This study enrolled 87 NSCLC patients who underwent curative surgical resections (23 patients experienced relapses during follow-up). A total of 163 plasma samples were collected at 7 days and 6 months post-surgery and were used for both whole-genome sequencing (WGS). The WGS-based cell-free DNA (cfDNA) fragment profile was used to develop regularized Cox regression models, and the models’ performance was evaluated using leave-one-out cross-validation.

The ultra-sensitive and affordable fragmentomic assay has shown promising results in detecting patients who are at high risk of recurrence. The fragmentomic model was able to detect high-risk patients at 7 days and 6 months post-surgery with an increased risk of 4.6 times and 8.3 times, outperforming the targeted sequencing-based circulating mutations. The overall sensitivity for detecting patients with recurrence reached 78.3% while using both fragmentomics and circulating mutation results from 7 days and 6 months postsurgical, which increased from the 43.5% sensitivity by using only the circulating mutations.

“The non-invasive liquid biopsy assay can effectively detect landmark MRD, which could aid in making informed decisions for post-surgery treatment.”, says Dr. Hua Bao, author and director of Geneseeq Research Institute.

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A summary of Geneseeq-collaborated studies:

Poster Discussion WS08.21, EP16.01-025

Immune Evolution of Local and Distant Metastases and Underlying Molecular Mechanisms in Non-small Cell Lung Cancer

Track: Tumor Biology and Biomarkers – Immune Biology & Immunotherapy

The immune profile is a crucial player in cancer development and metastasis. However, the understanding of the evolution of immune profile from primary non-small cell lung cancers (NSCLC) to metastases and the underlying molecular mechanisms, as well as the difference in immune evolution in local metastasis and distant metastasis is limited so far. In collaboration with researchers from Guangdong Provincial People’s Hospital, whole-exome sequencing (WES) and immunohistochemistry of CD8, CD4 and PD-L1 were performed with 73 samples including 29 primary, 9 lymph nodes, 9 local (pleural) and 26 distant (brain, bone and adrenal gland) metastases from 41 NSCLS patients. The study showed that acquired DNA damage repair deficiency is responsible for increased chromosomal instability in distant metastases of NSCLC. CD8 level is negatively correlated with chromosomal instability and decreased in distant metastases. Distant and local metastases had different immune profiles while the immune and genetic background of primary tumors may affect metastatic destinations.

Poster EP16.02-024

Plasma ctDNA Organ-Specific Genomic Patterns and Origination Analysis in Advanced Non-Small Cell Lung Cancer

Track: Tumor Biology and Biomarkers – Minimally Invasive Biomarkers

The utility of circulating tumor DNA (ctDNA) has been proven in guiding targeted therapies, predicting treatment responses, and monitoring disease recurrence. However, the patterns of ctDNA mutations and their origins remained not fully investigated in advanced cancers. In collaboration with researchers from Guangdong Provincial People’s Hospital and Zhongshan City People’s Hospital, the authors collected 23 baseline treatment-naïve plasma samples and 93 tissue samples including 40 regions from 23 primary tumors and 53 regions from 36 metastatic tumors from 23 NSCLC patients. A total of 40873 mutations were detected in tissue samples using WES. For each patient, the mutations were classified into three types: primary tumor-private (PT-private), metastasis-private (MT-private), and shared by primaries and metastases (shared) based on their presence in tissue samples. This study revealed that patients with locoregional metastases had more MT-private mutations detected in plasma, whereas those with distant metastases showed more PT-private mutations in plasma.

Poster EP01.01-011

Utility of Arm-level cfDNA Fragment Size Distribution in the Early Detection of Lung Cancer and Pan Cancer

Track: Early Detection and Screening – Biomarkers

Early detection of lung cancer is critical for improving the prognosis of patients. cfDNA fragmentomics has shown potential in the detection of lung cancer. However, existing predictive models lack extensive cross-study validation, and the robustness and generalizability of the features and models should be tested and improved.  In collaboration with researchers from Nanjing Drum Tower Hospital, a local lung cancer cohort consisting of 56 lung cancer patients (93% stage I) and 106 healthy volunteers were employed and then divided into a training cohort and a temporal validation cohort. Two types of cfDNA fragment features were extracted from whole-genome sequencing (WGS) results of the samples: window-level fragment size summary (WINDOW-FSS), which summarizes the fragment size distribution as short fragments (100-150bp) and total fragment coverage at 5MB window-level. And the newly developed arm-level fragment size distribution (ARM-FSD), which separately calculates the coverage of fragments with 5bp as a step at the arm level and retains the size distribution information. In addition, the derived PCA components and autoencoder deep features were also extracted and used to construct machine learning models for lung cancer prediction. The performance of the models was validated by the temporal validation cohort and two independent external cohorts. The detection value of the two cfDNA features was first assessed in a published pan-cancer cohort as training and validated using three separate cohorts.  Through multiple cohort evaluations, our newly-developed ARM-FSD demonstrated as a robust and generalized biomarker and has potential in the early detection of lung cancer and pan-cancer.

