Biology subjects

Quintanar, O.

Publications and source records attributed to Quintanar, O..

3 recordsLinked to original sources

bioRxiv2023

Novel hepatocellular carcinomas (HCC) Subtype-Specific Biomarkers

IntroductionHepatocellular carcinoma (HCC), the most common form of liver cancer, is a global health concern and a leading cause of cancer-related deaths. HCC accounts for a significant portion of liver cancers and has low survival rates of 5% to 30%, especially for HCC patients with a survival rate of 15%. Early detection is challenging due to the absence of symptoms in the early stages. The complexity and molecular diversity of HCC contribute to its poor prognosis. Understanding its molecular subtypes and mechanisms is crucial for improved management. MethodsThe study utilized publicly available data to investigate the potential diagnostic and prognostic biomarkers for hepatocellular carcinoma (HCC) based on their transcript per million (TPM) expression levels. A dataset of 407 HCC patient profiles was analyzed for survival trends and gene expression patterns. ResultsThrough a comprehensive approach, over 900 potential prognostic candidates were identified. Further analysis narrowed down 647 prognostic and diagnostic candidate biomarkers. The study also explored the role of the CmPn signaling network in HCC, reaffirming that its components could act as prognostic markers. Additionally, the study-utilized machine learning to discover 102 transcription factors (TFs) associated with HCC, from candidate biomarkers. ConclusionsThe findings provide insights into the molecular basis of HCC and offer potential avenues for improved diagnosis, treatment, and patient outcomes. The expanded prognostic biomarker pool aids in pinpointing HCC-specific grading and staging biomarkers, facilitating targeted therapies for improved patient outcomes and survival rates

cancer biology↗

bioRxiv2023

Identification of Cholangiocarcinoma (CCA) Subtype-Specific Biomarkers

Liver cancer ranks sixth globally in diagnoses and second in cancer-related deaths. Cholangiocarcinoma (CCA), a relatively rare cancer originating from bile duct epithelium, constitutes 2% of all cancers, with increasing occurrences in Westerns. Incidence is influenced by inflammation, genetics, risk factors, and regional disparities, with higher rates in the Eastern hemisphere. Diagnostic and prognostic biomarkers are pivotal for effective cancer prevention and management. Recent research explores serum proteins for non-invasive CCA diagnosis and proposes targeted receptor approaches for therapeutics. This study aims to identify these biomarkers via bioinformatics analysis of public datasets, focusing on CCA patient transcriptomes to uncover gene biomarkers linked to age and survival. Pathway analysis reveals functions and pathways associated with these biomarkers. Additionally, the study employs the ESM-TFpredict machine learning model to predict transcription factors (TFs) using protein sequence data. Leveraging publicly available data enhances our understanding of liver cancers molecular profiles and clinical relevance, particularly concerning CCA, This study integrates bioinformatics analysis, transcriptomic exploration, and machine learning to unveil a novel set of potential diagnostic and prognostic biomarkers for CCA.

systems biology↗

bioRxiv2023

Updated Biomarkers for TNBC in African vs. Caucasian American Women

IntroductionBreast cancer, especially triple-negative breast cancer (TNBC), is a significant concern in the US, being the most common cancer among women and the second leading cause of cancer-related deaths. TNBC lacks crucial receptors targeted in other breast cancer types, leading to a poor prognosis and limited treatment options due to its aggressive and heterogeneous nature. SignificanceAfrican American women (AAW) with TNBC face higher mortality rates and more aggressive disease compared to Caucasian American women (CAW). Despite efforts to find biomarkers specific to AAW and CAW with TNBC, limited sample availability and data resources have been obstacles. MethodsIn our study, we examined 237 candidate peptide biomarkers using publicly available data. Resultsidentify 23 unique prognostic biomarkers. These biomarkers accurately assess patient conditions based on race-specific gene expression patterns, holding potential to address racial disparities in TNBC treatment. ConclusionOverall, our research sheds light on how racial genetic profiles influence TNBC prognosis and treatment efficacy. The identified prognostic biomarkers pave the way for future studies addressing TNBC racial disparities and personalized treatment approaches.

genetics↗