Original tumour suppressor gene polycystic kidney and hepatic disease 1-like 1 is associated with thyroid cancer cell progression

PKHD1L1 is required for stereocilia bundle maintenance, durable hearing function and resilience to noise exposure

Sensory hair cells of the cochlea are essential for hearing, relying on the mechanosensitive stereocilia bundle at their apical pole for their function. Polycystic Kidney and Hepatic Disease 1-Like 1 (PKHD1L1) is a stereocilia protein required for normal hearing in mice, and for the formation of the transient stereocilia surface coat, expressed during early postnatal development. While the function of the stereocilia coat remains unclear, growing evidence supports PKHD1L1 as a human deafness gene. In this study we carry out in depth characterization of PKHD1L1 expression in mice during development and adulthood, analyze hair-cell bundle morphology and hearing function in aging PKHD1L1-defficient mouse lines, and assess their susceptibility to noise damage. Our findings reveal that PKHD1L1-deficient mice display no disruption to bundle cohesion or tectorial membrane attachment-crown formation during development. However, starting from 6 weeks of age, PKHD1L1-defficient mice display missing stereocilia and disruptions to bundle coherence. Both conditional and constitutive PKHD1L1 knock-out mice develop high-frequency hearing loss progressing to lower frequencies with age. Furthermore, PKHD1L1-deficient mice are susceptible to permanent hearing loss following moderate acoustic overexposure, which induces only temporary hearing threshold shifts in wild-type mice. These results suggest a role for PKHD1L1 in establishing robust sensory hair bundles during development, necessary for maintaining bundle cohesion and function in response to acoustic trauma and aging.

PKHD1L1, a gene involved in the stereocilia coat, causes autosomal recessive nonsyndromic hearing loss

Identification of genes associated with nonsyndromic hearing loss is a crucial endeavor given the substantial number of individuals who remain without a diagnosis after even the most advanced genetic testing. PKHD1L1 was established as necessary for the formation of the cochlear hair-cell stereociliary coat and causes hearing loss in mice and zebrafish when mutated. We sought to determine if biallelic variants in PKHD1L1 also cause hearing loss in humans. Exome sequencing was performed on DNA of four families segregating autosomal recessive nonsyndromic sensorineural hearing loss. Compound heterozygous p.[(Gly129Ser)];p.[(Gly1314Val)] and p.[(Gly605Arg)];p[(Leu2818TyrfsTer5)], homozygous missense p.(His2479Gln) and nonsense p.(Arg3381Ter) variants were identified in PKHD1L1 that were predicted to be damaging using in silico pathogenicity prediction methods. In vitro functional analysis of two missense variants was performed using purified recombinant PKHD1L1 protein fragments. We then evaluated protein thermodynamic stability with and without the missense variants found in one of the families and performed a minigene splicing assay for another variant. In silico molecular modeling using AlphaFold2 and protein sequence alignment analysis were carried out to further explore potential variant effects on structure. In vitro functional assessment indicated that both engineered PKHD1L1 p.(Gly129Ser) and p.(Gly1314Val) mutant constructs significantly reduced the folding and structural stabilities of the expressed protein fragments, providing further evidence to support pathogenicity of these variants. Minigene assay of the c.1813G>A p.(Gly605Arg) variant, located at the boundary of exon 17, revealed exon skipping leading to an in-frame deletion of 48 amino acids. In silico molecular modeling exposed key structural features that might suggest PKHD1L1 protein destabilization. Multiple lines of evidence collectively associate PKHD1L1 with nonsyndromic mild-moderate to severe sensorineural hearing loss. PKHD1L1 testing in individuals with mild-moderate hearing loss may identify further affected families.

PKHD1L1, A Gene Involved in the Stereocilia Coat, Causes Autosomal Recessive Nonsyndromic Hearing Loss

