1501 Background: Delays in cancer diagnosis can lead to increased mortality, leading to specialized diagnostic pathways for symptomatic patients when cancer is suspected. Identification of circulating tumour DNA can stratify individuals into those more or less likely to have cancer and predict the cancer origin. This could both expedite cancer diagnosis and reduce harm and inefficient investigation in those who do not have cancer. We evaluated the performance of a next-generation sequencing MCED test (GRAIL, LLC) using cell-free DNA (cfDNA) isolated from whole blood in symptomatic patients referred to cancer diagnostic clinics by their primary care physician. Methods: Patients referred for urgent imaging, endoscopy or other diagnostic modalities to investigate symptoms suspicious for cancer were invited to take part. Participants with non-specific symptoms or being tested for lung, gynaecological, upper gastrointestinal (GI) or lower GI cancers gave a blood sample on the day they attended for urgent standard of care investigations. cfDNA was isolated from blood samples and stored until the MCED test was performed in batches, blinded to clinical outcome. The test’s predictions (cancer signal detected yes/no; predicted signal origin) were compared with the diagnosis obtained by standard care to establish the positive and negative predictive value (PPV & NPV), sensitivity and specificity across the whole study population, by referral pathway, and by presenting symptom. In addition, sensitivity was analysed by cancer site and stage. Results: 6238 participants were recruited over 5 months from the 5 clinical pathways at 44 hospital sites in England and Wales. 5461 individuals had an MCED test result and diagnostic outcome and were evaluable. Mean age was 62.1 years (SD, 13.8), 3609 (66.1%) female, 2533 (46.4%) current or former smokers. 368 (6.7%) evaluable patients had a cancer diagnosed. The MCED test detected a cancer signal in 323 cases, 244 in whom cancer was diagnosed and 79 where it was not, yielding a PPV of 75.5% (95% CI 70.5-80.1%), NPV 97.6% (97.1-98.0%), sensitivity 66.3% (61.2-71.1%), and specificity 98.4% (98.1-98.8%). Sensitivity increased with increasing age and cancer stage, from 24.2% (16.0-34.1%) in Stage I to 95.3% (88.5-98.7%) in Stage IV. Sensitivity 80.4% (66.1-90.6%) and NPV 99.1% (98.2-99.6%) were highest for patients referred with symptoms qualifying for the upper GI pathway. Conclusions: This is the first large-scale prospective evaluation of an MCED test in a symptomatic population. These data provide the basis for a prospective, interventional study in patients presenting to primary care with non-specific signs and symptoms with low, but higher than background, probability of being due to cancer. Study data are also being used to enhance the negative predictive value of the current MCED classifier for a symptomatic population. Clinical trial information: ISRCTN10226380 .

Background Analysis of circulating tumour DNA could stratify cancer risk in symptomatic patients. We aimed to evaluate the performance of a methylation-based multicancer early detection (MCED) diagnostic test in symptomatic patients referred from primary care. Methods We did a multicentre, prospective, observational study at National Health Service (NHS) hospital sites in England and Wales. Participants aged 18 or older referred with non-specific symptoms or symptoms potentially due to gynaecological, lung, or upper or lower gastrointestinal cancers were included and gave a blood sample when they attended for urgent investigation. Participants were excluded if they had a history of or had received treatment for an invasive or haematological malignancy diagnosed within the preceding 3 years, were taking cytotoxic or demethylating agents that might interfere with the test, or had participated in another study of a GRAIL MCED test. Patients were followed until diagnostic resolution or up to 9 months. Cell-free DNA was isolated and the MCED test performed blinded to the clinical outcome. MCED predictions were compared with the diagnosis obtained by standard care to establish the primary outcomes of overall positive and negative predictive value, sensitivity, and specificity. Outcomes were assessed in participants with a valid MCED test result and diagnostic resolution. SYMPLIFY is registered with ISRCTN (ISRCTN10226380) and has completed follow-up at all sites. Findings 6238 participants were recruited between July 7 and Nov 30, 2021, across 44 hospital sites. 387 were excluded due to staff being unable to draw blood, sample errors, participant withdrawal, or identification of ineligibility after enrolment. Of 5851 clinically evaluable participants, 376 had no MCED test result and 14 had no information as to final diagnosis, resulting in 5461 included in the final cohort for analysis with an evaluable MCED test result and diagnostic outcome (368 [6 & BULL;7%] with a cancer diagnosis and 5093 [93 & BULL;3%] without a cancer diagnosis). The median age of participants was 61 & BULL;9 years (IQR 53 & BULL;4-73 & BULL;0), 3609 (66 & BULL;1%) were female and 1852 (33 & BULL;9%) were male. The MCED test detected a cancer signal in 323 cases, in whom 244 cancer was diagnosed, yielding a positive predictive value of 75 & BULL;5% (95% CI 70 & BULL;5-80 & BULL;1), negative predictive value of 97 & BULL;6% (97 & BULL;1-98 & BULL;0), sensitivity of 66 & BULL;3% (61 & BULL;2-71 & BULL;1), and specificity of 98 & BULL;4% (98 & BULL;1-98 & BULL;8). Sensitivity increased with increasing age and cancer stage, from 24 & BULL;2% (95% CI 16 & BULL;0-34 & BULL;1) in stage I to 95 & BULL;3% (88 & BULL;5-98 & BULL;7) in stage IV. For cases in which a cancer signal was detected among patients with cancer, the MCED test's prediction of the site of origin was accurate in 85 & BULL;2% (95% CI 79 & BULL;8-89 & BULL;3) of cases. Sensitivity 80 & BULL;4% (95% CI 66 & BULL;1-90 & BULL;6) and negative predictive value 99 & BULL;1% (98 & BULL;2-99 & BULL;6) were highest for patients with symptoms mandating investigation for upper gastrointestinal cancer. Interpretation This first large-scale prospective evaluation of an MCED diagnostic test in a symptomatic population demonstrates the feasibility of using an MCED test to assist clinicians with decisions regarding urgency and route of referral from primary care. Our data provide the basis for a prospective, interventional study in patients presenting to primary care with non-specific signs and symptoms.

