Progress of immunotherapy-related biomarkers for small cell lung cancer

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Research progress of immunotherapy-related biomarkers for small cell lung cancer

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Research progress of immunotherapy-related biomarkers for small cell lung cancer.

[Abstract]  

In the past 30 years, there has been no significant breakthrough in the treatment of small cell lung cancer (SCLC), and the overall prognosis has not been significantly improved. With the opening of the immunotherapy era, immune checkpoint inhibitors have made significant progress in the treatment of SCLC, but the overall benefits are still limited.

How to screen the beneficiaries to further improve the effect of immunotherapy is one of the current hot issues in SCLC research. Through an overview of the current situation of SCLC, focusing on the relevant biomarkers of SCLC immunotherapy, the current status and progress of the research on markers of SCLC immunotherapy in recent years are reviewed, in order to provide clues and ideas for optimizing immunotherapy strategies in the future.

［Key words］Small cell lung cancer; Immunotherapy; Biomarkers

Small cell lung cancer (SCLC) is a highly malignant neuroendocrine tumor, accounting for about 15% of all lung cancers [1]. According to the staging standards of the American Veterans Hospital, SCLC can be divided into limited period and extensive period. Most patients are already in the extensive period when they are first diagnosed, with limited treatment options, and the 5-year survival rate is less than 2% [2].

Etoposide combined with platinum drugs has been the first-line standard treatment for extensive-stage small cell lung cancer (ES-SCLC) for more than 30 years [3]. In recent years, the development of immune checkpoint inhibitor (ICI) has improved the survival of SCLC patients.

However, only a part of SCLC patients can benefit from immunotherapy for a long time.Finding suitable immunological biomarkers to guide the clinical practice of immunotherapy is the key to further improving the survival benefits of SCLC patients.

1. Biological characteristics of SCLC

Understanding the biological characteristics of SCLC can help us better find effective biomarkers. The evolution of SCLC subtypes and tumor immune microenvironment (TIME) have been the focus of research on the biological characteristics of SCLC in recent years.

1.1 The evolution of tumor subtypes

SCLC is a highly heterogeneous tumor. How to better define SCLC subtypes has always been one of the research hotspots. In 1985, Carney et al. [4] conducted a preliminary exploration of SCLC heterogeneity, which was based on levodopa decarboxylase, bombesin-like immunoreactivity, neuron-specific enolase and creatine kinase brain isoenzyme Different SCLC cell lines are divided into two categories: classic type and variant type.

Some studies [5-6] According to the SCLC in the SCLC achaete-scute complex-like 1 (achaete-scute complex-like 1, ASCL1), neurogenic differentiation factor 1 (neurogenic differentiation factor 1, NEUROD1), transcription co-activation The difference in expression of factor 1 (Yes-associated protein 1, YAP1) and level 2 POU domain transcription factor 3 (POU domain, class 2, transcription factor 3, POU2F3) divides SCLC into SCLC-A, SCLC-N, SCLC- There are four subtypes of Y and SCLC-P. The biological characteristics and sensitivity of different subtypes of SCLC are different. SCLC-Y is the subtype with potential immune benefit.

However, further research [7] found that YAP1 is also expressed in SCLC-P, so YAP1 as a marker for SCLC subtype classification is controversial. Recently, Gay et al. [8] used tumor gene expression data analysis and non-negative matrix factorization on 81 cases of SCLC patients’ surgical resection specimens to redefine the SCLC classification, and used SCLC-A, SCLC-N, SCLC-P On the basis of this, a subtype of high expression antigen presentation-related genes and T cell inflammatory gene expression profile (gene expression profile, GEP)—SCLC-I was proposed.

Compared with SCLC-Y, SCLC-I more accurately defines the characteristics of potential immune benefit subtypes, which provides the possibility for the screening of patients with SCLC immune benefit in the later stage.

1.2　TIME

TIME is an important place for tumor growth and metastasis, as well as a key mediator for the interaction between immune cells and tumors. Inhibitory TIME may be an important reason why SCLC immunotherapy does not benefit. Research [9-10] found that SCLC can promote tumor immune escape by down-regulating the expression of major histocompatibility complex (MHC) and up-regulating the expression of poliovirus receptors and CD47. Other molecules such as the upregulation of CD39, the increase of macrophage stimulating protein expression, the overexpression of transmembrane protein 1 induced by interferon, etc. are also involved in the formation of inhibitory TIME [11-13].

