Development and Validation of an ADME-Related Gene Signature for Survival, Treatment Outcome and Immune Cell Infiltration in Head and Neck Squamous Cell Carcinoma

Exploring the frontiers: tumor immune microenvironment and immunotherapy in head and neck squamous cell carcinoma

The global prevalence of head and neck malignancies positions them as the sixth most common form of cancer, with the head and neck squamous cell carcinoma (HNSCC) representing the predominant histological subtype. Despite advancements in multidisciplinary approaches and molecular targeted therapies, the therapeutic outcomes for HNSCC have only marginally improved, particularly in cases of recurrent or metastatic HNSCC (R/MHNSCC). This situation underscores the critical necessity for the development of innovative therapeutic strategies. Such strategies are essential not only to enhance the efficacy of HNSCC treatment but also to minimize the incidence of associated complications, thus improving overall patient prognosis. Cancer immunotherapy represents a cutting-edge cancer treatment that leverages the immune system for targeting and destroying cancer cells. It's applied to multiple cancers, including melanoma and lung cancer, offering precision, adaptability, and the potential for long-lasting remission through immune memory. It is observed that while HNSCC patients responsive to immunotherapy often experience prolonged therapeutic benefits, only a limited subset demonstrates such responsiveness. Additionally, significant clinical challenges remain, including the development of resistance to immunotherapy. The biological characteristics, dynamic inhibitory changes, and heterogeneity of the tumor microenvironment (TME) in HNSCC play critical roles in its pathogenesis, immune evasion, and therapeutic resistance. This review aims to elucidate the functions and mechanisms of anti-tumor immune cells and extracellular components within the HNSCC TME. It also introduces several immunosuppressive agents commonly utilized in HNSCC immunotherapy, examines factors influencing the effectiveness of these treatments, and provides a comprehensive summary of immunotherapeutic strategies relevant to HNSCC.

Prognostic DNA mutation and mRNA expression analysis of perineural invasion in oral squamous cell carcinoma

This study analyzed oral squamous cell carcinoma (OSCC) genomes and transcriptomes in relation to perineural invasion (PNI) and prognosis using Cancer Genome Atlas data and validated these results with GSE41613 data. Gene set enrichment analysis (GSEA), gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes were conducted. We identified 22 DNA mutations associated with both overall survival (OS) and PNI. Among them, TGFBR1 and RPS6KA4 mRNAs were overexpressed, while TYRO3 and GPR137 mRNAs were underexpressed in PNI patients. Among the 141 mRNA genes associated with both OS and PNI, we found overlap with PNI-related DNA mutations, including ZNF43, TEX10, TPSD1, and PSD3. In GSE41613 data, TGFBR1, RPS6KA4, TYRO3, GPR137, TEX10 and TPSD1 mRNAs were expressed differently according to the prognosis. The 22 DNA-mutated genes clustered into nervous system development, regulation of DNA-templated transcription, and transforming growth factor beta binding. GSEA analysis of mRNAs revealed upregulation of hallmarks epithelial mesenchymal transition (EMT), TNFα signaling via NF-κB, and IL2 STAT5 signaling. EMT upregulation aligned with the TGFBR1 DNA mutation, supporting its significance in PNI. These findings suggest a potential role of PNI genes in the prognosis of OSCC, providing insights for diagnosis and treatment of OSCC.

Identification of an ADME-related gene for forecasting the prognosis and responding to immunotherapy in sarcomas

There are more than 170 subtypes of sarcomas (SARC), which pose a challenge for diagnosis and patient management. Relatively simple or complex karyotypes play an indispensable role in the early diagnosis and effective treatment of SARC. The genes related to absorption, distribution, metabolism, and excretion (ADME) of a drug can serve as prognostic biomarkers of cancer and potential drug targets. In this study, a risk score signature was created. The SARC cohort was downloaded from The Cancer Genome Atlas (TCGA) database, and divided into high-risk group and low-risk group according to the median value of risk score. Compared with high-risk group, low-risk group has a longer survival time, which is also verified in osteosarcoma cohort from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. In addition, the relationship between the signature and immunophenotypes, including status of immune cell infiltration and immune checkpoint expression, was explored. Then, we found that high-risk group is in immunosuppressive status. Finally, we verified that PPARD played a role as a carcinogen in osteosarcoma, which provided a direction for targeted treatment of osteosarcoma in the future. Generally speaking, the signature can not only help clinicians predict the prognosis of patients with SARC, but also provide a theoretical basis for developing more effective targeted drugs in the future.

