Comprehensive T cell repertoire characterization of non-small cell lung cancer

Exploring the potential of the TCR repertoire as a tumor biomarker (Review)

T cells play an important role in adaptive immunity. Mature T cells specifically recognize antigens on major histocompatibility complex molecules through T-cell receptors (TCRs). As the TCR repertoire is highly diverse, its analysis is vital in the assessment of T cells. Advances in sequencing technology have provided convenient methods for further investigation of the TCR repertoire. In the present review, the TCR structure and the mechanisms by which TCRs function in tumor recognition are described. In addition, the potential value of the TCR repertoire in tumor diagnosis is reviewed. Furthermore, the role of the TCR repertoire in tumor immunotherapy is introduced, and the relationships between the TCR repertoire and the effects of different tumor immunotherapies are discussed. Based on the reviewed literature, it may be concluded that the TCR repertoire has the potential to serve as a biomarker for tumor prognosis. However, a wider range of cancer types and more diverse subjects require evaluation in future research to establish the TCR repertoire as a biomarker of tumor immunity.

Quantifiable TCR repertoire changes in prediagnostic blood specimens among patients with high-grade ovarian cancer

High-grade ovarian cancer (HGOC) is a major cause of death in women. Early detection of HGOC usually leads to a cure, yet it remains a clinical challenge with over 90% HGOCs diagnosed at advanced stages. This is mainly because conventional biomarkers are not sensitive enough to detect the microscopic yet metastatic early lesions. In this study, we sequence the blood T cell receptor (TCR) repertoires of 466 patients with ovarian cancer and controls and systematically investigate the immune repertoire signatures in HGOCs. We observe quantifiable changes of selected TCRs in HGOCs that are reproducible in multiple independent cohorts. Importantly, these changes are stronger during stage I. Using pre-diagnostic patient blood samples from the Nurses' Health Study, we confirm that HGOC signals can be detected in the blood TCR repertoire up to 4 years preceding conventional diagnosis. Our findings may provide the basis for future immune-based HGOC early detection criteria.

A multi-bin rarefying method for evaluating alpha diversities in TCR sequencing data

MOTIVATION

T cell receptors (TCRs) constitute a major component of our adaptive immune system, governing the recognition and response to internal and external antigens. Studying the TCR diversity via sequencing technology is critical for a deeper understanding of immune dynamics. However, library sizes differ substantially across samples, hindering the accurate estimation/comparisons of alpha diversities. To address this, researchers frequently use an overall rarefying approach in which all samples are sub-sampled to an even depth. Despite its pervasive application, its efficacy has never been rigorously assessed.

RESULTS

In this paper, we develop an innovative "multi-bin" rarefying approach that partitions samples into multiple bins according to their library sizes, conducts rarefying within each bin for alpha diversity calculations, and performs meta-analysis across bins. Extensive simulations using real-world data highlight the inadequacy of the overall rarefying approach in controlling the confounding effect of library size. Our method proves robust in addressing library size confounding, outperforming competing normalization strategies by achieving better-controlled type-I error rates and enhanced statistical power in association tests.

AVAILABILITY AND IMPLEMENTATION

The code is available at https://github.com/mli171/MultibinAlpha. The datasets are freely available at https://doi.org/10.21417/B7001Z and https://doi.org/10.21417/AR2019NC.

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.

Single-arm study of camrelizumab plus apatinib for patients with advanced mucosal melanoma

BACKGROUND

Previous studies have suggested the potential synergistic antitumor activity when combining immune checkpoint inhibitors with anti-angiogenic agents in various solid tumors. We aimed to assess the efficacy and safety of camrelizumab (a humanized programmed cell death-1 antibody) plus apatinib (a vascular endothelial growth factor receptor tyrosine kinase inhibitor) for patients with advanced mucosal melanoma (MM), and explore-related biomarkers.

METHODS

We conducted a single-center, open-label, single-arm, phase II study. Patients with unresectable or recurrent/metastatic MM received camrelizumab and apatinib. The primary endpoint was the confirmed objective response rate (ORR).

RESULTS

Between April 2019 and June 2022, 32 patients were enrolled, with 50.0% previously received systemic therapy. Among 28 patients with evaluable response, the confirmed ORR was 42.9%, the disease control rate was 82.1%, and the median progression-free survival (PFS) was 8.05 months. The confirmed ORR was 42.9% (6/14) in both treatment-naïve and previously treated patients. Notably, treatment-naïve patients had a median PFS of 11.89 months, and those with prior treatment had a median PFS of 6.47 months. Grade 3 treatment-related adverse events were transaminase elevation, rash, hyperbilirubinemia, proteinuria, hypertension, thrombocytopenia, hand-foot syndrome and diarrhea. No treatment-related deaths were observed. Higher tumor mutation burden (TMB), increased T-cell receptor (TCR) diversity, and altered receptor tyrosine kinase (RTK)/RAS pathway correlated with better tumor response.

CONCLUSION

Camrelizumab plus apatinib provided promising antitumor activity with acceptable toxicity in patients with advanced MM. TMB, TCR diversity and RTK/RAS pathway genes were identified as potential predictive biomarkers and warrant further validation.

TRIAL REGISTRATION NUMBER

Chinese Clinical Trial Registry, ChiCTR1900023277.

Expression of modified FcγRI enables myeloid cells to elicit robust tumor-specific cytotoxicity

Despite the central role of T cells in tumor immunity, attempts to harness their cytotoxic capacity as a therapy have met limited efficacy, partially as a result of the suppressive microenvironment which limits their migration and activation. In contrast, myeloid cells massively infiltrate tumors and are well adapted to survive these harsh conditions. While they are equipped with cell-killing abilities, they often adopt an immunosuppressive phenotype upon migration to tumors. Therefore, the questions of how to modify their activation programming against cancer, and what signaling cascades should be activated in myeloid cells to elicit their cytotoxicity have remained unclear. Here, we found that activation of IgM-induced signaling in murine myeloid cells results in secretion of lytic granules and massive tumor cell death. These findings open venues for designing novel immunotherapy by equipping monocytes with chimeric receptors that target tumor antigens and consequently, signal through IgM receptor. Nonetheless, we found that myeloid cells do not express the antibody-derived portion used to recognize the tumor antigen due to the induction of an ER stress response. To overcome this limitation, we designed chimeric receptors that are based on the high-affinity FcγRI for IgG. Incubation of macrophages expressing these receptors along with tumor-binding IgG induced massive tumor cell killing and secretion of reactive oxygen species and Granzyme B. Overall, this work highlights the challenges involved in genetically reprogramming the signaling in myeloid cells and provides a framework for endowing myeloid cells with antigen-specific cytotoxicity.

Further knowledge and developments in resistance mechanisms to immune checkpoint inhibitors

The past decade has witnessed a revolution in cancer treatment, shifting from conventional drugs (chemotherapies) towards targeted molecular therapies and immune-based therapies, in particular immune-checkpoint inhibitors (ICIs). These immunotherapies release the host's immune system against the tumor and have shown unprecedented durable remission for patients with cancers that were thought incurable, such as metastatic melanoma, metastatic renal cell carcinoma (RCC), microsatellite instability (MSI) high colorectal cancer and late stages of non-small cell lung cancer (NSCLC). However, about 80% of the patients fail to respond to these immunotherapies and are therefore left with other less effective and potentially toxic treatments. Identifying and understanding the mechanisms that enable cancerous cells to adapt to and eventually overcome therapy can help circumvent resistance and improve treatment. In this review, we describe the recent discoveries on the onco-immunological processes which govern the tumor microenvironment and their impact on the resistance to PD-1/PD-L1 checkpoint blockade.

The Deep Learning Framework iCanTCR Enables Early Cancer Detection Using the T-cell Receptor Repertoire in Peripheral Blood

T cells recognize tumor antigens and initiate an anticancer immune response in the very early stages of tumor development, and the antigen specificity of T cells is determined by the T-cell receptor (TCR). Therefore, monitoring changes in the TCR repertoire in peripheral blood may offer a strategy to detect various cancers at a relatively early stage. Here, we developed the deep learning framework iCanTCR to identify patients with cancer based on the TCR repertoire. The iCanTCR framework uses TCRβ sequences from an individual as an input and outputs the predicted cancer probability. The model was trained on over 2,000 publicly available TCR repertoires from 11 types of cancer and healthy controls. Analysis of several additional publicly available datasets validated the ability of iCanTCR to distinguish patients with cancer from noncancer individuals and demonstrated the capability of iCanTCR for the accurate classification of multiple cancers. Importantly, iCanTCR precisely identified individuals with early-stage cancer with an AUC of 86%. Altogether, this work provides a liquid biopsy approach to capture immune signals from peripheral blood for noninvasive cancer diagnosis.

SIGNIFICANCE

Development of a deep learning-based method for multicancer detection using the TCR repertoire in the peripheral blood establishes the potential of evaluating circulating immune signals for noninvasive early cancer detection.

