACKGROUND

Anillin is a F-actin binding protein (ANLN) mainly involved in the process of cytokinesis and known to be dysregulated in diverse cancers. However, the role of ANLN in pan-cancer prognosis and tumor immunity remains unclear.

METHODS

Gene expression profiles of 31 solid tumors were downloaded from The Cancer Genome Atlas (TCGA) database. ANLN mRNA and protein expression were quantified using quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC). Protein expression of ANLN was further confirmed in Human Protein Atlas (HPA) database. Cox regression and Kaplan-Meier analysis were utilized to assess the prognostic value of ANLN in pan-cancer. The correlation between ANLN and different immune gene markers and infiltration cells was analyzed via ESTIMATE and CIBERSORT. A BLCA immunotherapy cohort: IMvigor (210) was used to confirm the role of ANLN in immune response.

RESULTS

ANLN upregulation was detected in 21 types of cancers and was associated with poor overall survival (OS), disease-free interval (DFI), and progression-free interval (PFI) in most cancers except in THYM (Thymoma). Additionally, correlation analysis revealed a significantly positive association between ANLN expression and tumor mutation burden (TMB), microsatellite instability (MSI), immune cells infiltration. and immune checkpoint genes in various cancers. The BLCA immunotherapy cohort confirmed that patients with higher ANLN level had better immune responses and longer OS.

CONCLUSION

ANLN may serve as a prognostic biomarker for pan-cancer. ANLN upregulation is associated with higher TMB, MSI, and immune cell infiltration in multiple types of tumors, shedding new light for cancer treatment.

Clear Cell Renal Cell Carcinoma: From Biology to Treatment

The majority of kidney cancers are detected incidentally and typically diagnosed at a localized stage, however, the development of regional or distant disease occurs in one-third of patients. Over 90% of kidney tumors are renal cell carcinomas, of which, clear cell is the most predominate histologic subtype. Von Hippel Lindau (VHL) gene alterations result in the overexpression of growth factors that are central to the pathogenesis of clear cell carcinoma. The therapeutic strategies have revolved around this tumor suppressor gene and have led to the approval of tyrosine kinase inhibitors (TKI) targeting the vascular endothelial growth factor (VEGF) axis. The treatment paradigm shifted with the introduction of immune checkpoint inhibitors (ICI) and programed death-1 (PD-1) inhibition, leading to durable response rates and improved survival. Combinations of TKI and/or ICIs have become the standard of care for advanced clear cell renal cell carcinoma (ccRCC), changing the outlook for patients, with several new and promising therapeutic targets under development.

Objective response to immune checkpoint inhibitor therapy in NRAS-mutant melanoma: A systematic review and meta-analysis

Introduction

NRAS mutations are common in melanoma and confer a worse prognosis. Although most patients with metastatic melanoma receive immune checkpoint inhibitors (ICIs), the impact of NRAS mutational status on their efficacy remains under debate.

Methods

We performed a comprehensive literature search across several large databases. Inclusion criteria were trials, cohorts, and large case series that analyzed the primary outcome of objective response rate by NRAS mutational status in patients with melanoma treated with any line of ICI. At least two reviewers independently screened studies using Covidence software, extracted data, and assessed risk of bias. Standard meta-analysis was performed in R with sensitivity analysis and tests for bias.

Results

Data on 1770 patients from ten articles were pooled for meta-analysis, and the objective response rate to ICIs was calculated to compare NRAS-mutant and NRAS-wildtype melanoma. The objective response rate was 1.28 (95% confidence interval: 1.01-1.64). Sensitivity analysis identified the study by Dupuis et al. with influential impact on the pooled effect size and heterogeneity, favoring NRAS-mutant melanoma.

Discussion

In this meta-analysis evaluating the impact of NRAS mutational status on objective response to ICIs in metastatic melanoma, NRAS-mutant cutaneous melanoma demonstrated an increased likelihood of partial or complete tumor response, relative to NRAS-wildtype cutaneous melanoma. Genomic screening for NRAS mutations in patients with metastatic melanoma may improve predictive ability when initiating ICIs.

Development and validation of a mutation-based model to predict immunotherapeutic efficacy in NSCLC

Background

Immunotherapy has become increasingly important in the perioperative period of non-small-cell lung cancer (NSCLC). In this study, we intended to develop a mutation-based model to predict the therapeutic effificacy of immune checkpoint inhibitors (ICIs) in patients with NSCLC.

Methods

Random Forest (RF) classifiers were generated to identify tumor gene mutated features associated with immunotherapy outcomes. Then the best classifier with the highest accuracy served for the development of the predictive model. The correlations of some reported biomarkers with the model were analyzed, such as TMB, PD-(L)1, KEAP1-driven co-mutations, and immune subtypes. The training cohort and validation cohorts performed survival analyses to estimate the predictive efficiency independently.

Results

An 18-gene set was selected using random forest (RF) classififiers. A predictive model was developed based on the number of mutant genes among the candidate genes, and patients were divided into the MT group (mutant gene ≥ 2) and WT group (mutant gene < 2). The MT group (N = 54) had better overall survival (OS) compared to the WT group (N = 290); the median OS was not reached vs. nine months (P < 0.0001, AUC = 0.73). The robust predictive performance was confifirmed in three validation cohorts, with an AUC of 0.70, 0.57, and 0.64 (P < 0.05). The MT group was characterized by high tumor neoantigen burden (TNB), increased immune infifiltration cells such as CD8 T and macrophage cells, and upregulated immune checkpoint molecules, suggesting potential biological advantages in ICIs therapy.

Conclusions

The predictive model could precisely predict the immunotherapeutic efficacy in NSCLC based on the mutant genes within the model. Furthermore, some immune-related features and cell expression could support robust efficiency.

