Identification of core biomarkers associated with pathogenesis and prognostic outcomes of laryngeal squamous-cell cancer using bioinformatics analysis

KIF2C/MCAK a prognostic biomarker and its oncogenic potential in malignant progression, and prognosis of cancer patients: a systematic review and meta-analysis as biomarker

KIF2C/MCAK (KIF2C) is the most well-characterized member of the kinesin-13 family, which is critical in the regulation of microtubule (MT) dynamics during mitosis, as well as interphase. This systematic review briefly describes the important structural elements of KIF2C, its regulation by multiple molecular mechanisms, and its broad cellular functions. Furthermore, it systematically summarizes its oncogenic potential in malignant progression and performs a meta-analysis of its prognostic value in cancer patients. KIF2C was shown to be involved in multiple crucial cellular processes including cell migration and invasion, DNA repair, senescence induction and immune modulation, which are all known to be critical during the development of malignant tumors. Indeed, an increasing number of publications indicate that KIF2C is aberrantly expressed in multiple cancer entities. Consequently, we have highlighted its involvement in at least five hallmarks of cancer, namely: genome instability, resisting cell death, activating invasion and metastasis, avoiding immune destruction and cellular senescence. This was followed by a systematic search of KIF2C/MCAK's expression in various malignant tumor entities and its correlation with clinicopathologic features. Available data were pooled into multiple weighted meta-analyses for the correlation between KIF2Chigh protein or gene expression and the overall survival in breast cancer, non-small cell lung cancer and hepatocellular carcinoma patients. Furthermore, high expression of KIF2C was correlated to disease-free survival of hepatocellular carcinoma. All meta-analyses showed poor prognosis for cancer patients with KIF2Chigh expression, associated with a decreased overall survival and reduced disease-free survival, indicating KIF2C's oncogenic potential in malignant progression and as a prognostic marker. This work delineated the promising research perspective of KIF2C with modern in vivo and in vitro technologies to further decipher the function of KIF2C in malignant tumor development and progression. This might help to establish KIF2C as a biomarker for the diagnosis or evaluation of at least three cancer entities.

Immuno-oncologic signature of malignant transformation in oral squamous cell carcinoma

OBJECTIVE

The purpose of this study is to identify the immuno-oncologic (IO) signature at the surgical tumor margin (TM) of oral squamous cell carcinoma (OSCC) that is involved in the process of malignant transformation.

STUDY DESIGN

Under institutional review board approval, TM of 73 OSCC were investigated using immunohistochemistry for the immune biomarker, programmed death ligand-1 (PD-L1). NanoString 770 IO-focused gene set was analyzed in 5 pairs of TM and invasive tumor (T). PD-L1 regulation in response to interferon-gamma (IFN-γ) was investigated in an oral potentially malignant cell line (OPMC).

RESULTS

Programmed death ligand-1 expression in the epithelial margin directly correlated with its expression in the underlying immune cells (P = .0082). Differential gene expression showed downregulation of PD-L1 and IFN-γ 6 gene signature in the TM relative to T pair.CD8 and macrophages were higher in TM. CNTFR, LYZ, C7, RORC, and FGF13 downregulation in T relative to TM. TDO2, ADAM12, MMP1, LAMC2, MB21D1, TYMP, OASL, COL5A1, exhausted_CD8, Tregs,and NK_CD56dim were upregulated in T relative to TM. Finally, IFN-γ induced upregulation of PD-L1 in the OPMC.

CONCLUSIONS

Our work suggests a role for IFN-γ in PD-L1 upregulation in OPMC and presents novel IO transcriptional signatures for frankly invasive OSCC relative to TM.

Cell Cycle-Related Gene SPC24: A Novel Potential Diagnostic and Prognostic Biomarker for Laryngeal Squamous Cell Cancer

Laryngeal squamous cell cancer (LSCC) is a common malignant tumor with a high degree of malignancy, and its etiology remains unclear. Therefore, screening potential biomarkers is necessary to facilitate the treatment and diagnosis of LSCC. Robust rank aggregation (RRA) analysis was used to integrate two gene expression datasets of LSCC patients from the Gene Expression Omnibus (GEO) database and identify differentially expressed genes (DEGs) between LSCC and nonneoplastic tissues. A gene coexpression network was constructed using weighted gene correlation network analysis (WGCNA) to explore potential associations between the module genes and clinical features of LSCC. Combining differential gene expression analysis and survival analysis, we screened potential hub genes, including CDK1, SPC24, HOXB7, and SELENBP1. Subsequently, western blotting and immunohistochemistry were used to test the protein levels in clinical specimens to verify our findings. Finally, four candidate diagnostic and prognostic biomarkers (CDK1, SPC24, HOXB7, and SELENBP1) were identified. We propose, for the first time, that SPC24 is a gene that may associate with LSCC malignancy and is a novel therapeutic target. These findings may provide important mechanistic insight of LSCC.

