Prospective assessment of the clinical benefit of a tailored cancer gene set built on a next-generation sequencing platform in patients with recurrent or metastatic head and neck cancer

Transoral Robotic Surgery for Residual and Recurrent Oropharyngeal Cancers

Transoral robotic surgery (TORS) is a well-established treatment option for treatment-naïve oropharyngeal cancer. For residual, recurrent, and new primary oropharyngeal tumors emerging in previously irradiated fields, the global experience of management with TORS is limited. This article discusses current concepts on this topic, offers a deeper insight into the transoral anatomy for these cases, and covers the specific complexities of resections in the various subsites of the oropharynx. It provides practical tips on reconstruction, recovery, and rehabilitation as well as offering a synthesis of the current evidence and exploring future trends.

Construction of a prognostic immune signature for lower grade glioma that can be recognized by MRI radiomics features to predict survival in LGG patients

BACKGROUND

This study aimed to identify a series of prognostically relevant immune features by immunophenoscore. Immune features were explored using MRI radiomics features to prediction the overall survival (OS) of lower-grade glioma (LGG) patients and their response to immune checkpoints.

METHOD

LGG data were retrieved from TCGA and categorized into training and internal validation datasets. Patients attending the First Affiliated Hospital of Harbin Medical University were included in an external validation cohort. An immunophenoscore-based signature was built to predict malignant potential and response to immune checkpoint inhibitors in LGG patients. In addition, a deep learning neural network prediction model was built for validation of the immunophenoscore-based signature.

RESULTS

Immunophenotype-associated mRNA signatures (IMriskScore) for outcome prediction and ICB therapeutic effects in LGG patients were constructed. Deep learning of neural networks based on radiomics showed that MRI radiomic features determined IMriskScore. Enrichment analysis and ssGSEA correlation analysis were performed. Mutations in CIC significantly improved the prognosis of patients in the high IMriskScore group. Therefore, CIC is a potential therapeutic target for patients in the high IMriskScore group. Moreover, IMriskScore is an independent risk factor that can be used clinically to predict LGG patient outcomes.

CONCLUSIONS

The IMriskScore model consisting of a sets of biomarkers, can independently predict the prognosis of LGG patients and provides a basis for the development of personalized immunotherapy strategies. In addition, IMriskScore features were predicted by MRI radiomics using a deep learning approach using neural networks. Therefore, they can be used for the prognosis of LGG patients.

Worldwide prevalence of PI3K-AKT-mTOR pathway mutations in head and neck cancer: A systematic review and meta-analysis

A systematic review (SR) and meta-analysis were conducted to determine the prevalence of PI3K-AKT-mTOR signaling pathway mutations in patients with head and neck cancer (HNC). Overall, 105 studies comprising 8630 patients and 1306 mutations were selected. The estimated mutations prevalence was 13 % for PIK3CA (95 % confidence interval [CI] = 11-14; I² = 82 %; p < 0.0001), 4% for PTEN (95 % CI = 3-5; I² = 55 %; p < 0.0001), 3% for MTOR (95 % CI = 2-4; I² = 5%; p = 0.40), and 2% for AKT (95 % CI = 1-2; I² = 50 %; p = 0.0001). We further stratified the available data of the participants according to risk factors and tumor characteristics, including HPV infection, tobacco use, alcohol exposure, TNM stage, and histological tumor differentiation, and performed subgroup analysis. We identified significant associations between PI3K-AKT-mTOR pathway-associated mutations and advanced TNM stage (odds ratio [OR] = 0.20; 95 % CI = 0.09-0.44; I² = 71 %; p = 0.0001) and oropharyngeal HPV-positive tumors and PIK3CA mutations (OR = 17.48; 95 % CI = 4.20-72.76; I² = 69 %; p < 0.0002). No associations were found between alcohol and tobacco exposure, and tumor differentiation grade. This SR demonstrated that the PI3K-AKT-mTOR pathway emerges as a potential prognostic factor and could offer a molecular basis for future studies on therapeutic targeting in HNC patients.

A signature of 17 immune-related gene pairs predicts prognosis and immune status in HNSCC patients

Head and neck squamous cell carcinoma (HNSCC) is an invasive malignancy with high worldwide mortality. Growing evidence has indicated a pivotal correlation between HNSCC prognosis and immune signature. This study investigated an immune-related gene pairs (IRGPs) signature to predict the prognostic value of HNSCC patients. We constructed IRGPs via integrating multiple IRG expression data sets. Moreover, we established the predictive model base on the IRGPs for HNSCC, and utilized multidimensional bioinformatics methods to validate the robustness of prognostic value of the IRGPs signature. In addition, we explored the relationship between the IRGPs model and immune status. Seventeen IRGPs signature was built as the predictive model which predicted prognosis independently and reliably for HNSCC. Compared to the high-risk group, the low-risk group demonstrated a distinctly favorable prognosis including overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS). The low-risk group showed higher-immune score and lower-tumor purity than the high-risk group. In addition, the low-risk group exhibited higher expression of Programmed cell death 1 ligand 1 (PD-L1) and Microsatellite instability (MSI) score, and lower expression of Tumor Immune Dysfunction and Exclusion (TIDE), which indicated the low-risk group was much more sensitive to immunotherapy. Lastly, the IRGs signature has achieved a higher accuracy than clinical properties for estimation of survival. The IRGPs model is an independent biomarker for estimating the prognosis, and could be also used to predict immunotherapeutic response in HNSCC patients. These findings may provide new ideas for novel biomarkers and may be helpful to formulate personalized immunotherapy strategy.

Identification of Therapeutic and Prognostic Biomarkers of Lamin C (LAMC) Family Members in Head and Neck Squamous Cell Carcinoma

Background

Head and neck squamous cell carcinoma (HNSC) is an invasive malignancy with a high worldwide mortality, despite considerable recent advancements in diagnosis and treatment. Increasing evidence indicates that the Lamin C (LAMC) gene family is associated with the progression of diverse cancers, nevertheless, this association is not well understood.

Material/Methods

A systematic study addressing the expression and prognostic value of LAMC, and the relationship between LAMC and tumor immune response in HNSC was done. Finally, we performed drug screening to identify specific drugs.

Results

Compared to normal samples, expressions of LAMC1 and LAMC2 were significantly increased in HNSC, and LAMC2 was obviously correlated with an adverse prognosis for patients. LAMC2 expression level was significantly correlated with the infiltrating levels of B cells, CD8+ T cells, CD4+ T cells, and macrophages. Moreover, LAMC2 exhibited strong correlations with diverse immune markers, immune microenvironment, and immune checkpoint molecules. Finally, candidate drugs that targeted LAMC2 were identified.

Conclusions

This study suggests that LAMC2 could serve as a new prognostic biomarker, and it could be used for efficacy of target for immune response and for drug sensitivity prediction in HNSC.