Cancer neoantigens as potential targets for immunotherapy

Genomic instabilities in hepatocellular carcinoma: biomarkers and application in immunotherapies

Hepatocellular carcinoma (HCC) is one of the deadliest cancers. For patients with advanced HCC, liver function decompensation often occurs, which leads to poor tolerance to chemotherapies and other aggressive treatments. Therefore, it remains critical to develop effective therapeutic strategies for HCC. Etiological factors for HCC are complex and multifaceted, including hepatitis virus infection, alcohol, drug abuse, chronic metabolic abnormalities, and others. Thus, HCC has been categorized as a "genomically unstable" cancer due to the typical manifestation of chromosome breakage and aneuploidy, and oxidative DNA damage. In recent years, immunotherapy has provided a new option for cancer treatments, and the degree of genomic instability positively correlates with immunotherapy efficacies. This article reviews the endogenous and exogenous causes that affect the genomic stability of liver cells; it also updates the current biomarkers and their detection methods for genomic instabilities and relevant applications in cancer immunotherapies. Including genomic instability biomarkers in consideration of cancer treatment options shall increase the patients' well-being.

Immune responses and immunotherapeutic approaches in the treatment against cancer

Cancer cells within a population are heterogeneous due to genomic mutations or epigenetic changes. The immune response to cancer especially the T cell repertoire within the cancer microenvionment is important to the control and growth of cancer cells. When a cancer clone breaks through the surveillance of the immune system, it wins the battle to overcome the host's immune system. In this review, the complicated profile of the cancer microenvironment is emphasized. The molecular evidence of immune responses to cancer has been recently established. Based on these molecular mechanisms of immune interactions with cancer, clinical trials based on checkpoint inhibition therapy against CTLA-4 and/or PD-1 versus PD-L1 have been successful in the treatment of melanoma, lung cancer and other types of cancer. The diversity of the T cell repertoire is described and the tumor infiltrating lymphocytes within the cancer may be expanded ex vivo and infused back to the patient as a treatment modality for adoptive immunotherapy.

Immunologic tumor microenvironment modulators for turning cold tumors hot

Tumors can be classified into distinct immunophenotypes based on the presence and arrangement of cytotoxic immune cells within the tumor microenvironment (TME). Hot tumors, characterized by heightened immune activity and responsiveness to immune checkpoint inhibitors (ICIs), stand in stark contrast to cold tumors, which lack immune infiltration and remain resistant to therapy. To overcome immune evasion mechanisms employed by tumor cells, novel immunologic modulators have emerged, particularly ICIs targeting cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and programmed cell death protein 1/programmed death-ligand 1(PD-1/PD-L1). These agents disrupt inhibitory signals and reactivate the immune system, transforming cold tumors into hot ones and promoting effective antitumor responses. However, challenges persist, including primary resistance to immunotherapy, autoimmune side effects, and tumor response heterogeneity. Addressing these challenges requires innovative strategies, deeper mechanistic insights, and a combination of immune interventions to enhance the effectiveness of immunotherapies. In the landscape of cancer medicine, where immune cold tumors represent a formidable hurdle, understanding the TME and harnessing its potential to reprogram the immune response is paramount. This review sheds light on current advancements and future directions in the quest for more effective and safer cancer treatment strategies, offering hope for patients with immune-resistant tumors.

Tri-specific killer engager: unleashing multi-synergic power against cancer

Cancer continues to be a global health concern, necessitating innovative solutions for treatment. Tri-specific killer engagers (TriKEs) have emerged as a promising class of immunotherapeutic agents, offering a multifaceted approach to cancer treatment. TriKEs simultaneously engage and activate natural killer (NK) cells while specifically targeting cancer cells, representing an outstanding advancement in immunotherapy. This review explores the generation and mechanisms of TriKEs, highlighting their advantages over other immunotherapies and discussing their potential impact on clinical trials and cancer treatment. TriKEs are composed of three distinct domains, primarily antibody-derived building blocks, linked together by short amino acid sequences. They incorporate critical elements, anti-cluster of differentiation 16 (CD16) and interleukin-15 (IL-15), which activate and enhance NK cell function, together with specific antibody to target each cancer. TriKEs exhibit remarkable potential in preclinical and early clinical studies across various cancer types, making them a versatile tool in cancer immunotherapy. Comparative analyses with other immunotherapies, such as chimeric antigen receptor-T (CAR-T) cell therapy, immune checkpoint inhibitors (ICIs), cytokine therapies, and monoclonal antibodies (mAbs), reveal the unique advantages of TriKEs. They offer a safer pathway for immunotherapy by targeting cancer cells without hyperactivating T cells, reducing off-target effects and complications. The future of TriKEs involves addressing challenges related to dosing, tumor-associated antigen (TAA) expression, and NK cell suppression. Researchers are exploring innovative dosing strategies, enhancing specificity through tumor-specific antigens (TSAs), and combining TriKEs with other therapies for increased efficacy.