In terms of immune cell infiltration, a study of 104 cases of SCLC tumor tissue T cell infiltration [14] found that FOXP3 + T cells accounted for 72.1%, while CD8 + T cells accounted for only 12.5%. Carvajal-Hausdorf et al. [15] found that the absolute value of CD8+ T cells in lung adenocarcinoma was 5.4 times higher than that in SCLC, and that in lung squamous cell carcinoma was 6.0 times higher than that in SCLC.

In addition, studies [16] found that SCLC circulating tumor cells derived from ES-SCLC patients can accumulate tumor-associated macrophages (tumor-associated macrophage, TAM) by secreting a variety of cytokines. Bone marrow-derived suppressor cells (myeloid-derived suppressor cells, MDSC) are also one of the suppressive immune cells in the SCLC microenvironment.

MDSC can induce the aggregation of regulatory T cells (Treg) and promote the formation of suppressive TIME [17 ]. Based on the role of MDSC in SCLC, Iclozan et al. [18] found that the combination of MDSC inhibitor all-trans retinoic acid and p53 vaccine can increase the response of SCLC to immune vaccines, suggesting that elimination of MDSC can enhance the response of SCLC to immunotherapy.

2.  SCLC immunotherapy-related biomarkers

2.1 　 Immunotherapy-related biomarkers in clinical research

2.1.1 “Programmed death ligand-1 (PD-L1)

PD-L1 is one of tumor cell surface molecules, and it has been widely used in a variety of solid tumors including non-small cell lung cancer (NSCLC) as a biomarker for immunotherapy. With the development of SCLC immunotherapy research, the feasibility of PD-L1 as a marker of SCLC efficacy has also received attention.

The 2020 European Society for Medical Oncology (ESMO) meeting reported on the characteristics of SCLC long-term survivors in the IMpower133 study, and found that PD-L1 expression levels were not significantly correlated with long-term survival benefits of immunotherapy [19]. The conclusions obtained from the KEYNOTE-604 study and the CASPIAN study are similar [20-21].

In addition, the IFCT-1603 study [22] found that out of 54 SCLC tumor specimens that can detect PD-L1, only 1 tumor specimen was PD-L1 positive, and the progression-free survival of patients with PD-L1 positive and negative tumors (progression) -Free survival (PFS) and overall survival (OS) are not statistically different, but due to the large difference in sample size between the two groups in this study, the conclusions need to be treated with caution.

In fact, due to the low level of PD-L1 expression in tumor cells, the results of existing clinical trials do not yet support the use of PD-L1 expression as a marker for the efficacy of SCLC immunity.

2.1.2　TMB

SCLC is a tumor with extensive gene loss and mutation. The loss of tumor suppressor genes TP53, Rb1, PTEN, etc., the overexpression of PIK3CA, EGFR, etc., and the expansion of FGFR1, SOX2, and MYC families lead to the high tumor mutation burden of SCLC ( tumor mutational burden, TMB) [23]. The TMB of SCLC is about 7.4 mut/Mb, which is similar to NSCLC. In theory, high TMB can induce a strong T cell response, which may bring the benefit of SCLC immunotherapy [24].

Researchers have explored the feasibility of TMB as a marker of immune efficacy in a variety of solid tumors, including SCLC. In a study exploring the relationship between TMB and ICI efficacy in SCLC [25], it was found that the median PFS and median OS in the high TMB group were lower and the TMB group was significantly prolonged. In the CheckMate 032 trial, TMB was divided in more detail.

The researchers divided patients into low, medium, and high groups with 143 mut/Mb and 247 mut/Mb as the boundaries. The results showed that whether it was a single drug or a combination drug , The objective remission rate, 1-year PFS rate and 1-year OS rate in the high TMB group were significantly prolonged [26].

Although the thresholds of TMB in the above studies are different, the results of the study show that patients with high TMB have the advantage of immunotherapy benefit. It is worth noting that in the IMpower133 study [27], researchers explored the predictive efficacy of blood TMB (blood TMB, bTMB) as a marker of immune efficacy, and found that bTMB has nothing to do with immune efficacy. Therefore, further research based on TMB still needs to be carried out.

2.1.3　GEP

GEP is a gene expression profile related to antigen presentation, chemokine expression, etc., which can more comprehensively describe the characteristics of the tumor microenvironment from the genetic level [28].

KEYNOTE-028 is a study exploring the safety and effectiveness of pembrolizumab in the treatment of PD-L1 positive tumors [29]. The study included 24 patients with SCLC. The relationship between GEP and clinical efficacy is one of the exploratory endpoints. , The results found that patients with high GEP have a good prognosis, and the combination of TMB and GEP or PD-L1 has better predictive power. However, it is worth noting that the study included fewer SCLC patients, which may lead to bias. At the same time, whether the conclusions drawn for pan-tumor species can be directly applied to SCLC still needs further exploration.

