Molecular Risk Stratification is Independent of EGFR Mutation Status in Identifying Early-Stage Non-Squamous Non-Small Cell Lung Cancer Patients at Risk for Recurrence and Likely to Benefit From Adjuvant Chemotherapy

Analytical validation of a novel comprehensive genomic profiling informed circulating tumor DNA monitoring assay for solid tumors

Emerging technologies focused on the detection and quantification of circulating tumor DNA (ctDNA) in blood show extensive potential for managing patient treatment decisions, informing risk of recurrence, and predicting response to therapy. Currently available tissue-informed approaches are often limited by the need for additional sequencing of normal tissue or peripheral mononuclear cells to identify non-tumor-derived alterations while tissue-naïve approaches are often limited in sensitivity. Here we present the analytical validation for a novel ctDNA monitoring assay, FoundationOne®Tracker. The assay utilizes somatic alterations from comprehensive genomic profiling (CGP) of tumor tissue. A novel algorithm identifies monitorable alterations with a high probability of being somatic and computationally filters non-tumor-derived alterations such as germline or clonal hematopoiesis variants without the need for sequencing of additional samples. Monitorable alterations identified from tissue CGP are then quantified in blood using a multiplex polymerase chain reaction assay based on the validated SignateraTM assay. The analytical specificity of the plasma workflow is shown to be 99.6% at the sample level. Analytical sensitivity is shown to be >97.3% at ≥5 mean tumor molecules per mL of plasma (MTM/mL) when tested with the most conservative configuration using only two monitorable alterations. The assay also demonstrates high analytical accuracy when compared to liquid biopsy-based CGP as well as high qualitative (measured 100% PPA) and quantitative precision (<11.2% coefficient of variation).

Hybrid deep multi-task learning radiomics approach for predicting EGFR mutation status of non-small cell lung cancer in CT images

Objective.Epidermal growth factor receptor (EGFR) mutation genotyping plays a pivotal role in targeted therapy for non-small cell lung cancer (NSCLC). We aimed to develop a computed tomography (CT) image-based hybrid deep radiomics model to predict EGFR mutation status in NSCLC and investigate the correlations between deep image and quantitative radiomics features.Approach.First, we retrospectively enrolled 818 patients from our centre and 131 patients from The Cancer Imaging Archive database to establish a training cohort (N= 654), an independent internal validation cohort (N= 164) and an external validation cohort (N= 131). Second, to predict EGFR mutation status, we developed three CT image-based models, namely, a multi-task deep neural network (DNN), a radiomics model and a feature fusion model. Third, we proposed a hybrid loss function to train the DNN model. Finally, to evaluate the model performance, we computed the areas under the receiver operating characteristic curves (AUCs) and decision curve analysis curves of the models.Main results.For the two validation cohorts, the feature fusion model achieved AUC values of 0.86 ± 0.03 and 0.80 ± 0.05, which were significantly higher than those of the single-task DNN and radiomics models (allP< 0.05). There was no significant difference between the feature fusion and the multi-task DNN models (P> 0.8). The binary prediction scores showed excellent prognostic value in predicting disease-free survival (P= 0.02) and overall survival (P< 0.005) for validation cohort 2.Significance.The results demonstrate that (1) the feature fusion and multi-task DNN models achieve significantly higher performance than that of the conventional radiomics and single-task DNN models, (2) the feature fusion model can decode the imaging phenotypes representing NSCLC heterogeneity related to both EGFR mutation and patient NSCLC prognosis, and (3) high correlations exist between some deep image and radiomics features.

The impact of adjuvant EGFR-TKIs and 14-gene molecular assay on stage I non-small cell lung cancer with sensitive EGFR mutations

Background

Currently, the role of EGFR-TKIs as adjuvant therapy for stage I, especially IA NSCLC, after surgical resection remains unclear. We aimed to compare the effect of adjuvant EGFR-TKIs with observation in such patients by incorporating an established 14-gene molecular assay for risk stratification.

Methods

This retrospective cohort study was conducted at the First Affiliated Hospital of Guangzhou Medical University (Study ID: ChNCRCRD-2022-GZ01). From March 2013 to February 2019, completely resected stage I NSCLC (8th TNM staging) patients with sensitive EGFR mutation were included. Patients with eligible samples for molecular risk stratification were subjected to the 14-gene prognostic assay. Inverse probability of treatment weighting (IPTW) was employed to minimize imbalances in baseline characteristics.

Findings

A total of 227 stage I NSCLC patients were enrolled, with 55 in EGFR-TKI group and 172 in the observation group. The median duration of follow-up was 78.4 months. After IPTW, the 5-year DFS (HR = 0.30, 95% CI, 0.14-0.67; P = 0.003) and OS (HR = 0.26, 95% CI, 0.07-0.96; P = 0.044) of the EGFR-TKI group were significantly better than the observation group. For subgroup analyses, adjuvant EGFR-TKIs were associated with favorable 5-year DFS rates in both IA (100.0% vs. 84.5%; P = 0.007), and IB group (98.8% vs. 75.3%; P = 0.008). The 14-gene assay was performed in 180 patients. Among intermediate-high-risk patients, EGFR-TKIs were associated with a significant improvement in 5-year DFS rates compared to observation (96.0% vs. 70.5%; P = 0.012), while no difference was found in low-risk patients (100.0% vs. 94.9%; P = 0.360).