Immune Checkpoint Inhibitor Therapy in Oncology: Current Uses and Future Directions: JACC: CardioOncology State-of-the-Art Review

Immune checkpoint inhibitors (ICIs) are a major class of immuno-oncology therapeutics that have significantly improved the prognosis of various cancers, both in (neo)adjuvant and metastatic settings. Unlike other conventional therapies, ICIs elicit antitumor effects by enhancing host immune systems to eliminate cancer cells. There are 3 approved ICI classes by the U.S. Food and Drug Administration: inhibitors targeting cytotoxic T lymphocyte associated antigen 4, programmed death 1/programmed death-ligand 1, and lymphocyte-activation gene 3, with many more in development. ICIs are commonly associated with distinct toxicities, known as immune-related adverse events, which can arise during treatment or less frequently be of late onset, usually relating to excessive activation of the immune system. Acute cardiovascular immune-related adverse events such as myocarditis are rare; however, data suggesting chronic cardiovascular sequelae are emerging. This review presents the current landscape of ICIs in oncology, with a focus on important aspects relevant to cardiology.

ARID1A, BRG1, and INI1 deficiency in undifferentiated and dedifferentiated endometrial carcinoma: a clinicopathologic, immunohistochemical, and next-generation sequencing analysis of a case series from a single institution

Undifferentiated/dedifferentiated endometrial carcinomas (UDEC and DDEC) are rare, aggressive uterine neoplasms, with no specific line of differentiation. A significant proportion of these cases feature mutations of SWI/SNF chromatin remodeling complex members, including ARID1A, SMARCA4, and SMARCB1 genes. To study these entities more comprehensively, we identified 10 UDECs and 10 DDECs from our pathology archives, obtained clinicopathologic findings and follow-up data, and performed immunohistochemical studies for ARID1A, BRG1 (SMARCA4), and INI1 (SMARCB1) proteins. In addition, we successfully conducted targeted next-generation sequencing for 23 samples, including 7 UDECs, and 7 undifferentiated and 9 well/moderately-differentiated components of DDECs. Cases consisted of 18 hysterectomies and 2 curettage/biopsy specimens. Patient age ranged from 47 to 77 years (median, 59 years), with a median tumor size of 8.0 cm (range, 2.5-13.0 cm). All cases demonstrated lymphovascular invasion and the majority (13/20) were FIGO stage III-IV. By immunohistochemistry, ARID1A loss was observed in 15 cases, BRG1 loss in 4, and all cases had intact INI1 expression. A trend for enrichment of the undifferentiated component of DDECs for ARID1A loss was seen, although not statistically significant. Sequencing revealed frequent pathogenic mutations in PTEN, PIK3CA, ARID1A, CTNNB1, and RNF43, a recurrent MAX pathogenic mutation, and MYC and 12p copy number gains. In DDECs, the undifferentiated component featured a higher tumor mutational burden compared to the well/moderately-differentiated component; however, the mutational landscape largely overlapped. Overall, our study provides deep insights into the mutational landscape of UDEC/DDEC, SWI/SNF chromatin remodeling complex member status, and their potential relationships with tumor features.

Immunological and Genomic Analysis Reveals Clinically Relevant Distinctions between Angiosarcoma Subgroups

Angiosarcomas (AS) are extremely rare and aggressive vascular malignancies subdivided in de novo primary AS (pAS) and secondary AS (sAS). We hypothesize that the combination of immunological and genomic profiles significantly differs between primary and secondary AS, with potential impact on treatment strategies and a role for immunotherapy. Tumor-infiltrating lymphocytes were analyzed using multiplex immunohistochemistry from 79 pAS and 178 sAS. Median cell density was significantly higher in sAS for CD3+ T-cells (p < 0.001), CD8+ cytotoxic T-cells (p = 0.033), CD4+ T-helper cells (p < 0.001) and FoxP3+ T-regulatory cells (p < 0.001). CD20+ B-cell density was comparable (p = 0.417). Comprehensive genomic profiling was performed in 25 pAS and 25 sAS. A (likely) pathogenic mutation was detected in 80% of pAS vs. 88% of sAS (p = 0.702). Amplifications were found in 15% of pAS vs. 84% of sAS (p < 0.001). DNA damage response (DDR) pathway mutations (p = 0.021) and MYC amplifications (p < 0.001) were predominantly seen in sAS. In conclusion we observed a clear and clinical relevant distinction in immune infiltration and genomic profiles between pAS and sAS. The T-cell infiltrated tumor microenvironment and frequent DDR gene mutations, especially in sAS, warrant clinical trials with immunotherapy.

Comprehensive analysis of the expression profile and clinical implications of regulator of chromosome condensation 2 in pan-cancers

The Regulator of Chromosome Condensation 2 (RCC2) is an important gene that regulates mitosis and cytoplasmic division in the cell cycle. Although there have been reported in several individual tumors, an integrative analysis of RCC2 and its clinical significance across diverse cancer types is poorly elucidated. In this study, we performed integrative bioinformatics analyses to profile the expression landscape and assess the prognostic value of RCC2 in pan-cancers. Correlations between RCC2 expression and tumor-infiltrating immune cells, tumor mutation burden (TMB), microsatellite instability (MSI), chemokine and their receptors were analyzed using TCGA, ESTIMATE algorithm, and TISIDB database. We also explored the potential molecular functions of RCC2 through functional enrichment analysis and protein interaction networks. We discovered that RCC2 was highly expressed in various tumor tissues and was closely associated with cancer prognosis. Different RCC2-associated immune infiltration patterns were exhibited in different tumor-infiltrating immune cells. In addition, the RCC2 had a potential role in regulating the tumor immune microenvironment and the formation of cancer-associated fibroblasts (CAFs). Meanwhile, RCC2 showed a significant correlation with TMB, MSI, chemokines and their receptors in different tumor types. The role of RCC2 as a clinical therapeutic target was further revealed from the perspective of the immune microenvironment. In conclusion, RCC2 is closely associated with tumorigenesis and cancer-immune infiltration, and could be a promising prognostic and therapeutic biomarker in diverse cancers.

