Radiotherapy and internal radioisotope therapy (brachytherapy) induce tumor cell death through different molecular signaling pathways. However, these therapies in cancer patients are constrained by dose-related adverse effects and local discomfort due to the prolonged exposure to the surrounding tissues. Technological advancements in nanotechnology have resulted in synthesis of high atomic elements such as nanomaterials, which can be used as radiosensitizers due to their photoelectric characteristics. The aim of this review is to elucidate the effects of novel nanomaterials in the field of radiation oncology to ameliorate dose-related toxicity through the application of ideal nanoparticle-based radiosensitizers such as Au (gold), Bi (bismuth), and Lu (Lutetium-177) for enhancing cytotoxic effects of radiotherapy via the high-Z effect. In addition, we discuss the role of nanoparticle-enhanced radiotherapy in alleviating tumor hypoxia through the nanodelivery of genes/drugs and other functional anticancer molecules. The implications of engineered nanoparticles in preclinical and clinical studies still need to be studied in order to explore potential mechanisms for radiosensitization by minimizing tumor hypoxia, operational/logistic complications and by overcoming tumor heterogeneity in radiotherapy/brachytherapy.

Immune checkpoint inhibitors (ICIs) have dramatically enhanced the treatment outcomes for diverse malignancies. Yet, only 15–60% of patients respond significantly. Therefore, accurate responder identification and timely ICI administration are critical issues in tumor ICI therapy. Recent rapid developments at the intersection of oncology, immunology, biology, and computer science have provided an abundance of predictive biomarkers for ICI efficacy. These biomarkers can be invasive or non-invasive, depending on the specific sample collection method. Compared with invasive markers, a host of non-invasive markers have been confirmed to have superior availability and accuracy in ICI efficacy prediction. Considering the outstanding advantages of dynamic monitoring of the immunotherapy response and the potential for widespread clinical application, we review the recent research in this field with the aim of contributing to the identification of patients who may derive the greatest benefit from ICI therapy.

Background Studies are needed to assess risk factors pertinent to the incidence of secondary malignancies among childhood and adolescent lymphoma survivors. We aimed to identify risk factors pertinent to the incidence of secondary malignancies and subsequently establish a clinically practical predictive nomogram. Methods A total of 5561 patients who were diagnosed with primary lymphoma below the age of 20 years between 1975 and 2013 and survived for at least 5 years were identified. Standardized incidence ratio (SIR) and excess risk (ER) analysis were performed by sex, age, and year when primary lymphoma was diagnosed, sites and types of primary lymphoma, and therapy strategies. Univariable and multivariable logistic regression were used to identify independent risk factors for adolescent and childhood lymphoma-related secondary malignancies. Based on 5 factors (age, time from lymphoma diagnosis, gender, lymphoma type, and therapy), a nomogram for predicting the risk of a secondary malignancy for patients with childhood and adolescent primary lymphoma was established. Results Among 5561 lymphoma survivors, 424 developed a secondary malignancy. Females (SIR = 5.34, 95% CI, 4.73-5.99; ER = 50.58) exhibited a higher SIR and ER than males (SIR = 3.28, 95% CI, 2.76-3.87; ER = 15.53). Blacks were at a higher risk than Caucasians or others. Nodular lymphocyte-predominant Hodgkin lymphoma survivors exhibited typically high SIR (13.13, 95% CI, 6-24.92) and ER (54.79) among all lymphoma classifications. Lymphoma survivors who underwent radiotherapy, whether they received chemotherapy or not, had typically higher SIR and ER. Among all types of secondary malignancies, “bone and joint neoplasms” (SIR = 11.07, 95% CI, 5.52-19.81) and “soft tissue neoplasms” (SIR = 12.27, 95% CI, 7.59-18.76) presented significantly high SIR whereas “breast cancer” and “endocrine cancer” associated with higher ER. The median diagnosis age of secondary malignancies was 36 years old, and the median time interval between the diagnosis of two malignancies was 23 years. A nomogram was constructed to predict the risk of secondary malignancies in patients diagnosed with primary lymphoma before 20 years of age. After internal validation, the AUC and C-index of the nomogram are 0.804 and 0.804, respectively. Conclusion and Relevance The established nomogram provides a convenient and reliable tool for predicting the risk of a secondary malignancy among childhood and adolescent lymphoma survivors, concluding significant concern for lymphoma survivors with high-risk estimates.

Objective: Primary pulmonary sarcoma (PPS) is very rare in terms of incidence, henceforth, the clinical evidence pertinent to the prognosis of PPS is limited. The aim of this study was to construct a nomogram for evaluating the overall survival (OS) of patients diagnosed with PPS based on the stage, lymph node dissection, tumor size and degree of differentiation, and therapies. Methods: A total of 515 patients diagnosed with PPS during the period of 1998 to 2015 were obtained from the surveillance, epidemiology, and end results database and randomly segregated into ‘training group’ and ‘validation group’ with a ratio of 7:3. Regression analysis was executed for the training group to obtain the independent factors influencing prognosis of PPS patients. A nomogram was constructed as per the results obtained through multivariate Cox regression analysis subsequently validated using C index, receiver operating characteristic (ROC) curve, and calibration curves. Results: Age, tumor size, histology type, lymph node surgery, summary stage and differentiation grade were independent factors affecting the prognosis. C index was 0.775 and 0.737 for both training group, and validation group, respectively. Areas under the ROC curve of 1-year, 3-year, and 5-year OS were 87.6 (95% CI: 83.8-91.3), 90.1 (95% CI: 86.2-94.0) and 90.6 (95% CI: 85.8-95.4), respectively, in training group. Area under the curve values of 1-year, 3-year, and 5-year OS in the validation group were 83.1 (95% CI: 75.8-90.5), 82.9 (95% CI: 73.2-92.7) and 87.0 (95% CI: 75.9-98.1), respectively. Based on the nomogram, patients were segregated into low-risk group and high-risk group (degree of risk: cutoff score 193). OS of low-risk group was significantly higher when compared to high-risk group ( P < .001) in the training group and validation group. Radiotherapy was a risk factor for the low-risk group and adjuvant chemotherapy has not exhibited influence on OS pertinent to low-risk group. However, adjuvant radiotherapy or chemotherapy both significantly improved the prognosis of PPS patients ( P < .001) in the high-risk group. Conclusion: Constructed nomogram could have a strong predictive ability with higher accuracy for the prognosis of patients with PPS. Patients at low risk could not benefit from adjuvant radiotherapy or chemotherapy, while the prognosis clearly improved in the high-risk populations treated with either radiotherapy or chemotherapy.