Commemoration of body donors in a religiously diverse society: A tale of two Korean medical schools.

Although a diversity of religions exists in South Korea, with Buddhism and Christianity (Protestantism and Catholicism) being the two main faiths, Korean beliefs are deeply rooted in Confucianism. Despite the notion that the Confucian norm of filial piety discourages body donation to medical science, there has been a mindset shift in favor of body donation, driven by a heightened awareness of the body bequest programs and the care and dignity accorded to the altruistic body donors, together with the institution of commemorative services to honor them. As spirituality and religion are known to be factors that influence body donation, how religious- and non-religious-based memorial services are held to honor the donors as exemplified by two Korean medical schools-from a public university with no religious affiliation and from a Protestant-based university-are described here. The key concept of expressing gratitude and respect for the donors and their family members has positively impacted body bequest programs in this multi-religious society. Commemorative services held to pay tribute to the altruistic body donors may play an important role in inspiring a humanistic spirit in students, regardless of religious or non-religious beliefs, as exemplified by the two Korean medical schools. The takeaway here is that the elevation of spirituality in memorial services effectively resonates with society, thereby demonstrating the impact of spiritual principles independent of religious influence.

Advancement in Cancer Vasculogenesis Modeling through 3D Bioprinting Technology.

Cancer vasculogenesis is a pivotal focus of cancer research and treatment given its critical role in tumor development, metastasis, and the formation of vasculogenic microenvironments. Traditional approaches to investigating cancer vasculogenesis face significant challenges in accurately modeling intricate microenvironments. Recent advancements in three-dimensional (3D) bioprinting technology present promising solutions to these challenges. This review provides an overview of cancer vasculogenesis and underscores the importance of precise modeling. It juxtaposes traditional techniques with 3D bioprinting technologies, elucidating the advantages of the latter in developing cancer vasculogenesis models. Furthermore, it explores applications in pathological investigations, preclinical medication screening for personalized treatment and cancer diagnostics, and envisages future prospects for 3D bioprinted cancer vasculogenesis models. Despite notable advancements, current 3D bioprinting techniques for cancer vasculogenesis modeling have several limitations. Nonetheless, by overcoming these challenges and with technological advances, 3D bioprinting exhibits immense potential for revolutionizing the understanding of cancer vasculogenesis and augmenting treatment modalities.

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.

P-Element-Induced Wimpy Testis Proteins and P-Element-Induced Wimpy Testis-Interacting RNAs Expression in Ovarian Cancer Stem Cells.

Background: P-element-induced wimpy testis (PIWI)-interacting RNAs (piRNAs) are a type of noncoding RNA and are predominantly expressed in germline cells. piRNAs function as gene regulators and potential biomarkers for the development of a number of malignancies. The biological importance of piRNAs in ovarian cancer is still unknown. In this study, we investigated the expression of piRNAs in ovarian cancer stem cells and compared it with that in adherent cells. Methods: To assess changes in the expression levels of PIWIL1/HIWI, PIWIL2/HILI, PIWIL3, and PIWIL4/HIWI2, we used quantitative reverse-transcription polymerase chain reaction (RT-qPCR) analysis. Changes in piRNA expression levels in ovarian cancer stem cells were analyzed using Arraystar piRNA microarray screening. Gene Ontology (GO) enrichment analysis was conducted to determine the potential functions of piRNAs. Results: Using microarray analysis, we identified a cohort of differentially expressed piRNAs. Fifteen piRNAs, including DQ570763 and DQ597396, were downregulated, and 58 piRNAs were upregulated when compared with those in adherent A2780 and SKOV3 cells (p > 0.05, >2.0, respectively). GO functions of the downregulated piRNAs (DQ570763 and DQ570797) suggest that their roles are commonly associated with the Golgi apparatus. In addition, A2780-SP and SKOV3-SP cells had higher PIWIL3 and PIWIL4 mRNA levels than adherent cells (A2780 and SKOV3). Moreover, we determined, using receiver operating characteristic plot, that the expression level of PIWIL4 was lower in responders than in nonresponders after treatment with platins in patients with ovarian cancer. Finally, in ovarian cancer, PIWIL4 expression was associated with somatic mutations of dynein axonemal heavy chain 2, signal induced proliferation associated 1 like 2, YTH N6-methyladenosine RNA-binding protein 1, TBC1 domain family member 8, and LPS responsive Beige-like anchor protein. Conclusion: Our study showed that PIWI proteins and piRNAs are potential diagnostic and prognostic biomarkers for ovarian cancer.

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.

Clinical big-data-based design of GLUT2-targeted carbon nanodots for accurate diagnosis of hepatocellular carcinoma.

