The potential of piR-823 as a diagnostic biomarker in oncology: A systematic review.

BACKGROUND: Emerging evidence has demonstrated that PIWI-interacting RNAs (piRNAs) play important roles in various physiological processes and contribute to cancer progression. Moreover, piRNAs and PIWI protein levels are associated with the prognosis and chemoresistance of various cancers. The limitations of biomarkers challenge early detection and monitoring of chemoresistance and cancer relapse. METHODS: To evaluate the potential of piRNA as a diagnostic biomarker in oncology, we systematically reviewed previous studies on the subject. PubMed, Embase, and Cochrane databases were searched to evaluate the diagnostic relevance of piRNAs in cancer. Eighteen studies (2,352 patients) were included. The quality of each study was evaluated with AMSTAR and QUADAS-2 tool. RESULTS & CONCLUSIONS: The area under the curve (AUC) values of 26 piRNAs in patients with cancer ranged from 0.624 to 0.978, with piR-9491 showing the highest value (0.978). The sensitivity of the total of 21 piRNAs in cancer patients was between 42.86 and 100, with piR-9491 showing the highest sensitivity (100). The specificity of these 21 piRNAs ranged from 60.10 to 96.67 (with piR-018569 showing the highest specificity (96.67)). Their odds ratios were between 1.61 and 44.67, and piR-12488 showed the highest odds ratio (44.67). Generally, the piRNAs in this review showed better sensitivity and AUC values than current clinical diagnostic biomarkers, although current biomarkers appear to be more specific. Reviewed piRNAs showed better diagnostic performance than currently used clinical biomarkers. Notably, piR-823 showed a significant diagnostic performance in four types of cancer (colorectal, esophageal, gastric, and renal cell cancer). However, all 18 studies included in this review were a case-control study. So, further prospective studies are required for their validation.

Genetic heterogeneity of liver cancer stem cells.

Cancer cell heterogeneity is a serious problem in the control of tumor progression because it can cause chemoresistance and metastasis. Heterogeneity can be generated by various mechanisms, including genetic evolution of cancer cells, cancer stem cells (CSCs), and niche heterogeneity. Because the genetic heterogeneity of CSCs has been poorly characterized, the genetic mutation status of CSCs was examined using Exome-Seq and RNA-Seq data of liver cancer. Here we show that different surface markers for liver cancer stem cells (LCSCs) showed a unique propensity for genetic mutations. Cluster of differentiation 133 (CD133)-positive cells showed frequent mutations in the IRF2, BAP1, and ERBB3 genes. However, leucine-rich repeat-containing G protein-coupled receptor 5-positive cells showed frequent mutations in the CTNNB1, RELN, and ROBO1 genes. In addition, some genetic mutations were frequently observed irrespective of the surface markers for LCSCs. BAP1 mutations was frequently observed in CD133-, CD24-, CD13-, CD90-, epithelial cell adhesion molecule-, or keratin 19-positive LCSCs. ASXL2, ERBB3, IRF2, TLX3, CPS1, and NFATC2 mutations were observed in more than three types of LCSCs, suggesting that common mechanisms for the development of these LCSCs. The present study provides genetic heterogeneity depending on the surface markers for LCSCs. The genetic heterogeneity of LCSCs should be considered in the development of LCSC-targeting therapeutics.

Large-scale functional brain networks for consciousness.

The generation and maintenance of consciousness are fundamental but difficult subjects in the fields of psychology, philosophy, neuroscience, and medicine. However, recent developments in neuro-imaging techniques coupled with network analysis have greatly advanced our understanding of consciousness. The present review focuses on large-scale functional brain networks based on neuro-imaging data to explain the awareness (contents) and wakefulness of consciousness. Despite limitations, neuroimaging data suggests brain maps for important psychological and cognitive processes such as attention, language, self-referential, emotion, motivation, social behavior, and wakefulness. We considered a review of these advancements would provide new insights into research on the neural correlates of consciousness.

A User-Friendly, Web-Based Integrative Tool (ESurv) for Survival Analysis: Development and Validation Study.

