Publications by authors named "M Jesiotr"

BACKGROUND This report describes a 63-year-old Polish man presenting with COVID-19 (Coronavirus Disease 2019) pneumonia in early 2020, before vaccines to prevent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection were available. Nine weeks following recovery from the initial infection, he tested positive again for SARS-CoV-2. CASE REPORT Man, age 63, was admitted to the Military Institute of Medicine on March 12, 2020, with body temperature 40°C, a cough, and breathlessness.

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The transcription factor EVI1 plays an oncogenic role in several types of neoplasms by promoting aggressive cancer features. EVI1 contributes to epigenetic regulation and transcriptional control, and its overexpression has been associated with enhanced PI3K-AKT-mTOR signaling in some settings. These observations raise the possibility that EVI1 influences the prognosis and everolimus-based therapy outcome of clear cell renal cell carcinoma (ccRCC).

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Background: The aim of the present study was to search for predictive and prognostic factors in patients with metastatic renal cell carcinoma (mRCC) treated with everolimus among the components of the WNT/β-catenin pathway.

Patients And Methods: In a prospective, single-arm, phase II study, patients with mRCC received everolimus (10 mg/d) in a 30-day cycle. We performed a prospectively planned evaluation of the potential biomarkers of the WNT/β-catenin pathway.

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Inhibitors of the mechanistic target of rapamycin (mTOR) are currently used to treat advanced metastatic breast cancer. However, whether an aggressive phenotype is sustained through adaptation or resistance to mTOR inhibition remains unknown. Here, complementary studies in human tumors, cancer models and cell lines reveal transcriptional reprogramming that supports metastasis in response to mTOR inhibition.

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The fluorescence in situ (FISH) belongs to the most often used molecular cytogenetic techniques, applied in many areas of diagnosis and research. The analysis of FISH images relies on localization and counting the red and green spots in order to determine HER2 status of the breast cancer samples. The algorithm of spot localization presented in the paper is based on 3-D shape analysis of the image objects.

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