Identification of Clonal Neoantigens Derived From Driver Mutations in an EGFR-Mutated Lung Cancer Patient Benefitting From Anti-PD-1

Biomarkers and computational models for predicting efficacy to tumor ICI immunotherapy

Numerous studies have shown that immune checkpoint inhibitor (ICI) immunotherapy has great potential as a cancer treatment, leading to significant clinical improvements in numerous cases. However, it benefits a minority of patients, underscoring the importance of discovering reliable biomarkers that can be used to screen for potential beneficiaries and ultimately reduce the risk of overtreatment. Our comprehensive review focuses on the latest advancements in predictive biomarkers for ICI therapy, particularly emphasizing those that enhance the efficacy of programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibitors and cytotoxic T-lymphocyte antigen-4 (CTLA-4) inhibitors immunotherapies. We explore biomarkers derived from various sources, including tumor cells, the tumor immune microenvironment (TIME), body fluids, gut microbes, and metabolites. Among them, tumor cells-derived biomarkers include tumor mutational burden (TMB) biomarker, tumor neoantigen burden (TNB) biomarker, microsatellite instability (MSI) biomarker, PD-L1 expression biomarker, mutated gene biomarkers in pathways, and epigenetic biomarkers. TIME-derived biomarkers include immune landscape of TIME biomarkers, inhibitory checkpoints biomarkers, and immune repertoire biomarkers. We also discuss various techniques used to detect and assess these biomarkers, detailing their respective datasets, strengths, weaknesses, and evaluative metrics. Furthermore, we present a comprehensive review of computer models for predicting the response to ICI therapy. The computer models include knowledge-based mechanistic models and data-based machine learning (ML) models. Among the knowledge-based mechanistic models are pharmacokinetic/pharmacodynamic (PK/PD) models, partial differential equation (PDE) models, signal networks-based models, quantitative systems pharmacology (QSP) models, and agent-based models (ABMs). ML models include linear regression models, logistic regression models, support vector machine (SVM)/random forest/extra trees/k-nearest neighbors (KNN) models, artificial neural network (ANN) and deep learning models. Additionally, there are hybrid models of systems biology and ML. We summarized the details of these models, outlining the datasets they utilize, their evaluation methods/metrics, and their respective strengths and limitations. By summarizing the major advances in the research on predictive biomarkers and computer models for the therapeutic effect and clinical utility of tumor ICI, we aim to assist researchers in choosing appropriate biomarkers or computer models for research exploration and help clinicians conduct precision medicine by selecting the best biomarkers.

At the crossroads of immunotherapy for oncogene-addicted subsets of NSCLC

Non-small-cell lung cancer (NSCLC) has become a paradigm of precision medicine, with the discovery of numerous disease subtypes defined by specific oncogenic driver mutations leading to the development of a range of molecularly targeted therapies. Over the past decade, rapid progress has also been made in the development of immune-checkpoint inhibitors (ICIs), especially antagonistic antibodies targeting the PD-L1-PD-1 axis, for the treatment of NSCLC. Although many of the major oncogenic drivers of NSCLC are associated with intrinsic resistance to ICIs, patients with certain oncogene-driven subtypes of the disease that are highly responsive to specific targeted therapies might also derive benefit from immunotherapy. However, the development of effective immunotherapy approaches for oncogene-addicted NSCLC has been challenged by a lack of predictive biomarkers for patient selection and limited knowledge of how ICIs and oncogene-directed targeted therapies should be combined. Therefore, whether ICIs alone or with chemotherapy or even in combination with molecularly targeted agents would offer comparable benefit in the context of selected oncogenic driver alterations to that observed in the general unselected NSCLC population remains an open question. In this Review, we discuss the effects of oncogenic driver mutations on the efficacy of ICIs and the immune tumour microenvironment as well as the potential vulnerabilities that could be exploited to overcome the challenges of immunotherapy for oncogene-addicted NSCLC.

Neoantigen-specific TCR-T cell-based immunotherapy for acute myeloid leukemia

Neoantigens derived from non-synonymous somatic mutations are restricted to malignant cells and are thus considered ideal targets for T cell receptor (TCR)-based immunotherapy. Adoptive transfer of T cells bearing neoantigen-specific TCRs exhibits the ability to preferentially target tumor cells while remaining harmless to normal cells. High-avidity TCRs specific for neoantigens expressed on AML cells have been identified in vitro and verified using xenograft mouse models. Preclinical studies of these neoantigen-specific TCR-T cells are underway and offer great promise as safe and effective therapies. Additionally, TCR-based immunotherapies targeting tumor-associated antigens are used in early-phase clinical trials for the treatment of AML and show encouraging anti-leukemic effects. These clinical experiences support the application of TCR-T cells that are specifically designed to recognize neoantigens. In this review, we will provide a detailed profile of verified neoantigens in AML, describe the strategies to identify neoantigen-specific TCRs, and discuss the potential of neoantigen-specific T-cell-based immunotherapy in AML.