BACKGROUND: Prognostic genes or gene signatures have been widely used to predict patient survival and aid in making decisions pertaining to therapeutic actions. Although some web-based survival analysis tools have been developed, they have several limitations. OBJECTIVE: Taking these limitations into account, we developed ESurv (Easy, Effective, and Excellent Survival analysis tool), a web-based tool that can perform advanced survival analyses using user-derived data or data from The Cancer Genome Atlas (TCGA). Users can conduct univariate analyses and grouped variable selections using multiomics data from TCGA. METHODS: We used R to code survival analyses based on multiomics data from TCGA. To perform these analyses, we excluded patients and genes that had insufficient information. Clinical variables were classified as 0 and 1 when there were two categories (for example, chemotherapy: no or yes), and dummy variables were used where features had 3 or more outcomes (for example, with respect to laterality: right, left, or bilateral). RESULTS: Through univariate analyses, ESurv can identify the prognostic significance for single genes using the survival curve (median or optimal cutoff), area under the curve (AUC) with C statistics, and receiver operating characteristics (ROC). Users can obtain prognostic variable signatures based on multiomics data from clinical variables or grouped variable selections (lasso, elastic net regularization, and network-regularized high-dimensional Cox-regression) and select the same outputs as above. In addition, users can create custom gene signatures for specific cancers using various genes of interest. One of the most important functions of ESurv is that users can perform all survival analyses using their own data. CONCLUSIONS: Using advanced statistical techniques suitable for high-dimensional data, including genetic data, and integrated survival analysis, ESurv overcomes the limitations of previous web-based tools and will help biomedical researchers easily perform complex survival analyses.

FAM213A is linked to prognostic significance in acute myeloid leukemia through regulation of oxidative stress and myelopoiesis.

Accurate prediction of malignancies is important in choosing therapeutic strategies. Although there are many genetic and cytogenetic prognostic factors for acute myeloid leukemia (AML), prognosis is difficult to predict because of the heterogeneity of AML. Prognostic factors, including messenger RNA (mRNA) expression, have been determined for other malignancies, but not for AML. A total of 402 patients from The Cancer Genome Atlas, GSE12417 (GPL96, 97), and GSE12417 (GPL570) were included in this study. In Kaplan-Meier curve analyses, high expression of family with sequence similarity 213 member A (FAM213A), which activates antioxidant proteins, was associated with worse prognosis of AML. Similar to the results of the survival curve, C-indices and area under the curve values were high. Current prognostic factors of AML, unlike those of other cancers, do not take mRNA expression into consideration. Thus, the development of mRNA-based prognostic factors would be beneficial for accurate prediction of the survival of AML patients. Additionally, in vivo validation using zebrafish revealed that fam213a is important for myelopoiesis at the developmental stage and is a negative regulator of the p53 tumor suppressor gene. The findings implicate fam213a as a novel prognostic factor for AML patients.

Prognostic Role of Zinc Finger Homeobox 4 in Ovarian Serous Cystadenocarcinoma.

Introduction: The zinc finger homeobox 4 (ZFHX4) protein is a crucial molecular regulator of tumor-initiating stem cell-like functions. Objective: This study aimed to determine the role of ZFHX4 in the progression of ovarian serous cystadenocarcinoma (OSC). Methods: Differential gene expression ZFHX4 among low-stage (stages I and II), high-stage (stages III and IV), low-grade (grades I and II), and high-grade (grades III and IV) OSC patients was identified using four independent cohorts from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). We compared ZFHX4 expression as a prognostic factor using Kaplan-Meier survival curves, multivariate analysis, the time-dependent area under the curve (AUC) of Uno's C-index, and the AUC of the receiver operating characteristics at 4 years post diagnosis. Results: ZFHX4 gene expression in high-stage tumors is significantly higher than in low-stage tumors (TCGA, p = 0.007; GSE9891, p = 0.001). A Kaplan-Meier analysis revealed that elevated expression of ZFHX4 was associated with a poor prognosis in OSC patients for all cohorts, regardless of stage and grade (TCGA, p = 1e-04; GSE9891, p = 0.0044; GSE13876, p = 0.00078; GSE26712, p = 0.039). Analysis of C-indices and the area under the receiver operating characteristic curve further supported this result (C-index: TCGA, 0.599; GSE9891, 0.642; GSE13876, 0.585; GSE26712, 0.597). Moreover, univariate and multivariate Cox hazards analyses confirmed the prognostic significance of ZFHX4 levels. Conclusion: Collectively, these findings suggest that ZFHX4 is a prognostic factor for OSC.

