Prediction of radiotherapy response with a 5-microRNA signature-based nomogram in head and neck squamous cell carcinoma

Development and validation of a nomogram model of depression and sleep disorders and the risk of disease progression in patients with breast cancer

BACKGROUND

In this study, we investigated the relationship between the risk of postoperative progressive disease (PD) in breast cancer and depression and sleep disorders in order to develop and validate a suitable risk prevention model.

METHODS

A total of 750 postoperative patients with breast cancer were selected from the First People's Hospital of LianYunGang, and the indices of two groups (an event group and a non-event group) were compared to develop and validate a risk prediction model. The relationship between depression, sleep disorders, and PD events was investigated using the follow-up data of the 750 patients.

RESULTS

SAS, SDS, and AIS scores differed in the group of patients who experienced postoperative disease progression versus those who did not; the differences were statistically significant and the ability to differentiate prognosis was high. The area under the receiver operating characteristic (ROC) curves (AUC) were: 0.8049 (0.7685-0.8613), 0.768 (0.727-0.809), and 0.7661 (0.724--0.808), with cut-off values of 43.5, 48.5, and 4.5, respectively. Significant variables were screened by single-factor analysis and multi-factor analysis to create model 1, by lasso regression and cross-lasso regression analysis to create model 2, by random forest calculation method to create model 3, by stepwise regression method (backward method) to create model 4, and by including all variables for Cox regression to include significant variables to create model 5. The AUC of model 2 was 0.883 (0.848-0.918) and 0.937 (0.893-0.981) in the training set and validation set, respectively. The clinical efficacy of the model was evaluated using decision curve analysis and clinical impact curve, and then the model 2 variables were transformed into scores, which were validated in two datasets, the training and validation sets, with AUCs of 0.884 (0.848-0.919) and 0.885 (0.818-0.951), respectively.

CONCLUSION

We established and verified a model including SAS, SDS and AIS to predict the prognosis of breast cancer patients, and simplified it by scoring, making it convenient for clinical use, providing a theoretical basis for precise intervention in these patients. However, further research is needed to verify the generalization ability of our model.

Clinical Biomarkers of Tumour Radiosensitivity and Predicting Benefit from Radiotherapy: A Systematic Review

Modern advanced radiotherapy techniques have improved the precision and accuracy of radiotherapy delivery, with resulting plans being highly personalised based on individual anatomy. Adaptation for individual tumour biology remains elusive. There is an unmet need for biomarkers of intrinsic radiosensitivity that can predict tumour response to radiation to facilitate individualised decision-making, dosing and treatment planning. Over the last few decades, the use of high throughput molecular biology technologies has led to an explosion of newly discovered cancer biomarkers. Gene expression signatures are now used routinely in clinic to aid decision-making regarding adjuvant systemic therapy. They have great potential as radiotherapy biomarkers. A previous systematic review published in 2015 reported only five studies of signatures evaluated for their ability to predict radiotherapy benefits in clinical cohorts. This updated systematic review encompasses the expanded number of studies reported in the last decade. An additional 27 studies were identified. In total, 22 distinct signatures were recognised (5 pre-2015, 17 post-2015). Seventeen signatures were 'radiosensitivity' signatures and five were breast cancer prognostic signatures aiming to identify patients at an increased risk of local recurrence and therefore were more likely to benefit from adjuvant radiation. Most signatures (15/22) had not progressed beyond the discovery phase of development, with no suitable validated clinical-grade assay for application. Very few signatures (4/17 'radiosensitivity' signatures) had undergone any laboratory-based biological validation of their ability to predict tumour radiosensitivity. No signatures have been assessed prospectively in a phase III biomarker-led trial to date and none are recommended for routine use in clinical guidelines. A phase III prospective evaluation is ongoing for two breast cancer prognostic signatures. The most promising radiosensitivity signature remains the radiosensitivity index (RSI), which is used to calculate a genomic adjusted radiation dose (GARD). There is an ongoing phase II prospective biomarker-led study of RSI/GARD in triple negative breast cancer. The results of these trials are eagerly anticipated over the coming years. Future work in this area should focus on (1) robust biological validation; (2) building biobanks alongside large radiotherapy randomised controlled trials with dose variance (to demonstrate an interaction between radiosensitivity signature and dose); (3) a validation of clinical-grade cost-effective assays that are deliverable within current healthcare infrastructure; and (4) an integration with biomarkers of other determinants of radiation response.

RNA-Based Liquid Biopsy in Head and Neck Cancer

Head and neck cancer (HNC) is a prevalent and diverse group of malignancies with substantial morbidity and mortality rates. Early detection and monitoring of HNC are crucial for improving patient outcomes. Liquid biopsy, a non-invasive diagnostic approach, has emerged as a promising tool for cancer detection and monitoring. In this article, we review the application of RNA-based liquid biopsy in HNC. Various types of RNA, including messenger RNA (mRNA), microRNA (miRNA), long non-coding RNA (lncRNA), small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), circular RNA (circRNA) and PIWI-interacting RNA (piRNA), are explored as potential biomarkers in HNC liquid-based diagnostics. The roles of RNAs in HNC diagnosis, metastasis, tumor resistance to radio and chemotherapy, and overall prognosis are discussed. RNA-based liquid biopsy holds great promise for the early detection, prognosis, and personalized treatment of HNC. Further research and validation are necessary to translate these findings into clinical practice and improve patient outcomes.

