Mutation-tailored treatment selection in non-small cell lung cancer patients in daily clinical practice

Regional differences in predictive biomarker testing rates for patients with metastatic NSCLC in the Netherlands

BACKGROUND

Predictive biomarker testing has a key role in the treatment decision-making for patients with non-small cell lung cancer (NSCLC) and is mandated by (inter)national guidelines. The aim of this study was to establish guideline-adherent biomarker testing rates in the Netherlands in 2019 and to examine associations of demographical, clinical, and environmental factors with guideline-adherent testing.

METHODS

This study involved the integration of clinical data of the Netherlands Cancer Registry with pathology reports of the Dutch Nationwide Pathology Databank. Data extracted from these reports included sample type, diagnosis, and molecular testing status of predictive biomarkers. The study population comprised all patients diagnosed with metastatic non-squamous NSCLC in the Netherlands in 2019.

RESULTS

In the cohort of 3877 patients with metastatic non-squamous NSCLC under investigation, overall molecular testing rates for non-fusion predictive biomarkers (EGFR, KRAS, BRAF, ERBB2, MET) ranged from 73.9 to 89.0 %, while molecular testing for fusion-drivers (ALK, ROS1, RET, NTRK) ranged from 12.6 % to 63.9 %. Guideline-adherent testing of EGFR, KRAS, and ALK was performed in 85.2 % of patients, with regional rates spanning from 76.0 % to 90.8 %. Demographical and clinical factors associated with guideline-adherent biomarker testing included lower age (OR = 1.05 per one year decrease; p < 0.001), female sex (OR = 1.36; p = 0.002), diagnosis of adenocarcinoma (OR = 2.48; p < 0.001), availability of histological tumor material (OR = 2.46; p < 0.001), and clinical stage of metastatic disease (p = 0.002). Other factors associated with guideline-adherent biomarker testing included diagnosis at academic center (OR = 1.87; p = 0.002) and patient's region of residence (p < 0∙001).

CONCLUSION

Optimization of the chain-of-care of predictive biomarker testing in patients with NSCLC in the Netherlands is needed to provide adequate care for these patients.

Prediction of epidermal growth factor receptor mutation subtypes in non-small cell lung cancer from hematoxylin and eosin-stained slides using deep learning

Accurate assessment of epidermal growth factor receptor (EGFR) mutation status and subtype are critical for the treatment of non-small cell lung cancer (NSCLC) patients. Conventional molecular testing methods for detecting EGFR mutations have limitations. In this study, an artificial intelligence-powered deep learning framework was developed for weakly supervised prediction of EGFR mutations in NSCLC from hematoxylin and eosin (H&E)-stained histopathology whole-slide images (WSIs). The study cohort was partitioned into training and validation subsets. Foreground regions containing tumor tissue were extracted from WSIs. A convolutional neural network (CNN) employing a contrastive learning paradigm was implemented to extract patch-level morphological features. These features were aggregated using a vision-transformer-based model to predict EGFR mutation status and classify patient cases. The established prediction model was validated on unseen datasets. In internal validation with a cohort from (USTC)(n=172), the model achieved patient-level areas under the receiver operating characteristic (ROC) curve (AUCs) of 0.927 and 0.907, sensitivities of 81.6% and 93.0%, and specificities of 83.3% and 92.3%, for surgical resection and biopsy specimens in EGFR mutation subtype prediction, respectively. External validation with cohorts from the Second Affiliated Hospital of Anhui Medical University (AMU) and the First Affiliated Hospital of Wannan Medical College (WMC) (n=193) yielded patient-level AUCs of 0.849 and 0.871, sensitivities of 75.7% and 72.1%, and specificities of 90.5% and 90.3% for surgical and biopsy specimens, respectively. Further validation with The Cancer Genome Atlas (TCGA) dataset (n=81) showed an AUC of 0.861, sensitivity of 84.6%, and specificity of 90.5%. Deep learning solutions demonstrate potential advantages for automated, non-invasive, fast, cost-effective, and accurate inference of EGFR alterations from histomorphology. Integration of such artificial intelligence frameworks into routine digital pathology workflows could augment existing molecular testing pipelines.

Exploring the Cost Effectiveness of a Whole-Genome Sequencing-Based Biomarker for Treatment Selection in Patients with Advanced Lung Cancer Ineligible for Targeted Therapy

OBJECTIVE

We aimed to perform an early cost-effectiveness analysis of using a whole-genome sequencing-based tumor mutation burden (WGS-TMB), instead of programmed death-ligand 1 (PD-L1), for immunotherapy treatment selection in patients with non-squamous advanced/metastatic non-small cell lung cancer ineligible for targeted therapy, from a Dutch healthcare perspective.

