Harnessing big data to characterize immune-related adverse events

The Digital Revolution in Medicine: Applications in Cardio-Oncology

Purpose of review

A critical evaluation of contemporary literature regarding the role of big data, artificial intelligence, and digital technologies in precision cardio-oncology care and survivorship, emphasizing innovative and groundbreaking endeavors.

Recent findings

Artificial intelligence (AI) algorithm models can automate the risk assessment process and augment current subjective clinical decision tools. AI, particularly machine learning (ML), can identify medically significant patterns in large data sets. Machine learning in cardio-oncology care has great potential in screening, diagnosis, monitoring, and managing cancer therapy-related cardiovascular complications. To this end, large-scale imaging data and clinical information are being leveraged in training efficient AI algorithms that may lead to effective clinical tools for caring for this vulnerable population. Telemedicine may benefit cardio-oncology patients by enhancing healthcare delivery through lowering costs, improving quality, and personalizing care. Similarly, the utilization of wearable biosensors and mobile health technology for remote monitoring holds the potential to improve cardio-oncology outcomes through early intervention and deeper clinical insight. Investigations are ongoing regarding the application of digital health tools such as telemedicine and remote monitoring devices in enhancing the functional status and recovery of cancer patients, particularly those with limited access to centralized services, by increasing physical activity levels and providing access to rehabilitation services.

Summary

In recent years, advances in cancer survival have increased the prevalence of patients experiencing cancer therapy-related cardiovascular complications. Traditional cardio-oncology risk categorization largely relies on basic clinical features and physician assessment, necessitating advancements in machine learning to create objective prediction models using diverse data sources. Healthcare disparities may be perpetuated through AI algorithms in digital health technologies. In turn, this may have a detrimental effect on minority populations by limiting resource allocation. Several AI-powered innovative health tools could be leveraged to bridge the digital divide and improve access to equitable care.

A systematic review of gastritis as an immune-related adverse event in clinical interventions

Immune checkpoint inhibitors (ICIs) are crucial in cancer treatment, and the associated immune-related adverse events (irAEs) have garnered significant attention, yet reports on associated immune related gastritis are limited. The diagnosis of immune related gastritis remains predominantly exclusionary, meanwhile its management diverges significantly from that of conventional gastritis. Current guidelines lack standardized grading criteria, and substantial data from large-scale, tertiary clinical studies are absent, therefore we conducted a systematic review of Medline, Web of Science, and Embase databases, identifying 31 articles from 2017 to December 31, 2023, involving 258 patients. Clinical manifestations included epigastric pain (53.1%), mucosal erythema (56.1%), and lymphocyte infiltration (48.6%). Corticosteroid therapy was common (94.7%), with 86.7% experiencing post-treatment improvement. 80% of patients can be diagnosed through endoscopy and pathology, while the remaining 20% may require PET-CT. Hormonal therapy is favored but diverges from standard management. Accurate diagnosis is crucial in managing immune related gastritis effectively.

Leveraging pharmacovigilance data to predict population-scale toxicity profiles of checkpoint inhibitor immunotherapy

Immune checkpoint inhibitor (ICI) therapies have made considerable advances in cancer immunotherapy, but the complex and diverse spectrum of ICI-induced toxicities poses substantial challenges to treatment outcomes and computational analysis. Here we introduce DySPred, a dynamic graph convolutional network-based deep learning framework, to map and predict the toxicity profiles of ICIs at the population level by leveraging large-scale real-world pharmacovigilance data. DySPred accurately predicts toxicity risks across diverse demographic cohorts and cancer types, demonstrating resilience in small-sample scenarios and revealing toxicity trends over time. Furthermore, DySPred consistently aligns the toxicity-safety profiles of small-molecule antineoplastic agents with their drug-induced transcriptional alterations. Our study provides a versatile methodology for population-level profiling of ICI-induced toxicities, enabling proactive toxicity monitoring and timely tailoring of treatment and intervention strategies in the advancement of cancer immunotherapy.

Frequency and Consequences of Immune Checkpoint Inhibitor-Associated Inflammatory Changes in Different Organs: An Autopsy Study Over 13 -Years

Although immune checkpoint inhibitors (ICIs) have revolutionized modern oncology, they are also associated with immune-related adverse events (irAEs). Previous histopathologic descriptions of organ-related inflammatory changes do not consider systemic effects of ICIs, because of the absence of comprehensive autopsy studies. We performed a retrospective study on 42 whole-body autopsies of patients treated with ICIs from January 2011 to March 2024 to determine the frequency, organ distribution, and morphology of ICI-associated inflammatory changes as well as their clinical relevance. Twenty-three of 42 (54.8%) patients presented irAEs with inflammatory changes in at least one organ. Most frequent irAEs were ICI-related hypophysitis (N = 12; 28.6%), myocarditis (N = 8; 19.0%), pneumonitis (N = 5; 11.9%), hepatitis (N = 6; 14.3%), and adrenalitis (N = 5; 11.9%). ICI-related inflammation was mainly characterized by lymphohistiocytic and macrophage-rich tissue infiltrates, whereas a granulomatous "sarcoid-like" reaction was observed in 1 patient. Cause of death was attributable to ICI therapy in 7 (16.7%) patients, with ICI-associated myocarditis as the most common cause of death (N = 5; 71.4%). Clinically, irAEs were unsuspected in 5 of 7 ICI-related deaths (71.4%). Among irAEs, myocarditis has been clinically undiagnosed in 5 out of 8 cases (62.5%). Encephalitis was identified only at autopsy in all cases (N = 2). Hypophysitis was clinically unsuspected in 8 of 12 (66.7%) cases. Patients who died from irAEs developed more frequently a complete tumor regression than patients who died from other causes (P = .018). Of note, ICI-related myocarditis and pneumonitis were both associated with a systemic occurrence irAEs. Our study demonstrates that some irAEs, especially myocarditis, hypophysitis, and encephalitis, are clinically underdiagnosed. Autopsy remains a valuable tool to monitor diagnostic accuracy and therapeutic side effects in patients who died under ICI therapy.

Enhancing Precision in Detecting Severe Immune-Related Adverse Events: Comparative Analysis of Large Language Models and International Classification of Disease Codes in Patient Records

PURPOSE

Current approaches to accurately identify immune-related adverse events (irAEs) in large retrospective studies are limited. Large language models (LLMs) offer a potential solution to this challenge, given their high performance in natural language comprehension tasks. Therefore, we investigated the use of an LLM to identify irAEs among hospitalized patients, comparing its performance with manual adjudication and International Classification of Disease (ICD) codes.

METHODS

Hospital admissions of patients receiving immune checkpoint inhibitor (ICI) therapy at a single institution from February 5, 2011, to September 5, 2023, were individually reviewed and adjudicated for the presence of irAEs. ICD codes and an LLM with retrieval-augmented generation were applied to detect frequent irAEs (ICI-induced colitis, hepatitis, and pneumonitis) and the most fatal irAE (ICI-myocarditis) from electronic health records. The performance between ICD codes and LLM was compared via sensitivity and specificity with an α = .05, relative to the gold standard of manual adjudication. External validation was performed using a data set of hospital admissions from June 1, 2018, to May 31, 2019, from a second institution.

RESULTS

Of the 7,555 admissions for patients on ICI therapy in the initial cohort, 2.0% were adjudicated to be due to ICI-colitis, 1.1% ICI-hepatitis, 0.7% ICI-pneumonitis, and 0.8% ICI-myocarditis. The LLM demonstrated higher sensitivity than ICD codes (94.7% v 68.7%), achieving significance for ICI-hepatitis (P < .001), myocarditis (P < .001), and pneumonitis (P = .003) while yielding similar specificities (93.7% v 92.4%). The LLM spent an average of 9.53 seconds/chart in comparison with an estimated 15 minutes for adjudication. In the validation cohort (N = 1,270), the mean LLM sensitivity and specificity were 98.1% and 95.7%, respectively.

CONCLUSION

LLMs are a useful tool for the detection of irAEs, outperforming ICD codes in sensitivity and adjudication in efficiency.

Tumor cell membrane-based vaccines: A potential boost for cancer immunotherapy

Because therapeutic cancer vaccines can, in theory, eliminate tumor cells specifically with relatively low toxicity, they have long been considered for application in repressing cancer progression. Traditional cancer vaccines containing a single or a few discrete tumor epitopes have failed in the clinic, possibly due to challenges in epitope selection, target downregulation, cancer cell heterogeneity, tumor microenvironment immunosuppression, or a lack of vaccine immunogenicity. Whole cancer cell or cancer membrane vaccines, which provide a rich source of antigens, are emerging as viable alternatives. Autologous and allogenic cellular cancer vaccines have been evaluated as clinical treatments. Tumor cell membranes (TCMs) are an intriguing antigen source, as they provide membrane-accessible targets and, at the same time, serve as integrated carriers of vaccine adjuvants and other therapeutic agents. This review provides a summary of the properties and technologies for TCM cancer vaccines. Characteristics, categories, mechanisms, and preparation methods are discussed, as are the demonstrable additional benefits derived from combining TCM vaccines with chemotherapy, sonodynamic therapy, phototherapy, and oncolytic viruses. Further research in chemistry, biomedicine, cancer immunology, and bioinformatics to address current drawbacks could facilitate the clinical adoption of TCM vaccines.