Transcription Factor ETV4 Activates AURKA to Promote PD-L1 Expression and Mediate Immune Escape in Lung Adenocarcinoma

INTRODUCTION

The occurrence and progression of lung adenocarcinoma (LUAD) impair T-cell immune responses, causing immune escape and subsequently affecting the efficacy of immunotherapy in patients. Aurora kinase A (AURKA) is upregulated in varying cancers, but its role in LUAD immune escape is elusive. This work attempted to explore molecular mechanisms of AURKA regulation in LUAD immune escape.

METHODS

Through bioinformatics analysis, AURKA level in LUAD was evaluated, and potential upstream transcription factors of AURKA were predicted using hTFtarget. ETS variant transcription factor 4 (ETV4) expression in LUAD was analyzed through The Cancer Genome Atlas. Pearson's correlation analysis was then utilized to test the correlation between AURKA and ETV4. Interaction and binding between AURKA and ETV4 were validated through dual-luciferase assay and chromatin immunoprecipitation. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) tested relative mRNA expression of AURKA and ETV4 in LUAD cells, cell counting kit-8 assayed cell viability, and Western blot analysis was conducted to determine the protein level of programmed death-ligand 1 (PD-L1). Coculture of LUAD cells with activated CD8+ T cells was carried out, and an LDH assay was used to assess the cytotoxicity of CD8+ T cells against LUAD cells. Interferon-γ (IFN-γ), interleukin-2 (IL-2), and tumor necrosis factor-α (TNF-α) levels in the coculture system were assessed by enzyme-linked immunosorbent assay (ELISA). Western blot assessed protein levels of JAK2, p-JAK2, STAT3, and p-STAT3.

RESULTS

Compared to normal tissues, AURKA and ETV4 were upregulated in tumor tissues, and AURKA presented a negative association with CD8+ T-cell immune infiltration but a positive association with PD-L1. qRT-PCR unveiled significantly upregulated mRNA of AURKA and ETV4 in LUAD cells compared to normal lung epithelial cells. Knockdown of AURKA significantly decreased cell viability and PD-L1 protein level in LUAD cells, enhanced cytotoxicity of CD8+ T cells against LUAD cells and IFN-γ, IL-2, and TNF-α expression, while overexpression of AURKA yielded opposite results. Furthermore, the knockdown of ETV4 could reverse the oncogenic characteristics of cells caused by AURKA overexpression.

CONCLUSION

Our study illustrated that ETV4/AURKA axis promoted PD-L1 expression, suppressed CD8+ T-cell activity, and mediated immune escape in LUAD by regulating the JAK2/STAT3 signaling pathway.

Multidimensional biological characteristics of ground glass nodules

The detection rate of ground glass nodules (GGNs) has increased in recent years because of their malignant potential but relatively indolent biological behavior; thus, correct GGN recognition and management has become a research focus. Many scholars have explored the underlying mechanism of the indolent progression of GGNs from several perspectives, such as pathological type, genomic mutational characteristics, and immune microenvironment. GGNs have different major mutated genes at different stages of development; EGFR mutation is the most common mutation in GGNs, and p53 mutation is the most abundant mutation in the invasive stage of GGNs. Pure GGNs have fewer genomic alterations and a simpler genomic profile and exhibit a gradually evolving genomic mutation profile as the pathology progresses. Compared to advanced lung adenocarcinoma, GGN lung adenocarcinoma has a higher immune cell percentage, is under immune surveillance, and has less immune escape. However, as the pathological progression and solid component increase, negative immune regulation and immune escape increase gradually, and a suppressive immune environment is established gradually. Currently, regular computer tomography monitoring and surgery are the main treatment strategies for persistent GGNs. Stereotactic body radiotherapy and radiofrequency ablation are two local therapeutic alternatives, and systemic therapy has been progressively studied for lung cancer with GGNs. In the present review, we discuss the characterization of the multidimensional molecular evolution of GGNs that could facilitate more precise differentiation of such highly heterogeneous lesions, laying a foundation for the development of more effective individualized treatment plans.

Comprehensive Analysis of a Dendritic Cell Marker Genes Signature to Predict Prognosis and Immunotherapy Response in Lung Adenocarcinoma

With the development of immune checkpoints inhibitors (ICIs), immunotherapy has recently taken center stage in cancer treatment. Dendritic cells exert complicated and important functions in antitumor immunity. This study aims to construct a novel dendritic cell marker gene signature (DCMGS) to predict the prognosis and immunotherapy response of lung adenocarcinoma (LUAD). DC marker genes in LUAD were identified by analysis of single-cell RNA sequencing data. 6 genes (G0S2, KLF4, ALDH2, IER3, TXN, CD69) were screened as the most prognosis-related genes for constructing DCMGS on a training cohort from TCGA data set. Patients were divided into high-risk and low-risk groups by DCMGS risk score based on overall survival time. Then, the predictive ability of the risk model was validated in 6 independent cohorts. DCMGS was verified to be an independent prognostic factor in multivariate analysis. Furthermore, we performed pathway enrichment analysis to explore possible biological mechanisms of the powerful predictive ability of DCMGS, and immune cell infiltration landscape and inflammatory activities were exhibited to reflect the immune profile. Notably, we bridged DCMGS with expression of immune checkpoints and TCR/BCR repertoire diversity that can inflect immunotherapy response. Finally, the predictive ability of DCMGS in immunotherapy response was also validated by 2 cohorts that had received immunotherapy. As a result, the patients with lower DCMGS risk scores showed a better prognosis and immunotherapy response. In conclusion, DCMGS was suggested to be a promising prognostic indicator for LUAD and a desirable predictor for immunotherapy response.

Clonal expansion of shared T cell receptors reveals the existence of immune commonality among different lesions of synchronous multiple primary lung cancer

The increase in the detection rate of synchronous multiple primary lung cancer (MPLC) has posed remarkable clinical challenges due to the limited understanding of its pathogenesis and molecular features. Here, comprehensive comparisons of genomic and immunologic features between MPLC and solitary lung cancer nodule (SN), as well as different lesions of the same patient, were performed. Compared with SN, MPLC displayed a lower rate of EGFR mutation but higher rates of BRAF, MAP2K1, and MTOR mutation, which function exactly in the upstream and downstream of the same signaling pathway. Considerable heterogeneity in T cell receptor (TCR) repertoire exists among not only different patients but also among different lesions of the same patient. Invasive lesions of MPLC exhibited significantly higher TCR diversity and lower TCR expansion than those of SN. Intriguingly, different lesions of the same patient always shared a certain proportion of TCR clonotypes. Significant clonal expansion could be observed in shared TCR clonotypes, particularly in those existing in all lesions of the same patient. In conclusion, this study provided evidences of the distinctive mutational landscape, activation of oncogenic signaling pathways, and TCR repertoire in MPLC as compared with SN. The significant clonal expansion of shared TCR clonotypes demonstrated the existence of immune commonality among different lesions of the same patient and shed new light on the individually tailored precision therapy for MPLC.

Evolving insights into the improvement of adoptive T-cell immunotherapy through PD-1/PD-L1 blockade in the clinical spectrum of lung cancer

Undeniably, cancer immunotherapies have expanded the spectrum of cancer treatment, however, some patients do not respond to immunotherapies. This scenario is no different for lung cancer, whose two main types, non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), still pose a serious clinical challenge. Adoptive T-cell therapies (ATC), which primarily include cytokine-induced killer (CIK) cell therapy, chimeric antigen receptor T-cell (CAR T-cell) therapy and γδ-T-cell therapy, strengthen the patient's immune system in combating cancer. Combining ATC with immune checkpoint inhibitors (ICI) further enhances the effectiveness of this approach to eradicate cancer. With a particular emphasis on CIK cell therapy, which recently completed 30 years, we highlight the role of the PD-1/PD-L1 axis in NSCLC and SCLC. Besides, we provide insights into the potential synergies of PD-1/PD-L1 inhibitors with adoptive T-cell immunotherapy in reshaping the treatment paradigm for lung cancer.

The activity and immune dynamics of PD-1 inhibition on high-risk pulmonary ground glass opacity lesions: insights from a single-arm, phase II trial

Immune checkpoint inhibitors targeting the programmed cell death-1 (PD-1) protein significantly improve survival in patients with advanced non-small-cell lung cancer (NSCLC), but its impact on early-stage ground-glass opacity (GGO) lesions remains unclear. This is a single-arm, phase II trial (NCT04026841) using Simon's optimal two-stage design, of which 4 doses of sintilimab (200 mg per 3 weeks) were administrated in 36 enrolled multiple primary lung cancer (MPLC) patients with persistent high-risk (Lung-RADS category 4 or had progressed within 6 months) GGOs. The primary endpoint was objective response rate (ORR). T/B/NK-cell subpopulations, TCR-seq, cytokines, exosomal RNA, and multiplexed immunohistochemistry (mIHC) were monitored and compared between responders and non-responders. Finally, two intent-to-treat (ITT) lesions (pure-GGO or GGO-predominant) showed responses (ORR: 5.6%, 2/36), and no patients had progressive disease (PD). No grade 3-5 TRAEs occurred. The total response rate considering two ITT lesions and three non-intent-to-treat (NITT) lesions (pure-solid or solid-predominant) was 13.9% (5/36). The proportion of CD8+ T cells, the ratio of CD8+/CD4+, and the TCR clonality value were significantly higher in the peripheral blood of responders before treatment and decreased over time. Correspondingly, the mIHC analysis showed more CD8+ T cells infiltrated in responders. Besides, responders' cytokine concentrations of EGF and CTLA-4 increased during treatment. The exosomal expression of fatty acid metabolism and oxidative phosphorylation gene signatures were down-regulated among responders. Collectively, PD-1 inhibitor showed certain activity on high-risk pulmonary GGO lesions without safety concerns. Such effects were associated with specific T-cell re-distribution, EGF/CTLA-4 cytokine compensation, and regulation of metabolism pathways.

