Biomedical subjects

Enrique Velazquez-Villarreal

Publications and source records attributed to Enrique Velazquez-Villarreal.

4 recordsLinked to original sources

PubMed2025

AI-HOPE: an AI-driven conversational agent for enhanced clinical and genomic data integration in precision medicine research.

MOTIVATION: The growing complexity of clinical cancer research has fueled a surge in demand for automated bioinformatics tools capable of integrating clinical and genomic data to accelerate discovery efforts. RESULTS: We present the Artificial Intelligence Agent for High-Optimization and Precision Medicine (AI-HOPE), an AI-driven system that enables domain experts to conduct integrative data analyses through natural language interactions. Powered by Large Language Models, AI-HOPE interprets user instructions, converts them into executable code, and autonomously analyzes locally stored data. It supports flexible association studies, subset comparisons, clinical prevalence assessments and survival analyses. In addition, AI-HOPE enables global variable scans to identify features significantly associated with a user-defined outcome, making a powerful and intuitive tool for advancing precision medicine research. Importantly, its closed-system design prevents clinical data leakage. To demonstrate its utility, AI-HOPE was applied to The Cancer Genome Atlas data to address two clinical questions. First, it identified significant enrichment of TP53 mutations in late-stage colorectal cancer compared to early-stage cases. Second, it uncovered a strong association between KRAS mutations and poorer progression-free survival in FOLFOX-treated patients. These findings align with established literature and demonstrate AI-HOPE's ability to generate meaningful insights independently, without prior assumptions. By removing programming barriers and simplifying complex analyses, AI-HOPE bridges the gap between data complexity and research needs. With its scalable and adaptable framework, AI-HOPE has the potential to support diverse biomedical research fields, driving innovation and efficiency in translational studies. AVAILABILITY AND IMPLEMENTATION: The AI-HOPE software and demonstration data is available at https://github.com/Velazquez-Villarreal-Lab/AI-HOPE.

Precision Medicine↗

PubMed2025

Pathway-specific genomic alterations in pancreatic cancer across diverse cohorts.

BACKGROUND/OBJECTIVES: Pancreatic cancer (PC) is an aggressive malignancy with rising incidence and poor survival rates. While Hispanic/Latino (H/L) patients have a lower overall incidence compared to Non-Hispanic White (NHW) patients, they are diagnosed at younger ages, often present with more advanced disease, and experience worse survival outcomes. The molecular drivers underlying these disparities remain poorly understood. Key oncogenic pathways, including TP53, WNT, PI3K, TGF-Beta, and RTK/RAS, play crucial roles in tumor progression, therapy resistance, and response to targeted treatments. However, their ethnicity-specific alterations and prognostic implications in PC remain largely unexplored. This study aims to characterize pathway-specific mutations in PC among H/L and NHW patients, assess tumor mutation burden, and identify ethnicity-specific oncogenic drivers using publicly available datasets. The findings may provide critical insights to optimize precision medicine strategies and enhance targeted therapies for underrepresented populations. METHODS: A bioinformatics analysis was performed using publicly available PC datasets to evaluate mutation frequencies in genes associated with the TGF-Beta, RTK/RAS, WNT, PI3K, and TP53 pathways. The study included 4,248 patients, with 407 identified as H/L and 3,841 as NHW. Patients were stratified by ethnicity to assess differences in mutation prevalence. Chi-squared tests were conducted to compare mutation rates between groups, while Kaplan-Meier survival analysis was performed to evaluate overall survival differences based on pathway-specific alterations. RESULTS: Significant differences were observed in the TGF-Beta pathway between H/L and NHW patients. TGF-Beta mutations were less prevalent in H/L patients (18.4% vs. 24.4%, p = 8.6e-3). Additionally, genes related to the TGF-Beta pathway showed significant alterations, with SMAD2 (1.5% vs. 0.4%, p = 6.3e-3) and SMAD4 (15% vs. 19.9%, p = 0.02) exhibiting notable differences. Although RTK/RAS, WNT, PI3K, and TP53 pathway mutations were not statistically significant overall, borderline significance was observed in genes associated with these pathways, including ERBB4 (3.4% vs. 1.8%, p = 0.03), ALK (2.7% vs. 1.1%, p = 0.01), HRAS (1.2% vs. 0.1%, p = 1.3e-4), and RIT1 (0.7% vs. 0.1%, p = 0.03) in the RTK/RAS pathway, as well as CTNNB1 (2.9% vs. 1.3%, p = 0.01) in the WNT pathway. Survival analysis revealed no significant differences in overall survival among H/L patients. However, NHW patients with TP53 pathway alterations exhibited borderline significant differences in survival outcomes.

PI3K pathway↗

PubMed2025

Comparative genomic analysis of key oncogenic pathways in hepatocellular carcinoma among diverse populations.

