In addition to standard bioinformatics analyses, such as NGS data analysis, the core emphasizes in-depth bioinformatics support to enhance the research and strengthen the grant applications for our investigators.
Our teams use the same standard of operating procedure (SOP) by sharing the identical pipelines and tools for NGS data analysis that fits the NIH requirement about the reproducibility. We also promote interactions between investigators from both cancer centers and core bioinformaticians so that researchers from either Indiana University or Purdue University can contact staff at either campus. That means researchers can take advantage of any core personnel’s expertise specific to their own projects.
Cancer Bioinformatics has been working with the Center for Computational Biology and Bioinformatics (CCBB) and other IU shared facilities. We offer in-depth collaborative level bioinformatics services for our cancer researchers on experimental designs, data collection, processing, and diverse analyses.
We have extensive experience in diverse omics data analyses. We can process most NGS data at both bulk and single cell levels, such as RNA-seq, single cell RNA-seq, ATAC-seq, single cell ATAC-seq, 10X single cell Multiome (ATAC + Gene expression), ChIP-seq, CUT&RUN, DNA methylation data and Whole Genome/Exome Sequencing, with comprehensive downstream analysis, including biological functions and molecular pathways.
We conduct project-oriented, more advanced comprehensive bioinformatics analyses in which we would customize or even develop novel bioinformatics approaches according to special demands and experiment designs from researchers.
In addition, we can assist with data mining, learning, integrating, and visualizing large public domain datasets from projects such as TCGA, CCLE, and TARGET to complement data from our cancer researchers.
In addition to fundamental research support, the core also assists with translational studies, from modeling to predict the success of treatment in individual patients to the development of drugs and treatments specific to cancer.
For example, we worked with Dr. Mark Kelley and his team to integrate proteomics and transcriptome data from his Phase I clinical trial on the drug APX3330. We were able to identify in patient tumor samples from the trial effects of the drug on the target protein, APE1, validating the drug-target interaction and pharmacodynamics. We had assisted Dr. Kelley’s team on similar preclinical studies, which allowed us to translate those preclinical findings to clinical data.
In addition, we work with the Data Science and Informatics Program on the IU Grand Challenge Precision Health Initiative. The core provides expert support on genomics analysis, integration of genomic data with clinical data to inform novel, testable hypotheses from the cancer precision medicine clinic to the laboratory bench for further innovation.
Working with researchers at the two cancer centers, we have co-authored nearly 100 peer-reviewed papers with other collaborators, half of which were published in high-impact factor journals, including Nature Nanotechnology, Nature Biomedical Engineering, Science Immunology, Journal of Clinical Investigation, Nature Communications, Leukemia, Journal of Thoracic Oncology, Clinical Cancer Research, PNAS, and Cancer Research.
