Plasma Proteomic Signature Predicts Myeloid Neoplasm Risk.

PURPOSE: Clonal hematopoiesis (CH) is thought to be the origin of myeloid neoplasms (MN). Yet our understanding of the mechanisms driving CH progression to MN and clinical risk prediction of MN remains limited. The human proteome reflects complex interactions between genetic and epigenetic regulation of biological systems. We hypothesized that the plasma proteome might predict MN risk and inform our understanding of the mechanisms promoting MN development. EXPERIMENTAL DESIGN: We jointly characterized CH and plasma proteomic profiles of 46,237 individuals in the UK Biobank at baseline study entry. During 500,036 person-years of follow-up, 115 individuals developed MN. Cox proportional hazard regression was used to test for an association between plasma protein levels and MN risk. RESULTS: We identified 115 proteins associated with MN risk of which 30% (N=34) were also associated with CH. These were enriched for known regulators of the innate and adaptive immune system. Plasma proteomics improved the prediction of MN risk (AUC=0.85, p=5×10-9) beyond clinical factors and CH (AUC=0.80). In an independent group (N=381,485), we used inherited polygenic risk scores (PRS) for plasma protein levels to validate the relevance of these proteins to MN development. PRS analyses suggest that most MN-associated proteins we identified are not directly causally linked to MN risk, but rather represent downstream markers of pathways regulating the progression of CH to MN. CONCLUSIONS: These data highlight the role of immune cell regulation in the progression of CH to MN and the promise of leveraging multi-omic characterization of CH to improve MN risk stratification.

ArCH: improving the performance of clonal hematopoiesis variant calling and interpretation.

MOTIVATION: The acquisition of somatic mutations in hematopoietic stem and progenitor stem cells with resultant clonal expansion, termed clonal hematopoiesis (CH), is associated with increased risk of hematologic malignancies and other adverse outcomes. CH is generally present at low allelic fractions, but clonal expansion and acquisition of additional mutations leads to hematologic cancers in a small proportion of individuals. With high depth and high sensitivity sequencing, CH can be detected in most adults and its clonal trajectory mapped over time. However, accurate CH variant calling is challenging due to the difficulty in distinguishing low frequency CH mutations from sequencing artifacts. The lack of well-validated bioinformatic pipelines for CH calling may contribute to lack of reproducibility in studies of CH. RESULTS: Here, we developed ArCH, an Artifact filtering Clonal Hematopoiesis variant calling pipeline for detecting single nucleotide variants and short insertions/deletions by combining the output of four variant calling tools and filtering based on variant characteristics and sequencing error rate estimation. ArCH is an end-to-end cloud-based pipeline optimized to accept a variety of inputs with customizable parameters adaptable to multiple sequencing technologies, research questions, and datasets. Using deep targeted sequencing data generated from six acute myeloid leukemia patient tumor: normal dilutions, 31 blood samples with orthogonal validation, and 26 blood samples with technical replicates, we show that ArCH improves the sensitivity and positive predictive value of CH variant detection at low allele frequencies compared to standard application of commonly used variant calling approaches. AVAILABILITY AND IMPLEMENTATION: The code for this workflow is available at: https://github.com/kbolton-lab/ArCH.

Molecular Subclasses of Clear Cell Ovarian Carcinoma and Their Impact on Disease Behavior and Outcomes.

PURPOSE: To identify molecular subclasses of clear cell ovarian carcinoma (CCOC) and assess their impact on clinical presentation and outcomes. EXPERIMENTAL DESIGN: We profiled 421 primary CCOCs that passed quality control using a targeted deep sequencing panel of 163 putative CCOC driver genes and whole transcriptome sequencing of 211 of these tumors. Molecularly defined subgroups were identified and tested for association with clinical characteristics and overall survival. RESULTS: We detected a putative somatic driver mutation in at least one candidate gene in 95% (401/421) of CCOC tumors including ARID1A (in 49% of tumors), PIK3CA (49%), TERT (20%), and TP53 (16%). Clustering of cancer driver mutations and RNA expression converged upon two distinct subclasses of CCOC. The first was dominated by ARID1A-mutated tumors with enriched expression of canonical CCOC genes and markers of platinum resistance; the second was largely comprised of tumors with TP53 mutations and enriched for the expression of genes involved in extracellular matrix organization and mesenchymal differentiation. Compared with the ARID1A-mutated group, women with TP53-mutated tumors were more likely to have advanced-stage disease, no antecedent history of endometriosis, and poorer survival, driven by their advanced stage at presentation. In women with ARID1A-mutated tumors, there was a trend toward a lower rate of response to first-line platinum-based therapy. CONCLUSIONS: Our study suggests that CCOC consists of two distinct molecular subclasses with distinct clinical presentation and outcomes, with potential relevance to both traditional and experimental therapy responsiveness. See related commentary by Lheureux, p. 4838.

What Clonal Hematopoiesis Can Teach Us About MDS.

Clonal hematopoiesis (CH), defined as the clonal expansion of mutated hematopoietic stem and progenitor cells (HSPCs), is a common aging process. CH is a risk factor for the development of hematologic malignancies, most commonly myeloid neoplasms (MNs) including acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and myeloproliferative neoplasm (MPN). Recent work has elucidated how the development and cellular fitness of CH is shaped by aging, environmental exposures, and the germline (inherited) genetic background of an individual. This in turn has provided valuable insights into the pathogenesis of MNs including MDS. Here, in this review, we discuss the genetic origins of CH, the environmental stressors that influence CH, and the implications of CH on health outcomes including MDS. Since MNs have shared risk factors and underlying biology, most of our discussion regarding the implications of CH surrounds MN in general rather than focusing specifically on MDS. We conclude with future directions and areas of investigation including how intervention studies of CH might inform future therapeutic approaches to MN including MDS.