Autoreactive napsin A-specific T cells are enriched in lung tumors and inflammatory lung lesions during immune checkpoint blockade

Cancer type-specific adverse events of immune checkpoint inhibitors: A systematic review and meta-analysis

Background

The distribution of adverse events (AEs) triggered by immune checkpoint inhibitors (ICIs) across different cancer types has never been demonstrated.

Methods

Randomised controlled trials exclusively assessing ICI monotherapy in cohorts of over 100 patients were considered. Our primary outcome was a comprehensive summary of the distribution of all-grade treatment-related adverse events (TRAEs) as well as serious TRAEs (CTCAE grade 3 or higher) across different malignancies. The study is registered with PROSPERO CRD42023387934.

Findings

75 trials that enrolled over 100 patients were included. While investigating the incidence of each TRAE across various cancers, we found special linkages existed between certain TRAEs and particular cancer types. In anti-PD-1 monotherapy group, melanoma patients experienced the most frequent fatigue (31.1 %, 95 % CI 29.7%-32.5 %); the incidences of severe pneumonitis and other respiratory disorders were highest in Hodgkin lymphoma (4.1 %, 95 % CI 1.5%-8.6 %; 4.1 %, 95 % CI 1.5%-8.6 %, respectively). Among individuals undergoing single-agent anti-PD-L1, higher frequency of all-grade pruritus occurred in 19.0 % of renal cell carcinoma (RCC) patients (95 % CI 15.2%-23.2 %), and the highest probability of developing other severe musculoskeletal disorders was observed in patients with RCC (6.2 %, 95 % CI 4.0%-9.0 %). In anti-CTLA-4 monotherapy, the incidences of both all-grade and severe diarrhea occurred most frequently in prostate cancer patients (41.9 %, 95 % CI 37.9%-47.9; 14.8 %, 95 % CI 11.5%-18.7 %, respectively).

Interpretation

This is the first comprehensive study addressing the distribution of various TRAEs across cancer types. Our research emphasizes the significance of considering cancer-specific TRAEs when using ICIs for treatment.

The role of tumor types in immune-related adverse events

Immune checkpoint inhibitors (ICIs) are monoclonal antibodies that block inhibitors of T cell activation and function. With the widespread use of ICIs in cancer therapy, immune-related adverse events (irAEs) have gradually emerged as urgent clinical issues. Tumors not only exhibit high heterogeneity, and their response to ICIs varies, with "hot" tumors showing better anti-tumor effects but also a higher susceptibility to irAEs. The manifestation of irAEs displays a tumor-heterogeneous pattern, correlating with the tumor type in terms of the affected organs, incidence, median onset time, and severity. Understanding the mechanisms underlying the pathogenic patterns of irAEs can provide novel insights into the prevention and management of irAEs, guide the development of biomarkers, and contribute to a deeper understanding of the toxicological characteristics of ICIs. In this review, we explore the impact of tumor type on the therapeutic efficacy of ICIs and further elucidate how these tumor types influence the occurrence of irAEs. Finally, we assess key candidate biomarkers and their relevance to proposed irAE mechanisms. This paper also outlines management strategies for patients with various types of tumors, based on their disease patterns.

Autoimmunity Against Surfactant Protein B Is Associated with Pneumonitis During Checkpoint Blockade

Rationale: Immune checkpoint inhibitor (ICI)-related pneumonitis is a serious autoimmune event affecting as many as 20% of patients with non-small-cell lung cancer (NSCLC), yet the factors underpinning its development in some patients and not others are poorly understood. Objectives: To investigate the role of autoantibodies and autoreactive T cells against surfactant-related proteins in the development of pneumonitis. Methods: The study cohort consisted of patients with NSCLC who provided blood samples before and during ICI treatment. Serum was used for proteomics analyses and to detect autoantibodies present during pneumonitis. T-cell stimulation assays and single-cell RNA sequencing were performed to investigate the specificity and functionality of peripheral autoreactive T cells. The findings were confirmed in a validation cohort comprising patients with NSCLC and patients with melanoma. Measurements and Main Results: Across both cohorts, patients in whom pneumonitis developed had higher pretreatment levels of immunoglobulin G autoantibodies targeting surfactant protein (SP)-B. At the onset of pneumonitis, these patients also exhibited higher frequencies of CD4+ IFN-γ-positive SP-B-specific T cells and expanding T-cell clonotypes recognizing this protein, accompanied by a proinflammatory serum proteomic profile. Conclusions: Our data suggest that the cooccurrence of SP-B-specific immunoglobulin G autoantibodies and CD4+ T cells is associated with the development of pneumonitis during ICI therapy. Pretreatment levels of these antibodies may represent a potential biomarker for an increased risk of developing pneumonitis, and on-treatment levels may provide a diagnostic aid.