Hepatitis associated with immune checkpoint inhibitors-based combinations of other therapies: A real-world pharmacovigilance analysis based on the FDA adverse event reporting system (FAERS) database

BACKGROUND

The combination regimen with immune checkpoint inhibitors (ICIs) and other therapies has been widely applied for patients with non-small-cell lung cancer (NSCLC). To date, no literature has systematically addressed the risk of hepatitis associated with the combination therapy. We conducted this pharmacovigilance analysis using the Food and Drug Administration Adverse Event Reporting System (FAERS).

PATIENTS AND METHODS

A total of 587,016 NSCLC reports were extracted from FAERS database spanning from the first quarter of 2013 to the second quarter of 2023. After filtering duplicate reports, logistic regression model was used to detect safety signals, and multivariable logistic regression model was used to confirm the interaction between ICI and other drugs.

RESULTS

Of the 81,512 patients with NSCLC, 2785 cases developed hepatitis. Multivariable logistic regression analyses revealed that the adjusted ROR of ICI combined with targeted therapy (TT) was the highest 1.64 (95% CI, 1.32-2.02; P < 0.0001) among all therapies, while that of TT and ICI treatment were 1.07 (95% CI, 0.98-1.17; P = 0.1097) and 1.12 (95% CI, 1.03-1.22; P = 0.0111), respectively. The adjusted ROR for the interaction effect was 1.64 (95% CI, 1.32-2.02; P < 0.0001). Furthermore, the adjusted ROR of ICI combined with KRAS-targeted drugs was the highest 3.03 (95% CI, 1.49-5.93; P = 0.0016) among all targeted drugs, with an adjusted ROR of 3.03 (95% CI, 1.49-5.93; P = 0.0016), indicating a meaningful interaction of these two kinds of drugs.

CONCLUSION

We confirmed that combination treatment of ICI and TT is associated with the amplified risk of hepatitis, which is partly due to the interaction between ICI and TT, and the KRAS-targeted drugs may harbor the highest potential for hepatitis induction among TT drugs when combined with ICI. Besides, the combination treatment of ICI- and KRAS-targeted drugs also increases the incidence of colitis, pulmonary embolism and dehydration.

Immune checkpoint inhibitors-related thyroid dysfunction: influencing factor analysis, prediction model development, and management strategy proposal

BACKGROUND

With the extensive utilization of immune checkpoint inhibitors (ICIs) across various cancers, ICIs-related thyroid dysfunction (ICI-TD) has become a growing concern in clinical practice. This study aimed to devise an individualized management strategy for ICI-TD to enhance the early identification and proactive management in cancer patients.

METHODS

We designed and conducted a three-phase study. Initially, we analyzed the influencing factors through a systematic review and meta-analysis, which adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Moreover, the study protocol was registered with PROSPERO (CRD42019131133). Subsequently, prediction models for ICI-TD were developed utilizing 11 algorithms based on the real-world cohort data from July 20, 2018 (the approval date of the first ICIs, Pembrolizumab in China), to October 31, 2022. Considering discrimination, calibration, and clinical utility, we selected the model with the best performance for web calculator development. Finally, individualized management strategies for ICI-TD were proposed by combining evidence-based analysis with practical considerations.

RESULTS

The systematic review encompassed 21 observational studies involving 4,145 patients, revealing associations between ICI-TD and factors such as female gender, age, receipt of Pembrolizumab (versus other ICIs), and baseline levels of thyroid-stimulating hormone, free thyroxine, and antithyroid antibodies. In the prediction model development phase, 621 participants were enrolled, with 36 patients developing ICI-TD. The model based on the LightGBM algorithm demonstrated superior performance, leading to the development of a web calculator. Based on these findings and existing guidelines, individualized monitoring and treatment pathways for pharmacists were devised.

CONCLUSION

This study offers comprehensive insights into managing ICI-TD, potentially enhancing tailored cancer immunotherapy management.

Biomarkers associated with immune-related adverse events induced by immune checkpoint inhibitors

Immune checkpoint inhibitors (ICIs) constitute a pivotal class of immunotherapeutic drugs in cancer treatment. However, their widespread clinical application has led to a notable surge in immune-related adverse events (irAEs), significantly affecting the efficacy and survival rates of patients undergoing ICI therapy. While conventional hematological and imaging tests are adept at detecting organ-specific toxicities, distinguishing adverse reactions from those induced by viruses, bacteria, or immune diseases remains a formidable challenge. Consequently, there exists an urgent imperative for reliable biomarkers capable of accurately predicting or diagnosing irAEs. Thus, a thorough review of existing studies on irAEs biomarkers is indispensable. Our review commences by providing a succinct overview of major irAEs, followed by a comprehensive summary of irAEs biomarkers across various dimensions. Furthermore, we delve into innovative methodologies such as machine learning, single-cell RNA sequencing, multiomics analysis, and gut microbiota profiling to identify novel, robust biomarkers that can facilitate precise irAEs diagnosis or prediction. Lastly, this review furnishes a concise exposition of irAEs mechanisms to augment understanding of irAEs prediction, diagnosis, and treatment strategies.

Delayed immune-related adverse events in long-responders of immunotherapy: a single-center experience

BACKGROUND

Immune-checkpoint inhibitors (ICIs) often cause immune-related adverse events (irAEs). The spectrum of irAEs and their managements has been partially clarified, however the knowledge on time-course of irAEs is not well understood.

METHODS

A retrospective study based on the medical record was performed. The study subjects were consisting of patients with various types of solid tumors for whom ICIs (nivolumab, pembrolizumab, durvalumab, atezolizumab, nivolumab plus ipilimumab) were used between April 2016 and October 2021. We focused on irAEs developed more than 1-year after commencement ICIs (delayed irAE group) and compared with irAEs developed within 1-year (non-delayed irAE group) in terms of types and severity of irAEs.

RESULTS

A total of 336 patients were enrolled in the study. Eighty-eight patients (26.2%) developed irAEs and 248 did not. Most of the patients developing irAEs were treated using PD-L1/PD-1 inhibitors. Eighty-one patients (24.1%) in non-delayed irAE group and 7 patients (2.1%) in delayed irAE group developed irAEs. The median onset of irAEs in the delayed irAE group was 18.6 months (range: 13.5-24.3). The types of irAEs observed in delayed irAE group were dermatitis (2 cases), pneumonitis (2 cases), nephritis (1 case), arthritis (1 case), and gastritis (1 case). The severity of irAEs was almost mild (≤G2), but one patient (.3%) developed G3 nephritis.

CONCLUSION

PD-L1/PD-1 inhibitors frequently caused various irAEs but their severities were mostly tolerable. Few patients developed delayed irAE with mild toxities.

A case report of hemophagocytic lymphohistiocytosis induced by toripalimab plus chemoradiotherapy in cervical cancer

Background

Hemophagocytic lymphohistiocytosis (HLH) is a rare but life-threatening clinical syndrome characterized by immune hyperactivation. Unlike primary HLH, immune checkpoint inhibitor (ICI)-triggered HLH is not well described, and there is a lack of theranostic guidelines. Herein, we first reported the successful management of PD-1 inhibitor-associated HLH in locally advanced cervical cancer.

Case presentation

We report a case of HLH in a 47-year-old patient with International Federation of Gynecology and Obstetrics (FIGO) IIIC1r cervical cancer who received toripalimab, a programmed cell death-1 receptor inhibitor, combined with chemoradiotherapy. The patient developed pyrexia, splenomegaly, leukopenia, anemia, thrombocytopenia, hypertriglyceridemia, hypofibrinogenemia, hyperferritinemia, reduced NK cell activity, elevated sCD25 levels, and hemophagocytosis in a bone marrow aspirate. Our patient was successfully treated with methylprednisolone, indicating that immune-induced HLH might respond to glucocorticoids, and is still alive with a complete response of the tumor.

Conclusion

Considering the possibility of HLH is needed in patients receiving ICIs to detect rare toxicities at an early stage when the patient develops uncontrollable fever, cytopenia, and splenomegaly, our multidisciplinary treatment modality contributed to the early diagnosis and successful management of HLH, avoiding progressive tissue damage and organ failure. Whether glucocorticoids are used alone or not for immune-associated HLH needs further investigation.