GABRQ expression is a potential prognostic marker for patients with clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer. Novel biomarkers of ccRCC may provide crucial information on tumor features and prognosis. The present study aimed to determine whether the expression of γ-aminobutyric acid (GABA) A receptor subunit θ (GABRQ) could serve as a novel prognostic marker of ccRCC. GABA is the main inhibitory neurotransmitter in the brain that activates the receptor GABAA, which is comprised of three subunit isoforms: GABRA3, GABRB3 and GABRQ. A recent study reported that GABRQ is involved in the initiation and progression of hepatocellular carcinoma; however, the role of GABRQ in ccRCC remains unknown. In the present study, clinical and transcriptomic data were obtained from cohorts of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). Differential GABRQ expression levels among early (TI and II), late (TIII and IV), nonmetastatic (M0) and metastatic (M1, primary tumor) stages of ccRCC samples were then identified. Furthermore, the use of GABRQ as a prognostic gene was analyzed using Uno's C-index based on the time-dependent area under the curve (AUC), the AUC of the receiver operating characteristic curve at 5 years, the Kaplan-Meier survival curve and multivariate analysis. The survival curve analysis revealed that low GABRQ mRNA expression was significantly associated with a poor prognosis of ccRCC (P<0.001 and P=0.0012 for TCGA and ICGC data, respectively). In addition, analyses of the C-index and AUC values further supported this discriminatory power. Furthermore, the prognostic value of GABRQ mRNA expression was confirmed by multivariate Cox regression analysis. Taken together, these results suggested that GABRQ mRNA expression may be considered as a novel prognostic biomarker of ccRCC.

Prognostic role of the beta-2 adrenergic receptor in clear cell renal cell carcinoma.

The beta-2 adrenergic receptor (ADRB2) regulates the proliferation, apoptosis, angiogenesis, migration, and metastasis of cancer cells. However, its function in the progression of clear cell renal cell carcinoma (ccRCC) is unknown. Here, we report that ADRB2 can be a novel prognostic factor for patients with ccRCC. The differential expression of ADRB2 in low-stage (stages I and II), high-stage (stages III and IV), low-grade (grades I and II), and high-grade (grades III and IV) ccRCC was identified in cohorts of patients from The Cancer Genome Atlas and the International Cancer Genome Consortium. We evaluated ADRB2 expression as a prognostic factor using the Kaplan-Meier survival curve, multivariate analysis, time-dependent area under the curve (AUC) of Uno's C-index, and AUC of the receiver operating characteristics (ROC) at five years. Kaplan-Meier analysis revealed that reduced ADRB2 expression is associated with poor prognosis in ccRCC patients. Analysis of C-indices and AUC-ROC further confirmed this result. Moreover, multivariate analysis confirmed the prognostic significance of ADRB2 expression. Collectively, these findings suggest that ADRB2 is a potential prognostic factor for ccRCC.

DYSF expression in clear cell renal cell carcinoma: A retrospective study of 2 independent cohorts.

