Lin Wang

Conventional tumor markers for non-invasive diagnosis of gastric cancer (GC) exhibit insufficient sensitivity and specificity to facilitate detection of early gastric cancer (EGC). We aimed to identify EGC-specific exosomal lncRNA biomarkers that are highly sensitive and stable for the non-invasive diagnosis of EGC. Hence, in the present study, exosomes from the plasma of five healthy individuals and ten stage I GC patients and from culture media of four human primary stomach epithelial cells and four gastric cancer cells (GCCs) were isolated. Exosomal RNA profiling was performed using RNA sequencing to identify EGC-specific exosomal lncRNAs. A total of 79 and 285 exosomal RNAs were expressed at significantly higher levels in stage I GC patients and GCCs, respectively, than that in normal controls. Through combinational analysis of the RNA sequencing results, we found two EGC-specific exosomal lncRNAs, lncUEGC1 and lncUEGC2, which were further confirmed to be remarkably up-regulated in exosomes derived from EGC patients and GCCs. Furthermore, stability testing demonstrates that almost all the plasma lncUEGC1 was encapsulated within exosomes and thus protected from RNase degradation. The diagnostic accuracy of exosomal lncUEGC1 was evaluated, and lncUEGC1 exhibited AUC values of 0.8760 and 0.8406 in discriminating EGC patients from healthy individuals and those with premalignant chronic atrophic gastritis, respectively, which was higher than the diagnostic accuracy of carcinoembryonic antigen. Consequently, exosomal lncUEGC1 may be promising in the development of highly sensitive, stable, and non-invasive biomarkers for EGC diagnosis.

Abstract Early cancer detection greatly increases the chances for successful treatment, but available diagnostics for some tumours, including lung adenocarcinoma (LA), are limited. An ideal early-stage diagnosis of LA for large-scale clinical use must address quick detection, low invasiveness, and high performance. Here, we conduct machine learning of serum metabolic patterns to detect early-stage LA. We extract direct metabolic patterns by the optimized ferric particle-assisted laser desorption/ionization mass spectrometry within 1 s using only 50 nL of serum. We define a metabolic range of 100–400 Da with 143 m/z features. We diagnose early-stage LA with sensitivity~70–90% and specificity~90–93% through the sparse regression machine learning of patterns. We identify a biomarker panel of seven metabolites and relevant pathways to distinguish early-stage LA from controls ( p < 0.05). Our approach advances the design of metabolic analysis for early cancer detection and holds promise as an efficient test for low-cost rollout to clinics.

BACKGROUND: Recurrence and/or metastasis occurs in more than half of patients with head and neck squamous cell carcinoma (HNSCC), and these events pose the greatest threats to long-term survival. We set out to identify genetic alterations that underlie recurrent/metastatic HNSCC. METHODS: Whole-exome sequencing (WES) was performed on genomic DNA extracted from fresh-frozen whole blood and patient-matched tumor pairs from 13 HNSCC patients with synchronous lymph node metastases and 10 patients with metachronous recurrent tumors. Mutational concordance within and between tumor pairs was used to analyze the spatiotemporal evolution of HNSCC in individual patients and to identify potential therapeutic targets for functional evaluation. RESULTS: Approximately 86% and 60% of single somatic nucleotide variants (SSNVs) identified in synchronous nodal metastases and metachronous recurrent tumors, respectively, were transmitted from the primary index tumor. Genes that were mutated in more than one metastatic or recurrent tumor, but not in the respective primary tumors, include C17orf104, inositol 1,4,5-trisphosphate receptor, type 3 (ITPR3), and discoidin domain receptor tyrosine kinase 2 (DDR2). Select DDR2 mutations have been shown to confer enhanced sensitivity to SRC-family kinase (SFK) inhibitors in other malignancies. Similarly, HNSCC cell lines harboring endogenous and engineered DDR2 mutations were more sensitive to the SFK inhibitor dasatinib than those with WT DDR2. CONCLUSION: In this WES study of patient-matched tumor pairs in HNSCC, we found synchronous lymph node metastases to be genetically more similar to their paired index primary tumors than metachronous recurrent tumors. This study outlines a compendium of somatic mutations in primary, metastatic, and/or recurrent HNSCC cancers, with potential implications for precision medicine approaches. FUNDING: National Cancer Institute, American Cancer Society, Agency for Science, Technology and Research of Singapore, and Gilead Sciences Inc.

Cardiovascular diseases lead to 31.5% of deaths globally, and particularly myocardial infarction (MI) results in 7.4 million deaths per year. Diagnosis of MI and monitoring for prognostic use are critical for clinical management and biomedical research, which require advanced tools with accuracy and speed. Herein, we developed a plasmonic gold nano-island (pGold) chip assay for diagnosis and monitoring of MI. On-chip microarray analysis of serum biomarkers (e.g., cardiac troponin I) afforded up to 130-fold enhancement of near-infrared fluorescence for ultra-sensitive and quantitative detection within controlled periods, using 10 μL of serum only. The pGold chip assay achieved MI diagnostic sensitivity of 100% and specificity of 95.54%, superior to the standard chemiluminescence immunoassay in cardiovascular clinics. Further, we monitored biomarker concentrations regarding percutaneous coronary intervention for prognostic purpose. Our work demonstrated a designed approach using plasmonic materials for enhanced diagnosis and monitoring for prognostic use towards point-of-care testing.

Lymph node metastasis (LNM), a common metastatic gastric-cancer (GC) route, is closely related to poor prognosis in GC patients. Bone marrow-derived mesenchymal stem cells (BM-MSCs) preferentially engraft at metastatic lesions. Whether BM-MSCs are specifically reprogrammed by LNM-derived GC cells (LNM-GCs) and incorporated into metastatic LN microenvironment to prompt GC malignant progression remains unknown. Herein, we found that LNM-GCs specifically educated BM-MSCs via secretory exosomes. Exosomal Wnt5a was identified as key protein mediating LNM-GCs education of BM-MSCs, which was verified by analysis of serum exosomes collected from GC patients with LNM. Wnt5a-enriched exosomes induced YAP dephosphorylation in BM-MSCs, whereas Wnt5a-deficient exosomes exerted the opposite effect. Inhibition of YAP signaling by verteporfin blocked LNM-GC exosome- and serum exosome-mediated reprogramming in BM-MSCs. Analysis of MSC-like cells obtained from metastatic LN tissues of GC patients (GLN-MSCs) confirmed that BM-MSCs incorporated into metastatic LN microenvironment, and that YAP activation participated in maintaining their tumor-promoting phenotype and function. Collectively, our results show that LNM-GCs specifically educated BM-MSCs via exosomal Wnt5a-elicited activation of YAP signaling. This study provides new insights into the mechanisms of LNM in GC and BM-MSC reprogramming, and will provide potential therapeutic targets and detection indicators for GC patients with LNM.