Advancing nanotechnology for neoantigen-based cancer theranostics

Neoantigens play a pivotal role in the field of tumour therapy, encompassing the stimulation of anti-tumour immune response and the enhancement of tumour targeting capability. Nonetheless, numerous factors directly influence the effectiveness of neoantigens in bolstering anti-tumour immune responses, including neoantigen quantity and specificity, uptake rates by antigen-presenting cells (APCs), residence duration within the tumour microenvironment (TME), and their ability to facilitate the maturation of APCs for immune response activation. Nanotechnology assumes a significant role in several aspects, including facilitating neoantigen release, promoting neoantigen delivery to antigen-presenting cells, augmenting neoantigen uptake by dendritic cells, shielding neoantigens from protease degradation, and optimizing interactions between neoantigens and the immune system. Consequently, the development of nanotechnology synergistically enhances the efficacy of neoantigens in cancer theranostics. In this review, we provide an overview of neoantigen sources, the mechanisms of neoantigen-induced immune responses, and the evolution of precision neoantigen-based nanomedicine. This encompasses various therapeutic modalities, such as neoantigen-based immunotherapy, phototherapy, radiotherapy, chemotherapy, chemodynamic therapy, and other strategies tailored to augment precision in cancer therapeutics. We also discuss the current challenges and prospects in the application of neoantigen-based precision nanomedicine, aiming to expedite its clinical translation.

Pan-cancer and single-cell analyses identify CD44 as an immunotherapy response predictor and regulating macrophage polarization and tumor progression in colorectal cancer

Introduction

Cluster of differentiation (CD) 44 is a non-kinase cell surface transmembrane glycoprotein critical for tumor maintenance and progression.

Methods

We conducted a systematic analysis of the expression profile and genomic alteration profile of CD44 in 33 types of cancer. The immune characteristics of CD44 were comprehensively explored by TIMER2.0 and CIBERSORT. In addition, the CD44 transcriptional landscape was examined at the single-cell level. Then, Pseudotime trajectory analysis of CD44 gene expression was performed using Monocle 2, and CellChat was utilized to compare the crosstalk differences between CD44+monocytes and CD44- monocytes. Tumor immune dysfunction and exclusion (TIDE) was used to evaluate the predictive ability of CD44 for immune checkpoint blockade (ICB) responses. The effects of CD44 on colorectal cancer (CRC) and macrophage polarization were investigated by knocking down the expression of CD44 in HCT-116 cell and macrophages in vitro.

Results

The expression of CD44 elevated in most cancers, predicting unfavorable prognosis. In addditon, CD44 was correlation with immune cell infiltration and key immune regulators. CD44+ monocytes had a higher information flow intensity than CD44- monocytes. CD44 had good predictive ability for immune checkpoint blockade responses. Knockdown of CD44 inhibited the proliferation, migration, and invasion of HCT-116 cell in vitro. Knockdown of CD44 inhibited M2 macrophage polarization.

Discussion

These findings suggest that CD44 is involved in regulating tumor development, macrophage polarization, and has certain predictive value for patient clinical prognosis and response to immunotherapy.

Nanomaterial Delivery Vehicles for the Development of Neoantigen Tumor Vaccines for Personalized Treatment

Tumor vaccines have been considered a promising therapeutic approach for treating cancer in recent years. With the development of sequencing technologies, tumor vaccines based on neoantigens or genomes specifically expressed in tumor cells, mainly in the form of peptides, nucleic acids, and dendritic cells, are beginning to receive widespread attention. Therefore, in this review, we have introduced different forms of neoantigen vaccines and discussed the development of these vaccines in treating cancer. Furthermore, neoantigen vaccines are influenced by factors such as antigen stability, weak immunogenicity, and biosafety in addition to sequencing technology. Hence, the biological nanomaterials, polymeric nanomaterials, inorganic nanomaterials, etc., used as vaccine carriers are principally summarized here, which may contribute to the design of neoantigen vaccines for improved stability and better efficacy.

