Outcomes of Pediatric Patients with metastatic Ewing sarcoma treated with interval compression

Background: Interval compression (IC), defined as 2 week-long cycles of alternating vincristine/doxorubicin/cyclophosphamide and ifosfamide/etoposide, improves survival for localized Ewing sarcoma. The outcomes of patients with metastatic disease treated with IC are uncertain. Methods: We retrospectively reviewed the charts of pediatric patients with metastatic Ewing sarcoma treated with IC at our center between January-2013 and March-2020. We calculated event-free survival and overall survival and used log rank tests for univariate comparisons. Results: We identified 34 patients aged 2.7–17.1 years (median,11.6 years). Twenty-six patients (76%) had pulmonary metastases, and 14 (41%) had extra-pulmonary metastases in the bone (n = 11), lymph nodes (n = 2), and intraspinal tissue (n = 1). All patients received local control therapy: surgery only (n = 7, 21%), radiotherapy only (n = 18, 53%), or both (n = 9, 26%). The estimated 3-year OS and EFS were 62%±9% and 39%±9%, respectively. Patients with pulmonary only metastasis had a 3-year OS of 88%±8% in comparison to those with extra-pulmonary metastasis of 27%±13% (P=0.0074). Survival did not differ according to age group (> vs < 12 years), metastasis site, or primary tumor site, but 3-year event-free survival significantly differed according to local control therapy (surgery only, 83% ± 15%; combined surgery and radiation, 30% ± 18%; radiation only, 15% ± 10%; P = .048). Conclusion: IC yielded similar outcomes for patients with metastatic Ewing sarcoma to that reported in the literature using other regimens. We suggest including this approach to other blocks of therapy

Metastasis Patterns and Prognosis of Elderly Patients With Esophageal Adenocarcinoma in Stage IVB: A Population-Based Study

BackgroundEsophageal adenocarcinoma (EAC) is the most common kind of esophageal cancer. Age at diagnosis of advanced EAC is greater. Studies about practice patterns for elderly EAC patients with distant metastasis (DM) in stage IVB are limited. This retrospective, population-based study was conducted using data from the Surveillance, Epidemiology, and End Results (SEER) to evaluate 855 elderly EAC patients with DM in stage IVB from 2010 to 2015.Methods855 elderly EAC patients with DM in stage IVB between 2010 and 2015 were included in this study. Univariate and multivariate Cox-regression and Kaplan-Meier analyses were used to assess prognosis. These patients were classified to bone-only, brain-only, lung-only, liver-only, and multiple (patients with two or more organs in metastasis)-site group according to the site of metastasis. Overall survival (OS), cancer-specific survival (CSS), median survival time (MST), and survival rate (SR) were evaluated to analyze the survival outcomes.ResultsThe most common metastasis site was the liver among the single-organ metastasis population, followed by lung, bone, and brain. Compared with the bone-only group, the multiple-site group was associated with worst OS (HR: 1.037, 95% CI: 0.811–1.327, p = 0.770) and CSS (HR: 1.052, 95% CI: 0.816–1.357, p = 0.695). The multiple-site group also had the lowest MST in the population (MST: 2 months in OS and 3 months in CSS) and SR (6-month SR: 27.1% in OS, 29.9% in CSS, 1-year SR: 10.7% in OS, 12.0% in CSS, 3-year SR: 2.5% in OS, 2.8% in CSS). Compared to untreated patients (N) in the total population, other patients who were treated with surgery (S), radiotherapy (R), and chemotherapy (C) are beneficial for the prognosis (OS and CSS: p &lt; 0.001).ConclusionThis population-based study was conducted to ascertain metastasis patterns and survival outcomes of EAC patients with DM in stage IVB. Elderly patients with multiple-site metastasis exhibited the worst OS and CSS among all the populations, and patients with bone-only metastasis had the worst OS and CSS among single-organ metastasis populations. Active treatment is beneficial for elderly EAC patients with DM in stage IVB, especially chemotherapy. This study also shows that more than one third of the patients had not received any therapy.

Nanogenomics and Artificial Intelligence: A Dynamic Duo for the Fight Against Breast Cancer

Application software is utilized to aid in the diagnosis of breast cancer. Yet, recent advances in artificial intelligence (AI) are addressing challenges related to the detection, classification, and monitoring of different types of tumors. AI can apply deep learning algorithms to perform automated analysis on mammographic or histologic examinations. Large volume of data generated by digitalized mammogram or whole-slide images can be interoperated through advanced machine learning. This enables fast evaluation of every tissue patch on an image, resulting in a quicker more sensitivity, and more reproducible diagnoses compared to human performance. On the other hand, cancer cell-exosomes which are extracellular vesicles released by cancer cells into the blood circulation, are being explored as cancer biomarker. Recent studies on cancer-exosome-content revealed that the encapsulated miRNA and other biomolecules are indicative of tumor sub-type, possible metastasis and prognosis. Thus, theoretically, through nanogenomicas, a profile of each breast tumor sub-type, estrogen receptor status, and potential metastasis site can be constructed. Then, a laboratory instrument, fitted with an AI program, can be used to diagnose suspected patients by matching their sera miRNA and biomolecules composition with the available template profiles. In this paper, we discuss the advantages of establishing a nanogenomics-AI-based breast cancer diagnostic approach, compared to the gold standard radiology or histology based approaches that are currently being adapted to AI. Also, we discuss the advantages of building the diagnostic and prognostic biomolecular profiles for breast cancers based on the exosome encapsulated content, rather than the free circulating miRNA and other biomolecules.

Bone-targeted PAMAM nanoparticle to treat bone metastases of lung cancer

Aim: To prepare pH-sensitive nanoparticle composed of alendronate (ALN) and poly(amidoamine) (PAMAM) to treat bone metastases of lung cancer. Methods: The solvent evaporation method was used to prepare docetaxel (DTX)-loaded ALN-PAMAM nanoparticles (DTX@ALN-PAMAM). Results: The in vitro results showed DTX@ALN-PAMAM significantly enhanced the anticancer activity of DTX and inhibited the formation of osteoclasts. DTX@ALN-PAMAM concentrated at bone metastasis site in mice, which resulted in the suppression of bone resorption, pain response and growth of bone metastases. Eventually, the therapeutic effect of DTX on bone metastases of lung cancer was obviously improved. Conclusion: ALN modified PAMAM nanoparticle could be an effective platform for the treatment of bone metastases of lung cancer.