To gain more insight into the role of chromosomal instability (CIN), the cytogenetic hallmark of most solid tumors, we performed fluorescence in situ hybridization (FISH) on interphase nuclei of cytological specimens enabling the correct detection of chromosome copies in intact tumor cells of 18 well (G1), moderately (G2), or poorly (G3) differentiated hepatocellular carcinomas (HCCs). A close correlation between the morphological dedifferentiation and increasing copy numbers and variation of FISH signals was seen for chromosomes 1 and 8, respectively (P ≤ 0.0002). Four HCC G1 had constant chromosome patterns for chromosomes 1 and/or 8 with a mean of signals per nucleus ≤5.08 and ≤3 different signal combinations, indicating a low level of CIN, as confirmed by FISH using probes for centromeres of chromosomes 3, 7, and 17. In contrast to this, five HCC G2–3 revealed ≥8.46 signals per nucleus and 23–41 different signal combinations, indicating high levels of CIN. In the remaining cases, signal counts from 5.96–8.46 and 7–15 combinations were seen. Here, nuclei with constant aberration patterns and low copy numbers occurred alongside nuclei with inconstant patterns and high copy numbers. It is evident that in these cases a transition from well to moderately differentiated HCC developed in parallel to an increase in CIN, possibly induced by a major dysregulation of mitotic control mechanisms. In conclusion, CIN may induce a stepwise increase of aneuploidy in HCC that is mirrored by the morphological dedifferentiation of tumor cells.

Induction of aneuploidy by increasing chromosomal instability during dedifferentiation of hepatocellular carcinoma

Background Clear cell renal cell carcinoma (ccRCC) is a common genitourinary cancer type with a high mortality rate. Due to a diverse range of biochemical alterations and a high level of tumor heterogeneity, it is crucial to select highly validated prognostic biomarkers to be able to identify subtypes of ccRCC early and apply precision medicine approaches. Methods Transcriptome data of ccRCC and clinical traits of patients were obtained from the GSE126964 dataset of Gene Expression Omnibus and The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) database. Weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) screening were applied to detect common differentially co-expressed genes. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analysis, survival analysis, prognostic model establishment, and gene set enrichment analysis were also performed. Immunohistochemical analysis results of the expression levels of prognostic genes were obtained from The Human Protein Atlas. Single-gene RNA sequencing data were obtained from the GSE131685 and GSE171306 datasets. Results In the present study, a total of 2,492 DEGs identified between ccRCC and healthy controls were filtered, revealing 1,300 upregulated genes and 1,192 downregulated genes. Using WGCNA, the turquoise module was identified to be closely associated with ccRCC. Hub genes were identified using the maximal clique centrality algorithm. After having intersected the hub genes and the DEGs in GSE126964 and TCGA-KIRC dataset, and after performing univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses, ALDOB, EFHD1, and ESRRG were identified as significant prognostic factors in patients diagnosed with ccRCC. Single-gene RNA sequencing analysis revealed the expression profile of ALDOB, EFHD1, and ESRRG in different cell types of ccRCC. Conclusions The present results demonstrated that ALDOB, EFHD1, and ESRRG may act as potential targets for medical therapy and could serve as diagnostic biomarkers for ccRCC.

/pdf/identification-of-hub-genes-associated-with-clear-cell-renal-29j8b2g35s.pdf

Identification of Hub Genes Associated With Clear Cell Renal Cell Carcinoma by Integrated Bioinformatics Analysis.

Background Aging is a process that biological changes accumulate with time and lead to increasing susceptibility to diseases like cancer. This study is aimed at establishing an aging-related prognostic signature in colon adenocarcinoma (COAD). Methods The transcriptome data and clinical variables of COAD patients were downloaded from TCGA database. The genes in GOBP_AGING gene set was used for prognostic evaluation by the univariate and multivariate Cox regression analyses. The model was presented by a nomogram and assessed by the Kaplan-Meier curves and calibration curves. The drug response and gene mutation were also performed to implicate the clinical significance. The GO and KEGG analyses were employed to unravel the potential functional mechanism. Results The Gene Set Enrichment Analysis result indicates that GOBP_AGING pathway is significantly enriched in COAD samples. Four aging-related genes are finally used to construct the aging-related prognostic signature: FOXM1, PTH1R, KL, and CGAS. The COAD patients with high risk score have much shorter overall survival in both train cohort and test cohort. The nomogram is then assembled to predict 1-year, 3-year, and 5-year survival. Patients with high risk score have elevated infiltrating B cell naive and attenuated cisplatin sensitivity. The mutation landscape shows that the TTN, FAT4, ZFHX4, APC, and OBSCN gene mutation are different between high risk score patients and low risk score patients. The differentially expressed genes between patients with high score and low score are enriched in B cell receptor signaling pathway. Conclusion We constructed an aging-related signature in COAD patients, which can predict oncological outcome and optimize therapeutic strategy.