Comparative Study of T-Cell Repertoires after COVID-19 Immunization with Homologous or Heterologous Vaccine Booster

Sequencing of the T-cell repertoire is an innovative method to assess the cellular responses after immunization. The purpose of this study was to compare T-cell repertoires after COVID-19 immunization with homologous (HOB) and heterologous (HEB) boosting. The study included 20 participants with a median age of 27.5 (IQR:23) years, who were vaccinated with one dose of the Ad26.COV2.S vaccine and were boosted with either Ad26.COV2.S (n = 10) or BNT162b2 (n = 10) vaccine. Analysis of the T-cell receptor beta locus (TCRβ) sequencing one month after the booster dose identified that the HEB compared to the HOB group exhibited a higher number of both total and COVID-19-related functional T-cell rearrangements [mean of total productive rearrangements (TPRs): 63151.8 (SD ± 18441.5) vs. 34915.4 (SD ± 11121.6), p = 0.001 and COVID-19-TPRs: 522.5 (SD ± 178.0) vs. 298.3 (SD ± 101.1), p = 0.003]. A comparison between the HOB and HEB groups detected no statistically significant differences regarding T-cell Simpson clonality [0.021 (IQR:0.014) vs. 0.019 (IQR:0.007)], richness [8734.5 (IQR:973.3) vs. 8724 (IQR:383.7)] and T-cell fraction [0.19 (IQR:0.08) vs. 0.18 (IQR:0.08)]. HEB also exhibited a substantially elevated humoral immune response one month after the booster dose compared to HOB [median antibody titer (IQR): 10115.0 U/mL (6993.0) vs. 1781.0 U/mL (1314.0), p = 0.001]. T-cell repertoire sequencing indicated that HEB had increased SARS-CoV-2-related T-cell rearrangements, which was in accordance with higher humoral responses and possibly conferring longer protection. Data from the present study indicate that the administration of different COVID-19 vaccines as a booster may provide better protection.

An Investigation of the Immune Microenvironment and Genome during Lung Adenocarcinoma Development

Background: Adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) are two consecutive pathological processes that occur before invasive lung adenocarcinoma (LUAD). However, our understanding of the immune editing patterns during the progression of LUAD remains limited. Furthermore, we know very little about whether alterations in driver genes are involved in forming the tumor microenvironment (TME). Therefore, it is necessary to elucidate the regulatory role of TME in LUAD development from multiple dimensions, including immune cell infiltration, molecular mutation events, and oncogenic signaling pathways. Methods: We collected 145 surgically resected pulmonary nodule specimens, including 28 cases of AIS, 52 cases of MIA, and 65 cases of LUAD. Immunohistochemistry (IHC) was used to detect the expression of immune markers CD3, CD4, CD8, CD68 and programmed death ligand 1 (PD-L1). Genomic data and TMB generated by targeted next-generation sequencing (NGS). Results: LUAD exhibited higher levels of immune cell infiltration, tumor mutation burden (TMB), and activation of oncogenic pathways compared to AIS and MIA. In LUAD, compared to epidermal growth factor receptor (EGFR) single mutation and wild-type (WT) samples, cases with EGFR co-mutations showed a more pronounced rise in the CD4/CD8 ratio and CD68 infiltration. Patients with low-density lipoprotein (LDL) receptor-related protein 1B (LRP1B) mutation have higher TMB and PD-L1 expression. The transition from AIS to LUAD tends to shift the TME towards the PD-L1+CD8+ subtype (adaptive resistance). Progression-associated mutations (PAMs) were enriched in the lymphocyte differentiation pathway and related to exhausted cells' phenotype. Conclusion: Tumor-infiltrating immune cells tend to accumulate as the depth of LUAD invasion increases, but subsequently develop into an immune exhaustion and immune escape state. Mutations in EGFR and LRP1B could potentially establish an immune niche that fosters tumor growth. PAMs in LUAD may accelerate disease progression by promoting T cell differentiation into an exhausted state.

Characterization of T cell receptor repertoire in penile cancer

Tumor-infiltrating lymphocytes (TILs) play a key role in regulating the host immune response and shaping tumor microenvironment. It has been previously shown that T cell infiltration in penile tumors was associated with clinical outcomes. However, few studies have reported the T cell receptor (TCR) repertoire in patients with penile cancer. In the present study, we evaluated the TCR repertoires in tumor and adjacent normal tissues from 22 patients with penile squamous cell carcinoma (PSCC). Analysis of the T cell receptor beta-variable (TRBV) and joining (TRBJ) genes usage and analysis of complementarity determining region 3 (CDR3) length distribution did not show significant differences between tumor and matched normal tissues. Moreover, analysis of the median Jaccard index indicated a limited overlap of TCR repertoire between these groups. Compared with normal tissues, a significantly lower diversity and higher clonality of TCR repertoire was observed in tumor samples, which was associated with clinical characteristics. Further analysis of transcriptional profiles demonstrated that tumor samples with high clonality showed increased expression of genes associated with CD8 + T cells. In addition, we analyzed the TCR repertoire of CD4 + T cells and CD8 + T cells isolated from tumor tissues. We identified that expanded clonotypes were predominantly in the CD8 + T cell compartment, which presented with an exhausted phenotype. Overall, we comprehensively compared TCR repertoire between penile tumor and normal tissues and demonstrated the presence of distinct T cell immune microenvironments in patients with PSCC.

[Progress of Immunotherapy in EGFR-mutated Advanced Non-small Cell Lung Cancer]

Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) are currently the first-line standard of care for patients with non-small cell lung cancer (NSCLC) that harbor EGFR mutations. Nevertheless, resistance to EGFR-TKIs is inevitable. In recent years, although immune checkpoint inhibitors (ICIs) have significantly shifted the treatment paradigm in advanced NSCLC without driver mutation, clinical benefits of these agents are limited in patients with EGFR-mutated NSCLC. Compared with wild-type tumors, tumors with EGFR mutations show more heterogeneity in the expression level of programmed cell death ligand 1 (PD-L1), tumor mutational burden (TMB), and other tumor microenvironment (TME) characteristics. Whether ICIs are suitable for NSCLC patients with EGFR mutations is still worth exploring. In this review, we summarized the clinical data with regard to the efficacy of ICIs in patients with EGFR-mutated NSCLC and deciphered the unique TME in EGFR-mutated NSCLC.
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ATM Mutations Associate with Distinct Co-Mutational Patterns and Therapeutic Vulnerabilities in NSCLC

PURPOSE

Ataxia-telangiectasia mutated (ATM) is the most frequently mutated DNA damage repair gene in non-small cell lung cancer (NSCLC). However, the molecular correlates of ATM mutations and their clinical implications have not been fully elucidated.

EXPERIMENTAL DESIGN

Clinicopathologic and genomic data from 26,587 patients with NSCLC from MD Anderson, public databases, and a de-identified nationwide (US-based) NSCLC clinicogenomic database (CGDB) were used to assess the co-mutation landscape, protein expression, and mutational processes in ATM-mutant tumors. We used the CGDB to evaluate ATM-associated outcomes in patients treated with immune checkpoint inhibitors (ICI) with or without chemotherapy, and assessed the effect of ATM loss on STING signaling and chemotherapy sensitivity in preclinical models.

RESULTS

Nonsynonymous mutations in ATM were observed in 11.2% of samples (2,980/26,587) and were significantly associated with mutations in KRAS, but mutually exclusive with EGFR (q < 0.1). KRAS mutational status constrained the ATM co-mutation landscape, with strong mutual exclusivity with TP53 and KEAP1 within KRAS-mutated samples. Those ATM mutations that co-occurred with TP53 were more likely to be missense mutations and associate with high mutational burden, suggestive of non-functional passenger mutations. In the CGDB cohort, dysfunctional ATM mutations associated with improved OS only in patients treated with ICI-chemotherapy, and not ICI alone. In vitro analyses demonstrated enhanced upregulation of STING signaling in ATM knockout cells with the addition of chemotherapy.

CONCLUSIONS

ATM mutations define a distinct subset of NSCLC associated with KRAS mutations, increased TMB, decreased TP53 and EGFR co-occurrence, and potential increased sensitivity to ICIs in the context of DNA-damaging chemotherapy.

Radiomics-based decision support tool assists radiologists in small lung nodule classification and improves lung cancer early diagnosis

BACKGROUND

Methods to improve stratification of small (≤15 mm) lung nodules are needed. We aimed to develop a radiomics model to assist lung cancer diagnosis.