2.2 　Immunotherapy-related biomarkers worth exploring

2.2.1　CD47

CD47 is a transmembrane protein widely expressed on the cell surface, which is mainly composed of an N-terminal extracellular variable region, 5 hydrophobic transmembrane structures, and a C-terminal intracellular signal sequence. Signal regulatory protein α (SIRPα) is an inhibitory receptor on the surface of macrophages and MDSCs. The binding of CD47 to SIRPα causes the phosphorylation of intracellular tyrosine inhibitory motifs and inhibits the phagocytic function of macrophages. [30].

Weiskopf et al. [10] confirmed through cell experiments and animal models that blocking CD47 can promote the phagocytosis of SCLC by macrophages, confirming the potential role of CD47 as a SCLC therapeutic target. A clinical retrospective study [31] used CD47 expression as a grouping basis to explore the OS of different subgroups of patients, and found that CD47-positive patients had a better prognosis. Immunotherapy with CD47 as a checkpoint is emerging. CD47 as a therapeutic target and immune efficacy marker is a topic worthy of in-depth study in the future.

2.2.2　DLL3

δ-like ligand 3 (δ-like ligand 3, DLL3) is an inhibitory ligand of the Notch signal transduction pathway, which is expressed in large quantities in SCLC, mainly SCLC-A and SCLC-N subtypes [7].

With the analysis of the target function of DLL3, many new drugs targeting DLL3, such as AMG 757 and AMG 119, are under continuous development. AMG 757 is a bispecific antibody targeting DLL3 developed based on the bispecific T cell adapter system. Giffin et al. [32] used SCLC patient-derived xenograft models and cell line xenograft models to verify the specific killing of tumor cells expressing DLL3 by the antibody. The 2020 World Conference on Lung Cancer announced the preliminary data of the ongoing phase I clinical trial of AMG 757. 10 mg of AMG 757 has acceptable adverse reactions and shows good anti-tumor activity. Dose escalation trials are underway [33] . AMG 119 is a chimeric antigen receptor T-cell immunotherapy targeting DLL3. Clinical trials are ongoing and no data has been released yet. The above development of immunotherapy against DLL3 provides clues for future exploration of DLL3 as an immunotherapy marker.

2.2.3 　 Multiple marker combinations

The highly heterogeneous characteristics of SCLC may limit the accuracy of a single biomarker for screening immunotherapy-benefiting populations. In contrast, a combination of multiple indicators can provide more potential for the detection of potential immune-benefiting subgroups. Targeted information.

Chen et al. [34] analyzed the surgical resection specimens of 102 patients with SCLC by immunohistochemistry, and established an immune risk assessment model for SCLC based on the expression of Gal-9 on infiltrating lymphocytes, and verified the model. The multi-marker combination has higher predictive performance than a single marker. The development of a combined detection platform for multiple biomarkers is one of the future research directions for SCLC markers.

3. Summary and outlook

In recent years, the rapid development of bioinformatics technology, the popularization of sequencing technology and the development of spatial transcriptomics make it possible to fully explore the biological characteristics of SCLC.

However, due to the high heterogeneity of SCLC tumors and difficulty in obtaining materials, the current progress in the research of SCLC biomarkers is relatively slow, and the predictive efficacy of some effective markers in NSCLC for the efficacy of SCLC immunity has not reached expectations.

Figure 1 starts from the SCLC immunotherapy biomarkers, combined with the characteristics of SCLC, summarizes the promising markers. Researchers have never stopped further exploration of SCLC. A more comprehensive understanding of the characteristics of SCLC and accurate definition of SCLC subtypes to discover clinically valuable curative effect predictors will be one of the future development directions of the SCLC field.

Figure 1 　 Overview of research on biomarkers related to SCLC immunotherapy

Fig. 1 Overview of immune biomarkers for SCLC

MDSC: Myeloid-derived suppressor cells; NK: Natural killer; DLL3: δ-like ligand 3; YAP1: Yes-associated protein 1; CSF1: Colony-stimulating factor 1; CSF1R: Colony-stimulating factor 1 receptor; SIRPα: signal- regulatory protein α; CTLA-4: Cytolytic T lymphocyte-associated antigen-4; PD-L1: Programmed death ligand-1; TIM3: T-cell immunoglobulin and mucin domain 3; LAG3: Lymphocyte-activation gene 3

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