Evaluation of the Response of HNSCC Cell Lines to γ-Rays and 12C Ions: Can Radioresistant Tumors Be Identified and Selected for 12C Ion Radiotherapy?

RNA-binding protein expression based machine learning model predicts metastasis and treatment outcome of testicular cancer

BACKGROUND

RNA-binding proteins (RBPs) are key regulators of cellular transcription and are associated with the occurrence and development of diseases.

OBJECTIVE

This study aimed to validate the biological characteristics and clinical value of RBPs in testicular cancer, and then construct prediction models for testicular cancer metastasis and treatment outcome.

METHODS

RNA sequencing data from 150 testicular tumors and 6 normal tissues were obtained from the cancer genome atlas (TCGA). Additionally, RNA sequencing data from 165 normal testicular tissues were downloaded from the genotype-tissue expression (GTEx) portal. The chemotherapy sensitivity of testicular tumor was evaluated based on the genomics of drug sensitivity in cancer (GDSC) and cancer therapeutics response portal (CTRP) databases. RNA sequencing data was analyzed and predicted for tumor metastasis and treatment outcomes through machine learning models such as artificial neural networks (ANN), random forests (RF), support vector machines (SVM), and logistic regression models (LR).

RESULTS

A RBP risk-score model was developed with the genes: GAPDH, APOBEC3G, KRT18, NOSIP, KCTD12, ENO1, HMGA1, LDHB, ANXA2, ELOVL6, TCF7, BICD1. Those biomarkers were enriched in growth factor activity, hormone receptor binding, and cell killing signaling pathway. Risk-score model can predict the progress free interval (PFI), disease free interval (DFI), and metastasis status of patients with testicular cancer. Patients with high risk-score tumor had an increased tumor infiltrating M2 macrophage, and were more likely to progress after anti-PD-L1 immunotherapy. High risk patients seemed to benifit more from cisplatin-based chemotherapy, but less from bleomycin chemotherapy. Machine learning models basing on RBPs were able to predict tumor metastasis and the effects of chemotherapy and radiotherapy. ANN model achieved the highest accuracy in predicting tumor lymph node metastasis and radiotherapy sensitivity.

CONCLUSION

RBP signature genes can serve as biomarkers for testicular cancer and play a role in predicting tumor metastasis and therapeutic efficacy.

Defective homologous recombination and genomic instability predict increased responsiveness to carbon ion radiotherapy in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is notably resistant to conventional chemotherapy and radiation treatment. However, clinical trials indicate that carbon ion radiotherapy (CIRT) with concurrent gemcitabine is effective for unresectable locally advanced PDAC. This study aimed to identify patient characteristics predictive of CIRT response. We utilized a panel of human PDAC cell lines with diverse genetic profiles to determine their sensitivity to CIRT compared to γ-rays, assessing relative biological effectiveness (RBE) at 10% survival, which ranged from 1.96 to 3.04. Increased radiosensitivity was linked to impaired DNA double-strand break (DSB) repair, particularly in cell lines with deficiencies in the homologous recombination (HR) repair pathway and/or elevated genomic instability from replication stress. Furthermore, pretreatment with the HR inhibitor B02 significantly enhanced CIRT sensitivity in a radioresistant PDAC cell line when irradiated in the spread-out Bragg peak but not at the entry position of the beam. These findings suggest that PDAC tumors with HR pathway mutations or high replication stress are more likely to benefit from CIRT while minimizing normal tissue toxicity.

Identification of novel therapeutic targets for head and neck squamous cell carcinoma through bioinformatics analysis

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous cancer with limited therapeutic options. Using publicly available datasets, we identified the WD repeat domain 54 (WDR54) gene as a potential therapeutic target in HNSCC. Gene expression profiling interactive analysis version 2 (GEPIA2) was used to identify genes differentially overexpressed in HNSCC. Our results showed that WDR54, a member of the WD40 repeat domain family, was overexpressed in HNSCC tumor samples. Analysis of three gene expression omnibus datasets showed that WDR54 was overexpressed in tumor samples. Using the UALCAN database, we showed that WDR54 expression in patients with HNSCC at different tumor stages gradually increased with disease progression. We confirmed the association between WDR54 and metastasis using TNMplot.com. WDR54 was overexpressed in metastatic samples compared to that in normal and tumor samples. Kaplan-Meier analysis showed that patients with high WDR54 levels had a poorer prognosis. Additionally, WDR54 expression was correlated with the epidermal growth factor receptor, which is frequently overexpressed in HNSCC. Our findings suggest that WDR54 is a promising biomarker and therapeutic target in HNSCC.

Organization and operation of multi particle therapy facilities: the Marburg Ion-Beam Therapy Center, Germany (MIT)

Purpose

The Marburg Ion-Beam Therapy Center (MIT) is one of two particle therapy centers in Germany that enables the treatment of patients with both protons and carbon ions. The facility was build by Siemens Healthineers and is one of only two centers worldwide built by Siemens (Marburg, Germany and Shanghai, China). The present report provides an overview of technical and clinical operations as well as research activities at MIT.

Methods

The MIT was completed in 2011 and uses a synchrotron for accelerating protons and carbon ions up to energies of 250 MeV/u and 430 MeV/u respectively. Three treatment rooms with a fixed horizontal beam-line and one room with a 45 degree beam angle are available.