OBJECTIVE: Renal cell carcinoma (RCC) is the most typical type of kidney cancer in adults. Hypercalcemia is a well known paraneoplastic syndrome associated with RCC and recent studies have reported that hypercalcemia is closely related to the poor prognosis of RCC patients. Clear cell RCC (ccRCC) is the most common and aggressive subtype of RCC. Although the histological classification of RCC is important for determination of appropriate treatment strategies, effective biomarkers for predicting prognosis of ccRCC have not yet been identified. Since calcium levels affect the prognosis of RCC patients, we evaluated whether the calcium-sensing genes on the plasma membrane, including those encoding calcium channels, CaSR, GPRC6a, and DYSF, could be used as biomarkers to predict the prognosis of ccRCC patients. METHODS: Information from 537 patients from The Cancer Genome Atlas (TCGA; n = 446) and International Cancer Genome Consortium (ICGC; n = 91) was used in this study. Among these genes, DYSF was the only gene whose expression correlated with overall survival of both TGCA and ICGC patients. RESULTS: Although DYSF gene expression was higher in ccRCC tissue than in normal kidney tissue, Kaplan-Meier curves showed that the survival rate of ccRCC patients with high DYSF expression was significantly higher than that of patients with low DYSF expression (TCGA, P < 0.0001; ICGC, P = 0.0011). We also validated the potential of DYSF as a prognostic biomarker for ccRCC by conducting a time-dependent area under the curve (AUC) analysis and 5-years receiver operating characteristic curve analysis. Finally, multivariate regression analysis revealed that the expression of DYSF is independent of other prognostic parameters (TCGA, P = 0.017; ICGC, P = 0.006). CONCLUSIONS: These results suggested that DYSF may play a suppressive role in the progression of ccRCC and could act as a promising prognostic biomarker for predicting the survival of ccRCC patients.

Prognostic significance of EIF4G1 in patients with pancreatic ductal adenocarcinoma.

BACKGROUND: Advances in genomics have greatly improved the survival rate in cancer patients. However, due to genetic heterogeneity, pancreatic ductal adenocarcinoma (PDAC) is still difficult to diagnose early, and its survival rate is extremely low. Therefore, we identified biomarkers that predict the prognosis of PDAC patients using independent cohort data. MATERIALS AND METHODS: To develop a novel prognostic biomarker, we used the gene expression and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Kaplan-Meier survival curve using median values of genes as cutoff showed that EIF4G1 was the only statistically significant gene in the 3 cohorts. We analyzed the prognostic significance of EIF4G1 using the time-dependent area under the curve (AUC) of Uno's C-index, the AUC value of the receiver operating characteristics (ROC) at 3 years, and multivariate Cox analysis. We also compared EIF4G1 levels between tumors and matched non-tumor tissues. RESULTS: EIF4G1 is the only prognostic gene in patients with PDAC, which was selected by Kaplan-Meier survival analysis. The survival curve showed that high expression of EIF4G1 was associated with poor prognosis of PDAC with a good discriminative ability in 3 independent cohorts. The risk stratifying ability of EIF4G1 was demonstrated by analyzing C-indices and AUC values. Multivariate Cox regression confirmed its prognostic significance. EIF4G1 expression was significantly higher in PDAC tissues than in the matched normal tissues. CONCLUSION: EIF4G1 could be used as a novel prognostic marker for PDAC and to determine suitable treatment options.

Prognostic Role of TMED3 in Clear Cell Renal Cell Carcinoma: A Retrospective Multi-Cohort Analysis.

Transmembrane p24 trafficking protein 3 (TMED3) is a metastatic suppressor in colon cancer and hepatocellular carcinoma. However, its function in the progression of clear cell renal cell carcinoma (ccRCC) is unknown. Here, we report that TMED3 could be a new prognostic marker for ccRCC. Patient data were extracted from cohorts in the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). Differential expression of TMED3 was observed between the low stage (Stage I and II) and high stage (Stage III and IV) patients in the TCGA and ICGC cohorts and between the low grade (Grade I and II) and high grade (Grade III and IV) patients in the TCGA cohort. Further, we evaluated TMED3 expression as a prognostic gene using Kaplan-Meier survival analysis, multivariate analysis, the time-dependent area under the curve (AUC) of Uno's C-index, and the AUC of the receiver operating characteristics at 5 years. The Kaplan-Meier analysis revealed that TMED3 overexpression was associated with poor prognosis for ccRCC patients. Analysis of the C-indices and area under the receiver operating characteristic curve further supported this. Multivariate analysis confirmed the prognostic significance of TMED3 expression levels (P = 0.005 and 0.006 for TCGA and ICGC, respectively). Taken together, these findings demonstrate that TMED3 is a potential prognostic factor for ccRCC.

VNN3 is a potential novel biomarker for predicting prognosis in clear cell renal cell carcinoma.

