A Genomic-Clinicopathologic Nomogram Predicts Survival for Patients with Laryngeal Squamous Cell Carcinoma

Identification and validation of a novel risk model based on cuproptosis‑associated m6A for head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is a prevalent cancer with a poor survival rate due to anatomical limitations of the head and a lack of reliable biomarkers. Cuproptosis represents a novel cellular regulated death pathway, and N6-methyladenosine (m6A) is the most common internal RNA modification in mRNA. They are intricately connected to tumor formation, progression, and prognosis. This study aimed to construct a risk model for HNSCC using a set of mRNAs associated with m6A regulators and cuproptosis genes (mcrmRNA).

METHODS

RNA-seq and clinical data of HNSCC patients from The Cancer Genome Atlas (TCGA) database were analyzed to develop a risk model through the least absolute shrinkage and selection operator (LASSO) analysis. Survival analysis and receiver operating characteristic (ROC) analysis were performed for the high- and low-risk groups. Additionally, the model was validated using the GSE41613 dataset from the Gene Expression Omnibus (GEO) database. GSEA and CIBERSORT were applied to investigate the immune microenvironment of HNSCC.

RESULTS

A risk model consisting of 32 mcrmRNA was developed using the LASSO analysis. The risk score of patients was confirmed to be an independent prognostic indicator by multivariate Cox analysis. The high-risk group exhibited a higher tumor mutation burden. Additionally, CIBERSORT analysis indicated varying levels of immune cell infiltration between the two groups. Significant disparities in drug sensitivity to common medications were also observed. Enrichment analysis further unveiled significant differences in metabolic pathways and RNA processing between the two groups.

CONCLUSIONS

Our risk model can predict outcomes for HNSCC patients and offers valuable insights for personalized therapeutic approaches.

Identification and prognostic analysis of ferroptosis‑related gene HSPA5 to predict the progression of lung squamous cell carcinoma

Ferroptosis, an iron-dependent form of regulated cell death driven by excessive lipid peroxidation, is implicated in the development and therapeutic responses of cancer. However, the role of ferroptosis-related gene profiles in lung squamous cell carcinoma (LSCC) remains largely unknown. The present study aimed to identify the prognostic roles of ferroptosis-related genes in LSCC. Sequencing data from the Cancer Genome Atlas were analyzed and ferroptosis-related gene expression between tumor and para-tumor tissue was identified. The prognostic role of these genes was also assessed using Kaplan-Meier analyses and univariate and multivariate Cox proportional hazards regression model analyses. Immunological correlation, tumor stemness, drug sensitivity and the transcriptional differences of heat shock protein (HSP)A5 in LSCC were also analyzed. Thereafter, the expression of HSPA5 in 100 patients with metastatic LSCC was evaluated using immunohistochemistry (IHC) and the clinical significance of these markers with different risk factors was assessed. Of the 22 ferroptosis-related genes, the expression of HSPA5, HSPB1, glutathione peroxidase 4, Fanconi anemia complementation group D2, CDGSH iron sulfur domain 1, farnesyl-diphosphate farnesyltransferase 1, nuclear factor erythroid 2 like 2, solute carrier (SLC)1A5, ribosomal protein L8, nuclear receptor coactivator 4, transferrin receptor and SLC7A11 was significantly increased in LSCC compared with adjacent tissues. However, only high expression of HSPA5 was able to predict progression-free survival (PFS) and disease-free survival in LSCC. Although HSPA5 was also significantly elevated in patients with lung adenocarcinoma, HSPA5 expression did not predict the prognosis of patients with lung adenocarcinoma. Of note, a higher expression of HSPA5 was related to higher responses to chemotherapy but not to immunotherapy. In addition, HSPA5 expression was positively correlated with 'ferroptosis', 'cellular responses to hypoxia', 'tumor proliferation signature', 'G2M checkpoint', 'MYC targets' and 'TGFB'. IHC analysis also demonstrated that a high expression of HSPA5 in patients with metastatic LSCC in the study cohort was associated with shorter PFS and overall survival. In conclusion, the present study demonstrated that the expression of the ferroptosis-related gene HSPA5 may be a negative prognostic marker for LSCC.

