Background: Localized extranodal natural killer (NK)/T-cell lymphoma, nasal type, commonly has a low or low–intermediate risk of the international prognostic index (IPI), so the IPI has shown inconsistency in predicting prognosis. Thus, we analyzed Ki-67 expression and proposed a new prognostic model including Ki-67 expression for stage I/II extranodal NK/T-cell lymphoma. Patients and methods: We studied Ki-67 expression and its relationship with prognosis in 50 patients with extranodal NK/T-cell lymphoma. Results: The patients were dichotomized by the median value: low (<65%) versus high Ki-67 (≥65%). High Ki-67 was associated with a worse overall survival (OS; P = 0.021) and disease-free survival (DFS; P = 0.044). In multivariate analysis, Ki-67 expression and primary site of involvement were found to be an independent prognostic factor for OS and DFS (P < 0.05). Based on these results, we proposed a new clinico-pathological prognostic model with Ki-67 expression and the primary site of involvement. It showed a high degree of correlation with worse OS and DFS (P < 0.001). Conclusions: Ki-67 expression is predictive of prognosis, and our prognostic model may become a useful tool for predicting prognosis in patients with stage I/II extranodal NK/T-cell lymphoma, nasal type.

PD-L1 expression is associated with poor prognosis, although this relationship is unclear in bone marrow-derived haematologic malignancies, including multiple myeloma. We aimed to determine whether PD-L1 expression could predict the prognosis of newly diagnosed multiple myeloma (NDMM). We evaluated 126 NDMM patients (83, retrospectively; 43, prospectively) who underwent bone marrow examinations. Bone marrow aspirates were analysed for PD-L1 expression, categorized as low or high expression, using quantitative immunofluorescence. High PD-L1 expression could independently predict poor overall survival (OS) (95% CI = 1.692–8.346) in multivariate analysis. On subgroup analysis, high PD-L1 expression was associated with poor OS (95% CI = 2.283–8.761) and progression-free survival (95% CI = 1.024–3.484) in patients who did not undergo autologous stem cell transplantation (ASCT) compared with those who did. High PD-L1 expression was associated with poor OS despite frontline treatments with or without immunomodulators. Thus, PD-L1 expression can be a useful prognosis predictor in NDMM patients, whereas ASCT may be used in patients with high PD-L1 expression. We developed a prognostic nomogram and found that a combination of PD-L1 expression in bone marrow plasma cells and clinical parameters (age, cytogenetics, and lactate dehydrogenase) effectively predicted NDMM prognosis. We believe that our nomogram can help identify high-risk patients and select appropriate treatments.

Sung HJ, et al. J Korean Med Sci. 2010 Oct;25(10):1418-1426. http://dx.doi.org/10.3346/jkms.2010.25.10.1418

On the basis of our previous report verifying that chemokine (C-X-C motif) receptor 2 (CXCR2) ligands in human placenta-derived cell conditioned medium (hPCCM) support human pluripotent stem cell (hPSC) propagation without exogenous basic fibroblast growth factor (bFGF), this study was designed to identify the effect of CXCR2 manipulation on the fate of hPSCs and the underlying mechanism, which had not been previously determined. We observed that CXCR2 inhibition in hPSCs induces predominant differentiation to mesoderm and endoderm with concomitant loss of hPSC characteristics and accompanying decreased expression of mammalian target of rapamycin (mTOR), β-catenin, and human telomerase reverse transcriptase (hTERT). These phenomena are recapitulated in hPSCs propagated in conventional culture conditions, including bFGF as well as those in hPCCM without exogenous bFGF, suggesting that the action of CXCR2 on hPSCs might not be associated with a bFGF-related mechanism. In addition, the specific CXCR2 ligand growth-related oncogene α (GROα) markedly increased the expression of ectodermal markers in differentiation-committed embryoid bodies derived from hPSCs. This finding suggests that CXCR2 inhibition in hPSCs prohibits the propagation of hPSCs and leads to predominant differentiation to mesoderm and endoderm owing to the blockage of ectodermal differentiation. Taken together, our results indicate that CXCR2 preferentially supports the maintenance of hPSC characteristics as well as facilitates ectodermal differentiation after the commitment to differentiation, and the mechanism might be associated with mTOR, β-catenin, and hTERT activities.

Smartphone-based point-of-care testing (POCT) is rapidly emerging as an alternative to traditional screening and laboratory testing, particularly in resource-limited settings. In this proof-of-concept study, we present a smartphone- and cloud-based artificial intelligence quantitative analysis system (SCAISY) for relative quantification of SARS-CoV-2-specific IgG antibody lateral flow assays that enables rapid evaluation (<60 s) of test strips. By capturing an image with a smartphone camera, SCAISY quantitatively analyzes antibody levels and provides results to the user. We analyzed changes in antibody levels over time in more than 248 individuals, including vaccine type, number of doses, and infection status, with a standard deviation of less than 10%. We also tracked antibody levels in six participants before and after SARS-CoV-2 infection. Finally, we examined the effects of lighting conditions, camera angle, and smartphone type to ensure consistency and reproducibility. We found that images acquired between 45° and 90° provided accurate results with a small standard deviation and that all illumination conditions provided essentially identical results within the standard deviation. A statistically significant correlation was observed (Spearman correlation coefficient: 0.59, p = 0.008; Pearson correlation coefficient: 0.56, p = 0.012) between the OD450 values of the enzyme-linked immunosorbent assay and the antibody levels obtained by SCAISY. This study suggests that SCAISY is a simple and powerful tool for real-time public health surveillance, enabling the acceleration of quantifying SARS-CoV-2-specific antibodies generated by either vaccination or infection and tracking of personal immunity levels.