Expanded patient-derived models point toward new treatment paths
Cancer researchers have been using patient-derived tumor cell lines for decades. The familiar practice has expanded to patient-derived xenografts (PDX), patient-derived organoids (PDO), and humanized mice.
“The histomorphology of organoids developed from patient-derived xenografts bears an uncanny resemblance between the tumor and what is recreated in the culture dish,” said Senthil K. Muthuswamy, PhD, Beth Israel Deaconess Medical Center. “We have conditions that are quite reflective of the phenotypic traits of the patient tumor in a culture dish.”
Muthuswamy moderated a Forum exploring the expanding boundaries of Patient-Derived Models for Cancer on Tuesday, April 13. Registrants can watch a replay of the session anytime through June 21, 2021.
Researchers are using novel platforms to characterize adaptive responses that allow tumors to escape treatment and identify novel clinical targets.
Clinicians have long recognized that no cancer treatment is 100 percent effective. What has not been clear is how some tumor cells escape treatment. PDX models suggest that tumor cells use various adaptive responses to achieve drug-tolerance and continue to progress.
Tumors show different adaptive responses depending on tumor type and the initial drug treatment, said Joan S. Brugge, PhD, FAACR, Ludwig Center and Harvard Medical School.
“Cells in certain contexts are able to undergo remodeling,” she said. “We just have to get rid of those remodeled cells.”
Early-stage clinical trials have used PDX to track adaptive response in real time, she said, and adapt drug treatment to keep up with the changes in tumor cells. But adaptive drug treatment is not practical for broad clinical use.
Translational research and proof-of-concept trials are using PDO models to identify tumor-specific biomarkers and targetable adaptive responses. The next step is to optimize multi-agent treatment regimens, then confirm safety and clinical activity using the patient’s PDX for testing.
“The goal is a tumor-specific set of biomolecules that predict more effective tumor killing,” Brugge said. “Clinical trials are already underway.”
Similar approaches are underway using humanized mice to elucidate interactions between cancer and immune system—and design more effective therapeutic interventions.
Mouse models are widely used in cancer research but are a challenge in melanoma because there are fewer pathways shared with human disease. Humanized hNSG-SGMS mice show the same type of macroscopic metastases to liver, spleen, and other organs as human melanoma patients.
“We know from The Cancer Genome Atlas cohort that the KIT+ (CD117) transcriptome is correlated with survival in melanoma patients,” said Karolina Palucka, MD, PhD, The Jackson Laboratory for Genomic Medicine. “High KIT score is associated with shorter survival, low KIT score with longer survival.”
The same holds true for hNSG-SGMS mice, she said. Transplanting human KIT+ myeloid cells into hNSG-SGMS mice with human melanoma tumors facilitates metastatic colonization of distant organs by melanoma.
“This represents a novel candidate biomarker and a novel therapeutic opportunity for metastatic melanoma,” she said. “We are similarly using humanized mice to better understand the immunology of triple-negative breast cancer. There is a strong potential for new biologies in this model. We are moving to CRISPR-based screens with a more advanced model.”
These new models are being developed as long-standing questions about the reliability and accuracy of familiar pancreatic ductal adenocarcinoma (PDAC) cell lines and immortalized control cell lines are being answered.
Nearly all PDAC research labs use PANC-1 and MiaPaCa-3 ATT cell lines, said Anirban Maitra, MBBS, Sheikh Ahmed Center for Pancreatic Cancer Research Center, The University of Texas MD Anderson Cancer Center.
Users assume that these lines have stable genomic and transcriptomic clonal architecture over time. Users also assume that these cells lines retain fidelity to the normal control parameters for HPDE and HPNE. Single-cell genomic and transcriptomic analysis of widely used PDAC cell lines and non-transformed control cells suggest otherwise.
Single-cell RNA sequencing did confirm broad differentiation patterns in different pancreatic cell lines as expected, Maitra said. And single-cell copy number analysis established subclonal heterogeneity of PDAC lines.
“The surprise was finding gene loses and amplifications in commonly used immortalized pancreatic control lines,” he continued. “HPDE had both losses and amplifications at chromosome 22 while HPNE showed amplification at chromosome 17.”
There is also notable transcriptomic heterogeneity in MiaPaca-2 cells lines depending on the custodial source.
And growing conditions matter. There is identifiable transcriptomic divergence between Panc-1 cells grown in 2D versus 3D cultures that is driven by differences in chromatin accessibility.
“None of these are entirely unexpected,” Maitra said. “The inadvertent impact on the rigor and reproducibility of research in terms of establishing cell line identity remains uncertain but is a matter of concern for all of us.”