Results

Since the start of clinical operations in 2015, around 2.500 patients have been treated at MIT, about 40% with carbon ions and 60% with protons. Currently around 400 patients are treated each year. The majority of the patients suffered from benign and malign CNS tumors (around 40%) followed by head and neck tumors (around 23%). MIT is actively involved in clinical studies with its patients. In addition to clinical operations, there is active research at MIT in the fields of radiation biology and medical physics. The focus is on translational research to improve the treatment of H & N carcinomas and lung cancer (NSCLC). Moreover, intensive work is being carried out on the technical implementation of FLASH irradiation for research purposes.

Conclusion

The MIT is one of two centers worldwide that were built by Siemens Healtineers and has been successfully in clinical operation since 2015. The service provided by Siemens is guaranteed until 2030, the future after 2030 is currently under discussion.

The rationale for a carbon ion radiation therapy facility in Australia

Australia has taken a collaborative nationally networked approach to achieve particle therapy capability. This supports the under-construction proton therapy facility in Adelaide, other potential proton centres and an under-evaluation proposal for a hybrid carbon ion and proton centre in western Sydney. A wide-ranging overview is presented of the rationale for carbon ion radiation therapy, applying observations to the case for an Australian facility and to the clinical and research potential from such a national centre.

Identification of an individualized therapy prognostic signature for head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) are the most common cancers in the head and neck. Therapeutic response-related genes (TRRGs) are closely associated with carcinogenesis and prognosis in HNSCC. However, the clinical value and prognostic significance of TRRGs are still unclear. We aimed to construct a prognostic risk model to predict therapy response and prognosis in TRRGs-defined subgroups of HNSCC.

METHODS

The multiomics data and clinical information of HNSCC patients were downloaded from The Cancer Genome Atlas (TCGA). The profile data GSE65858 and GSE67614 chip was downloaded from public functional genomics data Gene Expression Omnibus (GEO). Based on TCGA-HNSC database, patients were divided into a remission group and a non-remission group according to therapy response, and differentially expressed TRRGs between those two groups were screened. Using Cox regression analysis and Least absolute shrinkage and selection operator (LASSO) analysis, candidate TRRGs that can predict the prognosis of HNSCC were identified and used to construct a TRRGs-based signature and a prognostic nomogram.

RESULT

A total of 1896 differentially expressed TRRGs were screened, including 1530 upregulated genes and 366 downregulated genes. Then, 206 differently expressed TRRGs that was significantly associated with the survival were chosen using univariate Cox regression analysis. Finally, a total of 20 candidate TRRGs genes were identified by LASSO analysis to establish a signature for risk prediction, and the risk score of each patient was calculated. Patients were divided into a high-risk group (Risk-H) and a low-risk group (Risk-L) based on the risk score. Results showed that the Risk-L patients had better overall survival (OS) than Risk-H patients. Receiver operating characteristic (ROC) curve analysis revealed great predictive performance for 1-, 3-, and 5-year OS in TCGA-HNSC and GEO databases. Moreover, for patients treated with post-operative radiotherapy, Risk-L patients had longer OS and lower recurrence than Risk-H patients. The nomogram involves risk score and other clinical factors had good performance in predicting survival probability.

CONCLUSIONS

The proposed risk prognostic signature and Nomogram based on TRRGs are novel promising tools for predicting therapy response and overall survival in HNSCC patients.

Adaptive c-Met-PLXDC2 Signaling Axis Mediates Cancer Stem Cell Plasticity to Confer Radioresistance-associated Aggressiveness in Head and Neck Cancer

Radiotherapy plays an essential role in the treatment of head and neck squamous cell carcinoma (HNSCC), yet radioresistance remains a major barrier to therapeutic efficacy. A better understanding of the predominant pathways determining radiotherapy response could help develop mechanism-informed therapies to improve cancer management. Here we report that radioresistant HNSCC cells exhibit increased tumor aggressiveness. Using unbiased proteome profiler antibody arrays, we identify that upregulation of c-Met phosphorylation is one of the critical mechanisms for radioresistance in HNSCC cells. We further uncover that radioresistance-associated HNSCC aggressiveness is effectively exacerbated by c-Met but is suppressed by its genetic knockdown and pharmacologic inactivation. Mechanistically, the resulting upregulation of c-Met promotes elevated expression of plexin domain containing 2 (PLXDC2) through activating ERK1/2-ELK1 signaling, which in turn modulates cancer cell plasticity by epithelial-mesenchymal transition (EMT) induction and enrichment of the cancer stem cell (CSC) subpopulation, leading to resistance of HNSCC cells to radiotherapy. Depletion of PLXDC2 overcomes c-Met-mediated radioresistance through reversing the EMT progress and blunting the self-renewal capacity of CSCs. Therapeutically, the addition of SU11274, a selective and potent c-Met inhibitor, to radiation induces tumor shrinkage and limits tumor metastasis to lymph nodes in an orthotopic mouse model. Collectively, these significant findings not only demonstrate a novel mechanism underpinning radioresistance-associated aggressiveness but also provide a possible therapeutic strategy to target radioresistance in patients with HNSCC.

Significance

This work provides novel insights into c-Met-PLXDC2 signaling in radioresistance-associated aggressiveness and suggests a new mechanism-informed therapeutic strategy to overcome failure of radiotherapy in patients with HNSCC.