Response to chemoradiatiotherapy in squamous cell carcinoma of the esophagus: evaluation of some prognostic factors

Dag Stockeld1, Ursula Falkmer2, Sture Falkmer3, Lars Backman1, Lars Granström1, Jan Fagerberg41Department of Surgery, Danderyd Hospital, Stockholm, Sweden; 2Department of Oncology; 3Department of Pathology, University Hospital, Trondheim, Norway; 4Department of Oncology, Radiumhemmet, Karolinska Hospital, Stockholm, SwedenObjective: To evaluate the predictive values of the expression of factor VIII, CD-34, p53, bcl-2, and DNA ploidy regarding the response to chemoradiation of squamous cell carcinoma of the esophagus.Design: Retrospective analysis of pretreatment biopsies with immunohistochemistry and flow cytometry. The results were correlated to tumor response (complete vs. noncomplete) following chemoradiation with three cycles of 5-FU and cisplatin combined with 40–64 Gy of radiation.Subjects: 44 consecutive patients with squamous cell carcinoma of the esophagus treated with chemoradiation with a curative intent from 1992–2000.Main outcome measures: Treatment response.Results: No correlations were found between the expressions of p53, bcl-2, or DNA ploidy and tumor response to chemoradiation. A positive correlation was found between factor VIII expression and a complete tumor response (p = 0.0357). However the other marker for angiogenesis, CD-34, showed a negative correlation (p = 0.0493). Both markers indicate blood vessel density meaning that, in this study, many vessels indicated a favorable response if measured with factor VIII, but a poor response if measured with CD-34. Conclusion: It is not possible to predict tumor response to our chemoradiation protocol through the analysis of pretreatment expression of p53, bcl-2 or DNA ploidy in biopsy specimens. In spite of significant correlations between complete tumor responses and the expressions of the markers for angiogenesis this significance may be questionable since one of the two markers, factor VIII had a positive and the other, CD-34, a negative correlation to tumor response.Keywords: chemoradiation, response, prognostic factor, apoptosis, p-53, angiogenesis, DNA ploid

Late cutaneous effects of a local potent steroid during adjuvant radiotherapy for breast cancer

Purpose: The aim of this study was to evaluate whether treatment with a local potent corticosteroid during adjuvant external radiotherapy (ERT) of breast cancer is associated with late skin toxicity. Material and methods: Sixty patients (32 treated with potent corticoid cream versus 28 controls treated with moisturizer) who had been included in a randomized study on prophylactic local corticosteroid treatment under adjuvant ERT in 2009 and 2010 were subjected to a follow-up study in 2016.Assessments of skin texture were registered according to the Late Radiation Morbidity Scoring Scheme (RTOG). Dryness, skin colour and skin thickness were objectively measured using non-invasive instruments. The patients were assessed for differences between their treated and untreated breasts. Results: Skin atrophy was not noticed in any of the 60 patients. Objective instrumental measurements did not reveal any significant differences in skin dryness, colour, pigmentation or skin thickness over the average follow-up time of six years. Clinical assessment based on the RTOG scoring system revealed that the odds ratio of having late skin problems in patients treated with moisturizer compared to patients treated with corticosteroid was 3.2 (95% CI: 1.0â10.1).Patients reported minor cosmetic dermatological sequelae. Seven patients developed telangiectasia, which caused cosmetic inconvenience. Conclusion: In this study, prophylactic corticosteroid treatment to ameliorate radiation dermatitis during adjuvant ERT of breast cancer was not associated with an increase in late skin toxicity nor did it result in skin atrophy. This study is limited by its small sample size, and the risk for false positive findings. Keywords: Adjuvant radiotherapy, Breast cancer, Corticosteroids, Radiation dermatitis, Steroid atrophy, Telangiectasi

