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

Reprogramming of Fatty Acid Metabolism in Acute Leukemia

Fatty acids are essential biomolecules that support several cellular processes, such as membrane structures, energy storage and production, as well as signal transduction. Accordingly, changes in fatty acid metabolism can have a significant impact on cell behavior, such as growth, survival, proliferation, differentiation, and motility. Therefore, it is not surprising that many aspects of fatty acid metabolism are frequently dysregulated in human cancer, including in highly aggressive blood cancers such as acute leukemia. The aims of this review are to summarize the aspects of fatty acid metabolism that are specifically coopted in acute leukemia as well as current preclinical strategies for targeting fatty acid metabolism in these cancers.

An Overview on Lipid Droplets Accumulation as Novel Target for Acute Myeloid Leukemia Therapy

Metabolic reprogramming is a key alteration in tumorigenesis. In cancer cells, changes in metabolic fluxes are required to cope with large demands on ATP, NADPH, and NADH, as well as carbon skeletons. In particular, dysregulation in lipid metabolism ensures a great energy source for the cells and sustains cell membrane biogenesis and signaling molecules, which are necessary for tumor progression. Increased lipid uptake and synthesis results in intracellular lipid accumulation as lipid droplets (LDs), which in recent years have been considered hallmarks of malignancies. Here, we review current evidence implicating the biogenesis, composition, and functions of lipid droplets in acute myeloid leukemia (AML). This is an aggressive hematological neoplasm originating from the abnormal expansion of myeloid progenitor cells in bone marrow and blood and can be fatal within a few months without treatment. LD accumulation positively correlates with a poor prognosis in AML since it involves the activation of oncogenic signaling pathways and cross-talk between the tumor microenvironment and leukemic cells. Targeting altered LD production could represent a potential therapeutic strategy in AML. From this perspective, we discuss the main inhibitors tested in in vitro AML cell models to block LD formation, which is often associated with leukemia aggressiveness and which may find clinical application in the future.

Genomic Regions Associated with Wool, Growth and Reproduction Traits in Uruguayan Merino Sheep

The aim of this study was to identify genomic regions and genes associated with the fiber diameter (FD), clean fleece weight (CFW), live weight (LW), body condition score (BCS), pregnancy rate (PR) and lambing potential (LP) of Uruguayan Merino sheep. Phenotypic records of approximately 2000 mixed-age ewes were obtained from a Merino nucleus flock. Genome-wide association studies were performed utilizing single-step Bayesian analysis. For wool traits, a total of 35 genomic windows surpassed the significance threshold (PVE ≥ 0.25%). The proportion of the total additive genetic variance explained by those windows was 4.85 and 9.06% for FD and CFW, respectively. There were 42 windows significantly associated with LWM, which collectively explained 43.2% of the additive genetic variance. For BCS, 22 relevant windows accounted for more than 40% of the additive genetic variance, whereas for the reproduction traits, 53 genomic windows (24 and 29 for PR and LP, respectively) reached the suggestive threshold of 0.25% of the PVE. Within the top 10 windows for each trait, we identified several genes showing potential associations with the wool (e.g., IGF-1, TGFB2R, PRKCA), live weight (e.g., CAST, LAP3, MED28, HERC6), body condition score (e.g., CDH10, TMC2, SIRPA, CPXM1) or reproduction traits (e.g., ADCY1, LEPR, GHR, LPAR2) of the mixed-age ewes.

High Expression of ACOT2 Predicts Worse Overall Survival and Abnormal Lipid Metabolism: A Potential Target for Acute Myeloid Leukemia

Acyl-CoA thioesterase (ACOT) plays a considerable role in lipid metabolism, which is closely related to the occurrence and development of cancer, nevertheless, its role has not been fully elucidated in acute myeloid leukemia (AML). To explore the role of ACOT2 in AML and to provide a potential therapeutic target for AML, the expression pattern of ACOT was investigated based on the TNMplot, Gene Expression Profiling Interactive Analysis (GEPIA), and Cancer Cell Line Encyclopedia (CCLE) database, and diagnostic value, prognostic value, and clinical phenotype of ACOT were explored based on data from The Cancer Genome Atlas (TCGA). Functional annotation and enrichment analysis of the common targets between ACOT2 coexpressed and AML-related genes were further performed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) analyses. The protein-protein interaction (PPI) network of ACOT2 coexpressed genes and functional ACOT2-related metabolites association network were constructed based on GeneMANIA and Human Metabolome Database. Among ACOTs, ACOT2 was highly expressed in AML compared to normal control subjects according to TNMplot, GEPIA, and CCLE database, which was significantly associated with poor overall survival (OS) in AML ( $P=0.003$ ). Moreover, ACOT2 exhibited excellent diagnostic efficiency for AML (AUC: 1.000) and related to French-American-British (FAB) classification and cytogenetics. GO, KEGG, and GSEA analyses of 71 common targets between ACOT2 coexpressed and AML-related genes revealed that ACOT2 is closely related to ACOT1, ACOT4, enoyl-acyl carrier protein reductase, mitochondrial (MECR), puromycin-sensitive aminopeptidase (NPEPPS), SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily B member 1 (SMARCB1), and long-chain fatty acid-CoA ligase 1 (ACSL1) in PPI network, and plays a significant role in lipid metabolism, that is, involved in fatty acid elongation and biosynthesis of unsaturated fatty acids. Collectively, the increase of ACOT2 may be an important characteristic of worse OS and abnormal lipid metabolism, suggesting that ACOT2 may become a potential therapeutic target for AML.