Integrative analysis confirms TPX2 as a novel biomarker for clinical implication, tumor microenvironment, and immunotherapy response across human solid tumors

Targeting Protein for Xenopus Kinesin Like Protein 2 (TPX2) serves as a microtubule associated protein for the regulation of spindle assembly and tumorigenesis. We aim to investigate the prognostic and immunological role of TPX2 in pan-cancer. TCGA database, Tumor Immune Single-cell Hub (TISCH), and Human Protein Atlas (HPA) were retrieved to evaluate the expression pattern of TPX2 as well as its diagnostic and prognostic value in solid tumors. Genomic alterations of TPX2 were assessed with cBioPortal database. In vitro experiments in lung adenocarcinoma (LUAD) were performed to confirm the potential role of TPX2. Overexpression of TPX2 was found in 22 types of cancers, and was positively related with copy number variations (CNV) and negative with methylation. Up-regulated TPX2 could predict worse outcomes in the majority of cancers. Single-cell analysis revealed that TPX2 was mainly distributed in malignant cells (especially in glioma) and proliferating T cells. Genomic alteration of TPX2 was common in different types of tumors, while with prognostic value in two types of cancers. Additionally, significant correlations were found between TPX2 expression and tumor microenvironment (including stromal cells and immune cells) as well as immune related genes across cancer types. Drug sensitivity analysis revealed that TPX2 could predict response to chemotherapy and immunotherapy. Functional analyses demonstrated close relationship of TPX2 with immune function and malignant phenotypes. Finally, it was confirmed that knockdown of TPX2 could reduce proliferation and migration ability of LUAD cells. In summary, TPX2 could serve as a diagnostic and prognostic biomarker and a potential immunotherapy marker.

Targeting Tumor Heterogeneity with Neoantigen-Based Cancer Vaccines

Neoantigen-based cancer vaccines have emerged as a promising immunotherapeutic approach to treat cancer. Nevertheless, the high degree of heterogeneity in tumors poses a significant hurdle for developing a vaccine that targets the therapeutically relevant neoantigens capable of effectively stimulating an immune response as each tumor contains numerous unique putative neoantigens. Understanding the complexities of tumor heterogeneity is crucial for the development of personalized neoantigen-based vaccines, which hold the potential to revolutionize cancer treatment and improve patient outcomes. In this review, we discuss recent advancements in the design of neoantigen-based cancer vaccines emphasizing the identification, validation, formulation, and targeting of neoantigens while addressing the challenges posed by tumor heterogeneity. The review highlights the application of cutting-edge approaches, such as single-cell sequencing and artificial intelligence to identify immunogenic neoantigens, while outlining current limitations and proposing future research directions to develop effective neoantigen-based vaccines.

Neoantigen cancer vaccines: a new star on the horizon

Immunotherapy represents a promising strategy for cancer treatment that utilizes immune cells or drugs to activate the patient's own immune system and eliminate cancer cells. One of the most exciting advances within this field is the targeting of neoantigens, which are peptides derived from non-synonymous somatic mutations that are found exclusively within cancer cells and absent in normal cells. Although neoantigen-based therapeutic vaccines have not received approval for standard cancer treatment, early clinical trials have yielded encouraging outcomes as standalone monotherapy or when combined with checkpoint inhibitors. Progress made in high-throughput sequencing and bioinformatics have greatly facilitated the precise and efficient identification of neoantigens. Consequently, personalized neoantigen-based vaccines tailored to each patient have been developed that are capable of eliciting a robust and long-lasting immune response which effectively eliminates tumors and prevents recurrences. This review provides a concise overview consolidating the latest clinical advances in neoantigen-based therapeutic vaccines, and also discusses challenges and future perspectives for this innovative approach, particularly emphasizing the potential of neoantigen-based therapeutic vaccines to enhance clinical efficacy against advanced solid tumors.