Identification of genes associated with nonsyndromic hearing loss is a crucial endeavor given the substantial number of individuals who remain without a diagnosis after even the most advanced genetic testing. PKHD1L1 was established as necessary for the formation of the cochlear hair-cell stereociliary coat and causes hearing loss in mice and zebrafish when mutated. We sought to determine if biallelic variants in PKHD1L1 also cause hearing loss in humans. Exome sequencing was performed on DNA of four families segregating autosomal recessive nonsyndromic sensorineural hearing loss. Compound heterozygous p.[(Gly129Ser)];p.[(Gly1314Val)] and p.[(Gly605Arg)];p[(Leu2818TyrfsTer5)], homozygous missense p.(His2479Gln) and nonsense p.(Arg3381Ter) variants were identified in PKHD1L1 that were predicted to be damaging using in silico pathogenicity prediction methods. In vitro functional analysis of two missense variants was performed using purified recombinant PKHD1L1 protein fragments. We then evaluated protein thermodynamic stability with and without the missense variants found in one of the families and performed a minigene splicing assay for another variant. In silico molecular modelling using AlphaFold2 and protein sequence alignment analysis were carried out to further explore potential variant effects on structure. In vitro functional assessment indicated that both engineered PKHD1L1 p.(Gly129Ser) and p.(Gly1314Val) mutant constructs significantly reduced the folding and structural stabilities of the expressed protein fragments, providing further evidence to support pathogenicity of these variants. Minigene assay of the c.1813G>A p.(Gly605Arg) variant, located at the boundary of exon 17, revealed exon skipping leading to an in-frame deletion of 48 amino acids. In silico molecular modelling exposed key structural features that might suggest PKHD1L1 protein destabilization. Multiple lines of evidence collectively associate PKHD1L1 with nonsyndromic mild-moderate to severe sensorineural hearing loss. PKHD1L1 testing in individuals with mild-moderate hearing loss may identify further affected families.

Excavation of diagnostic biomarkers and construction of prognostic model for clear cell renal cell carcinoma based on urine proteomics

Purpose

Clear cell renal cell carcinoma (ccRCC) is the most common pathology type in kidney cancer. However, the prognosis of advanced ccRCC is unsatisfactory. Thus, early diagnosis becomes one of the most important research priorities of ccRCC. However, currently available studies about ccRCC lack urine-related further studies. In this study, we applied proteomics to search urinary biomarkers to assist early diagnosis of ccRCC. In addition, we constructed a prognostic model to assist judge patients' prognosis.

Materials and methods

Urine which was used to perform 4D label-free quantitative proteomics was collected from 12 ccRCC patients and 11 non-tumor patients with no urinary system diseases. The urine of 12 patients with ccRCC confirmed by pathological examination after surgery was collected before operatoin. Bioinformatics analysis was used to describe the urinary proteomics landscape of these patients with ccRCC. The top ten proteins with the highest expression content were selected as the basis for subsequent validation. Urine from 46 ccRCC patients and 45 control patients were collected to use for verification by enzyme linked immunosorbent assay (ELISA). In order to assess the prognostic value of urine proteomics, a prognostic model was constructed by COX regression analysis on the intersection of RNA-sequencing data in The Cancer Genome Atlas (TCGA) database and our urine proteomic data.

Results

133 proteins differentially expressed in the urinary samples were found and 85 proteins (Fold Change, FC>1.5) were identified up-regulated while 48 down-regulated (FC<0.5). Top 10 proteins including S100A14, PKHD1L1, FABP4, ITIH2, C3, C8G, C2, ATF6, ANGPTL6, F13B were performed ELISA to verify. The results showed that PKHD1L1, ANGPTL6, FABP4 and C3 were statistically significant (P<0.05). We performed multivariate logistic regression analysis and plotted a nomogram. Receiver operating characteristic (ROC) curve indicted that the diagnostic efficiency of combined indicators is satisfactory (Aare under curve, AUC=0.835). Furthermore, the prognostic value of the urine proteomics was explored through the intersection between urine proteomics and TCGA RNA-seq data. Thus, COX regression analysis showed that VSIG4, HLA-DRA, SERPINF1, and IGLV2-23 were statistically significant (P<0.05).

Conclusion

Our study indicated that the application of urine proteomics to explore diagnostic biomarkers and to construct prognostic models of renal clear cell carcinoma is of certain clinical value. PKHD1L1, ANGPTL6, FABP4 and C3 can assist to diagnose ccRCC. The prognostic model constituted of VSIG4, HLA-DRA, SERPINF1, and IGLV2-23 can significantly predict the prognosis of ccRCC patients, but this still needs more clinical trials to verify.

Role and mechanism of benzo[a]pyrene in the transformation of chronic obstructive pulmonary disease into lung adenocarcinoma

OBJECTIVE

This experiment is explores the genes that play a key role, their expression changes and the biological processes in the transformation of chronic obstructive pulmonary disease (COPD) into lung adenocarcinoma (LAC). Meanwhile, identify the effects of Benzo[a]pyrene (BaP) in the conversion of COPD into LAC.