Prognostic signature related to the immune environment of oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) prognosis remains poor. Here we aimed to identify an effective prognostic signature for predicting the survival of patients with OSCC. Gene-expression and clinical data were obtained from the Cancer Genome Atlas database. Immune microenvironment-associated genes were identified using bioinformatics. Subtype and risk-score analyses were performed for these genes. Kaplan–Meier analysis and immune cell infiltration level were explored in different subtypes and risk-score groups. The prognostic ability, independent prognosis, and clinical features of the risk score were assessed. Furthermore, immunotherapy response based on the risk score was explored. Finally, a conjoint analysis of the subtype and risk-score groups was performed to determine the best prognostic combination. We found 11 potential prognostic genes and constructed a risk-score model. The subtype cluster 2 and a high-risk group showed the worst overall survival; differences in survival status might be due to the different immune cell infiltration levels. The risk score showed good performance, independent prognostic value, and valuable clinical application. Higher risk scores showed higher Tumor Immune Dysfunction and Exclusion scores, indicating that patients with a high-risk score were less likely to benefit from immunotherapy. Finally, conjoint analysis for the subgroups and risk groups showed the best predictive ability.

A TCR mimic CAR T cell specific for NDC80 is broadly reactive with solid tumors and hematologic malignancies

Target identification for chimeric antigen receptor (CAR) T-cell therapies remains challenging due to the limited repertoire of tumor-specific surface proteins. Intracellular proteins presented in the context of cell surface HLA provide a wide pool of potential antigens targetable through T-cell receptor mimic antibodies. Mass spectrometry (MS) of HLA ligands from 8 hematologic and nonhematologic cancer cell lines identified a shared, non-immunogenic, HLA-A*02-restricted ligand (ALNEQIARL) derived from the kinetochore-associated NDC80 gene. CAR T cells directed against the ALNEQIARL:HLA-A*02 complex exhibited high sensitivity and specificity for recognition and killing of multiple cancer types, especially those of hematologic origin, and were efficacious in mouse models against a human leukemia and a solid tumor. In contrast, no toxicities toward resting or activated healthy leukocytes as well as hematopoietic stem cells were observed. This shows how MS can inform the design of broadly reactive therapeutic T-cell receptor mimic CAR T-cell therapies that can target multiple cancer types currently not druggable by small molecules, conventional CAR T cells, T cells, or antibodies.

Characterization of Recurrent Relevant Genes Reveals a Novel Role of RPL36A in Radioresistant Oral Squamous Cell Carcinoma

Simple Summary

Radioresistance is one of the major factors contributing to radiotherapy failure in OSCC. By systematically comparing the prognostic values of all genes in TCGA-OSCC patients with and without radiotherapy, radioresistance-associated genes were identified. Higher RPL36A transcript levels were found to be associated with a poor prognosis only in OSCC patients with radiotherapy in the cohort of TCGA and another independent Taiwanese cohort. RPL36A was then shown to be involved in the regulation of DNA damage, cell cycle and apoptosis, leading to radioresistance. Thus, such integrated studies are expected to be greatly beneficial for the development of new therapeutic interventions for radioresistant OSCC in the future.

Abstract

Radioresistance is one of the major factors that contributes to radiotherapy failure in oral cavity squamous cell carcinoma (OSCC). By comparing the prognostic values of 20,502 genes expressed in patients in The Cancer Genome Atlas (TCGA)-OSCC cohort with (n = 162) and without radiotherapy (n = 118), herein identified 297 genes positively correlated with poor disease-free survival in OSCC patients with radiotherapy as the potential radioresistance-associated genes. Among the potential radioresistance-associated genes, 36 genes were upregulated in cancerous tissues relative to normal tissues. The bioinformatics analysis revealed that 60S ribosomal protein L36a (RPL36A) was the most frequently detected gene involved in radioresistance-associated gene-mediated biological pathways. Then, two independent cohorts (n = 162 and n = 136) were assessed to confirm that higher RPL36A transcript levels were significantly associated with a poor prognosis only in OSCC patients with radiotherapy. Mechanistically, we found that knockdown of RPL36A increased radiosensitivity via sensitizing cells to DNA damage and promoted G2/M cell cycle arrest followed by augmenting the irradiation-induced apoptosis pathway in OSCC cells. Taken together, our study supports the use of large-scale genomic data for identifying specific radioresistance-associated genes and suggests a regulatory role for RPL36A in the development of radioresistance in OSCC.