Expression and molecular regulation of non-coding RNAs in HPV-positive head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is the sixth most prevalent malignancy worldwide. Accumulating evidence suggests that persistent HPV infection is closely related to a subset of HNSCC types, and the incidence of human papillomavirus (HPV)-positive HNSCC has been annually increasing in recent decades. Although the carcinogenesis of HPV-positive HNSCC has not been completely elucidated, it has been well confirmed that E6 and E7, the main viral oncoproteins are responsible for the maintenance of malignant transformation, promotion of cell proliferation, and increase in tumor invasion. Moreover, compared with HPV-negative HNSCC, HPV-positive HNSCC shows some special clinical-pathological features, which are possibly related to HPV infection and their specific regulatory mechanisms. Non-coding RNA (ncRNA) is a class of RNA lacking the protein-coding function and playing a critical regulatory role via multiple complex molecular mechanisms. NcRNA is an important regulatory pattern of epigenetic modification, which can exert significant effects on HPV-induced tumorigenesis and progression by deregulating downstream genes. However, the knowledge of ncRNAs is still limited, hence, a better understanding of ncRNAs could provide some insights for exploring the carcinogenesis mechanism and identifying valuable biomarkers in HPV-positive HNSCC. Therefore, in this review, we mainly focused on the expression profile of ncRNAs (including lncRNA, miRNA, and circRNA) and explored their regulatory role in HPV-positive HNSCC, aiming to clarify the regulatory mechanism of ncRNAs and identify valuable biomarkers for HPV-positive HNSCC.

Constructing and Verifying an Alexithymia Risk-Prediction Model for Older Adults with Chronic Diseases Living in Nursing Homes: A Cross-Sectional Study in China

Alexithymia is a critical global public health concern. This questionnaire-based cross-sectional study explored the risk factors of alexithymia in older adults living in nursing homes with chronic diseases. It also developed and evaluated an alexithymia risk-prediction model. A total of 203 older adults with chronic diseases were selected from seven nursing homes in Changsha, China, using simple random and cluster sampling. The participants were surveyed using the Toronto Alexithymia Scale (TAS-20), Geriatric Depression Scale-15 (GDS-15), Connor-Davidson Resilience Scale (CD-RISC), Perceived Social Support Scale (PSSS), and a socio-demographic characteristics questionnaire. The alexithymia total score was 43.85 ± 9.570, with an incidence rate of 8.9%. Alexithymia had a partial mediating effect on the relationship between social support and psychological resilience (the effect value was 0.12), accounting for 19.04% of the total effect. Gender, depression, and psychological resilience were the main independent influencing factors of alexithymia (p < 0.05). The area under the receiver operating characteristic (AUC-ROC) curve of the risk-prediction model was 0.770. The participants, especially those who were male and depressed, exhibited a certain degree of alexithymia. Additionally, it partially mediated the association between social support and psychological resilience, which is a protective factor against alexithymia. The risk-prediction model showed good accuracy and discrimination. Hence, it can be used for preliminary screening of alexithymia in older adults with chronic diseases living in nursing homes.

Development and validation of novel nomograms to predict survival of patients with tongue squamous cell carcinoma

BACKGROUND

There is no unified standard to predict postoperative survival in patients with tongue squamous cell carcinoma (TSCC), hence the urgency to develop a model to accurately predict the prognosis of these patients.

AIM

To develop and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) of patients with TSCC.

METHODS

A cohort of 3454 patients with TSCC from the Surveillance, Epidemiology, and End Results (SEER) database was used to develop nomograms; another independent cohort of 203 patients with TSCC from the Department of Oral and Maxillofacial Surgery, First Affiliated Hospital of Zhejiang University School of Medicine, was used for external validation. Univariate and multivariate analyses were performed to identify useful variables for the development of nomograms. The calibration curve, area under the receiver operating characteristic curve (AUC) analysis, concordance index (C-index), net reclassification index (NRI), and decision curve analysis (DCA) were used to assess the calibration, discrimination ability, and clinical utility of the nomograms.

RESULTS

Eight variables were selected and used to develop nomograms for patients with TSCC. The C-index (0.741 and 0.757 for OS and CSS in the training cohort and 0.800 and 0.830 in the validation cohort, respectively) and AUC indicated that the discrimination abilities of these nomograms were acceptable. The calibration curves of OS and CSS indicated that the predicted and actual values were consistent in both the training and validation cohorts. The NRI values (training cohort: 0.493 and 0.482 for 3- and 5-year OS and 0.424 and 0.402 for 3- and 5-year CSS; validation cohort: 0.635 and 0.750 for 3- and 5-year OS and 0.354 and 0.608 for 3- and 5-year CSS, respectively) and DCA results indicated that the nomograms were significantly better than the tumor-node-metastasis staging system in predicting the prognosis of patients with TSCC.

CONCLUSION

Our nomograms can accurately predict patient prognoses and assist clinicians in improving decision-making concerning patients with TSCC in clinical practice.

Nomogram reliability for predicting potential risk in postgraduate medical students with anxiety symptoms

Purpose

This research aims to develop a Nomogram for exact anxiety symptoms prediction in postgraduate medical students so that they may be identified as high-risk individuals early and get focused care.

Methods

Using a convenient sampling method, for case-control matching, 126 participants with anxiety symptoms and 774 participants of the same age and gender but without anxiety symptoms were designated as the case group and control group, respectively. Multivariable logistic regression analysis was utilized to identify influencing factors for anxiety symptoms, then used to design and verify a Nomogram of anxiety symptoms.

Results

Multivariate logistic regression analysis showed that lack of social support (OR = 0.95, 95%CI: 0.91-0.99), low life satisfaction (OR = 0.91, 95%CI: 0.86-0.95), low subjective well-being (OR = 0.58, 95%CI: 0.41-0.83) and frequent tobacco and alcohol use (OR = 1.75, 95%CI: 1.10-2.80) were independent predictors of anxiety symptoms in postgraduate medical students (P < 0.05). The Nomogram risk prediction model based on the above four independent prediction factors was established, and the verified C-index (Concordance index) is 0.787 (95%CI: 0.744-0.803, P < 0.001).

Conclusions

Anxiety symptoms in postgraduate medical students are influenced by various variables. The Nomogram prediction model has high accuracy, validity, and reliability, which can provide reference for predicting anxiety symptoms in postgraduate medical students.