The potential role of lung microbiota and lauroylcarnitine in T-cell activation associated with checkpoint inhibitor pneumonitis

BACKGROUND

Checkpoint inhibitor pneumonitis (CIP) is a potentially fatal adverse event characterized by new pulmonary infiltrates in cancer patients receiving immune checkpoint inhibitor therapy. This study aims to explore the interplay between lung microbiota, dysregulated metabolites, and host immunity in CIP.

METHODS

We recruited thirteen hospitalized CIP patients, eleven idiopathic pulmonary fibrosis (IPF) patients, and ten new-onset non-small cell lung cancer patients. Bronchoalveolar lavage fluid samples were collected for 16S rRNA gene sequencing. The percentages of immune cells were determined using manual counting and flow cytometry. Interactions among microbiota, metabolites, and lymphocytes were analyzed using cultured mouse splenocytes and human T cells.

FINDINGS

Proteobacteria emerged as the dominant phylum, notably abundant in both the CIP and IPF groups. Vibrio, Halomonas, Mangrovibacter, and Salinivibrio were the predominant microbiota because of their discriminative abundance patterns. Vibrio (r = 0.72, P-adj = 0.007) and Halomonas (r = 0.65, P-adj = 0.023) demonstrated strong correlations with lymphocytes. Vibrio metschnikovii and Mangrovibacter plantisponsors were more abundant in the CIP group than in the IPF group. Lauroylcarnitine, a key intermediary metabolite co-occurring with the predominant microbiota, exhibited a potent effect on cytokine secretion by mouse and human T cells, notably enhancing IFN-γ and TNF-α production from CD4 and CD8 cells in vitro.

INTERPRETATION

Lauroylcarnitine, co-occurring with the predominant lung microbiota in CIP, could activate T cells in vitro. These findings suggest potential involvement of lung microbiota and acylcarnitine metabolism dysregulation in the pathogenesis of CIP.

FUNDING

This work was supported by Peking University People's Hospital Scientific Research Development Funds (RDJ2022-15) and Provincial Key Clinical Specialty Capacity Building Project 2020 (Department of the Respiratory Medicine).

Clinical and translational attributes of immune-related adverse events

With immune checkpoint inhibitors (ICIs) becoming the mainstay of treatment for many cancers, managing their immune-related adverse events (irAEs) has become an important part of oncological care. This Review covers the clinical presentation of irAEs and crucial aspects of reversibility, fatality and long-term sequelae, with special attention to irAEs in specific patient populations, such as those with autoimmune diseases. In addition, the genetic basis of irAEs, along with cellular and humoral responses to ICI therapy, are discussed. Detrimental effects of empirically used high-dose steroids and second-line immunosuppression, including impaired ICI effectiveness, call for more tailored irAE-treatment strategies. We discuss open therapeutic challenges and propose potential avenues to accelerate personalized management strategies and optimize outcomes.

Immune-related adverse events in non-small cell lung cancer: Occurrence, mechanisms and therapeutic strategies

The emergence of immune checkpoint inhibitors (ICIs) has heralded a transformative era in the therapeutic landscape of non-small cell lung cancer (NSCLC). While ICIs have demonstrated clinical efficacy in a portion of patients with NSCLC, these treatments concurrently precipitate a spectrum of immune-related adverse events (irAEs), encompassing mild to severe manifestations, collectively posing a risk of significant organ damage. Consequently, there exists an imperative to augment our comprehension of the pathophysiological underpinnings of irAEs and to formulate more efficacious preventive and ameliorative strategies. In this comprehensive review, we delineate the clinical presentation of organ-specific irAEs in patients with NSCLC and provide an in-depth analysis of recent advancements in understanding the mechanisms driving ICI-induced toxicity. Furthermore, we discuss potential strategies and targets for ameliorating these irAEs. Ultimately, this review aims to furnish valuable insights to guide further research endeavours in the context of irAEs in NSCLC patients.