Plasma metabolomics of immune-related adverse events for patients with lung cancer treated with PD-1/PD-L1 inhibitors

BACKGROUND

Metabolomics has the characteristics of terminal effects and reflects the physiological state of biological diseases more directly. Several current biomarkers of multiple omics were revealed to be associated with immune-related adverse events (irAEs) occurrence. However, there is a lack of reliable metabolic biomarkers to predict irAEs. This study aims to explore the potential metabolic biomarkers to predict risk of irAEs and to investigate the association of plasma metabolites level with survival in patients with lung cancer receiving PD-1/PD-L1 inhibitor treatment.

METHODS

The study collected 170 plasmas of 85 patients with lung cancer who received immune checkpoint inhibitors (ICIs) treatment. 58 plasma samples of 29 patients with irAEs were collected before ICIs treatment and at the onset of irAEs. 112 plasma samples of 56 patients who did not develop irAEs were collected before ICIs treatment and plasma matched by treatment cycles to onset of irAEs patients. Untargeted metabolomics analysis was used to identify the differential metabolites before initiating ICIs treatment and during the process that development of irAEs. Kaplan-Meier curves analysis was used to detect the associations of plasma metabolites level with survival of patients with lung cancer.

RESULTS

A total of 24 differential metabolites were identified to predict the occurrence of irAEs. Baseline acylcarnitines and steroids levels are significantly higher in patients with irAEs, and the model of eight acylcarnitine and six steroid metabolites baseline level predicts irAEs occurrence with area under the curve of 0.91. Patients with lower concentration of baseline decenoylcarnitine(AcCa(10:1) 2, decenoylcarnitine(AcCa(10:1) 3 and hexanoylcarnitine(AcCa(6:0) in plasma would have better overall survival (OS). Moreover, 52 differential metabolites were identified related to irAEs during ICIs treatment, dehydroepiandrosterone sulfate, corticoserone, cortisol, thyroxine and sphinganine 1-phaosphate were significantly decreased in irAEs group while oxoglutaric acid and taurocholic acid were significantly increased in irAEs group.

CONCLUSIONS

High levels of acylcarnitines and steroid hormone metabolites might be risk factor to development of irAEs, and levels of decenoylcarnitine (AcCa(10:1) 2, decenoylcarnitine (AcCa(10:1) 3 and hexanoylcarnitine (AcCa(6:0) could be used to predict OS for patients with lung cancer received ICIs treatment.

Integrating Network Pharmacology and Experimental Validation to Decipher the Mechanism of Action of Astragalus-Atractylodes Herb Pair in Treating Hepatocellular Carcinoma

Purpose

Traditional Chinese medicine (TCM) therapy is an important means to treat hepatocellular carcinoma (HCC), Astragalus (Latin name: Hedysarum Multijugum Maxim; Chinese name: Huangqi, HQ) and Atractylodes (Latin name: Atractylodes Macrocephala Koidz; Chinese name: Baizhu, BZ) (HQBZ), a classic herb pair, is often used in combination to HCC. However, the main components and potential mechanisms of HQBZ therapy in HCC remain unclear. This study aimed to identify the potential active ingredients and molecular mechanisms of action of HQBZ in HCC treatment.

Methods

The HQBZ-Compound-Target-HCC network and HQBZ-HCC transcriptional regulatory network were constructed to screen the core active compound components and targets of HQBZ therapy for HCC. Molecular docking techniques are used to verify the stability of binding core active compound components to targets. GO and KEGG enrichment analysis were used to explore the signaling pathway of HQBZ in HCC treatment, the mechanism of HQBZ treatment of HCC was verified based on in vivo H22 tumor bearing mice and in vitro cell experiments.

Results

Network pharmacology and molecular docking studies showed that HQBZ treatment of HCC was related to the targeted regulation of IL-6 and STAT3 by the active compound biatractylolide, KEGG pathway enrichment analysis suggest that HQBZ may play a role in the treatment of HCC through IL-6/STAT3 signaling pathway. In vitro experiment results proved that HQBZ could regulate IL-6/STAT3 signaling pathway transduction on CD8+T cells, inhibit CD8+T cell exhaustion and restore the function of exhausted CD8+T cells. In vivo experiment results proved that HQBZ can regulate IL-6/STAT3 signaling pathway transduction in H22 liver cancer model mouse tumor tissue, increased the proportion of tumor infiltrating CD8+T cells.

Conclusion

This study found that HQBZ may play a therapeutic role in HCC by targeting IL-6 and STAT3 through biatractylolide, its mechanism of action is related to regulating IL-6/STAT3 signaling pathway, reversing T cell failure and increasing tumor infiltration CD8+T cells.

Autoimmune Myocarditis, Old Dogs and New Tricks

Autoimmunity significantly contributes to the pathogenesis of myocarditis, underscored by its increased frequency in autoimmune diseases such as systemic lupus erythematosus and polymyositis. Even in cases of myocarditis caused by viral infections, dysregulated immune responses contribute to pathogenesis. However, whether triggered by existing autoimmune conditions or viral infections, the precise antigens and immunologic pathways driving myocarditis remain incompletely understood. The emergence of myocarditis associated with immune checkpoint inhibitor therapy, commonly used for treating cancer, has afforded an opportunity to understand autoimmune mechanisms in myocarditis, with autoreactive T cells specific for cardiac myosin playing a pivotal role. Despite their self-antigen recognition, cardiac myosin-specific T cells can be present in healthy individuals due to bypassing the thymic selection stage. In recent studies, novel modalities in suppressing the activity of pathogenic T cells including cardiac myosin-specific T cells have proven effective in treating autoimmune myocarditis. This review offers an overview of the current understanding of heart antigens, autoantibodies, and immune cells as the autoimmune mechanisms underlying various forms of myocarditis, along with the latest updates on clinical management and prospects for future research.

Proton pump inhibitors stabilize the expression of PD-L1 on cell membrane depending on the phosphorylation of GSK3β

BACKGROUND

Preclinical and clinical evidence indicates that proton pump inhibitors (PPIs) may indirectly diminish the microbiome diversity, thereby reducing the effectiveness of immune checkpoint inhibitors (ICIs). Conversely, recent publications have shown that PPIs could potentially enhance the response to ICIs. The precise mechanism through which PPIs modulate the ICIs remains unclear. In this study, we discovered a novel molecular function of PPIs in regulating immune invasion, specifically through inducing PD-L1 translocation in various tumor cells.

METHODS

C57BL/6 mice subcutaneous transplantation model is used to verify the potential efficacy of PPIs and PD-L1 antibody. Western blotting analysis and phosphorylated chip are used to verify the alteration of PD-L1-related pathways after being treated with PPIs. The related gene expression is performed by qRT-PCR and luciferase reporter analysis. We also collected 60 clinical patients diagnosed with esophageal cancer or reflux esophagitis and then detected the expression of PD-L1 in the tissue samples by immunohistochemistry.

RESULTS

We observed that the IC50 of tumor cells in response to PPIs was significantly higher than that of normal epithelial cells. PPIs significantly increased the expression of PD-L1 on cell membrane at clinically relevant concentrations. Furthermore, pre-treatment with PPIs appeared to synergize the efficiency of anti-PD-L1 antibodies in mouse models. However, PPI administration did not alter the transcription or total protein level of PD-L1 in multiple tumor cells. Using a phosphorylated protein chip, we identified that PPIs enhanced the phosphorylation of GSK3β, then leading to PD-L1 protein translocation to the cell membranes. The capacity of PPIs to upregulate PD-L1 was negated following GSK3β knockout. Furthermore, our clinical data showed that the PPIs use resulted in increased PD-L1 expression in esophageal cancer patients.

CONCLUSION

We mainly address a significant and novel mechanism that the usage of PPIs could directly induce the expression of PD-L1 by inducing GSK3β phosphorylation and facilitate primary tumor progression and metastasis.

Identification and Characterization of Immune Checkpoint Inhibitor-Induced Toxicities From Electronic Health Records Using Natural Language Processing

PURPOSE

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, yet their use is associated with immune-related adverse events (irAEs). Estimating the prevalence and patient impact of these irAEs in the real-world data setting is critical for characterizing the benefit/risk profile of ICI therapies beyond the clinical trial population. Diagnosis codes, such as International Classification of Diseases codes, do not comprehensively illustrate a patient's care journey and offer no insight into drug-irAE causality. This study aims to capture the relationship between ICIs and irAEs more accurately by using augmented curation (AC), a natural language processing-based innovation, on unstructured data in electronic health records.