A distinct lipid metabolism signature of acute myeloid leukemia with prognostic value

Background

Acute myeloid leukemia (AML) is a highly aggressive hematological malignancy characterized by extensive genetic abnormalities that might affect the prognosis and provide potential drug targets for treatment. Reprogramming of lipid metabolism plays important roles in tumorigenesis and progression and has been newly recognized a new hallmark of malignancy, and some related molecules in the signal pathways could be prognostic biomarkers and potential therapeutic targets for cancer treatment. However, the clinical value of lipid metabolism reprogramming in AML has not been systematically explored. In this study, we aim to explore the clinical value of lipid metabolism reprogramming and develop a prognostic risk signature for AML.

Methods

We implemented univariate Cox regression analysis to identify the prognosis-related lipid metabolism genes, and then performed LASSO analysis to develop the risk signature with six lipid metabolism-related genes (LDLRAP1, PNPLA6, DGKA, PLA2G4A, CBR1, and EBP). The risk scores of samples were calculated and divided into low- and high-risk groups by the median risk score.

Results

Survival analysis showed the high-risk group hold the significantly poorer outcomes than the low-risk group. The signature was validated in the GEO datasets and displayed a robust prognostic value in the stratification analysis. Multivariate analysis revealed the signature was an independent prognostic factor for AML patients and could serve as a potential prognostic biomarker in clinical evaluation. Furthermore, the risk signature was also found to be closely related to immune landscape and immunotherapy response in AML.

Conclusions

Overall, we conducted a comprehensive analysis of lipid metabolism in AML and constructed a risk signature with six genes related to lipid metabolism for the malignancy, prognosis, and immune landscape of AML, and our study might contribute to better understanding in the use of metabolites and metabolic pathways as the potential prognostic biomarkers and therapeutic targets for AML.

Clinically Tractable Outcome Prediction of non-WNT/non-SHH Medulloblastoma Based on TPD52 Immunohistochemistry in a Multicohort Study

PURPOSE

International consensus and the 2021 WHO classification recognize eight molecular subgroups among non-WNT/non-SHH (Group 3/4) medulloblastoma, representing ~60% of tumors. However, very few clinical centers worldwide possess the technical capabilities to determine DNA-methylation profiles or other molecular parameters of high-risk for Group 3/4 tumors. As a result, biomarker-driven risk stratification and therapy assignment constitutes a major challenge in medulloblastoma research. Here, we identify an immunohistochemistry (IHC) marker as a clinically tractable method for improved medulloblastoma risk stratification.

EXPERIMENTAL DESIGN

We bioinformatically analyzed published medulloblastoma transcriptomes and proteomes identifying as a potential biomarker TPD52, whose IHC prognostic value was validated across three Group 3/4 medulloblastoma clinical cohorts (n = 387) treated with conventional therapies.

RESULTS

TPD52 IHC positivity represented a significant independent predictor of early relapse and death for Group 3/4 medulloblastoma (HRs between 3.67-26.7 [95% CIs between 1.00-706.23], p = 0.05, 0.017 and 0.0058). Cross-validated survival models incorporating TPD52 IHC with clinical features outperformed existing state-of-the-art risk stratification schemes, and reclassified ~50% of patients into more appropriate risk categories. Finally, TPD52 immunopositivity was a predictive indicator of poor response to chemotherapy (HR 12.66 [95% CI 3.53-45.40], p < 0.0001), suggesting important implication for therapeutic choices.

CONCLUSIONS

The current study redefines the approach to risk stratification in Group 3/4 medulloblastoma in global practice. Since integration of TPD52 IHC in classification algorithms significantly improved outcome prediction, this test could be rapidly adopted for risk stratification on a global scale, independently of advanced but technically challenging molecular profiling techniques.