/pdf/establishing-and-validating-an-aging-related-prognostic-four-2s6p3pevh7.pdf

Establishing and Validating an Aging-Related Prognostic Four-Gene Signature in Colon Adenocarcinoma.

Purpose Gastric cancer (GC) is one of the most common and fatal malignancies globally. While microsatellite instability (MSI) index has earlier been correlated with survival outcome in gastric cancer patients, the present study aims to construct a risk-stratification model based on immune-related genes in GC patients with varying MSI status. Results The univariate and multivariate Cox regression analyses identified SEMA7A, NUDT6, SCGB3A1, NPR3, PTH1R, and SHC4 as signature genes, which were used to build the prognostic model for GC patients with microsatellite instability-low (MSI-L) and microsatellite stable (MSS). Whereas, for GC patients with microsatellite instability-high (MSI-H), prognostic model was established with three genes (SEMA6A, LTBP1, and BACH2), based on the univariate and multivariate Cox regression, and Kaplan-Meier survival analyses. Conclusion The prognostic immune-related gene signature identified in this study may offer new targets for personalized treatment and immunotherapy for GC patients with MSI-H or MSI-L/MSS status. Methods The Cancer Genome Atlas (TCGA) and ImmPort databases were used to extract expression data and to explore prognostic genes from the immune-related genes (IRGs), respectively. Univariate and multivariate Cox regression analysis were applied to identify IRGs correlated with patient prognosis. The regulatory network between prognostic IRGs and TFs were performed using R software.

Immune-related gene signature predicts overall survival of gastric cancer patients with varying microsatellite instability status.

The parathyroid hormone type 1 receptor (PTH1R), a canonical class B GPCR, is regulated by a positive allosteric modulator, extracellular Ca2+. Calcium ions prolong the residence time of PTH on the PTH1R, leading to increased receptor activation and duration of cAMP signaling. But the essential mechanism of the allosteric behavior of PTH1R is not fully understood. Here, extensive molecular dynamics (MD) simulations are performed for the PTH1R-G-protein combinations with and without Ca2+ to describe how calcium ions allosterically engage receptor-G-protein coupling. We find that the binding of Ca2+ stabilizes the conformation of the PTH1R-PTH-spep (the α5 helix of Gs protein) complex, especially the extracellular loop 1 (ECL1). Moreover, the MM-GBSA result indicates that Ca2+ allosterically promotes the interaction between PTH1R and spep, consistent with the observation of steered molecular dynamics (SMD) simulations. We further illuminate the possible allosteric signaling pathway from the stable Ca2+-coupling site to the intracellular G-protein binding site. These results unveil structural determinants for Ca2+ allosterism in the PTH1R-PTH-spep complex and give insights into pluridimensional GPCR signaling regulated by calcium ions.

Critical Extracellular Ca2+ Dependence of the Binding between PTH1R and a G-Protein Peptide Revealed by MD Simulations.

