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Genome-Wide Sequencing Detects Early Stage Lung Cancer From Blood Samples

Fuerst, Mark L.

doi: 10.1097/01.COT.0000544200.02646.06
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CHICAGO—A blood test may be able to detect early-stage lung cancer, according to results from the large, ongoing Circulating Cell-Free Genome Atlas (CCGA) Study. This is one of the first studies to explore blood tests analyzing free-floating or cell-free DNA as a tool for early detection of cancer.

Comprehensive sequencing of plasma cell-free DNA generates high-quality data across the spectrum of genomic features, including copy number, methylation, single nucleotide variants/indels, that permitted non-invasive cancer detection. Assays detected lung cancer across stages, histologies, and populations.

“We're excited that initial results from the CCGA study show it is possible to detect early-stage lung cancer from blood samples using genome sequencing,” said lead author Geoffrey R. Oxnard, MD, Associate Professor of Medicine at Dana-Farber Cancer Institute and Harvard Medical School in Boston. “There is an unmet need globally for early detection tests for lung cancer that can be easily implemented by health care systems.” Oxnard presented the results at a press briefing at the 2018 ASCO Annual Meeting (Abstract 8501).

The current lung cancer screening paradigm is not widely adopted. “Low-dose computed tomography improves lung cancer mortality in high-risk individuals, but rate of clinical adoption remains low (1.9%),” said Oxnard.

Cell-free DNA-based tests represent an untapped opportunity for cancer detection. “Cancer detection using plasma cell-free DNA aims to identify a broader cancer signature rather than specific individual mutations. Genome-wide approaches offer additional information that allow early detection,” he noted.

Analysis of cell-free DNA from blood is already used to help choose targeted therapies, but such liquid biopsies are used only for patients with advanced lung cancer. Until recently, there has been limited evidence to show cell-free DNA analysis may be feasible for early detection of lung cancer.

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Study Details

CCGA is a prospective, longitudinal cohort study designed for early cancer detection. The CCGA study has enrolled more than 12,000 of the planned 15,000 participants (70% with cancer, 30% without cancer), across 141 sites in the U.S. and Canada. Oxnard reported on the first pre-planned sub-study from the CCGA, in which three prototype sequencing assays were performed on blood samples from approximately 1,700 participants, with both the first training and test set analyses.

Twenty different cancer types across all stages were included in the sub-study. Results from other cancers, including breast, gastrointestinal, gynecologic, blood, and other cancers, were presented separately at ASCO (Abstracts 536, 12021, and 12003).

In this initial sub-analysis, Oxnard and colleagues explored the ability of three different assays to detect cancer in 127 people with stage I-IV lung cancer. “Prototype sequencing assays were used to comprehensively characterize cancer-specific cell-free DNA signals,” said Oxnard. The three assays that were designed to detect cancer-defining signals (mutations and other genomic changes) that could be used in the development of an early cancer detection test are:

  • targeted sequencing to detect non-inherited (somatic) mutations, such as single nucleotide variants and small insertions and/or deletions;
  • whole genome sequencing (WGS) to detect somatic gene copy number changes; and
  • whole-genome bisulfite sequencing (WGBS) of cell-free DNA to detect abnormal cell-free DNA methylation patterns (epigenetic changes).
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Key Findings

Among the 127 participants with lung cancer, the biologic signal for lung cancer was comparable across the assays, and the signal increased with cancer stage. At 98 percent specificity, the WGBS assay detected 41 percent of early stage (stage I-IIIA) lung cancers and 89 percent of late-stage (stage IIIB-IV) cancers. The WGS assay was similarly effective, detecting 38 percent of early-stage cancers and 87 percent of late-stage cancers. The targeted assay detected 51 percent of early-stage cancers and 89 percent of late-stage cancers.

Initial results showed that all three prototype assays could detect lung cancer with a low rate of false-positive findings. Of the 580 control samples in the sub-study, five (less than 1%) participants had a cancer-like signal across all three assays. Of those five participants, two participants were subsequently diagnosed with cancer (one with stage III ovarian cancer, and one with stage II endometrial cancer), highlighting the potential for such a test to identify early-stage cancers.

“There was a consistent biological signal across lung cancer stages in training and test sets,” noted Oxnard. “Similar sensitivities were observed across the three assays, and replicated in an independent test set.”

In addition, for participants with lung cancer, more than 54 percent of somatic (non-inherited) mutations detected in the blood samples were derived from white blood cells and not from tumors. These mutations are likely due to natural aging processes (so-called clonal hematopoiesis of indeterminate potential) and will be important to consider when developing blood tests for early detection of cancer. Oxnard noted that “white blood cell-derived mutations and copy number variations are a significant source of potential false-positives that must be accounted for to obtain high specificity.”

The researchers are verifying these results in an independent group of approximately 1,000 participants from CCGA as part of the same sub-study.

“These are promising early results, and next steps are to further optimize the assays and validate results in a larger group of people,” stated Oxnard. With increased sample sizes, machine learning approaches are expected to improve assay performance.

“Together, these early results support the promise of using cell-free DNA-based assays to develop an early cancer detection test with high specificity,” Oxnard concluded. “Additional training and validation using optimized assays will be performed in remaining CCGA participants.”

Mark L. Fuerst is a contributing writer.

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