Promising Biomarkers in Head and Neck Cancer: The Most Clinically Important miRNAs

Head and neck cancers (HNCs) comprise a heterogeneous group of tumors that extend from the oral cavity to the upper gastrointestinal tract. The principal etiologic factors for oral tumors include tobacco smoking and alcohol consumption, while human papillomavirus (HPV) infections have been accused of a high incidence of pharyngeal tumors. Accordingly, HPV detection has been extensively used to categorize carcinomas of the head and neck. The diverse nature of HNC highlights the necessity for novel, sensitive, and precise biomarkers for the prompt diagnosis of the disease, its successful monitoring, and the timely prognosis of patient clinical outcomes. In this context, the identification of certain microRNAs (miRNAs) and/or the detection of alterations in their expression patterns, in a variety of somatic fluids and tissues, could serve as valuable biomarkers for precision oncology. In the present review, we summarize some of the most frequently studied miRNAs (including miR-21, -375, -99, -34a, -200, -31, -125a/b, -196a/b, -9, -181a, -155, -146a, -23a, -16, -29, and let-7), their role as biomarkers, and their implication in HNC pathogenesis. Moreover, we designate the potential of given miRNAs and miRNA signatures as novel diagnostic and prognostic tools for successful patient stratification. Finally, we discuss the currently ongoing clinical trials that aim to identify the diagnostic, prognostic, or therapeutic utility of miRNAs in HNC.

The Prognostic Role of miR-31 in Head and Neck Squamous Cell Carcinoma: Systematic Review and Meta-Analysis with Trial Sequential Analysis

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide with high recurrence, metastasis, and poor treatment outcome. Prognostic survival biomarkers can be a valid tool for assessing a patient's life expectancy and directing therapy toward specific targets. Recent studies have reported microRNA (miR) might play a critical role in regulating different types of cancer. The main miR used as a diagnostic and prognostic biomarker and reported in the scientific literature for HNSCC is miR-21. Other miRs have been investigated to a lesser extent (miR-99a, miR-99b, miR-100, miR-143, miR-155, miR-7, miR-424, miR-183), but among these, the one that has attracted major interest is the miR-31.

METHODS

The systematic review was conducted following the PRISMA guidelines using electronic databases, such as PubMed, Scopus, and the Cochrane Central Register of Controlled Trials, with the use of combinations of keywords, such as miR-31 AND HNSCC, microRNA AND HNSCC, and miR-31. The meta-analysis was performed using the RevMan 5.41 software (Cochrane Collaboration, Copenhagen, Denmark).

RESULTS

This search produced 721 records, which, after the elimination of duplicates and the application of the inclusion and exclusion criteria, led to 4 articles. The meta-analysis was conducted by applying fixed-effects models, given the low rate of heterogeneity (I² = 40%). The results of the meta-analysis report an aggregate hazard ratio (HR) for the overall survival (OS), between the highest and lowest miR-31 expression, of 1.59, with the relative intervals of confidence (1.22 2.07). Heterogeneity was evaluated through Chi² = 5.04 df = 3 (p = 0.17) and the Higgins index I² = 40; testing for the overall effect was Z = 3.44 (p = 0.00006). The forest plot shows us a worsening HR value of OS, in relation to the elevated expression of miR-31.

CONCLUSIONS

In conclusion, the data resulting from the current meta-analysis suggest that miR-31 is associated with the prognosis of patients with HNSCC and that elevated miR-31 expression could predict a poor prognosis in patients with this type of neoplasm.

Transcriptome analysis reveals the prognostic and immune infiltration characteristics of glycolysis and hypoxia in head and neck squamous cell carcinoma

BACKGROUND

This study aims to construct a new prognostic gene signature in survival prediction and risk stratification for patients with Head and neck squamous cell carcinoma (HNSCC).

METHOD

The transcriptome profiling data and hallmark gene sets in the Molecular Signatures Database was used to explore the cancer hallmarks most relevant to the prognosis of HNSCC patients. Differential gene expression analysis, weighted gene co-expression network analysis, univariate COX regression analysis, random forest algorithm and multiple combinatorial screening were used to construct the prognostic gene signature. The predictive ability of gene signature was verified in the TCGA HNSCC cohort as the training set and the GEO HNSCC cohorts (GSE41613 and GSE42743) as the validation sets, respectively. Moreover, the correlations between risk scores and immune infiltration patterns, as well as risk scores and genomic changes were explored.

RESULTS

A total of 3391 differentially expressed genes in HNSCC were screened. Glycolysis and hypoxia were screened as the main risk factors for OS in HNSCC. Using univariate Cox analysis, 97 prognostic candidates were identified (P < 0.05). Top 10 important genes were then screened out by random forest. Using multiple combinatorial screening, a combination with less genes and more significant P value was used to construct the prognostic gene signature (RNF144A, STC1, P4HA1, FMNL3, ANO1, BASP1, MME, PLEKHG2 and DKK1). Kaplan-Meier analysis showed that patients with higher risk scores had worse overall survival (p < 0.001). The ROC curve showed that the risk score had a good predictive efficiency (AUC > 0.66). Subsequently, the predictive ability of the risk score was verified in the validation sets. Moreover, the two-factor survival analysis combining the cancer hallmarks and risk scores suggested that HNSCC patients with the high hypoxia or glycolysis & high risk-score showed the worst prognosis. Besides, a nomogram based on the nine-gene signature was established for clinical practice. Furthermore, the risk score was significantly related to tumor immune infiltration profiles and genome changes.

CONCLUSION

This nine-gene signature associated with glycolysis and hypoxia can not only be used for prognosis prediction and risk stratification, but also may be a potential therapeutic target for patients with HNSCC.

Dose-dependent expression of extracellular microRNAs in HCT116 colorectal cancer cells exposed to high-dose-rate ionising radiation

Biomarkers of tumour response to radiotherapy may help optimise cancer treatment. The aim of the present study was to identify changes in extracellular microRNAs (miRNAs) as a biomarker of radiation-induced damage to human colorectal cancer cells. HCT116 cells were exposed to increasing doses of X-rays, and extracellular miRNAs were analysed by microarray. The results were correlated with the frequency of micronuclei. A total of 59 miRNAs with a positive correlation and 4 with a negative correlation between dose (up to 6 Gy) and extracellular miRNA expression were identified. In addition, for doses between 0 and 10 Gy, 12 miRNAs among those 59 miRNAs with a positive correlation were identified; for these extracellular miRNAs, a significantly positive correlation was observed between their expression and the frequency of micronuclei for doses up to 10 Gy. These results suggest that specific miRNAs may be considered as cell damage markers and may serve as secreted radiotherapy response biomarkers for colorectal cancer; however, the results must be further validated in serum samples collected from patients undergoing radiotherapy.

