A Variant of a Killer Cell Immunoglobulin-like Receptor Is Associated with Resistance to PD-1 Blockade in Lung Cancer

Novel insights into immune cells modulation of tumor resistance

Tumor resistance poses a significant challenge to effective cancer treatment, making it imperative to explore new therapeutic strategies. Recent studies have highlighted the profound involvement of immune cells in the development of tumor resistance. Within the tumor microenvironment, macrophages undergo polarization into the M2 phenotype, thus promoting the emergence of drug-resistant tumors. Neutrophils contribute to tumor resistance by forming extracellular traps. While T cells and natural killer (NK) cells exert their impact through direct cytotoxicity against tumor cells. Additionally, dendritic cells (DCs) have been implicated in preventing tumor drug resistance by stimulating T cell activation. In this review, we provide a comprehensive summary of the current knowledge regarding immune cell-mediated modulation of tumor resistance at the molecular level, with a particular focus on macrophages, neutrophils, DCs, T cells, and NK cells. The targeting of immune cell modulation exhibits considerable potential for addressing drug resistance, and an in-depth understanding of the molecular interactions between immune cells and tumor cells holds promise for the development of innovative therapies. Furthermore, we explore the clinical implications of these immune cells in the treatment of drug-resistant tumors. This review emphasizes the exploration of novel approaches that harness the functional capabilities of immune cells to effectively overcome drug-resistant tumors.

A comprehensive and longitudinal evaluation of the different populations of lymphoid and myeloid cells in the peripheral blood of patients treated with chemoradiotherapy for head and neck cancer

BACKGROUND

Immunotherapy provided significant survival benefits for recurrent and metastatic patients with head and neck cancer. These improvements could not be reproduced in patients treated with curative-intent chemoradiotherapy (CRT) and the optimal radio-immunotherapy (RIT) concepts have yet to be designed. Exploration and analysis of the pre-therapeutic immune status of these patients and the changes occurring during the treatment course could be crucial in rationally designing future combined treatments.

METHODS

Blood samples were collected from a cohort of 25 head and neck cancer patients treated with curative-intended (C)-RT prior to therapy, after the first week of treatment, and three months after treatment completion. Peripheral blood mononuclear cells (PBMCs) or all nucleated blood cells were isolated and analyzed via flow cytometry.

RESULTS

At baseline, patients showed reduced monocyte and lymphocyte counts compared to healthy individuals. Although overall CD8+ T-cell frequencies were reduced, the proportion of memory subsets were increased in patients. Radiotherapy (RT) treatment led to a further increase in CD8+ effector memory T-cells. Among myeloid populations, tumor-promoting subsets became less abundant after RT, in favor of pro-inflammatory cells.

CONCLUSION

The present study prospectively demonstrated a complex interplay and distinct longitudinal changes in the composition of lymphocytic and myeloid populations during curative (C)-RT of head and neck cancer. Further validation of this method in a larger cohort could allow for better treatment guidance and tailored incorporation of immunotherapies (IT) in the future.

The genomic landscape of the immune system in lung cancer: present insights and continuing investigations

Lung cancer is one of the most prevalent malignancies worldwide, contributing to over a million cancer-related deaths annually. Despite extensive research investigating the genetic factors associated with lung cancer susceptibility and prognosis, few studies have explored genetic predispositions regarding the immune system. This review discusses the most recent genomic findings related to the susceptibility to or protection against lung cancer, patient survival, and therapeutic responses. The results demonstrated the effect of immunogenetic variations in immune system-related genes associated with innate and adaptive immune responses, cytokine, and chemokine secretions, and signaling pathways. These genetic diversities may affect the crosstalk between tumor and immune cells within the tumor microenvironment, influencing cancer progression, invasion, and prognosis. Given the considerable variability in the individual immunegenomics profiles, future studies should prioritize large-scale analyses to identify potential genetic variations associated with lung cancer using highthroughput technologies across different populations. This approach will provide further information for predicting response to targeted therapy and promotes the development of new measures for individualized cancer treatment.

Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles

Recent developments in immunotherapy, including immune checkpoint blockade (ICB) and adoptive cell therapy (ACT), have encountered challenges such as immune-related adverse events and resistance, especially in solid tumors. To advance the field, a deeper understanding of the molecular mechanisms behind treatment responses and resistance is essential. However, the lack of functionally characterized immune-related gene sets has limited data-driven immunological research. To address this gap, we adopted non-negative matrix factorization on 83 human bulk RNA sequencing (RNA-seq) datasets and constructed 28 immune-specific gene sets. After rigorous immunologist-led manual annotations and orthogonal validations across immunological contexts and functional omics data, we demonstrated that these gene sets can be applied to refine pan-cancer immune subtypes, improve ICB response prediction and functionally annotate spatial transcriptomic data. These functional gene sets, informing diverse immune states, will advance our understanding of immunology and cancer research.