Transcriptional subtypes of glottic cancer characterized by differential activation of canonical oncogenic programming

BACKGROUND

There is a paucity of data concerning molecular heterogeneity among glottic squamous cell carcinoma, and the clinical implications thereof.

METHODS

Data corresponding to glottic squamous cell carcinoma were derived from The Cancer Genome Atlas. The Onco-GPS computational methodology was levied to derive four patterns of transcriptional activity and three functional subtypes of glottic cancer.

RESULTS

Thirty glottic cancer samples stratified to three distinct oncogenic states (S0-S2) based on a Onco-GPS model containing four transcriptional components (F0-F3). Membership in S2 and association with transcriptional component F0 conveyed an invasive phenotype, with transcriptional activity strongly reflecting EMT programming (including TGF-B and NF-KB signaling). S2 membership also correlated with inferior disease-specific survival (HR 9.027, 95% CI 1.021-79.767), and higher incidences of extracapsular spread and perineural invasion.

CONCLUSIONS

We present a functional taxonomy of glottic cancer, with subtypes demonstrating differential upregulation of canonical oncogenic networks and survival implications.

Single-cell mapping of N6-methyladenosine in esophageal squamous cell carcinoma and exploration of the risk model for immune infiltration

BACKGROUND

N6-methyladenosine (m6A) modification is the most common RNA modification, but its potential role in the development of esophageal cancer and its specific mechanisms still need to be further investigated.

METHODS

Bulk RNA-seq of 174 patients with esophageal squamous carcinoma from the TCGA-ESCC cohort, GSE53625, and single-cell sequencing data from patients with esophageal squamous carcinoma from GSE188900 were included in this study. Single-cell analysis of scRNA-seq data from GSE188900 of 4 esophageal squamous carcinoma samples and calculation of PROGENy scores. Demonstrate the scoring of tumor-associated pathways for different cell populations. Cell Chat was calculated for cell populations. thereafter, m6A-related differential genes were sought and risk models were constructed to analyze the relevant biological functions and impact pathways of potential m6A genes and their impact on immune infiltration and tumor treatment sensitivity in ESCC was investigated.

RESULTS

By umap downscaling analysis, ESCC single-cell data were labelled into clusters of seven immune cell classes. Cellchat analysis showed that the network interactions of four signaling pathways, MIF, AFF, FN1 and CD99, all showed different cell type interactions. The prognostic risk model constructed by screening for m6A-related differential genes was of significant value in the prognostic stratification of ESCC patients and had a significant impact on immune infiltration and chemotherapy sensitivity in ESCC patients.

CONCLUSION

In our study, we explored a blueprint for the distribution of single cells in ESCC based on m6A methylation and constructed a risk model for immune infiltration analysis and tumor efficacy stratification in ESCC on this basis. This may provide important potential guidance for revealing the role of m6A in immune escape and treatment resistance in esophageal cancer.

The Mechanism of Nemo-Like Kinase (NLK) in Non-Small Cell Lung Cancer (NSCLC) Cells by Regulating Vascular Endothelial Growth Factor (VEGF)

Nemo-like kinase (NLK) is abnormally expressed in several tumors, but its role in NSCLC have not been reported. Real time PCR and Western blot were used to assess NLK level in tumor tissues and adjacent tissues of NSCLC. NSCLC cell line A549 cells were divided into three groups; NC group and si-NLK group which was transfected with NLK negative control or NLK siRNA respectively followed by analysis of NLK expression by real time PCR and Western blot, cell proliferation by MTT assay, cell migration by cell wound healing assay, cell invasion by transwell chamber and MMP-9 and VEGF expression by Western blot. The expression of NLK in NSCLC tumor tissue was increased, and the difference was statistically significant compared with adjacent tissues (P <0.05), and it was related to tumor size, degree of differentiation, metastasis and survival time (P <0.05). A549 cells showed significantly increased NLK. Transfection of NLK siRNA could significantly inhibit tumor cell proliferation, migration and invasion, and decrease the expression of MMP-9 and VEGF proteins (P <0.05). Elevated NLK level in NSCLC tumor tissues is related to clinicopathological characteristics. Decreased the expression of NLK can inhibit VEGF and MMP-9 expression, and inhibit cell function.

