Viviana Bazan

ORCID: 0000-0003-0939-255X
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About
Contact & Profiles
Research Areas
  • Cancer Genomics and Diagnostics
  • Lung Cancer Treatments and Mutations
  • BRCA gene mutations in cancer
  • Genetic factors in colorectal cancer
  • Colorectal Cancer Treatments and Studies
  • Cancer Immunotherapy and Biomarkers
  • MicroRNA in disease regulation
  • Gastric Cancer Management and Outcomes
  • Cancer-related Molecular Pathways
  • Cancer-related molecular mechanisms research
  • Nutrition, Genetics, and Disease
  • Lung Cancer Research Studies
  • Gastrointestinal Tumor Research and Treatment
  • Cholangiocarcinoma and Gallbladder Cancer Studies
  • Pancreatic and Hepatic Oncology Research
  • DNA Repair Mechanisms
  • Circular RNAs in diseases
  • RNA modifications and cancer
  • PARP inhibition in cancer therapy
  • Renal cell carcinoma treatment
  • Sarcoma Diagnosis and Treatment
  • Head and Neck Cancer Studies
  • Cancer Treatment and Pharmacology
  • Genomic variations and chromosomal abnormalities
  • Immunotherapy and Immune Responses

University of Palermo
2016-2025

Azienda Ospedaliera Universitaria Policlinico "Paolo Giaccone" di Palermo
1994-2023

Temple University
2009-2023

University of Palermo
2001-2018

Clinica Luganese Moncucco
2000-2013

Weatherford College
2012-2013

Sbarro Health Research Organization
2009

Hôpital Tenon
2005

Sorbonne Université
2005

The University of Western Australia
2005

Researchers worldwide with information about the Kirsten ras (Ki-ras) tumour genotype and outcome of patients colorectal cancer were invited to provide that data in a schematized format for inclusion collaborative database called RASCAL (The in-colorectal-cancer group). Our results from 2721 such have been presented previously first time any common cancer, showed conclusively different gene mutations impacts on outcome, even when occur at same site genome. To explore effect Ki-ras stages...

10.1054/bjoc.2001.1964 article EN cc-by-nc-sa British Journal of Cancer 2001-08-01

MicroRNAs (miRNAs) are small non-coding RNAs that regulate the expression of different genes, including genes involved in cancer progression. A functional link between hypoxia, a key feature tumor microenvironment, and miRNA has been documented. We investigated whether how miR-20b can vascular endothelial growth factor (VEGF) MCF-7 breast cells under normoxic hypoxia-mimicking conditions (CoCl(2) exposure). Using immunoblotting, ELISA, quantitative real-time PCR, we demonstrated decreased...

10.1002/jcp.22126 article EN Journal of Cellular Physiology 2010-03-15

// Francesco Passiglia 1, * , Giuseppe Bronte Viviana Bazan Clara Natoli 2 Sergio Rizzo 1 Antonio Galvano Angela Listì Cicero Christian Rolfo 3 Daniele Santini 4 Russo Section of Medical Oncology, Department Surgical, Oncological and Oral Sciences, University Palermo, Italy Medical, Biotechnological "G. D'Annunzio", Chieti, Phase I- Early Clinical Trials Unit, Oncology Multidisciplinary Center Antwerp (MOCA), Hospital, Edegem, Belgium Department, Campus Biomedico, Rome, These authors have...

10.18632/oncotarget.7582 article EN Oncotarget 2016-02-22

Despite a proportion of renal cancer patients can experiment marked and durable responses to immune-checkpoint inhibitors, the treatment efficacy is widely variable identifying patient who will benefit from immunotherapy remains an issue. We performed prospective study investigate if soluble forms immune-checkpoints PD-1 (sPD-1), PD-L1 (sPD-L1), pan-BTN3As, BTN3A1, BTN2A1, could be candidate predict response blockade therapy. evaluated plasma levels in learning cohort metastatic clear cell...

10.1080/2162402x.2020.1832348 article EN cc-by-nc OncoImmunology 2020-01-01

Hereditary breast cancer (BC), ovarian (OC), and pancreatic (PC) are the major BRCA-associated tumours. However, some BRCA1/2-wild-type (wt) patients with a strong personal and/or family history of need further genetic testing through multi-gene panel containing other high- moderate-risk susceptibility genes.

10.1016/j.esmoop.2021.100235 article EN cc-by-nc-nd ESMO Open 2021-08-01

Metastatic colorectal cancer (mCRC) is a severe condition with high rates of illness and death. Current treatments are limited not always effective because the responds differently to drugs in different patients. This research aims use artificial intelligence (AI) improve treatment by predicting which therapies will work best for individual By analyzing large sets patient data using machine learning, we hope create model that can identify patients respond chemotherapy, either alone or...

10.3390/life15020320 article EN cc-by Life 2025-02-19
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