Neoadjuvant camrelizumab (an anti-PD-1 antibody) plus chemotherapy or apatinib (a VEGFR-2 inhibitor) for initially unresectable stage II-III non-small-cell lung cancer: a multicentre, two-arm, phase 2 exploratory study

This multicentre, two-arm, phase 2 study aimed to explore the efficacy and safety of neoadjuvant camrelizumab plus chemotherapy or apatinib in patients with initially unresectable stage II-III non-small-cell lung cancer (NSCLC). Eligible patients regardless of PD-L1 expression received neoadjuvant camrelizumab 200 mg and platinum-doublet chemotherapy every 3 weeks (arm A) or those with PD-L1-positive tumors received neoadjuvant camrelizumab and apatinib 250 mg once daily (arm B), for 2-4 cycles, followed by surgery. The primary endpoint was major pathological response (MPR) rate. Thirty patients in arm A and 21 in arm B were enrolled. Surgery rates were 50.0% (15/30) in arm A and 42.9% (9/21) in arm B, with all patients achieving R0 resections. Of these patients, the MPR and pathological complete response rates were both 20.0% (95% CI 4.3-48.1) in arm A and were 55.6% (95% CI 21.2-86.3) and 11.1% (95% CI 0.3-48.2) in arm B, respectively. The corresponding objective response rates were 33.3% (95% CI 11.8-61.6) and 55.6% (95% CI 21.2-86.3). With a median follow-up of 22.4 months (95% CI 19.0-26.0), the median event-free survival was not reached (NR; 95% CI 13.6-NR) in arm A and 16.8 months (95% CI 8.6-NR) in arm B. Grade 3 or above treatment-related adverse events occurred in eight (26.7%) patients in arm A and three (14.3%) in arm B. Biomarker analysis showed baseline TYROBP expression was predictive of treatment response in arm B. Neoadjuvant camrelizumab plus chemotherapy or apatinib exhibits preliminary efficacy and manageable toxicity in patients with initially unresectable stage II-III NSCLC.

Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles

Recent developments in immunotherapy, including immune checkpoint blockade (ICB) and adoptive cell therapy, have encountered challenges such as immune-related adverse events and resistance, especially in solid tumors. To advance the field, a deeper understanding of the molecular mechanisms behind treatment responses and resistance is essential. However, the lack of functionally characterized immune-related gene sets has limited data-driven immunological research. To address this gap, we adopted non-negative matrix factorization on 83 human bulk RNA-seq datasets and constructed 28 immune-specific gene sets. After rigorous immunologist-led manual annotations and orthogonal validations across immunological contexts and functional omics data, we demonstrated that these gene sets can be applied to refine pan-cancer immune subtypes, improve ICB response prediction and functionally annotate spatial transcriptomic data. These functional gene sets, informing diverse immune states, will advance our understanding of immunology and cancer research.

Prediction of KIR3DL1/Human Leukocyte Antigen binding

KIR3DL1 is a polymorphic inhibitory Natural Killer (NK) cell receptor that recognizes Human Leukocyte Antigen (HLA) class I allotypes that contain the Bw4 motif. Structural analyses have shown that in addition to residues 77-83 that span the Bw4 motif, polymorphism at other sites throughout the HLA molecule can influence the interaction with KIR3DL1. Given the extensive polymorphism of both KIR3DL1 and HLA class I, we built a machine learning prediction model to describe the influence of allotypic variation on the binding of KIR3DL1 to HLA class I. Nine KIR3DL1 tetramers were screened for reactivity against a panel of HLA class I molecules which revealed different patterns of specificity for each KIR3DL1 allotype. Separate models were trained for each of KIR3DL1 allotypes based on the full amino sequence of exons 2 and 3 encoding the α1 and α2 domains of the class I HLA allotypes, the set of polymorphic positions that span the Bw4 motif, or the positions that encode α1 and α2 but exclude the connecting loops. The Multi-Label-Vector-Optimization (MLVO) model trained on all alpha helix positions performed best with AUC scores ranging from 0.74 to 0.974 for the 9 KIR3DL1 allotype models. We show that a binary division into binder and non-binder is not precise, and that intermediate levels exist. Using the same models, within the binder group, high- and low-binder categories can also be predicted, the regions in HLA affecting the high vs low binder being completely distinct from the classical Bw4 motif. We further show that these positions affect binding affinity in a nonadditive way and induce deviations from linear models used to predict interaction strength. We propose that this approach should be used in lieu of simpler binding models based on a single HLA motif.