[Development and validation of nomogram for predicting prognosis of patients with laryngeal squamous cell carcinoma after surgery]

Objective:To explore the relationship between preoperative blood indexes, clinicopathological characteristics and prognosis of patients with laryngeal squamous cell carcinoma（LSCC）, and to establish a nomogram for predicting survival and recurrence time of LSCC patients. Methods:The clinical data of 530 patients with LSCC who received primary surgical treatment were analyzed retrospectively. The patients were randomly divided into training group and testing group according to the ratio of 7∶3. The nomograms of overall survival（OS） and recurrence-free survival（RFS） were constructed based on Cox regression model, and the nomograms were verified and compared with TNM stage. Results:The results of multivariate analysis showed that age, operation mode, tumor diameter, TNM stage, cervical lymph node metastasis, fibrinogen level and systemic immune inflammation index were significantly correlated with OS, while operation mode, tumor diameter, TNM stage, cervical lymph node metastasis, international normalized ratio, neutrophil to lymphocyte ratio and platelet to lymphocyte ratio were significantly correlated with RFS. The nomograms were constructed based on the above factors. The C-indexes of the nomograms of OS and RFS in the training group were 0.755 and 0.687, respectively, which were higher than those of TNM stage（0.657 and 0.582）. In the testing group, the C-indexes of OS and RFS nomograms were 0.717 and 0.646, respectively, which were higher than those of TNM stage（0.599 and 0.528）. The area under the receiver operating characteristic curves of these nomograms were also higher than TNM stage. The calibration curves showed that the models had good consistency. Decision curve analysis（DCA） showed that these nomograms had higher clinical benefit than TNM stage. Conclusion:Based on the independent prognostic factors, the predictive nomograms of OS and RFS at 1, 3 and 5 years after LSCC were constructed, which have certain clinical significance in guiding the individualized diagnosis and treatment of LSCC.

Radiomics of dual-energy computed tomography for predicting progression-free survival in patients with early glottic cancer

Aim: This study aimed to predict progression-free survival (PFS) in patients with early glottic cancer using radiomic features on dual-energy computed tomography iodine maps. Methods: Radiomic features were extracted from arterial and venous phase iodine maps, and radiomic risk scores were determined by univariate Cox proportional hazards regression analysis and least absolute shrinkage and selection operator regression with tenfold cross-validation. The Kaplan-Meier method was used to evaluate the association between radiomic risk scores and PFS. Results: Patients were stratified into low-risk and high-risk groups using radiomics, the PFS corresponding rates with statistical significance between the two groups. The high-risk group showed better survival, benefiting from laryngectomy. Conclusion: Radiomics could provide a promising biomarker for predicting the PFS of early glottic cancer patients.

Dual-energy CT may predict post-operative recurrence in early-stage glottic laryngeal cancer: a novel nomogram and risk stratification system

OBJECTIVES

To establish and validate a predictive model integrating with clinical and dual-energy CT (DECT) variables for individual recurrence-free survival (RFS) prediction in early-stage glottic laryngeal cancer (EGLC) after larynx-preserving surgery.

METHODS

This retrospective study included 212 consecutive patients with EGLC who underwent DECT before larynx-preserving surgery between January 2015 and December 2018. Using Cox proportional hazard regression model to determine independent predictors for RFS and presented on a nomogram. The model's performance was assessed using Harrell's concordance index (C-index), time-dependent area under curve (TD-AUC) plot, and calibration curve. A risk stratification system was established using the nomogram with median scores of all cases to divide all patients into two prognostic groups.

RESULTS

Recurrence occurred in 39/212 (18.4%) cases. Normalized iodine concentration in arterial (NICAP) and venous phases (NICVP) were verified as significant predictors of RFS in multivariate Cox regression (hazard ratio [HR], 4.2; 95% confidence interval [CI]: 2.3, 7.7, p < .001 and HR, 3.0; 95% CI: 1.5, 5.9, p = .002, respectively). Nomogram based on clinical and DECT variables was better than did only clinical variables. The prediction model proved well-calibrated and had good discriminative ability in the training and validation samples. A risk stratification system was built that could effectively classify EGLC patients into two risk groups.