A novel m7G regulator-based methylation patterns in head and neck squamous cell carcinoma

Abnormal RNA N7-methylguanosine (m7G) modification is known to contribute to effects on tumor occurrence and development. Nevertheless, the mechanisms of its function in immunoregulation, tumor microenvironment (TME) modulation, and tumor promotion remain largely unknown. A series of computer-aided bioinformatic analyses were conducted based on transcriptomic, single-cell sequence, and spatial transcriptomic data to determine the m7G modification patterns in head and neck squamous cell carcinoma (HNSCC). Consensus clustering approach was employed according to the expressions of 33 m7G regulators. ESTIMATE, CIBERSORT, and single sample gene set enrichment analysis algorithms were adopted to investigate the immune cell infiltration features. A prognostic model named m7Gscore was established. Seurat, SingleR, and Monocle2 were used to analyze the single-cell sequence profiling. STUtility was used to integrate multiple spatial transcriptomic datasets. Quantitative reverse transcription polymerase chain reaction, transwell, and wound-healing assay were performed to verify the oncogenes. Here, three different m7G modification patterns were highlighted in HNSCC patients, which were also related to various clinical manifestations and three representative immunophenotypes: immune-excluded, immune-desert, and inflamed, separately. Patients with lower m7Gscore were highlighted by higher immune cell infiltrations, better overall survival rates, lesser tumor mutation burden (TMB), lower sensitivities to target inhibitors therapies, and better immunotherapeutic response. Moreover, DCPS, EIF4E, EIF4E2, LSM1, NCBP2, NUDT1, and NUDT5 were identified to play critical roles in T-cell differentiation. Knockdown of LSM1/NUDT5 could restrain the malignancy of HNSCC cells. Collectively, quantitative assessment of m7G modification patterns in individual HNSCC patients could contribute to identifying more efficient immunotherapeutic approaches and improve the clinical outcome of HNSCC.

Exploration of the radiosensitivity-related prognostic risk signature in patients with glioma: evidence from microarray data

BACKGROUND

Gene expression signatures can be used as prognostic biomarkers in various types of cancers. We aim to develop a gene signature for predicting the response to radiotherapy in glioma patients.

METHODS

Radio-sensitive and radio-resistant glioma cell lines (M059J and M059K) were subjected to microarray analysis to screen for differentially expressed mRNAs. Additionally, we obtained 169 glioblastomas (GBM) samples and 5 normal samples from The Cancer Genome Atlas (TCGA) database, as well as 80 GBM samples and 4 normal samples from the GSE7696 set. The "DESeq2" R package was employed to identify differentially expressed genes (DEGs) between the normal brain samples and GBM samples. Combining the prognostic-related molecules identified from the TCGA, we developed a radiosensitivity-related prognostic risk signature (RRPRS) in the training set, which includes 152 patients with glioblastoma. Subsequently, we validated the reliability of the RRPRS in a validation set containing 616 patients with glioma from the TCGA database, as well as an internal validation set consisting of 31 glioblastoma patients from the Nanfang Hospital, Southern Medical University.

RESULTS

Based on the microarray and LASSO COX regression analysis, we developed a nine-gene radiosensitivity-related prognostic risk signature. Patients with glioma were divided into high- or low-risk groups based on the median risk score. The Kaplan-Meier survival analysis showed that the progression-free survival (PFS) of the high-risk group was significantly shorter. The signature accurately predicted PFS as assessed by time-dependent receiver operating characteristic curve (ROC) analyses. Stratified analysis demonstrated that the signature is specific to predict the outcome of patients who were treated using radiotherapy. Univariate and multivariate Cox regression analysis revealed that the predictor was an independent predictor for the prognosis of patients with glioma. The prognostic nomograms accompanied by calibration curves displayed the 1-, 2-, and 3-year PFS and OS in patients with glioma.

CONCLUSION

Our study established a new nine-gene radiosensitivity-related prognostic risk signature that can predict the prognosis of patients with glioma who received radiotherapy. The nomogram showed great potential to predict the prognosis of patients with glioma treated using radiotherapy.