Computational markers for personalized prediction of outcomes in non-small cell lung cancer patients with brain metastases.

Intracranial progression after curative treatment of early-stage non-small cell lung cancer (NSCLC) occurs from 10 to 50% and is difficult to manage, given the heterogeneity of clinical presentations and the variability of treatments available. The objective of this study was to develop a mechanistic model of intracranial progression to predict survival following a first brain metastasis (BM) event occurring at a time [Formula: see text]. Data included early-stage NSCLC patients treated with a curative intent who had a BM as the first and single relapse site (N = 31). We propose a mechanistic mathematical model able to derive computational markers from primary tumor and BM data at [Formula: see text] and estimate the amount and sizes of (visible and invisible) BMs, as well as their future behavior. These two key computational markers are [Formula: see text], the proliferation rate of a single tumor cell; and [Formula: see text], the per day, per cell, probability to metastasize. The predictive value of these individual computational biomarkers was evaluated. The model was able to correctly describe the number and size of metastases at [Formula: see text] for 20 patients. Parameters [Formula: see text] and [Formula: see text] were significantly associated with overall survival (OS) (HR 1.65 (1.07-2.53) p = 0.0029 and HR 1.95 (1.31-2.91) p = 0.0109, respectively). Adding the computational markers to the clinical ones significantly improved the predictive value of OS (c-index increased from 0.585 (95% CI 0.569-0.602) to 0.713 (95% CI 0.700-0.726), p < 0.0001). We demonstrated that our model was applicable to brain oligoprogressive patients in NSCLC and that the resulting computational markers had predictive potential. This may help lung cancer physicians to guide and personalize the management of NSCLC patients with intracranial oligoprogression.

Killing a fly with a sledgehammer: Atezolizumab exposure in real-world lung cancer patients.

Atezolizumab is an anti-PDL1 approved for treating lung cancer. A threshold of 6 µg/mL in plasma has been associated with target engagement. The extent to which patients could be overexposed with the standard 1200 mg q3w dosing remains unknown. Here, we monitored atezolizumab peak and trough levels in 27 real-world patients with lung cancer as part of routine therapeutic drug monitoring. Individual pharmacokinetic (PK) parameters were calculated using a population approach and optimal dosing-intervals were simulated with respect to the target trough levels. No patient had plasma levels below 6 µg/mL. The results showed that the mean trough level after the first treatment was 78.3 ± 17 µg/mL, that is, 13 times above the target concentration. The overall response rate was 55.5%. Low-grade immune-related adverse events was observed in 37% of patients. No relationship was found between exposure metrics of atezolizumab (i.e., minimum plasma concentration, maximum plasma concentration, and area under the curve) and pharmacodynamic end points (i.e., efficacy and toxicity). Further simulations suggest that the dosing interval could be extended from 21 days to 49 up to 136 days (mean: 85.7 days, i.e., q12w), while ensuring plasma levels still above the 6 µg/mL target threshold. This observational, real-world study suggests that the standard 1200 mg q3w fixed-dose regimen of atezolizumab results in significant overexposure in all the patients. This was not associated with increased side effects. As plasma levels largely exceed pharmacologically active concentrations, interindividual variability in PK parameters did not impact efficacy. Our data suggest that dosing intervals could be markedly extended with respect to the target threshold associated with efficacy.

Immunologic constant of rejection as a predictive biomarker of immune checkpoint inhibitors efficacy in non-small cell lung cancer.

BACKGROUND: Anti-PD1/PDL1 immune checkpoint inhibitors (ICI) transformed the prognosis of patients with advanced non-small cell lung cancer (NSCLC). However, the response rate remains disappointing and toxicity may be life-threatening, making urgent identification of biomarkers predictive for efficacy. Immunologic Constant of Rejection signature (ICR) is a 20-gene expression signature of cytotoxic immune response with prognostic value in some solid cancers. Our objective was to assess its predictive value for benefit from anti-PD1/PDL1 in patients with advanced NSCLC. METHODS: We retrospectively profiled 44 primary tumors derived from NSCLC patients treated with ICI as single-agent in at least the second-line metastatic setting. Transcriptomic analysis was performed using the nCounter® analysis system and the PanCancer Immune Profiling Panel. We then pooled our data with clinico-biological data from four public gene expression data sets, leading to a total of 162 NSCLC patients treated with single-agent anti-PD1/PDL1. ICR was applied to all samples and correlation was searched between ICR classes and the Durable Clinical Benefit (DCB), defined as stable disease or objective response according to RECIST 1.1 for a minimum of 6 months after the start of ICI. RESULTS: The DCB rate was 29%; 22% of samples were classified as ICR1, 30% ICR2, 22% ICR3, and 26% ICR4. These classes were not associated with the clinico-pathological variables, but showed enrichment from ICR1 to ICR4 in quantitative/qualitative markers of immune response. ICR2-4 class was associated with a 5.65-fold DCB rate when compared with ICR1 class. In multivariate analysis, ICR classification remained associated with DCB, independently from PDL1 expression and other predictive immune signatures. By contrast, it was not associated with disease-free survival in 556 NSCLC TCGA patients untreated with ICI. CONCLUSION: The 20-gene ICR signature was independently associated with benefit from anti-PD1/PDL1 ICI in patients with advanced NSCLC. Validation in larger retrospective and prospective series is warranted.