Loss-of-function mutations in the histone methyltransferase EZH2 promote chemotherapy resistance in AML

Chemotherapy resistance is the main impediment in the treatment of acute myeloid leukaemia (AML). Despite rapid advances, the various mechanisms inducing resistance development remain to be defined in detail. Here we report that loss-of-function mutations (LOF) in the histone methyltransferase EZH2 have the potential to confer resistance against the chemotherapeutic agent cytarabine. We identify seven distinct EZH2 mutations leading to loss of H3K27 trimethylation via multiple mechanisms. Analysis of matched diagnosis and relapse samples reveal a heterogenous regulation of EZH2 and a loss of EZH2 in 50% of patients. We confirm that loss of EZH2 induces resistance against cytarabine in the cell lines HEK293T and K562 as well as in a patient-derived xenograft model. Proteomics and transcriptomics analysis reveal that resistance is conferred by upregulation of multiple direct and indirect EZH2 target genes that are involved in apoptosis evasion, augmentation of proliferation and alteration of transmembrane transporter function. Our data indicate that loss of EZH2 results in upregulation of its target genes, providing the cell with a selective growth advantage, which mediates chemotherapy resistance.

Identification of prognostic mRNAs in metastatic cutaneous melanoma

Cutaneous melanoma is the most common cause of skin cancer-related deaths worldwide. There is an urgent need to identify prognostic biomarkers to facilitate decision-making for treatment of metastatic cutaneous melanoma. Gene expression microarrays and RNA-seq technology have recently improved or changed current prognostic and therapeutic strategies for several cancers. However, according to the current melanoma staging system, prognosis is almost entirely dependent on clinicopathological features. To identify novel prognostic biomarkers, we investigated gene expression and clinical data for patients with cutaneous melanoma from three cohorts of The Cancer Genome Atlas and Gene Expression Omnibus. Kaplan-Meier survival analysis using median values of each gene as cutoff value revealed that nine genes (ABCC3, CAPS2, CCR6, CDCA8, CLU, DPF1, PTK2B, SATB1, and SYNE1) were statistically significant prognostic biomarkers of metastatic cutaneous melanoma in all three independent cohorts. Low expression of two genes (CDCA8 and DPF1) and high expression of seven genes (ABCC3, CAPS2, CCR6, CLU, PTK2B, SATB1, and SYNE) were significantly associated with positive metastatic cutaneous melanoma prognoses. In conclusion, we suggest nine novel prognostic biomarkers for cutaneous metastatic melanoma.

AML poor prognosis factor, TPD52, is associated with the maintenance of haematopoietic stem cells through regulation of cell proliferation

Acute myeloid leukaemia (AML) is a blood cancer where undifferentiated myeloid cells are increased in the bone marrow and peripheral blood. As AML is dangerous and shows poor prognosis, many researchers categorised the relevant cytogenetic factors according to risk and prognosis. However, the specific reasons for poor cytogenetic factors remain unknown. We analysed a large data set from AML patients and found that TPD52 expression is elevated in patient groups with poor cytogenetic factors. As the amino acid sequence of TPD52 is evolutionally conserved in vertebrates, zebrafish embryos were used to investigate the function of TPD52. Since myeloid-biased haematopoietic stem cells (HSCs) are relevant to AML, the function of TPD52 in the development of HSCs was investigated. We determined that the zebrafish paralog, tpd52, is important for the maintenance of HSCs through regulation of cell proliferation. As tpd52 is linked to cell proliferation in zebrafish embryos, the proliferation-related gene, CD59, was correlated to TPD52 in every AML cohort with a high correlation coefficient. We suggest that TPD52 can be a novel therapeutic target for AML patients with poor cytogenetic factors. Additionally, more studies between TPD52 and CD59 will further increase the value of TPD52 as a novel target.

Endogenous retroviruses are a source of enhancers with oncogenic potential in acute myeloid leukaemia

Acute myeloid leukemia (AML) is characterised by a series of genetic and epigenetic alterations that result in deregulation of transcriptional networks. One understudied source of transcriptional regulators are transposable elements (TEs), whose aberrant usage could contribute to oncogenic transcriptional circuits. However, the regulatory influence of TEs and their links to AML pathogenesis remain unexplored. Here we identify six endogenous retrovirus (ERV) families with AML-associated enhancer chromatin signatures that are enriched in binding of key regulators of hematopoiesis and AML pathogenesis. Using both locus-specific genetic editing and simultaneous epigenetic silencing of multiple ERVs, we demonstrate that ERV deregulation directly alters the expression of adjacent genes in AML. Strikingly, deletion or epigenetic silencing of an ERV-derived enhancer suppresses cell growth by inducing apoptosis in leukemia cell lines. This work reveals that ERVs are a previously unappreciated source of AML enhancers that may be exploited by cancer cells to help drive tumour heterogeneity and evolution.