METHODS

1. Differential expression genes of COPD and LAC were screened and analyzed by high-throughput microarray data between the two diseases and their respective control groups. 2. The screened genes were used for routine bioinformatics analysis such as functional analysis, expression verification, protein interaction analysis and functional enrichment. 3. Cigarette smoke extract (CSE) combined with lipopolysaccharide (LPS) was used to establish an in vitro COPD model. 4. MTT assay was used to detect the influence of B(a)P in effect on A549 cell proliferation. CCK-8, Transwell invasion test and scratch test were used to detect the cell proliferation, invasion and migration ability, while qPCR and Western Blot tests were used to observe the cell proliferation, apoptosis and changes in related indicators such as EMT. 5. Experimental method of separately adding agonists (tBHQ) and inhibitors (DIC) of NQO1 was used to confirm the effect of NQO1 on A549 cell proliferation, apoptosis, migration and invasion. 6. To further clarify whether BaP exerted effect on cell proliferation, apoptosis, migration and invasion through NQO1, we knocked down NQO1 gene and then infecting cells with BaP.

RESULTS

1. We screened genes of COPD and LAC using datasets from GSE151052, GSE118370, and GSE140797. After screening, the genes upregulated in COPD and downregulated in LAC were RTKN2, SLC6A4, and HBB, the gene downregulated in COPD and upregulated in LAC was NQO1, the genes downregulated in both COPD and LAC were FPR1, LYVE1 and PKHD1L1. 2. The main signaling pathways in which the target genes were enriched are cell cycle, EMT, PI3K/AKT, and apoptosis. In the data included GEPIA, PKHD1L1, FPR1, LYVE1, RTKN2, HBB, and SLC6A4 were significantly downregulated and NQO1 was upregulated in LAC relative to controls. In addition, there were 46 interaction proteins in the target genes, and the functions they enriched included hydrogen peroxide catabolism, etc. 3. When A549 cell was stimulated with 100 ng/mL LPS+ 10% CSE, the COX-2 expression indicated that COPD model in vitro was successfully established. 4. The optimal dose and action time were screened which were 1 μM and 24 h. Compared to the control group, COPD and BaP group increased cell proliferation and invasion capabilities. On the basis of COPD, adding BaP could further increase the proliferation and migration capabilities. Interestingly, the levels of NQO1 decreased in COPD models, while increased by BaP. 5. tBHQ can increase the proliferation and migration capacity of A549 cells, which is inhibited by the addition of DIC. 6. The enhanced proliferation, migration and invasion of A549 cells by BaP were attenuated after knockdown of NQO1.

CONCLUSION

Our study reveals that PKHD1L1, FPR1, LYVE1, RTKN2, HBB, SLC6A4 and NQO1 may play an important role in the conversion of COPD to LAC. High NQO1 expression may increase the proliferation and migration ability of A549 cells, and BaP may promote the EMT state by increasing the expression of NQO1, thereby making the COPD model in vitro expose the tumor characteristics.

Analysis of the Mechanism of Maslinic Acid on Papillary Thyroid Carcinoma Based on RNA-Seq Technology

Objective

This study analyzed gene sequence changes in the thyroid papillary carcinoma (PTC) cell line TPC-1 treated with the natural compound maslinic acid (MA) through RNA-sequencing (RNA-seq) and identified the necessary genes to provide a basis for the study of the molecular mechanism of action of MA in PTC treatment.

Methods

RNA-seq technology was used to detect genetic differences between the normal cell group (Nthy-ori 3-1) and the TPC-1 cell group (N vs T). Then, gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Venn diagram analysis of shared genes, and protein–protein interaction (PPI) network analysis were used to analyze the therapeutic effect of the MA on TPC-1 cells. Real-time quantitative PCR (qRT-PCR) was used to verify six key genes.