Immune checkpoint inhibitors in breast cancer: development, mechanisms of resistance and potential management strategies

The use of immune checkpoint inhibitors (ICIs) has increased exponentially in the past decade, although its progress specifically for breast cancer has been modest. The first U.S. Food and Drug Administration approval for ICI in breast cancer came in 2019, eight years after the first-ever approval of an ICI. At present, current indications for ICIs are relevant only to a subset of patients with triple-negative breast cancer, or those displaying high microsatellite instability or deficiency in the mismatch repair protein pathway. With an increasing understanding of the limitations of using ICIs, which stem from breast cancer being innately poorly immunogenic, as well as the presence of various intrinsic and acquired resistance pathways, ongoing trials are evaluating different combination therapies to overcome these barriers. In this review, we aim to describe the development timeline of ICIs and resistance mechanisms limiting their utility, and summarise the available approaches and ongoing trials relevant to overcoming each resistance mechanism.

Colorectal Cancer Immunotherapy: State of the Art and Future Directions

Cancer immunotherapy has become an indispensable mode of treatment for a multitude of solid tumor cancers. Colorectal cancer (CRC) has been one of the many cancer types to benefit from immunotherapy, especially in advanced disease where standard treatment fails to prevent recurrence or results in poor survival. The efficacy of immunotherapy in CRC has not been without challenge, as early clinical trials observed dismal responses in unselected CRC patients treated with checkpoint inhibitors. Many studies and clinical trials have since refined immunotherapies available for CRC, solidifying immunotherapy as a powerful asset for CRC treatment. This review article examines CRC immunotherapies, from their foundation, through emerging avenues for improvement, to future directions.

The screening, identification, design and clinical application of tumor-specific neoantigens for TCR-T cells

Recent advances in neoantigen research have accelerated the development of tumor immunotherapies, including adoptive cell therapies (ACTs), cancer vaccines and antibody-based therapies, particularly for solid tumors. With the development of next-generation sequencing and bioinformatics technology, the rapid identification and prediction of tumor-specific antigens (TSAs) has become possible. Compared with tumor-associated antigens (TAAs), highly immunogenic TSAs provide new targets for personalized tumor immunotherapy and can be used as prospective indicators for predicting tumor patient survival, prognosis, and immune checkpoint blockade response. Here, the identification and characterization of neoantigens and the clinical application of neoantigen-based TCR-T immunotherapy strategies are summarized, and the current status, inherent challenges, and clinical translational potential of these strategies are discussed.

Unveiling the interplay between mutational signatures and tumor microenvironment: a pan-cancer analysis

Background

While recent studies have separately explored mutational signatures and the tumor microenvironment (TME), there is limited research on the associations of both factors in a pan-cancer context.

Materials and methods

We performed a pan-cancer analysis of over 8,000 tumor samples from The Cancer Genome Atlas (TCGA) project. Machine learning methods were employed to systematically explore the relationship between mutational signatures and TME and develop a risk score based on TME-associated mutational signatures to predict patient survival outcomes. We also constructed an interaction model to explore how mutational signatures and TME interact and influence cancer prognosis.

Results

Our analysis revealed a varied association between mutational signatures and TME, with the Clock-like signature showing the most widespread influence. Risk scores based on mutational signatures mainly induced by Clock-like and AID/APOBEC activity exhibited strong pan-cancer survival stratification ability. We also propose a novel approach to predict transcriptome decomposed infiltration levels using genome-derived mutational signatures as an alternative approach for exploring TME cell types when transcriptome data are unavailable. Our comprehensive analysis revealed that certain mutational signatures and their interaction with immune cells significantly impact clinical outcomes in particular cancer types. For instance, T cell infiltration levels only served as a prognostic biomarker in melanoma patients with high ultraviolet radiation exposure, breast cancer patients with high homologous recombination deficiency signature, and lung adenocarcinoma patients with high tobacco-associated mutational signature.

Conclusion

Our study comprehensively explains the complex interplay between mutational signatures and immune infiltration in cancer. The results highlight the importance of considering both mutational signatures and immune phenotypes in cancer research and their significant implications for developing personalized cancer treatments and more effective immunotherapy.

Autologous dendritic cells loaded with antigens from self-renewing autologous tumor cells as patient-specific therapeutic cancer vaccines

A promising personal immunotherapy is autologous dendritic cells (DC) loaded ex vivo with autologous tumor antigens (ATA) derived from self-renewing autologous cancer cells. DC-ATA are suspended in granulocyte-macrophage colony stimulating factor at the time of each subcutaneous injection. Previously, irradiated autologous tumor cell vaccines have produced encouraging results in 150 cancer patients, but the DC-ATA vaccine demonstrated superiority in single-arm and randomized trials in metastatic melanoma. DC-ATA have been injected into more than 200 patients with melanoma, glioblastoma, and ovarian, hepatocellular, and renal cell cancers. Key observations include: [1] greater than 95% success rates for tumor cell cultures and monocyte collection for dendritic cell production; [2] injections are well-tolerated; [3] the immune response is rapid and includes primarily TH1/TH17 cellular responses; [4] efficacy has been suggested by delayed but durable complete tumor regressions in patients with measurable disease, by progression-free survival in glioblastoma, and by overall survival in melanoma.