Unraveling the complex interplay between anti-tumor immune response and autoimmunity mediated by B cells and autoantibodies in the era of anti-checkpoint monoclonal antibody therapies

The intricate relationship between anti-tumor immunity and autoimmunity is a complex yet crucial aspect of cancer biology. Tumor microenvironment often exhibits autoimmune features, a phenomenon that involves natural autoimmunity and the induction of humoral responses against self-antigens during tumorigenesis. This induction is facilitated by the orchestration of anti-tumor immunity, particularly within organized structures like tertiary lymphoid structures (TLS). Paradoxically, a significant number of cancer patients do not manifest autoimmune features during the course of their illness, with rare instances of paraneoplastic syndromes. This discrepancy can be attributed to various immune-mediated locks, including regulatory or suppressive immune cells, anergic autoreactive lymphocytes, or induction of effector cells exhaustion due to chronic stimulation. Overcoming these locks holds the risk to induce autoimmune mechanisms during cancer progression, a phenomenon notably observed with anti-immune checkpoint therapies, in contrast to more conventional treatments like chemotherapy or radiotherapy. Therefore, the challenge arises in managing immune-related adverse events (irAEs) induced by immune checkpoint inhibitors treatment, as decoupling them from the anti-tumor activity poses a significant clinical dilemma. This review summarizes recent advances in understanding the link between B-cell driven anti-tumor responses and autoimmune reactions in cancer patients, and discusses the clinical implications of this relationship.

Tumor-Reactive CD8+ T Cells Enter a TCF1+PD-1- Dysfunctional State

T cells recognize several types of antigens in tumors, including aberrantly expressed, nonmutated proteins, which are therefore shared with normal tissue and referred to as self/shared-antigens (SSA), and mutated proteins or oncogenic viral proteins, which are referred to as tumor-specific antigens (TSA). Immunotherapies such as immune checkpoint blockade (ICB) can activate T-cell responses against TSA, leading to tumor control, and also against SSA, causing immune-related adverse events (irAE). To improve anti-TSA immunity while limiting anti-SSA autoreactivity, we need to understand how tumor-specific CD8+ T cells (TST) and SSA-specific CD8+ T (SST) cells differentiate in response to cognate antigens during tumorigenesis. Therefore, we developed a genetic cancer mouse model in which we can track TST and SST differentiation longitudinally as liver cancers develop. We found that both TST and SST lost effector function over time, but while TST persisted long term and had a dysfunctional/exhausted phenotype (including expression of PD1, CD39, and TOX), SST exited cell cycle prematurely and disappeared from liver lesions. However, SST persisted in spleens in a dysfunctional TCF1+PD-1- state: unable to produce effector cytokines or proliferate in response to ICB targeting PD-1 or PD-L1. Thus, our studies identify a dysfunctional T-cell state occupied by T cells reactive to SSA: a TCF1+PD-1- state lacking in effector function, demonstrating that the type/specificity of tumor antigen may determine tumor-reactive T-cell differentiation.

Autoreactive T cells targeting type II pneumocyte antigens in COVID-19 convalescent patients

BACKGROUND

The role of autoreactive T cells on the course of Coronavirus disease-19 (COVID-19) remains elusive. Type II pneumocytes represent the main target cells of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Autoimmune responses against antigens highly expressed in type II pneumocytes may influence the severity of COVID-19 disease.

OBJECTIVE

The aim of this study was to investigate autoreactive T cell responses against self-antigens highly expressed in type II pneumocytes in the blood of COVID-19 patients with severe and non-severe disease.

METHODS

We collected blood samples of COVID-19 patients with varying degrees of disease severity and of pre-pandemic controls. T cell stimulation assays with peptide pools of type II pneumocyte antigens were performed in two independent cohorts to analyze the autoimmune T cell responses in patients with non-severe and severe COVID-19 disease. Target cell lysis assays were performed with lung cancer cell lines to determine the extent of cell killing by type II PAA-specific T cells.