Advances in sex disparities for cancer immunotherapy: unveiling the dilemma of Yin and Yang

A wide sex disparity has been demonstrated in cancer incidence, tumor aggressiveness, prognosis, and treatment response of different types of cancer. The sex specificity of cancer appears to be a relevant issue in managing the disease, and studies investigating the role of sex and gender are becoming extremely urgent. Immunotherapy plays a leading role in cancer treatment, offering a new perspective on advanced malignancies. Gender has not been considered in standard cancer treatment, suggesting increasing the recognition of sex differences in cancer research and clinical management. This paper provides an overview of sex and gender disparities in cancer immunotherapy efficacy, anti-cancer immune response, predictive biomarkers, and so on. We focus on the molecular differences between male and female patients across a broad range of cancer types to arouse the attention and practice of clinicians and researchers in a sex perspective of new cancer treatment strategies.

Sex differences exist in the prevalence, tumor invasiveness, treatment responses, and clinical outcomes of pan-cancer, suggesting that, while not yet incorporated, sex will probably be considered in future practice guidelines.

Inherent genetic differences, overlapping epigenetic alterations, and sex hormone influences underpin everything. Androgen receptors influence the sexual differences in TME by regulating epigenetic and transcriptional differentiation programs. It highlights a sex-based therapeutic target for cancer immunotherapy.

Proper consideration of sex, age, sex hormones/menopause status, and socio-cultural gender differences in clinical investigation and gene association studies of cancer are needed to fill current gaps and implement precision medicine for patients with cancer.

Immune Checkpoint Inhibitors and Other Immune Therapies in Breast Cancer: A New Paradigm for Prolonged Adjuvant Immunotherapy

Background: Breast cancer is the most common form of cancer in women worldwide. Advances in the early diagnosis and treatment of cancer in the last decade have progressively decreased the cancer mortality rate, and in recent years, immunotherapy has emerged as a relevant tool against cancer. HER2+ and triple-negative breast cancers (TNBCs) are considered more immunogenic and suitable for this kind of treatment due to the higher rate of tumor-infiltrating lymphocytes (TILs) and programmed death ligand 1 (PD-L1) expression. In TNBC, genetic aberrations further favor immunogenicity due to more neo-antigens in cancer cells. Methods: This review summarizes the principal ongoing conventional and investigational immunotherapies in breast cancer. Particularly, immune checkpoint inhibitors (ICIs) and their use alone or combined with DNA damage repair inhibitors (DDRis) are described. Then, the issue on immunotherapy with monoclonal antibodies against HER-2 family receptors is updated. Other investigational immunotherapies include a new schedule based on the interferon beta-interleukin-2 sequence that was given in ER+ metastatic breast cancer patients concomitant with anti-estrogen therapy, which surprisingly showed promising results. Results: Based on the scientific literature and our own findings, the current evaluation of tumor immunogenicity and the conventional model of adjuvant chemotherapy (CT) are questioned. Conclusions: A novel strategy based on additional prolonged adjuvant immunotherapy combined with hormone therapy or alternated with CT is proposed.

TMBcat: A multi-endpoint p-value criterion on different discrepancy metrics for superiorly inferring tumor mutation burden thresholds

Tumor mutation burden (TMB) is a widely recognized stratification biomarker for predicting the efficacy of immunotherapy; however, the number and universal definition of the categorizing thresholds remain debatable due to the multifaceted nature of efficacy and the imprecision of TMB measurements. We proposed a minimal joint p-value criterion from the perspective of differentiating the comprehensive therapeutic advantages, termed TMBcat, optimized TMB categorization across distinct cancer cohorts and surpassed known benchmarks. The statistical framework applies to multidimensional endpoints and is fault-tolerant to TMB measurement errors. To explore the association between TMB and various immunotherapy outcomes, we performed a retrospective analysis on 78 patients with non-small cell lung cancer and 64 patients with nasopharyngeal carcinomas who underwent anti-PD-(L)1 therapy. The stratification results of TMBcat confirmed that the relationship between TMB and immunotherapy is non-linear, i.e., treatment gains do not inherently increase with higher TMB, and the pattern varies across carcinomas. Thus, multiple TMB classification thresholds could distinguish patient prognosis flexibly. These findings were further validated in an assembled cohort of 943 patients obtained from 11 published studies. In conclusion, our work presents a general criterion and an accessible software package; together, they enable optimal TMB subgrouping. Our study has the potential to yield innovative insights into therapeutic selection and treatment strategies for patients.

Biological Pathway-Derived TMB Robustly Predicts the Outcome of Immune Checkpoint Blockade Therapy

Although immune checkpoint blockade (ICB) therapies have achieved great progress, the patient response varies among cancers. In this study, we analyzed the potential genomic indicators contributing to ICB therapy response. The results showed that high tumor mutation burden (TMB) failed to predict response in anti-PD1 treated melanoma. SERPINB3 was the most significant response-related gene in melanoma and mutations in either SERPINB3 or PEG3 can serve as an independent risk factor in melanoma. Some recurrent mutations in CSMD3 were only in responders or non-responders, indicating their diverse impacts on patient response. Enrichment scores (ES) of gene mutations in 12 biological pathways were significantly higher in responders or non-responders. Next, the P-TMB calculated from genes in these pathways was significantly related to patient response with prediction AUC 0.74–0.82 in all collected datasets. In conclusion, our work provides new insights into the application of TMB in predicting patient response, which will benefit to immunotherapy research.

The role of DNA damage repair (DDR) system in response to immune checkpoint inhibitor (ICI) therapy

As our understanding of the mechanisms of cancer treatment has increased, a growing number of studies demonstrate pathways through which DNA damage repair (DDR) affects the immune system. At the same time, the varied response of patients to immune checkpoint blockade (ICB) therapy has prompted the discovery of various predictive biomarkers and the study of combination therapy. Here, our investigation explores the interactions involved in combination therapy, accompanied by a review that summarizes currently identified and promising predictors of response to immune checkpoint inhibitors (ICIs) that are useful for classifying oncology patients. In addition, this work, which discusses immunogenicity and several components of the tumor immune microenvironment, serves to illustrate the mechanism by which higher response rates and improved efficacy of DDR inhibitors (DDRi) in combination with ICIs are achieved.