Construction and systematic evaluation of a machine learning-based cuproptosis-related lncRNA score signature to predict the response to immunotherapy in hepatocellular carcinoma

Introduction

Hepatocellular carcinoma (HCC) is a common malignant cancer with a poor prognosis. Cuproptosis and associated lncRNAs are connected with cancer progression. However, the information on the prognostic value of cuproptosis-related lncRNAs is still limited in HCC.

Methods

We isolated the transcriptome and clinical information of HCC from TCGA and ICGC databases. Ten cuproptosis-related genes were obtained and related lncRNAs were correlated by Pearson's correlation. By performing lasso regression, we created a cuproptosis-related lncRNA prognostic model based on the cuproptosis-related lncRNA score (CLS). Comprehensive analyses were performed, including the fields of function, immunity, mutation and clinical application, by various R packages.

Results

Ten cuproptosis-related genes were selected, and 13 correlated prognostic lncRNAs were collected for model construction. CLS was positively or negatively correlated with cancer-related pathways. In addition, cell cycle and immune related pathways were enriched. By performing tumor microenvironment (TME) analysis, we determined that T-cells were activated. High CLS had more tumor characteristics and may lead to higher invasiveness and treatment resistance. Three genes (TP53, CSMD1 and RB1) were found in high CLS samples with more mutational frequency. More amplification and deletion were detected in high CLS samples. In clinical application, a CLS-based nomogram was constructed. 5-Fluorouracil, gemcitabine and doxorubicin had better sensitivity in patients with high CLS. However, patients with low CLS had better immunotherapeutic sensitivity.

Conclusion

We created a prognostic CLS signature by machine learning, and we comprehensively analyzed the signature in the fields of function, immunity, mutation and clinical application.

SARS-CoV-2-correlated ASGR1 is a novel potential marker for the treatment and identification of multiple human cancers

OBJECTIVES

Cancer patients are reported to be more susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the COVID-19 (the Corona Virus Disease 2019) patients with cancer suffer from certain serious complications. ASGR1 has been recently identified as a novel receptor of SARS-CoV-2 in human cells; however, there are limited studies on ASGR1 in various human cancers.

METHODS

This study utilized a comprehensive analysis of COVID-19-related ASGR1 in multiple human cancers based on 18,589 multi-center samples. Using Wilcoxon rank-sum analysis, a difference in ASGR1 expression between cancer and control tissues was detected. Cox regression analysis, Kaplan-Meier curves, and receiver operating characteristic curves were utilized to determine the correlation between ASGR1 expression and the clinical parameters of cancer patients. The immune relevance and potential mechanisms of ASGR1 in various cancers were also investigated.

RESULTS

Abnormal ASGR1 mRNA expression was observed in 16 of 20 different cancers (e.g., it was upregulated in colon adenocarcinoma but downregulated in cholangiocarcinoma; P < 0.05). ASGR1 was related to prognosis, e.g., overall survival, in 14 cancers (P < 0.05), such as adrenocortical carcinoma. The gene was also found to be a potential marker that can be utilized to distinguish eleven cancers from controls with moderate to high accuracy (e.g., the area under the curve for cholangiocarcinoma = 1.000). ASGR1 expression was related to DNA methyltransferases, mismatch repair genes, immune checkpoints, levels of tumor mutational burden, microsatellite instability, neoantigen count, and immune infiltration levels in certain cancers (P < 0.05). The gene plays a role in multiple cancers by affecting four signaling pathways, such as cytokine-cytokine receptor interaction. Cancer patients with high ASGR1 expression are sensitive to 25 drugs, including ulixertinib.

CONCLUSIONS

SARS-CoV-2-correlated ASGR1 is a novel marker that can be used for treating and identifying multiple human cancers.