Although pathological observations provide approximate prognoses, it is difficult to achieve prognosis in patients with existing prognostic factors. Therefore, it is very important to find appropriate biomarkers to achieve accurate cancer prognosis. Renal cell carcinoma (RCC) has several subtypes, the discrimination of which is crucial for proper treatment. Here, we present a novel biomarker, VNN3, which is used to prognose clear cell renal cell carcinoma (ccRCC), the most common and aggressive subtype of kidney cancer. Patient information analyzed in our study was extracted from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) cohorts. VNN3 expression was considerably higher in stages III and IV than in stages I and II. Moreover, Kaplan-Meier curves associated high VNN3 expression with poor prognoses (TCGA, p < .0001; ICGC, p = .00076), confirming that ccRCC prognosis can be predicted via VNN3 expression patterns. Consistent with all patient results, the prognosis of patients with higher VNN3 expression was worse in both low stage (I and II) and high stage (III and IV) (TCGA, p < 0.0001 in stage I and II; ICGC, p = 0.028 in stage I and II; TCGA, p = 0.005 in stage III and IV). Area under the curve and receiver operating characteristic curves supported our results that highlighted VNN3 expression as a suitable ccRCC biomarker. Multivariate analysis also verified the prognostic performance of VNN3 expression (TCGA, p < .001; ICGC, p = .017). Altogether, we suggest that VNN3 is applicable as a new biomarker to establish prognosis in patients with ccRCC.

Evaluation of the prognostic significances of γ-secretase genes in pancreatic cancer.

With the growing requirement for novel prognostic biomarkers for pancreatic cancer, many studies have focused on clinical and/or genomic variables. Although many studies have been performed, carbohydrate antigen 19-9 is the only biomarker in clinical use. Therefore, the present study examined whether γ-secretase genes, including presenilin (PSEN), nicastrin (NCSTN), presenilin enhancer protein 2 (PSENEN), and anterior pharynx-defective 1 (APH1-), could serve as prognostic factors for pancreatic cancer. The cohorts selected included >100 pancreatic cancer patients. Patient data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GSE21501). The prognostic roles of the γ-secretase genes were analyzed by several survival analysis methods. Among the γ-secretase genes, the prognosis tended to be worse in the 2 cohorts with increasing expression of PSEN1, APH1A, and PSENEN, while the remaining genes were the opposite in the 2 cohorts. Notably, although the patient characteristics were quite different, APH1A was statistically significantly associated with prognosis in the 2 cohorts. The hazard ratio of APH1A for overall survival was 1.598 (TCGA) and 2.724 (GSE21501). These results contribute to the study of γ-secretase in pancreatic cancer. We believe that γ-secretase, particularly APH1A, will be a new prognostic biomarker for pancreatic cancer.

Development of a risk scoring system for patients with papillary thyroid cancer.

As the importance of personalized therapeutics in aggressive papillary thyroid cancer (PTC) increases, accurate risk stratification is required. To develop a novel prognostic scoring system for patients with PTC (n = 455), we used mRNA expression and clinical data from The Cancer Genome Atlas. We performed variable selection using Network-Regularized high-dimensional Cox-regression with gene network from pathway databases. The risk score was calculated using a linear combination of regression coefficients and mRNA expressions. The risk score and clinical variables were assessed by several survival analyses. The risk score showed high discriminatory power for the prediction of event-free survival as well as the presence of metastasis. In multivariate analysis, the risk score and presence of metastasis were significant risk factors among the clinical variables that were examined together. In the current study, we developed a risk scoring system that will help to identify suitable therapeutic options for PTC.

The AP2M1 gene expression is a promising biomarker for predicting survival of patients with hepatocellular carcinoma.