METHODS

A decision-model simulating individual patients with metastatic non-small cell lung cancer was used to evaluate diagnostic strategies to select first-line immunotherapy only or the immunotherapy plus chemotherapy combination. Treatment was selected using PD-L1 [A, current practice], WGS-TMB [B], and both PD-L1 and WGS-TMB [C]. Strategies D, E, and F take into account a patient's disease burden, in addition to PD-L1, WGS-TMB, and both PD-L1 and WGS-TMB, respectively. Disease burden was defined as a fast-growing tumor, a high number of metastases, and/or weight loss. A threshold of 10 mutations per mega-base was used to classify patients into TMB-high and TMB-low groups. Outcomes were discounted quality-adjusted life-years (QALYs) and healthcare costs measured from the start of first-line treatment to death. Healthcare costs includes drug acquisition, follow-up costs, and molecular diagnostic tests (i.e., standard diagnostic techniques and/or WGS for strategies involving TMB). Results were reported using the net monetary benefit at a willingness-to-pay threshold of €80,000/QALY. Additional scenario and threshold analyses were performed.

RESULTS

Strategy B had the lowest QALYs (1.84) and lowest healthcare costs (€120,800). The highest QALYs and healthcare costs were 2.00 and €140,400 in strategy F. In the base-case analysis, strategy A was cost effective with the highest net monetary benefit (€27,300), followed by strategy B (€26,700). Strategy B was cost effective when the cost of WGS testing was decreased by at least 24% or when immunotherapy results in an additional 0.5 year of life gained or more for TMB high compared with TMB low. Strategies C and F, which combined TMB and PD-L1 had the highest net monetary benefit (≥ €76,900) when the cost of WGS testing, immunotherapy, and chemotherapy acquisition were simultaneously reduced by at least 47%, 39%, and 43%, respectively. Furthermore, strategy C resulted in the highest net monetary benefit (≥ €39,900) in a scenario where patients with both PD-L1 low and TMB low were treated with chemotherapy instead of immunotherapy plus chemotherapy.

CONCLUSIONS

The use of WGS-TMB is not cost effective compared to PD-L1 for immunotherapy treatment selection in non-squamous metastatic non-small cell lung cancer in the Netherlands. WGS-TMB could become cost effective provided there is a reduction in the cost of WGS testing or there is an increase in the predictive value of WGS-TMB for immunotherapy effectiveness. Alternatively, a combination strategy of PD-L1 testing with WGS-TMB would be cost effective if used to support the choice to withhold immunotherapy in patients with a low expected benefit of immunotherapy.

Developments in predictive biomarker testing and targeted therapy in advanced stage non-small cell lung cancer and their application across European countries

In the past two decades, the treatment of metastatic non-small cell lung cancer (NSCLC), has undergone significant changes due to the introduction of targeted therapies and immunotherapy. These advancements have led to the need for predictive molecular tests to identify patients eligible for targeted therapy. This review provides an overview of the development and current application of targeted therapies and predictive biomarker testing in European patients with advanced stage NSCLC. Using data from eleven European countries, we conclude that recommendations for predictive testing are incorporated in national guidelines across Europe, although there are differences in their comprehensiveness. Moreover, the availability of recently EMA-approved targeted therapies varies between European countries. Unfortunately, routine assessment of national/regional molecular testing rates is limited. As a result, it remains uncertain which proportion of patients with metastatic NSCLC in Europe receive adequate predictive biomarker testing. Lastly, Molecular Tumor Boards (MTBs) for discussion of molecular test results are widely implemented, but national guidelines for their composition and functioning are lacking. The establishment of MTB guidelines can provide a framework for interpreting rare or complex mutations, facilitating appropriate treatment decision-making, and ensuring quality control.

