The mechanistic target of rapamycin (mTOR) coordinates eukaryotic cell growth and metabolism with environmental inputs, including nutrients and growth factors. Extensive research over the past two decades has established a central role for mTOR in regulating many fundamental cell processes, from protein synthesis to autophagy, and deregulated mTOR signaling is implicated in the progression of cancer and diabetes, as well as the aging process. Here, we review recent advances in our understanding of mTOR function, regulation, and importance in mammalian physiology. We also highlight how the mTOR signaling network contributes to human disease and discuss the current and future prospects for therapeutically targeting mTOR in the clinic.

mTOR Signaling in Growth, Metabolism, and Disease

Importance Biomarkers that reflect prognosis and cellular immunity in patients with head and neck squamous cell carcinoma (HNSCC) are a prerequisite for improving individualized treatment that limits the intensity and morbidity of conventional treatment and may be useful in the introduction of new immunotherapy regimens. Objective To determine if specific classes of tumor-infiltrating lymphocytes (TILs) in pretreatment biopsy specimens have prognostic value for outcomes in a large training and validation cohort of patients with HNSCC. Design, Setting, and Participants In this prospective, epidemiologic study with a median follow-up of 47.5 months, in 464 previously untreated patients with available tissue for construction of tissue microarray, HNSCC disease sites included oral cavity (228), oropharynx (147), larynx (74), and hypopharynx (15). The training cohort consisted of 241 patients and the validation cohort consisted of 223 patients. Overall tumor stage was I (55), II (69), III (71), or IV (269). Patients were enrolled between November 2008 to October 2014. Data were analyzed between October 2018 to April 2019. Main Outcomes and Measures Semiquantitative levels of CD4, CD8, and FoxP3 lymphocytes were assessed by immunohistologic analysis and correlations with clinical prognostic factors, initial treatment modality, and overall survival (OS) and disease-specific (DSS) survival were determined. A principal component analysis was performed to generate a combined TIL-weighted sum score (TILws). Results Of the 464 participants, 135 (29%) were women; mean (SD) age was 61.1 (11.8) years. Higher CD8 counts were associated with improved OS in both training and validation sets (HR, 0.94; 95% CI, 0.90-0.98; and HR, 0.97; 95% CI, 0.95-0.99, respectively). Higher TILwslevels were associated with improved OS and DSS in both the training set (HR, 0.91; 95% CI, 0.86-0.96; and HR, 0.93; 95% CI, 0.87-0.99, respectively) and validation set (HR, 0.96; 95% CI, 0.93-0.99; and HR, 0.94; 95% CI, 0.89-0.99, respectively). A multivariable Cox model controlling for batch, age, clinical stage, disease site, comorbidities, HPV status, and smoking, showed that higher TILwslevels were associated with improved OS and DSS (HR, 0.94; 95% CI, 0.92-0.97; and HR, 0.94; 95% CI, 0.90-0.98, respectively). When grouped by treatment (surgery vs chemoradiation) and tested for interaction, treatment was found to be an effect modifier for CD4 levels and OS. Low CD4 levels were showed greater association with decreased survival in the chemoradiation cohort than the surgery cohort. Conclusions and Relevance The findings from this large cohort study suggest that levels of TILs are an independent prognostic factor in patients with HNSCC. Subsets of TILs and combined TIL scores may be clinically useful predictive and prognostic factors.

/pdf/prognostic-value-of-tumor-infiltrating-lymphocytes-in-head-jq7gxewl5m.pdf

Prognostic Value of Tumor-Infiltrating Lymphocytes in Head and Neck Squamous Cell Carcinoma.

In the past few years, immunotherapy has changed the way we treat solid tumors. People pay more and more attention to the immune microenvironment of laryngeal squamous cell carcinoma (LSCC). In this study, our immunotherapy research took advantage of the clinical database and focused our in-depth analysis on the tumor microenvironment (TME). This study evaluated the relationship between the clinical outcome and the local tissue and overall immune status in 412 patients with primary LSCC. We constructed and validated a risk model that could predict prognosis, assess immune status, identify high-risk patients, and develop personalized treatment plans through bioinformatics. In addition, through immunohistochemical analysis, we verified the differential expression of CTSL and KDM5D genes with the largest weight coefficients in the model in LSCC tissues and their influence on the prognosis and tumor-infiltrating lymphocytes (TILs). We found that interstitial tumor-infiltrating lymphocytes, tumor parenchymal-infiltrating lymphocyte volume, tumor infiltrates lymphocytes of frontier invasion, and the platelet-to-lymphocyte ratio (PLR) were independent factors affecting the prognosis of patients with LSCC. A novel risk model can guide clinicians to accurately predict prognosis, identify high-risk patients, and formulate personalized treatment plans. The differential expression of genes such as CTSL and KDM5D has a significant correlation with the TILs of LSCC and the prognosis of patients. Local and systemic inflammatory markers in patients with laryngeal squamous cell carcinoma are reliable prognostic factors. The risk model and CTSL, KDM5D gene have important potential research value.