Immune Checkpoint Inhibitors: A Narrative Review on PD-1/PD-L1 Blockade Mechanism, Efficacy, and Safety Profile in Treating Malignancy

Checkpoint inhibitors have been implicated in the treatment of several cancers due to their ability to exploit the immune system's regulatory pathways. This article serves to emphasize the importance of these immunotherapeutic agents and provide further insight into their mechanisms, efficacies, and safety profiles. The main agents in question include programmed cell death protein 1 (PD-1) and programmed death ligand 1 (PD-L1). Several literature sources were found to assess the use of these inhibitors in cancers involving the lung, breast, and skin. Several peer-reviewed systematic reviews and the outcomes of clinical trials are combined within this article to support the use and further investigation of these agents in treating neoplasms. Further research into these forms of therapy underscores the revolutionary advancement of oncological interventions, which is important given the rising incidence of neoplasms within populations.

18 F-FDG PET/CT for evaluation of metastases in nonsmall cell lung cancer on the efficacy of immunotherapy

OBJECTIVE

This study aimed to investigate the relationship between 18 F-fluorodeoxyglucose PET/computed tomography ( 18 F-FDG PET/CT) metabolic parameters and clinical benefit and prognosis in nonsmall cell lung cancer (NSCLC).

METHODS

In total, 34 advanced NSCLC patients who received 18 F-FDG PET/CT before immunotherapy were retrospectively included in this study. All patients were divided into two groups, the clinical benefit (CB) group and the no-clinical benefit (no-CB) group, based on the efficacy of evaluation after 6 months of treatment. Also clinical information, characteristics of metastases, survival, PD-L1 expression level and glucose metabolic parameters were evaluated.

RESULTS

Finally, 24 patients were in the CB group, and 10 patients were in the no-CB group. There was a significant difference between the CB group and the no-CB group in TNM stages ( P  = 0.005), visceral and bone metastasis ( P  = 0.031), metabolic tumor volume of primary lesion (MTV-P; P  = 0.003), the metabolic tumor volume of whole-body (MTVwb; P  = 0.005) and total lesion glycolysis of whole-body (TLGwb, P  = 0.015). However, for patient outcomes, the independent prognostic factors associated with progression free survival were TNM stage (HR = 0.113; 95% CI, 0.029-0.439; P  = 0.002), TLG-P (HR = 0.085; 95% CI, 0.018-0.402; P  = 0.002) and TLG-LN (HR = 0.068; 95% CI, 0.015-0.308; P  = 0.000), and the TLG-LN (HR = 0.242; 95% CI, 0.066-0.879; P  = 0.002) was the independent prognostic factor associated with overall survival.

CONCLUSIONS

Metastatic lesion burden evaluated by 18 F-FDG PET/ CT can predict response to immunotherapy in advanced NSCLC patients, in which lymph node metastasis lesion metabolic burden is a meaningful predictor, but a large multicenter trial is still needed to validate this conclusion.

Combination cancer immunotherapies: Emerging treatment strategies adapted to the tumor microenvironment

Immune checkpoint blockade (ICB) has revolutionized cancer treatment. However, resistance to ICB occurs frequently due to tumor-intrinsic alterations or extrinsic factors in the tumor microenvironment. This Viewpoint aims to give an update on recent developments in immunotherapy for solid tumors and highlights progress in translational research and clinical practice.

Integrated Analysis of Single-Cell and Bulk RNA-Sequencing Reveals a Tissue-Resident Macrophage-Related Signature for Predicting Immunotherapy Response in Breast Cancer Patients

Immune checkpoint therapy (ICT) is among the widely used treatments for breast cancer (BC), but most patients do not respond to ICT and the availability of the predictive biomarkers is limited. Emerging evidence indicates that tissue-resident macrophages (RTMs) inhibit BC progression, suggesting that their presence may predict immunotherapy response. A single-cell RNA-sequencing analysis of BC samples was performed to identify five RTM clusters with a mixed phenotype of M1-M2 macrophages. The comprehensive results showed that a high score of each RTM cluster was associated with a high infiltration of CD8+ T cells, M1 macrophages, and dendritic cells, and improved overall survival. In addition, a low score of each RTM cluster was associated with a high infiltration of M0 macrophages, naïve B cells and Tregs, and poor overall survival. Gene signatures from each RTM cluster were significantly enriched in responders compared with nonresponders. Each RTM cluster expression was significantly higher in responders than in nonresponders. The analyses of bulk RNA-seq datasets of BC samples led to identification and validation of a gene expression signature, named RTM.Sig, which contained the related genes of RTM clusters for predicting response to immunotherapy. This study highlights RTM.Sig could provide a valuable tool for clinical decisions in administering ICT.