Towards an accurate and robust analysis pipeline for somatic mutation calling

Accurate and robust somatic mutation detection is essential for cancer treatment, diagnostics and research. Various analysis pipelines give different results and thus should be systematically evaluated. In this study, we benchmarked 5 commonly-used somatic mutation calling pipelines (VarScan, VarDictJava, Mutect2, Strelka2 and FANSe) for their precision, recall and speed, using standard benchmarking datasets based on a series of real-world whole-exome sequencing datasets. All the 5 pipelines showed very high precision in all cases, and high recall rate in mutation rates higher than 10%. However, for the low frequency mutations, these pipelines showed large difference. FANSe showed the highest accuracy (especially the sensitivity) in all cases, and VarScan and VarDictJava outperformed Mutect2 and Strelka2 in low frequency mutations at all sequencing depths. The flaws in filter was the major cause of the low sensitivity of the four pipelines other than FANSe. Concerning the speed, FANSe pipeline was 8.8∼19x faster than the other pipelines. Our benchmarking results demonstrated performance of the somatic calling pipelines and provided a reference for a proper choice of such pipelines in cancer applications.

Neoantigen Vaccines; Clinical Trials, Classes, Indications, Adjuvants and Combinatorial Treatments

Simple Summary

Personalized neoantigen vaccines are a diverse group of personally tailored cancer vaccines that strengthen patients´ own immune reaction against cancer antigens. We analyzed 147 neoantigen vaccine clinical trials from ClinicalTrials.gov database and showed that peptide vaccines were the dominating vaccine type, while there were multiple new neoantigen vaccine types in the field. We also showed that neoantigen vaccines were mostly used in the treatment of small cell lung cancer, non-small cell lung cancer, melanoma, and glioma. According to our results neoantigen vaccines work at their best when combined with other treatments such as immune checkpoint inhibitors, chemotherapy, and radiation therapy. The effect of some neoantigen vaccine types were also often promoted with adjuvant therapy where poly-ICLC were the most recurrent adjuvant choice.

Abstract

Personalized neoantigen vaccines are a highly specific cancer treatment designed to induce a robust cytotoxic T-cell attack against a patient’s cancer antigens. In this study, we searched ClinicalTrials.gov for neoantigen vaccine clinical trials and systematically analyzed them, a total of 147 trials. Peptide vaccines are the largest neoantigen vaccine type, comprising up to 41% of the clinical trials. However, mRNA vaccines are a growing neoantigen vaccine group, especially in the most recent clinical trials. The most common cancer types in the clinical trials are glioma, lung cancer, and malignant melanoma, being seen in more than half of the clinical trials. Small-cell lung cancer and non-small-cell lung cancer are the largest individual cancer types. According to the results from the clinical trials, neoantigen vaccines work best when combined with other cancer treatments, and popular combination treatments include immune checkpoint inhibitors, chemotherapy, and radiation therapy. Additionally, half of the clinical trials combined neoantigen vaccines with an adjuvant to boost the immune effects, with poly-ICLC being the most recurrent adjuvant choice. This study clarifies the rapid clinical trial development of personalized neoantigen vaccines as an emerging class of cancer treatment with increasingly diversified opportunities in classes, indications, and combinatorial treatments.

Hospitalized cancer patients with comorbidities and low lymphocyte counts had poor clinical outcomes to immune checkpoint inhibitors

Background

Immune checkpoint inhibitor (ICI) therapy has improved survivals with a favorable toxicity profile in a variety of cancer patients. We hypothesized that hospitalized cancer patients who have acute or chronic comorbidities may have suppressed immune systems and poor clinical outcomes to ICIs. The objective of this study was to explore clinical outcomes and predictive factors of hospitalized cancer patients who received ICI therapy at an NCI-designated Comprehensive Cancer Center.

Methods

A retrospective review of electronic medical records was conducted for adult cancer patients who received an FDA-approved ICI during admission from 08/2016 to 01/2022. For each patient we extracted demographics, cancer histology, comorbidities, reasons for hospitalization, ICI administered, time from treatment to discharge, time from treatment to progression or death, and complete blood counts. Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method and compared using the log-rank test. The 95% confidence interval for survival was calculated using the exact binomial distribution. Statistical significance was defined as 2-sided p<0.05.

