NEW YORK (GenomeWeb) – A group of researchers led by the University of Pennsylvania and the University of California San Francisco has identified treatment-emergent mutations that occur in patients with acute myeloid leukemia (AML).
Using Mission Bio's Tapestri single-cell sequencing sample prep and analysis platform, the team tracked the evolution of AML clonal mutations in response to targeted drug treatment.
The researchers aimed to characterize the clonal evolution of AML by identifying multiple resistant clones missed by standard sequencing methods.
UPenn associate medical professor Alexander Perl explained that for several years, clinicians had prescribed a drug called quizartinib for patients with AML. However, the inhibitor had a very short duration of response, limited by development of on-target resistance from fms-like tyrosine kinase 3 (FLT3) mutations.
"Until [researchers] developed drugs that were effective to naturally occurring and secondary mutations after therapy, we worried that we wouldn't get potent or sustained target inhibition in patients," Perl explained. "Enter gilteritinib, recently approved in a phase 3 clinical trial [as] a type 1 FLT3 inhibitor that can inhibit kinase mutations in both their active or inactive conformation."
In order to track cancer growth in response to therapy, researchers have often relied on bulk next-generation sequencing methods, which Perl noted rely on sample averages and can miss genetic factors driving the cancer.
In a study published earlier this month in Cancer Discovery, Perl and his team analyzed baseline and progression samples from 41 AML patients with newly detected RAS mutations treated on clinical trials of gilteritinib. The group collected peripheral blood or bone marrow aspirates from the patients before and after treatment with gilteritinib.
"We were interested in whether or not gilteritinib resistance patterns were on-target or off-target, [and] whether this was going to be similar to what we saw with quizartinib," Perl said.
Patients in the study received gilteritinib between a range of 4 to 78 weeks. However, most patients ultimately discontinued gilteritinib due to AML relapse and progression.
The researchers initially found that while FLT3-F69Il mutations happened in a small group of patients with gilteritinib, the most common mechanism of resistance to gilteritinib were RAS pathway mutation activations.
In order to understand how clonal diversity in AML could promote development of resistance to FLT3 inhibition, the researcher used targeted NGS at the time of AML progression on gilteritinib, identifying treatment-emergent mutations that activate RAS/MAPK pathway signaling. The group found that RAS/MAPK pathway mutations were common following gilteritinib treatment in patients with relapsed/refractory FLT3-mutated AML, suggesting a clinically significant mechanism of resistance. Introducing the same RAS mutations into FLT3 mutated cell lines conferred in vitro resistance to gilteritinib, validating the approach.
To further define changes in clonal architecture found by bulk targeted NGS analysis, the group performed single-cell DNA sequencing on the patient samples using Tapestri.
Perl explained that his team worked with Mission Bio and its Tapestri assay because the group had prior history with the firm in another study that examined on-target quizartinib resistance in AML. Perl's team had previously sequenced mutated genes but did not have the tools available at the time to examine both on- and off-target resistance at the single-cell level.
"We wanted to know whether we're just looking at clonal evolution in the marrow, or whether we're looking at the mutational evolution in the leukemia cell," Perl said. "We saw patients who cleared their FLT3 mutations, and yet [still] had a RAS mutation."
Perl's group therefore began searching for therapy-resistant mutations beyond FLT3 and other genes, since it had already identified NRAS mutations using bulk sequencing.
"Tapestri has provided a tool that can resolve these heterogenous causes of mutational resistance, which was why we sought to use it to study mechanisms of gilteritinib resistance" Perl said.
With AML, Perl noted that clinicians can serially sample the tumor directly during therapy, allowing the group to bank cells during monthly marrow biopsies.
"With bulk sequencing, you can't tell whether a rising clone is occurring in the cell with the FLT3 mutation or in the same marrow but a different cell," Perl explained. "We solved that by using the Tapestri assay, which can genotype cell by cell by encapsulating the cell, barcoding DNA, and cleaving the protein with a protease."
According to Perl, Tapestri allowed his team to introduce specific PCR reagents to targeted genes and run barcoded NGS panels on the sample. From there, the researchers could deconvolute the NGS data and figure out which sequence came from which cell. In addition, the team could examine which mutations occur in which cells and which mutations are seen together on a cell by cell basis.