High dose androgen suppresses natural killer cytotoxicity of castration-resistant prostate cancer cells via altering AR/circFKBP5/miRNA-513a-5p/PD-L1 signals

Most advanced prostate cancer (PCa) patients initially respond well to androgen deprivation therapy, but almost all eventually develop castration-resistant prostate cancer (CRPC). Early studies indicated the bipolar androgen therapy via a cycling of high dose and low dose of androgen to suppress PCa growth might be effective in a select patient population. The detailed mechanisms, however, remain unclear. Here we found the capacity of natural killer (NK) cells to suppress the CRPC cells could be suppressed by a high dose of dihydrotestosterone (DHT). Mechanism dissection indicates that transactivated AR can increase circularRNA-FKBP5 (circFKBP5) expression, which could sponge/inhibit miR-513a-5p that suppresses the PD-L1 expression via direct binding to its 3'UTR to negatively impact immune surveillance from NK cells. Preclinical data from in vitro cell lines and an in vivo mouse model indicate that targeting PD-L1 with sh-RNA or anti-PD-L1 antibody can enhance the high dose DHT effect to better suppress CRPC cell growth. These findings may help us to develop novel therapies via combination of high dose androgen with PD-1/PD-L1 checkpoint inhibitors to better suppress CRPC progression.

Immunogenomics of Killer Cell Immunoglobulin-Like Receptor (KIR) and HLA Class I: Coevolution and Consequences for Human Health

Interactions of killer cell immunoglobin-like receptors (KIR) with human leukocyte antigens (HLA) class I regulate effector functions of key cytotoxic cells of innate and adaptive immunity. The extreme diversity of this interaction is genetically determined, having evolved in the ever-changing environment of pathogen exposure. Diversity of KIR and HLA genes is further facilitated by their independent segregation on separate chromosomes. That fetal implantation relies on many of the same types of immune cells as infection control places certain constraints on the evolution of KIR interactions with HLA. Consequently, specific inherited combinations of receptors and ligands may predispose to specific immune-mediated diseases, including autoimmunity. Combinatorial diversity of KIR and HLA class I can also differentiate success rates of immunotherapy directed to these diseases. Progress toward both etiopathology and predicting response to therapy is being achieved through detailed characterization of the extent and consequences of the combinatorial diversity of KIR and HLA. Achieving these goals is more tractable with the development of integrated analyses of molecular evolution, function, and pathology that will establish guidelines for understanding and managing risks. Here, we present what is known about the coevolution of KIR with HLA class I and the impact of their complexity on immune function and homeostasis.

Decoding the diversity of killer immunoglobulin-like receptors by deep sequencing and a high-resolution imputation method

The killer cell immunoglobulin-like receptor (KIR) recognizes human leukocyte antigen (HLA) class I molecules and modulates the function of natural killer cells. Despite its role in immunity, the complex genomic structure has limited a deep understanding of the KIR genomic landscape. Here we conduct deep sequencing of 16 KIR genes in 1,173 individuals. We devise a bioinformatics pipeline incorporating copy number estimation and insertion or deletion (indel) calling for high-resolution KIR genotyping. We define 118 alleles in 13 genes and demonstrate a linkage disequilibrium structure within and across KIR centromeric and telomeric regions. We construct a KIR imputation reference panel (n_reference = 689, imputation accuracy = 99.7%), apply it to biobank genotype (n_total = 169,907), and perform phenome-wide association studies of 85 traits. We observe a dearth of genome-wide significant associations, even in immune traits implicated previously to be associated with KIR (the smallest p = 1.5 × 10^-4). Our pipeline presents a broadly applicable framework to evaluate innate immunity in large-scale datasets.

