Dissecting the Contributions of Cooperating Gene Mutations to Cancer Phenotypes and Drug Responses with Patient-Derived iPSCs

摘要

class="head no_bottom_margin" id="sec1title">IntroductionPrecision oncology aims to match patients with drugs that target the specific genetic makeup of their malignant cells to enhance their chances of response. Pairing specific mutations with drug responses is central to this goal, but hindered by the immense genetic diversity and complexity of both hematologic malignancies and solid tumors. The vast majority of human malignancies contain more than one recurrent genetic lesion that cooperatively confer their phenotypic characteristics. In addition to associations of specific mutations to drug responses, associations of mutations to cellular phenotypes would also be valuable to help determine the most useful functional assays to guide drug testing. Furthermore, understanding the relative contribution of each genetic lesion to the malignant phenotype can aid the understanding of mechanisms of oncogenesis and the importance of the order of mutation acquisition.Current experimental methods afford limited opportunities for drawing genotype-to-phenotype and genotype-to-drug response associations. Very few associations of gene mutations to drug responses can be made directly in the clinic due to the complexity and heterogeneity of cancer genomes, the relative rarity of some cancers and genotypes and the constrains imposed by currently administered therapies. Patient-derived xenograft models have been used to predict therapeutic responses but variable clonal dynamics and genetic drifts hamper systematic connections of specific mutations with drug responses (, ). Genetically engineered mouse models offer precise genetic models amenable to studies of mutational cooperation, but can be limited by species-determined differences in disease phenotypes, downstream mechanisms, and drug specificities (, , ).Myelodysplastic syndrome (MDS) genomes typically harbor two or more genetic lesions, including gene mutations and larger-scale genetic abnormalities, mainly deletions of the long arm of chromosomes 5, 7, and 20 (). Mutations in genes encoding splicing factors have recently been discovered as the most frequent class of mutations in MDS (, , ). Serine/arginine-rich splicing factor 2 (SRSF2) is a member of the serine/arginine-rich (SR) protein family that contributes to both constitutive and alternative splicing by binding to RNA sequence motifs that are enriched in exons, called exonic splicing enhancer (ESE) sequences. Mutations of SRSF2 are found in 20%–30% of MDS patients and, less frequently, in other hematologic malignancies and solid tumors and are almost always heterozygous missense substitutions at codon P95 (P95 L/R/H) (, , ). Somatic loss of one copy of the long arm of chromosome 7 (del(7q)) is a characteristic cytogenetic abnormality in MDS and other myeloid malignancies, associated with unfavorable prognosis and can co-occur with the SRSF2 P95 mutation in patients with MDS and acute myeloid leukemia (AML) (, ).Here we combined patient-derived induced pluripotent stem cells (iPSCs) with the CRISPR/Cas9 system to interrogate the contributions of the SRSF2 P95 mutation and of the del(7q) to cellular phenotype and drug responses. We find that the SRSF2 P95 mutation confers dysplastic morphology and other phenotypic characteristics to iPSC-derived hematopoietic progenitor cells (iPSC-HPCs) in support of a role early in the transformation process, while del(7q)-iPSC-HPCs exhibit a more severe differentiation block, concomitant with disease progression—findings consistent with clinical observations and population genetics analyses. We show that SRSF2 mutant iPSC-HPCs are preferentially sensitive to splicing modulator drugs and identify candidate compounds preferentially targeting del(7q) cells through an unbiased large-scale small-molecule screen. To facilitate drug testing and screening, we report the derivation of iPSC-derived expandable HPCs (eHPCs) that can be grown like conventional cell lines while maintaining specific drug sensitivities. These results demonstrate the power of patient-derived iPSCs and genome editing in dissecting the individual contributions of cooperating genetic lesions to clinically relevant cancer features.