Alternating exosomes and their mimetics as an emergent strategy for targeted cancer therapy

Exosomes, a subtype of the class of extracellular vesicles and nano-sized particles, have a specific membrane structure that makes them an alternative proposition to combat with cancer through slight modification. As constituents of all most all the primary body fluids, exosomes establish the status of intercellular communication. Exosomes have specific proteins/mRNAs and miRNAs which serve as biomarkers, imparting a prognostic tool in clinical and disease pathologies. They have efficient intrinsic targeting potential and efficacy. Engineered exosomes are employed to deliver therapeutic cargos to the targeted tumor cell or the recipient. Exosomes from cancer cells bring about changes in fibroblast via TGFβ/Smad pathway, augmenting the tumor growth. These extracellular vesicles are multidimensional in terms of the functions that they perform. We herein discuss the uptake and biogenesis of exosomes, their role in various facets of cancer studies, cell-to-cell communication and modification for therapeutic and diagnostic use.

A Joint Model Considering Measurement Errors for Optimally Identifying Tumor Mutation Burden Threshold

Tumor mutation burden (TMB) is a recognized stratification biomarker for immunotherapy. Nevertheless, the general TMB-high threshold is unstandardized due to severe clinical controversies, with the underlying cause being inconsistency between multiple assessment criteria and imprecision of the TMB value. The existing methods for determining TMB thresholds all consider only a single dimension of clinical benefit and ignore the interference of the TMB error. Our research aims to determine the TMB threshold optimally based on multifaceted clinical efficacies accounting for measurement errors. We report a multi-endpoint joint model as a generalized method for inferring the TMB thresholds, facilitating consistent statistical inference using an iterative numerical estimation procedure considering mis-specified covariates. The model optimizes the division by combining objective response rate and time-to-event outcomes, which may be interrelated due to some shared traits. We augment previous works by enabling subject-specific random effects to govern the communication among distinct endpoints. Our simulations show that the proposed model has advantages over the standard model in terms of precision and stability in parameter estimation and threshold determination. To validate the feasibility of the proposed thresholds, we pool a cohort of 73 patients with non-small-cell lung cancer and 64 patients with nasopharyngeal carcinoma who underwent anti-PD-(L)1 treatment, as well as validation cohorts of 943 patients. Analyses revealed that our approach could grant clinicians a holistic efficacy assessment, culminating in a robust determination of the TMB screening threshold for superior patients. Our methodology has the potential to yield innovative insights into therapeutic selection and support precision immuno-oncology.

Comprehensive Evaluation of the m6A Regulator Prognostic Risk Score in the Prediction of Immunotherapy Response in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is known for its high drug resistance. The tumor-immune crosstalk mediated by the epigenetic regulation of N6-methyladenosine (m6A) modification has been demonstrated in recent studies. Therefore, m6A modification-mediated immune cell infiltration characteristics may be helpful to guide immunotherapy for ccRCC.

Methods

This study comprehensively analyzed m6A modifications using the clinical parameters, single-cell RNA sequencing data, and bulk RNA sequencing data from the TCGA-ccRC cohort and 13 external validation cohorts. A series of bioinformatic approaches were applied to construct an m6A regulator prognostic risk score (MRPRS) to predict survival and immunotherapy response in ccRCC patients. Immunological characteristics, enriched pathways, and mutation were evaluated in high- and low-MRPRS groups.

Results

The expressional alteration landscape of m6A regulators was profiled in ccRCC cell clusters and tissue. The 8 regulator genes with minimal lambda were integrated to build an MRPRS, and it was positively correlated with immunotherapeutic response in extent validation cohorts. The clinicopathological features and immune infiltration characteristics could be distinguished by the high- and low-MRPRS. Moreover, the MRPRS-mediated mutation pattern has an enhanced response to immune checkpoint blockade in the ccRCC and pan-cancer cohorts.

Conclusions

The proposed MRPRS is a promising biomarker to predict clinical outcomes and therapeutic responses in ccRCC patients.

Aspirin Suppressed PD-L1 Expression through Suppressing KAT5 and Subsequently Inhibited PD-1 and PD-L1 Signaling to Attenuate OC Development

Ovarian cancer (OC) is a frequently occurred malignancy with high incidence and poor survival worldwide. In recent years, immune checkpoint inhibition that targets PD-1/PD-L1 axis has become an efficient and popular therapy for cancers. Aspirin (ASP), an anti-inflammatory drug, exhibits a wide spectrum of biological functions including anticancer property. However, the role of ASP treatment in ovarian cancer treatment remains unclear. In this work, we explored the role of ASP in modulating PD-L1 signaling during OC development. Notably, in vitro experiments showed that ASP treatment caused repressed proliferation of OC cells. The results from in vivo xenograft model suggested suppressed tumor growth and tumor weight under ASP treatment. ASP treatment also caused downregulated PD-L1 and Ki-67 levels in mice tumors. Moreover, the IFN-γ-caused PD-L1 accumulation was inhibited by ASP treatment. The administration of ASP decreased the expression of PD-L1 of OC cells in a coculture system with activated T cell or unstimulated PBMCs, along with decreased expression of PD-1 by activated T cells. ASP reversed PD-L1 expression caused by coculture with activated T cells and abolished the suppressed T cells activation and proliferation. Analysis on molecular mechanisms revealed that KAT5 bonded to the promoter region of PD-L1 and upregulated its expression via enhancing histone H3 lysine 27 acetylation (H3K27ac), whereas ASP downregulated KAT5 expression and blocked this phenomenon. Moreover, ASP enhanced the effect of antiPD-L1 therapy in the in vivo tumor model. Hence, we proposed that ASP decreased expression of PD-L1 protein via inhibiting the epigenetic regulation by KAT5 and suppressed the PD-1/PD-L1 signaling to attenuate tumor growth. ASP may be a promising adjuvant in OC immunotherapy.