Allele imputation for the killer cell immunoglobulin-like receptor KIR3DL1/S1

Highly polymorphic interaction of KIR3DL1 and KIR3DS1 with HLA class I ligands modulates the effector functions of natural killer (NK) cells and some T cells. This genetically determined diversity affects severity of infections, immune-mediated diseases, and some cancers, and impacts the course of immunotherapies, including transplantation. KIR3DL1 is an inhibitory receptor, and KIR3DS1 is an activating receptor encoded by the KIR3DL1/S1 gene that has more than 200 diverse and divergent alleles. Determination of KIR3DL1/S1 genotypes for medical application is hampered by complex sequence and structural variation, requiring targeted approaches to generate and analyze high-resolution allele data. To overcome these obstacles, we developed and optimized a model for imputing KIR3DL1/S1 alleles at high-resolution from whole-genome SNP data. We designed the model to represent a substantial component of human genetic diversity. Our Global imputation model is effective at genotyping KIR3DL1/S1 alleles with an accuracy ranging from 88% in Africans to 97% in East Asians, with mean specificity of 99% and sensitivity of 95% for alleles >1% frequency. We used the established algorithm of the HIBAG program, in a modification named Pulling Out Natural killer cell Genomics (PONG). Because HIBAG was designed to impute HLA alleles also from whole-genome SNP data, PONG allows combinatorial diversity of KIR3DL1/S1 with HLA-A and -B to be analyzed using complementary techniques on a single data source. The use of PONG thus negates the need for targeted sequencing data in very large-scale association studies where such methods might not be tractable.

Therapeutic Implications of Tumor Microenvironment in Lung Cancer: Focus on Immune Checkpoint Blockade

In the last decade, the treatment of non-small cell lung cancer (NSCLC) has been revolutionized by the introduction of immune checkpoint inhibitors (ICI) directed against programmed death protein 1 (PD-1) and its ligand (PD-L1), or cytotoxic T lymphocyte antigen 4 (CTLA-4). In spite of these improvements, some patients do not achieve any benefit from ICI, and inevitably develop resistance to therapy over time. Tumor microenvironment (TME) might influence response to immunotherapy due to its prominent role in the multiple interactions between neoplastic cells and the immune system. Studies investigating lung cancer from the perspective of TME pointed out a complex scenario where tumor angiogenesis, soluble factors, immune suppressive/regulatory elements and cells composing TME itself participate to tumor growth. In this review, we point out the current state of knowledge involving the relationship between tumor cells and the components of TME in NSCLC as well as their interactions with immunotherapy providing an update on novel predictors of benefit from currently employed ICI or new therapeutic targets of investigational agents. In first place, increasing evidence suggests that TME might represent a promising biomarker of sensitivity to ICI, based on the presence of immune-modulating cells, such as Treg, myeloid derived suppressor cells, and tumor associated macrophages, which are known to induce an immunosuppressive environment, poorly responsive to ICI. Consequently, multiple clinical studies have been designed to influence TME towards a pro-immunogenic state and subsequently improve the activity of ICI. Currently, the mostly employed approach relies on the association of "classic" ICI targeting PD-1/PD-L1 and novel agents directed on molecules, such as LAG-3 and TIM-3. To date, some trials have already shown promising results, while a multitude of prospective studies are ongoing, and their results might significantly influence the future approach to cancer immunotherapy.

Application of immune checkpoint targets in the anti-tumor novel drugs and traditional Chinese medicine development

Immune checkpoints are the crucial regulators of immune system and play essential roles in maintaining self-tolerance, preventing autoimmune responses, and minimizing tissue damage by regulating the duration and intensity of the immune response. Furthermore, immune checkpoints are usually overexpressed in cancer cells or noninvasive cells in tumor tissues and are capable of suppressing the antitumor response. Based on substantial physiological analyses as well as preclinical and clinical studies, checkpoint molecules have been evaluated as potential therapeutic targets for the treatment of multiple types of cancers. In the last few years, extensive evidence has supported the immunoregulatory effects of traditional Chinese medicines (TCMs). The main advantage of TCMs and natural medicine is that they usually contain multiple active components, which can act on multiple targets at the same time, resulting in additive or synergistic effects. The strong immune regulation function of traditional Chinese medicine on immune checkpoints has also been of great interest. For example, Astragalus membranaceus polysaccharides can induce anti-PD-1 antibody responses in animals, and these antibodies can overcome the exhaustion of immune cells under tumor immune evasion. Furthermore, many other TCM molecules could also be novel and effective drug candidates for the treatment of cancers. Therefore, it is essential to assess the application of immune checkpoints in the development of new drugs and TCMs. In this review, we focus on research progress in the field of immune checkpoints based on three topics: (1) immune checkpoint targets and pathways, (2) development of novel immune checkpoint-based drugs, and (3) application of immune checkpoints in the development of TCMs.

Distinctive germline expression of class I human leukocyte antigen (HLA) alleles and DRB1 heterozygosis predict the outcome of patients with non-small cell lung cancer receiving PD-1/PD-L1 immune checkpoint blockade

BACKGROUND

Nivolumab is a human monoclonal antibody against programmed cell death receptor-1 (PD-1) able to rescue quiescent tumor infiltrating cytotoxic T lymphocytes (CTLs) restoring their ability to kill target cells expressing specific tumor antigen-derived epitope peptides bound to homologue human leukocyte antigen (HLA) molecules. Nivolumab is currently an active but expensive therapeutic agent for metastatic non-small cell lung cancer (mNSCLC), producing, in some cases, immune-related adverse events (irAEs). At the present, no reliable biomarkers have been validated to predict either treatment response or adverse events in treated patients.

