Researchers at the University of California, Santa Cruz, and the University of California, Los Angeles (UCLA) have identified abnormal signaling pathways in metastatic prostate cancer cells that play a crucial role in tumor cell proliferation and in resistance to androgen-deprivation therapy.
Results of the study, “Phosphoproteome Integration Reveals Patient-Specific Networks in Prostate Cancer,” published in the journal Cell, also reveal a new computational approach that analyzes patient-specific data and identifies tailored targets for therapy, helping doctors select the most effective drugs for individual patients.
“It’s like having a blueprint for each tumor. This is our dream for personalized cancer therapy, so we’re not just guessing anymore about which drugs will work but can choose drug targets based on what’s driving that patient’s cancer,” Josh Stuart, the Baskin professor of biomolecular engineering at UC Santa Cruz, director of cancer and stem cell genomics at the university’s Genomics Institute, and a senior corresponding author of the paper, said in a press release.
Identifying the genetic mutations present in cancer cells may improve personalized cancer treatment in the future. But interpreting the data to understand which mutations are actually driving a patient’s tumor remains a challenge.
Researchers integrated data from genome mutations with data assessing which pathways were active in prostate cancer cells. To do that, they examined the phosphorylation status of each protein. Phosphorylation, which consists of the addition of a phosphate group to specific parts of a protein, is a key step in many signaling pathways as it can activate or deactivate specific proteins.
By mapping which proteins had more or less phosphate groups in prostate cancer cells compared to healthy prostate cells, scientists were able to identify specific kinases — the proteins that add the phosphate to other proteins — whose inhibition could potentially decrease cancer cell proliferation.
In fact, many new cancer drugs are kinase inhibitors, meaning that identifying the specific kinases involved in the progression of a patient’s cancer could help doctors choose the appropriate kinase inhibitors.
“Having the phosphoproteomics data in addition to the traditional genomics and transcriptomics enabled us to get a more comprehensive view of aberrant signaling in this disease,” said Evan Paull, who was a grad student in Stuart’s lab at UC Santa Cruz who led the computational analyses. “We developed a method to integrate these multiple large datasets to understand what’s driving the disease in individual patients.”
The researchers have already generated an online tool named pCHIPS that will allow other doctors to insert patient data and receive information about the signaling pathways activated in their cancer cells.
“For now it’s a research tool, but the hope is to have a strategy like this to use in the clinic,” Stuart said. “These mutations in the genome create a lot of havoc in the cell, and trying to interpret the genomic information can be overwhelming. You need the computer to help you make sense of it and find the Achilles heel in the network that you can hit with a drug.”
In addition, the team identified a mechanism through which prostate cancer cells become resistant to androgen deprivation therapies. The therapies, which rely on the fact that prostate cancer cell growth is stimulated by male sex hormones, impair the androgen signaling pathway either by reducing androgen synthesis or by blocking the receptor. However, most cases of prostate cancer eventually become resistant to such therapies.