S100A9-CXCL12 activation in BRCA1-mutant breast cancer promotes an immunosuppressive microenvironment associated with resistance to immunotherapy

Immune checkpoint blockade (ICB) is a powerful approach for cancer therapy although good responses are only observed in a fraction of cancer patients. Breast cancers caused by deficiency of breast cancer-associated gene 1 (BRCA1) do not have an improved response to the treatment. To investigate this, here we analyze BRCA1 mutant mammary tissues and tumors derived from both BRCA1 mutant mouse models and human xenograft models to identify intrinsic determinants governing tumor progression and ICB responses. We show that BRCA1 deficiency activates S100A9-CXCL12 signaling for cancer progression and triggers the expansion and accumulation of myeloid-derived suppressor cells (MDSCs), creating a tumor-permissive microenvironment and rendering cancers insensitive to ICB. These oncogenic actions can be effectively suppressed by the combinatory treatment of inhibitors for S100A9-CXCL12 signaling with αPD-1 antibody. This study provides a selective strategy for effective immunotherapy in patients with elevated S100A9 and/or CXCL12 protein levels.

Identification of the Immune Signatures for Ovarian Cancer Based on the Tumor Immune Microenvironment Genes

Ovarian cancer (OV) is a deadly gynecological cancer. The tumor immune microenvironment (TIME) plays a pivotal role in OV development. However, the TIME of OV is not fully known. Therefore, we aimed to provide a comprehensive network of the TIME in OV. Gene expression data and clinical information from OV patients were obtained from the Cancer Genome Atlas Program (TCGA) database. Non-negative Matrix Factorization, NMFConsensus, and nearest template prediction algorithms were used to perform molecular clustering. The biological functions of differentially expressed genes (DEGs) were identified using Metascape, gene set enrichment analysis (GSEA), gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The copy number variations (CNVs), single nucleotide polymorphisms (SNPs) and tumor mutation burden were analyzed using Gistic 2.0, R package maftools, and TCGA mutations, respectively. Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data and CIBERSORT were utilized to elucidate the TIME. Moreover, external data from the International Cancer Genome Consortium (ICGC) and ArrayExpress databases were used to validate the signature. All 361 samples from the TCGA OV dataset were classified into Immune Class and non-Immune Class with immune signatures. By comparing the two classes, we identified 740 DEGs that accumulated in immune-related, cancer-related, inflammation-related biological functions and pathways. There were significant differences in the CNVs between the Immune and non-Immune Classes. The Immune Class was further divided into immune-activated and immune-suppressed subtypes. There was no significant difference in the top 20 genes in somatic SNPs among the three groups. In addition, the immune-activated subtype had significantly increased proportions of CD4 memory resting T cells, T cells, M1 macrophages, and M2 macrophages than the other two groups. The qRT-PCR results indicated that the mRNA expression levels of RYR2, FAT3, MDN1 and RYR1 were significantly down-regulated in OV compared with normal tissues. Moreover, the signatures of the TIME were validated using ICGC cohort and the ArrayExpress cohort. Our study clustered the OV patients into an immune-activated subtype, immune-suppressed subtype, and non-Immune Class and provided potential clues for further research on the molecular mechanisms and immunotherapy strategies of OV.

A mutation-based gene set predicts survival benefit after immunotherapy across multiple cancers and reveals the immune response landscape

Background

Immune checkpoint inhibitor (ICI) therapy has revolutionized the treatment of many cancers. However, the limited population that benefits from ICI therapy makes it necessary to screen predictive biomarkers for stratifying patients. Currently, many biomarkers, such as tumor mutational burden (TMB), have been used in the clinic as indicative biomarkers. However, some high-TMB patients with mutations in genes that are closely related to immunotherapeutic resistance are not sensitive to ICI therapy. Thus, there is a need to move beyond TMB and identify specific genetic determinants of the response to ICI therapy. In this study, we established a comprehensive mutation-based gene set across different tumor types to predict the efficacy of ICI therapy.

Methods

We constructed and validated a mutational signature to predict the prognosis of patients treated with ICI therapy. Then, the underlying immune response landscapes of different subtypes were investigated with multidimensional data.

Results

This study included genomic and clinical data for 12,647 patients. An eleven-gene mutation-based gene set was generated to divide patients into a high-risk group and a low-risk group in a training cohort (1572 patients with 9 types of cancers who were treated with ICI therapy). Validation was performed in a validation cohort (932 patients with 5 types of cancers who were treated with ICI therapy). Mutations in these 11 genes were associated with a better response to ICI therapy. In addition, the mutation-based gene set was demonstrated to be an independent prognostic factor after ICI therapy. We further explored the role of the immune context in determining the benefits of immunotherapy in 10,143 patients with 33 types of cancers and found distinct immune landscapes for the high- and low-risk groups.

Conclusions

The mutation-based gene set developed in this study can be used to reliably predict survival benefit across cancers in patients receiving ICI therapy. The close interplay between the extrinsic and intrinsic immune landscapes in the identified patient subgroups and the subgroups’ differing responses to ICI therapy could guide immunotherapy treatment decisions for cancer patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01024-y.

Prospects of Immunotherapy for Triple-Negative Breast Cancer

In the classification and typing of breast cancer, triple-negative breast cancer (TNBC) is one type of refractory breast cancer, while chemotherapy stays in the traditional treatment methods. However, the impact of chemotherapy is short-lived and may lead to recurrence due to incomplete killing of tumor cells. The occurrence, development, and relapse of breast cancer are relevant to T cell dysfunction, multiplied expression of related immune checkpoint molecules (ICIs) such as programmed death receptor 1 (PD-1), programmed cell death 1 ligand 1 (PD-L1), and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) produce immunosuppressive effect. Immunotherapy (namely, immune checkpoint inhibitors, adoptive cellular immunotherapy, CAR-T immunotherapy and some potential treatments) provides new hope in TNBC. This review focuses on the new immune strategies of TNBC patients.