METHODS

Patients were retrospectively identified using health records from January 2007 to December 2018. The external test set was obtained from the national LIBRA study and a prospective Lung Cancer Screening programme. Radiomics features were extracted from multi-region CT segmentations using TexLab2.0. LASSO regression generated the 5-feature small nodule radiomics-predictive-vector (SN-RPV). K-means clustering was used to split patients into risk groups according to SN-RPV. Model performance was compared to 6 thoracic radiologists. SN-RPV and radiologist risk groups were combined to generate "Safety-Net" and "Early Diagnosis" decision-support tools.

RESULTS

In total, 810 patients with 990 nodules were included. The AUC for malignancy prediction was 0.85 (95% CI: 0.82-0.87), 0.78 (95% CI: 0.70-0.85) and 0.78 (95% CI: 0.59-0.92) for the training, test and external test datasets, respectively. The test set accuracy was 73% (95% CI: 65-81%) and resulted in 66.67% improvements in potentially missed [8/12] or delayed [6/9] cancers, compared to the radiologist with performance closest to the mean of six readers.

CONCLUSIONS

SN-RPV may provide net-benefit in terms of earlier cancer diagnosis.

Pathomic Features Reveal Immune and Molecular Evolution From Lung Preneoplasia to Invasive Adenocarcinoma

Recent statistics on lung cancer, including the steady decline of advanced diseases and the dramatically increasing detection of early-stage diseases and indeterminate pulmonary nodules, mark the significance of a comprehensive understanding of early lung carcinogenesis. Lung adenocarcinoma (ADC) is the most common histologic subtype of lung cancer, and atypical adenomatous hyperplasia is the only recognized preneoplasia to ADC, which may progress to adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) and eventually to invasive ADC. Although molecular evolution during early lung carcinogenesis has been explored in recent years, the progress has been significantly hindered, largely due to insufficient materials from ADC precursors. Here, we employed state-of-the-art deep learning and artificial intelligence techniques to robustly segment and recognize cells on routinely used hematoxylin and eosin histopathology images and extracted 9 biology-relevant pathomic features to decode lung preneoplasia evolution. We analyzed 3 distinct cohorts (Japan, China, and United States) covering 98 patients, 162 slides, and 669 regions of interest, including 143 normal, 129 atypical adenomatous hyperplasia, 94 AIS, 98 MIA, and 205 ADC. Extracted pathomic features revealed progressive increase of atypical epithelial cells and progressive decrease of lymphocytic cells from normal to AAH, AIS, MIA, and ADC, consistent with the results from tissue-consuming and expensive molecular/immune profiling. Furthermore, pathomics analysis manifested progressively increasing cellular intratumor heterogeneity along with the evolution from normal lung to invasive ADC. These findings demonstrated the feasibility and substantial potential of pathomics in studying lung cancer carcinogenesis directly from the low-cost routine hematoxylin and eosin staining.

Globally shared TCR repertoires within the tumor-infiltrating lymphocytes of patients with metastatic gynecologic cancer

Gynecologic cancer, including ovarian cancer and endometrial cancer, is characterized by morphological and molecular heterogeneity. Germline and somatic testing are available for patients to screen for pathogenic variants in genes such as BRCA1/2. Tissue expression levels of immunogenomic markers such as PD-L1 are also being used in clinical research. The basic therapeutic approach to gynecologic cancer combines surgery with chemotherapy. Immunotherapy, while not yet a mainstream treatment for gynecologic cancers, is advancing, with Dostarlimab recently receiving approval as a treatment for endometrial cancer. The goal remains to harness stimulated immune cells in the bloodstream to eradicate multiple metastases, a feat currently deemed challenging in a typical clinical setting. For the discovery of novel immunotherapy-based tumor targets, tumor-infiltrating lymphocytes (TILs) give a key insight on tumor-related immune activities by providing T cell receptor (TCR) sequences. Understanding the TCR repertoires of TILs in metastatic tissues and the circulation is important from an immunotherapy standpoint, as a subset of T cells in the blood have the potential to help kill tumor cells. To explore the relationship between distant tissue biopsy regions and blood circulation, we investigated the TCR beta chain (TCRβ) in bulk tumor and matched blood samples from 39 patients with gynecologic cancer. We found that the TCR clones of TILs at different tumor sites were globally shared within patients and had high overlap with the TCR clones in peripheral blood.

Spatial heterogeneity of T cell repertoire across NSCLC tumors, tumor edges, adjacent and distant lung tissues

Background

A better understanding of T cells in lung cancer and their distribution across tumor-adjacent lungs and peripheral blood is needed to improve efficacy and minimize toxicity from immunotherapy to lung cancer patients.

Methods

Here, we performed CDR3β TCR sequencing of 136 samples from 20 patients with early-stage NSCLC including peripheral blood mononuclear cells, tumors, tumor edges (<1 cm from tumor), as well as adjacent lungs 1 cm, 2 cm, 5 cm, and 10 cm away from the tumor to gain insight into the spatial heterogeneity of T cells across the lungs in patients with NSCLC. PD-L1, CD4, and CD8 expression was assessed using immunohistochemical staining, and genomic features were derived by targeted sequencing of 1,021 cancer-related genes. Multiplex immunohistochemistry against PD-1, CTLA4, LAG3, and TIM3 was performed on four patients to assess T cell exhaustion.

Results

Our study reveals a decreasing gradient in TIL Tumor Infiltrating Lymphocytes homology with tumor edge, adjacent lungs, and peripheral blood but no discernible distance-associated patterns of T cell trafficking within the adjacent lung itself. Furthermore, we show a decrease in pathogen-specific TCRs in regions with high T cell clonality and PD-L1 expression.

Conclusions

Exclusion in T exhaustion cells at play across the lungs of patients with NSCLC may potentially be the mechanism for lung cancer occurrence.

Features of the TCR repertoire associate with patients' clinical and molecular characteristics in acute myeloid leukemia

Background

Allogeneic hematopoietic stem cell transplant remains the most effective strategy for patients with high-risk acute myeloid leukemia (AML). Leukemia-specific neoantigens presented by the major histocompatibility complexes (MHCs) are recognized by the T cell receptors (TCR) triggering the graft-versus-leukemia effect. A unique TCR signature is generated by a complex V(D)J rearrangement process to form TCR capable of binding to the peptide-MHC. The generated TCR repertoire undergoes dynamic changes with disease progression and treatment.

Method

Here we applied two different computational tools (TRUST4 and MIXCR) to extract the TCR sequences from RNA-seq data from The Cancer Genome Atlas (TCGA) and examine the association between features of the TCR repertoire in adult patients with AML and their clinical and molecular characteristics.

Results

We found that only ~30% of identified TCR CDR3s were shared by the two computational tools. Yet, patterns of TCR associations with patients' clinical and molecular characteristics based on data obtained from either tool were similar. The numbers of unique TCR clones were highly correlated with patients' white blood cell counts, bone marrow blast percentage, and peripheral blood blast percentage. Multivariable regressions of TCRA and TCRB median normalized number of unique clones with mutational status of AML patients using TRUST4 showed significant association of TCRA or TCRB with WT1 mutations, WBC count, %BM blast, and sex (adjusted in TCRB model). We observed a correlation between TCRA/B number of unique clones and the expression of T cells inhibitory signal genes (TIGIT, LAG3, CTLA-4) and foxp3, but not IL2RA, CD69 and TNFRSF9 suggestive of exhausted T cell phenotypes in AML.

Conclusion

Benchmarking of computational tools is needed to increase the accuracy of the identified clones. The utilization of RNA-seq data enables identification of highly abundant TCRs and correlating these clones with patients' clinical and molecular characteristics. This study further supports the value of high-resolution TCR-Seq analyses to characterize the TCR repertoire in patients.

Complete loss of TP53 and RB1 is associated with complex genome and low immune infiltrate in pleomorphic rhabdomyosarcoma

Rhabdomyosarcoma accounts for roughly 1% of adult sarcomas, with pleomorphic rhabdomyosarcoma (PRMS) as the most common subtype. Survival outcomes remain poor for patients with PRMS, and little is known about the molecular drivers of this disease. To better characterize PRMS, we performed a broad array of genomic and immunostaining analyses on 25 patient samples. In terms of gene expression and methylation, PRMS clustered more closely with other complex karyotype sarcomas than with pediatric alveolar and embryonal rhabdomyosarcoma. Immune infiltrate levels in PRMS were among the highest observed in multiple sarcoma types and contrasted with low levels in other rhabdomyosarcoma subtypes. Lower immune infiltrate was associated with complete loss of both TP53 and RB1. This comprehensive characterization of the genetic, epigenetic, and immune landscape of PRMS provides a roadmap for improved prognostications and therapeutic exploration.

Intratumoral CD103+ CD8+ T cells predict response to neoadjuvant chemoimmunotherapy in advanced head and neck squamous cell carcinoma

BACKGROUND

Immune cell heterogenicity is known to determine the therapeutic response to cancer progression. Neoadjuvant chemoimmunotherapy (NACI) has shown clinical benefits in some patients with advanced head and neck squamous cell carcinoma (HNSCC), but the underlying mechanism behind this clinical response is unknown. The efficacy of NACI needs to be potentiated by identifying accurate biomarkers to predict clinical responses. Here, we attempted to identify molecules predicting NACI response in advanced HNSCC.

