statement: In a series of 51 patients with chest CT and RT-PCR assay performed within 3 days, the sensitivity of CT for COVID-19 infection was 98% compared to RT-PCR sensitivity of 71% (p<.001).

Circulating tumor DNA (ctDNA) provides a potential non-invasive biomarker for cancer diagnosis and prognosis, but whether it could reflect tumor heterogeneity and monitor therapeutic responses in hepatocellular carcinoma (HCC) is unclear. Focusing on 574 cancer genes known to harbor actionable mutations, we identified the mutation repertoire of HCC tissues, and monitored the corresponding ctDNA features in blood samples to evaluate its clinical significance. Analysis of 3 HCC patients' mutation profiles revealed that ctDNA could overcome tumor heterogeneity and provide information of tumor burden and prognosis. Further analysis was conducted on the 4th HCC case with multiple lesion samples and sequential plasma samples. We identified 160 subclonal SNVs in tumor tissues as well as matched peritumor tissues with PBMC as control. 96.9% of this patient's tissue mutations could be also detected in plasma samples. These subclonal SNVs were grouped into 9 clusters according to their trends of cellular prevalence shift in tumor tissues. Two clusters constituted of tumor stem somatic mutations showed circulating levels relating with cancer progression. Analysis of tumor somatic mutations revealed that circulating level of such tumor stem somatic mutations could reflect tumor burden and even predict prognosis earlier than traditional strategies. Furthermore, HCK (p.V174M), identified as a recurrent/metastatic related mutation site, could promote migration and invasion of HCC cells. Taken together, study of mutation profiles in biopsy and plasma samples in HCC patients showed that ctDNA could overcome tumor heterogeneity and real-time track the therapeutic responses in the longitudinal monitoring.Hepatocellular carcinoma (HCC), one of the extraordinarily heterogeneous malignancy diseases, ranks the third leading cause of cancer-related death in China. 1 Unlike most other solid tumors, majority of HCC cases were developed with a history of cirrhosis due to chronic HBV or HCV infections. 2,3 Surgical resection was demonstrated to be the first choice for HCC treatment according to the clinical experiences of the past 50 years. 4 However, the prognosis of HCC remains poor owing to high recurrent/metastatic rate after curative resection, since some of these patients could develop multiple tumor lesions, portal vein tumor thrombus (PVTT), lymph node metastases or other distant metastases. 5,6 The majority

RT-PCR is the primary method to diagnose COVID-19 and is also used to monitor the disease course. This approach, however, suffers from false negatives due to RNA instability and poses a high risk to medical practitioners. Here, we investigated the potential of using serum proteomics to predict viral nucleic acid positivity during COVID-19. We analyzed the proteome of 275 inactivated serum samples from 54 out of 144 COVID-19 patients and shortlisted 42 regulated proteins in the severe group and 12 in the non-severe group. Using these regulated proteins and several key clinical indexes, including days after symptoms onset, platelet counts, and magnesium, we developed two machine learning models to predict nucleic acid positivity, with an AUC of 0.94 in severe cases and 0.89 in non-severe cases, respectively. Our data suggest the potential of using a serum protein-based machine learning model to monitor COVID-19 progression, thus complementing swab RT-PCR tests. More efforts are required to promote this approach into clinical practice since mass spectrometry-based protein measurement is not currently widely accessible in clinic.