METHODS

In a cohort of 9,290 patients treated with ICIs at Mayo Clinic from 2005 to 2021, we compared the prevalence of irAEs using diagnosis codes and AC models, which classify drug-irAE pairs in clinical notes with implied textual causality. Four illustrative irAEs with high patient impact-myocarditis, encephalitis, pneumonitis, and severe cutaneous adverse reactions, abbreviated as MEPS-were analyzed using corticosteroid administration and ICI discontinuation as proxies of severity.

RESULTS

For MEPS, only 70% (n = 118) of patients found by AC were also identified by diagnosis codes. Using AC models, patients with MEPS received corticosteroids for their respective irAE 82% of the time and permanently discontinued the ICI because of the irAE 35.9% (n = 115) of the time.

CONCLUSION

Overall, AC models enabled more accurate identification and assessment of patient impact of ICI-induced irAEs not found using diagnosis codes, demonstrating a novel and more efficient strategy to assess real-world clinical outcomes in patients treated with ICIs.

Knowledge domains and emerging trends in immune-related adverse events from immune checkpoint inhibitors: A bibliometrics and visualized analysis

Objective

The primary objective of this paper is to investigate the research hotspots and future trends of immune-related adverse events induced by immune checkpoint inhibitors, offering valuable insights for researchers in this field.

Methodology

Using the visual analysis software, this study conducted quantitative statistics and visualization research on the relevant literature concerning immune-related adverse events caused by immune checkpoint inhibitors in the Web of Science Core Collection Database. By evaluating the publication trends, countries, institutions, keywords, research status, cited documents, and document co-citations, among several others, the discussion revolved around the hot spots and future development trends in this field and provided references for future research.

Findings and conclusions

A total of 514 English articles were included, and the top three countries in the research field at the time of this study were the United States, Japan, and China. More specifically, the University of Texas MD Anderson Cancer Center, Dana-Farber Cancer Institute, and Massachusetts General Hospital have been the top three research institutes with more than 10 publications. The frequency of keyword use linked to immune-related adverse events caused by immune checkpoint inhibitors in literature research has been steadily growing over the years. Additionally, the research with respect to the disease focuses on melanoma, cell lung cancer, hepatocellular carcinoma, and breast cancer. In the context of drugs, cancer-related research has mainly focused on the combined use of nivolumab, pembrolizumab, ipilimumab, and immune checkpoint inhibitors. Meanwhile, research on adverse events has delved into the immune checkpoint inhibitors causing vitiligo, thyroid dysfunction, pancreatitis, cholangitis, and rheumatism. Related studies cover acute arthritis, myositis, acute kidney injury, as well as the combination therapy of immune checkpoint inhibitors and docetaxel, management of irAEs in cancer immunotherapy, and biomarkers of immune adverse reactions of immune checkpoint inhibitors. Finally, case report studies of immune adverse reactions caused by immune checkpoint inhibitors could serve as research hotspots in the future.

Worldwide research trends on tumor burden and immunotherapy: a bibliometric analysis

Various immunotherapy has been greatly applied to comprehensive treatment of malignant cancer under different degrees of tumor burden. Scientific researchers have gained considerable progress in the relationship between immunotherapy and tumor burden in recent years. This review aimed to explore the prospect and developing trends in the field of tumor burden and immunotherapy from a bibliometric perspective. Articles about tumor burden and immunotherapy were collected from the Web of Science Core Collection (WoSCC) (retrieved on 3 January 2023). The R package 'Bibliometrix' analyzed the primary bibliometric features and created a three-filed plot to display the relationship between institutions, countries, and keywords. VOSviewer was used for co-authorship analysis, co-occurrence analysis, and their visualization. And CiteSpace calculated the citation burst references and keywords. A total of 1030 publications were retrieved from 35 years of scientific researches. The United States (US) and China published the most articles. The most productive journals were Cancer Immunology Immunotherapy and Journal for ImmunoTherapy of Cancer . The top one institution of the highest output was University of Texas MD Anderson Cancer Center. The hot keywords of strong citation burst strength in recent years were 'nivolumab', 'tumor microenvironment', and 'immune checkpoint inhibitor'. The most popular tumor type is melanoma. This bibliometric analysis mapped a basic knowledge structure. The field of tumor burden and immunotherapy is entering a rapid growing stage and keeping it value for future research.

Integrating network pharmacology and drug side-effect data to explore mechanism of liver injury-induced by tyrosine kinase inhibitors

Tyrosine kinase inhibitors (TKIs) are highly efficient small-molecule anticancer drugs. Despite the specificity and efficacy of TKIs, they can produce off-target effects, leading to severe liver toxicity, and even some of them are labeled as black box hepatotoxicity. Thus, we focused on representative TKIs associated with severe hepatic adverse events, namely lapatinib, pazopanib, regorafenib, and sunitinib as objections of study, then integrated drug side-effect data from United State Food and Drug Administration (U.S. FDA) and network pharmacology to elucidate mechanism underlying TKI-induced liver injury. Based on network pharmacology, we constructed a specific comorbidity module of high risk of serious adverse effects and created drug-disease networks. Enrichment analysis of the networks revealed the depletion of all-trans-retinoic acid and the involvement of down-regulation of the HSP70 family-mediated endoplasmic reticulum (ER) stress as key factors in TKI-induced liver injury. These results were further verified by transcription data. Based on the target prediction results of drugs and reactive metabolites, we also shed light on the association between toxic metabolites and severe hepatic adverse reactions, and thinking HSPA8, HSPA1A, CYP1A1, CYP1A2 and CYP3A4 were potential therapeutic or preventive targets against TKI-induced liver injury. In conclusion, our research provides comprehensive insights into the mechanism underlying severe liver injury caused by TKIs, offering a better understanding of how to enhance patient safety and treatment efficacy.

Big data and artificial intelligence in cancer research

The field of oncology has witnessed an extraordinary surge in the application of big data and artificial intelligence (AI). AI development has made multiscale and multimodal data fusion and analysis possible. A new era of extracting information from complex big data is rapidly evolving. However, challenges related to efficient data curation, in-depth analysis, and utilization remain. We provide a comprehensive overview of the current state of the art in big data and computational analysis, highlighting key applications, challenges, and future opportunities in cancer research. By sketching the current landscape, we seek to foster a deeper understanding and facilitate the advancement of big data utilization in oncology, call for interdisciplinary collaborations, ultimately contributing to improved patient outcomes and a profound understanding of cancer.

Immune-Related Adverse Events of Immune Checkpoint Inhibitors

Immune-related adverse events (irAEs) are toxicities that arise after the administration of monoclonal antibodies targeting immune checkpoints (immune checkpoint inhibitors [ICIs]) in patients with cancer. They can occur at any time after initiation of ICI treatment, with a broad clinical phenotype that can be organ-specific or systemic. Although most irAEs manifest as mild to moderate signs and symptoms, severe forms of irAEs can lead to irreversible organ failure and have acute life-threatening presentations. Treatment should be tailored to the specific organ involved and the severity. Glucocorticoids are the first-line treatment for most irAEs, with immunosuppressants and biologics mainly used as second-line treatments.

Gut microbiome for predicting immune checkpoint blockade-associated adverse events

BACKGROUND

The impact of the gut microbiome on the initiation and intensity of immune-related adverse events (irAEs) prompted by immune checkpoint inhibitors (ICIs) is widely acknowledged. Nevertheless, there is inconsistency in the gut microbial associations with irAEs reported across various studies.

METHODS

We performed a comprehensive analysis leveraging a dataset that included published microbiome data (n = 317) and in-house generated data from 16S rRNA and shotgun metagenome samples of irAEs (n = 115). We utilized a machine learning-based approach, specifically the Random Forest (RF) algorithm, to construct a microbiome-based classifier capable of distinguishing between non-irAEs and irAEs. Additionally, we conducted a comprehensive analysis, integrating transcriptome and metagenome profiling, to explore potential underlying mechanisms.

RESULTS

We identified specific microbial species capable of distinguishing between patients experiencing irAEs and non-irAEs. The RF classifier, developed using 14 microbial features, demonstrated robust discriminatory power between non-irAEs and irAEs (AUC = 0.88). Moreover, the predictive score from our classifier exhibited significant discriminative capability for identifying non-irAEs in two independent cohorts. Our functional analysis revealed that the altered microbiome in non-irAEs was characterized by an increased menaquinone biosynthesis, accompanied by elevated expression of rate-limiting enzymes menH and menC. Targeted metabolomics analysis further highlighted a notably higher abundance of menaquinone in the serum of patients who did not develop irAEs compared to the irAEs group.

CONCLUSIONS

Our study underscores the potential of microbial biomarkers for predicting the onset of irAEs and highlights menaquinone, a metabolite derived from the microbiome community, as a possible selective therapeutic agent for modulating the occurrence of irAEs.