METHODS

We performed combined single-cell RNA sequencing (scRNA-seq) and multiplex immunofluorescence (mIHC) staining with tumor samples derived from NACI-treated HNSCC patients to identify a new tumor-infiltrating cell (TIL) subtype, CD103+ CD8+ TILs, associated with clinical response, while both in vitro and in vivo assays were carried out to determine its antitumor efficiency. The regulatory mechanism of the CD103+ CD8+ TILs population was examined by performing cell-cell interaction analysis of the scRNA-seq data and spatial analysis of the mIHC images.

RESULTS

We established intratumoral CD103+ CD8+ TILs density as a determinant of NACI efficacy in cancers. Our scRNA-seq results indicated that the population of CD103+ CD8+ TILs was dramatically increased in the responders of NACI-treated HNSCC patients, while mIHC analysis confirmed the correlation between intratumoral CD103+ CD8+ TILs density and NACI efficacy in HNSCC patients. Further receiver operating characteristic curve analysis defined this TIL subset as a potent marker to predict patient response to NACI. Functional assays showed that CD103+ CD8+ TILs were tumor-reactive T cells, while programmed cell death protein-1 (PD-1) blockade enhanced CD103+ CD8+ TILs cytotoxicity against tumor growth in vivo. Mechanistically, targeting the triggering receptor expressed on myeloid cells 2-positive (TREM2+ ) macrophages might enhance the population of CD103+ CD8+ TILs and facilitate antitumor immunity during NACI treatment.

CONCLUSIONS

Our study highlights the impact of intratumoral CD103+ CD8+ TILs density on NACI efficacy in different cancers, while the efforts to elevate its population warrant further clinical investigation.

Autotaxin suppresses cytotoxic T cells via LPAR5 to promote anti-PD-1 resistance in non-small cell lung cancer

Non-small cell lung cancers that harbor concurrent KRAS and TP53 (KP) mutations are immunologically warm tumors with partial responsiveness to anti-PD-(L)1 blockade; however, most patients observe little or no durable clinical benefit. To identify novel tumor-driven resistance mechanisms, we developed a panel of KP murine lung cancer models with intrinsic resistance to anti-PD-1 and queried differential gene expression between these tumors and anti-PD-1-sensitive tumors. We found that the enzyme autotaxin (ATX), and the metabolite it produces, lysophosphatidic acid (LPA), were significantly upregulated in resistant tumors and that ATX directly modulated antitumor immunity, with its expression negatively correlating with total and effector tumor-infiltrating CD8+ T cells. Pharmacological inhibition of ATX, or the downstream receptor LPAR5, in combination with anti-PD-1 was sufficient to restore the antitumor immune response and efficaciously control lung tumor growth in multiple KP tumor models. Additionally, ATX was significantly correlated with inflammatory gene signatures, including a CD8+ cytolytic score in multiple lung adenocarcinoma patient data sets, suggesting that an activated tumor-immune microenvironment upregulates ATX and thus provides an opportunity for cotargeting to prevent acquired resistance to anti-PD-1 treatment. These data reveal the ATX/LPA axis as an immunosuppressive pathway that diminishes the immune checkpoint blockade response in lung cancer.

Predicting benefit from immune checkpoint inhibitors in patients with non-small-cell lung cancer by CT-based ensemble deep learning: a retrospective study

BACKGROUND

Only around 20-30% of patients with non-small-cell lung cancer (NCSLC) have durable benefit from immune-checkpoint inhibitors. Although tissue-based biomarkers (eg, PD-L1) are limited by suboptimal performance, tissue availability, and tumour heterogeneity, radiographic images might holistically capture the underlying cancer biology. We aimed to investigate the application of deep learning on chest CT scans to derive an imaging signature of response to immune checkpoint inhibitors and evaluate its added value in the clinical context.

METHODS

In this retrospective modelling study, 976 patients with metastatic, EGFR/ALK negative NSCLC treated with immune checkpoint inhibitors at MD Anderson and Stanford were enrolled from Jan 1, 2014, to Feb 29, 2020. We built and tested an ensemble deep learning model on pretreatment CTs (Deep-CT) to predict overall survival and progression-free survival after treatment with immune checkpoint inhibitors. We also evaluated the added predictive value of the Deep-CT model in the context of existing clinicopathological and radiological metrics.

FINDINGS

Our Deep-CT model demonstrated robust stratification of patient survival of the MD Anderson testing set, which was validated in the external Stanford set. The performance of the Deep-CT model remained significant on subgroup analyses stratified by PD-L1, histology, age, sex, and race. In univariate analysis, Deep-CT outperformed the conventional risk factors, including histology, smoking status, and PD-L1 expression, and remained an independent predictor after multivariate adjustment. Integrating the Deep-CT model with conventional risk factors demonstrated significantly improved prediction performance, with overall survival C-index increases from 0·70 (clinical model) to 0·75 (composite model) during testing. On the other hand, the deep learning risk scores correlated with some radiomics features, but radiomics alone could not reach the performance level of deep learning, indicating that the deep learning model effectively captured additional imaging patterns beyond known radiomics features.

INTERPRETATION

This proof-of-concept study shows that automated profiling of radiographic scans through deep learning can provide orthogonal information independent of existing clinicopathological biomarkers, bringing the goal of precision immunotherapy for patients with NSCLC closer.

FUNDING

National Institutes of Health, Mark Foundation Damon Runyon Foundation Physician Scientist Award, MD Anderson Strategic Initiative Development Program, MD Anderson Lung Moon Shot Program, Andrea Mugnaini, and Edward L C Smith.

B4GALT1 promotes immune escape by regulating the expression of PD-L1 at multiple levels in lung adenocarcinoma

BACKGROUND

Invasive adenocarcinoma (IAC), which is typically preceded by minimally invasive adenocarcinoma (MIA), is the dominant pathological subtype of early-stage lung adenocarcinoma (LUAD). Identifying the molecular events underlying the progression from MIA to IAC may provide a crucial perspective and boost the exploration of novel strategies for early-stage LUAD diagnosis and treatment.

METHODS

Transcriptome sequencing of four pairs of MIA and IAC tumours obtained from four multiple primary lung cancer patients was performed to screen out beta-1,4-galactosyltransferase1 (B4GALT1). Function and mechanism experiments in vitro and in vivo were performed to explore the regulatory mechanism of B4GALT1-mediated immune evasion by regulating programmed cell death ligand 1 (PD-L1).

RESULTS

B4GALT1, a key gene involved in N-glycan biosynthesis, was highly expressed in IAC samples. Further experiments revealed that B4GALT1 regulated LUAD cell proliferation and invasion both in vitro and in vivo and was related to the impaired antitumour capacity of CD8 + T cells. Mechanistically, B4GALT1 directly mediates the N-linked glycosylation of PD-L1 protein, thus preventing PD-L1 degradation at the posttranscriptional level. In addition, B4GALT1 stabilized the TAZ protein via glycosylation, which activated CD274 at the transcriptional level. These factors lead to lung cancer immune escape. Importantly, inhibition of B4GALT1 increased CD8 + T-cell abundance and activity and enhanced the antitumour immunity of anti-PD-1 therapy in vivo.

CONCLUSION

B4GALT1 is a critical molecule in the development of early-stage LUAD and may be a novel target for LUAD intervention and immunotherapy.

T cell receptor and B cell receptor exhibit unique signatures in tumor and adjacent non-tumor tissues of hepatocellular carcinoma

Background

The tumor microenvironment in hepatocellular carcinoma (HCC) is complicated. Tumor-infiltrating T and B cells play a pivotal role in anti-tumor immunity. T cell receptor (TCR) and B cell receptor (BCR) features may reflect the disease-associated antigen response.

Methods

By combining bulk TCR/BCR-sequencing, RNA-sequencing, whole exome-sequencing, and human leukocyte antigen-sequencing, we examined the immune repertoire (IR) features of tumor and adjacent non-tumor tissues obtained from 64 HCC patients.

Results

High IR heterogeneity with weak similarity was discovered between tumor and non-tumor tissues. Higher BCR diversity, richness, and somatic hypermutation (SHM) were found in non-tumor tissues, while TCRα and TCRβ diversity and richness were comparable or higher in tumor. Additionally, lower immune infiltration was found in tumor than non-tumor tissues; the microenvironment in tumor appeared to keep stably inhibited and changed slightly with tumor progression. Moreover, BCR SHM was stronger, whereas TCR/BCR diversity declined with HCC progression. Importantly, we found that higher IR evenness in tumor and lower TCR richness in non-tumor tissues indicated better survival in HCC patients. Collectively, the results revealed that TCR and BCR exhibited distinct features in tumor and non-tumor tissues.

Conclusions

We demonstrated that IR features vary between different tissues of HCC. IR features may represent a biomarker for the diagnosis and treatment of HCC patients, providing references for subsequent immunotherapy research and strategy selection.