Immunotherapy for EGFR-mutant advanced non-small-cell lung cancer: Current status, possible mechanisms and application prospects

Immune checkpoint inhibitors (ICIs) are effective against advanced and even perioperative non-small-cell lung cancer (NSCLC) and result in durable clinical benefit, regardless of programmed death ligand-1 (PD-L1) expression status in cancer. Existing clinical evidence shows that the effect of immunotherapy in patients with EGFR-mutant NSCLC after the development of tyrosine kinase inhibitor (TKI) resistance is not satisfactory. However, compared with monotherapy, ICIs combined with chemotherapy can improve the efficacy. Encouragingly, compared with that of patients with sensitive mutations, the progression-free survival of patients with rare mutations who were treated with ICIs was increased. Adequately maximizing the efficacy of ICIs in EGFR-mutant NSCLC patients is worth exploring. In this review, we described preclinical and clinical studies of ICIs or combined therapy for EGFR-mutant NSCLC. We further focused on EGFR mutations and the cancer immune response, with particular attention given to the role of EGFR activation in the cancer-immunity cycle. The mechanisms for the natural resistance to ICIs were explored to identify corresponding countermeasures that made more EGFR-mutant NSCLC patients benefit from ICIs.

TCR Gene Therapy for Cancer

The protocol describes the procedure of antigen-specific T cell generation and TCR identification for the use in adoptive T cell therapy. We describe two paths of generating antigen-specific T cells, first, T cell stimulation with autologous dendritic cells pulsed with antigen peptide, second, in vivo T cell stimulation with peptide or DNA by gene gun application in a suitable mouse model followed by in vitro enrichment of peptide-reactive T cells. Peptide-stimulated T cells are sorted by fluorescence-activated cell sorting for CD107α or IFNγ expression and subsequently isolated RNA is used in a 5' rapid amplification of cDNA ends (RACE )-PCR specific for TCR for TCR chain identification. After retroviral cloning, it is re-expressed on human T cells to test its applicability in adoptive T cell therapy.

Isolation of Neoantigen-Specific Human T Cell Receptors from Different Human and Murine Repertoires

Simple Summary

T cell-based immunotherapy has achieved remarkable clinical responses in patients with cancer. Neoepitope-specific T cells can specifically recognize mutated tumor cells and have led to tumor regression in mouse models and clinical studies. However, isolating neoepitope-specific T cell receptors (TCRs) from the patients’ own repertoire has shown limited success. Sourcing T cell repertoires, other than the patients’ own, has certain advantages: the availability of larger amounts of blood from healthy donors, circumventing tumor-related immunosuppression in patients, and including different donors to broaden the pool of specific T cells. Here, for the first time, a side-by-side comparison of three different TCR donor repertoires, including patients and HLA-matched allogenic healthy human repertoires, as well as repertoires of transgenic mice, is performed. Our results support recent studies that using not only healthy donor T cell repertoires, but also transgenic mice might be a viable strategy for isolating TCRs with known specificity directed against neoantigens for adoptive T cell therapy.

Abstract

(1) Background: Mutation-specific T cell receptor (TCR)-based adoptive T cell therapy represents a truly tumor-specific immunotherapeutic strategy. However, isolating neoepitope-specific TCRs remains a challenge. (2) Methods: We investigated, side by side, different TCR repertoires—patients’ peripheral lymphocytes (PBLs) and tumor-infiltrating lymphocytes (TILs), PBLs of healthy donors, and a humanized mouse model—to isolate neoepitope-specific TCRs against eight neoepitope candidates from a colon cancer and an ovarian cancer patient. Neoepitope candidates were used to stimulate T cells from different repertoires in vitro to generate neoepitope-specific T cells and isolate the specific TCRs. (3) Results: We isolated six TCRs from healthy donors, directed against four neoepitope candidates and one TCR from the murine T cell repertoire. Endogenous processing of one neoepitope, for which we isolated one TCR from both human and mouse-derived repertoires, could be shown. No neoepitope-specific TCR could be generated from the patients’ own repertoire. (4) Conclusion: Our data indicate that successful isolation of neoepitope-specific TCRs depends on various factors such as the heathy donor’s TCR repertoire or the presence of a tumor microenvironment allowing neoepitope-specific immune responses of the host. We show the advantage and feasibility of using healthy donor repertoires and humanized mouse TCR repertoires to generate mutation-specific TCRs with different specificities, especially in a setting when the availability of patient material is limited.