BACKGROUND/OBJECTIVES: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, with significant racial and ethnic disparities in incidence, tumor biology, and clinical outcomes. Hispanic/Latino (H/L) patients tend to be diagnosed at younger ages and more advanced stages than Non-Hispanic White (NHW) patients, yet the molecular mechanisms underlying these disparities remain poorly understood. Key oncogenic pathways, including RTK/RAS, TGF-Beta, WNT, PI3K, and TP53, play pivotal roles in tumor progression, treatment resistance, and response to targeted therapies. However, ethnicity-specific alterations within these pathways remain largely unexplored. This study aims to compare pathway-specific mutations in HCC between H/L and NHW patients, assess tumor mutation burden, and identify ethnicity-associated oncogenic drivers using publicly available datasets. Findings from this analysis may inform precision medicine strategies for improving early detection and targeted therapies in underrepresented populations. METHODS: We conducted a bioinformatics analysis using publicly available HCC datasets to assess mutation frequencies in RTK/RAS, TGF-Beta, WNT, PI3K, and TP53 pathway genes. The study included 547 patients, consisting of 69 H/L patients and 478 NHW patients. Patients were stratified by ethnicity (H/L vs. NHW) to evaluate differences in mutation prevalence. Chi-squared tests were used to compare mutation frequencies, while Kaplan-Meier survival analysis assessed overall survival differences associated with pathway-specific alterations in both populations. RESULTS: Significant differences were observed in the RTK/RAS pathway related genes, particularly in FGFR4 mutations, which were more prevalent in H/L patients compared to NHW patients (4.3% vs. 0.6%, p = 0.02). Additionally, IGF1R mutations exhibited borderline significance (7.2% vs. 2.9%, p = 0.07). In the PI3K pathway, INPP4B alterations were more frequent in H/L patients than in NHW patients (4.3% vs. 1%, p = 0.06), while in the TGF-Beta pathway, TGFBR2 mutations were more common in H/L patients (2.9% vs. 0.4%, p = 0.07), suggesting potential ethnicity-specific variations. Survival analysis revealed no significant differences in overall survival between H/L and NHW patients, indicating that molecular alterations alone may not fully explain survival disparities and suggesting a role for additional factors such as immune response, environmental exposures, or access to targeted therapies. CONCLUSIONS: This study provides one of the first ethnicity-focused analyses of key oncogenic pathway alterations in HCC, revealing distinct molecular differences between H/L and NHW patients. The findings suggest that RTK/RAS (FGFR4, IGF1R), PI3K (INPP4B), and TGF-Beta (TGFBR2) pathway alterations may play a distinct role in HCC among H/L patients, while their prognostic significance in NHW patients remains unclear. These insights emphasize the importance of incorporating ethnicity-specific molecular profiling into precision medicine approaches to improve early detection, targeted therapies, and clinical outcomes in HCC, particularly for underrepresented populations.

PI3K pathway↗

PubMed2025

Molecular alterations in TP53, WNT, PI3K, TGF-Beta and RTK/RAS pathways in gastric cancer among ethnically heterogeneous cohorts.

BACKGROUND/OBJECTIVES: Gastric cancer (GC) remains a leading cause of cancer-related mortality worldwide, with significant racial and ethnic disparities in incidence, molecular characteristics, and patient outcomes. However, genomic studies focusing on Hispanic/Latino (H/L) populations remain scarce, limiting our understanding of ethnicity-specific molecular alterations. This study aims to characterize pathway-specific mutations in TP53, WNT, PI3K, TGF-Beta and RTK/RAS signaling pathways in GC and compare mutation frequencies between H/L and Non-Hispanic White (NHW) patients. Additionally, we evaluate the impact of these alterations on overall survival using publicly available datasets. METHODS: We conducted a bioinformatics analysis using publicly available GC datasets to assess mutation frequencies in TP53, WNT, PI3K, TGF-Beta and RTK/RAS pathway genes. A total of 800 patients were included in the analysis, comprising 83 H/L patients and 717 NHW patients. Patients were stratified by ethnicity (H/L vs. NHW) to evaluate differences in mutation prevalence. Chi-squared tests were performed to compare mutation rates between groups, and Kaplan-Meier survival analysis was used to assess overall survival differences based on pathway alterations among both H/L and NHW patients. RESULTS: Significant differences were observed in the TP53 pathway and related genes when comparing GC in H/L patients to NHW patients. TP53 mutations were less prevalent in H/L patients (9.6% vs. 19%, p = 0.03). Borderline significant differences were noted in the WNT pathway when comparing GC in H/L patients to NHW GC patients, with WNT alterations more frequent in H/L GC (8.4% vs. 4%, p = 0.08), and APC mutations significantly higher (3.6% vs. 0.8%, p = 0.05). Although alterations in PI3K, TGF-Beta and RTK/RAS pathways were not statistically significant, borderline significance was observed in genes related to these pathways, including EGFR (p = 0.07), FGFR1 (p = 0.05), FGFR2 (p = 0.05), and PTPN11 (p = 0.05) in the PI3K pathway, and SMAD4 (p = 0.08) in the TGF-Beta pathway. Survival analysis revealed no significant differences among H/L patients. However, NHW patients with TP53 and PI3K pathway alterations exhibited significant differences in overall survival, while those without TGF-Beta pathway alterations also showed a significant survival impact. In contrast, WNT pathway alterations were not associated with significant survival differences. These findings suggest that TP53, PI3K, and TGF-Beta pathway disruptions may have distinct prognostic implications in NHW GC patients. CONCLUSIONS: This study provides one of the first ethnicity-focused analyses of TP53, WNT, PI3K, TGF-Beta and RTK/RAS pathway alterations in GC, revealing significant racial/ethnic differences in pathway dysregulation. The findings suggest that TP53 and WNT alterations may play a critical role in GC among H/L patients, while PI3K and TGF-Beta alterations may have greater prognostic significance in NHW patients. These insights emphasize the need for precision medicine approaches that account for genetic heterogeneity and ethnicity-specific pathway alterations to improve cancer care and outcomes for underrepresented populations.

PI3K pathway↗