Connectivity mapping-based identification of pharmacological inhibitor targeting HDAC6 in aggressive pancreatic ductal adenocarcinoma.
Pranita AtriAshu ShahGopalakrishnan NatarajanSatyanarayana RachaganiSanchita RauthKoelina GangulyJoseph CarmichealDario GhersiJesse L CoxLynette M SmithManeesh JainSushil KumarMoorthy Palanimuthu PonnusamySatyanarayana RachaganiSurinder K BatraPublished in: NPJ precision oncology (2024)
Pancreatic ductal adenocarcinoma (PDAC) remains highly lethal due to limited therapeutic options and expensive/burdensome drug discovery processes. Utilizing genomic-data-driven Connectivity Mapping (CMAP) to identify a drug closer to real-world PC targeting may improve pancreatic cancer (PC) patient outcomes. Initially, we mapped CMAP data to gene expression from 106 PC patients, identifying nine negatively connected drugs. These drugs were further narrowed down using a similar analysis for PC cell lines, human tumoroids, and patient-derived xenografts datasets, where ISOX emerged as the most potent agent to target PC. We used human and mouse syngeneic PC cells, human and mouse tumoroids, and in vivo mice to assess the ability of ISOX alone and in combination with 5FU to inhibit tumor growth. Global transcriptomic and pathway analysis of the ISOX-LINCS signature identified HDAC 6/cMyc as the target axis for ISOX. Specifically, we discovered that genetic and pharmacological targeting of HDAC 6 affected non-histone protein cMyc acetylation, leading to cMyc instability, thereby disrupting PC growth and metastasis by affecting cancer stemness. Finally, Kras G12D harboring tumoroids and mice responded effectively against ISOX and 5FU treatment by enhancing survival and controlling metastasis incidence. Overall, our data validate ISOX as a new drug to treat advanced PC patients without toxicity to normal cells. Our study supports the clinical utility of ISOX along with 5FU in future PC clinical trials.
Keyphrases
- endothelial cells
- gene expression
- end stage renal disease
- clinical trial
- ejection fraction
- newly diagnosed
- chronic kidney disease
- prognostic factors
- dna methylation
- induced pluripotent stem cells
- stem cells
- type diabetes
- emergency department
- high resolution
- randomized controlled trial
- multiple sclerosis
- epithelial mesenchymal transition
- electronic health record
- machine learning
- white matter
- resting state
- rna seq
- single cell
- cell death
- induced apoptosis
- copy number
- drug delivery
- artificial intelligence
- cell proliferation
- mass spectrometry
- adipose tissue
- oxidative stress
- lymph node metastasis
- binding protein
- papillary thyroid
- phase ii