Despite advances in diagnostic and therapeutic methods, the prognosis of patients with hepatocellular carcinoma (HCC) remains poor due to the delay in diagnosis. Herein, we aimed to discover a highly sensitive and specific biomarker for HCC based on genomic big data analysis and create an HCC-targeted imaging probe using carbon nanodots (CNDs) as contrast agents. In genomic analysis, we selected glucose transporter 2 (GLUT2) as a potential imaging target for HCC. We confirmed the target suitability by immunohisto-chemistry tests of 339 patient samples, where 81.1% of the patients exhibited underexpression of GLUT2, i.e., higher GLUT2 intensity in non-tumor tissues than in tumor tissues. To visualize GLUT2, we conjugated CNDs with glucosamine (GLN) as a targeting ligand to yield glucosamine-labeled CNDs (GLN-CNDs). A series of in vitro and in vivo experiments were conducted on GLUT2-modified HepG2 cells to confirm the specificity of the GLN-CNDs. Since the GLUT2 expression is higher in hepatocytes than in HCC cells, the GLUT2-targeted contrast agent is highly attached to normal cells. However, it is possible to produce images in the same form as the images obtained with a cancer cell-targeted contrast agent by inverting color scaling. Our results indicate that GLUT2 is a promising target for HCC and that GLN-CNDs may potentially be used as targeted imaging probes for diagnosing HCC.

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.

Novel Prognostic Factor for Uveal Melanoma: Bioinformatics Analysis of Three Independent Cohorts.

BACKGROUND/AIM: Because 50% of uveal melanoma metastasize within 10 years of diagnosis, there is urgent need for accurate prognostic factors. MATERIALS AND METHODS: To identify genes that can act as prognostic factors in uveal melanoma, we performed survival analyses using three independent cohorts. Using log-rank test and univariate cox regression, genes which could stratify the prognosis in all cohorts simultaneously depending on their expression levels were selected as novel biomarkers. Hub genes were obtained by analyzing the interaction and relationship between the selected genes using String and Cytoscape. Additionally, prognostic power was calculated by using C-indices and AUC. RESULTS: A total of 37 oncogene-like and 14 tumor suppressor-like genes were selected. Protein-protein analysis revealed that NDUFB9, NDUFV2, CYC1 among oncogene-like genes, CTNNB1 among tumor suppressor-like genes were found to be hub genes and core biomarkers in uveal melanoma. CONCLUSION: NDUFB9, NDUFV2, CYC1 and CTNNB1 genes may act as prognostic factors in uveal melanoma.

Development and Validation of a Risk Scoring System Derived from Meta-Analyses of Papillary Thyroid Cancer.

BACKGROUND: The aim of this study was to develop a scoring system to stratify the risk of papillary thyroid cancer (PTC) and to select the proper management. METHODS: We performed a systematic search of MEDLINE and Embase. Data regarding patients' prognoses were obtained from the included studies. Odds ratios (ORs) with statistical significance were extracted from the publications. To generate a risk scoring system (RSS), ORs were summed (RSS1), and summed after natural-logarithmic transformation (RSS2). RSS1 and RSS2 were compared to the eighth edition of the American Joint Committee on Cancer (AJCC) staging system and the 2015 American Thyroid Association (ATA) guidelines for thyroid nodules and differentiated thyroid carcinoma. RESULTS: Five meta-analyses were eligible for inclusion in the study. Eight variables (sex, tumour size, extrathyroidal extension, BRAF mutation, TERT mutation, histologic subtype, lymph node metastasis, and distant metastasis) were included. RSS1 was the best of the analysed models. CONCLUSION: We developed and validated a new RSS derived from previous meta-analyses for patients with PTC. This RSS seems to be superior to previously published systems.

Role of kif2c, A Gene Related to ALL Relapse, in Embryonic Hematopoiesis in Zebrafish.

Relapse of acute lymphoblastic leukemia (ALL) is dangerous and it worsens the prognosis of patients; however, prognostic markers or therapeutic targets for ALL remain unknown. In the present study, using databases such as TARGET, GSE60926 and GSE28460, we determined that KIF2C and its binding partner, KIF18B are overexpressed in patients with relapsed ALL compared to that in patients diagnosed with ALL for the first time. As 50% of the residues are exactly the same and the signature domain of KIF2C is highly conserved between human and zebrafish, we used zebrafish embryos as a model to investigate the function of kif2c in vivo. We determined that kif2c is necessary for lymphopoiesis in zebrafish embryos. Additionally, we observed that kif2c is not related to differentiation of HSCs; however, it is important for the maintenance of HSCs as it provides survival signals to HSCs. These results imply that the ALL relapse-related gene KIF2C is linked to the survival of HSCs. In conclusion, we suggest that KIF2C can serve as a novel therapeutic target for relapsed ALL.

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.