OLFM4, LY6D and S100A7 as potent markers for distant metastasis in estrogen receptor‐positive breast carcinoma

Metastatic breast cancer is a highly lethal disease, and it is very important to evaluate the biomarkers associated with distant metastasis. However, molecular features of distant metastasis remain largely unknown in breast cancer. Estrogens play an important role in the progression of breast cancer and the majority of stage IV breast carcinomas express estrogen receptor (ER). Therefore, in this study, we examined molecular markers associated with distant metastasis in ER‐positive breast carcinoma by microarray and immunohistochemistry. When we examined the gene expression profile of ER‐positive stage IV breast carcinoma tissues (n = 7) comparing ER‐positive stage I‐III cases (n = 11) by microarray analysis, we newly identified OLFM4, LY6D and S100A7, which were closely associated with the distant metastasis. Subsequently, we performed immunohistochemistry for OLFM4, LY6D and S100A7 in 168 ER‐positive breast carcinomas. OLFM4, LY6D and S100A7 immunoreactivities were significantly associated with stage, pathological T factor, distant metastasis and Ki67 status in the ER‐positive breast carcinomas. Moreover, these immunoreactivities were significantly associated with a worse prognostic factor for distant metastasis‐free and breast cancer‐specific survival in ER‐positive stage I‐III breast cancer patients. However, when we performed immunohistochemistry for OLFM4, LY6D and S100A7 in 40 ER‐negative breast carcinomas, these immunoreactivities were not generally associated with the clinicopathological factors examined, including distant metastasis and prognosis of patients, in this study. These results suggest that OLFM4, LY6D and S100A7 immunoreactivity are associated with an aggressive phenotype of ER‐positive breast carcinoma, and these are potent markers for distant metastasis of ER‐positive breast cancer patients.     

Inter-prefectural Travel and Network Connectedness During the COVID-19 Pandemic in Japan

BackgroundIncreases in human mobility have been linked to rises in novel coronavirus disease 2019 (COVID-19) transmission. The pandemic era in Japan has been characterized by changes in inter-prefectural mobility across state of emergency (SOE) declarations and travel campaigns, but they have yet to be characterized.MethodsUsing Yahoo Japan mobility data extracted from the smartphones of more than 10 million Japanese residents, we calculated the monthly number of inter-prefectural travel instances, stratified by residential prefecture and destination prefecture. We then used this adjacency matrix to calculate two network connectedness metrics, closeness centrality and effective distance, that reliably predict disease transmission.ResultsInter-prefectural mobility and network connectedness decreased most considerably during the first SOE, but this decrease dampened with each successive SOE. Mobility and network connectedness increased during the Go To Travel campaign. Travel volume between distant prefectures decreased more than travel between prefectures with geographic proximity. Closeness centrality was found to be negatively correlated with the rate of COVID-19 infection across prefectures, with the strength of this association increasing in tandem with the infection rate. Changes in effective distance were more visible among geographically isolated prefectures (Hokkaido and Okinawa) than among metropolitan, central prefectures (Tokyo, Aichi, Osaka, and Fukuoka).ConclusionThe magnitude of reductions in human mobility decreased with each subsequent state of emergency, consistent with pandemic fatigue. The association between network connectedness and rates of COVID-19 infection remained visible throughout the entirety of the pandemic period, suggesting that inter-prefectural mobility may have contributed to disease spread.Key words: Japan, human mobility, domestic travel, COVID-19, travel campaign     

Advantages of Using Both Voxel- and Surface-based Morphometry in Cortical Morphology Analysis: A Review of Various Applications

Surface-based morphometry (SBM) is extremely useful for estimating the indices of cortical morphology, such as volume, thickness, area, and gyrification, whereas voxel-based morphometry (VBM) is a typical method of gray matter (GM) volumetry that includes cortex measurement. In cases where SBM is used to estimate cortical morphology, it remains controversial as to whether VBM should be used in addition to estimate GM volume. Therefore, this review has two main goals. First, we summarize the differences between the two methods regarding preprocessing, statistical analysis, and reliability. Second, we review studies that estimate cortical morphological changes using VBM and/or SBM and discuss whether using VBM in conjunction with SBM produces additional values. We found cases in which detection of morphological change in either VBM or SBM was superior, and others that showed equivalent performance between the two methods. Therefore, we concluded that using VBM and SBM together can help researchers and clinicians obtain a better understanding of normal neurobiological processes of the brain. Moreover, the use of both methods may improve the accuracy of the detection of morphological changes when comparing the data of patients and controls.In addition, we introduce two other recent methods as future directions for estimating cortical morphological changes: a multi-modal parcellation method using structural and functional images, and a synthetic segmentation method using multi-contrast images (such as T1- and proton density-weighted images).     

Sarcopenia with inflammation as a predictor of survival in patients with head and neck cancer

ObjectiveAlthough both sarcopenia and systemic inflammation affect the outcomes of head and neck cancer (HNC) patients, the association between sarcopenia and systemic inflammation and the combined prognostic effect of these factors in HNC patients remain unknown. This study aimed to evaluate the effect of sarcopenia with systemic inflammation on survival and disease control in HNC patients.MethodsWe retrospectively reviewed medical records of HNC patients treated between 2009 and 2016. The skeletal muscle area was measured using a single computed tomography image slice at the level of the third cervical vertebra. A prognostic score (SPLR) was developed based on sarcopenia and the platelet-lymphocyte ratio (PLR), and its prognostic value was evaluated.ResultsOverall, 164 patients were enrolled. In the multivariate analysis, sarcopenia was significantly associated with poor overall survival (OS) (p < 0.01). However, neither sarcopenia nor a high PLR was an independent prognostic factor for disease-free survival (DFS) or locoregional recurrence-free survival (LRFS). A high PLR was an independent predictor for sarcopenia (p < 0.01). A high SPLR was associated with older age, lower serum hemoglobin, and lower body mass index (all p < 0.05). Multivariate analysis revealed that SPLR was a significant independent predictor of OS, DFS, and LRFS (all p < 0.05).ConclusionsSystemic inflammation is significantly associated with sarcopenia. The survival and oncological effects of sarcopenia were enhanced when PLR was high. Thus, the combination of these two parameters may be useful for identifying HNC patients at a risk of poor survival outcomes.