Intratumoral versus Circulating Lymphoid Cells as Predictive Biomarkers in Lung Cancer Patients Treated with Immune Checkpoint Inhibitors: Is the Easiest Path the Best One?

Gascón, Marta; Isla, Dolores; Cruellas, Mara; Gálvez, Eva M.; Lastra, Rodrigo Pimienta; Ocáriz, Maitane; Paño, José Ramón; Ramírez, Ariel; Sesma, Andrea; Torres-Ramón, Irene; Yubero, A.; Pardo, Julián; Martínez-Lostao, Luis

doi:10.3390/cells9061525

Cited by 14 publications

(15 citation statements)

References 89 publications

(114 reference statements)

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“…However, ICI treatments are only effective in approximately 20% to 30% of cancer patients whose tumors are generally hot tumors with a high degree of T cell infiltration and high immune checkpoint expression ( 3 ). The majority of patients have no response or are resistant to the treatment, which is largely associated with cold tumors with few or absence of T cells, low tumor mutational burden, and poor antigen presentation ( 3 ). Furthermore, the efficacy varies among different tumor types, which further complicates treatment strategy.…”

Section: Introductionmentioning

confidence: 99%

FDA-Approved and Emerging Next Generation Predictive Biomarkers for Immune Checkpoint Inhibitors in Cancer Patients

et al. 2021

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A patient’s response to immune checkpoint inhibitors (ICIs) is a complex quantitative trait, and determined by multiple intrinsic and extrinsic factors. Three currently FDA-approved predictive biomarkers (progra1mmed cell death ligand-1 (PD-L1); microsatellite instability (MSI); tumor mutational burden (TMB)) are routinely used for patient selection for ICI response in clinical practice. Although clinical utility of these biomarkers has been demonstrated in ample clinical trials, many variables involved in using these biomarkers have poised serious challenges in daily practice. Furthermore, the predicted responders by these three biomarkers only have a small percentage of overlap, suggesting that each biomarker captures different contributing factors to ICI response. Optimized use of currently FDA-approved biomarkers and development of a new generation of predictive biomarkers are urgently needed. In this review, we will first discuss three widely used FDA-approved predictive biomarkers and their optimal use. Secondly, we will review four novel gene signature biomarkers: T-cell inflamed gene expression profile (GEP), T-cell dysfunction and exclusion gene signature (TIDE), melanocytic plasticity signature (MPS) and B-cell focused gene signature. The GEP and TIDE have shown better predictive performance than PD-L1, and PD-L1 or TMB, respectively. The MPS is superior to PD-L1, TMB, and TIDE. The B-cell focused gene signature represents a previously unexplored predictive biomarker to ICI response. Thirdly, we will highlight two combined predictive biomarkers: TMB+GEP and MPS+TIDE. These integrated biomarkers showed improved predictive outcomes compared to a single predictor. Finally, we will present a potential nucleic acid biomarker signature, allowing DNA and RNA biomarkers to be analyzed in one assay. This comprehensive signature could represent a future direction of developing robust predictive biomarkers, particularly for the cold tumors, for ICI response.

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Section: Introductionmentioning

confidence: 99%

FDA-Approved and Emerging Next Generation Predictive Biomarkers for Immune Checkpoint Inhibitors in Cancer Patients

et al. 2021

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“…Tumor-immune relationship plays an important role in tumor development and tumor progression, and tumor immune microenvironment (TIM) is widely accepted as a significant factor influencing therapeutic efficiency of ICB therapy (Song et al, 2020;Wang et al, 2020). Specifically, tumorinfiltrating lymphocytes (TILs) score (Gascón et al, 2020;Hashemi et al, 2021) and PD-L1 status (Wu et al, 2020) were previously suggested as potential biomarkers to be applied in clinical practice for LUAD. However, its translation from bench to bedside is largely limited by the dependence on tissue sample availability and the nonstandardization for evaluation of TIL score and PD-L1 expression.…”

Section: Discussionmentioning

confidence: 99%

“…Screening for potentially responsive LUAD patients to ICB therapy before treatment by using an effective immunoligical biomarker is beneficial to remarkably improve the outcome of LUAD patients with ICB therapy (Wu et al, 2020). Tumor-infiltrating lymphocyte (TIL) score and PD-L1 expression in TME are previously suggested as potential biomarkers to select potentially sensitive subpopulation to ICB therapy prior to treatment and to predict survival for LUAD patients (Gascón et al, 2020;Jin et al, 2020;Hashemi et al, 2021). However, evaluations for the status of TIL and PD-L1 are currently non-standardized and limited by tissue samples availability.…”

Section: Introductionmentioning

confidence: 99%

The Predictive Role of Immune Related Subgroup Classification in Immune Checkpoint Blockade Therapy for Lung Adenocarcinoma

Wang

Chen

et al. 2021

Front. Genet.