Background and aim Hypercalcemia is a potentially fatal and not rare complication of hepatocellular carcinoma (HCC), and its underlying mechanism remains unclear. Parathyroid hormone (PTH) is the most important regulator of the concentrations of calcium and phosphate in blood; parathyroid hormone-related protein (PTHrP) was the most frequent cause of humoral hypercalcemia of malignancy; parathyroid hormone 1 receptor (PTH1R) is the common receptor for PTH and PTHrP. The aim of this study is to investigate the expression of PTH, PTHrP, and PTH1R in HCC tissues, and their relationship with clinical pathological characters in HCC. Methods First, a meta-analysis based on online Oncomine Expression Array database was conducted to compare the different mRNA expression of PTH1R, PTH and PTHrP between hepatocellular carcinoma and normal tissues. Then, the protein expression level of differentially expressed gene was examined by immunohistochemistry staining in 223 HCC tissues and 102 non-tumorous liver tissues controls. The relationship between the protein expression and clinicopathological parameters was analyzed by χ2 test, and overall survival analysis was performed using Kaplan-Meier survival analysis. Results PTH1R mRNA expression was significantly lower in HCC tissues compared with normal tissues, while the expression of PTH and PTHrP showed no significant difference between HCC tissues and normal tissues. High PTH1R protein expression was found in 90/102 cases of adjacent non-tumorous liver tissues, and in 91 of 223 cases of HCC tissues. PTH1R expression was significantly related to tumor size, Edmondson Grade, AFP, and overall survival. Conclusions PTH1R may be the major cause of hypercalcemia in HCC, and the decreased PTH1R expression was a poor prognosis in HCC.

Decreased expression of PTH1R is a poor prognosis in hepatocellular carcinoma.

Background and aim: ZW10 interacting kinetochore protein 1 (Zwint-1), one of the major kinetochore proteins, is essential for kinetochore function, such as spindle assembly checkpoint function and kinetochore-microtubule attachment. Recently, it has been found over-expressed in some human cancers, including ovarian cancer, bladder cancer, and pulmonary adenocarcinoma. However, few studies of the expression of Zwint-1 in hepatocellular carcinoma (HCC) have been reported. This study is aimed to investigate the expression of Zwint-1 and its relationship with clinical pathological characters in HCC. Methods: The expression of Zwint-1 protein was analyzed by immunohistochemistry staining on tissue microarrays containing 171 HCC tissues and 187 control non-tumorous liver tissues. The relationships between the Zwint-1 expression and the clinicopathological parameters, and survival analysis were investigated using SPSS software 13.0. Results: Zwint-1 was found uniformly expressed in adjacent non-tumorous liver tissues (184/187, 98.40%), while was significantly decreased in HCC tissues, or even absent (150 of 171, 61.82%, P<0.001). The expression of Zwint-1 was negatively associated with age, tumor size, and Edmondson Grade. Besides, HCC patients with low Zwint-1 expression were also correlated with poor overall survival of the patients. Conclusions: Decreased expression of Zwint-1 was associated with poor prognosis in HCC.

Decreased expression of Zwint-1 is associated with poor prognosis in hepatocellular carcinoma.

Background Citron kinase (CIT) is a protein related to cytokinesis and is an important abscission regulator. However, the relationship between CIT and hepatocellular carcinoma (HCC) is unclear. The aim of this study was to investigate the expression CIT in HCC tissues, and explore the connection between this expression and clinicopathological characteristics of HCC. Methods Immunohistochemistry staining on 235 HCC tissues and 96 non-tumorous liver tissues controls was performed to examine the CIT protein expression. We then analyzed the correlation between protein expression and clinicopathological parameters via χ2 tests, and we performed overall survival analyses via the Kaplan-Meier survival approach. Based on the online Oncomine Expression Array and UALCAN databases, we more broadly compared CIT mRNA expression between normal and HCC tissues. Finally, we compared CIT mRNA expression in these databases to protein expression in our study and explored potential sources for any observe differences. Results Compared to normal tissues, CIT expression was significantly lower in HCC tissues. Low CIT expression was found to be related to gender, tumor size, Edmondson Grade, Microvascular invasion, serum AFP levels and poor overall survival. Based on the online databases, CIT mRNA expression was found to be high in HCC tissues and decreased in normal tissues. We hypothesize that this unexpected result is due to a negative feedback loop whereby low protein CIT levels mediate increased CIT mRNA levels. Conclusions Lower CIT protein levels are associated with a poorer prognosis in HCC patients, and lower CIT protein levels may mediate a negative feedback loop leading to increased CIT mRNA levels.

https://tcr.amegroups.com/article/download/37601/pdf

Low expression of citron kinase is associated with poor patient outcomes in hepatocellular carcinoma

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Decreased expression of PTH1R is a poor prognosis in hepatocellular carcinoma.

Decreased expression of Zwint-1 is associated with poor prognosis in hepatocellular carcinoma.

Low expression of citron kinase is associated with poor patient outcomes in hepatocellular carcinoma