Combination of Radiosensitivity Gene Signature and PD-L1 Status Predicts Clinical Outcome of Patients With Locally Advanced Head and Neck Squamous Cell Carcinoma: A Study Based on The Cancer Genome Atlas Dataset

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.

Improving the efficacy of combined radiotherapy and immunotherapy: focusing on the effects of radiosensitivity

Cancer treatment is gradually entering an era of precision, with multitude studies in gene testing and immunotherapy. Tumor cells can be recognized and eliminated by the immune system through the expression of tumor-associated antigens, but when the cancer escapes or otherwise suppresses immunity, the balance between cancer cell proliferation and immune-induced cancer cell killing may be interrupted, resulting in tumor proliferation and progression. There has been significant attention to combining conventional cancer therapies (i.e., radiotherapy) with immunotherapy as opposed to treatment alone. The combination of radio-immunotherapy has been demonstrated in both basic research and clinical trials to provide more effective anti-tumor responses. However, the absolute benefits of radio-immunotherapy are dependent on individual characteristics and not all patients can benefit from radio-immunotherapy. At present, there are numerous articles about exploring the optimal models for combination radio-immunotherapy, but the factors affecting the efficacy of the combination, especially with regard to radiosensitivity remain inconclusive. Radiosensitivity is a measure of the response of cells, tissues, or individuals to ionizing radiation, and various studies have shown that the radiosensitivity index (RSI) will be a potential biomarker for predicting the efficacy of combination radio-immunotherapy. The purpose of this review is to focus on the factors that influence and predict the radiosensitivity of tumor cells, and to evaluate the impact and predictive significance of radiosensitivity on the efficacy of radio-immunotherapy combination.

LINC00963-FOSB-mediated transcription activation of UBE3C enhances radioresistance of breast cancer cells by inducing ubiquitination-dependent protein degradation of TP73

BACKGROUND

The ubiquitin protein ligase E3C (UBE3C) has been reported to play an oncogenic role in breast cancer (BRCA). This work further investigates the effect of UBE3C on the radioresistance of BRCA cells.

METHODS

Molecules linking to radioresistance in BRCA were identified by analyzing two GEO datasets, GSE31863 and GSE101920. UBE3C overexpression or knockdown was induced in parental or radioresistant BRCA cells, followed by irradiation treatment. The malignant properties of cells in vitro, and the growth and metastatic activity of cells in nude mice, were analyzed. Downstream target proteins, as well as upstream transcriptional regulators of UBE3C, were predicted by bioinformatics tools. Molecular interactions were confirmed by immunoprecipitation and immunofluorescence assays. Furthermore, artificial alterations of TP73 and FOSB were induced in the BRCA cells for functional rescue assays.

RESULTS

According to bioinformatics analyses, UBE3C expression was linked to radioresistance in BRCA. UBE3C knockdown in radioresistant BRCA cells reduced while its overexpression in parental BRCA cells increased the radioresistance of cells in vitro and in vivo. UBE3C, which induced ubiquitination-dependent protein degradation of TP73, was transcriptionally activated by FOSB. The radioresistance of cancer cells was blocked by TP73 overexpression or FOSB knockdown. Additionally, LINC00963 was found to be responsible for the recruitment of FOSB to the UBE3C promoter for transcription activation.

CONCLUSION

This work demonstrates that LINC00963 induces nuclear translocation of FOSB and the consequent transcription activation of UBE3C, which enhances radioresistance of BRCA cells by inducing ubiquitination-dependent protein degradation of TP73.

A Four-Gene Signature Associated with Radioresistance in Head and Neck Squamous Cell Carcinoma Identified by Text Mining and Data Analysis

Purpose

Head and neck squamous cell carcinoma (HNSCC) is the sixth leading cancer globally, and radiotherapy plays a crucial part in its treatment. This study was designed to identify potential genes related to radiation resistance in HNSCC.

Method

We first used text mining to obtain common genes related to radiotherapy resistance and HNSCC in published articles. Functional enrichment analyses were conducted to identify the significantly enriched pathways and genes. Protein and protein interactions were performed, and the most significant gene modules were determined; then, genes in the gene modules were validated at transcriptional levels and overall survival. Gene set variation analysis (GSVA) score was calculated, and the association between GSVA score and survival/pathway was estimated. Immune cell infiltration, methylation, and genetic alteration analysis of these genes was conducted in HNSCC patients. Finally, potential sensitive anticancer drugs related to target genes were obtained.

Result

We identified 583 common genes through text mining. After further validation, a four-gene signature (EPHB2, SPP1, SERPINE1, and VEGFC) was constructed. The patients with higher GSVA scores have a worse prognosis than those with lower GSVA scores. Differences in methylation of these four genes in HNSCC tumor tissue and normal tissue were compared, with higher methylation levels of EBPH2 and SPP1 in normal tissue and higher methylation levels of SERPINE1 in the tumor. Immune cell infiltration revealed that the increased expression of these genes was closely related to the infiltration level of CD4+ T cell, neutrophil, macrophage, and dendritic cell. Thirty drugs, including 22 positively and eight negatively correlated drugs that most correlated with related genes, were available for treating HNSCC.

Conclusion

In this study, we identified four potential genes as well as corresponding drugs that might be related to radioresistance in HNSCC patients. These candidate genes may provide a promising avenue to further elevate radiotherapy efficacy.

Prognostic value of PD-1, PD-L1 and PD-L2 deserves attention in head and neck cancer

Head and neck cancer has high heterogeneity with poor prognosis, and emerging researches have been focusing on the prognostic markers of head and neck cancer. PD-L1 expression is an important basis for strategies of immunosuppressive treatment, but whether it has prognostic value is still controversial. Although meta-analysis on PD-L1 expression versus head and neck cancer prognosis has been performed, the conclusions are controversial. Since PD-L1 and PD-L2 are two receptors for PD-1, here we summarize and analyze the different prognostic values of PD-1, PD-L1, and PD-L2 in head and neck cancer in the context of different cell types, tissue localization and protein forms. We propose that for head and neck cancer, the risk warning value of PD-1/PD-L1 expression in precancerous lesions is worthy of attention, and the prognostic value of PD-L1 expression at different subcellular levels as well as the judgment convenience of prognostic value of PD-1, PD-L1, PD-L2 should be fully considered. The PD-L1 evaluation systems established based on immune checkpoint inhibitors (ICIs) are not fully suitable for the evaluation of PD-L1 prognosis in head and neck cancer. It is necessary to establish a new PD-L1 evaluation system based on the prognosis for further explorations. The prognostic value of PD-L1, PD-L2 expression in head and neck cancer may be different for early-stage and late-stage samples, and further stratification is required.