There is a growing need for the discovery of new prognostic factors for cases where the scoring and staging system of hepatocellular carcinoma (HCC) does not result in a clear definition. We analyzed whether AP-2 complex subunit mu (AP2M1) expression could be a new prognostic marker for HCC based on the roles of AP2M1 in influencing hepatocyte growth factor (HGF) promoter regulation and hepatitis C virus (HCV) assembly. Patient data were extracted from cohorts of the Gene Expression Omnibus (GSE10186), International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). Differential expression value between matched cancer and normal liver was identified using ICGC cohort. Subsequently, we compared AP2M1 expression as a prognostic gene with other well-known prognostic genes for HCC, using the time-dependent area under the curve (AUC) of the Uno's C-index, the AUC value of the receiver operating characteristics at 5 years, Kaplan-Meier survival curve, and multivariate analysis. Particularly, TCGA and GSE10186 patients were divided into subgroups based on alcohol intake, hepatitis B, and C viral infections, and analyzed in the same methods. The AP2M1 expression values in patients with cancer were much higher than matched normal liver. The AP2M1 level showed excellent prognosis predictions in comparison with existing markers in the three independent cohorts (n = 647). In particular, it was more predictive of prognosis than other markers in alcohol intake and HCV infections. In conclusion, we were confident that AP2M1 provides sufficient value as a new prognostic marker for HCC especially patients with HCV infection and/or alcohol intake.

Prognostic role of TPD52 in acute myeloid leukemia: A retrospective multicohort analysis.

Generating accurate prognoses is extremely important for treating patients with cancer. Prognostic prediction based on messenger RNA (mRNA) expression has shown superior clinical value to other markers for some cancers but is not currently used for acute myeloid leukemia (AML). Lipid metabolism is associated with biological aspects of cancer progression, including massive proliferation, and abnormal signaling. Moreover, abnormalities in lipid metabolism have prognostic significance. Patients with AML display abnormalities in sphingolipid metabolism and fatty acid oxidation. TPD52 is a regulator of lipid metabolism and plays a role in the formation of lipid droplets and fatty acid storage. Although the prognostic significance of TPD52 expression has been reported for many types of cancer, it has not yet been assessed in patients with AML. Therefore, the aim of the current study was to assess the prognostic significance of TPD52 in AML using three independent AML cohorts: one from The Cancer Genome Atlas (TGCA; n = 142) and two from the National Center for Biotechnology Information: GSE12417 (GPL96-97; n = 162) and GSE12417 (GPL570; n = 78). TPD52 was found to be overexpressed in patients with AML (GSE84881; n = 23). The Kaplan-Meier curve revealed that TPD52 overexpression was associated with a poor prognosis for patients with AML with good discrimination ( P = 0.013, P = 0.005, and P = 0.032 for the TGCA, GSE12417, and GSE12417, respectively). Analysis of C-indices and area under the receiver operating characteristic curve values further supported this discriminative ability. Moreover, multivariate analysis confirmed the prognostic significance of TPD52 expression levels ( P = 0.0196). These results suggest that the TPD52 mRNA level is a potential biomarker for AML.

ALKBH5 gene is a novel biomarker that predicts the prognosis of pancreatic cancer: A retrospective multicohort study.

BACKGROUNDS/AIMS: Discovery of new prognostic factors for cases in which the pancreatic cancer scoring and staging system does not result in a clear definition is imperative. We examined the role of Human AlkB homolog H5 (ALKBH5) as a prognostic marker for pancreatic cancer. METHODS: Patient data were extracted from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). The prognostic value of ALKBH5 was confirmed via analysis of ALKBH5 and other clinical factors, such as age, sex, and stage, using the time-dependent area under the curve (AUC) of Uno's C-index, the AUC value of the receiver operating characteristics (ROC) at three years, the Kaplan-Meier survival curve, and multivariate analysis. RESULTS: ALKBH5 showed excellent prognosis prediction in comparison with existing markers in the two independent cohorts (n=262). Kaplan-Meier survival analysis showed that ALKBH5 expression was positively associated with overall survival (log-rank test, ICGC, p=0.001; TCGA, p=0.01). Notably, comparison of C-index and AUC values in ROC analysis showed that ALKBH5 was associated with high C-index and AUC values compared with other clinical variables (C-index: ICGC, 0.621; TCGA, 0.614 and AUC at three years: ICGC, 0.609; TCGA, 0.558). Multivariate analysis demonstrated thatALKBH5 is an independent prognostic factor (ICGC, p=0.0123; TCGA, p<0.001). CONCLUSIONS: These findings contribute to the study of RNA methylation in pancreatic cancer. We believe that ALKBH5 is a new prognostic marker for pancreatic cancer.

SAC3D1: a novel prognostic marker in hepatocellular carcinoma.