Interpretation

Our study suggested that adjuvant EGFR-TKI might improve DFS and OS of stage IA and IB EGFR-mutated NSCLC, and the 14-gene molecular assay could help patients that would benefit the most from treatment.

Funding

This work was supported by China National Science Foundation (82022048, 82373121).

The Evolving Role for Systemic Therapy in Resectable Non-small Cell Lung Cancer

During the last 2 decades, the understanding of non-small cell lung cancer (NSCLC) has evolved from a purely histologic classification system to a more complex model synthesizing clinical, histologic, and molecular data. Biomarker-driven targeted therapies have been approved by the United States Food and Drug Administration for patients with metastatic NSCLC harboring specific driver alterations in EGFR, HER2, KRAS, BRAF, MET, ALK, ROS1, RET, and NTRK. Novel immuno-oncology agents have contributed to improvements in NSCLC-related survival at the population-level. However, only in recent years has this nuanced understanding of NSCLC permeated into the systemic management of patients with resectable tumors.

[Consensus on Postoperative Recurrence Prediction of Non-small Cell Lung Cancer Based on Molecular Markers]

Significant progress has been made in lung cancer screening, surgery, chemoradiation, targeted therapy, and immunotherapy recently. Surgical resection is the most important treatment for localized non-small cell lung cancer (NSCLC) so far, but there are still many patients who develop local recurrence or distant metastases within 5 years of surgery. Currently, the risk factors of recurrence in patients with NSCLC are mainly based on clinical and pathological features, which hardly identify patients at high risk of recurrence accurately. With the development of new detection technologies, a number of molecular markers that may have a predictive risk of recurrence in NSCLC have been discovered over the years. In order to summarize the molecular markers related to postoperative recurrence in NSCLC patients, we have formulated a consensus on the prediction of postoperative recurrence of NSCLC based on molecular markers. This consensus mainly focuses on the early stage NSCLC patients, discusses and summarizes the risk factors of disease recurrence from the molecular level. It is hoped that more and more valuable information can be provided for the management of patients, so as to provide more guidance for the perioperative management of the patients with early stage NSCLC in the future.
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Germline mutations in high penetrance genes are associated with worse clinical outcomes in patients with non-small cell lung cancer

Objective

To determine the frequency of pathogenic mutations in high-penetrance genes (HPGs) in patients with non-small cell lung cancer (NSCLC) and identify whether such mutations are associated with clinicopathologic outcomes.

Methods

Patients with NSCLC who had consented to participate in a linked clinical database and biorepository underwent germline DNA sequencing using a next-generation sequencing panel that included cancer-associated HPGs and cancer risk-associated single nucleotide polymorphisms (SNPs). These data were linked to the clinical database to assess for associations between germline variants and clinical phenotype using Fisher's exact test and multivariable logistic and Cox regression.

Results

We analyzed 151 patients, among whom 33% carried any pathogenic HPG mutation and 23% had a genetic risk score (GRS) >1.5. Among the patients without any pathogenic mutation, 31% were at cancer stage II or higher, compared with 55% of those with 2 types of HPG mutations (P = .0293); 40% of patients with both types of HPG mutations had cancer recurrence, compared with 21% of patients without both types (P = .0644). In multivariable analysis, the presence of 2 types of HPG mutations was associated with higher cancer stage (odds ratio [OR], 3.32; P = .0228), increased recurrence of primary tumor (OR, 2.93; P = .0527), shorter time to recurrence (hazard ratio [HR], 3.03; P = .0119), and decreased cancer-specific (HR, 3.53; P = .0039) and overall survival (HR, 2.44; P = .0114).

Conclusions

The presence of mutations in HPGs is associated with higher cancer stage, increased risk of recurrence, and worse cancer-specific and overall survival in patients with NSCLC. Further large studies are needed to better delineate the role of HPGs in cancer recurrence and the potential benefit of adjuvant treatment in patients harboring such mutations.

Improved outcomes and staging in non-small-cell lung cancer guided by a molecular assay

There remains a critical need for improved staging of non-small-cell lung cancer, as recurrence and mortality due to undetectable metastases at the time of surgery remain high even after complete resection of tumors currently categorized as ‘early stage.’ A 14-gene quantitative PCR-based expression profile has been extensively validated to better identify patients at high-risk of 5-year mortality after surgical resection than conventional staging – mortality that almost always results from previously undetectable metastases. Furthermore, prospective studies now suggest a predictive benefit in disease-free survival when the assay is used to guide adjuvant chemotherapy decisions in early-stage non-small-cell lung cancer patients.

There is a need for improvement in the way early-stage non-small-cell lung cancers are staged and treated because many patients with ‘early-stage’ disease suffer high rates of cancer recurrence after surgery. In recent years, a specialized test has been developed to allow better characterization of a tumor's risk of recurrence based on the genes being expressed by tumor cells. Use of this test, in conjunction with standard staging methods, is better able to identify patients at high risk of cancer recurrence after surgery. Evidence suggests that giving chemotherapy to patients at high risk of recurrence after surgery reduces recurrence rates and improves long-term patient survival.