Gastric adenocarcinoma is a common form of cancer associated with a poor prognosis. We analyzed microarray profiling data from 48 patients with gastric adenocarcinoma to characterize gastric cancer subtypes and identify biomarkers associated with prognosis. We identified two major subtypes of gastric adenocarcinoma differentially associated with overall survival (P = 0.025). Genes that were differentially expressed were identified using specific criteria (P < 0.001 and >1.5-fold); expression of 294 and 116 genes was enriched in good and poor prognosis subtypes, respectively. Genes related to translational elongation and cell cycle were upregulated in the poor prognosis group. Of these genes, upregulation of proteasome subunit beta type 8 PSMB8 and PDZ binding kinase PBK was confirmed by real-time reverse transcription-PCR analysis. PSMB8 or PBK knockdown had no effect on gastric cancer cell proliferation but suppressed cell migration and invasion, respectively. Furthermore, immunohistochemistry analysis of 385 gastric cancer patients revealed that increased nuclear expression of PSMB8 and PBK was correlated with depth of invasion, lymph node metastasis, and lower survival rates. Taken together, two gastric adenocarcinoma subtypes were predictive of prognosis. PSMB8 and PBK were predictive of gastric cancer prognosis and could be potential gastric cancer subtype-specific biomarkers.

Increased TFE3 expression in RCC was associated with poor PFS regardless of the gene translocation status. Moreover, morphological analysis should help to select candidates who would benefit from TFE3 staining and FISH analysis.

Background PD-L1 expression levels determined by immunostaining are known to be related to the survival rate and prognosis of patients with various types of cancers, as well as to the therapeutic response to immune checkpoint inhibitors. Recently, the U.S. Food and Drug Administration approved an immune checkpoint inhibitor for the treatment of non-small cell lung cancer along with the clones used for PD-L1 immunostaining to predict the resulting response. In this study, we performed PD-L1 immunostaining of tissue microarrays from ovarian epithelial cancer using SP263, an approved clone, and examined the effect of PD-L1 expression on survival rate and prognosis. Methods Tissue microarrays were constructed from ovarian epithelial cancer tissues of 248 patients and PD-L1 immunostaining was performed using the SP263 clone. PD-L1 expression levels in tumor cells, intraepithelial tumor-infiltrating lymphocytes, and stromal tumor-infiltrating lymphocytes were evaluated, and the effect of PD-L1 expression on survival and prognosis was analyzed. Results PD-L1 was detected in tumor cells as well as intraepithelial tumor-infiltrating lymphocytes and stromal tumor-infiltrating lymphocytes. It was most frequently expressed in stromal tumor-infiltrating lymphocytes. The Kaplan-Meier curve analysis and log rank test showed that only high stromal PD-L1 expression was associated with increased overall survival in ovarian serous carcinoma. Multivariate and univariate Cox regression analyses revealed that stromal PD-L1 expression was an independent prognostic factor, especially in ovarian serous carcinoma. Conclusions PD-L1 immunostaining using SP263 was observed in tumor cells as well as intraepithelial and stromal tumor-infiltrating lymphocytes. PD-L1-expressing stromal tumor-infiltrating lymphocytes were associated with an increased overall survival rate and may serve as a favorable prognostic factor in ovarian cancer, particularly serous carcinoma. Electronic supplementary material The online version of this article (10.1186/s13048-019-0526-0) contains supplementary material, which is available to authorized users.

The diagnostic performances of cerebrospinal fluid (CSF) biomarkers and amyloid positron emission tomography (PET) were compared by examining the association and concordance or discordance between CSF A␤ 1-42 and amyloid PET, after determining our own cut-off values for CSF Alzheimer's disease (AD) biomarkers. Furthermore, we evaluated the ability of CSF biomarkers and amyloid PET to predict clinical progression. CSF A␤ 1-42 , t-tau, and p-tau levels were analyzed in 203 individuals [27 normal controls, 38 mild cognitive impairment (MCI), 62 AD dementia, and 76 patients with other