DIRC3 and near NABP1 genetic polymorphisms are associated laryngeal squamous cell carcinoma patient survival

Epithelial cell-related prognostic risk model in breast cancer based on single-cell and bulk RNA sequencing

Objective

This study aims to construct an epithelial cell-related prognostic risk model for breast cancer (BRCA) and explore its significance.

Methods

GSE42568, GSE10780, GSE245601, and TCGA-BRCA datasets were sourced from public databases. Epithelial cell-related differentially expressed genes were identified using single-cell data analysis. Venn diagrams determined the intersecting genes between epithelial cell-related and BRCA-related genes. Batch Kaplan-Meier (K-M) survival analysis identified core intersecting genes for BRCA overall survival. Consensus clustering, enrichment, LASSO, and COX regression analyses were performed on the core intersecting genes, and then a prognostic risk model was constructed. The diagnostic and prognostic effectiveness of the risk model was subsequently evaluated and immune infiltration analysis was conducted. Finally, qRT-PCR was used to verify the expression of genes in the risk model.

Results

There were 374 intersecting genes between epithelial cell-related and BRCA-related genes, among which 51 core intersecting genes were associated with BRCA prognosis. Consensus clustering categorized TCGA-BRCA into C1 and C2, with shared regulation of the estrogen signaling pathway. Three genes (DIRC3, SLC6A2, TUBA3D) were independent predictors of BRCA prognosis, forming the basis for a risk model. Except for exhibiting satisfactory diagnostic efficacy, the risk score elevation correlated with poor prognosis, elevated matrix, immune, and ESTIMATE scores, and negative correlation with microsatellite instability. The in vitro results confirmed the differential expression levels of DIRC3, SLC6A2, and TUBA3D.

Conclusion

The prognostic risk model associated with epithelial cells demonstrates effective diagnostic performance in BRCA, serving as an independent prognostic factor for BRCA patients. Additionally, it exhibits a correlation with immune scores.

Inconsistency in the expression pattern of a five-lncRNA signature as a potential diagnostic biomarker for gastric cancer patients in bioinformatics and in vitro

OBJECTIVES

Due to diagnosis of gastric cancer in advanced stages as well as its poor prognosis, finding biomarkers is essential. In this study, using the TCGA RNAseq data of gastric cancer patients, we evaluated the diagnostic value of lncRNAs that had differential expression.

MATERIALS AND METHODS

We evaluated P-value, FDR, and log fold change for whole transcripts. Next, by comparison of the RNAseq gene names with the total known lncRNA names, we identified differential expressed lncRNAs. Following this, specificity and sensitivity for lncRNAs coming from the previous step were calculated. For more confirmation, we predicted target genes and performed GO and KEGG signaling pathway analysis. In the end, we examined reliability and consistency of expression of this signature in three gastric cancer cell lines and one of them in twenty tumors and tumor-adjacent normal tissue samples using qRT-PCR.

RESULTS

Five lncRNAs had proper sensitivity and specificity and had target genes involved in cancer-related signaling pathways; however, they showed different expression patterns in TCGA data and in vitro.

CONCLUSION

The results of our study demonstrated that the five-lncRNAs PART1, UCA1, DIRC3, HOTAIR, and HOXA11AS require more investigation to be confirmed as diagnostic biomarkers in gastric cancer.

A systematic review of long non-coding RNAs with a potential role in breast cancer

The human transcriptome contains many non-coding RNAs (ncRNAs), which play important roles in gene regulation. Long noncoding RNAs (lncRNAs) are an important class of ncRNAs with lengths between 200 and 200,000 bases. Unlike mRNA, lncRNA lacks protein-coding features, specifically, open-reading frames, and start and stop codons. LncRNAs have been reported to play a role in the pathogenesis and progression of many cancers, including breast cancer (BC), acting as tumor suppressors or oncogenes. In this review, we systematically mined the literature to identify 65 BC-related lncRNAs. We then perform an integrative bioinformatics analysis to identify 14 lncRNAs with a potential regulatory role in BC. The biological function of these 14 lncRNAs, their regulatory mechanisms, and roles in the initiation and progression of BC are discussed in this review. Additionally, we elaborate on the current and future applications of lncRNAs as diagnostic and/or therapeutic biomarkers in BC.

LncRNA-IUR Sponges miR-24 to Upregulate P53 in Laryngeal Squamous Cell Carcinoma

Objective

The functions of lncRNA-IUR in laryngeal squamous cell carcinoma (LSCC) were investigated in this study.

Methods

RT-qPCR and paired t-test were used to measure and compare expression levels of IUR, miR-24 and p53 in LSCC and non-tumor tissues. Human LSCC cell line UM-SCC-17A was used and transfected by pcDNA3.1 vector to overexpress IUR and miR-24. The transwell assay and wound healing assay illustrated the effect of overexpression of IUR or miR-24 in the cell invasion and migration of LSCC. Subcutaneous tumor model in nude mice was carried out to demonstrate the mechanism between IUR and miR-24 in regulating tumor growth.

Results

We found that IUR was downregulated in LSCC. Low expression levels of IUR were correlated with the poor survival of LSCC patients. Overexpression experiments showed that overexpression of IUR led to increased, while overexpression of miR-24 led to decreased expression levels of p53 in LSCC cells. And bioinformatics analysis showed that IUR may sponge miR-24. Cell proliferation assay showed that overexpression of IUR and p53 led to decreased proliferation rate of LSCC cells, while overexpression of miR-24 led to increased proliferation rate of LSCC cells. We also illustrated that overexpression of IUR promoted cell migration and invasion while miR-24 had opposite effects. In addition, subcutaneous tumor model in nude mice showed that overexpression of miR-24 attenuated the effects of overexpression of IUR on the expression of p53 and cancer cell proliferation.