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Background: In lung adenocarcinoma (LUAD), the predictive role of immune-related subgroup classification in immune checkpoint blockade (ICB) therapy remains largely incomplete.Methods: Transcriptomics analysis was performed to evaluate the association between immune landscape and ICB therapy in lung adenocarcinoma and the associated underlying mechanism. First, the least absolute shrinkage and selection operator (LASSO) algorithm and K-means algorithm were used to identify immune related subgroups for LUAD cohort from the Cancer Genome Atlas (TCGA) database (n = 572). Second, the immune associated signatures of the identified subgroups were characterized by evaluating the status of immune checkpoint associated genes and the immune cell infiltration. Then, potential responses to ICB therapy based on the aforementioned immune related subgroup classification were evaluated via tumor immune dysfunction and exclusion (TIDE) algorithm analysis, and survival analysis and further Cox proportional hazards regression analysis were also performed for LUAD. In the end, gene set enrichment analysis (GSEA) was performed to explore the metabolic mechanism potentially responsible for immune related subgroup clustering. Additionally, two LUAD cohorts from the Gene Expression Omnibus (GEO) database were used as validation cohort.Results: A total of three immune related subgroups with different immune-associated signatures were identified for LUAD. Among them, subgroup 1 with higher infiltration scores for effector immune cells and immune checkpoint associated genes exhibited a potential response to IBC therapy and a better survival, whereas subgroup 3 with lower scores for immune checkpoint associated genes but higher infiltration scores for suppressive immune cells tended to be insensitive to ICB therapy and have an unfavorable prognosis. GSEA revealed that the status of glucometabolic reprogramming in LUAD was potentially responsible for the immune-related subgroup classification.Conclusion: In summary, immune related subgroup clustering based on distinct immune associated signatures will enable us to screen potentially responsive LUAD patients for ICB therapy before treatment, and the discovery of metabolism associated mechanism is beneficial to comprehensive therapeutic strategies making involving ICB therapy in combination with metabolism intervention for LUAD.

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“…It is known that CD4 + T-cells mediate systemic immunity, which is important for long-term tumor elimination ( Wang et al, 2018 ). CD8 + T-cells have the potential not only to recognize, but also to destroy tumor cells ( Gascón et al, 2020 ). Although following CAR modification, cytotoxic CD8 + T-cells mediate the direct eradication of tumor cells, also CD4 + T helper cells (Th cells) have been identified as highly efficient and clinically important T-cells ( Stock et al, 2019 ).…”

Section: T-cells In Cart Therapymentioning

confidence: 99%

“…Recent studies indicate that CD4 + CART cells have a cytotoxic ability comparable to cytotoxic CD8 + CART cells ( Stock et al, 2019 ), and can increase the proliferation of CD8 + T cells ( Yang Y. et al, 2017 ). Based on data inferred from T cell biology, trials have been designed and conducted using defined mixtures of CD8 and CD4 T cells to generate CAR products that have demonstrated success in CD19 + leukemias and lymphomas ( Gascón et al, 2020 ).…”

Section: T-cells In Cart Therapymentioning

confidence: 99%

Potential of Stem Cells and CART as a Potential Polytherapy for Small Cell Lung Cancer

Скурихин

Першина

Zhukova

et al. 2021

Front. Cell Dev. Biol.

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Despite the increasing urgency of the problem of treating small cell lung cancer (SCLC), information on the causes of its development is fragmentary. There is no complete understanding of the features of antitumor immunity and the role of the microenvironment in the development of SCLC resistance. This impedes the development of new methods for the diagnosis and treatment of SCLC. Lung cancer and chronic obstructive pulmonary disease (COPD) have common pathogenetic factors. COPD is a risk factor for lung cancer including SCLC. Therefore, the search for effective approaches to prevention, diagnosis, and treatment of SCLC in patients with COPD is an urgent task. This review provides information on the etiology and pathogenesis of SCLC, analyses the effectiveness of current treatment options, and critically evaluates the potential of chimeric antigen receptor T cells therapy (CART therapy) in SCLC. Moreover, we discuss potential links between lung cancer and COPD and the role of endothelium in the development of COPD. Finally, we propose a new approach for increasing the efficacy of CART therapy in SCLC.

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Intratumoral versus Circulating Lymphoid Cells as Predictive Biomarkers in Lung Cancer Patients Treated with Immune Checkpoint Inhibitors: Is the Easiest Path the Best One?

Cited by 14 publications

References 89 publications

FDA-Approved and Emerging Next Generation Predictive Biomarkers for Immune Checkpoint Inhibitors in Cancer Patients

FDA-Approved and Emerging Next Generation Predictive Biomarkers for Immune Checkpoint Inhibitors in Cancer Patients

The Predictive Role of Immune Related Subgroup Classification in Immune Checkpoint Blockade Therapy for Lung Adenocarcinoma

Potential of Stem Cells and CART as a Potential Polytherapy for Small Cell Lung Cancer

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