scholarly journals Single-cell transcriptomic analysis reveals the critical molecular pattern of UV-induced cutaneous squamous cell carcinoma

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Guorong Yan ◽  
Liang Li ◽  
Sibo Zhu ◽  
Yuhao Wu ◽  
Yeqiang Liu ◽  
...  

AbstractCutaneous squamous cell carcinoma (cSCC) is the second most common nonmelanoma skin cancer characterized by high invasiveness, heterogeneity, and mainly occurs in the ultraviolet (UV)-exposed regions of the skin, but its pathogenesis is still unclear. Here, we generated single-cell transcriptome profiles for 350 cells from six primary UV-induced cSCCs, together with matched adjacent skin samples, and three healthy control skin tissues by single-cell RNA-sequencing technology based on Smart-seq2 strategy. A series of bioinformatics analyses and in vitro experiments were used to decipher and validate the critical molecular pattern of cSCC. Results showed that cSCC cells and normal keratinocytes were significantly distinct in gene expression and chromosomal copy number variation. Furthermore, cSCC cells exhibited 18 hallmark pathways of cancer by gene set enrichment analysis. Differential expression analysis demonstrated that many members belonging to S100 gene family, SPRR gene family, and FABP5 were significantly upregulated in cSCC cells. Further experiments confirmed their upregulation and showed that S100A9 or FABP5 knockdown in cSCC cells inhibited their proliferation and migration through NF-κB pathway. Taken together, our data provide a valuable resource for deciphering the molecular pattern in UV-induced cSCC at a single-cell level and suggest that S100A9 and FABP5 may provide novel targets for therapeutic intervention of cSCC in the future.

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhimin Shen ◽  
Mingduan Chen ◽  
Fei Luo ◽  
Hui Xu ◽  
Peipei Zhang ◽  
...  

Esophageal squamous cell carcinoma (ESCC) ranks as the fourth leading cause of cancer-related death in China. Although paclitaxel has been shown to be effective in treating ESCC, the prolonged use of this chemical will lead to paclitaxel resistance. In order to uncover genes and pathways driving paclitaxel resistance in the progression of ESCC, bioinformatics analyses were performed based on The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database including GSE86099 and GSE161533. Differential expression analysis was performed in TCGA data and two GEO datasets to obtain differentially expressed genes (DEGs). Based on GSE161533, weighted gene co-expression network analysis (WGCNA) was conducted to identify the key modules associated with ESCC tumor status. The DEGs common to the two GEO datasets and the genes in the key modules were intersected to obtain the paclitaxel resistance-specific or non-paclitaxel resistance-specific genes, which were subjected to subsequent least absolute shrinkage and selection operator (LASSO) feature selection, whereby paclitaxel resistance-specific or non-paclitaxel resistance-specific key genes were selected. Ten machine learning models were used to validate the biological significance of these key genes; the potential therapeutic drugs for paclitaxel resistance-specific genes were also predicted. As a result, we identified 24 paclitaxel resistance-specific genes and 18 non-paclitaxel resistance-specific genes. The ESCC machine classifiers based on the key genes achieved a relatively high AUC value in the cross-validation and in an independent test set, GSE164158. A total of 207 drugs (such as bevacizumab) were predicted to be alternative therapeutics for ESCC patients with paclitaxel resistance. These results might shed light on the in-depth research of paclitaxel resistance in the context of ESCC progression.


Author(s):  
Yixiu Yu ◽  
Jiamei Niu ◽  
Xingwei Zhang ◽  
Xue Wang ◽  
Hongquan Song ◽  
...  

ORAL squamous cell carcinoma (OSCC) is a malignant tumor with the highest incidence among tumors involving the oral cavity maxillofacial region, and is notorious for its high recurrence and metastasis potential. Long non-coding RNAs (lncRNAs), which regulate the genesis and evolution of cancers, are potential prognostic biomarkers. This study identified HOTAIRM1 as a novel significantly upregulated lncRNA in OSCC, which is strongly associated with unfavorable prognosis of OSCC. Systematic bioinformatics analyses demonstrated that HOTAIRM1 was closely related to tumor stage, overall survival, genome instability, the tumor cell stemness, the tumor microenvironment, and immunocyte infiltration. Using biological function prediction methods, including Weighted gene co-expression network analysis (WGCNA), Gene set enrichment analysis (GSEA), and Gene set variation analysis (GSVA), HOTAIRM1 plays a pivotal role in OSCC cell proliferation, and is mainly involved in the regulation of the cell cycle. In vitro, cell loss-functional experiments confirmed that HOTAIRM1 knockdown significantly inhibited the proliferation of OSCC cells, and arrested the cell cycle in G1 phase. At the molecular level, PCNA and CyclinD1 were obviously reduced after HOTAIRM1 knockdown. The expression of p53 and p21 was upregulated while CDK4 and CDK6 expression was decreased by HOTAIRM1 knockdown. In vivo, knocking down HOTAIRM1 significantly inhibited tumor growth, including the tumor size, weight, volume, angiogenesis, and hardness, monitored by ultrasonic imaging and magnetic resonance imaging In summary, our study reports that HOTAIRM1 is closely associated with tumorigenesis of OSCC and promotes cell proliferation by regulating cell cycle. HOTAIRM1 could be a potential prognostic biomarker and a therapeutic target for OSCC.


2018 ◽  
Vol 80 (4) ◽  
pp. 331-335
Author(s):  
Reika FUKUCHI ◽  
Sayaka KUWATSUKA ◽  
Yukie SATO ◽  
Yutaka KUWATSUKA ◽  
Atsushi UTANI

2019 ◽  
Vol 3 ◽  
pp. S50
Author(s):  
Michael R Migden ◽  
Todd E Schlesinger ◽  
Chrysalyne D Schmults ◽  
Scott M Dinehart ◽  
Robert L Ferris ◽  
...  

Abstract not available.


Sign in / Sign up

Export Citation Format

Share Document