Hemophagocytic lymphohistiocytosis following pembrolizumab and bevacizumab combination therapy for cervical cancer: a case report and systematic review

BACKGROUND

Programmed cell death protein 1 (PD-1) checkpoint inhibitors such as pembrolizumab are novel therapeutics used to treat various advanced malignancies. Immune-related adverse events are common, among the most serious of these toxicities is hemophagocytic lymphohistiocytosis (HLH), which is a life-threatening disorder of unbridled immune activation but has not been properly established.

METHODS

We have procured the first case of hemophagocytic lymphohistiocytosis as an aftermath of treatment with pembrolizumab from the Sir Run Run Shaw Hospital, Zhejiang University, China. In a pursuit to enhance the understanding of this condition, a comprehensive systematic review was performed encompassing all reported instances of ICI-associated Hemophagocytic lymphohistiocytosis within the realms of PubMed and Embase databases.

RESULTS

We detail the recovery of a cervical cancer patient with a history of psoriasis who developed HLH after combined pembrolizumab and bevacizumab treatment. Remarkably, tumor lesions exhibited substantial and sustained regression. From an analysis of 52 identified Immune Checkpoint Inhibitor (ICI)-related HLH cases, we discovered that HLH often occurred within the first two treatment cycles and approximately 20% of these patients had a history of autoimmune-related diseases. Despite a 15% mortality rate, the majority of patients experienced positive outcomes. Notably, in instances of recovery from HLH, 80% showed positive tumor outcomes. Even after discontinuation of ICI treatment, tumor control persisted in some cases.

CONCLUSION

We identified the first case of HLH caused by ICI treatment in cervical cancer and summarized the possible occurrence factors of these cases, the treatment outcomes of HLH, and the impact on tumor outcomes.

Mechanisms and biomarkers of immune-related adverse events in gastric cancer

Immune-checkpoint inhibitors (ICIs), different from traditional cancer treatment models, have shown unprecedented anti-tumor effects in the past decade, greatly improving the prognosis of many malignant tumors in clinical practice. At present, the most widely used ICIs in clinical immunotherapy for a variety of solid tumors are monoclonal antibodies against cytotoxic T lymphocyte antigen-4 (CTLA-4), programmed cell death protein 1 (PD-1) and their ligand PD-L1. However, tumor patients may induce immune-related adverse events (irAEs) while performing immunotherapy, and irAE is an obstacle to the prospect of ICI treatment. IrAE is a non-specific disease caused by immune system imbalance, which can occur in many tissues and organs. For example, skin, gastrointestinal tract, endocrine system and lung. Although the exact mechanism is not completely clear, related studies have shown that irAE may develop through many ways. Such as excessive activation of autoreactive T cells, excessive release of inflammatory cytokines, elevated levels of autoantibodies, and common antigens between tumors and normal tissues. Considering that the occurrence of severe IrAE not only causes irreversible damage to the patient's body, but also terminates immunotherapy due to immune intolerance. Therefore, accurate identification and screening of sensitive markers of irAE are the main beneficiaries of ICI treatment. Additionally, irAEs usually require specific management, the most common of which are steroids and immunomodulatory therapies. This review aims to summarize the current biomarkers for predicting irAE in gastric cancer and their possible mechanisms.

Effect of age on the risk of immune-related adverse events in patients receiving immune checkpoint inhibitors

Identifying patients at increased risk of immune-related adverse events (irAEs) facilitates safe application of immune checkpoint inhibitors (ICIs). This retrospective study aimed to determine the effect of age on the risk of irAEs in patients receiving ICIs and to identify potential mechanisms underlying age-related irAE risk differences. We analyzed reports of FDA Adverse Event Reporting System from July 1, 2014, to September 30, 2021. The information component ratio (ICΔ) was used to compare the irAE risk between older adults (> 65 years) and younger adults (25-65 years), of which the 95% confidential interval lower limit (ICΔ025) exceeding zero indicated significantly increased risk. We found that older adults had a significantly higher overall irAE risk than younger adults (ICΔ025 0.38), which was observed in almost all organ systems. We further analyzed the correlation between age-related irAE risks and age-related transcriptional changes to identify potential genes and pathways underlying age-related irAE risk differences. We found that genes significantly correlated with ICΔ were enriched in processes including extracellular matrix organization, regulation of myeloid leukocyte mediated immunity, and regulation of c-Jun N-terminal kinase (JNK) cascade. In addition, single-cell RNA sequencing analysis confirmed that genes involved in collagen-containing extracellular matrix and JNK cascade were significantly upregulated in myeloid cells from ICI-associated colitis tissues compared with ICI-treated colon tissues without colitis. In conclusion, older adults receiving ICIs have higher irAE risks than younger adults. Upregulation of genes involved in JNK cascade and collagen-containing extracellular matrix in myeloid cells may contribute to increased irAE risks in older adults.

Sintilimab-induced inflammatory myopathy in a patient with esophageal cancer: a case report

The use of immune checkpoint inhibitors (ICIs) has shown remarkable efficacy in the treatment of various malignancies, significantly reshaping cancer treatment. However, as a result of the widespread use of ICIs, several immune-related adverse events (iRAEs) have emerged, some of which can be rare and potentially fatal. In this paper, we reported the earliest case of Sintilimab used in the treatment of esophageal cancer with severe inflammatory myopathy (involving the cardiac, respiratory, and skeletal muscles)in China. This patient was an elderly female who presented to our institution with progressive limb weakness and ptosis. Prior to the onset of symptoms, the patient had undergone a radical esophagectomy for esophageal cancer, experienced several cycles of of radiotherapy and chemotherapy, as well as two doses of Sintilimab treatment. Shortly after initiating immunotherapy, the patient developed symptoms including bilateral ptosis, limb weakness, and difficulty swallowing and breathing. The levels of creatine kinase and troponin I in the patient's blood were significantly elevated, and positive results were observed for anti-skeletal and anti-cardiac muscle antibodies, indicating that the patient might be developing ICIs-related inflammatory myopathy. Fortunately, the patient responded well to treatment including corticosteroids, plasmapheresis, intravenous immunoglobulin, and other supportive therapies. Here, we discuss the incidence, mechanisms, and management strategies of fatal iRAEs. Early detection and timely intervention may be critical in reducing the incidence and mortality rates of iRAEs and improving patient outcomes.

Expanding PROTACtable genome universe of E3 ligases

Proteolysis-targeting chimera (PROTAC) and other targeted protein degradation (TPD) molecules that induce degradation by the ubiquitin-proteasome system (UPS) offer new opportunities to engage targets that remain challenging to be inhibited by conventional small molecules. One fundamental element in the degradation process is the E3 ligase. However, less than 2% amongst hundreds of E3 ligases in the human genome have been engaged in current studies in the TPD field, calling for the recruiting of additional ones to further enhance the therapeutic potential of TPD. To accelerate the development of PROTACs utilizing under-explored E3 ligases, we systematically characterize E3 ligases from seven different aspects, including chemical ligandability, expression patterns, protein-protein interactions (PPI), structure availability, functional essentiality, cellular location, and PPI interface by analyzing 30 large-scale data sets. Our analysis uncovers several E3 ligases as promising extant PROTACs. In total, combining confidence score, ligandability, expression pattern, and PPI, we identified 76 E3 ligases as PROTAC-interacting candidates. We develop a user-friendly and flexible web portal ( https://hanlaboratory.com/E3Atlas/ ) aimed at assisting researchers to rapidly identify E3 ligases with promising TPD activities against specifically desired targets, facilitating the development of these therapies in cancer and beyond.

Global Cardio Oncology Registry (G-COR): Registry Design, Primary Objectives, and Future Perspectives of a Multicenter Global Initiative

BACKGROUND

Global collaboration in cardio-oncology is needed to understand the prevalence of cancer therapy-related cardiovascular toxicity in different risk groups, practice settings, and geographic locations. There are limited data on the socioeconomic and racial/ethnic disparities that may impact access to care and outcomes. To address these gaps, we established the Global Cardio-Oncology Registry, a multinational, multicenter prospective registry.

METHODS

We assembled cardiologists and oncologists from academic and community settings to collaborate in the first Global Cardio-Oncology Registry. Subsequently, a survey for site resources, demographics, and intention to participate was conducted. We designed an online data platform to facilitate this global initiative.

RESULTS

A total of 119 sites responded to an online questionnaire on their practices and main goals of the registry: 49 US sites from 23 states and 70 international sites from 5 continents indicated a willingness to participate in the Global Cardio-Oncology Registry. Sites were more commonly led by cardiologists (85/119; 72%) and were more often university/teaching (81/119; 68%) than community based (38/119; 32%). The average number of cardio-oncology patients treated per month was 80 per site. The top 3 Global Cardio-Oncology Registry priorities in cardio-oncology care were breast cancer, hematologic malignancies, and patients treated with immune checkpoint inhibitors. Executive and scientific committees and specific committees were established. A pilot phase for breast cancer using Research Electronic Data Capture Cloud platform recently started patient enrollment.