Laryngeal Squamous Cell Carcinoma: Clinical Significance and Potential Mechanism of Cell Division Cycle 45

Background: Cell division cycle 45 (CDC45) plays an important role in the occurrence and development of numerous carcinomas, but its effect in laryngeal squamous cell carcinoma (LSCC) remains unclear. Materials and Methods: The messenger RNA and protein expression levels of CDC45 in LSCC were evaluated with a t test and the standard mean difference (SMD). The ability of CDC45 expression to distinguish the LSCC was assessed through receiver operating characteristic (ROC) curves. Gene set enrichment analysis (GSEA), protein-protein interaction, public databases, and online tools were used to explore the potential molecular mechanism of CDC45 in LSCC. Results: A high expression of CDC45 was identified in LSCC (SMD = 2.61, 95% confidence interval [1.62-3.61]). Through ROC curves, the expression of CDC45 makes it feasible to distinguish the LSCC group from the non-LSCC counterpart. CDC45 was relevant to the progression-free interval of LSCC patients (log-rank p = 0.03). GSEAs show that CDC45 is related to the cell cycle. CDC45, CDC6, KIF2C, and AURKB were identified as hub genes of LSCC. E2F1 may be the regulatory transcription factor of CDC45. Conclusions: High expression of CDC45 likely demonstrates carcinogenic effects in LSCC, and CDC45 is a potential target in screening and treatment of LSCC.

Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

Background

Triple-negative breast cancer (TNBC) is a highly heterogeneous subtype of breast cancer, showing aggressive clinical behaviors and poor outcomes. It urgently needs new therapeutic strategies to improve the prognosis of TNBC. Bioinformatics analyses have been widely used to identify potential biomarkers for facilitating TNBC diagnosis and management.

Methods

We identified potential biomarkers and analyzed their diagnostic and prognostic values using bioinformatics approaches. Including differential expression gene (DEG) analysis, Receiver Operating Characteristic (ROC) curve analysis, functional enrichment analysis, Protein-Protein Interaction (PPI) network construction, survival analysis, multivariate Cox regression analysis, and Non-negative Matrix Factorization (NMF).

Results

A total of 105 DEGs were identified between TNBC and other breast cancer subtypes, which were regarded as heterogeneous-related genes. Subsequently, the KEGG enrichment analysis showed that these genes were significantly enriched in ‘cell cycle’ and ‘oocyte meiosis’ related pathways. Four (FAM83B, KITLG, CFD and RBM24) of 105 genes were identified as prognostic signatures in the disease-free interval (DFI) of TNBC patients, as for progression-free interval (PFI), five genes (FAM83B, EXO1, S100B, TYMS and CFD) were obtained. Time-dependent ROC analysis indicated that the multivariate Cox regression models, which were constructed based on these genes, had great predictive performances. Finally, the survival analysis of TNBC subtypes (mesenchymal stem-like [MSL] and mesenchymal [MES]) suggested that FAM83B significantly affected the prognosis of patients.

Conclusions

The multivariate Cox regression models constructed from four heterogeneous-related genes (FAM83B, KITLG, RBM24 and S100B) showed great prediction performance for TNBC patients’ prognostic. Moreover, FAM83B was an important prognostic feature in several TNBC subtypes (MSL and MES). Our findings provided new biomarkers to facilitate the targeted therapies of TNBC and TNBC subtypes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08318-1.

Prognostic nomogram based on immune scores for laryngeal squamous cell cancer

PURPOSE

Immune scores have been used as a prognostic factor for various types of cancer. However, the association between immune scores and the prognosis of laryngeal squamous cell cancer (LSCC) has not yet been investigated. This study aimed to explore the prognostic significance of immune scores and construct a clinical nomogram to predict the survival of patients with LSCC.

METHODS

The clinicopathological characteristics and immune scores of 102 patients with LSCC were obtained from TCGA database and a nomogram was developed. C-index and calibration curves were applied to assess the performance of the model.

RESULTS

Patients with higher immune scores had significantly better overall survival (OS). The prognostic nomogram presented a good performance in survival prediction.

CONCLUSIONS

High immune scores are correlated with improved OS in patients with LSCC. In addition, the nomogram developed for this study may assist clinicians in the prognostic evaluation of patients with LSCC.