Beyond Sequencing: Prioritizing and Delivering Neoantigens for Cancer Vaccines

Neoantigens are tumor-specific proteins and peptides that can be highly immunogenic. Immune-mediated tumor rejection is strongly associated with cytotoxic responses to neoantigen-derived peptides in noncovalent association with self-HLA molecules. Neoantigen-based therapies, such as adoptive T cell transfer, have shown the potential to induce remission of treatment-resistant metastatic disease in select patients. Cancer vaccines are similarly designed to elicit or amplify antigen-specific T cell populations and stimulate directed antitumor immunity, but the selection and prioritization of the neoantigens remains a challenge. Bioinformatic algorithms can predict tumor neoantigens from somatic mutations, insertion-deletions, and other aberrant peptide products, but this often leads to hundreds of potential neoepitopes, all unique for that tumor. Selecting neoantigens for cancer vaccines is complicated by the technical challenges of neoepitope discovery, the diversity of HLA molecules, and intratumoral heterogeneity of passenger mutations leading to immune escape. Despite strong preclinical evidence, few neoantigen cancer vaccines tested in vivo have generated epitope-specific T cell populations, suggesting suboptimal immune system activation. In this chapter, we review factors affecting the prioritization and delivery of candidate neoantigens in the design of therapeutic and preventive cancer vaccines and consider synergism with standard chemotherapies.

A Pyroptosis-Related Gene Prognostic Index Correlated with Survival and Immune Microenvironment in Glioma

Purpose

As an inflammatory form of programmed cell death, pyroptosis has been well established to be associated with tumorigenesis and tumor immune microenvironment. In this paper, we aimed at the construction of a pyroptosis-related gene prognostic index (PRGPI) for predicting prognosis and guiding individualized immunotherapy in glioma patients.

Patients and Methods

Pyroptosis-related genes (PRGs) were identified based on a detailed review of published literatures. The transcriptome data and clinical information of glioma patients were obtained from CGGA and TCGA databases. PRGPI was constructed by using the multivariate Cox regression method. The immune cell infiltration level was analyzed via CIBERSORT algorithm. The tumor immune dysfunction and exclusion (TIDE) algorithm was applied to evaluate the potential response to immune checkpoint inhibitor (ICI) therapy. The expression patterns of PRGs in PRGPI were validated in cell lines and pathological specimens.

Results

We identified a total of 31 PRGs. Among them, PRGs (CASP3, DPP9, MAPK8, PELP1 and TOMM20) were selected for the construction of PRGPI. In both training (CGGA693) and validation (CGGA325 and TCGA) cohorts, PRGPI-high patients showed an inferior survival outcome compared with PRGPI-low patients. ROC curves illustrated that the prognostic prediction power of PRGPI was robust. A nomogram was developed based on independent prognostic indicators (PRGPI, age and WHO grade), and also exhibited a strong forecasting ability for overall survival (OS). Additionally, PRGPI-high patients exhibited higher immune, stroma and ESTIMATE scores, lower tumor purity, higher infiltration of M2-type macrophages, lower infiltration of CD8⁺ T cells and activated NK cells, higher tumor mutation burden (TMB), and higher expression of immune checkpoints. TIDE showed that PRGPI-high group had more responders of ICI therapy than PRGPI-low group. Finally, the expression patterns of five selected PRGs in PRGPI were significantly different between normal and glioma.

Conclusion

The constructed PRGPI can be used for predicting prognosis and guiding individualized immunotherapy in glioma patients.

The importance of enhancer methylation for epigenetic regulation of tumorigenesis in squamous lung cancer

Lung squamous cell carcinoma (LUSC) is a subtype of non-small cell lung cancer (NSCLC). LUSC occurs at the bronchi, shows a squamous appearance, and often occurs in smokers. To determine the epigenetic regulatory mechanisms of tumorigenesis, we performed a genome-wide analysis of DNA methylation in tumor and adjacent normal tissues from LUSC patients. With the Infinium Methylation EPIC Array, > 850,000 CpG sites, including ~350,000 CpG sites for enhancer regions, were profiled, and the differentially methylated regions (DMRs) overlapping promoters (pDMRs) and enhancers (eDMRs) between tumor and normal tissues were identified. Dimension reduction based on DMR profiles revealed that eDMRs alone and not pDMRs alone can differentiate tumors from normal tissues with the equivalent performance of total DMRs. We observed a stronger negative correlation of LUSC-specific gene expression with methylation for enhancers than promoters. Target genes of eDMRs rather than pDMRs were found to be enriched for tumor-associated genes and pathways. Furthermore, DMR methylation associated with immune infiltration was more frequently observed among enhancers than promoters. Our results suggest that methylation of enhancer regions rather than promoters play more important roles in epigenetic regulation of tumorigenesis and immune infiltration in LUSC.

The developing landscape of combinatorial therapies of immune checkpoint blockade with DNA damage repair inhibitors for the treatment of breast and ovarian cancers

The use of immune checkpoint blockade (ICB) using antibodies against programmed death receptor (PD)-1, PD ligand (PD-L)-1, and cytotoxic T-lymphocyte antigen 4 (CTLA-4) has redefined the therapeutic landscape in solid tumors, including skin, lung, bladder, liver, renal, and breast tumors. However, overall response rates to ICB therapy remain limited in PD-L1-negative patients. Thus, rational and effective combination therapies will be needed to address ICB treatment resistance in these patients, as well as in PD-L1-positive patients who have progressed under ICB treatment. DNA damage repair inhibitors (DDRis) may activate T-cell responses and trigger inflammatory cytokines release and eventually immunogenic cancer cell death by amplifying DNA damage and generating immunogenic neoantigens, especially in DDR-defective tumors. DDRi may also lead to adaptive PD-L1 upregulation, providing a rationale for PD-L1/PD-1 blockade. Thus, based on preclinical evidence of efficacy and no significant overlapping toxicity, some ICB/DDRi combinations have rapidly progressed to clinical testing in breast and ovarian cancers. Here, we summarize the available clinical data on the combination of ICB with DDRi agents for treating breast and ovarian cancers and discuss the mechanisms of action and other lessons learned from translational studies conducted to date. We also review potential biomarkers to select patients most likely to respond to ICB/DDRi combination therapy.