Quantitative annotations of T-Cell repertoire specificity

The specificity of a T-cell receptor (TCR) repertoire determines personalized immune capacity. Existing methods have modeled the qualitative aspects of TCR specificity, while the quantitative aspects remained unaddressed. We developed a package, TCRanno, to quantify the specificity of TCR repertoires. We created deep-learning-based, epitope-aware vector embeddings to infer individual TCR specificity. Then we aggregated clonotype frequencies of TCRs to obtain a quantitative profile of repertoire specificity at epitope, antigen and organism levels. Applying TCRanno to 4195 TCR repertoires revealed quantitative changes in repertoire specificity upon infections, autoimmunity and cancers. Specifically, TCRanno found cytomegalovirus-specific TCRs in seronegative healthy individuals, supporting the possibility of abortive infections. TCRanno discovered age-accumulated fraction of severe acute respiratory syndrome coronavirus 2 specific TCRs in pre-pandemic samples, which may explain the aggressive symptoms and age-related severity of coronavirus disease 2019. TCRanno also identified the encounter of Hepatitis B antigens as a potential trigger of systemic lupus erythematosus. TCRanno annotations showed capability in distinguishing TCR repertoires of healthy and cancers including melanoma, lung and breast cancers. TCRanno also demonstrated usefulness to single-cell TCRseq+gene expression data analyses by isolating T-cells with the specificity of interest.

Immune cellular patterns of distribution affect outcomes of patients with non-small cell lung cancer

Studying the cellular geographic distribution in non-small cell lung cancer is essential to understand the roles of cell populations in this type of tumor. In this study, we characterize the spatial cellular distribution of immune cell populations using 23 makers placed in five multiplex immunofluorescence panels and their associations with clinicopathologic variables and outcomes. Our results demonstrate two cellular distribution patterns-an unmixed pattern mostly related to immunoprotective cells and a mixed pattern mostly related to immunosuppressive cells. Distance analysis shows that T-cells expressing immune checkpoints are closer to malignant cells than other cells. Combining the cellular distribution patterns with cellular distances, we can identify four groups related to inflamed and not-inflamed tumors. Cellular distribution patterns and distance are associated with survival in univariate and multivariable analyses. Spatial distribution is a tool to better understand the tumor microenvironment, predict outcomes, and may can help select therapeutic interventions.

Molecular, metabolic and functional CD4 T cell paralysis impedes tumor control

CD4 T cells are important effectors of anti-tumor immunity, yet the regulation of CD4 tumor-specific T (T TS ) cells during cancer development is still unclear. We demonstrate that CD4 T TS cells are initially primed in the tumor draining lymph node and begin to divide following tumor initiation. Distinct from CD8 T TS cells and previously defined exhaustion programs, CD4 T TS cell proliferation is rapidly frozen in place and differentiation stunted by a functional interplay of T regulatory cells and both intrinsic and extrinsic CTLA4 signaling. Together these mechanisms paralyze CD4 T TS cell differentiation, redirecting metabolic and cytokine production circuits, and reducing CD4 T TS cell accumulation in the tumor. Paralysis is actively maintained throughout cancer progression and CD4 T TS cells rapidly resume proliferation and functional differentiation when both suppressive reactions are alleviated. Strikingly, Treg depletion alone reciprocally induced CD4 T TS cells to themselves become tumor-specific Tregs, whereas CTLA4 blockade alone failed to promote T helper differentiation. Overcoming their paralysis established long-term tumor control, demonstrating a novel immune evasion mechanism that specifically cripples CD4 T TS cells to favor tumor progression.

Antigen-specificity measurements are the key to understanding T cell responses

Antigen-specific T cells play a central role in the adaptive immune response and come in a wide range of phenotypes. T cell receptors (TCRs) mediate the antigen-specificities found in T cells. Importantly, high-throughput TCR sequencing provides a fingerprint which allows tracking of specific T cells and their clonal expansion in response to particular antigens. As a result, many studies have leveraged TCR sequencing in an attempt to elucidate the role of antigen-specific T cells in various contexts. Here, we discuss the published approaches to studying antigen-specific T cells and their specific TCR repertoire. Further, we discuss how these methods have been applied to study the TCR repertoire in various diseases in order to characterize the antigen-specific T cells involved in the immune control of disease.

Architecture of the SARS-CoV-2-specific T cell repertoire

The T cell response plays an indispensable role in the early control and successful clearance of SARS-CoV-2 infection. However, several important questions remain about the role of cellular immunity in COVID-19, including the shape and composition of disease-specific T cell repertoires across convalescent patients and vaccinated individuals, and how pre-existing T cell responses to other pathogens—in particular, common cold coronaviruses—impact susceptibility to SARS-CoV-2 infection and the subsequent course of disease. This review focuses on how the repertoire of T cell receptors (TCR) is shaped by natural infection and vaccination over time. We also summarize current knowledge regarding cross-reactive T cell responses and their protective role, and examine the implications of TCR repertoire diversity and cross-reactivity with regard to the design of vaccines that confer broader protection against SARS-CoV-2 variants.

T-Cell Receptor Repertoire Sequencing in the Era of Cancer Immunotherapy

T cells are integral components of the adaptive immune system, and their responses are mediated by unique T-cell receptors (TCR) that recognize specific antigens from a variety of biological contexts. As a result, analyzing the T-cell repertoire offers a better understanding of immune responses and of diseases like cancer. Next-generation sequencing technologies have greatly enabled the high-throughput analysis of the TCR repertoire. On the basis of our extensive experience in the field from the past decade, we provide an overview of TCR sequencing, from the initial library preparation steps to sequencing and analysis methods and finally to functional validation techniques. With regards to data analysis, we detail important TCR repertoire metrics and present several computational tools for predicting antigen specificity. Finally, we highlight important applications of TCR sequencing and repertoire analysis to understanding tumor biology and developing cancer immunotherapies.

UcTCRdb: An unconventional T cell receptor sequence database with online analysis functions

Unlike conventional major histocompatibility complex (MHC) class I and II molecules reactive T cells, the unconventional T cell subpopulations recognize various non-polymorphic antigen-presenting molecules and are typically characterized by simplified patterns of T cell receptors (TCRs), rapid effector responses and ‘public’ antigen specificities. Dissecting the recognition patterns of the non-MHC antigens by unconventional TCRs can help us further our understanding of the unconventional T cell immunity. The small size and irregularities of the released unconventional TCR sequences are far from high-quality to support systemic analysis of unconventional TCR repertoire. Here we present UcTCRdb, a database that contains 669,900 unconventional TCRs collected from 34 corresponding studies in humans, mice, and cattle. In UcTCRdb, users can interactively browse TCR features of different unconventional T cell subsets in different species, search and download sequences under different conditions. Additionally, basic and advanced online TCR analysis tools have been integrated into the database, which will facilitate the study of unconventional TCR patterns for users with different backgrounds. UcTCRdb is freely available at http://uctcrdb.cn/.

Heterogeneity of tumor immune microenvironment of EGFR/ALK-positive tumors versus EGFR/ALK-negative tumors in resected brain metastases from lung adenocarcinoma

BACKGROUND

Previous studies found that lung adenocarcinomas (LUAD) with EGFR-positive and ALK-positive were less responsive to immunotherapy, which may be associated with a suppressive tumor immune microenvironment (TIME). Given the discordance in the TIME between primary lung cancer and brain metastasis, it is urgent to explore the TIME in patients with EGFR/ALK-positive LUAD with brain metastases (BMs).

METHODS

The transcriptome feature of formalin-fixed and paraffin-embedded samples of BMs and paired primary LUAD from 70 patients with LUAD BMs was illustrated by RNA-sequencing. Six of them were available for paired sample analysis. Then, after excluding 3 co-occurring patients, we divided 67 BMs patients into 41 EGFR/ALK-positive and 26 EGFR/ALK-negative patients. The differences in immune profiling between the two groups were analyzed from three dimensions: TIME, T-cell receptor repertoire, and immunohistochemistry. Finally, the survival data of 55 patients were collected.

RESULTS

Compared with primary LUAD, BMs present an immunosuppressed TIME, manifested as: inhibition of immune-related pathways; low expression of immune checkpoint; decreased infiltration of CD8+T cells and cytotoxic lymphocyte; increased proportion of suppressive M2 macrophages. In different subgroups based on EGFR/ALK gene variation status, both EGFR-positive and ALK-positive tumors present a relatively immunosuppressive microenvironment, but the heterogeneity of tumor microenvironment may undergo different mechanisms. EGFR-positive BMs showed decreased CD8+T cells and increased regulatory T cells (Treg) cells, while ALK-positive BMs showed decreased CD8+T cells and increased M2 macrophages. Moreover, in the TCGA-LUAD cohort, EGFR-positive tumors showed reduced CD8+T cell infiltrations (p<0.001) and borderline significantly higher Tregs than EGFR/ALK-negative (p=0.072). In parallel, ALK-positive tumors had higher median M2 macrophages infiltrations than EGFR/ALK-negative (p=0.175), although there was no statistical significance. Collectively, there was a similar immunosuppressive milieu between EGFR/ALK-positive primary LUAD and BMs. Moreover, survival analysis uncovered higher CD8A expression, cytotoxic lymphocyte infiltration, and immune scores were significantly associated with better prognosis in both EGFR/ALK-positive and EGFR/ALK-negative groups.