Results

Of 37 patients identified, 2 were excluded due to lack of complete blood counts on admission. Average hospital stay was 24.2 (95% CI 16.5, 31.9) days. Ten (27.0%) patients died during the same hospitalization as treatment. Of those who followed up, 22 (59.5%) died within 90 days of inpatient therapy. The median PFS was 0.86 (95% CI 0.43, 1.74) months and median OS was 1.55 (95% CI 0.76, 3.72) months. Patients with ≥3 comorbidities had poorer PFS (2.4 vs. 0.4 months; p=0.0029) and OS (5.5 vs. 0.6 months; p=0.0006). Pre-treatment absolute lymphocyte counts (ALC) <600 cells/µL were associated with poor PFS (0.33 vs. 1.35 months; p=0.0053) and poor OS (0.33 vs. 2.34 months; p=0.0236). Pre-treatment derived neutrophil to lymphocyte ratio (dNLR) <4 was associated with good median PFS (1.6 vs. 0.4 months; p=0.0157) and OS (2.8 vs. 0.9 months; p=0.0375).

Conclusions

Administration of ICI therapy was associated with poor clinical outcomes and high rates of both inpatient mortality and 90-day mortality after inpatient ICI therapy. The presence of ≥3 comorbidities, ALC <600/μL, or dNLR >4 in hospitalized patients was associated with poor survival outcomes.

CDK2AP1 influences immune infiltrates and serves as a prognostic indicator for hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is a tumor with high malignancy and poor 5-years survival rate. Excellent tumor markers are very important for early clinical diagnosis and prognosis evaluation. Previous studies have shown that CDK2AP1 (Cyclin-dependent kinase 2-associated protein 1) is involved in cell-cycle and epigenetic regulation. In the present study, we assess CDK2AP1 expression, prognostic value, immunomodulatory and possible influencing pathways in HCC.

Method: The Cancer Genome Atlas (TCGA) database was used to analyse gene expression, clinicopathology and prognosis. The protein level of CDK2AP1 in HCC tissues was detected in the Human Protein Atlas (HPA) database. The immune score in HCC to CDKAP1 expression were analyzed using ESTIMATE. Furthermore, we use Tumor IMmune Estimation Resource (TIMER) database to study CDK2AP1 expression and Immune Infiltration Levels in HCC. Co-expressed genes of CDK2AP1 were predicted and elaborated by LinkedOmics.

Results: In normal liver tissues, the expression of CDK2AP1 was significantly lower than tumor tissues, and was correlated with the level of clinical stage and histologic grade in HCC patients. Patients with high expression of CDK2AP1 have a poor prognosis than patients with low CDK2AP1 expression. CDK2AP1 expression level exhibits significantly positive correlations with the number of infiltrating B cells, CD4+ T cells, CD8+ T cells, Macrophages, Neutrophils, and DCs in HCC tissues. KEGG enrichment analysis showed that the related pathways affected by CDK2AP1 mainly include: Fc gamma R-mediated phagocytosis, Th1 and Th2 cell differentiation, Cell cycle, etc. Both in vitro and in vivo experiments confirmed that CDK2AP1 promotes the proliferation and metastasis in hepatocellular carcinoma. Our results highlight the role of CDK2AP1 as an important prognostic indicator and immunotherapy target for HCC patients.

Conclusion: We found CDK2AP1 as a new prognostic biomarker for HCC, which could help explain changes in the biological processes and immune environment lead to liver cancer development. Therefore, CDK2AP1 is a potential new target for HCC therapy.

A Proposed Link Between Acute Thymic Involution and Late Adverse Effects of Chemotherapy

Epidemiologic data suggest that cancer survivors tend to develop a protuberant number of adverse late effects, including second primary malignancies (SPM), as a result of cytotoxic chemotherapy. Besides the genotoxic potential of these drugs that directly inflict mutational burden on genomic DNA, the precise mechanisms contributing to SPM development are poorly understood. Cancer is nowadays perceived as a complex process that goes beyond the concept of genetic disease and includes tumor cell interactions with complex stromal and immune cell microenvironments. The cancer immunoediting theory offers an explanation for the development of nascent neoplastic cells. Briefly, the theory suggests that newly emerging tumor cells are mostly eliminated by an effective tissue immunosurveillance, but certain tumor variants may occasionally escape innate and adaptive mechanisms of immunological destruction, entering an equilibrium phase, where immunologic tumor cell death "equals" new tumor cell birth. Subsequent microenvironmental pressures and accumulation of helpful mutations in certain variants may lead to escape from the equilibrium phase, and eventually cause an overt neoplasm. Cancer immunoediting functions as a dedicated sentinel under the auspice of a highly competent immune system. This perspective offers the fresh insight that chemotherapy-induced thymic involution, which is characterized by the extensive obliteration of the sensitive thymic epithelial cell (TEC) compartment, can cause long-term defects in thymopoiesis and in establishment of diverse T cell receptor repertoires and peripheral T cell pools of cancer survivors. Such delayed recovery of T cell adaptive immunity may result in prolonged hijacking of the cancer immunoediting mechanisms, and lead to development of persistent and mortal infections, inflammatory disorders, organ-specific autoimmunity lesions, and SPMs. Acknowledging that chemotherapy-induced thymic involution is a potential risk factor for the emergence of SPM demarcates new avenues for the rationalized development of pharmacologic interventions to promote thymic regeneration in patients receiving cytoreductive chemotherapies.

