A key genomic signature associated with lymphovascular invasion in head and neck squamous cell carcinoma

Abstract

Background: Lymphovascular invasion (LOI), a key pathological feature of head and neck squamous cell carcinoma (HNSCC), is predictive of poor survival; however, the associated clinical characteristics and underlying molecular mechanisms remain largely unknown. Methods: We performed weighted gene co-expression network analysis to construct gene co-expression networks and investigate the relationship between key modules and the LOI clinical phenotype. Functional enrichment and KEGG pathway analyses were performed with differentially expressed genes. A protein–protein interaction network was constructed using Cytoscape, and module analysis was performed using MCODE. Prognostic value, expression analysis, and survival analysis were conducted using hub genes; GEPIA and the Human Protein Atlas database were used to determine the mRNA and protein expression levels of hub genes, respectively. Multivariable Cox regression analysis was used to establish a prognostic risk formula and the areas under the receiver operating characteristic curve (AUCs) were used to evaluate prediction efficiency. Finally, potential small molecular agents that could target LOI were identified with DrugBank. Results: Ten co-expression modules in two key modules (turquoise and pink) associated with LOI were identified. Functional enrichment and KEGG pathway analysis revealed that turquoise and pink modules played significant roles in HNSCC progression. Seven hub genes (CNFN, KIF18B, KIF23, PRC1, CCNA2, DEPDC1, and TTK) in the two modules were identified and validated by survival and expression analyses, and the following prognostic risk formula was established: [risk score = EXP DEPDC1 * 0.32636 + EXP CNFN * (−0.07544)]. The low-risk group showed better overall survival than the high-risk group ( P < 0.0001), and the AUCs for 1-, 3-, and 5-year overall survival were 0.582, 0.634, and 0.636, respectively. Eight small molecular agents, namely XL844, AT7519, AT9283, alvocidib, nelarabine, benzamidine, L-glutamine, and zinc, were identified as novel candidates for controlling LOI in HNSCC ( P < 0.05). Conclusions: The two-mRNA signature (CNFN and DEPDC1) could serve as an independent biomarker to predict LOI risk and provide new insights into the mechanisms underlying LOI in HNSCC. In addition, the small molecular agents appear promising for LOI treatment.

KIF23 is a potential biomarker of diffuse large B cell lymphoma

“…Previous researches indicated that KIF23 was involved in the initiation, development, and progression of tumors. Overexpression of KIF23 was detected in squamous cell carcinoma, [ 22 ] gastric cancer, [ 23 ] breast cancer, [ 24 ] and lung cancer. [ 25 ] In this study, integrating four gene expression datasets covering DLBCL patients and normal tissues, we identified that KIF23 expression showed a remarkable discrepancy between normal tissues and tumor tissues of DLBCL.…”

Silencing of KIF18B restricts proliferation and invasion and enhances the chemosensitivity of breast cancer via modulating Akt/GSK‐3β/β‐catenin pathway

“…KIF18B has been found to be differentially expressed in a number of cancers. Elevated levels of KIF18B have been detected in cervical cancer, 17 lung cancer, 31 renal cancer, 32 pancreatic cancer, 20 melanoma, 33 head and neck squamous cell carcinoma, 16 osteosarcoma, 18 and hepatocellular carcinoma 34 . In the present work, we also demonstrated high levels of KIF18B expression in breast cancer.…”

“…Microarray analysis reveals that KIF18B deregulation affects the expression of various central cell cycle regulatory genes that drive cancer progression 13 . Indeed, KIF18B overexpression has been found in a number of cancers and is associated with tumor progression as well as poor outcomes 14–16 . KIF18B aids cancer progression via effects on malignant biological behaviors of cancer cells 17–20 .…”

“…13 Indeed, KIF18B overexpression has been found in a number of cancers and is associated with tumor progression as well as poor outcomes. [14][15][16] KIF18B aids cancer progression via effects on malignant biological behaviors of cancer cells. [17][18][19][20] Therefore, KIF18B exerts a vital function in malignant transformation and may be a useful target for anti-cancer therapy development.…”

A TRP Family Based Signature for Prognosis Prediction in Head and Neck Squamous Cell Carcinoma

“…Moreover, similar results were found in the validation and entire cohorts, suggesting that TFBS has robust ability for prognosis prediction (Figures 2(g) and 2(h); Figures 2(k) and 2(l)). Also, we implemented ROC analyses to compare the prediction ability of TFBS with other established risk models [17,18], and our nominated TFBS had the highest AUC values (Figure 3), suggesting the robust ability of TFBS for prognosis prediction.…”