The dynamic interactome of microRNAs and the human papillomavirus in head and neck cancers

The Human Papillomavirus type 16 is a major etiologic factor for a subset of Head and Neck cancers. These cancers of the oropharyngeal region are growing, and it is expected to exceed cervical cancers in the near future. The major oncogenes E6 and E7 mediate many of the early transformation stages targeting p53 and other tumour suppressor genes. The majority of this regulation is centred on protein coding genes but more recently small non-coding RNAs, such as miRNAs are also regulated by HPV16. However, the system-wide impact of HPV16 on miRNAs is yet to be fully understood. To fully gauge the overall relationship between HPV16 and miRNAs, several studies have devised dynamic interactomes which encompass viral oncogenes, miRNAs and gene targets. These interactomes map potential pathways which permit the identification of possible mechanistic links. Our review will discuss the latest developments in using viral interactomes to understand viral mechanisms and how these approaches may aid in the elucidation of potential druggable pathways.

Multiple microRNA signature panel as promising potential for diagnosis and prognosis of head and neck cancer

MicroRNAs are small non-coding RNA that regulate gene expressions of human body. To date, numerous studies have reported that microRNAs possess great diagnostic and prognostic power in head and neck cancer and had governed a lot of attention. The factor for the successfulness of miRNAs in these aspects is due to cancer being fundamentally tied to genetic changes, which are regulated by these miRNAs. Head and neck cancer, leading the world record for cancer as number sixth, is caused by multiple risk factors such as tobacco consumption, alcohol consumption, dietary factors, ethnicity, family history, and human papilloma virus. It derives at locations such as oral cavity, pharynx, larynx, paranasal sinus and salivary gland and have high rate of mortality with high recurrence rate. Besides, head and neck cancer is also usually having poor prognosis due to its asymptomatic nature. However, this diagnostic and prognostic power can be further improved by using multiple panels of miRNA as a signature or even combined with TNM staging system to obtain even more remarkable results. This is due to multiple factors such as tumour heterogeneity and components of the tumour which may affect the composition of miRNAs. This review covers the examples of such miRNA signatures, compare their diagnostic and prognostic powers, discuss some controversial roles of unreported miRNAs, and the molecular mechanisms of the miRNAs in gene targeting and pathways.

FOXC2/ADAM12-dependent radiosensitivity of head and neck squamous cell carcinoma cells

BACKGROUND

Radiotherapy greatly benefits patients with tumors, but not all patients show favorable treatment response. This study investigated the impact of forkhead box protein C2 (FOXC2)-mediated a disintegrin and metalloprotease 12 (ADAM12) on the radiosensitivity of head and neck squamous cell carcinoma (HNSCC).

METHODS

After transfection and ionizing radiation, the biological activities of HNSCC cells were assessed. The relationship between ADAM12 and FOXC2 was verified. A xenograft model was used to evaluate the effect of FOXC2 knockdown on HNSCC growth in the context of radiation therapy.

RESULTS

FOXC2 and ADAM12 were upregulated in irradiated CAL-27 and HN4 cells. Knockdown of FOXC2 suppressed the malignant behaviors of CAL-27 and HN4 cells and inhibited the growth of transplanted tumors in nude mice. FOXC2 could bind ADAM12 promoter. Overexpression of ADAM12 reversed the promotion of FOXC2 silencing on the radiosensitivity of HNSCC cells.

CONCLUSIONS

FOXC2 regulates the radiosensitivity of HNSCC by targeting ADAM12.

Predictive potential of STEAP family for survival, immune microenvironment and therapy response in glioma

Glioma is the most commonly diagnosed primary tumor of central nervous system. Previous studies found that the six-transmembrane epithelial antigen of prostate (STEAP) family can regulate the biological behaviors of several cancers. However, the role of STEAP family in glioma remains unclear. Here, we systematically evaluated the relationship between STEAP family and prognosis of glioma patients in multiple cohorts. The analysis showed that dysregulation of STEAP family may affect cancer-immunity cycle, immune infiltration and phenotypes resulting in an immunosuppressive microenvironment in glioma. To accurately predict the prognosis of glioma patients, gene-based risk models were established based on the expression of STEAP1, 2 and 3. Multivariate and univariate Cox analyses demonstrated that the risk models could independently predict the prognosis of glioma. Finally, chemotherapy and immune therapy responses for high- and low-risk patients were predicted. In conclusion, this study systematically analyzed the role of STEAP family in glioma and established a model for predicting therapy response in patients with glioma.

Immune-related miRNA signature identifies prognosis and immune landscape in head and neck squamous cell carcinomas

Background: Head and neck squamous cell carcinoma (HNSCC) is recognised as an immune active cancer, but little is known about the role of microRNAs (miRNAs) in it. In the present study, we aim to determine a prognostic and immune-related miRNAs signature (IRMS) in HNSCC.

Methods: Spearman correlation analysis was used to screen out prognostic immune-related miRNAs based on single-sample gene set enrichment analysis (ssGSEA). Least absolute shrinkage and selection operator (LASSO) Cox regression model was used to establish IRMS in HNSCC. Then, the influence of the IRMS on HNSCC was comprehensively analysed.

Results: We obtained 11 prognostic immune-related miRNAs based on ssGSEA. Then an IRMS integrated with six miRNAs was established through LASSO Cox regression analysis. The stratification survival analysis indicated that IRMS was independent from other characteristics and performed favourably in the overall survival (OS) prediction. The function annotation suggested that IRMS was highly associated with the immune-related response biological processes and pathways which are so important for tumorigenesis of HNSCC. Moreover, the nomogram demonstrated that our model was identified as an independent prognostic factor. In addition, we found that IRMS was significantly correlated with the immune infiltration and expression of critical immune checkpoints, indicating that the poor prognosis might be caused partly by immunosuppressive microenvironment.

