The clinical manifestations and molecular pathogenesis of radiation fibrosis.

Advances in radiation techniques have enabled the precise delivery of higher doses of radiotherapy to tumours, while sparing surrounding healthy tissues. Consequently, the incidence of radiation toxicities has declined, and will likely continue to improve as radiotherapy further evolves. Nonetheless, ionizing radiation elicits tissue-specific toxicities that gradually develop into radiation-induced fibrosis, a common long-term side-effect of radiotherapy. Radiation fibrosis is characterized by an aberrant wound repair process, which promotes the deposition of extensive scar tissue, clinically manifesting as a loss of elasticity, tissue thickening, and organ-specific functional consequences. In addition to improving the existing technologies and guidelines directing the administration of radiotherapy, understanding the pathogenesis underlying radiation fibrosis is essential for the success of cancer treatments. This review integrates the principles for radiotherapy dosimetry to minimize off-target effects, the tissue-specific clinical manifestations, the key cellular and molecular drivers of radiation fibrosis, and emerging therapeutic opportunities for both prevention and treatment.

Elevation in viral entry genes and innate immunity compromise underlying increased infectivity and severity of COVID-19 in cancer patients.

Multiple studies have reported a doubling in risk of Coronavirus Disease-2019 (COVID-19) among cancer patients. Here, we examine the potential biological rationale behind this recurrent epidemiological observation. By leveraging large-scale genome-wide transcriptional data of normal and malignant tissues from adults and children, we found evidence of increased expression of SARS-CoV-2 viral entry genes in the cancer state, particularly in respiratory, gastrointestinal, and genitourinary tract tissues, with decreased expression in pediatric vs. adult samples. Additionally, by interrogating the temporal effects of radiotherapy on human peripheral blood mononuclear and mucosal cells, we observed important treatment-related alterations in host innate immunity, specifically type I interferon responses. Overall, cancers enhance expression of critical viral entry genes, and innate viral defenses can be dysregulated transiently during radiation treatments. These factors may contribute to the observed increased susceptibility to SARS-CoV-2 entry and severity of COVID-19 in cancer patients.

Development and Validation of a Risk Model for Breast Cancer-Related Lymphedema.

Importance: Approximately 1 in 5 patients with breast cancer who undergo axillary lymph node dissection will develop lymphedema. To appropriately triage and monitor these patients for timely diagnosis and treatment, robust risk models are required. Objective: To evaluate the prognostic value of mammographic breast density in estimating lymphedema severity. Design, Setting, and Participants: This prognostic study collected data from July 16, 2018, to March 3, 2020, from the electronic health records of patients of the Cancer Rehabilitation and Survivorship Program at the Princess Margaret Cancer Centre in Toronto, Ontario, Canada. Participants included women who had completed curative treatment for a first diagnosis of breast cancer and who were referred to the program. Also included were a sample of patients in the general breast oncology population who were receiving follow-up care at the center during the same period but who were not referred to the program. All patients attended follow-up appointments at the Princess Margaret Cancer Centre from January 1, 2016, to May 1, 2018. The cohort was randomly split 2:1 to group patients into a training cohort and a validation cohort. Exposures: Participant demographic and clinical characteristics included age, sex, body mass index (BMI), medical history, cancer characteristics, and cancer treatment. Main Outcomes and Measures: Spearman correlation coefficient between measured and predicted volume of lymphedema was calculated. Area under the curve (AUC) values were generated for predicting the occurrence of at least mild lymphedema (volume, >200 mL) and severe lymphedema (volume, >500 mL) at the time of initial lymphedema diagnosis. Results: A total of 373 female patients (median [interquartile range] age, 52.3 [45.9-60.1] years) were eligible for this analysis. Multivariate linear regression identified 3 patient factors (age, BMI, and mammographic breast density), 1 cancer factor (number of pathological lymph nodes), and 1 treatment factor (axillary lymph node dissection) as independent prognostic variables. In validation testing, Spearman correlation revealed a statistically significant moderate correlation (coefficient, 0.42; 95% CI, 0.26-0.56; P < .001) between measured volume and predicted volume of lymphedema. The AUC values were 0.72 (95% CI, 0.60-0.83) for predicting the occurrence of mild lymphedema and 0.83 (95% CI, 0.74-0.93) for severe lymphedema. Conclusions and Relevance: This prognostic study found that patients with low breast density appeared to be at a higher risk of developing severe lymphedema. The finding suggests that by combining breast density with established risk factors a multivariate linear regression model could be used to predict the development of lymphedema and provide volumetric estimates of lymphedema severity in patients with breast cancer.