METHODS

We performed a retrospective multi-institutional analysis including 119 patients with mNSCLC who received PD-1 blockade since November 2015 to investigate the predictive role of germinal class I HLA and DRB1 genotype. We investigated the correlation among patients' outcome and irAEs frequency with specific HLA A, B, C and DRB1 alleles by reverse sequence-specific oligonucleotide (SSO) DNA typing.

RESULTS

A poor outcome in patients negative for the expression of two most frequent HLA-A alleles was detected (HLA: HLA-A*01 and or A*02; progression-free survival (PFS): 7.5 (2.8 to 12.2) vs 15.9 (0 to 39.2) months, p=0.01). In particular, HLA-A*01-positive patients showed a prolonged PFS of 22.6 (10.2 to 35.0) and overall survival (OS) of 30.8 (7.7 to 53.9) months, respectively. We also reported that HLA-A and DRB1 locus heterozygosis (het) were correlated to a worse OS if we considered het in the locus A; in reverse, long survival was correlated to het in DRB1.

CONCLUSIONS

This study demonstrate that class I and II HLA allele characterization to define tumor immunogenicity has relevant implications in predicting nivolumab efficacy in mNSCLC and provide the rationale for further prospective trials of cancer immunotherapy.

TNFα and Immune Checkpoint Inhibition: Friend or Foe for Lung Cancer?

Tumor necrosis factor-alpha (TNFα) can bind two distinct receptors (TNFR1/2). The transmembrane form (tmTNFα) preferentially binds to TNFR2. Upon tmTNFα cleavage by the TNF-alpha-converting enzyme (TACE), its soluble (sTNFα) form is released with higher affinity for TNFR1. This assortment empowers TNFα with a plethora of opposing roles in the processes of tumor cell survival (and apoptosis) and anti-tumor immune stimulation (and suppression), in addition to angiogenesis and metastases. Its functions and biomarker potential to predict cancer progression and response to immunotherapy are reviewed here, with a focus on lung cancer. By mining existing sequencing data, we further demonstrate that the expression levels of TNF and TACE are significantly decreased in lung adenocarcinoma patients, while the TNFR1/TNFR2 balance are increased. We conclude that the biomarker potential of TNFα alone will most likely not provide conclusive findings, but that TACE could have a key role along with the delicate balance of sTNFα/tmTNFα as well as TNFR1/TNFR2, hence stressing the importance of more research into the potential of rationalized treatments that combine TNFα pathway modulators with immunotherapy for lung cancer patients.

[Immunotherapy for Lung Cancer: Mechanisms of Resistance and Response Strategy]

Inhibition of immune checkpoints is at the forefront of immunotherapy for lung cancer. However, a high percentage of lung cancer patients do not respond to these immunotherpy or their responses are transient, indicating the existence of immune resistance. Emerging evidence suggested that the interactions between cancer cells and immune system were continuous and dynamic. Here, we review how a range of cancer-cell-autonomous characteristics, tumor-microenvironment factors, and host-related influences account for heterogenous responses. Furthermore, with the identification of new targets of immunotherapy and development of immune-based combination therapy, we elucidate the methods might useful to overcome resistance.

Meta-analysis of tumor- and T cell-intrinsic mechanisms of sensitization to checkpoint inhibition

Checkpoint inhibitors (CPIs) augment adaptive immunity. Systematic pan-tumor analyses may reveal the relative importance of tumor-cell-intrinsic and microenvironmental features underpinning CPI sensitization. Here, we collated whole-exome and transcriptomic data for >1,000 CPI-treated patients across seven tumor types, utilizing standardized bioinformatics workflows and clinical outcome criteria to validate multivariable predictors of CPI sensitization. Clonal tumor mutation burden (TMB) was the strongest predictor of CPI response, followed by total TMB and CXCL9 expression. Subclonal TMB, somatic copy alteration burden, and histocompatibility leukocyte antigen (HLA) evolutionary divergence failed to attain pan-cancer significance. Dinucleotide variants were identified as a source of immunogenic epitopes associated with radical amino acid substitutions and enhanced peptide hydrophobicity/immunogenicity. Copy-number analysis revealed two additional determinants of CPI outcome supported by prior functional evidence: 9q34 (TRAF2) loss associated with response and CCND1 amplification associated with resistance. Finally, single-cell RNA sequencing (RNA-seq) of clonal neoantigen-reactive CD8 tumor-infiltrating lymphocytes (TILs), combined with bulk RNA-seq analysis of CPI-responding tumors, identified CCR5 and CXCL13 as T-cell-intrinsic markers of CPI sensitivity.

