Undifferentiated pleomorphic sarcoma is a very rare and aggressive type of primary cardiac tumors. Most cardiac sarcomas result in rapid growth and quick death. According to different sources the median survival is typically 6 to 12 months. We are presenting a case of primary cardiac sarcoma with 26 months disease free survival following cytoreductive surgery and chemotherapy. A 48-year-old woman with progressing symptoms of dyspnea and palpitations for over 2 months was referred to a cardiologist. With the help of echocardiography and cardiovascular magnetic resonance cardiac sarcoma was suspected. Open biopsy and cytoreductive surgery were performed, complete resection of the tumor was not possible. Histology revealed undifferentiated pleomorphic sarcoma. Seven cycles of chemotherapy with Doxorubicine and Ifosfamide were completed. Cardiovascular magnetic resonance revealed a complete response – only signs of fibrosis without any signs of tumor were visible. Follow ups with echocardiography, cardiovascular magnetic resonance and chest, abdomen and pelvic computed tomography is performed every 3 months. Twenty-six months from initial diagnosis the patient is still free of recurrence of tumor with no compromises of the quality of life. Standard chemotherapy together with cytoreductive surgery can have a complete response effect in undifferentiated pleomorphic sarcoma with unusual long-term survival.

Background. The most important anthracycline side effect is cardiotoxicity, resulting in congestive heart failure (HF). Early detection of cardiac dysfunction and appropriate treatment can improve outcomes and reduce the progression of HF. The aim of our study was to evaluate changes in clinical data, echocardiographic parameters, and NT-proBNP, as well as their associations with early anthracycline-induced cardiotoxicity (AIC) in patients treated with anthracycline-based chemotherapy. Methods and Materials. Patients with breast cancer were prospectively assessed with echocardiography, as well as NT-proBNP testing at baseline, (T0), after two cycles (T1) and four cycles (T2) of chemotherapy. AIC was defined as a new decrease in the LVEF of 10 percentage points, to a value below the lower limit of normal. Results. We evaluated 85 patients aged 54.5 ± 9.3 years. After a cumulative dose of 237.9 mg/m² of doxorubicin, 22 patients (25.9%) met the criteria of AIC after chemotherapy. Patients who subsequently progressed to cardiotoxicity had demonstrated a significantly larger impairment in LV systolic function compared to those who did not develop cardiotoxicity (LVEF: 54.0 ± 1.6% vs. 57.1 ± 1.4% at T1, p < 0.001, and 49.9 ± 2.1% vs. 55.8 ± 1.6% at T2, p < 0.001; GLS: −17.8 ± 0.4% vs. −19.3 ± 0.9% at T1, p < 0.001, and −16.5 ± 11.1% vs. −18.5 ± 0.9% at T2, p < 0.001, respectively). The levels of NT-proBNP increased significantly from 94.8 ± 43.8 ng/L to 154.1 ± 75.6 ng/L, p < 0.001. A relative decrease in GLS ≤ −18.0% (sensitivity: 72.73%; specificity: 92.06%; AUC, 0.94; p < 0.001) and a relative increase in NT-proBNP > 125 ng/L (sensitivity: 90.0%; specificity: 56.9%; AUC, 0.78; p < 0.001) from baseline to T1 predicted subsequent LV cardiotoxicity at T2. Conclusions. Decrease in GLS and elevation in NT-proBNP were significantly associated with AIC, and these could potentially be used to predict subsequent declines in LVEF with anthracycline-based chemotherapy.

Background. Cardiac side effects associated with anthracycline-based treatment may seriously compromise the prognosis of patients with breast cancer (BC). Evidence shows that genes that operate in drug metabolism can influence the risk of anthracycline-induced cardiotoxicity (AIC). ATP-binding cassette (ABC) transporters could serve as one of the potential biomarkers for AIC risk stratification. We aimed to determine the link between single-nucleotide polymorphisms (SNPs) in several ABC genes (ABCB1 rs1045642, ABCC1 rs4148350, ABCC1 rs3743527) and cardiotoxicity. Methods. The study included 71 patients with BC, who were treated with doxorubicin-based chemotherapy. Two-dimensional echocardiography and speckle-tracking echocardiography were performed. AIC was defined as a new decrease of 10 percentage points in the left ventricular ejection fraction (LVEF). SNPs in ABCB1 and ABCC1 genes were evaluated using real-time PCR. Results. After a cumulative dose of 236.70 mg/m² of doxorubicin, 28.2% patients met the criteria of AIC. Patients who developed AIC had a larger impairment in left ventricular systolic function compared to those who did not develop AIC (LVEF: 50.20 ± 2.38% vs. 55.41 ± 1.13%, p < 0.001; global longitudinal strain: −17.03 ± 0.52% vs. −18.40 ± 0.88%, p < 0.001). The ABCC1 rs4148350 TG genotype was associated with higher rates of cardiotoxicity (TG vs. GG OR = 8.000, 95% CI = 1.405–45.547, p = 0.019). Conclusions. The study showed that ABCC1 rs4148350 is associated with AIC and could be a potential biomarker to assess the risk of treatment side effects in patients with BC.

Background: Timely recognition of cancer progression and treatment complications is important for treatment guidance. Digital phenotyping is a promising method for precise and remote monitoring of patients in their natural environments by using passively generated data from sensors of personal wearable devices. Further studies are needed to better understand the potential clinical benefits of digital phenotyping approaches to optimize care of patients with cancer. Objective: We aim to evaluate whether passively generated data from smartphone sensors are feasible for remote monitoring of patients with cancer to predict their disease trajectories and patient-centered health outcomes. Methods: We will recruit 200 patients undergoing treatment for cancer. Patients will be followed up for 6 months. Passively generated data by sensors of personal smartphone devices (eg, accelerometer, gyroscope, GPS) will be continuously collected using the developed LAIMA smartphone app during follow-up. We will evaluate (1) mobility data by using an accelerometer (mean time of active period, mean time of exertional physical activity, distance covered per day, duration of inactive period), GPS (places of interest visited daily, hospital visits), and gyroscope sensors and (2) sociability indices (frequency of duration of phone calls, frequency and length of text messages, and internet browsing time). Every 2 weeks, patients will be asked to complete questionnaires pertaining to quality of life (European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire [EORTC QLQ-C30]), depression symptoms (Patient Health Questionnaire-9 [PHQ-9]), and anxiety symptoms (General Anxiety Disorder-7 [GAD-7]) that will be deployed via the LAIMA app. Clinic visits will take place at 1-3 months and 3-6 months of the study. Patients will be evaluated for disease progression, cancer and treatment complications, and functional status (Eastern Cooperative Oncology Group) by the study oncologist and will complete the questionnaire for evaluating quality of life (EORTC QLQ-C30), depression symptoms (PHQ-9), and anxiety symptoms (GAD-7). We will examine the associations among digital, clinical, and patient-reported health outcomes to develop prediction models with clinically meaningful outcomes. Results: As of July 2023, we have reached the planned recruitment target, and patients are undergoing follow-up. Data collection is expected to be completed by September 2023. The final results should be available within 6 months after study completion. Conclusions: This study will provide in-depth insight into temporally and spatially precise trajectories of patients with cancer that will provide a novel digital health approach and will inform the design of future interventional clinical trials in oncology. Our findings will allow a better understanding of the potential clinical value of passively generated smartphone sensor data (digital phenotyping) for continuous and real-time monitoring of patients with cancer for treatment side effects, cancer complications, functional status, and patient-reported outcomes as well as prediction of disease progression or trajectories. International Registered Report Identifier (IRRID): PRR1-10.2196/49096