/pdf/assessment-of-immune-status-of-laryngeal-squamous-cell-1ci3zclerz.pdf

Assessment of immune status of laryngeal squamous cell carcinoma can predict prognosis and guide treatment

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease characterized by different molecular subgroups and clinical features. Therefore, it is important to uncover reliable molecular biomarkers for distinguishing different risk patient subgroup. Here, we conducted a multi-omics analysis to examine the joint predictive power of a multi-type RNA signature in the prognosis of HNSCC patients through integration analysis of mRNA, miRNA, and lncRNA expression profiles and clinical data in a large number of HNSCC patients. A multi-type RNA signature (15SigRS) was constructed which can classify patients into the high-risk group and low-risk group with the significantly different outcome [hazard ratio (HR) = 2.718, 95% confidence interval (CI), 2.258-3.272, p < 0.001] in the discovery data set, and subsequently validated in the Cancer Genome Atlas (TCGA) testing data set (HR = 1.299, 95% CI, 1.170-1.442, p < 0.001) and another independent GSE65858 data set (HR = 1.077, 95% CI, 1.016-1.143, p = 0.013). Further multivariate Cox regression analysis and stratification analysis demonstrated the independence of predictive performance of the 15SigRS relative to conventional clinicopathological factors. Furthermore, the 15SigRS has a prior performance in prognostic prediction than other single RNA type-based signatures. Functional analysis suggested that the 15SigRS are involved in immune- or metabolism-related KEGG pathways. In summary, our study demonstrated the potential application of mixed RNA types as molecular markers for predicting the outcome of cancer patients.

/pdf/identification-and-validation-of-an-immune-related-rna-2jdkv4cj93.pdf

Identification and Validation of an Immune-Related RNA Signature to Predict Survival of Patients With Head and Neck Squamous Cell Carcinoma.

Abstract Patients with locally advanced head and neck squamous cell carcinoma (HNSCC) may benefit from personalised treatment, requiring biomarkers that characterize the tumour and predict treatment response. We integrate pre-treatment CT radiomics and whole-transcriptome data from a multicentre retrospective cohort of 206 patients with locally advanced HNSCC treated with primary radiochemotherapy to classify tumour molecular subtypes based on radiomics, develop surrogate radiomics signatures for gene-based signatures related to different biological tumour characteristics and evaluate the potential of combining radiomics features with full-transcriptome data for the prediction of loco-regional control (LRC). Using end-to-end machine-learning, we developed and validated a model to classify tumours of the atypical subtype (AUC [95% confidence interval] 0.69 [0.53–0.83]) based on CT imaging, observed that CT-based radiomics models have limited value as surrogates for six selected gene signatures (AUC &lt; 0.60), and showed that combining a radiomics signature with a transcriptomics signature consisting of two metagenes representing the hedgehog pathway and E2F transcriptional targets improves the prognostic value for LRC compared to both individual sources (validation C-index [95% confidence interval], combined: 0.63 [0.55–0.73] vs radiomics: 0.60 [0.50–0.71] and transcriptomics: 0.59 [0.49–0.69]). These results underline the potential of multi-omics analyses to generate reliable biomarkers for future application in personalized oncology. 

https://www.nature.com/articles/s41598-022-21159-7.pdf

Integrated radiogenomics analyses allow for subtype classification and improved outcome prognosis of patients with locally advanced HNSCC

Background Head and neck squamous cell carcinoma (HNSCC) has a poor prognosis that has not significantly improved in the past several decades. A prognostic-related signature was needed. Methods The Cancer Genome Atlas and GSE41613 databases were downloaded as a training and validation set, respectively. We identified 12 genes that demonstrated progression and prognostic value, and then, a gene signature was constructed. Results This classification could reflect distinct characteristics, phenotypically and molecularly, among HNSCC tumors. It could stratify patients with significantly different survival rates (median survival: 2083 days vs 927 days; P = 3.85E-08) in the training cohort and validation cohort (P = 0.007) and was significantly involved in immune/inflammatory response and tumor progression processes. Conclusions This bioinformatics-based signature suggested the presence of two distinct populations of patients with HNSCC with distinguishable phenotypic characteristics and clinical outcomes and might provide insight for new types of immune therapy.

A gene signature associated with prognosis and immune processes in head and neck squamous cell carcinoma

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A gene signature associated with prognosis and immune processes in head and neck squamous cell carcinoma