Predictive biomarkers in radioresistant rectal cancer:A systematic review

Background and aims: The treatment of locally advanced rectal cancer often consists of neoadjuvant chemoradiotherapy followed by surgery. However, approximately 15% of patients show no response to this neoadjuvant chemoradiotherapy. This systematic review aimed to identify biomarkers of innate radioresistant rectal cancer. Method: Through a systematic literature search, 125 papers were included and analyzed using ROBINS-I, a Cochrane risk of bias tool for non-randomized studies of interventions. Both statistically significant and nonsignificant biomarkers were identified. Biomarkers mentioned more than once in the results or biomarkers with a low or moderate risk of bias were included as the final results. Results: Thirteen unique biomarkers, three genetic signatures, one specific pathway, and two combinations of two or four biomarkers were identified. In particular, the connection between HMGCS2, COASY, and PI3K-pathway seems promising. Future scientific research should focus on further validating these genetic resistance markers

Dynamic Risk Prediction of 30-Day Mortality in Patients With Advanced Lung Cancer:Comparing Five Machine Learning Approaches

International audiencePURPOSE Administering systemic anticancer treatment (SACT) to patients near death can negatively affect their health-related quality of life. Late SACT administrations should be avoided in these cases. Machine learning techniques could be used to build decision support tools leveraging registry data for clinicians to limit late SACT administration. MATERIALS AND METHODS Patients with advanced lung cancer who were treated at the Department of Oncology, Aalborg University Hospital and died between 2010 and 2019 were included (N = 2,368). Diagnoses, treatments, biochemical data, and histopathologic results were used to train predictive models of 30-day mortality using logistic regression with elastic net penalty, random forest, gradient tree boosting, multilayer perceptron, and long short-term memory network. The importance of the variables and the clinical utility of the models were evaluated. RESULTS The random forest and gradient tree boosting models outperformed other models, whereas the artificial neural network–based models underperformed. Adding summary variables had a modest effect on performance with an increase in average precision from 0.500 to 0.505 and from 0.498 to 0.509 for the gradient tree boosting and random forest models, respectively. Biochemical results alone contained most of the information with a limited degradation of the performances when fitting models with only these variables. The utility analysis showed that by applying a simple threshold to the predicted risk of 30-day mortality, 40% of late SACT administrations could have been prevented at the cost of 2% of patients stopping their treatment 90 days before death. CONCLUSION This study demonstrates the potential of a decision support tool to limit late SACT administration in patients with cancer. Further work is warranted to refine the model, build an easy-to-use prototype, and conduct a prospective validation study

Fractional exhaled nitric oxide as a potential biomarker for radiation pneumonitis in patients with non-small cell lung cancer:A pilot study

Introduction The aim of the study was to investigate repetitive fractional exhaled nitric oxide (FeNO) measurements during high-dose radiation therapy (HDRT) and to evaluate the use of FeNO to predict symptomatic radiation pneumonitis (RP) in patients being treated for non-small cell lung cancer (NSCLC). Materials and methods A total of 50 patients with NSCLC referred for HDRT were enrolled. FeNO was measured at baseline, weekly during HDRT, one month- and every third month after HDRT for a one-year follow-up period. The mean FeNO(visit 0-6) was calculated using the arithmetic mean of the baseline and weekly measurements during HDRT. Patients with grade ≥ 2 of RP according to the Common Terminology Criteria for Adverse Events (CTCAE) were considered symptomatic. Results A total of 42 patients completed HDRT and weekly FeNO measurements. Grade ≥ 2 of RP was diagnosed in 24 (57%) patients. The mean FeNO(visit 0-6) ± standard deviation in patients with and without RP was 15.0 ± 7.1 ppb (95%CI: 12.0–18.0) and 10.3 ± 3.4 ppb (95%CI: 8.6–11.9) respectively with significant differences between the groups (p = 0.0169, 95%CI: 2.3–2.6). The leave-one-out cross-validated cut-off value of the mean FeNO(visit 0-6) ≥ 14.8 ppb was predictive of grade ≥ 2 RP with a specificity of 71% and a positive predictive value of 78%. Conclusions The mean FeNO(visit 0-6) in patients with symptomatic RP after HDRT for NSCLC was significantly higher than in patients without RP and may serve as a potential biomarker for RP