Conclusion: We established a novel IRMS, which exhibited a potent prognostic value and could be representative of immune status in HNSCC.

Role of Non-coding RNAs on the Radiotherapy Sensitivity and Resistance of Head and Neck Cancer: From Basic Research to Clinical Application

Head and neck cancers (HNCs) rank as the sixth common and the seventh leading cause of cancer-related death worldwide, with an estimated incidence of 600,000 cases and 40-50% mortality rate every year. Radiotherapy is a common local therapeutic modality for HNC mainly through the function of ionizing radiation, with approximately 60% of patients treated with radiotherapy or chemoradiotherapy. Although radiotherapy is more advanced and widely used in clinical practice, the 5-year overall survival rates of locally advanced HNCs are still less than 40%. HNC cell resistance to radiotherapy remains one of the major challenges to improve the overall survival in HNC patients. Non-coding RNAs (ncRNAs) are newly discovered functional small RNA molecules that are different from messenger RNAs, which can be translated into a protein. Many previous studies have reported the dysregulation and function of ncRNAs in HNC. Importantly, researchers reported that several ncRNAs were also dysregulated in radiotherapy-sensitive or radiotherapy-resistant HNC tissues compared with the normal cancer tissues. They found that ectopically elevating or knocking down expression of some ncRNAs could significantly influence the response of HNC cancer cells to radiotherapy, indicating that ncRNAs could regulate the sensitivity of cancer cells to radiotherapy. The implying mechanism for ncRNAs in regulating radiotherapy sensitivity may be due to its roles on affecting DNA damage sensation, inducing cell cycle arrest, regulating DNA damage repair, modulating cell apoptosis, etc. Additionally, clinical studies reported that in situ ncRNA expression in HNC tissues may predict the response of radiotherapy, and circulating ncRNA from body liquid serves as minimally invasive therapy-responsive and prognostic biomarkers in HNC. In this review, we aimed to summarize the current function and mechanism of ncRNAs in regulating the sensitivity of HNC cancer cells to radiotherapy and comprehensively described the state of the art on the role of ncRNAs in the prognosis prediction, therapy monitoring, and prediction of response to radiotherapy in HNC.

A novel prognostic model predicting the long-term cancer-specific survival for patients with hypopharyngeal squamous cell carcinoma

Background

Hypopharyngeal squamous cell carcinoma (HSCC) is a rare type of head and neck cancer with poor prognosis. However, till now, there is still no model predicting the survival outcomes for HSCC patients. We aim to develop a novel nomogram predicting the long-term cancer-specific survival (CSS) for patients with HSCC and establish a prognostic classification system.

Methods

Data of 2021 eligible HSCC patients were retrieved from the Surveillance, Epidemiology and End Results database between 2010 and 2015. We randomly split the whole cases (ratio: 7:3) into the training and the validation cohort. Cox regression as well as the Least absolute shrinkage and selection operator (LASSO) COX were used to select significant predictors of CSS. Based on the beta-value of these predictors, a novel nomogram was built. The concordance index (C-index), the calibration curve and the decision curve analysis (DCA) were utilized for the model validation and evaluation using the validation cohort.

Results

In total, cancer-specific death occurred in 974/2021 (48.2%) patients. LASSO COX indicated that age, race, T stage, N stage, M stage, surgery, radiotherapy and chemotherapy are significant prognosticators of CSS. A prognostic model based on these factors was constructed and visually presented as nomogram. The C-index of the model was 0.764, indicating great predictive accuracy. Additionally, DCA and calibration curves also demonstrated that the nomogram had good clinical effect and satisfactory consistency between the predictive CSS and actual observation. Furthermore, we developed a prognostic classification system that divides HSCC patients into three groups with different prognosis. The median CSS for HSCC patients in the favorable, intermediate and poor prognosis group was not reached, 39.0-Mo and 10.0-Mo, respectively (p < 0.001).

Conclusions

In this study, we constructed the first nomogram as well as a relevant prognostic classification system that predicts CSS for HSCC patients. We believe these tools would be helpful for clinical practice in patients’ consultation and risk group stratification.

MicroRNA profile in the squamous cell carcinoma: prognostic and diagnostic roles

Head and neck squamous cell carcinomas (HNSCCs) are human malignancies associated with both genetic and environmental factors. MicroRNAs (miRNAs) as a group of small non-coding RNAs have prominent roles in the development of this kind of cancer. Expressions of several miRNAs have been demonstrated to be increased in HNSCC samples vs. non-malignant tissues. In silico prediction tools and functional analyses have confirmed the function of some miRNAs in the modulation of cancer-associated targets, thus indicating these miRNAs as onco-miRs. Moreover, numerous miRNAs have been down-regulated in HNSCC samples. Their targets mostly enhance cell proliferation or inhibit apoptosis. miRNAs signature has practical implications in the diagnosis, staging, and management of HNSC. Most notably, numerous miRNAs have been shown to alter response of tumor cells to anti-cancer drugs such as cisplatin and doxorubicin. Circulating levels of these small transcripts have been suggested as promising biomarkers for diagnosis of HNSCC. In the present manuscript, we sum up the available literature regarding the miRNAs signature in HNSCC and their role as diagnostic/prognostic biomarkers.

Prediction of Radiosensitivity in Head and Neck Squamous Cell Carcinoma Based on Multiple Omics Data

Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor. Radiotherapy (RT) is an important treatment for HNSCC, but not all patients derive survival benefit from RT due to the individual differences on radiosensitivity. A prediction model of radiosensitivity based on multiple omics data might solve this problem. Compared with single omics data, multiple omics data can illuminate more systematical associations between complex molecular characteristics and cancer phenotypes. In this study, we obtained 122 differential expression genes by analyzing the gene expression data of HNSCC patients with RT (N = 287) and without RT (N = 189) downloaded from The Cancer Genome Atlas. Then, HNSCC patients with RT were randomly divided into a training set (N = 149) and a test set (N = 138). Finally, we combined multiple omics data of 122 differential genes with clinical outcomes on the training set to establish a 12-gene signature by two-stage regularization and multivariable Cox regression models. Using the median score of the 12-gene signature on the training set as the cutoff value, the patients were divided into the high- and low-score groups. The analysis revealed that patients in the low-score group had higher radiosensitivity and would benefit from RT. Furthermore, we developed a nomogram to predict the overall survival of HNSCC patients with RT. We compared the prognostic value of 12-gene signature with those of the gene signatures based on single omics data. It suggested that the 12-gene signature based on multiple omics data achieved the best ability for predicting radiosensitivity. In conclusion, the proposed 12-gene signature is a promising biomarker for estimating the RT options in HNSCC patients.

