Comprehensive study of clinicopathological and immune cell infiltration and lactate dehydrogenase expression in patients with thymic epithelial tumours.

BACKGROUND: Lactate dehydrogenase (LDH) has emerged as a promising biomarker for cancer. However, the current understanding of LDH and circulating LDH expression in thymic epithelial tumour (TET) is lacking. METHODS: A comprehensive literature review and meta-analysis were performed to evaluate the clinical significance of circulating LDH levels in patients with TET. Circulating LDH levels were measured using a laboratory analyser (Cobas8000, Roche, Basel, Switzerland). The maximum standardised uptake value (SUVmax) was determined in patients who underwent whole-body 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT). Multiplex immunohistochemistry (IHC) was performed using a commercially available kit (Opal 6-plex Detection Kit, Akoya Biosciences, Marlborough, MA, USA) and slide scanner (Slideview VS200, Olympus, Tokyo, Japan). All statistical analyses were performed using SPSS (IBM Corp., Armonk, NY, USA) and Prism version 9.0 (GraphPad Inc., San Diego, CA, USA). Differences with p < 0.05 were considered to be statistically significant. RESULTS: Meta-analysis revealed that elevated circulating serum levels of LDH predicted poor prognosis in patients with TET. Circulating levels of LDH were analysed in the serum of 313 patients with TET and 87 with benign mediastinal mass. The mean circulating LDH level in patients with thymic carcinoma (TC) was significantly higher than that in those with thymoma (TM) and the benign group (p < 0.001). Expression levels of circulating LDH were significantly reduced in postoperative samples compared with that in preoperative samples (p < 0.05). Receiver operating characteristic (ROC) curve analysis for diagnosing TC yielded an area under the curve of 0.74, with a sensitivity of 54 % and specificity of 86 %. Furthermore, patients with TC exhibited higher 18F-FDG PET/CT SUVmax values compared to those with TM. Correlation analysis demonstrated a positive association between SUVmax values and circulating LDH levels. In addition, the percentages of LDH-positive cells in TC and type B1 TM tissues were higher than those in other subtypes of TM, and a significant positive correlation between the percentages of LDH-positive and CD20-positive cells was detected in patients with TET (p < 0.05). CONCLUSION: Circulating serum LDH level may serve as a non-invasive biomarker for the diagnosis and prognosis of TET. The relationship between LDH expression and immune cell infiltration merits further regarding its application in companion diagnosis for immunotherapy.

Radiation-sensitive genetic prognostic model identifies individuals at risk for radiation resistance in head and neck squamous cell carcinoma.

BACKGROUND: The advantages of radiotherapy for head and neck squamous cell carcinoma (HNSCC) depend on the radiation sensitivity of the patient. Here, we established and verified radiological factor-related gene signature and built a prognostic risk model to predict whether radiotherapy would be beneficial. METHODS: Data from The Cancer Genome Atlas, Gene Expression Omnibus, and RadAtlas databases were subjected to LASSO regression, univariate COX regression, and multivariate COX regression analyses to integrate genomic and clinical information from patients with HNSCC. HNSCC radiation-related prognostic genes were identified, and patients classified into high- and low-risk groups, based on risk scores. Variations in radiation sensitivity according to immunological microenvironment, functional pathways, and immunotherapy response were investigated. Finally, the expression of HNSCC radiation-related genes was verified by qRT-PCR. RESULTS: We built a clinical risk prediction model comprising a 15-gene signature and used it to divide patients into two groups based on their susceptibility to radiation: radiation-sensitive and radiation-resistant. Overall survival was significantly greater in the radiation-sensitive than the radiation-resistant group. Further, our model was an independent predictor of radiotherapy response, outperforming other clinical parameters, and could be combined with tumor mutational burden, to identify the target population with good predictive value for prognosis at 1, 2, and 3 years. Additionally, the radiation-resistant group was more vulnerable to low levels of immune infiltration, which are significantly associated with DNA damage repair, hypoxia, and cell cycle regulation. Tumor Immune Dysfunction and Exclusion scores also suggested that the resistant group would respond less favorably to immunotherapy. CONCLUSIONS: Our prognostic model based on a radiation-related gene signature has potential for application as a tool for risk stratification of radiation therapy for patients with HNSCC, helping to identify candidates for radiation therapy and overcome radiation resistance.