Centrosome-associated proteins are recognized as prognostic factors in many cancers because centrosomes are critical structures for the cell cycle progression and genomic stability. SAC3D1, however, is associated with centrosome abnormality, although its prognostic potential has not been evaluated in hepatocellular carcinoma (HCC). In this study, 3 independent cohorts (GSE10186, n = 80; TCGA, n = 330 and ICGC, n = 237) were used to assess SAC3D1 as a biomarker, which demonstrated SAC3D1 overexpression in HCC tissues when compared to the matched normal tissues. Kaplan-Meier survival analysis also showed that its overexpression was associated with poor prognosis of HCC with good discriminative ability in 3 independent cohorts (GSE10186, P = 0.00469; TCGA, P = 0.0000413 and ICGC, P = 0.0000114). Analysis of the C-indices and AUC values further supported its discriminative ability. Finally, multivariate analysis confirmed its prognostic significance (GSE10186, P = 0.00695; TCGA, P = 0.0000289 and ICGC, P = 0.0000651). These results suggest a potential of SAC3D1 as a biomarker for HCC.

TMEM18: A Novel Prognostic Marker in Acute Myeloid Leukemia.

BACKGROUND: Certain nuclear envelope proteins are associated with important cancer cell characteristics, including migration and proliferation. Abnormal expression of and genetic changes in nuclear envelope proteins have been reported in acute myeloid leukemia (AML) patients. Transmembrane protein 18 (TMEM18), a nuclear envelope protein, is involved in neural stem cell migration and tumorigenicity. METHODS: To examine the prognostic significance of TMEM18 in AML patients, we analyzed an AML cohort from The Cancer Genome Atlas (TCGA, n = 142). RESULTS: Kaplan-Meier survival analysis revealed that TMEM18 overexpression was associated with a better AML prognosis with good discrimination (p = 0.019). Interestingly, this ability to predict the prognosis was significant in male AML patients, but not in female ones. C-index and area-under-the-curve analyses further supported this discriminative ability and multivariate analysis confirmed its prognostic significance (p = 0.00347). Correlation analysis revealed that TMEM18 had a statistically significant positive correlation with nuclear envelop protein 133 (NUP133), NUP35, NUP54, NUP62, and NUP88. CONCLUSION: Because the current AML prognostic factors do not take mRNA expression into consideration unlike other cancers, the development of mRNA-based prognostic factors would be beneficial for accurate prediction of the survival of AML patients. Therefore, TMEM18 gene is a potential biomarker for AML.

mRNA Expression of SLC5A5 and SLC2A Family Genes in Papillary Thyroid Cancer: An Analysis of The Cancer Genome Atlas.

PURPOSE: The present study investigated the dynamics and prognostic role of messenger RNA (mRNA) expression responsible for ¹8F-fluorodeoxyglucose (FDG) uptake in FDG positron emission tomography (PET) and radioactive iodine (¹³¹I) uptake in whole-body radioactive iodine scans (WBS) in papillary thyroid cancer (PTC) patients. MATERIALS AND METHODS: The primary and processed data were downloaded from the Genomic Data Commons Data Portal. Expression data for sodium/iodide symporter (solute carrier family 5 member 5, SLC5A5), hexokinase (HK1-3), glucose-6-phosphate dehydrogenase (G6PD), and glucose transporter (solute carrier family 2, SLC2A1-4) mRNA were collected. RESULTS: Expression of SLC5A5 mRNA were negatively correlated with SLC2A1 mRNA and positively correlated with SLC2A4 mRNA. In PTC with BRAF mutations, expressions of SLC2A1, SLC2A3, HK2, and HK3 mRNA were higher than those in PTC without BRAF mutations. Expression of SLC5A5, SLC2A4, HK1, and G6PD mRNA was lower in PTC without BRAF mutation. PTCs with higher expression of SLC5A5 mRNA had more favorable disease-free survival, but no association with overall survival. CONCLUSION: Expression of SLC5A5 mRNA was negatively correlated with SLC2A1 mRNA. This finding provides a molecular basis for the management of PTC with negative WBS using ¹8F-FDG PET scans. In addition, higher expression of SLC5A5 mRNA was associated with less PTC recurrence, but not with deaths.