NEW YORK – Using single-cell sequencing data, researchers from the University of Texas MD Anderson Cancer Center have begun to explore the clonal diversity and determine the evolution of acute myeloid leukemia.
By better understanding the heterogeneity of cancer cells, researchers can gain insight into both how cancer develops as well as which targeted treatments might be best used to treat it. To that end, researchers led by MD Anderson's Koichi Takahashi conducted single-cell sequencing of samples from more than 100 AML patients.
With the single-cell data they generated, the researchers detected driver mutations that tended to co-occur as well as mutations that were mutually exclusive and began to tease out the evolutionary history of some of those mutations, as they reported on Wednesday in Nature Communications. With a set of longitudinal samples, they further observed how clonal architecture changed in response to different treatments, suggesting single-cell analyses could inform treatment decisions.
"So far AML — or actually any cancer — has not been really well characterized by a single-cell DNA sequencing platform," Takahashi said in an interview. "We just wanted to understand the landscape of genetic diversity in AML and not only look at a few cases — we wanted to do a large cohort analysis."
By taking a single cell-based approach, the researchers hoped to generate a picture of diversity among cells from AML patients at a high resolution. Using Mission Bio's Tapestri single-cell sequencing platform, Takahashi and his colleagues analyzed 154 samples of bone marrow mononuclear cells from 123 AML patients. They additionally analyzed the samples by conventional bulk sequencing, which they used to guide which targeted gene panel they used for their single-cell sequencing analysis.
In all, they sequenced more than 730,000 cells to find 543 somatic mutations in 31 cancer-related genes, 98 percent of which they orthogonally validated. The most common mutations they detected were in NPM1, followed by ones in DNMT3A and NRAS.
They further found that while a number of mutations that were functionally redundant were found in the same patients, the alterations were often found in mutually exclusive clones. This extended to alterations affecting receptor tyrosine kinase (RTK)/Gas GTPase (RAS)/MAP kinase (MAPK) signaling pathway genes as well as IDH1 and IDH2 mutations and TET2 and IDH mutations. This suggested to the researchers that cells either don't need two mutations or that, when they appear together, the mutations are toxic — which could suggest a potential treatment avenue to investigate.
With the caveat that their analysis was based on mutations in cancer genes, the researchers additionally noted that about half the AML patients exhibited linear clonal evolution — a pattern Takahashi noted is a classical cancer development model — but half exhibited branching clonal evolution. A branching pattern, Takahashi added, was known to occur in cancer and AML, but he noted that here, they were able to reconstruct it with more confidence and robustness.
Some patients exhibited extreme bursts of branching, which Takahashi said made him wonder why some cases need to have multiple branches of subclones. He further noted that this might be a finding to study in a future analysis.
Additionally, he and his colleagues used a feature of the Tapestri platform that allowed them to simultaneously analyze single-cell DNA and cell surface proteins of more than a dozen patients by first treating the samples with antibodies. From this, they analyzed genotype-phenotype correlations among the cells to find, for instance, that cells with NPM1 or IDH mutations expressed lower levels of CD34 and HLA-DR, while cells with a single TP53 mutations had CD34+CD117+ phenotype, but double TP53 mutations had a monocytic immunophenotype.
For slightly more than a dozen patients, the researchers had a set of longitudinal samples, which enabled them to examine how their clonal architecture changed in response to therapy. For instance, one patient receiving treatment with azacitidine and sorafenib, an FLT3 inhibitor, had a subclone with an FLT3 mutation that was associated with relapse, suggesting ongoing clonal selection. Similarly, another patient exhibited clonal selection for NRAS and PTPN11, FLT2-ITD, and IDH1 mutations during treatment with azacitidine and the IDH2 inhibitor enasidenib.
"This information is also somewhat available from longitudinal bulk sequencing data longitudinally, but I think single-cell data uniquely provides this meticulous view of clone-by-clone dynamics, which is just simply not possible by bulk sequencing," Takahashi said. He added that one of his plans stemming from this work is to gauge whether single-cell sequencing could be applied to residual disease monitoring efforts.