A potential prognostic model based on miRNA expression profile in The Cancer Genome Atlas for bladder cancer patients

Background

This study aimed to construct prognostic model by screening prognostic miRNA signature of bladder cancer.

Methods

The miRNA expression profile data of bladder cancer (BC) in The Cancer Genome Atlas (TCGA) were obtained and randomly divided into the training set and the validation set. Differentially expressed miRNAs (DEMs) between BC and normal control samples in the training set were firstly identified, and DEMs related to prognosis were screened by Cox Regression analysis. Then, the MiR Score system was constructed using X-Tile based cutoff points and verified in the validation set. The prognostic clinical factors are selected out by univariate and multivariate Cox Regression analysis. Finally, the mRNAs related to prognosis were screened and the biological pathway analysis was carried out.

Results

We identified the 7-miRNA signature was significantly associated with the patient’s Overall Survival (OS). A prognostic model was constructed based on the prognostic 7-miRNA signature, and possessed a relative satisfying predicted ability both in the training set and validation set. In addition, univariate and multivariate Cox Regression analysis showed that age, lymphovascular invasion and MiR Score were considered as independent prognostic factors in BC patients. Furthermore, based on MiR Score prognostic model, several differentially expressed genes (DEGs), such as WISP3 and UNC5C, as well as their related biological pathway(s), including cell–cell adhesion and neuroactive ligand-receptor interaction, were considered to be related to BC prognosis.

Conclusion

The prognostic model which was constructed based on the prognostic 7-miRNA signature presented a high predictive ability for BC.

Methodological Development of Combination Drug and Radiotherapy in Basic and Clinical Research

Newer technical improvements in radiation oncology have been rapidly implemented in recent decades, allowing an improved therapeutic ratio. The development of strategies using local and systemic treatments concurrently, mainly targeted therapies, has however plateaued. Targeted molecular compounds and immunotherapy are increasingly being incorporated as the new standard of care for a wide array of cancers. A better understanding of possible prior methodology issues is therefore required and should be integrated into upcoming early clinical trials including individualized radiotherapy-drug combinations. The outcome of clinical trials is influenced by the validity of the preclinical proofs of concept, the impact on normal tissue, the robustness of biomarkers and the quality of the delivery of radiation. Herein, key methodological aspects are discussed with the aim of optimizing the design and implementation of future precision drug-radiotherapy trials.

Radiation-induced circulating miRNA expression in blood of head and neck cancer patients

In recent years, scientists have found evidence confirming the aberrant expression of miRNAs in cancer patients compared to healthy individuals. The growing interest in the identification of non-invasive and specific diagnostic and prognostic molecular markers has identified microRNAs as potential candidates in cancer diagnosis, prognosis and treatment response. In the present study, we have analyzed the expression profile of circulating miR-21, -191 and -421 in peripheral blood of head and neck cancer patients (HNC) to investigate a possible modulation of mRNA levels by radiation and to identify the role of mRNA as biomarkers of cancer prognosis. Results showed a modulation of the microRNA expression at different time points after radiotherapy, suggesting that treatment may influence the release of circulating miRNAs depending also on the time interval elapsed since radiotherapy. The expression levels of miR-21, -191 and -421 were higher in blood of patients treated with radiotherapy alone after 6 months from the end of therapy and high levels of them seemed to correlate with the remission of the disease. The trends shown in this study confirmed that miRNAs could be useful prognosis markers and could provide preliminary data for further evaluation in predicting patients' response to radiotherapy by developing miRNA-based treatments to improve the sensitivity of cancer cells to radiotherapy.

Salivary microRNAs identified by small RNA sequencing as potential predictors of response to intensity-modulated radiotherapy in head and neck cancer patients

PURPOSE

Progress in radiation therapy of head and neck squamous cell carcinomas (HNSCCs) is logically linked to the development of molecular predictors that would help to enhance individually tailored treatment. MicroRNA (miRNA) expression profiles in tumors have repeatedly been tested to optimize the molecular diagnostics of HNSCC. In addition to tumor tissues, miRNAs are stably present in body fluids, including saliva, and can thus be collected non-invasively. The aim of our current study was to evaluate whether salivary miRNAs have potential as response predictors in HNSCC patients treated with intensity modulated radiation therapy (IMRT).

METHODS

In total 48 HNSCC patients treated by definitive IMRT were enrolled in our prospective study. To identify predictive salivary miRNAs, we used small RNA sequencing in 14 saliva samples of HNSCC patients and qRT-PCR validation of selected miRNA candidates in an independent set of 34 patients.

RESULTS

We found that salivary miR-15a-5p and miR-15b-5p exhibited differential levels between patients with and without complete remission (p = 0.025 and p = 0.028, respectively). Subsequent Kaplan-Meier analysis confirmed that patients with higher levels of miR-15a-5p reached a significantly longer locoregional progression-free survival (LPFS) than those with low levels (p = 0.024). Finally, multivariate Cox regression analysis revealed that miR-15a-5p may serve as an independent predictive biomarker of LPFS in HNSCC patients treated with IMRT (HR 0.104; 95% CI 0.004-0.911; p = 0.04).