RESULTS

We identified autoreactive T cell responses against four recently described self-antigens highly expressed in type II pneumocytes, known as surfactant protein A, surfactant protein B, surfactant protein C and napsin A, in the blood of COVID-19 patients. These antigens were termed type II pneumocyte-associated antigens (type II PAAs). We found that patients with non-severe COVID-19 disease showed a significantly higher frequency of type II PAA-specific autoreactive T cells in the blood when compared to severely ill patients. The presence of high frequencies of type II PAA-specific T cells in the blood of non-severe COVID-19 patients was independent of their age. We also found that napsin A-specific T cells from convalescent COVID-19 patients could kill lung cancer cells, demonstrating the functional and cytotoxic role of these T cells.

CONCLUSIONS

Our data suggest that autoreactive type II PAA-specific T cells have a protective role in SARS-CoV-2 infections and the presence of high frequencies of these autoreactive T cells indicates effective viral control in COVID-19 patients. Type II-PAA-specific T cells may therefore promote the killing of infected type II pneumocytes and viral clearance.

Immune aging - A mechanism in autoimmune disease

Evidence is emerging that the process of immune aging is a mechanism leading to autoimmunity. Over lifetime, the immune system adapts to profound changes in hematopoiesis and lymphogenesis, and progressively restructures in face of an ever-expanding exposome. Older adults fail to generate adequate immune responses against microbial infections and tumors, but accumulate aged T cells, B cells and myeloid cells. Age-associated B cells are highly efficient in autoantibody production. T-cell aging promotes the accrual of end-differentiated effector T cells with potent cytotoxic and pro-inflammatory abilities and myeloid cell aging supports a low grade, sterile and chronic inflammatory state (inflammaging). In pre-disposed individuals, immune aging can lead to frank autoimmune disease, manifesting with chronic inflammation and irreversible tissue damage. Emerging data support the concept that autoimmunity results from aging-induced failure of fundamental cellular processes in immune effector cells: genomic instability, loss of mitochondrial fitness, failing proteostasis, dwindling lysosomal degradation and inefficient autophagy. Here, we have reviewed the evidence that malfunctional mitochondria, disabled lysosomes and stressed endoplasmic reticula induce pathogenic T cells and macrophages that drive two autoimmune diseases, rheumatoid arthritis (RA) and giant cell arteritis (GCA). Recognizing immune aging as a risk factor for autoimmunity will open new avenues of immunomodulatory therapy, including the repair of malfunctioning mitochondria and lysosomes.

Effects of immune-related adverse events (irAEs) and their treatment on antitumor immune responses

Immune checkpoint inhibitors (ICIs) are potentially life-saving cancer therapies that can trigger immune-related adverse events (irAEs). irAEs can impact any organ and range in their presentation from mild side effects to life-threatening complications. The relationship between irAEs and antitumor immune responses is nuanced and may depend on the irAE organ, the tumor histology, and the patient. While some irAEs likely represent an immune response against antigens shared between tumor cells and healthy tissues, other irAEs may be entirely unrelated to antitumor immune responses. Clinical observations suggest that low-grade irAEs have a positive association with responses to ICIs, but the correlation between severe irAEs and clinical benefit is less clear. Currently, severe irAEs are typically treated by interrupting or permanently discontinuing ICI treatment and administering empirically selected systemic immunosuppressive agents. However, these interventions could potentially diminish the antitumor effects of ICIs. Efforts to understand the mechanistic relationship between irAEs and the tumor microenvironment have yielded meaningful insights and nominated therapeutic targets for irAE management that may preserve or even boost ICI efficacy. We explore the clinical and molecular relationship between irAEs and antitumor immunity as well as the role that irAE treatments may play in shaping antitumor immune responses.

Autoimmunity in immune checkpoint inhibitor-induced immune-related adverse events: A focus on autoimmune skin toxicity and pneumonitis

Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy. However, their use is frequently associated with immune-related adverse events (irAEs) potentially affecting any organ. The mechanisms mediating such irAEs remain poorly understood and biomarkers to predict the development of irAEs are lacking. Growing evidence shows the importance of self-antigens in mediating irAEs during ICI therapy, in particular the well-described melanocyte differentiation antigens in melanoma patients. This review will focus on two novel classes of self-antigens involved in mediating autoimmune skin toxicity and pneumonitis in non-small cell lung cancer patients treated with immunotherapy. T cells specific for these self-antigens are thought to not only mediate irAEs but are thought to simultaneously mediate anti-tumor responses and are therefore associated with both autoimmune toxicity and response to ICI therapy. We further discuss emerging cellular and proteomic immune signatures of irAEs that may serve as biomarkers to help predict which patients are at higher risk of developing these irAEs. The determination of new tumor antigens involved in ICI therapy and the identification of related biomarkers brings us a step forward in the mechanistic understanding of ICIs and will help to monitor patients at higher risk of developing irAEs. Lastly, we discuss the current challenges in collecting research samples for the study of ICI-related mechanisms and in distinguishing between immune signatures of response and those of irAEs.