CONCLUSIONS

DECT could provide independent RFS indicators in patients with EGLC, and the nomogram based on DECT and clinical variables was useful in predicting RFS at several time points.

KEY POINTS

• Dual-energy CT(DECT) variables can predict recurrence-free survival (RFS) after larynx-preserving surgery in patients with early-stage glottic laryngeal cancer (EGLC). • The model that integrates clinical and DECT variables predicted RFS better than did only clinical variables. • A risk stratification system based on the nomogram could effectively classify EGLC patients into two risk groups.

Construction of a ceRNA network and a genomic-clinicopathologic nomogram to predict survival for HBV-related HCC

Some lncRNA-associated competing endogenous RNAs (ceRNAs) are considered as potential biomarkers for targeted therapies and prognosis in human cancer. In our present study, we aimed to construct a ceRNA network and establish a genomic-clinicopathologic nomogram to provide insights into the molecular mechanisms and predict survival for HBV-related HCC. The Cancer Genome Atlas (TCGA) database was applied to collect the data of LIHC RNA-seq dataset and miRNA-seq dataset as well as the clinicopathological information. Identification of differentially expressed RNAs (mRNAs, lncRNAs, and miRNAs) between HBV-related HCC samples and normal samples was conducted using Limma package in R. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for performing the functional enrichment analysis of differentially expressed mRNAs. The ceRNA network was carried out using Cytoscape. The LASSO-penalized Cox regression analysis was implemented to identify HCC-related lncRNAs, and the multivariate Cox regression analysis was conducted for the establishment of a genomic-clinicopathology nomogram. A total of 1859 DEmRNAs, 113 DElncRNAs, and 89 DEmiRNAs were screened out etween HBV-related HCC samples and normal samples. A ceRNA network including 44 DEmRNAs, 7 DElncRNAs, and 20 DEmiRNAs was constructed. 7 DElncRNAs (PVT1, LINC01138, LINC02499, AL355488.2, FGF14-AS2, MAFG-AS1 and LINC00261) were finally identified as prognostic indicators. The area under the curve reached 0.8169 for the 7-lncRNA signature. The predictive accuracy and clinical application value were remarkably high for the genomic-clinicopathologic nomogram integrating the histological grade and the 7-gene-based prognostic index. Taken together, we have established a ceRNA network with HBV-related HCC-specific DElncRNAs, DEmiRNAs, and DEmRNAs. Furthermore, the genome-wide data of lncRNA expression were analyzed using the TCGA database, and a 7-lncRNA signature was identified as a potential prognostic predictor for HBV-related HCC patients. Novel functional studies were provided by our current findings for elucidating the molecular mechanism of lncRNA in HBV-related HCC.

The LncRNA FGD5-AS1/miR-497-5p axis regulates septin 2 (SEPT2) to accelerate cancer progression and increase cisplatin-resistance in laryngeal squamous cell carcinoma

Aberrant expression or mutation of the Septin gene family is closely associated with cancer progression, and septin 2 (SEPT2) exerts its tumor-promoting effects in multiple cancers, but its role in regulating laryngeal squamous cell carcinoma (LSCC) progression and drug resistance has not been investigated. Based on the published data, the present study identified that SEPT2 promoted cancer progression and increased cisplatin-resistance in LSCC, and a novel LncRNA FGD5-AS1/miR-497-5p axis was crucial for this process. Mechanistically, SEPT2 tended to be enriched in LSCC tissues and cells, and knock-down of SEPT2 inhibited cell proliferation, viability, migration, and tumorigenesis in LSCC cells in vitro and in vivo. Aside from that, SEPT2 overexpression increased cisplatin resistance in LSCC cells. Next, by conducting the dual-luciferase reporter gene system assay, we identified that the LncRNA FGD5-AS1/miR-497-5p axis regulated SEPT2 in LSCC. Specifically, LncRNA FGD5-AS1 sponged miR-497-5p to upregulate SEPT2 in LSCC cells in a competing endogenous RNA (ceRNA) mechanisms-dependent manner. Interestingly, upregulated LncRNA FGD5-AS1 and downregulated miR-497-5p were observed in LSCC tissues and cells, and LncRNA FGD5-AS1 ablation inhibited cancer progression. Also, LncRNA FGD5-AS1 overexpression increased cisplatin-resistance in LSCC by modulating the miR-497-5p/SEPT2 axis. Collectively, we conclude that targeting the LncRNA FGD5-AS1/miR-497-5p/SEPT2 signaling cascade may be an alternative strategy to treat LSCC in the clinic.