CONCLUSION

This study found that LUAD-derived BMs exhibited an immunosuppressive TIME and revealed that EGFR-positive and ALK-positive BMs exhibited different immunosuppressive characteristics. Meanwhile, EGFR-negative BMs showed a potential benefit to immunotherapy. These findings boost molecular and clinical understanding of LUAD BMs.

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.

Peripheral T-cell receptor repertoire dynamics in small cell lung cancer

Background

Identifying a circulating biomarker predictive of immune checkpoint inhibitor (ICI) benefit in patients with small cell lung cancer (SCLC) remains an unmet need. Characteristics of peripheral and intratumoral T-cell receptor (TCR) repertoires have been shown to predict clinical outcomes in non-small cell lung cancer (NSCLC). Recognizing a knowledge gap, we sought to characterize circulating TCR repertoires and their relationship with clinical outcomes in SCLC.

Methods

SCLC patients with limited (n=4) and extensive (n=10) stage disease were prospectively enrolled for blood collection and chart review. Targeted next-generation sequencing of TCR beta and alpha chains of peripheral blood samples was performed. Unique TCR clonotypes were defined by identical CDR3, V gene, and J gene nucleotide sequences of the beta chain and subsequently used to calculate TCR diversity indices.

Results

Patients with stable versus progressive and limited versus extensive stage disease did not demonstrate significant differences in V gene usage. Kaplan-Meier curve and log-rank analysis did not identify a statistical difference in progression-free survival (PFS) (P=0.900) or overall survival (OS) (P=0.200) between high and low on-treatment TCR diversity groups, although the high diversity group exhibited a trend toward increased OS.

Conclusions

We report the second study investigating peripheral TCR repertoire diversity in SCLC. With a limited sample size, no statistically significant associations between peripheral TCR diversity and clinical outcomes were observed, though further study is warranted.

Immune repertoire and responses to neoadjuvant TCHP therapy in HER2-positive breast cancer

Background

Despite the introduction of trastuzumab, pathologic complete response (pCR) is not attained in approximately 30-40% of Human epithelial growth factor receptor-2-positive breast cancer. Tumor-infiltrating lymphocytes (TIL) have been suggested as a predictive marker of treatment response, albeit not always effective. We investigated the relationship between trastuzumab, docetaxel, carboplatin, and pertuzumab (TCHP) treatment and immune repertoire as a treatment response predictor.

Design

In all, 35 cases were divided into two experimental groups: 10 and 25 cases in the preliminary and main experiments, respectively. In the preliminary experiment, the biopsy tissues before TCHP treatment and the surgical tissues after TCHP treatment were compared. In the main experiment, the biopsy tissues before TCHP treatment were compared according to the TCHP treatment response.

Methods

The T-cell repertoire for TRA, TRB, TRG, and TRD, and B-cell repertoire for immunoglobulin heavy, immunoglobulin kappa, and immunoglobulin lambda were evaluated. Whole transcriptome sequencing was also performed.

Results

In the preliminary experiment, the density and richness of the T-cell receptor (TCR) and B-cell receptor (BCR) repertoires decreased after treatment, regardless of TCHP response. In the main experiment, the Shannon's entropy index, density, and length of CDR3 of the TCR and BCR repertoires did not differ significantly in patients who did and did not achieve pCR. The pCR and non-pCR subgroups according to the level of TILs revealed that the non-pCR/lowTIL group had a higher proportion of low-frequency clones than the pCR/lowTIL group in TRA (non-pCR/lowTIL versus pCR/lowTIL, 0.01-0.1%, 63% versus 45.3%; <0.01%, 32.9% versus 51.8%, p < 0.001) and TRB (non-pCR/lowTIL versus pCR/lowTIL, 0.01-0.1%, 26.5% versus 14.7%; <0.01%, 72.0% versus 84.1%, p < 0.001).

Conclusions

The role of the diversity, richness, and density of the TCR and BCR repertoires as predictive markers for TCHP response was not identified. Compositions of low-frequency clones could be candidates for predictive factors of TCHP response; however, validation studies and further research are necessary.

Biomarkers of response to immunotherapy in early stage non-small cell lung cancer

Immunotherapy with immune-checkpoint inhibitors (ICIs) targeting programmed cell death 1 or programmed death-ligand 1 has revolutionised the treatment of advanced non-small cell lung cancer (NSCLC) and has been investigated in early NSCLC, alone or in combination with chemotherapy, anti-CTLA-4 antibodies and radiotherapy. Although more mature data are needed before setting a change of paradigm in early stages, reports of pathological response rates and disease-free survival are promising, especially with neoadjuvant multimodality approaches. Nevertheless, major pathological response rates for neoadjuvant anti-PD-(L)1 monotherapy rarely exceed 40%, and biomarkers for characterising patients who may benefit the most from ICIs are lacking. These biomarkers have a distinct value from the metastatic setting, with highly different tumour biologies. Among the most investigated so far in this context, programmed death-ligand 1 expression and, to a lesser extent, tumour mutational burden seem to correlate better with higher pathological response rates and survival. Epidermal growth factor receptor, Serine/Threonine Kinase 11and Kelch-like ECH-associated protein 1 mutations rise as essential determinations for the treatment selection in early-stage NSCLC. Emerging and promising approaches comprise evaluation of blood-based ratios, microbiota, and baseline intratumoural TCR clonality. Circulating tumour DNA will be of great help in the near future when selecting best candidates for adjuvant ICIs, monitoring the tumour response to the neoadjuvant treatment in order to improve the rates of complete resections in the early stage.

Evolving Treatment Landscape of HER2-mutant Non-Small Cell Lung Cancer: Trastuzumab Deruxtecan and Beyond

Successful targeting of HER2-activating mutations in DESTINY-Lung02 phase II study has led to the approval of the antibody-drug conjugate (ADC) trastuzumab deruxtecan (T-DXd) as second-line treatment in patients with non-small cell lung cancer (NSCLC). Despite the impressive results, several matters need to be addressed, including the clinical activity of T-DXd in patients with disease in the central nervous system as well as the role of T-DXd in the context of HER2 overexpression. Additionally, data regarding novel agents used to target HER2 continue to accumulate. This review highlights the challenges and unanswered questions that have emerged after the approval of T-DXd in patients with HER2-mutant NSCLC.

Progress on neoadjuvant immunotherapy in resectable non-small cell lung cancer and potential biomarkers

Immune checkpoint inhibitors (ICIs) are highly concerned in the treatment of non-small cell lung cancer (NSCLC), represented by inhibitors of programmed death protein 1 (PD-1) and its ligand (PD-L1), and inhibitors of cytotoxic T lymphocyte-associated antigen-4 (CTLA-4). The introduction of immunotherapy in the treatment of perioperative NSCLC has improved the prognosis to a great extent, as demonstrated by several phase II and III clinical trials. The target population for immunotherapy in early-stage NSCLC is still under discussion, and the biomarkers for neoadjuvant immunotherapy population selection are the next pending problem. The predictive efficacy of many potential makers is still being explored, including PD-L1 expression levels, tumor mutation burden, circulating tumor DNA, components of the tumor microenvironment, and several clinical factors. We summarize key findings on the utility of ICIs in clinical trials of preoperative NSCLC patients and conclude analyses of relevant biomarkers to provide a better understanding of potentially predictive biomarkers in neoadjuvant immunotherapy.

Analysis of Immune Intratumor Heterogeneity Highlights Immunoregulatory and Coinhibitory Lymphocytes as Hallmarks of Recurrence in Stage I Non-Small Cell Lung Cancer

Our understanding of the molecular mechanisms underlying postsurgical recurrence of non-small cell lung cancer (NSCLC) is rudimentary. Molecular and T cell repertoire intratumor heterogeneity (ITH) have been reported to be associated with postsurgical relapse; however, how ITH at the cellular level impacts survival is largely unknown. Here we report the analysis of 2880 multispectral images representing 14.2% to 27% of tumor areas from 33 patients with stage I NSCLC, including 17 cases (relapsed within 3 years after surgery) and 16 controls (without recurrence ≥5 years after surgery) using multiplex immunofluorescence. Spatial analysis was conducted to quantify the minimum distance between different cell types and immune cell infiltration around malignant cells. Immune ITH was defined as the variance of immune cells from 3 intratumor regions. We found that tumors from patients having relapsed display different immune biology compared with nonrecurrent tumors, with a higher percentage of tumor cells and macrophages expressing PD-L1 (P =.031 and P =.024, respectively), along with an increase in regulatory T cells (Treg) (P =.018), antigen-experienced T cells (P =.025), and effector-memory T cells (P =.041). Spatial analysis revealed that a higher level of infiltration of PD-L1+ macrophages (CD68+PD-L1+) or antigen-experienced cytotoxic T cells (CD3+CD8+PD-1+) in the tumor was associated with poor overall survival (P =.021 and P =.006, respectively). A higher degree of Treg ITH was associated with inferior recurrence-free survival regardless of tumor mutational burden (P =.022), neoantigen burden (P =.021), genomic ITH (P =.012) and T cell repertoire ITH (P =.001). Using multiregion multiplex immunofluorescence, we characterized ITH at the immune cell level along with whole exome and T cell repertoire sequencing from the same tumor regions. This approach highlights the role of immunoregulatory and coinhibitory signals as well as their spatial distribution and ITH that define the hallmarks of tumor relapse of stage I NSCLC.