CONCLUSIONS

We present the structure for a global collaboration. Information derived from the Global Cardio-Oncology Registry will help understand the risk factors impacting cancer therapy-related cardiovascular toxicity in different geographic locations and therefore contribute to reduce access gaps in cardio-oncology care. Risk calculators will be prospectively derived and validated.

Divergent tumor and immune cell reprogramming underlying immunotherapy response and immune-related adverse events in lung squamous cell carcinoma

BACKGROUND

Lung squamous cell carcinoma (LUSC) remains a leading cause of cancer-related deaths with few therapeutic strategies. Immune checkpoint inhibitors (ICIs) have demonstrated promising efficacy in patients with LUSC. However, ICIs could also lead to a unique spectrum of immune-related adverse events (irAEs), which dampen the clinical outcome. In-depth characterization of the immune hallmarks of antitumor responses and irAEs remains an unmet need to maximize ICI-treatment benefits of patients.

METHODS

We performed single-cell RNA sequencing (scRNA-seq) on pre-ICI and on-ICI treatment tumor biopsies. We used bulk RNA-seq data of matched pretreatment/on-treatment tumors and irAE affected organs to validate observations from scRNA-seq analysis. Two independent patient cohorts were collected to determine circulating tumor necrosis factor (TNF) protein expression levels.

RESULTS

We found that increased proportions of a macrophage subcluster with highly expressed secreted phosphoprotein 1 (SPP1) and two tumor cell subclusters in irAE patients, whereas proportions of two cytotoxic CD8+ T cell subclusters were higher in patients with partial response (PR). TNF signaling pathway was conversely associated with treatment efficacy and irAE development in most macrophage and tumor cell subclusters. Cell-cell communications for TNF ligand-receptor pairs between macrophage/T cells and tumor cells were also bidirectionally remodeled in responders versus non-responders and irAE versus non-irAE patients. Bulk RNA-seq analysis on matched pretreatment/on-treatment tumors and irAE affected organs revealed remarkably enhanced macrophage abundance and TNF signaling pathway in on-treatment tumors and organs developed irAEs. Furthermore, we observed significantly increased circulating TNF protein in plasma or serum of irAE patients but not ICI responders, based on analysis of two independent LUSC patient cohorts and one published ICI patient cohort.

CONCLUSIONS

Our data depicts specific reprogramming of macrophage, T cells and tumor cells associated with ICI response and irAEs, elucidates divergent roles of TNF signaling in antitumor immunity and irAEs, and highlights the significance of TNF expression in irAE development in the LUSC setting.

The Era of Immunotherapy in Hepatocellular Carcinoma: The New Mission and Challenges of Magnetic Resonance Imaging

In recent years, significant advancements in immunotherapy for hepatocellular carcinoma (HCC) have shown the potential to further improve the prognosis of patients with advanced HCC. However, in clinical practice, there is still a lack of effective biomarkers for identifying the patient who would benefit from immunotherapy and predicting the tumor response to immunotherapy. The immune microenvironment of HCC plays a crucial role in tumor development and drug responses. However, due to the complexity of immune microenvironment, currently, no single pathological or molecular biomarker can effectively predict tumor responses to immunotherapy. Magnetic resonance imaging (MRI) images provide rich biological information; existing studies suggest the feasibility of using MRI to assess the immune microenvironment of HCC and predict tumor responses to immunotherapy. Nevertheless, there are limitations, such as the suboptimal performance of conventional MRI sequences, incomplete feature extraction in previous deep learning methods, and limited interpretability. Further study needs to combine qualitative features, quantitative parameters, multi-omics characteristics related to the HCC immune microenvironment, and various deep learning techniques in multi-center research cohorts. Subsequently, efforts should also be undertaken to construct and validate a visual predictive tool of tumor response, and assess its predictive value for patient survival benefits. Additionally, future research endeavors must aim to provide an accurate, efficient, non-invasive, and highly interpretable method for predicting the effectiveness of immune therapy.

Nano-vaccines combining customized in situ anti-PD-L1 depot for enhanced tumor immunotherapy

Low response rate of immune checkpoint blockade (ICB) has limited its clinical application. A promising strategy to overcome this limitation is the use of therapeutic cancer vaccines, which aim to induce robust immune responses that synergize with ICB through immune enhancement and immune normalization strategies. Herein, we developed a combination immunotherapy by combining nano-vaccines consisting of whole tumor cell lysates/CpG liposomes (LCLs) with an anti-PD-L1 loaded lipid gel (aPD-L1@LG). The LCLs were fabricated using cationic liposomes, while the lipid gels (LGs) were prepared by using soybean phosphatidylcholine (SPC) and glycerol dioleate (GDO). Subcutaneous administration of LCLs successfully activated dendritic cells (DCs), and intratumoral administration of anti-PD-L1@LG ensured sustained ICB activity. These results demonstrated that this combination immunotherapy enhanced anti-tumor efficacy and prolonged the survival time in melanoma by activating systemic anti-tumor immune responses. These findings highlight the potential of this rational design as a promising strategy for tumor treatment.

Cardiovascular Toxicity of Immune Checkpoint Inhibitors: A Guide for Clinicians

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment and care of patients with cancer owing to unique features, including the occurrence of the so-called immune-related adverse events (irAEs). A multidisciplinary team, possibly including a cardio-oncology specialist, is warranted to achieve a favorable patient outcome. Cardiovascular toxicity, especially myocarditis, emerged as a life-threatening irAE in the real-word setting, and the European Society of Cardiology has recently published the first guideline on cardio-oncology to increase awareness and promote a standardized approach to tackle this complex multimodal issue, including diagnostic challenges, assessment, treatment, and surveillance of patients with cancer receiving ICIs. In this article, through a question & answer format made up of case vignettes, we offer a clinically oriented overview on the latest advancements of ICI-related cardiovascular toxicity, focusing on myocarditis and associated irAEs (myositis and myasthenia gravis within the so-called overlap syndrome), with the purpose of assisting clinicians and healthcare professionals in daily clinical practice.

Immune checkpoint therapy for solid tumours: clinical dilemmas and future trends

Immune-checkpoint inhibitors (ICBs), in addition to targeting CTLA-4, PD-1, and PD-L1, novel targeting LAG-3 drugs have also been approved in clinical application. With the widespread use of the drug, we must deeply analyze the dilemma of the agents and seek a breakthrough in the treatment prospect. Over the past decades, these agents have demonstrated dramatic efficacy, especially in patients with melanoma and non-small cell lung cancer (NSCLC). Nonetheless, in the field of a broad concept of solid tumours, non-specific indications, inseparable immune response and side effects, unconfirmed progressive disease, and complex regulatory networks of immune resistance are four barriers that limit its widespread application. Fortunately, the successful clinical trials of novel ICB agents and combination therapies, the advent of the era of oncolytic virus gene editing, and the breakthrough of the technical barriers of mRNA vaccines and nano-delivery systems have made remarkable breakthroughs currently. In this review, we enumerate the mechanisms of each immune checkpoint targets, associations between ICB with tumour mutation burden, key immune regulatory or resistance signalling pathways, the specific clinical evidence of the efficacy of classical targets and new targets among different tumour types and put forward dialectical thoughts on drug safety. Finally, we discuss the importance of accurate triage of ICB based on recent advances in predictive biomarkers and diagnostic testing techniques.

Thermoresponsive Polypeptide Fused L-Asparaginase with Mitigated Immunogenicity and Enhanced Efficacy in Treating Hematologic Malignancies

L-Asparaginase (ASP) is well-known for its excellent efficacy in treating hematological malignancies. Unfortunately, the intrinsic shortcomings of ASP, namely high immunogenicity, severe toxicity, short half-life, and poor stability, restrict its clinical usage. Poly(ethylene glycol) conjugation (PEGylation) of ASP is an effective strategy to address these issues, but it is not ideal in clinical applications due to complex chemical synthesis procedures, reduced ASP activity after conjugation, and pre-existing anti-PEG antibodies in humans. Herein, the authors genetically engineered an elastin-like polypeptide (ELP)-fused ASP (ASP-ELP), a core-shell structured tetramer predicted by AlphaFold2, to overcome the limitations of ASP and PEG-ASP. Notably, the unique thermosensitivity of ASP-ELP enables the in situ formation of a sustained-release depot post-injection with zero-order release kinetics over a long time. The in vitro and in vivo studies reveal that ASP-ELP possesses increased activity retention, improved stability, extended half-life, mitigated immunogenicity, reduced toxicity, and enhanced efficacy compared to ASP and PEG-ASP. Indeed, ASP-ELP treatment in leukemia or lymphoma mouse models of cell line-derived xenograft (CDX) shows potent anti-cancer effects with significantly prolonged survival. The findings also indicate that artificial intelligence (AI)-assisted genetic engineering is instructive in designing protein-polypeptide conjugates and may pave the way to develop next-generation biologics to enhance cancer treatment.

