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Abstract Background Late detection of hepatocellular carcinoma (HCC) results in an overall 5-year survival rate of less than 16%. Liquid biopsy (LB) assays based on detecting circulating tumor DNA (ctDNA) might provide an opportunity to detect HCC early noninvasively. Increasing evidence indicates that ctDNA detection using mutation-based assays is significantly challenged by the abundance of white blood cell-derived mutations, non-tumor tissue-derived somatic mutations in plasma, and the mutational tumor heterogeneity. Methods Here, we employed concurrent analysis of cancer-related mutations, and their fragment length profiles to differentiate mutations from different sources. To distinguish persons with HCC (PwHCC) from healthy participants, we built a classification model using three fragmentomic features of ctDNA through deep sequencing of thirteen genes associated with HCC. Results Our model achieved an area under the curve (AUC) of 0.88, a sensitivity of 89%, and a specificity of 82% in the discovery cohort consisting of 55 PwHCC and 55 healthy participants. In an independent validation cohort of 54 PwHCC and 53 healthy participants, the established model achieved comparable classification performance with an AUC of 0.86 and yielded a sensitivity and specificity of 81%. Conclusions Our study provides a rationale for subsequent clinical evaluation of our assay performance in a large-scale prospective study.

Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (screening for the presence of tumor by methylation and size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (~0.55×) of cell-free DNA. We applied SPOT-MAS to 738 non-metastatic patients with breast, colorectal, gastric, lung, and liver cancer, and 1550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 73.9% and 62.3% for stages I and II, respectively, increasing to 88.3% for non-metastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening.

Objectives To establish the proportion of mild traumatic brain injury (mTBI) diagnosis among people presenting to an emergency department (ED), to determine the accuracy of recorded ED diagnoses. We also aimed to describe challenges in mTBI case identification and its acute hospital management. Design and setting A retrospective chart review of all ED attendances to a major trauma hospital, over a 9-month period (June 2015–February 2016). Participants Adults aged 18–65 years consecutively presenting to an ED. Primary outcome measures Proportion of mTBI diagnosis among ED attendances (ie, confirmed mTBI based on the WHO criteria or indeterminate mTBI based on secondary criteria), and proportion of accurately recorded mTBI diagnosis by ED clinicians (ie, ‘mTBI’, ‘concussion’). Results Of 30 479 ED attendances, 351 (1.15%) confirmed mTBI diagnosis and 180 (0.6%) indeterminate diagnosis were identified. Only 81 (23.1%) individuals with a confirmed mTBI had a ‘mTBI diagnosis’ clearly recorded in the medical notes. Of the allocated discharge diagnosis codes to the two identified cohorts, 89.8% were not indicative of mTBI. Intracranial injuries were found in 31 (8.5%) confirmed cases. Glasgow Coma Scale scores were consistently assessed in the ED but identified only 117 (33.3%) confirmed mTBI cases. Post-traumatic amnesia (PTA) testing was able to confirm acute cognitive impairment in 113 (62.1%) of those who were tested (182, 51.3%). Conclusions mTBI is a common, but an under-recognised cause for ED attendance. Despite challenges, the use of an operational definition such as the WHO diagnostic criteria can improve accuracy in mTBI identification. Acute management may be enhanced by rapid assessment of PTA. [ABSTRACT FROM AUTHOR]