Targeting metabolic dysregulation for fibrosis therapy.

Fibrosis is the abnormal deposition of extracellular matrix, which can lead to organ dysfunction, morbidity, and death. The disease burden caused by fibrosis is substantial, and there are currently no therapies that can prevent or reverse fibrosis. Metabolic alterations are increasingly recognized as an important pathogenic process that underlies fibrosis across many organ types. As a result, metabolically targeted therapies could become important strategies for fibrosis reduction. Indeed, some of the pathways targeted by antifibrotic drugs in development - such as the activation of transforming growth factor-ß and the deposition of extracellular matrix - have metabolic implications. This Review summarizes the evidence to date and describes novel opportunities for the discovery and development of drugs for metabolic reprogramming, their associated challenges, and their utility in reducing fibrosis. Fibrotic therapies are potentially relevant to numerous common diseases such as cirrhosis, non-alcoholic steatohepatitis, chronic renal disease, heart failure, diabetes, idiopathic pulmonary fibrosis, and scleroderma.

Radiomic Biomarkers to Refine Risk Models for Distant Metastasis in HPV-related Oropharyngeal Carcinoma.

PURPOSE: Distant metastasis (DM) is the main cause of death for patients with human papillomavirus (HPV)-related oropharyngeal cancers (OPCs); yet, there are few reliable predictors of DM in this disease. The role of quantitative imaging (ie, radiomic) analysis was examined to determine whether there are primary tumor features discernible on imaging studies that are associated with a higher risk of DM developing. METHODS AND MATERIALS: Radiation therapy planning computed tomography scans were retrieved for all nonmetastatic p16-positive OPC patients treated with radiation therapy or chemoradiation therapy at a single institution between 2005 and 2010. Radiomic biomarkers were derived from each gross tumor volume. The biomarkers included 4 representative radiomic features from tumor first-order statistics, shape, texture, and wavelet groups, as well as a combined 4-feature signature. Univariable Cox proportional hazards models for DM risk were identified. The discriminative performance of prognostic univariable and multivariable models was compared using the concordance index (C-index). Subgroup analyses were performed. RESULTS: There were 300 HPV-related OPC patients who were eligible for the analysis. A total of 36 DM events occurred within a median follow-up period of 5 years. On univariable analysis, top results included the 4 representative radiomic features (C-index, 0.670-0.686; P < .001), the radiomic signature (C-index, 0.670; P < .001), tumor stage (C-index, 0.633; P < .001), tumor diameter (C-index, 0.653; P < .001), and tumor volume (C-index, 0.674; P < .001), which demonstrated moderate discrimination of DM risk. Combined clinical-radiomic models yielded significantly improved performance (C-index, 0.701-0.714; P < .05). In subgroup analyses, the radiomic biomarkers consistently stratified patients for DM risk, particularly for those cohorts with greater risks (C-index, 0.663-0.796), such as patients with stage III disease. CONCLUSIONS: Radiomic biomarkers appear to classify DM risk for patients with nonmetastatic HPV-related OPC. Radiomic biomarkers could be used either alone or with other clinical characteristics in the assignment of DM risk in future HPV-related OPC clinical trials.

Mapping genomic and transcriptomic alterations spatially in epithelial cells adjacent to human breast carcinoma.

Almost all genomic studies of breast cancer have focused on well-established tumours because it is technically challenging to study the earliest mutational events occurring in human breast epithelial cells. To address this we created a unique dataset of epithelial samples ductoscopically obtained from ducts leading to breast carcinomas and matched samples from ducts on the opposite side of the nipple. Here, we demonstrate that perturbations in mRNA abundance, with increasing proximity to tumour, cannot be explained by copy number aberrations. Rather, we find a possibility of field cancerization surrounding the primary tumour by constructing a classifier that evaluates where epithelial samples were obtained relative to a tumour (cross-validated micro-averaged AUC = 0.74). We implement a spectral co-clustering algorithm to define biclusters. Relating to over-represented bicluster pathways, we further validate two genes with tissue microarrays and in vitro experiments. We highlight evidence suggesting that bicluster perturbation occurs early in tumour development.