Investigation and analysis of the comprehensive unmet needs of cancer patients treated with immune checkpoint inhibitors: a cross-sectional study

PURPOSE

This study aimed to describe the level of comprehensive needs among cancer patients treated with immune checkpoint inhibitors, to explore the relationship between comprehensive needs and demographic factors, and to examine the relationship between comprehensive needs and treatment variables.

METHOD

A cross-sectional descriptive study design was adopted. From September 2021 to July 2022, 194 cancer patients treated with immune checkpoint inhibitors were recruited using a convenience sampling method in tertiary teaching hospitals in Zhejiang Province, China. The Comprehensive Needs Assessment Tool for Cancer Patients (CNAT) and questionnaires to assess demographic and clinical characteristics were used to collect data.

RESULTS

The average comprehensive needs score for cancer patients treated with immune checkpoint inhibitors was 39.2 ± 17.2. Patients reported high levels of medical care needs, knowledge information needs, hospital facilities needs and nursing needs but low levels of religious spiritual support needs, psychoemotional needs, actual support needs, and physical symptom needs. Multiple stepwise linear regression showed that age, primary caregivers, cancer type, number of immunotherapy courses and the occurrence of immune-related adverse events (irAEs) were the main factors affecting the comprehensive needs of cancer patients treated with ICIs (p < 0.05).

CONCLUSIONS

Age, primary caregivers, cancer type, number of immunotherapy treatment courses and the occurrence of irAEs are important factors affecting the comprehensive unmet needs of cancer patients treated with immune checkpoint inhibitors. Nurses should perform targeted interventions according to the different situations of patients to improve the quality of care.

Updates in toxicities associated with immune checkpoint inhibitors

INTRODUCTION

Immune checkpoint inhibitors (ICIs) have become a pillar of treatment for numerous cancers with increasing use in combination with other ICIs and in earlier stages of disease treatment. Although effective, ICI use is accompanied by a milieu of potentially bothersome or even life-threatening toxicities known as immune-related adverse events (irAEs), necessitating careful monitoring and early intervention.

AREAS COVERED

In this review, we provide an overview of recent advances surrounding toxicity pathophysiology and treatment in the context of relevant organ systems. An emphasis on current treatments by toxicity, as well as updates on steroid-refractory toxicities, chronic toxicities, and biomarkers will be a focus of this update on the current understanding of irAEs.

EXPERT OPINION

ICI toxicities are a major limitation on the deployment of multi-agent ICI regimens and are thus a major priority to understand, treat, and prevent. Recent developments have led to greater understanding of the pathophysiology of these events, which may lead to improved prevention or mitigation strategies. Further, early studies have also suggested steroid-sparing approaches that may be useful. Ultimately, preventing and managing irAEs will be a key goal toward successful ICI treatment across a broader range of patients with cancer.

Immune checkpoint inhibitors: maximizing benefit whilst minimizing toxicity

INTRODUCTION

The advent of immunotherapy has revolutionized the treatment of cancer; anti-tumor efficacy has been observed with immune checkpoint inhibitors (ICI) in ~20 different cancer types with durable responses in some cases. However, the risk of toxicity in the form of immune-related adverse events (irAE) partially counterbalances these benefits, and there are no FDA-approved biomarkers to categorize patients by likelihood of response or risk of irAEs.

AREAS COVERED

We conducted a thorough review of the literature of clinical studies regarding ICI and their toxicities. In this review, we synthesize the current body of literature about ICI treatment and irAE by summarizing the classes and uses of ICI, how to identify patients at risk for irAE, present the current understanding of irAE development, describe ongoing research into biomarkers of irAE, examine opportunities for irAE prevention, described management of steroid refractory irAE, and highlight future directions for development of prevention and management strategies.

EXPERT OPINION

While ongoing biomarker studies are promising, it is unlikely that there will be a 'one-size-fits-all' approach to categorizing irAE risk. In contrast, improved management and irAE prophylaxis are potentially in reach, and ongoing trials will help elucidate best practices.

Better Late Than Never: The Impact of Steroidal Treatment on the Outcome of Melanoma Patients Treated with Immunotherapy

BACKGROUND

Successful treatment with Immune Checkpoint Inhibitors (ICI) requires the balanced activation of the immune system. Over-activation may result in immune-related adverse events (irAEs), which often require steroidal treatment. This study examined the possible impact of steroids on treatment efficacy in melanoma patients concerning initiation timing and dosage.

METHODS

A retrospective, single-center analysis of patients with advanced melanoma who underwent first-line ICI therapy during 2014-2020 was conducted.

RESULTS

Among the 415 patients, two-hundred patients (48.3%) were exposed to steroids during the first line, most of them due to irAEs (n = 169, 84.5%). Nearly a quarter of them were exposed to steroids within the first four weeks of treatment. Surprisingly, steroidal exposure was associated with better progression-free survival (PFS; HR = 0.74, p = 0.015); however, early exposure (within four weeks of treatment) resulted in a significantly shorter PFS compared to late exposure (adjusted HR 3.2, p < 0.001).

CONCLUSIONS

Early exposure to corticosteroids during the priming phase of ICI therapy could impede the establishment of an effective immune response. These results suggest that caution should be exercised when considering the use of steroids for the management of early-onset irAEs.

Immunosuppression for immune-related adverse events during checkpoint inhibition: an intricate balance

Immune checkpoint inhibitors (ICIs) have changed perspectives for patients with cancer, but come with severe immune-related adverse events (irAEs). To prevent fatality or chronicity, these irAEs are often promptly treated with high-dose immunosuppressants. Until recently, evidence on the effects of irAE management on ICI efficacy has been sparse. As a result, algorithms for irAE management are mostly expert-opinion based and barely consider possible detrimental effects of immunosuppressants on ICI efficacy. However, recent growing evidence suggests that vigorous immunosuppressive management of irAEs comes with unfavourable effects on ICI efficacy and survival. With expansion of the indications of ICIs, evidence-based treatment of irAEs without hampering tumour control becomes more and more important. In this review, we discuss novel evidence from pre-clinical and clinical studies on the effects of different irAE management regimens including corticosteroids, TNF inhibition and tocilizumab on cancer control and survival. We provide recommendations for pre-clinical research, cohort studies and clinical trials that can help clinicians in tailored irAE management, minimising patients' burden while maintaining ICI efficacy.

Evaluation of uveitis events in real-world patients receiving immune checkpoint inhibitors based on the FAERS database

PURPOSE

Immune checkpoint inhibitors (ICIs) have emerged as a novel class of drugs carrying a potential risk of uveitis. Due to the rarity, current knowledge on this safety issue is still incomplete. This study employed the post-marketing surveillance data to comprehensively describe and assess the uveitis events after the use of ICIs.

METHODS

Data between 2004 and 2021 were downloaded from the Food and Drug Administration Adverse Event Reporting System (FAERS), and the uveitis events reported for ICIs were identified and included in this study. Clinical details of these reports were collected and analyzed. Four data mining methods were utilized to investigate the potential associations between uveitis and different ICI regimens.

RESULTS

Overall, 461 uveitis cases after exposure to ICI therapies were reported. Melanoma (58.79%) was revealed as the most common indication for receiving ICIs. The median onset time of uveitis was 41 (interquartile range 18-91) days after ICI initiation. 9.54% of these cases resulted in disability. Data mining results showed 5 ICIs generated positive uveitis signals when used alone. Ipilimumab yielded the most noticeable uveitis signal with the highest reporting odds ratio (ROR = 6.73, 95% two-sided CI = 5.26, 8.60), proportional reporting ratio (PRR = 6.69, χ²=308.52), information component (IC = 2.74, IC025 = 2.14) and empirical Bayes geometric mean (EBGM = 6.66, EBGM05 = 5.42), followed by pembrolizumab, cemiplimab, nivolumab and atezolizumab. When nivolumab, pembrolizumab or atezolizumab was administrated together with ipilimumab, obviously stronger uveitis signal was detected than that for either of them.

CONCLUSIONS

This study provided an overview of the clinical features of ICI-related uveitis cases in the FAERS. Data mining results revealed that positive uveitis signals commonly existed within this drug class, but signal strength varied among ICIs. When ICIs were used in a combined way, uveitis signals became obviously stronger. Therefore, early ophthalmic monitoring is important when applying ICIs to patients, especially those with a tendency for uveitis, such as melanoma patients.

