Actionable Molecular Alterations Are Revealed in Majority of Advanced Non-Small Cell Lung Cancer Patients by Genomic Tumor Profiling at Progression after First Line Treatment

Factors for a broad technology assessment of comprehensive genomic profiling in advanced cancer, a systematic review

Comprehensive Genomic Profiling (CGP) allows for the identification of many targets. Reimbursement decision-making is, however, challenging because besides the health benefits of on-label treatments and costs, other factors related to diagnostic and treatment pathways may also play a role. The aim of this study was to identify which other factors are relevant for the technology assessment of CGP and to summarize the available evidence for these factors. After a scoping search and two expert sessions, five factors were identified: feasibility, test journey, wider implications of diagnostic results, organisation of laboratories, and "scientific spillover". Subsequently, a systematic search identified 83 studies collecting mainly evidence for the factors "test journey" and "wider implications of diagnostic results". Its nature was, however, of limited value for decision-making. We recommend the use of comparative strategies, uniformity in outcome definitions, and the inclusion of a comprehensive set of factors in future evidence generation.

Clinicopathological characterization of next-generation sequencing detected mutations in lung cancers-a single-center experience

Background

Despite many advances in molecular procedures many lung cancer patients do not receive full panel testing. This can limit the comprehensive understanding of their disease and potentially hinder personalized treatment options.

Methods

In this retrospective analysis, we used results from next-generation sequencing (NGS) testing of 154 patients with adenocarcinoma (AC) or squamous cell carcinoma (SCC) of the lung treated at the University Hospital, Ludwig-Maximilians Universität (LMU) Munich between 2018 and 2021. We compared different clinicopathological features and patients' baseline characteristics with results of NGS testing. We used t-test and analysis of variance (ANOVA) to compare metric- and χ2-test and Fisher's exact test to compare categorical variables.

Results

NGS testing found mutations in 107 (69.5%) patients; 44 patients (28.6%) had more than one mutation. The majority (79.2%) of patients had AC and 64.9% were metastasized at diagnosis. Patients with detected mutations had significantly higher PD-L1 expression than those without mutations (36.4% vs. 19.2%, P=0.005). Mean PD-L1 expression also differed between different mutations ranging from 24.0% in EGFR to 56.8% in patients with MET alterations, and increased with the number of different mutations (P=0.07). EGFR mutations were significantly more common in females compared to males (22.9% vs. 9.5%, P=0.04) and PIK3CA mutations significantly more common in SCC (21.9% vs. 2.5%, P=0.004). We found 23 different mutations in AC and 13 different gene mutations in SCC.

Conclusions

Mutation profiles differed by histological type and metastases status and were significantly associated with PD-L1 expression. In the context of limited resources, our results may help prioritize patient for testing when tissue material and funding is limited.

Circulating Tumor DNA Monitoring Reveals Molecular Progression before Radiologic Progression in a Real-life Cohort of Patients with Advanced Non-small Cell Lung Cancer

PURPOSE

The clinical potential of liquid biopsy in patients with advanced cancer is real-time monitoring for early detection of treatment failure. Our study aimed to investigate the clinical validity of circulating tumor DNA (ctDNA) treatment monitoring in a real-life cohort of patients with advanced non-small cell lung cancer (NSCLC).

EXPERIMENTAL DESIGN

Patients with advanced or noncurative locally advanced NSCLC were prospectively included in an exploratory study (NCT03512847). Selected cancer-specific mutations were measured in plasma by standard or uniquely designed droplet digital PCR assays before every treatment cycle during first-line treatment until progressive disease (PD). Correlation between an increase in ctDNA (= molecular progression) and radiologic PD was investigated, defined as lead time, and the corresponding numbers of likely futile treatment cycles were determined. Utility of ctDNA measurements in clarifying the results of nonconclusive radiologic evaluation scans was evaluated.

RESULTS

Cancer-specific mutations and longitudinal plasma sampling were present in 132 of 150 patients. ctDNA was detectable in 88 (67%) of 132 patients treated by respectively chemotherapy (n = 41), immunotherapy (n = 43), or combination treatment (n = 4). In 66 (90%) of 73 patients experiencing PD, a ctDNA increase was observed with a median lead time of 1.5 months before radiologic PD. Overall, 119 (33%) of 365 treatment cycles were administered after molecular progression. In addition, ctDNA measurements could clarify the results in 38 (79%) of 48 nonconclusive radiologic evaluations.

CONCLUSIONS

ctDNA monitoring leads to earlier detection of treatment failure, and clarifies the majority of nonconclusive radiologic evaluations, giving the potential of sparing patients from likely futile treatments and needless adverse events.

SIGNIFICANCE

Treatment monitoring by ctDNA has the clinical potential to reveal PD before radiologic evaluation and consequently spare patients with advanced cancer from likely ineffective, costly cancer treatments and adverse events.

A health condition index for assessing disease progression

INTRODUCTION

Currently immunotherapy is considered a cutting edge pharmaceutical treatment for non-small cell lung cancer. Tumor profile plays a crucial role in identifying the correct patinet group.

METHODS

Therefore initial biopsies and re-biopsies are necessary in order to identify the expression of programmed death-ligand-1.

RESULTS

This information is crucial and therefore all future immunotherapy studies have to be built upon a specific statistical model which associates the tumor profile and tumor profile expression along with treatment efficiency.

DISCUSSION

We present a novel statistical methodology for future immunotherapy studies of non-small cell lung cancer.