Genomic correlates of programmed cell death ligand 1 (PD-L1) expression in Chinese lung adenocarcinoma patients

Background

Although PD-L1 expression is a crucial predictive biomarker for immunotherapy, it can be influenced by many factors.

Methods

A total of 248 Chinese patients with lung adenocarcinoma was retrospectively identified. Data for clinical features, gene alternations, signaling pathways and immune signatures was analyzed among negative expression group (TPS < 1%, n = 124), intermediate expression group (1% ≤ TPS < 50%, n = 93), and high expression group (TPS ≥ 50%, n = 38). Clinical outcomes among different expression groups were also evaluated from public database.

Results

Firstly, high tumor mutation burden was significantly associated with high PD-L1 expression in these Chinese patients with lung adenocarcinoma. In addition, gene alternations including TP53, PRKDC, KMT2D, TET1 and SETD2 apparently occurred in high PD-L1 expression group. Moreover, pathway analysis showed that mutations involving in DDR pathway, TP53 pathway, cell-cycle pathway and NOTCH pathway were obviously varied among three PD-L1 expression groups. Besides, most of patients in high PD-L1 expression group from TCGA database were determined as high-grade immune subtypes (C2-C4), showing significant higher proportions of IFN-gamma, CD8+ T-cells, NK cells, NK CD56 dim cells, Th1 cells, Th2 cells (P < 0.0001). Moreover, SETD2 mutation slightly correlated with overall survival from MSKCC cohort (HR 1.92 [95%CI 0.90–4.10], P = 0.085), and the percentage of IFN-gamma was significantly higher in SETD2 mutant group than in wild-type group (P < 0.01).

Conclusions

This study illustrated in-depth genomic correlates of PD-L1 expression in Chinese lung adenocarcinoma patients and relevant immune signatures from public database, which might interpret more potential molecular mechanisms for immunotherapy in NSCLC.

The Promise of Personalized TCR-Based Cellular Immunotherapy for Cancer Patients

Mutation-derived neoantigens are now established as attractive targets for cancer immunotherapy. The field of adoptive T cell transfer (ACT) therapy was significantly reshaped by tumor neoantigens and is now moving towards the genetic engineering of T cells with neoantigen-specific T cell receptors (TCRs). Yet, the identification of neoantigen-reactive TCRs remains challenging and the process needs to be adapted to clinical timelines. In addition, the state of recipient T cells for TCR transduction is critical and can affect TCR-ACT efficacy. Here we provide an overview of the main strategies for TCR-engineering, describe the selection and expansion of optimal carrier cells for TCR-ACT and discuss the next-generation methods for rapid identification of relevant TCR candidates for gene transfer therapy.

The Current Lung Cancer Neoantigen Landscape and Implications for Therapy

All tumors harbor unique mutant peptides, some of which are able to elicit T-cell-mediated immune responses. These are known as neoantigens. Lung cancers bear a heavy mutational burden and hence many potential neoantigens. Neoantigens are increasingly recognized as key mediators of tumor-specific immune activation and have been identified as potential targets for personalized cancer therapies. In this review, we discuss the current data on neoantigens in lung cancer and provide an overview of the recent advances in neoantigen-based immunotherapy. Furthermore, we look ahead to highlight the major opportunities and challenges for the clinical application of neoantigen-based treatment strategies for thoracic and other malignancies.

HLA loss of heterozygosity-mediated discordant responses to immune checkpoint blockade in squamous cell lung cancer with renal metastasis

Despite the significant success of immune checkpoint blockade therapy in advanced non-small-cell lung cancer compared with chemotherapy, efficacy varies greatly across patients, and acquired resistance frequently occurs. In particular, during immunotherapy, the dynamic changes in molecular events have not been characterized. The authors report a case of squamous cell lung carcinoma with renal metastasis, treated with pembrolizumab, in which the primary tumor and rare renal metastases showed different responses. Using whole-exome sequencing, the authors found loss of heterogeneity in HLA genes in all tumors and high levels of intratumor heterogeneity in metastases. The increased levels of HLA loss led to therapy resistance during tumor evolution. In addition to tumor mutational burden and PD-L1, HLA loss of heterozygosity and intratumor heterogeneity should be taken into consideration during immunotherapy.