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Lung Cancer Related Thrombosis (LCART): Focus on Immune Checkpoint Blockade.

ABSTRACT: Cancer-associated thrombosis (CAT) is a common complication in lung cancer patients. Lung cancer confers an increased risk of thrombosis compared to other solid malignancies across all stages of the disease. Newer treatment agents, including checkpoint immunotherapy and targeted agents, may further increase the risk of CAT. Different risk-assessment models, such as the Khorana Risk Score, and newer approaches that incorporate genetic risk factors have been used in lung cancer patients to evaluate the risk of thrombosis. The management of CAT is based on the results of large prospective trials, which show similar benefits to low-molecular-weight heparins (LMWHs) and direct oral anticoagulants (DOACs) in ambulatory patients. The anticoagulation agent and duration of therapy should be personalized according to lung cancer stage and histology, the presence of driver mutations and use of antineoplastic therapy, including recent curative lung surgery, chemotherapy or immunotherapy. Treatment options should be evaluated in the context of the COVID-19 pandemic, which has been shown to impact the thrombotic risk in cancer patients. This review focuses on the epidemiology, pathophysiology, risk factors, novel predictive scores and management of CAT in patients with active lung cancer, with a focus on immune checkpoint inhibitors.

SUBMITTER: Charpidou A

PROVIDER: S-EPMC10814098 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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Lung Cancer Related Thrombosis (LCART): Focus on Immune Checkpoint Blockade.

Charpidou Andriani A Gerotziafas Grigorios G Popat Sanjay S Araujo Antonio A Scherpereel Arnaud A Kopp Hans-Georg HG Bironzo Paolo P Massard Gilbert G Jiménez David D Falanga Anna A Kollias Anastasios A Syrigos Konstantinos K

Cancers 20240120 2

Cancer-associated thrombosis (CAT) is a common complication in lung cancer patients. Lung cancer confers an increased risk of thrombosis compared to other solid malignancies across all stages of the disease. Newer treatment agents, including checkpoint immunotherapy and targeted agents, may further increase the risk of CAT. Different risk-assessment models, such as the Khorana Risk Score, and newer approaches that incorporate genetic risk factors have been used in lung cancer patients to evaluat ...[more]

PMID: 38275891

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

Project description:BACKGROUND:Resistance to immune checkpoint inhibitors (ICIs) has been linked to local immunosuppression independent of major ICI targets (e.g., PD-1). Clinical experience with response prediction based on PD-L1 expression suggests that other factors influence sensitivity to ICIs in non-small cell lung cancer (NSCLC) patients. METHODS:Tumor specimens from 120 NSCLC patients from 10 institutions were evaluated for PD-L1 expression by immunohistochemistry, and global proliferative profile by targeted RNA-seq. RESULTS:Cell proliferation, derived from the mean expression of 10 proliferation-associated genes (namely BUB1, CCNB2, CDK1, CDKN3, FOXM1, KIAA0101, MAD2L1, MELK, MKI67, and TOP2A), was identified as a marker of response to ICIs in NSCLC. Poorly, moderately, and highly proliferative tumors were somewhat equally represented in NSCLC, with tumors with the highest PD-L1 expression being more frequently moderately proliferative as compared to lesser levels of PD-L1 expression. Proliferation status had an impact on survival in patients with both PD-L1 positive and negative tumors. There was a significant survival advantage for moderately proliferative tumors compared to their combined highly/poorly counterparts (p = 0.021). Moderately proliferative PD-L1 positive tumors had a median survival of 14.6 months that was almost twice that of PD-L1 negative highly/poorly proliferative at 7.6 months (p = 0.028). Median survival in moderately proliferative PD-L1 negative tumors at 12.6 months was comparable to that of highly/poorly proliferative PD-L1 positive tumors at 11.5 months, but in both instances less than that of moderately proliferative PD-L1 positive tumors. Similar to survival, proliferation status has impact on disease control (DC) in patients with both PD-L1 positive and negative tumors. Patients with moderately versus those with poorly or highly proliferative tumors have a superior DC rate when combined with any classification schema used to score PD-L1 as a positive result (i.e., TPS ≥ 50% or ≥ 1%), and best displayed by a DC rate for moderately proliferative tumors of no less than 40% for any classification of PD-L1 as a negative result. While there is an over representation of moderately proliferative tumors as PD-L1 expression increases this does not account for the improved survival or higher disease control rates seen in PD-L1 negative tumors. CONCLUSIONS:Cell proliferation is potentially a new biomarker of response to ICIs in NSCLC and is applicable to PD-L1 negative tumors.

Project description: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.

Dataset Information

Lung Cancer Related Thrombosis (LCART): Focus on Immune Checkpoint Blockade.

Publications

Lung Cancer Related Thrombosis (LCART): Focus on Immune Checkpoint Blockade.

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