Transcriptome Analyses Implicate Endogenous Retroviruses Involved in the Host Antiviral Immune System through the Interferon Pathway

Human endogenous retroviruses (HERVs) are the remains of ancient retroviruses that invaded our ancestors' germline cell and were integrated into the genome. The expression of HERVs has always been a cause for concern because of its association with various cancers and diseases. However, few previous studies have focused on specific activation of HERVs by viral infections. Our previous study has shown that dengue virus type 2 (DENV-2) infection induces the transcription of a large number of abnormal HERVs loci; therefore, the purpose of this study was to explore the relationship between exogenous viral infection and HERV activation further. In this study, we retrieved and reanalyzed published data on 21 transcriptomes of human cells infected with various viruses. We found that infection with different viruses could induce transcriptional activation of HERV loci. Through the comparative analysis of all viral datasets, we identified 43 key HERV loci that were up-regulated by DENV-2, influenza A virus, influenza B virus, Zika virus, measles virus, and West Nile virus infections. Furthermore, the neighboring genes of these HERVs were simultaneously up-regulated, and almost all such neighboring genes were interferon-stimulated genes (ISGs), which are enriched in the host's antiviral immune response pathways. Our data supported the hypothesis that activation of HERVs, probably via an interferon-mediated mechanism, plays an important role in innate immunity against viral infections.

A dynamic prognostic nomogram to predict the benefit from surgical treatment modality for patients with laryngeal squamous cell carcinoma

BACKGROUND

Although nonsurgical treatment strategy is increasingly adopted in patients with locoregionally advanced laryngeal squamous cell carcinoma (LSCC), survival disparities were reported between surgical treatment modality and organ preservation protocols, highlighting the great importance for accurate patients' selection.

METHOD

This secondary analysis used data from the Surveillance, Epidemiology, and End Results database between 2010 and 2015 with follow-up data up to 2018. We developed and validated a dynamic prognostic nomogram for overall survival (OS) in 4237 patients with LSCC and subgroup of 2087 patients with locoregionally advanced laryngeal squamous cell carcinoma (LALSCC). Based on the total risk score derived from the dynamic nomogram, two well-matched risk groups (i.e., low- and high-risk) were created via X-tile software and 1-to-1 propensity score matching (PSM); surgical treatment modality was compared with nonsurgical one in each risk group.

RESULTS

A more accurate and convenient dynamic prognostic nomogram based on age, marital status, T category, N category, M category, tumor size, and tumor differentiation was developed and validated, of which the predictive performance was superior to that of TNM staging system. For high-risk LALSCC selected by the dynamic nomogram, after 1-to-1 PSM, significantly improved OS was observed in patients with receiving surgical treatment compared to those receipt of nonsurgical management (restricted mean survival time at 36-month: 26.6 vs 22.7, p < 0.001; restricted mean survival time at 60-month: 36.7 vs 31.0, p = 0.003).

CONCLUSION

We establish and validate a more accurate and convenient dynamic prognostic nomogram for patients with LSCC, which may predict the benefit from surgical treatment modality for patients with high-risk LALSCC.

Identification and validation of methylation-driven genes prognostic signature for recurrence of laryngeal squamous cell carcinoma by integrated bioinformatics analysis

Background

Recurrence remains a major obstacle to long-term survival of laryngeal squamous cell carcinoma (LSCC). We conducted a genome-wide integrated analysis of methylation and the transcriptome to establish methylation-driven genes prognostic signature (MDGPS) to precisely predict recurrence probability and optimize therapeutic strategies for LSCC.