T-cell tolerant fraction as a predictor of immune-related adverse events

BACKGROUND

Immune checkpoint inhibitor (ICI) therapies may cause unpredictable and potentially severe autoimmune toxicities termed immune-related adverse events (irAEs). Because T cells mediate ICI effects, T cell profiling may provide insight into the risk of irAEs. Here we evaluate a novel metric-the T-cell tolerant fraction-as a predictor of future irAEs.

METHODS

We examined T-cell receptor beta (TRB) locus sequencing from baseline pretreatment samples from an institutional registry and previously published studies. For each patient, we used TRB sequences to calculate the T-cell tolerant fraction, which was then assessed as a predictor of future irAEs (classified as Common Terminology Criteria for Adverse Event grade 0-1 vs grade ≥2). We then compared the tolerant fraction to TRB clonality and diversity. Finally, the tolerant fraction was assessed on (1) T cells enriched against napsin A, a potential autoantigen of irAEs; (2) thymic versus peripheral blood T cells; and (3) TRBs specific for various infections and autoimmune diseases.

RESULTS

A total of 77 patients with cancer (22 from an institutional registry and 55 from published studies) receiving ICI therapy (43 CTLA4, 19 PD1/PDL1, 15 combination CTLA4+PD1/PDL1) were included in the study. The tolerant fraction was significantly lower in cases with clinically significant irAEs (p<0.001) and had an area under the receiver operating curve (AUC) of 0.79. The tolerant fraction was lower for each ICI treatment category, reaching statistical significance for CTLA4 (p<0.001) and demonstrating non-significant trends for PD1/PDL1 (p=0.21) and combination ICI (p=0.18). The tolerant fraction for T cells enriched against napsin A was lower than other samples. The tolerant fraction was also lower in thymic versus peripheral blood samples, and lower in some (multiple sclerosis) but not other (type 1 diabetes) autoimmune diseases. In our study cohort, TRB clonality had an AUC of 0.62, and TRB diversity had an AUC of 0.60 for predicting irAEs.

CONCLUSIONS

Among patients receiving ICI, the baseline T-cell tolerant fraction may serve as a predictor of clinically significant irAEs.

Predicting response and toxicity to immune checkpoint inhibitors in lung cancer using antibodies to frameshift neoantigens

PURPOSE

To evaluate a new class of blood-based biomarkers, anti-frameshift peptide antibodies, for predicting both tumor responses and adverse immune events to immune checkpoint inhibitor (ICI) therapies in advanced lung cancer patients.

EXPERIMENTAL DESIGN

Serum samples were obtained from 74 lung cancer patients prior to palliative PD-(L)1 therapies with subsequently recorded tumor responses and immune adverse events (irAEs). Pretreatment samples were assayed on microarrays of frameshift peptides (FSPs), representing ~ 375,000 variant peptides that tumor cells can be informatically predicted to produce from translated mRNA processing errors. Serum-antibodies specifically recognizing these ligands were measured. Binding activities preferentially associated with best-response and adverse-event outcomes were determined. These antibody bound FSPs were used in iterative resampling analyses to develop predictive models of tumor response and immune toxicity.

RESULTS

Lung cancer serum samples were classified based on predictive models of ICI treatment outcomes. Disease progression was predicted pretreatment with ~ 98% accuracy in the full cohort of all response categories, though ~ 30% of the samples were indeterminate. This model was built with a heterogeneous sample cohort from patients that (i) would show either clear response or stable outcomes, (ii) would be administered either single or combination therapies and (iii) were diagnosed with different lung cancer subtypes. Removing the stable disease, combination therapy or SCLC groups from model building increased the proportion of samples classified while performance remained high. Informatic analyses showed that several of the FSPs in the all-response model mapped to translations of variant mRNAs from the same genes. In the predictive model for treatment toxicities, binding to irAE-associated FSPs provided 90% accuracy pretreatment, with no indeterminates. Several of the classifying FSPs displayed sequence similarity to self-proteins.