Dynamic immune signatures as biomarkers for irAEs

Identifying predictive biomarkers of immune-related adverse events (irAEs) is crucial to maximize the benefits for patients with cancer treated with immune checkpoint inhibitors (ICIs). In a recent study published in Med,Nuñez et al. utilized multi-omics approaches and identified blood immune signatures that have the potential to predict the development of autoimmune toxicity.

Advancing CAR T cell therapy through the use of multidimensional omics data

Despite the notable success of chimeric antigen receptor (CAR) T cell therapies in the treatment of certain haematological malignancies, challenges remain in optimizing CAR designs and cell products, improving response rates, extending the durability of remissions, reducing toxicity and broadening the utility of this therapeutic modality to other cancer types. Data from multidimensional omics analyses, including genomics, epigenomics, transcriptomics, T cell receptor-repertoire profiling, proteomics, metabolomics and/or microbiomics, provide unique opportunities to dissect the complex and dynamic multifactorial phenotypes, processes and responses of CAR T cells as well as to discover novel tumour targets and pathways of resistance. In this Review, we summarize the multidimensional cellular and molecular profiling technologies that have been used to advance our mechanistic understanding of CAR T cell therapies. In addition, we discuss current applications and potential strategies leveraging multi-omics data to identify optimal target antigens and other molecular features that could be exploited to enhance the antitumour activity and minimize the toxicity of CAR T cell therapy. Indeed, fully utilizing multi-omics data will provide new insights into the biology of CAR T cell therapy, further accelerate the development of products with improved efficacy and safety profiles, and enable clinicians to better predict and monitor patient responses.

Predictive Biomarkers for Checkpoint Inhibitor Immune-Related Adverse Events

Immune-checkpoint inhibitors (ICIs) are antagonists of inhibitory receptors in the immune system, such as the cytotoxic T-lymphocyte-associated antigen-4, the programmed cell death protein-1 and its ligand PD-L1, and they are increasingly used in cancer treatment. By blocking certain suppressive pathways, ICIs promote T-cell activation and antitumor activity but may induce so-called immune-related adverse events (irAEs), which mimic traditional autoimmune disorders. With the approval of more ICIs, irAE prediction has become a key factor in improving patient survival and quality of life. Several biomarkers have been described as potential irAE predictors, some of them are already available for clinical use and others are under development; examples include circulating blood cell counts and ratios, T-cell expansion and diversification, cytokines, autoantibodies and autoantigens, serum and other biological fluid proteins, human leucocyte antigen genotypes, genetic variations and gene profiles, microRNAs, and the gastrointestinal microbiome. Nevertheless, it is difficult to generalize the application of irAE biomarkers based on the current evidence because most studies have been retrospective, time-limited and restricted to a specific type of cancer, irAE or ICI. Long-term prospective cohorts and real-life studies are needed to assess the predictive capacity of different potential irAE biomarkers, regardless of the ICI type, organ involved or cancer site.

Predicting survival of NSCLC patients treated with immune checkpoint inhibitors: Impact and timing of immune-related adverse events and prior tyrosine kinase inhibitor therapy

Introduction

Immune checkpoint inhibitors (ICIs) produce a broad spectrum of immune-related adverse events (irAEs) affecting various organ systems. While ICIs are established as a therapeutic option in non-small cell lung cancer (NSCLC) treatment, most patients receiving ICI relapse. Additionally, the role of ICIs on survival in patients receiving prior targeted tyrosine kinase inhibitor (TKI) therapy has not been well-defined.

Objective

To investigate the impact of irAEs, the relative time of occurrence, and prior TKI therapy to predict clinical outcomes in NSCLC patients treated with ICIs.

Methods

A single center retrospective cohort study identified 354 adult patients with NSCLC receiving ICI therapy between 2014 and 2018. Survival analysis utilized overall survival (OS) and real-world progression free survival (rwPFS) outcomes. Model performance matrices for predicting 1-year OS and 6-month rwPFS using linear regression baseline, optimal, and machine learning modeling approaches.

Results

Patients experiencing an irAE were found to have a significantly longer OS and rwPFS compared to patients who did not (median OS 25.1 vs. 11.1 months; hazard ratio [HR] 0.51, confidence interval [CI] 0.39- 0.68, P-value <0.001, median rwPFS 5.7 months vs. 2.3; HR 0.52, CI 0.41- 0.66, P-value <0.001, respectively). Patients who received TKI therapy before initiation of ICI experienced significantly shorter OS than patients without prior TKI therapy (median OS 7.6 months vs. 18.5 months; P-value < 0.01). After adjusting for other variables, irAEs and prior TKI therapy significantly impacted OS and rwPFS. Lastly, the performances of models implementing logistic regression and machine learning approaches were comparable in predicting 1-year OS and 6-month rwPFS.

Conclusion

The occurrence of irAEs, the timing of the events, and prior TKI therapy were significant predictors of survival in NSCLC patients on ICI therapy. Therefore, our study supports future prospective studies to investigate the impact of irAEs, and sequence of therapy on the survival of NSCLC patients taking ICIs.

Cartography of Genomic Interactions Enables Deep Analysis of Single-Cell Expression Data

Remarkable advances in single cell genomics have presented unique challenges and opportunities for interrogating a wealth of biomedical inquiries. High dimensional genomic data are inherently complex because of intertwined relationships among the genes. Existing methods, including emerging deep learning-based approaches, do not consider the underlying biological characteristics during data processing, which greatly compromises the performance of data analysis and hinders the maximal utilization of state-of-the-art genomic techniques. In this work, we develop an entropy-based cartography strategy to contrive the high dimensional gene expression data into a configured image format, referred to as genomap, with explicit integration of the genomic interactions. This unique cartography casts the gene-gene interactions into the spatial configuration of genomaps and enables us to extract the deep genomic interaction features and discover underlying discriminative patterns of the data. We show that, for a wide variety of applications (cell clustering and recognition, gene signature extraction, single cell data integration, cellular trajectory analysis, dimensionality reduction, and visualization), the proposed approach drastically improves the accuracies of data analyses as compared to the state-of-the-art techniques.

Distinct T cell sub-clusters may serve as biomarkers for immune related adverse events

Identifying biomarkers of irAEs is the prerequisite for maximizing clinical benefits of patients treated by immune checkpoint inhibitors. Bukhari et al.¹ identified significant associations between different peripheral T cell sub-clusters and arthritis, pneumonitis, and thyroiditis.

Interstitial pneumonitis associated with combined regimen of immunotherapy and conventional therapies-pharmacovigilance database analysis with real-world data validation

BACKGROUND

Immune checkpoint inhibitor (ICI) therapy combined with conventional therapies is being broadly applied in non-small cell lung cancer (NSCLC) patients. However, the risk of interstitial pneumonitis (IP) following a combined regimen is incompletely characterized.

METHODS

A total of 46,127 NSCLC patients were extracted for disproportionality analyses of IP from the Food and Drug Administration's Adverse Event Reporting System (FAERS) database. A total of 1108 NSCLC patients who received ICI treatment at Nanfang Hospital of Southern Medical University were collected and utilized for real-world validation.

RESULTS

Of the 46,127 patients with NSCLC, 3830 cases (8.3%; 95% confidence interval [CI], 8.05-8.56) developed IP. Multivariable logistic regression analyses revealed that the adjusted ROR of ICI combined with radiation (RT) was the highest (121.69; 95% CI, 83.60-184.96; P < 0.0001) among all therapies, while that of ICI combined with chemotherapy (CHEMO) or targeted therapy (TARGET) was 0.90 (95% CI, 0.78-1.04; P = 0.160) and 1.49 (95% CI, 0.95-2.23; P = 0.065), respectively, using ICI monotherapy as reference. Furthermore, analyses from our validation cohort of 1108 cases showed that the adjusted odds ratio of ICI combined with RT was the highest (12.25; 95% CI, 3.34-50.22; P < 0.01) among all the therapies, while that of ICI combined with CHEMO or TARGET was 2.32 (95% CI, 0.89-7.92; P = 0.12) and 0.66 (95% CI, 0.03-4.55; P = 0.71), respectively, using ICI monotherapy as reference.

CONCLUSIONS

Compared with ICI monotherapy, ICI combined with RT, rather than with CHEMO or TARGET, is associated with a higher risk of IP in NSCLC patients. Hence, patients receiving these treatments should be carefully monitored for IP.

Advances in CT features and radiomics of checkpoint inhibitor-related pneumonitis: A short review

Checkpoint inhibitor-related pneumonitis (CIP) is a complication of immunotherapy for malignant tumors that severely limits the treatment cycles as well as endangers patients' health. The chest CT imaging features or typing of CIP and the application of radiomics will contribute to the precise prevention, early diagnosis and instant treatment of CIP. This article reviews the advances in the CT features and the application of radiomics in CIP.