Optimized whole-genome sequencing workflow for tumor diagnostics in routine pathology practice

Two decades after the genomics revolution, oncology is rapidly transforming into a genome-driven discipline, yet routine cancer diagnostics is still mainly microscopy based, except for tumor type-specific predictive molecular tests. Pathology laboratories struggle to quickly validate and adopt biomarkers identified by genomics studies of new targeted therapies. Consequently, clinical implementation of newly approved biomarkers suffers substantial delays, leading to unequal patient access to these therapies. Whole-genome sequencing (WGS) can successfully address these challenges by providing a stable molecular diagnostic platform that allows detection of a multitude of genomic alterations in a single cost-efficient assay and facilitating rapid implementation, as well as by the development of new genomic biomarkers. Recently, the Whole-genome sequencing Implementation in standard Diagnostics for Every cancer patient (WIDE) study demonstrated that WGS is a feasible and clinically valid technique in routine clinical practice with a turnaround time of 11 workdays. As a result, WGS was successfully implemented at the Netherlands Cancer Institute as part of routine diagnostics in January 2021. The success of implementing WGS has relied on adhering to a comprehensive protocol including recording patient information, sample collection, shipment and storage logistics, sequencing data interpretation and reporting, integration into clinical decision-making and data usage. This protocol describes the use of fresh-frozen samples that are necessary for WGS but can be challenging to implement in pathology laboratories accustomed to using formalin-fixed paraffin-embedded samples. In addition, the protocol outlines key considerations to guide uptake of WGS in routine clinical care in hospitals worldwide.

Phospholipase Family Enzymes in Lung Cancer: Looking for Novel Therapeutic Approaches

Lung cancer (LC) is the second most common neoplasm in men and the third most common in women. In the last decade, LC therapies have undergone significant improvements with the advent of immunotherapy. However, the effectiveness of the available treatments remains insufficient due to the presence of therapy-resistant cancer cells. For decades, chemotherapy and radiotherapy have dominated the treatment strategy for LC; however, relapses occur rapidly and result in poor survival. Malignant lung tumors are classified as either small- or non-small-cell lung carcinoma (SCLC and NSCLC). Despite improvements in the treatment of LC in recent decades, the benefits of surgery, radiotherapy, and chemotherapy are limited, although they have improved the prognosis of LC despite the persistent low survival rate due to distant metastasis in the late stage. The identification of novel prognostic molecular markers is crucial to understand the underlying mechanisms of LC initiation and progression. The potential role of phosphatidylinositol in tumor growth and the metastatic process has recently been suggested by some researchers. Phosphatidylinositols are lipid molecules and key players in the inositol signaling pathway that have a pivotal role in cell cycle regulation, proliferation, differentiation, membrane trafficking, and gene expression. In this review, we discuss the current understanding of phosphoinositide-specific phospholipase enzymes and their emerging roles in LC.

Real-world treatment patterns and survival of patients with ROS1 rearranged stage IV non-squamous NSCLC in the Netherlands

INTRODUCTION

Rearrangement of c-ros oncogene 1 (ROS1) is a rare gene alteration in patients with stage IV non-squamous non-small cell lung cancer (NSCLC). Molecular testing for ROS1 is recommended to enable primary treatment with tyrosine kinase inhibitors (TKI). Aim of this study was to describe real-world treatment patterns and survival for patients with ROS1 in the Netherlands.

METHODS

All non-squamous NSCLC stage IV patients, diagnosed 2015-2019, were identified from the population-based Netherlands Cancer Registry (N = 19,871). For patients with ROS1 rearrangements (ROS1+ ) who received first line TKI, additional information about progression and second-line treatment was retrieved by active follow-up. Overall survival (OS) and progression-free survival (PFS) were calculated using Kaplan-Meier estimators.

RESULTS

A total of 67 patients (0.43%) were diagnosed with a ROS1+ NSCLC. Systemic treatment was administered in 75% which was most often TKI (n = 34) followed by chemotherapy (n = 14). Two-year OS for patients receiving upfront TKI versus other systemic treatment was 53% (95% CI 35-68) and 50% (95% CI 25-71), respectively. For patients receiving TKI, median OS was 24.3 months. Survival was inferior in case of brain metastasis (BM) at diagnosis (5.2 months). One in five patients receiving TKI as a first line treatment had BM at diagnosis, of the remaining 22 another 9 developed BM during follow up. PFS was also inferior for patients with BM at diagnosis with a median PFS of 4.3 months versus 9.0 without BM.

CONCLUSION

In this real-world population of ROS1+ NSCLC patients, only half received primary treatment with TKI. Overall survival and PFS during TKI were disappointing, mainly related to brain metastasis. TKI treatment with agents that have intra-cranial activity may be beneficial in this patient population and our results confirm the importance of performing an MRI of the brain as part of the standard diagnostic work up in patients with ROS1+ NSCLC.