Transposable elements are a potential source of transcriptional regulators, but how these sequences contribute to oncogenesis remains poorly understood. Here, the authors identify endogenous retroviruses (ERVs) with acute myeloid leukemia (AML)-associated enhancer chromatin signatures, and provide evidence that ERV activation provides an additional layer of gene regulation in AML.

Systematic Construction and Validation of a Metabolic Risk Model for Prognostic Prediction in Acute Myelogenous Leukemia

Background: Acute myelogenous leukemia (AML) is a heterogeneous disease with recurrent gene mutations and variations in disease-associated gene expression, which may be useful for prognostic prediction. Methods: RNA matrix and clinical data of AML were downloaded from GEO, TCGA, and TARGET databases. Prognostic metabolic genes were identified by LASSO analysis to establish a metabolic model. Prognostic accuracy of the model was quantified by time-dependent receiver operating characteristic curves and the area under the curve (AUC). Survival analysis was performed by log-rank tests. Enriched pathways in different metabolic risk statuses were evaluated by gene set enrichment analyses (GSEA). Results: We identified nine genes to construct a prognostic model of shorter survival in the high-risk vs. low-risk group. The prognostic model showed good predictive efficacy, with AUCs for 5-year overall survival of 0.78 (0.73-0.83), 0.76 (0.62-0.89), and 0.66 (0.57-0.75) in the training, adult external, and pediatric external cohorts, respectively. Multivariable analysis demonstrated that the metabolic signature had independent prognostic value with hazard ratios of 2.75 (2.06-3.66), 1.89 (1.09-3.29), and 1.96 (1.00-3.84) in the training, adult external, and pediatric external cohorts, respectively. Combining metabolic signatures and classic prognostic factors improved 5-year overall survival prediction compared to the prediction by classic prognostic factors (p < 0.05). GSEA revealed that most pathways were metabolism-related, indicating potential mechanisms. Conclusion: We identified dysregulated metabolic features in AML and constructed a prognostic model to predict the survival of patients with AML.

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 GABA_A, 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.

Proteomic and histopathological characterisation of sicca subjects and primary Sjögren's syndrome patients reveals promising tear, saliva and extracellular vesicle disease biomarkers

Background

Mononuclear cell infiltration of exocrine glands, production of Ro/SSA and La/SSB autoantibodies, along with oral and ocular dryness, are characteristic features of primary Sjögren’s syndrome (pSS). Non-SS sicca subjects, an underexplored group in relation to pSS, display similar sicca symptoms, with possible mild signs of inflammation in their salivary glands, yet with no serological detection of autoantibody production. In this study, we investigated inflammatory manifestations in the salivary gland tissue, tear fluid and saliva of non-SS subjects, as compared to pSS patients and healthy individuals.

Methods

Fifteen non-SS, 10 pSS and 10 healthy subjects were included in the analyses. Histological evaluation of salivary gland biopsies was performed. Liquid chromatography-mass spectrometry (LC-MS) was conducted on tear fluid and stimulated whole saliva, and proteomic biomarker profiles were generated. Extracellular vesicle (EVs) isolation and characterisation from both fluids were also combined with LC-MS. The LC-MS data were analysed for quantitative differences between patient and control groups using Scaffold. Database for Annotation, Visualization and Integrated Discovery (DAVID) and Functional Enrichment Analysis Tool (FunRich) were applied for functional analyses.

Results

Histopathological evaluation of salivary gland biopsies showed implications of milder inflammation in non-SS subjects through mononuclear cell infiltration, fibrosis and fatty replacement, as compared to pSS patients. Although unaffected in the non-SS group, upregulation of proinflammatory pathways and proteins involved in ubiquitination (LMO7 and HUWE1) and B cell differentiation (TPD52) were detected in tear fluid of pSS patients. Moreover, overexpression of proteins STOM, ANXA4 and ANXA1, regulating cellular innate and adaptive immunological pathways, were further identified in EVs from tear fluid of pSS patients. Finally, whole saliva and EVs isolated from whole saliva of pSS patients expressed proteins vital for innate MHC class I cellular regulation (NGAL) and T cell activation (CD44).

Conclusions

Non-SS sicca subjects may show implications of mild inflammation in their glandular tissue, while their protein profile was strikingly more similar to healthy controls than to pSS patients. Hence, the tear and salivary biomarkers identified could be implemented as potential non-invasive diagnostic tools that may aid in increasing diagnostic accuracy when evaluating non-SS subjects and pSS patients and monitoring disease progression.

Electronic supplementary material

The online version of this article (10.1186/s13075-019-1961-4) contains supplementary material, which is available to authorized users.

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.

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.

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.