In cancer, epithelial-mesenchymal transition (EMT) is associated with metastasis. Characterizing EMT phenotypes in circulating tumor cells (CTCs) has been challenging because epithelial marker-based methods have typically been used for the isolation and detection of CTCs from blood samples. The aim of this study was to use the optimized CanPatrol CTC enrichment technique to classify CTCs using EMT markers in different types of cancers. The first step of this technique was to isolate CTCs via a filter-based method; then, an RNA in situ hybridization (RNA-ISH) method based on the branched DNA signal amplification technology was used to classify the CTCs according to EMT markers. Our results indicated that the efficiency of tumor cell recovery with this technique was at least 80%. When compared with the non-optimized method, the new method was more sensitive and more CTCs were detected in the 5-ml blood samples. To further validate the new method, 164 blood samples from patients with liver, nasopharyngeal, breast, colon, gastric cancer, or non-small-cell lung cancer (NSCLC) were collected for CTC isolation and characterization. CTCs were detected in 107(65%) of 164 blood samples, and three CTC subpopulations were identified using EMT markers, including epithelial CTCs, biophenotypic epithelial/mesenchymal CTCs, and mesenchymal CTCs. Compared with the earlier stages of cancer, mesenchymal CTCs were more commonly found in patients in the metastatic stages of the disease in different types of cancers. Circulating tumor microemboli (CTM) with a mesenchymal phenotype were also detected in the metastatic stages of cancer. Classifying CTCs by EMT markers helps to identify the more aggressive CTC subpopulation and provides useful evidence for determining an appropriate clinical approach. This method is suitable for a broad range of carcinomas.

Cytokine release syndrome (CRS) is a major cause of the multi-organ injury and fatal outcome induced by SARS-CoV-2 infection in severe COVID-19 patients. Metabolism can modulate the immune responses against infectious diseases, yet our understanding remains limited on how host metabolism correlates with inflammatory responses and affects cytokine release in COVID-19 patients. Here we perform both metabolomics and cytokine/chemokine profiling on serum samples from healthy controls, mild and severe COVID-19 patients, and delineate their global metabolic and immune response landscape. Correlation analyses show tight associations between metabolites and proinflammatory cytokines/chemokines, such as IL-6, M-CSF, IL-1α, IL-1β, and imply a potential regulatory crosstalk between arginine, tryptophan, purine metabolism and hyperinflammation. Importantly, we also demonstrate that targeting metabolism markedly modulates the proinflammatory cytokines release by peripheral blood mononuclear cells isolated from SARS-CoV-2-infected rhesus macaques ex vivo, hinting that exploiting metabolic alterations may be a potential strategy for treating fatal CRS in COVID-19.

Background We aim to investigate the profile of acute antibody response in COVID-19 patients, and provide proposals for the usage of antibody test in clinical practice.Methods A multi-center cross-section study (285 patients) and a single-center follow-up study (63 patients) were performed to investigate the feature of acute antibody response to SARS-CoV-2. A cohort of 52 COVID-19 suspects and 64 close contacts were enrolled to evaluate the potentiality of the antibody test. ResultsThe positive rate for IgG reached 100% around 20 days after symptoms onset.The median day of seroconversion for both lgG and IgM was 13 days after symptoms onset. Seroconversion of IgM occurred at the same time, or earlier, or later than that of IgG. IgG levels in 100% patients (19/19) entered a platform within 6 days after seroconversion. The criteria of "IgG seroconversion" and "≥ 4-fold increase in the IgG titers in sequential samples" together diagnosed 82.9% (34/41) of the patients.Antibody test aided to confirm 4 patients with COVID-19 from 52 suspects who failed to be confirmed by RT-PCR and 7 patients from 148 close contacts with negative RT-PCR. ConclusionIgM and IgG should be detected simultaneously at the early phase of infection. The serological diagnosis criterion of seroconversion or the "≥ 4-fold increase in the IgG titer" is suitable for a majority of COVID-19 patients. Serologic test is helpful for the diagnosis of SARS-CoV-2 infection in suspects and close contacts.

The ISGC classifier could effectively predict recurrence and survival of GC, and complemented the prognostic value of the TNM staging system. Moreover, the ISGC might be a useful predictive tool to identify stage II and III GC patients who would benefit from adjuvant chemotherapy.