CONCLUSIONS

We conclude that salivary miR-15a-5p may represent a potential biomarker for individualized treatment decision-making in HNSCC patients.

microRNAs identified in prostate cancer: Correlative studies on response to ionizing radiation

As the most frequently diagnosed non-skin cancer in men and a leading cause of cancer-related death, understanding the molecular mechanisms that drive treatment resistance in prostate cancer poses a significant clinical need. Radiotherapy is one of the most widely used treatments for prostate cancer, along with surgery, hormone therapy, and chemotherapy. However, inherent radioresistance of tumor cells can reduce local control and ultimately lead to poor patient outcomes, such as recurrence, metastasis and death. The underlying mechanisms of radioresistance have not been fully elucidated, but it has been suggested that miRNAs play a critical role. miRNAs are small non-coding RNAs that regulate gene expression in every signaling pathway of the cell, with one miRNA often having multiple targets. By fine-tuning gene expression, miRNAs are important players in modulating DNA damage response, cell death, tumor aggression and the tumor microenvironment, and can ultimately affect a tumor's response to radiotherapy. Furthermore, much interest has focused on miRNAs found in biofluids and their potential utility in various clinical applications. In this review, we summarize the current knowledge on miRNA deregulation after irradiation and the associated functional outcomes, with a focus on prostate cancer. In addition, we discuss the utility of circulating miRNAs as non-invasive biomarkers to diagnose, predict response to treatment, and prognosticate patient outcomes.

Transcriptomics and Epigenomics in head and neck cancer: available repositories and molecular signatures

For many years, head and neck squamous cell carcinoma (HNSCC) has been considered as a single entity. However, in the last decades HNSCC complexity and heterogeneity have been recognized. In parallel, high-throughput omics techniques had allowed picturing a larger spectrum of the behavior and characteristics of molecules in cancer and a large set of omics web-based tools and informative repository databases have been developed. The objective of the present review is to provide an overview on biological, prognostic and predictive molecular signatures in HNSCC. To contextualize the selected data, our literature survey includes a short summary of the main characteristics of omics data repositories and web-tools for data analyses. The timeframe of our analysis was fixed, encompassing papers published between January 2015 and January 2019. From more than 1000 papers evaluated, 61 omics studies were selected: 33 investigating mRNA signatures, 11 and 13 related to miRNA and other non-coding-RNA signatures and 4 analyzing DNA methylation signatures. More than half of identified signatures (36) had a prognostic value but only in 10 studies selection of a specific anatomical sub-site (8 oral cavity, 1 oropharynx and 1 both oral cavity and oropharynx) was performed. Noteworthy, although the sample size included in many studies was limited, about one-half of the retrieved studies reported an external validation on independent dataset(s), strengthening the relevance of the obtained data. Finally, we highlighted the development and exploitation of three gene-expression signatures, whose clinical impact on prognosis/prediction of treatment response could be high. Based on this overview on omics-related literature in HNSCC, we identified some limits and strengths. The major limits are represented by the low number of signatures associated to DNA methylation and to non-coding RNA (miRNA, lncRNA and piRNAs) and the availability of a single dataset with multiple omics on more than 500 HNSCC (i.e. TCGA). The major strengths rely on the integration of multiple datasets through meta-analysis approaches and on the growing integration among omics data obtained on the same cohort of patients. Moreover, new approaches based on artificial intelligence and informatic analyses are expected to be available in the next future.

MicroRNA-15b-5p Predicts Locoregional Relapse in Head and Neck Carcinoma Patients Treated With Intensity-modulated Radiotherapy

BACKGROUND/AIM

Head and neck cancers are a heterogenous group of epithelial tumors represented mainly by squamous cell carcinomas (HNSCC), which are the sixth most common type of cancer worldwide. Surgery together with radiotherapy (RT) is among the basic treatment modalities for most HNSCC patients. Various biomarkers aiming to predict patients' response to RT are currently investigated. The reason behind this effort is, on one hand, to distinguish radioresistant patients that show weak benefit from RT and, on the other hand, reduce the ionizing radiation dose in less aggressive radiosensitive HNSCC with possibly less acute or late toxicity.

MATERIALS AND METHODS

A total of 94 HNSCC patients treated by definitive intensity-modulated radiotherapy were included in our retrospective study. We used a global expression analysis of microRNAs (miRNAs) in 43 tumor samples and validated a series of selected miRNAs in an independent set of 51 tumors.

RESULTS

We identified miR-15b-5p to be differentially expressed between patients with short and long time of locoregional control (LRC). Kaplan-Meier analysis confirmed that HNSCC patients with higher expression of miR-15b-5p reach a significantly longer locoregional relapse-free survival compared to patients expressing low levels. Finally, multivariable Cox regression analysis revealed that miR-15b-5p is an independent predictive biomarker of LRC in HNSCC patients (HR=0.25; 95% CI=0.05-0.78; p<0.016).

CONCLUSION

miR-15b-5p represents a potentially helpful biomarker for individualized treatment decisions concerning the management of HNSCC patients.

Modeling the effect of intratumoral heterogeneity of radiosensitivity on tumor response over the course of fractionated radiation therapy

Background

Standard radiobiology theory of radiation response assumes a uniform innate radiosensitivity of tumors. However, experimental data show that there is significant intratumoral heterogeneity of radiosensitivity. Therefore, a model with heterogeneity was developed and tested using existing experimental data to show the potential effects from the presence of an intratumoral distribution of radiosensitivity on radiation therapy response over a protracted radiation therapy treatment course.

Methods

The standard radiation response curve was modified to account for a distribution of radiosensitivity, and for variations in the repopulation rates of the tumor cell subpopulations. Experimental data from the literature were incorporated to determine the boundaries of the model. The proposed model was then used to show the changes in radiosensitivity of the tumor during treatment, and the effects of fraction size, α/β ratio and variation of the repopulation rates of tumor cells.

Results

In the presence of an intratumoral distribution of radiosensitivity, there is rapid selection of radiation-resistant cells over a course of fractionated radiation therapy. Standard treatment fractionation regimes result in the near-complete replacement of the initial population of sensitive cells with a population of more resistant cells. Further, as treatment progresses, the tumor becomes more resistant to further radiation treatment, making each fractional dose less efficacious. A wider initial distribution induces increased radiation resistance. Hypofractionation is more efficient in a heterogeneous tumor, with increased cell kill for biologically equivalent doses, while inducing less resistance. The model also shows that a higher growth rate in resistant cells can account for the accelerated repopulation that is seen during the clinical treatment of patients.