"While not a perfect assay, Tapestri genotypes approximately 10,000 cells and can resolve down to the level of a handful of resistant cells," Perl highlighted. "You can track the mutation via therapy to know if this was present prior to therapy and just expanded, or if it was something that evolved after several months on therapy,"
In the study, Perl's team found that the samples lacked any evidence of on-target mutations of FLT3 — besides gatekeeping mutations — that conferred resistance to gilteritinib.
According to the study authors, Tapestri highlighted diverse patterns of clonal selection and evolution in response to FLT3 inhibition, including RAS mutations in FLT3-mutated subclones, expansion of alternative FLT3 wild-type subclones, or both patterns at the same time.
The researchers believe that the data therefore illustrates dynamic and complex changes in clonal architecture underlying response and resistance to mutation-selective tyrosine kinase inhibitor therapy in AML.
"Our single-cell analysis showed that the NRAS and KRAS mutations identified following gilteritinib therapy were present in clonal cell populations containing FLT3 mutations in the samples tested," the authors said. "PTPN11 mutations occurred in both FLT3-WT and FLT3-mutated populations, illustrating the value of single-cell sequencing methods for elucidation mechanisms of resistance to targeted therapies."
In addition, Perl highlighted that his team could successfully show the evolution of leukemia over the course of therapy to see how certain cell populations rise and fall.
"We can see a generation of resistant cells that lack a drug target, a set of cells that have the target and additional mutations, and a new population that will evolve all by themselves, which we don't understand why," Perl said.
The researchers noted that the study had several limitations due to sample size and potential variations in drug exposure. Perl's team attempted to draw as many samples as possible from a prior phase I/2 study, but he noted that "it was a population with quite varied prior therapy."
In addition, Perl noted that the patients could have developed a resistance to the drug for several reasons, including prior FLT3 exposure.
"We were only able to bank samples of patients who could provide actual samples, so we tended to err on the side of patients who had a lot of tumor prior to the study and gave us marrow during the study," Perl said. "The patients staying on the drug gave us more samples as well, which might indicate some selection bias."
Perl also acknowledged that his team initially needed a brief period to learn how to use Tapestri and interpret the data provided by the assay.
"Going through the [data analysis] and asking 'what's the allele dropout and what's real' when we see these populations together, there's a little bit of nuance that [Mission Bio] was able to help us work through," Perl said. "It's the first time we've looked at it in a targeted inhibitor, for any disease, which is novel and a bit of a learning curve."
In general, Perl noted that the biggest challenge in single-cell sequencing relates to expense — though he didn't elaborate on pricing — and the need for bioinformatic analysis. He believes that technical issues linked to allele dropout during amplification can lead to noise in the data.
Perl's group will continue to examine the potential of monitoring patients after gilteritinib therapy. He also speculated whether leftover evidence of clonality after chemotherapy might indicate a higher risk of relapse, and how that would dictate the proper course of treatment.
Perl's group will also use single-cell sequencing methods to track potential minimal residual disease in patients. If the team identifies low levels of resistance mutations, the group may choose one investigational approach over another.
"Persistence of measurable disease over time during therapy appears to trump pre-treatment models of relapse risk estimation that are derived from baseline [or] pre-treatment characteristics," Perl said. "What is not yet established is the best method to follow and/or quantify MRD and whether pre-emptively changing to alternate treatment strategy truly improves survival, versus waiting for relapse to occur and then treating them."
The group will therefore combine gilteritinib with other target agents to selectively investigate emerging and potential variants of resistant clones and mutations that might occur during therapy.
While Perl's team applied Mission Bio's Tapestri approach in the prospective study, other commercial players also offer their own single-cell sequencing platforms for groups to analyze DNA for cancer-linked mutations.
Fluidigm has helped mold the market with its C1 single-cell genomic system for preparing single-cell templates for DNA sequencing, mRNA sequencing, epigenetics and miRNA expression.
10X Genomics launched three single-cell analysis products for its Chromium Controller platform in 2018, which add to its existing products for linked-read DNA sequencing and single-cell gene expression profiling.
Celsee also launched its single-cell analysis platform in 2018, which uses a gravity-based method to capture and isolate up to 100,00 individual cells per run while ensuring viability and structural integrity for sequencing.