Tissue of origin prediction for cancer of unknown primary using a targeted methylation sequencing panel.

RATIONALE: Cancer of unknown primary (CUP) is a group of rare malignancies with poor prognosis and unidentifiable tissue-of-origin. Distinct DNA methylation patterns in different tissues and cancer types enable the identification of the tissue of origin in CUP patients, which could help risk assessment and guide site-directed therapy. METHODS: Using genome-wide DNA methylation profile datasets from The Cancer Genome Atlas (TCGA) and machine learning methods, we developed a 200-CpG methylation feature classifier for CUP tissue of origin prediction (MFCUP). MFCUP was further validated with public-available methylation array data of 2977 specimens and targeted methylation sequencing of 78 Formalin-fixed paraffin-embedded (FFPE) samples from a single center. RESULTS: MFCUP achieved an accuracy of 97.2% in a validation cohort (n = 5923) representing 25 cancer types. When applied to an Infinium 450 K array dataset (n = 1052) and an Infinium EPIC (850 K) array dataset (n = 1925), MFCUP achieved an overall accuracy of 93.4% and 84.8%, respectively. Based on MFCUP, we established a targeted bisulfite sequencing panel and validated it with FFPE sections from 78 patients of 20 cancer types. This methylation sequencing panel correctly identified tissue of origin in 88.5% (69/78) of samples. We also found that the methylation levels of specific CpGs can distinguish one cancer type from others, indicating their potential as biomarkers for cancer diagnosis and screening. CONCLUSION: Our methylation-based cancer classifier and targeted methylation sequencing panel can predict tissue of origin in diverse cancer types with high accuracy.

Bioinformatics algorithm for lung adenocarcinoma based on macropinocytosis-related long noncoding RNAs as a reliable indicator for predicting survival outcomes and selecting suitable anti-tumor drugs.

As a highly conserved endocytic mechanism during evolution, macropinocytosis is enhanced in several malignant tumors, which promotes tumor growth by ingesting extracellular nutrients. Recent research has emphasized the crucial role of macropinocytosis in tumor immunity. In the present study, we established a new macropinocytosis-related algorithm comprising molecular subtypes and a prognostic signature, in which patients with lung adenocarcinoma (LUAD) were classified into different clusters and risk groups based on the expression of 16 macropinocytosis-related long noncoding RNAs. According to the molecular subtypes, we discovered that patients with LUAD in cluster1 had a higher content of stromal cells and immune cells, stronger intensity of immune activities, higher expression of PD1, PDL1, and HAVCR2, and a higher tumor mutational burden, while patients in cluster2 exhibited better survival advantages. Furthermore, the constructed prognostic signature revealed that low-risk patients showed better survival outcomes, earlier tumor stage, higher abundance of stromal cells and immune cells, higher immune activities, higher expression of PD1, PDL1, CTLA4, and HAVCR2, and more sensitivity to Paclitaxel and Erlotinib. By contrast, patients with high scores were more suitable for Gefitinib treatment. In conclusion, the novel algorithm that divided patients with LUAD into different groups according to their clusters and risk groups, which could provide theoretical support for predicting their survival outcomes and selecting drugs for chemotherapy, targeted therapy, and immunotherapy.

Nucleoprotein-based indirect enzyme-linked immunosorbent assay (indirect ELISA) for detecting antibodies specific to Ebola virus and Marbug virus.

Full-length nucleoproteins from Ebola and Marburg viruses were expressed as His-tagged recombinant proteins in Escherichia coli and nucleoprotein-based enzyme-linked immunosorbent assays (ELISAs) were established for the detection of antibodies specific to Ebola and Marburg viruses. The ELISAs were evaluated by testing antisera collected from rabbit immunized with Ebola and Marburg virus nucleoproteins. Although little cross-reactivity of antibodies was observed in anti-Ebola virus nucleoprotein rabbit antisera, the highest reactions to immunoglobulin G (IgG) were uniformly detected against the nucleoprotein antigens of homologous viruses. We further evaluated the ELISA's ability to detect antibodies to Ebola and Marburg viruses using human sera samples collected from individuals passing through the Guangdong port of entry. With a threshold set at the mean plus three standard deviations of average optical densities of sera tested, the ELISA systems using these two recombinant nucleoproteins have good sensitivity and specificity. These results demonstrate the usefulness of ELISA for diagnostics as well as ecological and serosurvey studies of Ebola and Marburg virus infection.