CONCLUSIONS

Anti-FSP antibodies may serve as biomarkers for predicting ICI outcomes when tested against ligands corresponding to mRNA-error derived FSPs. Model performances suggest this approach might provide a single test to predict treatment response to ICI and identify patients at high risk for immunotherapy toxicities.

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.

Immune signatures predict development of autoimmune toxicity in patients with cancer treated with immune checkpoint inhibitors

BACKGROUND

Immune checkpoint inhibitors (ICIs) are among the most promising treatment options for melanoma and non-small cell lung cancer (NSCLC). While ICIs can induce effective anti-tumor responses, they may also drive serious immune-related adverse events (irAEs). Identifying biomarkers to predict which patients will suffer from irAEs would enable more accurate clinical risk-benefit analysis for ICI treatment and may also shed light on common or distinct mechanisms underpinning treatment success and irAEs.

METHODS

In this prospective multi-center study, we combined a multi-omics approach including unbiased single-cell profiling of over 300 peripheral blood mononuclear cell (PBMC) samples and high-throughput proteomics analysis of over 500 serum samples to characterize the systemic immune compartment of patients with melanoma or NSCLC before and during treatment with ICIs.

FINDINGS

When we combined the parameters obtained from the multi-omics profiling of patient blood and serum, we identified potential predictive biomarkers for ICI-induced irAEs. Specifically, an early increase in CXCL9/CXCL10/CXCL11 and interferon-γ (IFN-γ) 1 to 2 weeks after the start of therapy are likely indicators of heightened risk of developing irAEs. In addition, an early expansion of Ki-67⁺ regulatory T cells (Tregs) and Ki-67⁺ CD8⁺ T cells is also likely to be associated with increased risk of irAEs.

CONCLUSIONS

We suggest that the combination of these cellular and proteomic biomarkers may help to predict which patients are likely to benefit most from ICI therapy and those requiring intensive monitoring for irAEs.

FUNDING

This work was primarily funded by the European Research Council, the Swiss National Science Foundation, the Swiss Cancer League, and the Forschungsförderung of the Kantonsspital St. Gallen.

Artificial Intelligence-Assisted Transcriptomic Analysis to Advance Cancer Immunotherapy

The emergence of immunotherapy has dramatically changed the cancer treatment paradigm and generated tremendous promise in precision medicine. However, cancer immunotherapy is greatly limited by its low response rates and immune-related adverse events. Transcriptomics technology is a promising tool for deciphering the molecular underpinnings of immunotherapy response and therapeutic toxicity. In particular, applying single-cell RNA-seq (scRNA-seq) has deepened our understanding of tumor heterogeneity and the microenvironment, providing powerful help for developing new immunotherapy strategies. Artificial intelligence (AI) technology in transcriptome analysis meets the need for efficient handling and robust results. Specifically, it further extends the application scope of transcriptomic technologies in cancer research. AI-assisted transcriptomic analysis has performed well in exploring the underlying mechanisms of drug resistance and immunotherapy toxicity and predicting therapeutic response, with profound significance in cancer treatment. In this review, we summarized emerging AI-assisted transcriptomic technologies. We then highlighted new insights into cancer immunotherapy based on AI-assisted transcriptomic analysis, focusing on tumor heterogeneity, the tumor microenvironment, immune-related adverse event pathogenesis, drug resistance, and new target discovery. This review summarizes solid evidence for immunotherapy research, which might help the cancer research community overcome the challenges faced by immunotherapy.

Immune biology of NSCLC revealed by single-cell technologies: implications for the development of biomarkers in patients treated with immunotherapy

First-line immunotherapy in non-small-cell lung cancer largely improved patients' survival. PD-L1 testing is required before immune checkpoint inhibitor initiation. However, this biomarker fails to accurately predict patients' response. On the other hand, immunotherapy exposes patients to immune-related toxicity, the mechanisms of which are still unclear. Hence, there is an unmet need to develop clinically approved predictive biomarkers to better select patients who will benefit the most from immune checkpoint inhibitors and improve risk management. Single-cell technologies provide unprecedented insight into the tumor and its microenvironment, leading to the discovery of immune cells involved in immune checkpoint inhibitor response or toxicity. In this review, we will underscore the potential of the single-cell approach to identify candidate biomarkers improving non-small-cell lung cancer patients' care.