High DNMT1 Is Associated With Worse Local Control in Early-Stage Laryngeal Squamous Cell Carcinoma.

OBJECTIVES/HYPOTHESIS: Early-stage laryngeal squamous cell carcinoma (LSCC) has yielded local control rates of 75% after radiotherapy. DNA methylation, in which DNA methyltransferases play an important role, has influence on tumorigenesis. In this study, we investigated the association between the expression of DNA methyltransferase 1 (DNMT1) and local control in early-stage LSCC treated with radiotherapy. STUDY DESIGN: Retrospective cohort study. METHODS: We analyzed a well-defined homogeneous series of 125 LSCC patients treated with radiotherapy with curative intent. The association of immunohistochemical expression of DNMT1 with local control was evaluated using Cox proportional hazard regression models. RESULTS: With a median follow-up of 58 months, 29 local recurrences (23%) were observed. On univariate analysis, worse local control was associated with high DNMT1 expression (hazard ratio [HR] 2.57, 95% confidence interval [CI] 1.10-6.01). Also, higher T-stage (HR 2.48, 95% CI 1.06-5.80) and positive N-status (HR 2.62, 95% CI 1.06-6.47) were associated with worse local control. Multivariate Cox regression demonstrated that high DNMT1 (HR 2.81; 95% CI 1.20-6.58) was independently associated with worse local control. CONCLUSIONS: We found an association between high DNMT1 expression and worse local control in a homogeneous well-defined cohort of early-stage LSCC patients treated with definitive radiotherapy. The association between DNA methylation status as determined by DNMT1 expression and local control suggests that DNMT1 acts as a potential prognostic tumor marker in treatment decision-making in early-stage laryngeal carcinoma. LEVEL OF EVIDENCE: NA Laryngoscope, 132:801-805, 2022.

The OncoLifeS data-biobank for oncology: a comprehensive repository of clinical data, biological samples, and the patient's perspective.

BACKGROUND: Understanding cancer heterogeneity, its temporal evolution over time, and the outcomes of guided treatment depend on accurate data collection in a context of routine clinical care. We have developed a hospital-based data-biobank for oncology, entitled OncoLifeS (Oncological Life Study: Living well as a cancer survivor), that links routine clinical data with preserved biological specimens and quality of life assessments. The aim of this study is to describe the organization and development of a data-biobank for cancer research. RESULTS: We have enrolled 3704 patients aged ≥ 18 years diagnosed with cancer, of which 45 with hereditary breast-ovarian cancer (70% participation rate) as of October 24th, 2019. The average age is 63.6 ± 14.2 years and 1892 (51.1%) are female. The following data are collected: clinical and treatment details, comorbidities, lifestyle, radiological and pathological findings, and long-term outcomes. We also collect and store various biomaterials of patients as well as information from quality of life assessments. CONCLUSION: Embedding a data-biobank in clinical care can ensure the collection of high-quality data. Moreover, the inclusion of longitudinal quality of life data allows us to incorporate patients' perspectives and inclusion of imaging data provides an opportunity for analyzing raw imaging data using artificial intelligence (AI) methods, thus adding new dimensions to the collected data.

Validation and Modification of a Prediction Model for Acute Cardiac Events in Patients With Breast Cancer Treated With Radiotherapy Based on Three-Dimensional Dose Distributions to Cardiac Substructures.

Purpose A relationship between mean heart dose (MHD) and acute coronary event (ACE) rate was reported in a study of patients with breast cancer (BC). The main objective of our cohort study was to validate this relationship and investigate if other dose-distribution parameters are better predictors for ACEs than MHD. Patients and Methods The cohort consisted of 910 consecutive female patients with BC treated with radiotherapy (RT) after breast-conserving surgery. The primary end point was cumulative incidence of ACEs within 9 years of follow-up. Both MHD and various dose-distribution parameters of the cardiac substructures were collected from three-dimensional computed tomography planning data. Results The median MHD was 2.37 Gy (range, 0.51 to 15.25 Gy). The median follow-up time was 7.6 years (range, 0.1 to 10.1 years), during which 30 patients experienced an ACE. The cumulative incidence of ACE increased by 16.5% per Gy (95% CI, 0.6 to 35.0; P = .042). Analysis showed that the volume of the left ventricle receiving 5 Gy (LV-V5) was the most important prognostic dose-volume parameter. The most optimal multivariable normal tissue complication probability model for ACEs consisted of LV-V5, age, and weighted ACE risk score per patient (c-statistic, 0.83; 95% CI, 0.75 to 0.91). Conclusion A significant dose-effect relationship was found for ACEs within 9 years after RT. Using MHD, the relative increase per Gy was similar to that reported in the previous study. In addition, LV-V5 seemed to be a better predictor for ACEs than MHD. This study confirms the importance of reducing exposure of the heart to radiation to avoid excess risk of ACEs after radiotherapy for BC.