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Treatment of Complications from Immune Checkpoint Inhibition in Patients with Lung Cancer.

ABSTRACT: OPINION STATEMENT:Immune checkpoint inhibitors have revolutionized the management of advanced NSCLC. With the intention of generating an anti-tumor immune response, ICIs can also lead to inflammatory side effects involving a wide variety of organs in the body, termed immune-related adverse events. Although no prospective clinical trial exists to guide recommendations for optimal and more specific immunosuppressive treatments rather than corticosteroids, further studies may lead to a more mechanistic-based approach towards these toxicities in the future. In relation to current practice, we recommend adherence to the recent published guidelines which emphasize the importance of early recognition and administration of temporary immunosuppressive therapy with corticosteroids in most cases, depending on the organ system involved, and the severity of toxicity. Recognition of these toxicities is increasingly important as the use of these agents expand within different indications for patients with lung cancers, and to other tumor types.

SUBMITTER: Wills B

PROVIDER: S-EPMC7102206 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Treatment of Complications from Immune Checkpoint Inhibition in Patients with Lung Cancer.

Wills Beatriz B Brahmer Julie R JR Naidoo Jarushka J

Current treatment options in oncology 20180813 9

<h4>Opinion statement</h4>Immune checkpoint inhibitors have revolutionized the management of advanced NSCLC. With the intention of generating an anti-tumor immune response, ICIs can also lead to inflammatory side effects involving a wide variety of organs in the body, termed immune-related adverse events. Although no prospective clinical trial exists to guide recommendations for optimal and more specific immunosuppressive treatments rather than corticosteroids, further studies may lead to a more ...[more]

PMID: 30101402

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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:BackgroundThe development of immune checkpoint inhibitors (ICIs) is a revolutionary milestone in the field of immune-oncology. However, the low response rate is the major problem of ICI treatment. The recent studies showed that response rate to single-agent programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibition in unselected non-small cell lung cancer (NSCLC) patients is 25% so that researchers defined several biomarkers to predict the response of immunotherapy in ICIs treatment. Common biomarkers like tumor mutational burden (TMB) and PD-L1 expression have several limitations, such as low accuracy and inadequately validated cutoff value.MethodsTwo published and an unpublished ICIs treatment NSCLC cohorts with 129 patients were collected and divided into a training cohort (n = 53), a validation cohort (n = 22), and two independent test cohorts (n = 34 and n = 20). We identified six immune-related pathways whose mutational status was significantly associated with overall survival after ICIs treatment. Then these pathways mutational status combined with TMB, PD-L1 expression and intratumor heterogeneity were incorporated to build a Bayesian-regularization neural networks (BRNN) model to predict the ICIs treatment response.ResultsWe firstly proved that TMB, PD-L1, and mutant-allele tumor heterogeneity (MATH) were independent biomarkers. The survival analysis of six immune-related pathways revealed the mutational status could distinguish overall survival after ICIs treatment. When predicting immunotherapy efficacy, the overall accuracy of area under curve (AUC) in validation cohort reaches 0.85, outperforming previous predictors in either sensitivity or specificity. And the AUC in two independent test cohorts reach 0.74 and 0.80.ConclusionWe developed a pathway-model that could predict the efficacy of ICIs in NSCLC patients. Our study made a significant contribution to solving the low prediction accuracy of immunotherapy of single biomarker. With the accumulation of larger data sets, further studies are warranted to refine the predictive performance of the approach.

Dataset Information

Treatment of Complications from Immune Checkpoint Inhibition in Patients with Lung Cancer.

Publications

Treatment of Complications from Immune Checkpoint Inhibition in Patients with Lung Cancer.

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