Biomarkers for response to immune checkpoint inhibitors in gastrointestinal cancers

Gastrointestinal (GI) cancers account for a large proportion of cancer deaths worldwide and pose a major public health challenge. Immunotherapy is considered to be one of the prominent and successful approaches in cancer treatment in recent years. Among them, immune checkpoint inhibitor (ICI) therapy, has received widespread attention, and many clinical findings support the feasibility of ICIs, with sustained responses and significantly prolonged lifespan observed in a wide range of tumors. However, patients treated with ICIs have not fully benefited, and therefore, the identification and development of biomarkers for predicting ICI treatment response have received further attention and exploration. From tumor genome to molecular interactions in the tumor microenvironment, and further expanding to circulating biomarkers and patient characteristics, the exploration of biomarkers is evolving with high-throughput sequencing as well as bioinformatics. More large-scale prospective and specific studies are needed to explore biomarkers in GI cancers. In this review, we summarize the known biomarkers used in ICI therapy for GI tumors. In addition, some ICI biomarkers applied to other tumors are included to provide insights and further validation for GI tumors. Moreover, we present single-cell analysis and machine learning approaches that have emerged in recent years. Although there are no clear applications yet, it can be expected that these techniques will play an important role in the application of biomarker prediction.

CCR4 as a Therapeutic Target for Cancer Immunotherapy

Simple Summary

CCR4 is a chemokine receptor selectively expressed on normal T cell subsets such as type 2 helper T cells, skin-homing T cells and regulatory T cells, and on skin-associated T cell malignancies such as adult T cell leukemia/lymphoma (ATLL), which is etiologically associated with human T lymphocyte virus type 1 (HTLV-1), and cutaneous T cell lymphomas (CTCLs). Mogamulizumab is a fully humanized and glyco-engineered monoclonal anti-CCR4 antibody used for the treatment of refractory/relapsed ATLL and CTCLs, often resulting in complete remission. The clinical applications of Mogamulizumab are now being extended to solid tumors, exploring the therapeutic effect of regulatory T cell depletion. This review overviews the expression of CCR4 in various T cell subsets, HTLV-1-infected T cells, ATLL and CTCLs, and the clinical applications of Mogamulizumab.

Abstract

CCR4 is a chemokine receptor mainly expressed by T cells. It is the receptor for two CC chemokine ligands, CCL17 and CCL22. Originally, the expression of CCR4 was described as highly selective for helper T type 2 (Th2) cells. Later, its expression was extended to other T cell subsets such as regulatory T (Treg) cells and Th17 cells. CCR4 has long been regarded as a potential therapeutic target for allergic diseases such as atopic dermatitis and bronchial asthma. Furthermore, the findings showing that CCR4 is strongly expressed by T cell malignancies such as adult T cell leukemia/lymphoma (ATLL) and cutaneous T cell lymphomas (CTCLs) have led to the development and clinical application of the fully humanized and glyco-engineered monoclonal anti-CCR4 Mogamulizumab in refractory/relapsed ATLL and CTCLs with remarkable successes. However, Mogamulizumab often induces severe adverse events in the skin possibly because of its efficient depletion of Treg cells. In particular, treatment with Mogamulizumab prior to allogenic hematopoietic stem cell transplantation (allo-HSCT), the only curative option of these T cell malignancies, often leads to severe glucocorticoid-refractory graft-versus-host diseases. The efficient depletion of Treg cells by Mogamulizumab has also led to its clinical trials in advanced solid tumors singly or in combination with immune checkpoint inhibitors. The main focus of this review is CCR4; its expression on normal and malignant T cells and its significance as a therapeutic target in cancer immunotherapy.