Molecular profiling of non-small-cell lung cancer patients with or without brain metastases included in the randomized SAFIR02-LUNG trial and association with intracranial outcome.

INTRODUCTION: Lung cancer remains the most frequent cause of brain metastases (BMs) and is responsible for high morbidity and mortality. Intracranial response to systemic treatments is inconsistent due to several mechanisms: genomic heterogeneity, blood-tumor barrier, and the brain-specific microenvironment. We conducted a study using data from the SAFIR02-LUNG trial. The primary objective was to compare the molecular profiles of non-small-cell lung cancer (NSCLC) with or without BMs. The secondary objective was to explore central nervous system (CNS) outcomes with various maintenance treatment regimens. METHODS: In total, 365 patients harboring interpretable molecular data were included in this analysis. Clinical and biological data were collected. Genomic analyses were based on array-comparative genomic hybridization and next-generation sequencing (NGS) following the trial recommendations. RESULTS: Baseline genomic analyses of copy number variations identified a 24-gene signature specific to lung cancer BM occurrence, all previously known to take part in oncogenesis. NGS analysis identified a higher proportion of KRAS mutations in the BM-positive group (44.3% versus 32.3%), especially G12C mutations (63% versus 47%). Protein interaction analyses highlighted several functional interactions centered on EGFR. Furthermore, the risk of CNS progression was decreased with standard pemetrexed maintenance therapy. The highest rate of CNS progression was observed with durvalumab, probably because of the specific intracranial immune microenvironment. CONCLUSION: This work identified a 24-gene signature specific to lung cancer with BM. Further studies are needed to precisely determine the functional implications of these genes to identify new therapeutic targets for the treatment of lung cancer with BM.

The Value of Population Screening in Advancing Personalized Medicine in the Field of Lung Cancer.

During the past decade, progress has been made in the field of lung cancer molecular biology and onco-immunology, leading to prolonged survival of patients. The combination of increased fundamental knowledge and the pharmaceutical pipeline has allowed the development of various tyrosine kinase inhibitors, targeting numerous molecular alterations. These drugs are now available in daily practice and have transformed survival outcomes for patients harboring EGFR, ALK or ROS1 alterations. Multiple clinical trials are now ongoing in order to increase the number of approved drugs, thus overcoming the issues of rare mutations and tyrosine kinase inhibitors resistance. Immune checkpoint inhibitors development has also changed lung cancer outcomes, but underwhelming response rates highlight the need for immune biomarkers. While PD-L1 expression was the first approved immune biomarker, it has shown several limitations and new biomarkers have to be identified to predict response or resistance to immune checkpoint inhibitors. Testing methods, molecular results and targeted therapeutic schedules will be harmonized in the coming years, with the help of dedicated molecular multidisciplinary boards.

[Predictable toxicities with futures immunotherapies or combinations]. / Toxicités à prévoir avec les futures immunothérapies ou associations.

Immunotherapy by immune check-points inhibitors (ICIs) recently improved many solid tumors survival data. ICIs target and inhibit down-regulation signals between T cells and tumor cells involved in carcinogenesis, in order to enhance anti-tumor immunity. With few years' hindsight of ICIs utilization in daily practice, we learned about their safety profile. By releasing the brakes of the host immune-system, ICIs exposure leads to on-target off-tumor immune related adverse events (IRAEs). Compared to standard chemotherapiy regimens, IRAEs remain rare, but sometimes serious and compromising treatment continuation, mostly despite objective tumor response. Several immunotherapy molecules are currently developed, with various mechanisms of action but always targeting the immune anti-tumor response. New drugs imply new safety profiles, especially since a lot of ongoing clinical trials are assessing combination of multiples drugs. Consequently, a good knowledge and management of these new toxicities will be essential to choose the new therapeutic schedules in many tumor types. Indeed, despite the actual poor prognosis of concerned tumor types, the progressive outcomes improvement implies long-term exposure to treatments. Safety and quality of life under treatment will become key endpoints for therapeutic decision.