Results

GO and KEGG analyses showed that four crucial signaling pathways are related to TPC development: cytoplasmic molecule (cell adhesion molecules), neuroactive ligand–receptor interaction, tumor transcriptional disorder, and cytokine–cytokine interaction. The Venn diagram revealed 434 genes were shared between the MA vs T-group and 387 genes were shared between the MATH vs T and N vs T groups. PPI and ClueGO showed that NLRP3, SERPINE1, CD74, EDN1, HMOX1, and CXCL1 genes were significantly associated with PTC, while CXCL1, HMOX1, and other factors were mainly involved in the cytokine–cytokine interaction. The qRT-PCR results showed that the expression of NLRP3, EDN1, HMOX1, and CXCL1 genes was significantly upregulated in the TPC-1 group but significantly downregulated after MA treatment (p < 0.01). SERPINE1 and CD74 genes were not expressed in TPC-1 cells, whereas they were significantly upregulated after MA treatment (p < 0.01).

Conclusions

This present study proves for the first time that MA can treat PTC, and the preliminary identification of key genes and rich signal transduction pathways provides potential biomarkers. It also provides potential biomarkers for the treatment of PTC with the natural compound MA and preliminarily discusses the therapeutic mechanism of action of MA against PTC, which is helpful for the further diagnosis and treatment of PTC patients.

An 11-Gene Signature Risk-Prediction Model Based on Prognosis-Related miRNAs and Their Target Genes in Lung Adenocarcinoma

Aberrant expression of microRNAs may affect tumorigenesis and progression by regulating their target genes. This study aimed to construct a risk model for predicting the prognosis of patients with lung adenocarcinoma (LUAD) based on differentially expressed microRNA-regulated target genes. The miRNA sequencing data, RNA sequencing data, and patients’ LUAD clinical data were downloaded from the The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs and genes were screened out by combining differential analysis with LASSO regression analysis to further screen out miRNAs associated with patients’ prognosis, and target gene prediction was performed for these miRNAs using a target gene database. Overlapping gene screening was performed for target genes and differentially expressed genes. LASSO regression analysis and survival analysis were then used to identify key genes. Risk score equations for prognostic models were established using multifactorial COX regression analysis to construct survival prognostic models, and the accuracy of the models was evaluated using subject working characteristic curves. The groups were divided into high- and low-risk groups according to the median risk score, and the correlation with the clinicopathological characteristics of the patients was observed. A total of 123 up-regulated miRNAs and 22 down-regulated miRNAs were obtained in this study. Five prognosis-related miRNAs were screened using LASSO regression analysis and Kaplan-Meier method validation, and their target genes were screened with the overlap of differentially expressed genes before multifactorial COX analysis finally resulted in an 11-gene risk model for predicting patient prognosis. The area under the ROC curve proved that the model has high accuracy. The 11-gene risk-prediction model constructed in this study may be an effective predictor of prognosis.

A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD)

Background

Lung adenocarcinoma (LUAD) is one of the most common types in the world with a high mortality rate. Despite advances in treatment strategies, the overall survival (OS) remains short. Our study aims to establish a reliable prognostic signature closely related to the survival of LUAD patients that can better predict prognosis and possibly help with individual monitoring of LUAD patients.

Methods

Raw RNA-sequencing data were obtained from Fudan University and used as a training group. Differentially expressed genes (DEGs) for the training group were screened. The univariate, least absolute shrinkage and selection operator (LASSO), and multivariate cox regression analysis were conducted to identify the candidate prognostic genes and construct the risk score model. Kaplan–Meier analysis, time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic power and performance of the signature. Moreover, The Cancer Genome Atlas (TCGA-LUAD) dataset was further used to validate the predictive ability of prognostic signature.

Results

A prognostic signature consisting of seven prognostic-related genes was constructed using the training group. The 7-gene prognostic signature significantly grouped patients in high and low-risk groups in terms of overall survival in the training cohort [hazard ratio, HR = 8.94, 95% confidence interval (95% CI)] [2.041–39.2]; P = 0.0004), and in the validation cohort (HR = 2.41, 95% CI [1.779–3.276]; P < 0.0001). Cox regression analysis (univariate and multivariate) demonstrated that the seven-gene signature is an independent prognostic biomarker for predicting the survival of LUAD patients. ROC curves revealed that the 7-gene prognostic signature achieved a good performance in training and validation groups (AUC = 0.91, AUC = 0.7 respectively) in predicting OS for LUAD patients. Furthermore, the stratified analysis of the signature showed another classification to predict the prognosis.

Conclusion

Our study suggested a new and reliable prognostic signature that has a significant implication in predicting overall survival for LUAD patients and may help with early diagnosis and making effective clinical decisions regarding potential individual treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-01975-z.