Overall survival in advanced epidermal growth factor receptor mutated non-small cell lung cancer using different tyrosine kinase inhibitors in The Netherlands: a retrospective, nationwide registry study

Background

Clinical guidelines advise osimertinib as preferred first line treatment for advanced epidermal growth factor receptor (EGFR) mutated non-small cell lung cancer (NSCLC) with deletions in exon 19 (del19) or exon 21 L858R mutation. However, for first-line osimertinib the real world overall survival (OS) in mutation subgroups remains unknown. Therefore, the aim of this study was to evaluate the real-world OS of those patients treated with different generations of EGFR-tyrosine kinase inhibitors (TKI), and to identify predictors of survival.

Methods

Using real-world data from the Netherlands Cancer Registry (NCR) we assessed patients diagnosed with stage IV NSCLC with del19 or L858R mutation between January 1, 2015, and December 31, 2020, primarily treated with then regularly available TKIs (including osimertinib).

Findings

Between January 1, 2015, and December 31, 2020, 57,592 patients were included in the NCR. Within this cohort we identified 1109 patients, 654 (59%) with del19 and 455 (41%) with L858R mutations, respectively; 230 (21%) patients were diagnosed with baseline brain metastases (BM). Patients were treated with gefitinib (19%, 213/1109), erlotinib (42%, 470/1109), afatinib (15%, 161/1109) or osimertinib (24%, 265/1109). Median OS was superior for del19 versus L858R (28.4 months (95% CI 25.6-30.6) versus 17.7 months (95% CI 16.1-19.5), p < 0.001. In multivariable analysis, no difference in survival was observed between various TKIs in both groups. Only in the subgroup of patients with del19 and baseline BM, a benefit was observed for treatment with osimertinib.

Interpretation

In this nationwide real-world cohort, survival of Dutch patients with advanced NSCLC and an EGFR del19 mutation was superior versus those harboring an L858R mutation. Osimertinib performed only better as first-line treatment in patients with del19 and BM.

Funding

None.

Optimizing molecular testing of lung cancer needle biopsy specimens: potential solutions from an interdisciplinary qualitative study

BACKGROUND

Molecular testing can detect actionable genomic alterations and tumor cell surface proteins in patients with non-small cell lung cancer (NSCLC). However, utilization remains suboptimal, representing missed treatment opportunities. This study aimed to identify challenges and potential solutions to obtaining percutaneous lung needle biopsy specimens for successful molecular testing in patients with advanced NSCLC.

METHODS

This interdisciplinary qualitative study included ten radiologists and four pathologists from academic and community settings across the United States who routinely perform and analyze percutaneous lung needle biopsies. Participants underwent semi-structured one-on-one interviews (Phase 1). Interview questionnaires were constructed based on a literature review of key lines of inquiry and conducted by professional market researchers using the theoretical domains framework. Primary barriers to molecular testing were identified using thematic analysis. Subsequently, multidisciplinary focus groups were convened to identify potential solutions (Phase 2).

RESULTS

Four themes emerged as barriers to molecular testing and were matched to the clinical workflow: (1) biopsy request, (2) biopsy procedure, (3) specimen analysis, and (4) communication. The nineteen potential solutions included adding a "checkbox" to indicate molecular testing in the biopsy request, leveraging pre-procedural imaging to guide biopsies, conserving tissue through appropriate allocation strategies and next generation sequencing panels instead of sequential single-gene assays, instituting reflex-molecular testing upon NSCLC diagnosis, tracking and communicating biopsy outcomes at multidisciplinary tumor boards, and improving integration of radiologists and pathologists into oncology care teams.

CONCLUSIONS

Potential solutions exist to increase successful molecular testing of lung needle biopsy specimens in patients with advanced NSCLC.

Feasibility of whole genome sequencing based tumor diagnostics in routine pathology practice