Conclusion

IUR sponges miR-24 to upregulate p53 in LSCC, thereby inhibiting cancer cell proliferation.

Identification of potential prognostic long non-coding RNA for predicting survival in intrahepatic cholangiocarcinoma

Intrahepatic cholangiocarcinoma (ICC) is an aggressive biliary epithelial tumor with poor prognosis. There are increasing evidences that long non-coding RNAs (lncRNAs) are dysregulated in multifarious tumors, revealing potential significant role of lncRNAs in tumorigenesis.We used the ICC dataset retrieved from The Cancer Genome Atlas and the Gene Expression Omnibus database to obtain the lncRNAs expression profiles and identify potential prognostic lncRNAs for predicting the prognosis in ICC. Univariate and multivariate Cox regression analyses were performed to construct a prognostic index (PI). Furthermore, coexpression analysis and functional assessment were performed to initially investigate the function of these prognostic lncRNAs.A total of 255 differentially expressed lncRNAs (DElncRNAs) were identified among two RNA sequencing dataset of a total 63 ICC patients with 98 samples using R platform. Thirteen of 255 DElncRNAs were identified as prognostic lncRNAs and used for a PI. Patients with high PI were associated with poor prognostic (P = .0064), and the Cox regression showed consistent result (P = .042). The time-dependent receiver operating characteristic analysis showed the PI performed well in ICC survival prediction with an area under curve of 0.921, 0.801, and 0.717 for 1-, 3-, and 5-year survival, respectively.In conclusion, we included 13 identified prognostic DElncRNAs and constructed a prognostic signature/PI. ICC patient with higher PI was associated with poorer prognosis. However, the clinical role as well as biological functions of constructed PI and these prognostic DElncRNAs need to be verified in future study.

The Contribution of Genetic Variants to the Risk of Papillary Thyroid Carcinoma in the Kazakh Population: Study of Common Single Nucleotide Polymorphisms and Their Clinicopathological Correlations

OBJECTIVE

Risk for developing papillary thyroid carcinoma (PTC), the most common endocrine malignancy, is thought to be mediated by lifestyle, environmental exposures and genetic factors. Recent progress in the genome-wide association studies of thyroid cancer leads to the identification of several genetic variants conferring risk to this malignancy across different ethnicities. We set out to elucidate the impact of selected single nucleotide polymorphisms (SNPs) on PTC risk and to evaluate clinicopathological correlations of these genetic variants in the Kazakh population for the first time.

METHODS

Eight SNPs were genotyped in 485 patients with PTC and 1,008 healthy control Kazakh subjects. The association analysis and multivariable modeling of PTC risk by the genetic factors, supplemented with rigorous statistical validation, were performed.

RESULT

Five of the eight SNPs: rs965513 (FOXE1/PTCSC2, P = 1.3E-16), rs1867277 (FOXE1 5'UTR, P = 7.5E-06), rs2439302 (NRG1 intron 1, P = 4.0E-05), rs944289 (PTCSC3/NKX2-1, P = 4.5E-06) and rs10136427 (BATF upstream, P = 9.8E-03) were significantly associated with PTC. rs966423 (DIRC3, P = 0.07) showed a suggestive association. rs7267944 (DHX35) was associated with PTC risk in males (P = 0.02), rs1867277 (FOXE1) conferred the higher risk in subjects older than 55 years (P = 7.0E-05), and rs6983267 (POU5F1B/CCAT2) was associated with pT3-T4 tumors (P = 0.01). The contribution of genetic component (unidirectional independent effects of rs965513, rs944289, rs2439302 and rs10136427 adjusted for age and sex) to PTC risk in the analyzed series was estimated to be 30-40%.

CONCLUSION

Genetic factors analyzed in the present work display significant association signals with PTC either on the whole group analysis or in particular clinicopathological groups and account for about one-third of the risk for PTC in the Kazakh population.

Association of genetic polymorphisms with laryngeal carcinoma prognosis in a Chinese population

We analyzed the effects of single-nucleotide polymorphisms (SNPs) on laryngeal carcinoma (LC) risk and overall survival (OS) in 170 Chinese male LC patients followed for 10 years. After assessment of clinical characteristics (age, laryngectomy, neck dissection, tumor differentiation, TNM status), the patients were genotyped for 24 SNPs associated with risk in multiple cancers. LC risk was assessed using log-rank test and Cox proportional hazard models. The median OS time was 48 months. By the follow-up deadline, OS was 41.2%. Kaplan-Meier analysis indicated 1-, 3-, and 5-year survival rates to be 84.7%, 57.2%, and 47.1%, respectively. Five LC clinicopathological characteristics, namely total laryngectomy (TL), low differentiation (LD), T3-T4, N1-N2, and clinical stage III-IV were associated with worse OS (HR: 2.35, p < 0.001; HR: 2.39, p = 0.02; HR: 2.17, p < 0.001; HR: 2.39, p < 0.001; and HR: 3.29, p < 0.001, respectively). Univariate cox regression analysis indicated that four SNPs were associated (p < 0.05) with LC OS in the codominant genetic model compared to patients with the homozygous wild-type genotype: rs10088262 G/A (HR = 1.57), rs1665650 A/G (HR = 0.65); rs3802842 C/C (HR = 2.18), and rs59336 T/A and T/T (HR = 0.61 and 2.61, respectively).