Homozygous deletion of the HLA-B gene as an acquired-resistance mechanism to nivolumab in a patient with lung adenocarcinoma: a case report

Immune checkpoint inhibitors (ICIs) have greatly improved the treatment of advanced non-small-cell lung cancer, including lung adenocarcinoma (LUAD). Patients treated with ICIs can have long-term clinical outcomes; however, acquired resistance to ICI therapy has been frequently observed. To date, little is known about the underlying mechanisms. In this study, we report the case of a male smoker with metastatic LUAD who initially received multi-line radiotherapy and chemotherapy and achieved stable disease (SD) for almost 10 years. The patient was treated with nivolumab for about 15 months. However, the disease later progressed rapidly. A genetic profile of the patient revealed the homozygous deletion of the human leukocyte antigen (HLA)-B gene, which may have conferred the acquired resistance. Our study is the first to describe the homozygous deletion of the HLA-B gene as an acquired-resistance mechanism to programmed cell death protein 1 (PD-1) blockade in a patient with LUAD. This evidence suggests that tumor cells can selectively lose HLA-A, B, and C to survive under strong immune pressure. This discovery enriches and develops our understanding of the mechanism of drug resistance in ICI therapy in LUAD. However, further investigations are urgently needed to be conducted to determine how this resistance can be overcome.

Dl-3-N-Butylphthalide Presents Anti-Cancer Activity in Lung Cancer by Targeting PD-1/PD-L1 Signaling

Introduction

Lung cancer serves as one of the most malignant cancer types. Immunotherapy targeting PD-1/PD-L1 axis is a promising strategy for cancer treatment. Dl-3-N-butylphthalide (NBP), a small molecule compound extracted from the seeds of Apium graveolens, possesses a large range of biological effects and demonstrates anti-cancer activities. However, the role of NBP in the modulation of lung cancer remains obscure.

Methods

In this study, we aimed to explore the effect of NBP on PD-L1 signaling and the progression of lung cancer.

Results

Significantly, the treatment of NBP repressed the proliferation of lung cancer cells in vitro. Tumorigenicity analysis in nude mice showed that the tumor volume and tumor weight were attenuated by the treatment of NBP in the mice. Meanwhile, the levels of Ki-67 and PD-L1 were reduced by the treatment of NBP in the tumor tissues of the mice. NBP suppressed IFN-γ-induced PD-L1 enhancement in lung cancer cells. The treatment of NBP inhibited PD-L1 expression in lung cancer cells co-cultured with unstimulated PBMCs or activated T cell. NBP inhibited PD-1 expression in activated T cells co-cultured with lung cancer cells. Conditioned medium from activated T cells increased PD-L1 expression, and NBP reversed this effect. Co-culture with A549 and H1975 cells reduced T cell proliferation and activity, while the treatment of NBP reversed the reduction. Consistently, the treatment of NBP caused notably decreased apoptosis of co-cultured T cells. Mechanically, KAT7 was able to bind to PD-L1 promoter and epigenetically induce PD-L1 expression by promoting the enrichment of histone H3 lysine 14 acetylation (H3K14ac) and RNA polymerase II on PD-L1 promoter.

Discussion

Thus, we concluded that NBP repressed PD-L1 expression by targeting KAT7 and attenuated PD-1/PD-L1 axis to relieve lung cancer progression. NBP may be applied as the potential therapeutic strategy in immunotherapy of lung cancer.

Sex Disparities of Genomic Determinants in Response to Immune Checkpoint Inhibitors in Melanoma

Background

Despite the acknowledged sex-related differences in immune response and immune checkpoint inhibitor (ICI) efficacy, little is known about the sex disparities in melanoma of novel genomic determinants for ICI therapies.

Methods

Pretreatment genomic profiles and clinical characteristics of 631 melanoma patients treated with ICIs (i.e., inhibitors of CTLA-4, PD-1/PD-L1, or both) were comprehensively curated. Genomic factors, i.e., significantly mutated genes (SMGs), mutational signatures, and molecular subtypes were identified, and their associations with ICI treatment efficacy in male and female patients were evaluated.

Results

Of the 15 SMGs identified in this study, three genes (i.e., CFH, DGKG, and PPP6C) were found to exhibit sex differences with respect to ICI efficacy. Among these, CFH mutations exhibited both response rate and survival benefits in male, but not in female patients. A total of four mutational signatures (i.e., signatures 1, 4, 7, and 11) were extracted. Male patients with signature 4 (also known as smoking-related signature) had an inferior ICI response rate and overall survival. However, this association was not significant in females. An immune subtype based on mutational activities was found to be significantly associated with poor ICI survival in female patients.

Conclusion

We uncovered several sex-dependent genomic correlates of response to ICI treatment, such as male-biased CFH mutations and signature 4 and the female-biased immune resistance subtype. The findings derived from this research provide clues for exploring different immunotherapeutic approaches in male and female patients with melanoma.

Combined CTLA-4 and PD-L1 blockade in patients with chemotherapy-naïve metastatic castration-resistant prostate cancer is associated with increased myeloid and neutrophil immune subsets in the bone microenvironment

BACKGROUND

Immune checkpoint therapy (ICT) has low response rates in patients with metastatic castration-resistant prostate cancer (mCRPC), in part due to few T cells in the tumor microenvironment (TME). Anti-cytotoxic T lymphocyte-associated protein 4 (CTLA-4) promotes intratumoral T cell infiltration but induces upregulation of PD-1 and programmed death ligand-1 (PD-L1) within the prostate TME. Combined anti-CTLA-4 plus anti-PD-1 can partly overcome this adaptive resistance and was recently shown to augment responses in patients with mCRPC with measurable disease. Although bone is the most common site of metastasis in prostate cancer, patients with bone-predominant disease are frequently excluded from trials because they lack measurable disease, which limits assessment of disease progression and tissue sampling. We therefore designed this study to investigate combined ICT in mCRPC to bone.

HYPOTHESIS

Combined anti-CTLA-4 (tremelimumab) plus anti-PD-L1 (durvalumab) is safe and well tolerated in patients with chemotherapy-naïve mCRPC to bone.

PATIENTS AND METHODS

In this single-arm pilot study, men with chemotherapy-naïve mCRPC to bone received tremelimumab (75 mg intravenous) plus durvalumab (1500 mg intravenous) every 4 weeks (up to four doses), followed by durvalumab (1500 mg intravenous) maintenance every 4 weeks (up to nine doses). The primary endpoint was incidence of adverse events. Secondary endpoints included serum prostate-specific antigen (PSA), progression-free survival (PFS), radiographic PFS (rPFS), and maximal PSA decline.