The current increase in number and diversity of targeted anticancer agents poses challenges to the logistics and timeliness of molecular diagnostics (MolDx), resulting in underdiagnosis and treatment. Whole‐genome sequencing (WGS) may provide a sustainable solution for addressing current as well as future diagnostic challenges. The present study therefore aimed to prospectively assess feasibility, validity, and value of WGS in routine clinical practice. WGS was conducted independently of, and in parallel with, standard of care (SOC) diagnostics on routinely obtained tumor samples from 1,200 consecutive patients with metastatic cancer. Results from both tests were compared and discussed in a dedicated tumor board. From 1,200 patients, 1,302 samples were obtained, of which 1,216 contained tumor cells. WGS was successful in 70% (854/1,216) of samples with a median turnaround time of 11 days. Low tumor purity (<20%) was the main reason for not completing WGS. WGS identified 99.2% and SOC MolDx 99.7% of the total of 896 biomarkers found in genomic regions covered by both tests. Actionable biomarkers were found in 603/848 patients (71%). Of the 936 associated therapy options identified by WGS, 343 were identified with SOC MolDx (36.6%). Biomarker‐based therapy was started in 147 patients. WGS revealed 49 not previously identified pathogenic germline variants. Fresh‐frozen, instead of formalin‐fixed and paraffin‐embedded, sample logistics were easily adopted as experienced by the professionals involved. WGS for patients with metastatic cancer is well feasible in routine clinical practice, successfully yielding comprehensive genomic profiling for the vast majority of patients. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Cost-Effectiveness of Parallel Versus Sequential Testing of Genetic Aberrations for Stage IV Non-Small-Cell Lung Cancer in the Netherlands

PURPOSE

A large number of targeted treatment options for stage IV nonsquamous non–small-cell lung cancer with specific genetic aberrations in tumor DNA is available. It is therefore important to optimize diagnostic testing strategies, such that patients receive adequate personalized treatment that improves survival and quality of life. The aim of this study is to assess the efficacy (including diagnostic costs, turnaround time (TAT), unsuccessful tests, percentages of correct findings, therapeutic costs, and therapeutic effectiveness) of parallel next generation sequencing (NGS)–based versus sequential single-gene–based testing strategies routinely used in patients with metastasized non–small-cell lung cancer in the Netherlands.

METHODS

A diagnostic microsimulation model was developed to simulate 100,000 patients with prevalence of genetic aberrations, extracted from real-world data from the Dutch Pathology Registry. These simulated patients were modeled to undergo different testing strategies composed of multiple tests with different test characteristics including single-gene and panel tests, test accuracy, the probability of an unsuccessful test, and TAT. Diagnostic outcomes were linked to a previously developed treatment model, to predict average long-term survival, quality-adjusted life-years (QALYs), costs, and cost-effectiveness of parallel versus sequential testing.

RESULTS

NGS-based parallel testing for all actionable genetic aberrations is on average €266 cheaper than single-gene–based sequential testing, and detects additional relevant targetable genetic aberrations in 20.5% of the cases, given a TAT of maximally 2 weeks. Therapeutic costs increased by €8,358, and 0.12 QALYs were gained, leading to an incremental cost-effectiveness ratio of €69,614/QALY for parallel versus sequential testing.

CONCLUSION

NGS-based parallel testing is diagnostically superior over single-gene–based sequential testing, as it is cheaper and more effective than sequential testing. Parallel testing remains cost-effective with an incremental cost-effectiveness ratio of 69,614 €/QALY upon inclusion of therapeutic costs and long-term outcomes.

Direct identification of ALK and ROS1 fusions in non-small cell lung cancer from hematoxylin and eosin-stained slides using deep learning algorithms

Anaplastic lymphoma kinase (ALK) and ROS oncogene 1 (ROS1) gene fusions are well-established key players in non-small cell lung cancer (NSCLC). Although their frequency is relatively low, their detection is important for patient care and guides therapeutic decisions. The accepted methods used for their detection are immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) assay, as well as DNA and RNA-based sequencing methodologies. These assays are expensive, time-consuming, and require technical expertise and specialized equipment as well as biological specimens that are not always available. Here we present an alternative detection method using a computer vision deep learning approach. An advanced convolutional neural network (CNN) was used to generate classifier models to detect ALK and ROS1-fusions directly from scanned hematoxylin and eosin (H&E) whole slide images prepared from NSCLC tumors of patients. A two-step training approach was applied, with an initial unsupervised training step performed on a pan-cancer sample cohort followed by a semi-supervised fine-tuning step, which supported the development of a classifier with performances equal to those accepted for diagnostic tests. Validation of the ALK/ROS1 classifier on a cohort of 72 lung cancer cases who underwent ALK and ROS1-fusion testing at the pathology department at Sheba Medical Center displayed sensitivities of 100% for both genes (six ALK-positive and two ROS1-positive cases) and specificities of 100% and 98.6% respectively for ALK and ROS1, with only one false-positive result for ROS1-alteration. These results demonstrate the potential advantages that machine learning solutions may have in the molecular pathology domain, by allowing fast, standardized, accurate, and robust biomarker detection overcoming many limitations encountered when using current techniques. The integration of such novel solutions into the routine pathology workflow can support and improve the current clinical pipeline.