Methods

LSCC DNA methylation datasets and RNA sequencing (RNA-seq) dataset were acquired from the Cancer Genome Atlas (TCGA). MethylMix was applied to detect DNA methylation-driven genes (MDGs). By univariate and multivariate Cox regression analyses, five genes of DNA MDGs was developed a recurrence-free survival (RFS)-related MDGPS. The predictive accuracy and clinical value of the MDGPS were evaluated by receiver operating characteristic (ROC) and decision curve analysis (DCA), and compared with TNM stage system. Additionally, prognostic value of MDGPS was validated by external Gene Expression Omnibus (GEO) database. According to 5 MDGs, the candidate small molecules for LSCC were screen out by the CMap database. To strengthen the bioinformatics analysis results, 30 pairs of clinical samples were evaluated by digoxigenin-labeled chromogenic in situ hybridization (CISH).

Results

A total of 88 DNA MDGs were identified, and five RFS-related MDGs (LINC01354, CCDC8, PHYHD1, MAGEB2 and ZNF732) were chosen to construct a MDGPS. The MDGPS can effectively divide patients into high-risk and low-risk group, with the area under curve (AUC) of 0.738 (5-year RFS) and AUC of 0.74 (3-year RFS). Stratification analysis affirmed that the MDGPS was still a significant statistical prognostic model in subsets of patients with different clinical variables. Multivariate Cox regression analysis indicated the efficacy of MDGPS appears independent of other clinicopathological characteristics. In terms of predictive capacity and clinical usefulness, the MDGPS was superior to traditional TNM stage. Additionally, the MDGPS was confirmed in external LSCC cohorts from GEO. CMap matched the 9 most significant small molecules as promising therapeutic drugs to reverse the LSCC gene expression. Finally, CISH analysis in 30 LSCC tissues and paired adjacent normal tissues revealed that MAGEB2 has significantly higher expression of LSCC compared to adjacent non-neoplastic tissues; LINC01354, CCDC8, PHYHD1, and ZNF732 have significantly lower expression of LSCC compared to adjacent non-neoplastic tissues, which were in line with bioinformatics analysis results.

Conclusion

A MDGPS, with five DNA MDGs, was identified and validated in LSCC patients by combining transcriptome and methylation datasets analysis. Compared TNM stage alone, it generates more accurate estimations of the recurrence prediction and maybe offer novel research directions and prospects for individualized treatment of patients with LSCC.

lncRNAs classifier to accurately predict the recurrence of thymic epithelial tumors

Background

Long non‐coding RNAs (lncRNAs), which have little or no ability to encode proteins, have attracted special attention due to their potential role in cancer disease. In this study we aimed to establish a lncRNAs classifier to improve the accuracy of recurrence prediction for thymic epithelial tumors (TETs).

Methods

TETs RNA sequencing (RNA‐seq) data set and the matched clinicopathologic information were downloaded from the Cancer Genome Atlas. Using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analysis, we developed a lncRNAs classifier related to recurrence. Functional analysis was conducted to investigate the potential biological processes of the lncRNAs target genes. The independent prognostic factors were identified by Cox regression model. Additionally, predictive ability and clinical application of the lncRNAs classifier were assessed, and compared with the Masaoka staging by receiver operating characteristic (ROC) analysis and decision curve analysis (DCA).

Results

Four recurrence‐free survival (RFS)‐related lncRNAs were identified, and the classifier consisting of the identified four lncRNAs was able to effectively divide the patients into high and low risk subgroups, with an area under curve (AUC) of 0.796 (three‐year RFS) and 0.788 (five‐year RFS), respectively. Multivariate analysis indicated that the lncRNAs classifier was an independent recurrence risk factor. The AUC of the lncRNAs classifier in predicting RFS was significantly higher than the Masaoka staging system. Decision curve analysis further demonstrated that the lncRNAs classifier had a larger net benefit than the Masaoka staging system.

Conclusions

A lncRNAs classifier for patients with TETs was an independent risk factor for RFS despite other clinicopathologic variables. It generated more accurate estimations of the recurrence probability when compared to the Masaoka staging system, but additional data is required before it can be used in clinical practice.