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New blood test accurately detects more than 50 types of cancer

In a study involving thousands of participants, a new blood test detected more than 50 types of cancer as well as their location within the body with a high degree of accuracy, according to an international team of researchers led by Dana-Farber Cancer Institute and the Mayo Clinic.

The results indicate that the test – which identified some particularly dangerous cancers that lack standard approaches to screening – can play a key role in early detection of cancer. Early detection can often be critical to successful treatment.

Developed by GRAIL Inc, the test uses next-generation sequencing to analyse the arrangement of chemical units called methyl groups on the DNA of cancer cells. Adhering to specific sections of DNA, methyl groups help control whether genes are active or inactive. In cancer cells, the placement of methyl groups, or methylation pattern, is often markedly different from that of normal cells – to the extent that abnormal methylation patterns are even more characteristic of cancer cells than genetic mutations are. When tumour cells die, their DNA, with methyl groups firmly attached, empties into the blood, where it can be analysed by the new test.

"Our previous work indicated that methylation-based tests outperform traditional DNA-sequencing approaches to detecting multiple forms of cancer in blood samples," said Dana-Farber's Dr Geoffrey Oxnard, co-lead author of the study with Dr Minetta Liu, of the Mayo Clinic. "The results of this study suggest that such assays could be a feasible way of screening people for a wide variety of cancers."

In the study, investigators used the test to analyse cell-free DNA (DNA from normal and cancerous cells that had entered the bloodstream upon the cells' death) in 6,689 blood samples, including 2,482 from people diagnosed with cancer and 4,207 from people without cancer. The samples from patients with cancer represented more than 50 cancer types, including breast, colorectal, oesophageal, gallbladder, bladder, gastric, ovarian, head and neck, lung, lymphoid leukaemia, multiple myeloma, and pancreatic cancer.

The overall specificity of the test was 99.3%, meaning that only 0.7% of the results incorrectly indicated that cancer was present. The sensitivity of the assay for 12 cancers that account for nearly two-thirds of US cancer deaths was 67.3%, meaning the test could find the cancer two-thirds of the time but a third of the time the test returned a negative result. Within this group, the sensitivity was 39% for patients with stage I cancer, 69% for those with stage II, 83% for those with stage III, and 92% for those with stage IV.

The stage I-III sensitivity across all 50 cancer types was 43.9%. When cancer was detected, the test correctly identified the organ or tissue where the cancer originated in more than 90% of cases – critical information for determining how the disease is diagnosed and managed.

"Our results show that this approach to testing cell-free DNA in blood can detect a broad range of cancer types at virtually any stage of the disease, with specificity and sensitivity approaching the level needed for population-level screening," Oxnard observed. "The test can be an important part of clinical trials for early cancer detection."

Abstract
Background: Early cancer detection could identify tumors when outcomes are superior at a time when outcomes are superior and treatment is less morbid. This prospective case-control sub-study (from NCT02889978 and NCT03085888) assessed the performance of targeted methylation analysis of circulating cell-free DNA (cfDNA) to detect and localize multiple cancer types across all stages at high specificity.
Participants and methods: The 6689 participants [2482 cancer (>50 cancer types), 4207 non-cancer] were divided into training and validation sets. Plasma cfDNA underwent bisulfite sequencing targeting a panel of >100 000 informative methylation regions. A classifier was developed and validated for cancer detection and tissue of origin (TOO) localization.

Results: Performance was consistent in training and validation sets. In validation, specificity was 99.3% [95% confidence interval (CI): 98.3% to 99.8%; 0.7% false-positive rate (FPR)]. Stage IeIII sensitivity was 67.3% (CI: 60.7% to 73.3%) in a pre-specified set of 12 cancer types (anus, bladder, colon/rectum, esophagus, head and neck, liver/bile-duct, lung, lymphoma, ovary, pancreas, plasma cell neoplasm, stomach), which account for w63% of US cancer deaths annually, and was 43.9% (CI: 39.4% to 48.5%) in all cancer types.
Detection increased with increasing stage: in the pre-specified cancer types sensitivity was 39% (CI: 27% to 52%) in stage I, 69% (CI: 56% to 80%) in stage II, 83% (CI: 75% to 90%) in stage III, and 92% (CI: 86% to 96%) in stage IV. In all cancer types sensitivity was 18% (CI: 13% to 25%) in stage I, 43% (CI: 35% to 51%) in stage II, 81% (CI: 73% to 87%) in stage III, and 93% (CI: 87% to 96%) in stage IV. TOO was predicted in 96% of samples with cancer-like signal; of those, the TOO localization was accurate in 93%.
Conclusions: cfDNA sequencing leveraging informative methylation patterns detected more than 50 cancer types across stages. Considering the potential value of early detection in deadly malignancies, further evaluation of this test is justified in prospective population-level studies.

Authors
MC Liu, GR Oxnard, EA Klein, C Swanton, MV Seiden, Steven R Cummings, Farnaz Absalan, Gregory Alexander, Brian Allen, Hamed Amini, Alexander M Aravanis, Siddhartha Bagaria, Leila Bazargan, John F Beausang, Jennifer Berman, Craig Betts, Alexander Blocker, Joerg Bredno, Robert Calef, Gordon Cann, Jeremy Carter, Christopher Chang, Hemanshi Chawla, Xiaoji Chen, Tom C Chien, Daniel Civello, Konstantin Davydov, Vasiliki Demas, Mohini Desai, Zhao Dong, Saniya Fayzullina, Alexander P Fields, Darya Filippova, Peter Freese, Eric T Fung, Sante Gnerre, Samuel Gross, Meredith Halks-Miller, Megan P Hall, Anne-Renee Hartman, Chenlu Hou, Earl Hubbell, Nathan Hunkapiller, Karthik Jagadeesh, Arash Jamshidi, Roger Jiang, Byoungsok Jung, TaeHyung Kim, Richard D Klausner, Kathryn N. Kurtzman, Mark Lee, Wendy Lin, Jafi Lipson, Hai Liu, Qinwen Liu, Margarita Lopatin, Tara Maddala, M Cyrus Maher, Collin Melton, Andrea Mich, Shivani Nautiyal, Jonathan Newman, Joshua Newman, Virgil Nicula, Cosmos Nicolaou, Ongjen Nikolic, Wenying Pan, Shilpen Patel, Sarah A Prins, Richard Rava, Neda Ronaghi, Onur Sakarya, Ravi Vijaya Satya, Jan Schellenberger, Eric Scott, Amy J Sehnert, Rita Shaknovich, Avinash Shanmugam, KC Shashidhar, Ling Shen, Archana Shenoy, Seyedmehdi Shojaee, Pranav Singh, Kristan K Steffen, Susan Tang, Jonathan M Toung, Anton Valouev, Oliver Venn, Richard T Williams, Tony Wu, Hui H Xu, Christopher Yakym, Xiao Yang, Jessica Yecies, Alexander S Yip, Jack Youngren, Jeanne Yue, Jingyang Zhang, Lily Zhang, Lori (Quan) Zhang, Nan Zhang, Christina Curtis, Donald A Berry

[link url="https://www.sciencedaily.com/releases/2020/03/200330203241.htm"]Dana-Farber Cancer Institute material[/link]

[link url="https://www.annalsofoncology.org/article/S0923-7534(20)36058-0/pdf"]Annals of Oncology abstract[/link]

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