Conclusions

Modeling of tumor cell survival with radiosensitivity heterogeneity alters the predicted tumor response, and explains the induction of radiation resistance by radiation treatment, the development of accelerated repopulation, and the potential beneficial effects of hypofractionation. Tumor response to treatment may be better predicted by assaying for the distribution of radiosensitivity, or the extreme of the radiosensitivity, rather than measuring the initial, general radiation sensitivity of the untreated tumor.

Analysis of microRNA expression profiles reveals a 5‑microRNA prognostic signature for predicting overall survival time in patients with gastric adenocarcinoma

There is growing evidence supporting dysregulated microRNAs (miRNAs) as potential prognostic biomarkers in cancer. The present study aimed to identify an miRNA model set with prognostic power for patients with gastric adenocarcinoma. miRNA‑seq data from 155 patients and 37 controls were downloaded from The Cancer Genome Atlas (TCGA) database for a comprehensive analysis of miRNA expression profiles and were used as training data. A total of 5 prognostic miRNAs, which have not been previously reported, were identified using univariate and multivariate Cox regression analyses. A separate 155‑patient TCGA cohort was used as a validation set for evaluation of the risk model. Patients in the training set were assigned into high‑ and low‑risk groups according to the 5‑miRNA signature risk scores. Kaplan‑Meier survival analyses demonstrated that patients with high risk scores had significantly shorter survival times than those with low risk scores. The risk model validation confirmed the prognostic ability of this 5‑miRNA signature in predicting the risk status of patients. Stratification analysis for clinical prognostic variables demonstrated recurrence and age were significant prognostic factors in the low‑ and high‑risk groups, respectively. In conclusion, the present 5‑miRNA signature is a potential independent risk factor for patient outcomes. The risk model based on the 5‑miRNA signature performed well in predicting overall survival time in patients with gastric adenocarcinoma.

Personalized prognostication in head and neck cancer: A systematic review of nomograms according to the AJCC precision medicine core (PMC) criteria

BACKGROUND

The American Joint Committee on Cancer (AJCC) Precision Medicine Core (PMC) has recognized the need for more personalized probabilistic predictions above the "TNM" staging system and has recently released a checklist of inclusion and exclusion criteria for evaluating prognostic models.

METHODS

A systematic review of articles in which nomograms were created for head and neck cancer (HNC) was carried out according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The AJCC PMC criteria were used to score the individual studies.

RESULTS

Forty-four studies were included in the final qualitative analysis. The mean number of inclusion criteria met was 9.3 out of 13, and the mean number of exclusion criteria met was 2.1 out of 3. Studies were generally of high quality, but no single study fulfilled all of the AJCC PMC criteria.

CONCLUSION

This is the first study to utilize the AJCC checklist to comprehensively evaluate the published prognostic nomograms in HNC. Future studies should attempt to adhere to the AJCC PMC criteria. Recommendations for future research are given.

SUMMARY

The AJCC recently released a set of criteria to grade the quality of prognostic cancer models. In this study, we grade all published nomograms for head and neck cancer according to the new guidelines.

miR-31-5p Is a Potential Circulating Biomarker and Therapeutic Target for Oral Cancer

MicroRNAs have been proposed as novel biomarkers for the diagnosis and treatment of many types of cancer. The levels of five candidate microRNAs (miRNAs) (miR-99a-5p, miR-31-5p, miR-138-5p, miR-21-5p, and miR-375-3p) in sera from oral cancer patients and paired tumor and normal tissues were detected by real-time qPCR. The diagnostic power of these miRNAs was analyzed by receiver operating characteristic (ROC) curves. Patient-derived xenograft (PDX) models of oral cancer were established and utilized to verify the potential therapeutic effect of miR-31-5p. Candidate miRNAs were screened from our previous studies and verified in 11 paired oral cancer and adjacent normal tissues. Only serum miR-31-5p levels were significantly different between oral cancer patients and healthy controls and between pre- and postoperative patients. Based on the logistic regression model, this panel of five miRNAs distinguished oral cancer patients from healthy control, with an area under the ROC curve (AUC) of 0.776 (sensitivity = 76.8% and specificity = 73.6%). Furthermore, a miR-31-5p mimic enhanced the proliferation of normal epithelial cells, and antagomiR-31-5p inhibited the proliferation of oral cancer cells in vitro. In vivo, antagomiR-31-5p significantly inhibited tumor growth in oral cancer PDX models. Our findings suggest that circulating miR-31-5p might act as an independent biomarker for oral cancer diagnosis and could serve as a therapeutic target for oral cancer.

A novel six-microRNA-based model to improve prognosis prediction of breast cancer

Current tumor-node-metastasis (TNM) stage is unable to accurately predict the overall survival (OS) in breast cancer (BC) patients. This study aimed to construct a microRNA (miRNA)-based model to improve survival prediction of BC. We confirmed 99 differentially expressed miRNAs (DEMs) in 1044 BC samples compared to 102 adjacent normal breast tissues from The Cancer Genome Atlas (TCGA) database. Prognostic DEMs were used to establish a miRNA-based nomogram via Cox regression model. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes analyses (KEGG) were executed to analyze target genes of miRNAs. A six-miRNA signature was screened to effectively distinguish high-risk patients in the primary and validation cohort (all P<0.001). Furthermore, we established a novel prognostic model incorporating the six-miRNA signature and clinical risk factors to predict 5-year OS of BC. Time-dependent receiver operating characteristic analysis suggested that the predictive accuracy of the six-miRNA-based nomogram was distinctly higher than that of TNM stage (0.758 vs 0.650, P<0.001). GO and KEGG pathway analyses showed that the 39 target genes mainly enrichment in protein binding, cytoplasm and MAPK signaling pathway. Our six-miRNA-based model is a reliable prognostic tool for survival prediction and provides information for individualized treatment decisions in BC patients.