In silico tools for accurate HLA and KIR inference from clinical sequencing data empower immunogenetics on individual-patient and population scales

Immunogenetic variation in humans is important in research, clinical diagnosis and increasingly a target for therapeutic intervention. Two highly polymorphic loci play critical roles, namely the human leukocyte antigen (HLA) system, which is the human version of the major histocompatibility complex (MHC), and the Killer-cell immunoglobulin-like receptors (KIR) that are relevant for responses of natural killer (NK) and some subsets of T cells. Their accurate classification has typically required the use of dedicated biological specimens and a combination of in vitro and in silico efforts. Increased availability of next generation sequencing data has led to the development of ancillary computational solutions. Here, we report an evaluation of recently published algorithms to computationally infer complex immunogenetic variation in the form of HLA alleles and KIR haplotypes from whole-genome or whole-exome sequencing data. For both HLA allele and KIR gene typing, we identified tools that yielded >97% overall accuracy for four-digit HLA types, and >99% overall accuracy for KIR gene presence, suggesting the readiness of in silico solutions for use in clinical and high-throughput research settings.

Cancer cell-derived exosomal circUHRF1 induces natural killer cell exhaustion and may cause resistance to anti-PD1 therapy in hepatocellular carcinoma

Objective

Natural killer (NK) cells play a critical role in the innate antitumor immune response. Recently, NK cell dysfunction has been verified in various malignant tumors, including hepatocellular carcinoma (HCC). However, the molecular biological mechanisms of NK cell dysfunction in human HCC are still obscure.

Methods

The expression of circular ubiquitin-like with PHD and ring finger domain 1 RNA (circUHRF1) in HCC tissues, exosomes, and cell lines was detected by qRT-PCR. Exosomes were isolated from the culture medium of HCC cells and plasma of HCC patients using an ultracentrifugation method and the ExoQuick Exosome Precipitation Solution kit and then characterized by transmission electronic microscopy, NanoSight and western blotting. The role of circUHRF1 in NK cell dysfunction was assessed by ELISA. In vivo circRNA precipitation, RNA immunoprecipitation, and luciferase reporter assays were performed to explore the molecular mechanisms of circUHRF1 in NK cells. In a retrospective study, the clinical characteristics and prognostic significance of circUHRF1 were determined in HCC tissues.

Results

Here, we report that the expression of circUHRF1 is higher in human HCC tissues than in matched adjacent nontumor tissues. Increased levels of circUHRF1 indicate poor clinical prognosis and NK cell dysfunction in patients with HCC. In HCC patient plasma, circUHRF1 is predominantly secreted by HCC cells in an exosomal manner, and circUHRF1 inhibits NK cell-derived IFN-γ and TNF-α secretion. A high level of plasma exosomal circUHRF1 is associated with a decreased NK cell proportion and decreased NK cell tumor infiltration. Moreover, circUHRF1 inhibits NK cell function by upregulating the expression of TIM-3 via degradation of miR-449c-5p. Finally, we show that circUHRF1 may drive resistance to anti-PD1 immunotherapy in HCC patients.

Conclusions

Exosomal circUHRF1 is predominantly secreted by HCC cells and contributes to immunosuppression by inducing NK cell dysfunction in HCC. CircUHRF1 may drive resistance to anti-PD1 immunotherapy, providing a potential therapeutic strategy for patients with HCC.

Peripheral natural killer cells and myeloid-derived suppressor cells correlate with anti-PD-1 responses in non-small cell lung cancer

Inhibition of immune checkpoint proteins like programmed death 1 (PD-1) is a promising therapeutic approach for several cancers, including non-small cell lung cancer (NSCLC). Although PD-1 ligand (PD-L1) expression is used to predict anti-PD-1 therapy responses in NSCLC, its accuracy is relatively less. Therefore, we sought to identify a more accurate predictive blood biomarker for evaluating anti-PD-1 response. We evaluated the frequencies of T cells, B cells, natural killer (NK) cells, polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs), mononuclear myeloid-derived suppressor cells (M-MDSCs), and Lox-1+ PMN-MDSCs in peripheral blood samples of 62 NSCLC patients before and after nivolumab treatment. Correlation of immune-cell population frequencies with treatment response, progression-free survival, and overall survival was also determined. After the first treatment, the median NK cell percentage was significantly higher in responders than in non-responders, while the median Lox-1+ PMN-MDSC percentage showed the opposite trend. NK cell frequencies significantly increased in responders but not in non-responders. NK cell frequency inversely correlated with that of Lox-1+ PMN-MDSCs after the first treatment cycle. The NK cell-to-Lox-1+ PMN-MDSC ratio (NMR) was significantly higher in responders than in non-responders. Patients with NMRs ≥ 5.75 after the first cycle had significantly higher objective response rates and longer progression-free and overall survival than those with NMRs <5.75. NMR shows promise as an early predictor of response to further anti-PD-1 therapy.