T cell receptor repertoire sequencing reveals chemotherapy-driven clonal expansion in colorectal liver metastases

BACKGROUND

Colorectal liver metastasis (CLM) is a leading cause of colorectal cancer mortality, and the response to immune checkpoint inhibition (ICI) in microsatellite-stable CRC has been disappointing. Administration of cytotoxic chemotherapy may cause increased density of tumor-infiltrating T cells, which has been associated with improved response to ICI. This study aimed to quantify and characterize T-cell infiltration in CLM using T-cell receptor (TCR) repertoire sequencing. Eighty-five resected CLMs from patients included in the Oslo CoMet study were subjected to TCR repertoire sequencing. Thirty-five and 15 patients had received neoadjuvant chemotherapy (NACT) within a short or long interval, respectively, prior to resection, while 35 patients had not been exposed to NACT. T-cell fractions were calculated, repertoire clonality was analyzed based on Hill evenness curves, and TCR sequence convergence was assessed using network analysis.

RESULTS

Increased T-cell fractions (10.6% vs. 6.3%) were detected in CLMs exposed to NACT within a short interval prior to resection, while modestly increased clonality was observed in NACT-exposed tumors independently of the timing of NACT administration and surgery. While private clones made up >90% of detected clones, network connectivity analysis revealed that public clones contributed the majority of TCR sequence convergence.

CONCLUSIONS

TCR repertoire sequencing can be used to quantify T-cell infiltration and clonality in clinical samples. This study provides evidence to support chemotherapy-driven T-cell clonal expansion in CLM in a clinical context.

Network Pharmacology and Molecular Docking Analysis on Molecular Targets and Mechanisms of Aidi Injection Treating of Nonsmall Cell Lung Cancer

Background. Aidi injection (ADI) is a compound preparation injection of Chinese herbs used to treat patients of nonsmall cell lung cancer (NSCLC) in China. This study aimed to reveal the mechanism of ADI in the treatment of NSCLC by using network pharmacology and molecular docking. Methods. The related targets of ADI and NSCLC were obtained from multiple databases. The network diagram of disease-drug-components-targets (DDCT) and protein-protein interaction (PPI) was constructed to screen key targets. Then, the key targets and main signaling pathways were screened by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Next, in order to validate the results of network pharmacology, expression analysis and survival analysis of key genes were performed. Finally, we carried out the technology of molecular docking to further validate the accuracy of the above results. Results. A total of 207 targets of ADI and 5282 targets of NSCLC were obtained finally. Through the construction of DDCT and PPI network diagrams, 28 key targets were finally obtained. The results of the KEGG enrichment analysis indicated that multiple signaling pathways were associated with NSCLC, which included the MAPK signaling pathway, the IL-17 signaling pathway, and the PI3K/AKT signaling pathway. The key genes in the signaling pathway mainly include TP53, CASP3, MMP9, AKT1, PTGS2, and MAPK1. The results of differently expressed analysis of key genes showed that TP53, CASP3, MMP9, AKT1, PTGS2, and MAPK1 had statistical differences in lung squamous cell carcinoma (LUSC) compared with normal tissue $\left(p<0.001\right)$ . In lung adenocarcinoma (LUAD), the expression of TP53, CASP3, MMP9, AKT1, and PTGS2 had statistical differences compared with normal tissue $\left(p<0.001\right)$ , while the expression of MAPK1 had no statistical difference $\left(p>0.05\right)$ . The results of survival analysis of key genes showed that AKT1, MAPK1, CASP3, MMP9, TP53, and PTGS2 had statistical differences in the OS or RFS of NSCLC patients $\left(p<0.05\right)$ . In addition, the results of molecular docking indicated that the key genes and the main components have good docking activity. Conclusions. This study revealed the potential mechanism of ADI in the treatment of NSCLC with multipathways and multitargets and provided a scientific basis for the in-depth study of ADI in the treatment of NSCLC.

Immunogenomic intertumor heterogeneity across primary and metastatic sites in a patient with lung adenocarcinoma

Background

Lung cancer is the leading cause of cancer death, partially owing to its extensive heterogeneity. The analysis of intertumor heterogeneity has been limited by an inability to concurrently obtain tissue from synchronous metastases unaltered by multiple prior lines of therapy.

Methods

In order to study the relationship between genomic, epigenomic and T cell repertoire heterogeneity in a rare autopsy case from a 32-year-old female never-smoker with left lung primary late-stage lung adenocarcinoma (LUAD), we did whole-exome sequencing (WES), DNA methylation and T cell receptor (TCR) sequencing to characterize the immunogenomic landscape of one primary and 19 synchronous metastatic tumors.

Results

We observed heterogeneous mutation, methylation, and T cell patterns across distinct metastases. Only TP53 mutation was detected in all tumors suggesting an early event while other cancer gene mutations were later events which may have followed subclonal diversification. A set of prevalent T cell clonotypes were completely excluded from left-side thoracic tumors indicating distinct T cell repertoire profiles between left-side and non left-side thoracic tumors. Though a limited number of predicted neoantigens were shared, these were associated with homology of the T cell repertoire across metastases. Lastly, ratio of methylated neoantigen coding mutations was negatively associated with T-cell density, richness and clonality, suggesting neoantigen methylation may partially drive immunosuppression.

Conclusions

Our study demonstrates heterogeneous genomic and T cell profiles across synchronous metastases and how restriction of unique T cell clonotypes within an individual may differentially shape the genomic and epigenomic landscapes of synchronous lung metastases.

An EGFR L858R mutation identified in 1862 Chinese NSCLC patients can be a promising neoantigen vaccine therapeutic strategy

Background

This study aimed to develop a vaccine that targets mutation-derived neoantigen in Chinese non-small-cell lung cancer (NSCLC).

Methods

A cohort of 1862 Chinese NSCLC patients who underwent targeted sequencing with a 1021-gene panel was investigated. HLA typing was done using OptiType v1.0 and neoantigens were predicted by netMHCpan v4.0. HLA LOH was inferred using the lohhla algorithm and TMB were quantified by counting the total number of non-synonymous ones based on our panel data. CIBERSORT was utilized to estimate the TME in different EGFR mutant subtype by using TCGA data.

Results

HLA-A*11:01(42.59%) was the top one allele and HLA-A*33:03(12.94%) ranked 12th. EGFR L858R (22.61%) was the most prevalent gene variant. The binding affinity (IC50 MT = 22.9 nM) and shared frequency (2.93%) of EGFR L858R in combination with HLA-A*33:03 were optimal. In a subsequent further analysis on immunological features of EGFR mutant subtypes, 63.1% HLA loss of heterozygosity LOH (HLA LOH) and 0.37% (7 of 1862) B2M aberrations were found in our population, both had no significant association with EGFR mutant subtypes suggesting that the process of antigen presentation involved HLA LOH and B2M mechanisms in EGFR L858R is working. Tumor mutation burden (TMB) was investigated by utilizing our panel and showed that EGFR L858R had the lowest TMB compared with other EGFR mutant subtypes. In addition, analysis of 22 immune cell types from The Cancer Genome Atlas (TCGA) data showed EGFR L858R was correlated with low level of CD8 T cells, activated CD4 memory T cells and elevated level of macrophage M2 suggesting an inhibited tumor microenvironment (TME).

Conclusion

Our study identified that EGFR L858R neoantigen had the potential to generate cancer vaccines in NSCLC patients with HLA A*33:03. The neoantigen-based vaccines may become an effective salvage regimen for EGFR L858R subgroup after targeted therapy or immune checkpoint inhibitors (ICIs) failure.

T cell receptor convergence is an indicator of antigen-specific T cell response in cancer immunotherapies

T cells are potent at eliminating pathogens and playing a crucial role in the adaptive immune response. T cell receptor (TCR) convergence describes T cells that share identical TCRs with the same amino acid sequences but have different DNA sequences due to codon degeneracy. We conducted a systematic investigation of TCR convergence using single-cell immune profiling and bulk TCRβ-sequence (TCR-seq) data obtained from both mouse and human samples and uncovered a strong link between antigen-specificity and convergence. This association was stronger than T cell expansion, a putative indicator of antigen-specific T cells. By using flow-sorted tetramer+ single T cell data, we discovered that convergent T cells were enriched for a neoantigen-specific CD8+ effector phenotype in the tumor microenvironment. Moreover, TCR convergence demonstrated better prediction accuracy for immunotherapy response than the existing TCR repertoire indexes. In conclusion, convergent T cells are likely to be antigen-specific and might be a novel prognostic biomarker for anti-cancer immunotherapy.