BackgroundRecently, rapid advances have been made in metabolomics-based, easy-to-use early cancer detection methods using blood samples. Among metabolites, profiling of plasma free amino acids (PFAAs) is a promising approach because PFAAs link all organ systems and have important roles in metabolism. Furthermore, PFAA profiles are known to be influenced by specific diseases, including cancers. Therefore, the purpose of the present study was to determine the characteristics of the PFAA profiles in cancer patients and the possibility of using this information for early detection.Methods and FindingsPlasma samples were collected from approximately 200 patients from multiple institutes, each diagnosed with one of the following five types of cancer: lung, gastric, colorectal, breast, or prostate cancer. Patients were compared to gender- and age- matched controls also used in this study. The PFAA levels were measured using high-performance liquid chromatography (HPLC)–electrospray ionization (ESI)–mass spectrometry (MS). Univariate analysis revealed significant differences in the PFAA profiles between the controls and the patients with any of the five types of cancer listed above, even those with asymptomatic early-stage disease. Furthermore, multivariate analysis clearly discriminated the cancer patients from the controls in terms of the area under the receiver-operator characteristics curve (AUC of ROC >0.75 for each cancer), regardless of cancer stage. Because this study was designed as case-control study, further investigations, including model construction and validation using cohorts with larger sample sizes, are necessary to determine the usefulness of PFAA profiling.ConclusionsThese findings suggest that PFAA profiling has great potential for improving cancer screening and diagnosis and understanding disease pathogenesis. PFAA profiles can also be used to determine various disease diagnoses from a single blood sample, which involves a relatively simple plasma assay and imposes a lower physical burden on subjects when compared to existing screening methods.
Induced pluripotent stem cells (iPSCs) can now be produced from various somatic cell (SC) lines by ectopic expression of the four transcription factors. Although the procedure has been demonstrated to induce global change in gene and microRNA expressions and even epigenetic modification, it remains largely unknown how this transcription factor-induced reprogramming affects the total glycan repertoire expressed on the cells. Here we performed a comprehensive glycan analysis using 114 types of human iPSCs generated from five different SCs and compared their glycomes with those of human embryonic stem cells (ESCs; nine cell types) using a high density lectin microarray. In unsupervised cluster analysis of the results obtained by lectin microarray, both undifferentiated iPSCs and ESCs were clustered as one large group. However, they were clearly separated from the group of differentiated SCs, whereas all of the four SCs had apparently distinct glycome profiles from one another, demonstrating that SCs with originally distinct glycan profiles have acquired those similar to ESCs upon induction of pluripotency. Thirty-eight lectins discriminating between SCs and iPSCs/ESCs were statistically selected, and characteristic features of the pluripotent state were then obtained at the level of the cellular glycome. The expression profiles of relevant glycosyltransferase genes agreed well with the results obtained by lectin microarray. Among the 38 lectins, rBC2LCN was found to detect only undifferentiated iPSCs/ESCs and not differentiated SCs. Hence, the high density lectin microarray has proved to be valid for not only comprehensive analysis of glycans but also diagnosis of stem cells under the concept of the cellular glycome.
◥ Accumulating evidence indicates that CD8 þ T cells in the tumor microenvironment and systemic CD4 þ T-cell immunity play an important role in mediating durable antitumor responses. We longitudinally examined T-cell immunity in the peripheral blood of patients with non-small lung cancer and found that responders had significantly (P < 0.0001) higher percentages of effector, CD62L low CD4 þ T cells prior to PD-1 blockade. Conversely, the percentage of CD25 þ FOXP3 þ CD4 þ T cells was significantly (P ¼ 0.034) higher in nonresponders. We developed a formula, which demonstrated 85.7% sensitivity and 100% specificity, based on the percentages of CD62L low CD4 þ T cells and CD25 þ FOXP3 þ cells to predict nonresponders. Mass cytometry analysis revealed that the CD62L low CD4 þ T-cell subset expressed T-bet þ , CD27 À , FOXP3 À , and CXCR3 þ , indicative of a Th1 subpopulation. CD62L low CD4 þ T cells significantly correlated with effector CD8 þ T cells (P ¼ 0.0091) and with PD-1 expression on effector CD8 þ T cells (P ¼ 0.0015). Gene expression analysis revealed that CCL19, CLEC-2A, IFNA, IL7, TGFBR3, CXCR3, and HDAC9 were preferentially expressed in CD62L low CD4 þ T cells derived from responders. Notably, longterm responders, who had >500-day progression-free survival, showed significantly higher numbers of CD62L low CD4 þ T cells prior to PD-1 blockade therapy. Decreased CD62L low CD4 þ T-cell percentages after therapy resulted in acquired resistance, with longterm survivors maintaining high CD62L low CD4 þ T-cell percentages. These results pave the way for new treatment strategies for patients by monitoring CD4 þ T-cell immune statuses in their peripheral blood.
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