Poster EP08.02-073

Clinical and Genomic Analysis of Primary and Secondary MET Fusions with Intact Kinase Domain in Lung Cancer

Track: Metastatic Non-small Cell Lung Cancer – Molecular Targeted Treatments

Several kinase gene fusions, including MET, have been uncovered as oncogenic alterations in lung cancer beyond the well-studied ALK, RET, and ROS1 fusions. As amplification and exon 14 skipping were the two most frequent MET alterations, MET fusions are rarely reported and less investigated. Though the potential role of MET fusions as a resistance mechanism to tyrosine kinase
inhibitors (TKIs) has been proposed in a series of case reports, comprehensive studies remain to be performed in large cohorts. Using Geneseeq targeted panels, the author comprehensively investigated 44 patients harboring MET fusions with intact kinase domain (KD) in a large lung cancer cohort. Interestingly, both primary and secondary MET fusions were identified in this cohort,  which might serve the role of oncogene and resistance mechanism to TKIs respectively.
The study also showed that targeted sequencing with multiple sample types could promote personalized treatment by providing comprehensive molecular portraits.

Poster EP08.02-073

RET fusions as primary oncogenic drivers and secondary acquired resistance to EGFR TKI in a large cohort of non-small-cell lung cancers

Track: Metastatic Non-small Cell Lung Cancer – Molecular Targeted Treatments

RET fusions occur in 1-2% of non-small-cell lung cancers (NSCLCs), which are associated with unique clinical features and poor prognosis and may contribute to resistance to EGFR-TKIs. Despite the development of highly potent RET inhibitors, the genetic architecture of primary and secondary RET fusions in NSCLCs remains to be systematically elucidated. The authors systematically evaluated the genetic landscape underlying RET fusions as a rare driver gene and provide important insights into secondary resistance to EGFR TKIs in Chinese NSCLCs. These will be important considerations in improving the efficacy and clinical outcome of existing RET inhibitors and facilitating the development of new therapeutics. 

Poster EP16.03-044

Genomic evidence depicting clonal evolution of lung adenosquamous carcinoma

Track: Tumor Biology and Biomarkers – Molecular Profiling and Targeted Therapeutics

Adenosquamous carcinoma (ASC) is a rare subtype of NSCLC containing both adenocarcinoma (AC) and squamous cell carcinoma (SCC) components. However, the genomic background, tumor origins, and mechanisms of ASC are not fully understood. In this Geneseeq-collaborated study, 33 micro-dissected surgical ASC and seven primary EGFR-positive SCC samples were subjected to WES. The genomic profiles, mutational signatures, and evolutionary origins were analyzed to depict clonal relationships. Asian lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) cases were obtained from The Cancer Genome Atlas for comparison. A xenograft model was further established to show the histologic transformation. A separate cohort of EGFR-positive LUAD, ASC, and LUSC patients was evaluated for their response to tyrosine kinase inhibitors. The results showed that AC and SCC components of ASC monoclonal originated through genomic and phylogenetic analyses. EGFR-positive NSCLC subtypes share similar mutation profiles and might undergo phenotypic transitions. First-line TKI should be considered for EGFR-positive ASC and LUSC patients to obtain optimal clinical benefit.

The post GENESEEQ AND COLLABORATORS SHARE NEW FINDINGS AT WORLD CONFERENCE ON LUNG CANCER 2022 appeared first on Geneseeq Technology Inc. | A Precision Oncology Company.

This study enrolled 292 stage I LUAD patients from three medical centers in China as well as 230 healthy volunteers. The LUAD patients included invasive adenocarcinoma (ADC) and minimally invasive adenocarcinoma (MIA). The cfDNA was prepared from the plasma samples, followed by whole-genome sequencing (WGS). Multiple cfDNA fragmentomic motif features and machine learning algorithms were investigated to select the best model. During this process, the participants from Center I were randomly assigned to the training and internal validation cohorts for model construction and cutoff determination. The cancer patients from Centers II and III were assigned to the external validation cohort with 40 healthy controls for independent validation.

A novel 6bp-breakpoint-motif feature using the logistic regression model reached 98.0% sensitivity and 94.7% specificity in the internal validation cohort (Area Under the Curve AUC: 0.985), and 92.5% sensitivity and 90.0% specificity in the external validation cohort (AUC: 0.954), consistently outperforming other cfDNA-based methods for stage I lung adenocarcinoma detection. Notably, this assay is sensitive for early-stage (e.g., 100% sensitivity for MIA) and <1 cm (92.9%-97.7% sensitivity) tumors. The predictive power remained high with 0.5× WGS (AUC: 0.977 and 0.931 for internal and external cohorts). These results justified the cfDNA breakpoint motif-based machine learning model for detecting early-stage LUAD, especially the MIA and very small-size tumors.

“Noninvasive detection of early-stage lung cancer using plasma cfDNA has attracted increasing attention and is still in progress for leveraging its performance. Optimal cfDNA features and machine learning algorithms could improve the prediction power and need to be intensively tested in the clinical settings”, says Dr. Hua Bao, author and the Associate Dean of Geneseeq Research Institute.

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