RESULTS

Twenty-six patients were treated between August 8, 2017 and March 28, 2019. Grade ≥3 treatment-related adverse events (TRAEs) occurred in 11 patients (42%), with no grade 4 or 5 events. TRAEs leading to discontinuation occurred in three patients (12%). PSA decline ≥50% occurred in three patients (12%). Six patients (24%) achieved stable disease for >6 months. At a median follow-up of 43.6 months, median rPFS was 3.7 months (95% CI: 1.9 to 5.7), and median overall survival was 28.1 months (95% CI: 14.5 to 37.3). Post-treatment evaluation of the bone microenvironment revealed transcriptional upregulation in myeloid and neutrophil immune subset signatures and increased expression of inhibitory immune checkpoints.

CONCLUSIONS

Tremelimumab plus durvalumab was safe and well tolerated in patients with chemotherapy-naïve mCRPC to bone, with potential activity in a small number of patients as measured by rPFS. Combination of CTLA-4 and PD-L1 blockade with therapies targeting the myeloid compartment or other inhibitory immune receptors may be necessary to overcome mechanisms of resistance within prostate bone microenvironment.

TRIAL REGISTRATION NUMBER

NCT03204812.

Alterations in DNA damage response and repair genes as potential biomarkers for immune checkpoint blockade in gastrointestinal cancer

Objective:

Immune checkpoint inhibitors (ICIs) have achieved remarkable results in cancer treatments. However, there is no effective predictive biomarker for gastrointestinal (GI) cancer.

Methods:

We conducted integrative analyses of the genomic and survival data of ICI-treated GI cancer patients from the Memorial Sloan Kettering Cancer Center cohort (MSK-GI, n = 227), the Janjigian cohort (n = 40), and the Peking University Cancer Hospital & Institute cohort (PUCH, n = 80) to determine the possible associations between DNA damage response and repair (DDR) gene mutations and clinical outcomes. Data from The Cancer Genome Atlas database were analyzed to determine the possible correlations between DDR gene mutations and the tumor microenvironment.

Results:

In the MSK cohort, the presence of ≥ 2 DDR gene mutations was correlated with prolonged overall survival (OS). The Janjigian and PUCH cohorts further confirmed that subgroups with ≥ 2 DDR gene mutations displayed a prolonged OS and a higher durable clinical benefit. Furthermore, the DDR gene mutation load could be considered as an independent prognostic factor, and exhibited a potential predictive value for survival in GI cancer patients treated with ICIs. Mechanistically, we showed that the presence of ≥ 2 DDR gene mutations was correlated with higher levels of tumor mutation burden, neoantigen, and T cell infiltration.

Conclusions:

The DDR gene mutation status was correlated with favorable clinical outcomes in GI cancer patients receiving ICIs, which could serve as a potential biomarker to guide patient selection for immunotherapy.

Refining patient selection for breast cancer immunotherapy: beyond PD-L1

Therapies that modulate immune response to cancer, such as immune checkpoint inhibitors, began an intense development a few years ago; however, in breast cancer (BC), the results have been relatively disappointing so far. Finding biomarkers for better selection of BC patients for various immunotherapies remains a significant unmet medical need. At present, only tumour tissue programmed death-ligand 1 (PD-L1) and mismatch repair deficiency status are approved as theranostic biomarkers for programmed cell death-1 (PD-1)/PD-L1 inhibitors in BC. However, due to the complexity of tumour microenvironment (TME) and cancer response to immunomodulators, none of them is a perfect selector. Therefore, an intense quest is ongoing for complementary tumour- or host-related predictive biomarkers in breast immuno-oncology. Among the upcoming biomarkers, quantity, immunophenotype and spatial distribution of tumour-infiltrating lymphocytes and other TME cells as well as immune gene signatures emerge as most promising and are being increasingly tested in clinical trials. Biomarkers or strategies allowing dynamic assessment of BC response to immunotherapy, such as circulating/exosomal PD-L1, quantity of white/immune blood cell subpopulations and molecular imaging are particularly suitable for immunotreatment monitoring. Finally, host-related factors, such as microbiome and lifestyle, should also be taken into account when planning integration of immunomodulating therapies into BC management. As none of the biomarkers taken separately is accurate enough, the solution could come from composite biomarkers, which would combine clinical, molecular and immunological features of the disease, possibly powered by artificial intelligence.

•

At present, immune checkpoint inhibitors (ICIs) are the only approved immunotherapy drugs in BC.

•

Tumour PD-L1 and microsatellite status are current companion biomarkers for ICIs in BC; however, these need improvement.

•

Evaluation of tumour immune contexture and the dynamics of circulating immune cell counts are promising novel approaches.

•

Development of noninvasive monitoring and composite biomarkers will facilitate cancer immunotherapy, including in BC.

Adverse cardiovascular events in patients treated with mogamulizumab

Study objectives

Mogamulizumab is an important treatment for T-cell leukemia and lymphoma. Adverse cardiovascular events (ACE) after mogamulizumab therapy have not been investigated. The aim of the study is to investigate ACE occurrence after mogamulizumab therapy.

Methods

The International World Health Organization database, VigiBase, was analyzed from January 2013 to August 2019 for all adverse events, including ACE, that occurred after mogamulizumab treatment. ACE was defined as: cardiac death, myocardial infarction, heart failure, myocarditis, arrhythmia, vasculitis, thrombosis, palpitations and new hypertension.

Results

ACE after mogamulizumab therapy affected 28 out of 650 unique patients (4.3%). Heart failure (42.8%) and ventricular arrhythmias (17.85%) were most common. ACE accounted for 10% of all fatal adverse outcomes, and 25% of all ACE were fatal. Time to fatal outcome was significantly shorter for patients with ACE compared to non-cardiovascular events, with a mean of 7.7 days (SD 6.91) vs 73 days (SD 90.7), p = 0.017, respectively. There was an increased total number of adverse cardiovascular events in patients greater than 65 and in Asian countries.

Conclusions

Cardiovascular toxicity with mogamulizumab is a possible early occurring adverse outcome associated with high mortality.