Background . Chronic lymphocytic leukaemia (CLL) is always preceded by preclinical clonal B-cell disorders such as monoclonal B-cell lymphocytosis (MBL). Pre-malignant clonal B-cells are identifiable in asymptomatic individuals, a minority of whom will progress to symptomatic CLL. While some people remain at pre-cancerous or asymptomatic early stage CLL, others experience clinically aggressive disease. There is currently no method to effectively stratify individuals at higher risk of developing symptomatic CLL. Despite recent advances in treatment options available, the disease remains incurable. Therefore, we need to expand our knowledge and improve current classification methods. Here, we propose a molecular classifier using whole genome sequencing (WGS). This classifier was obtained by performing genomic characterization in pre-malignancy / early stages of the disease and comparing the genomic subgroups with those of symptomatic CLL. Methods . Individuals with newly diagnosed monoclonal B-cell lymphocytosis and early asymptomatic chronic lymphocytic leukaemia were enrolled in the OXPLORED clinical trial (Oxford Pre-cancerous Lymphoproliferative Disorders: Analysis and Interception study). We performed WGS in 400 samples from 200 individuals (sorted CD19+ B-cells as tumour, and matched salivary DNA as germline) to detect somatic alterations. We derived immunoglobulin heavy chain variable (IGHV) mutational status, stereotype and an additional 186 genomic features as previously described (Robbe*, Ridout* et al. Nature Genetics 2022) including known and recently discovered candidate drivers of CLL, recurrent structural variants, mutational signatures, genomic complexity measures, mutational burden, and pathway alterations. All the data was compiled into a matrix to extract meaningful sets of features to cluster patients' genomes using non-negative matrix factorization (NMF). Genomic findings were compared to the largest CLL whole genome cohort of symptomatic patients requiring frontline treatment (n=443). Results . The IGHV mutational status was found unmutated in 31% of individuals and hypermutated in 69% (excluding missing data for 6 genomes). Next, we considered mutations and CNAs in 58 common CLL drivers and 34 regions with recurrent CNAs. Although numbers were lower than in frontline CLL, most individuals presented at least one driver (86%) or more (57%) (by comparison, the CLL frontline cohort presented at least one CLL driver in 98% of patients). Genomic complexity, defined as 4 or more CNAs was detected in 12%, and complex genome defined as the presence of both CN gains and CN losses in 22%, indicating that newly diagnosed monoclonal B-cell lymphocytosis and early asymptomatic CLL present a relatively high degree of genomic complexity similar to what was observed in frontline CLL. The most common driver was del13q (60%), including as a sole driver in a third of these genomes. Other recurrent alterations were IGLL5 mutations (20%), trisomy 12 (9%), and mutations in MYD88 (8%), CREBBP (5%), NOTCH1 (5%), and SPEN (5%). Noncoding elements were also found mutated, including 30 promoters (including BIRC3 in 7%), five UTRs and eight enhancers, including BCL6 and PAX5 enhancers in 18% and 3.4% of individuals, respectively. When comparing this cohort with CLL genomes, we found that alterations in the main cancer pathways were depleted in OXPLORED, including known drivers such as ATM, NOTCH1, SF3B1. Finally, moving away from single-alteration grouping, we clustered the 643 genomes (443 CLL + 200 OXPLORED) using 186 genomic features by applying NMF. Importantly, we found distinct genomic profiles in the early disease cohort, including a subgroup like symptomatic CLL at frontline and another distinct subgroup, hinting towards identifying a genomic subgroup at higher risk of progressing to CLL. Conclusion: The comprehensive characterisation of genomic events that determine progression to malignancy are essential to understand the mechanisms of disease progression. Our study opens new horizons towards identifying individuals at higher risk and might pinpoint to individuals who need early intervention with curative intent. Therefore, we propose to analyse newly generated whole-genome sequencing (WGS) data to establish genomic subgroups in early CLL / pre-malignancy stages.