PD-1+ natural killer cells in human non-small cell lung cancer can be activated by PD-1/PD-L1 blockade

Natural killer (NK) cells are critically involved in anti-tumor immunity by targeting tumor cells. In this study, we show that intratumoral NK cells from NSCLC patients expressed elevated levels of the immune checkpoint receptor PD-1 on their cell surface. In contrast to the expression of activating receptors, PD-1⁺ NK cells co-expressed more inhibitory receptors compared to PD-1^- NK cells. Intratumoral NK cells were less functional compared to peripheral NK cells, and this dysfunction correlated with PD-1 expression. Tumor cells expressing PD-L1 inhibited the functionality of PD-1⁺ NK cells in ex vivo models and induced PD-1 clustering at the immunological synapse between NK cells and tumor cells. Notably, treatment with PD-1 blockade was able to reverse PD-L1-mediated inhibition of PD-1⁺ NK cells. Our findings highlight the therapeutic potential of PD-1⁺ NK cells in immune checkpoint blockade and could guide the development of NK cell-stimulating agents in combination with PD-1 blockade.

Resistance Mechanism of PD-1/PD-L1 Blockade in the Cancer-Immunity Cycle

In recent years, the PD-1/PD-L1 axis blockade has become a very promising therapy with significant clinical benefits for multiple tumor types. However, some patients still do not respond sufficiently to PD-1/PD-L1 targeted monotherapy. Therefore, investigating the mechanism of PD-1 blockade resistance will assist in exploring new immunotherapy strategies, controlling the progress of the disease, and thus bringing more sustainable survival benefits to patients. The tumor-immune cycle is divided into the following seven steps: the release of cancer antigens, cancer antigen presentation, priming and activation, trafficking of T cells to tumors, infiltration of T cells into tumors, recognition of cancer cells by T cells, and killing of cancer cells. Given that PD-1/PD-L1 blockade is primarily involved in step 7, any abnormalities in the previous steps may affect the efficacy of PD-1/PD-L1 inhibitors and lead to drug resistance. This review discussed the resistance mechanisms of PD-1/PD-L1 blockade in each cancer-immunity step to finding a more suitable treatment population and an optimized combination therapy to exert immunotherapy in tumor treatment to a greater extent.

Tumor mutational burden assessed by targeted NGS predicts clinical benefit from immune checkpoint inhibitors in non-small cell lung cancer

In non‐small cell lung cancer (NSCLC), immune checkpoint inhibitors (ICIs) significantly improve overall survival (OS). Tumor mutational burden (TMB) has emerged as a predictive biomarker for patients treated with ICIs. Here, we evaluated the predictive power of TMB measured by the Oncomine™ Tumor Mutational Load targeted sequencing assay in 76 NSCLC patients treated with ICIs. TMB was assessed retrospectively in 76 NSCLC patients receiving ICI therapy. Clinical data (RECIST 1.1) were collected and patients were classified as having either durable clinical benefit (DCB) or no durable benefit (NDB). Additionally, genetic alterations and PD‐L1 expression were assessed and compared with TMB and response rate. TMB was significantly higher in patients with DCB than in patients with NDB (median TMB = 8.5 versus 6.0 mutations/Mb, Mann–Whitney p = 0.0244). 64% of patients with high TMB (cut‐off = third tertile, TMB ≥ 9) were responders (DCB) compared to 33% and 29% of patients with intermediate and low TMB, respectively (cut‐off = second and first tertile, TMB = 5–9 and TMB ≤ 4, respectively). TMB‐high patients showed significantly longer progression‐free survival (PFS) and OS (log‐rank test p = 0.0014 for PFS and 0.0197 for OS). While identifying different subgroups of patients, combining PD‐L1 expression and TMB increased the predictive power (from AUC 0.63 to AUC 0.65). Our results show that the TML panel is an effective tool to stratify patients for ICI treatment. A combination of biomarkers might maximize the predictive precision for patient stratification. Our study supports TMB evaluation through targeted NGS in NSCLC patient samples as a tool to predict response to ICI therapy. We offer recommendations for a reliable and cost‐effective assessment of TMB in a routine diagnostic setting. © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.