Plasma versus tissue tumor mutational burden as biomarkers of durvalumab plus tremelimumab response in patients with metastatic colorectal cancer in the CO.26 trial.

PURPOSE: Tissue derived tumor mutation burden (TMB) of ≥10 mutations/Mb is a histology agnostic biomarker for the immune checkpoint inhibitor (ICI) pembrolizumab. However, the dataset on which this was validated lacked colorectal cancers (CRCs), and there is limited evidence for immunotherapy benefit in CRC using this threshold. PATIENTS AND METHODS: CO.26 was a randomized phase II study of 180 patients comparing durvalumab and tremelimumab (D+T, n=119 patients) versus best supportive care (BSC, n=61 patients). ctDNA sequencing was available for 168 patients (n=118 D+T, n=50), of which 165 had evaluable plasma TMB (pTMB). Tissue sequencing was available for 108 patients. Optimal thresholds for stratifying patients based on overall survival were determined using a minimal p-value approach. This report includes the final overall survival analysis. RESULTS: Tissue TMB ≥10 mutations/Mb was not predictive of benefit from D+T compared to BSC in microsatellite stable (MSS) metastatic CRC (HR 0.71 [95% CI:0.28-1.80], p=0.47). No tissue TMB threshold could identify a high TMB group that benefited from ICI. In contrast, plasma TMB (pTMB) ≥28 mutations/Mb was predictive of benefit from D+T (HR=0.34 [95%CI:0.13-0.85], p=0.022), as was clonal pTMB ≥10.6 mutations/Mb (HR=0.10 [95%CI:0.014-0.79], p=0.029) and subclonal pTMB ≥25.9/Mb (HR=0.20 [95% CI:0.061-0.69], p=0.010). Higher pTMB was associated with length of time on cytotoxic agents (p=0.021) and prior anti-EGFR exposure (p=2.44x10-06). CONCLUSION: pTMB derived from either clonal or subclonal mutations may identify a group more likely to benefit from immunotherapy, though validation is required. Tissue TMB provided no predictive utility for immunotherapy in this trial.

Translation efficiency driven by CNOT3 subunit of the CCR4-NOT complex promotes leukemogenesis.

Protein synthesis is frequently deregulated during tumorigenesis. However, the precise contexts of selective translational control and the regulators of such mechanisms in cancer is poorly understood. Here, we uncovered CNOT3, a subunit of the CCR4-NOT complex, as an essential modulator of translation in myeloid leukemia. Elevated CNOT3 expression correlates with unfavorable outcomes in patients with acute myeloid leukemia (AML). CNOT3 depletion induces differentiation and apoptosis and delayed leukemogenesis. Transcriptomic and proteomic profiling uncovers c-MYC as a critical downstream target which is translationally regulated by CNOT3. Global analysis of mRNA features demonstrates that CNOT3 selectively influences expression of target genes in a codon usage dependent manner. Furthermore, CNOT3 associates with the protein network largely consisting of ribosomal proteins and translation elongation factors in leukemia cells. Overall, our work elicits the direct requirement for translation efficiency in tumorigenesis and propose targeting the post-transcriptional circuitry via CNOT3 as a therapeutic vulnerability in AML.

Chronic Lymphocytic Leukemia IGHV Somatic Hypermutation Detection by Targeted Capture Next-Generation Sequencing.

BACKGROUND: Somatic hypermutation (SHM) status of the immunoglobulin heavy variable (IGHV) gene plays a crucial role in determining the prognosis and treatment of patients with chronic lymphocytic leukemia (CLL). A common approach for determining SHM status is multiplex polymerase chain reaction and Sanger sequencing of the immunoglobin heavy locus; however, this technique is low throughput, is vulnerable to failure, and does not allow multiplexing with other diagnostic assays. METHODS: Here we designed and validated a DNA targeted capture approach to detect immunoglobulin heavy variable somatic hypermutation (IGHV SHM) status as a submodule of a larger next-generation sequencing (NGS) panel that also includes probes for ATM, BIRC3, CHD2, KLHL6, MYD88, NOTCH1, NOTCH2, POT1, SF3B1, TP53, and XPO1. The assay takes as input FASTQ files and outputs a report containing IGHV SHM status and V allele usage following European Research Initiative on CLL guidelines. RESULTS: We validated the approach on 35 CLL patient samples, 34 of which were characterized using Sanger sequencing. The NGS panel identified the IGHV SHM status of 34 of 35 CLL patients. We showed 100% sensitivity and specificity among the 33 CLL samples with both NGS and Sanger sequencing calls. Furthermore, we demonstrated that this panel can be combined with additional targeted capture panels to detect prognostically important CLL single nucleotide variants, insertions/deletions, and copy number variants (TP53 copy number loss). CONCLUSIONS: A targeted capture approach to IGHV SHM detection can be integrated into broader sequencing panels, allowing broad CLL prognostication in a single molecular assay.

Multisite clinical cross-validation and variant interpretation of a next generation sequencing panel for lymphoid cancer prognostication.

AIMS: Genomic sequencing of lymphomas is under-represented in routine clinical testing despite having prognostic and predictive value. Clinical implementation is challenging due to a lack of consensus on reportable targets and a paucity of reference samples. We organised a cross-validation study of a lymphoma-tailored next-generation sequencing panel between two College of American Pathologists (CAP)-accredited clinical laboratories to mitigate these challenges. METHODS: A consensus for the genomic targets was discussed between the two institutes based on recurrence in diffuse large B-cell lymphoma, follicular lymphoma, mantle cell lymphoma, chronic lymphocytic leukaemia and T-cell lymphomas. Using the same genomic targets, each laboratory ordered libraries independently and a cross-validation study was designed to exchange samples (8 cell lines and 22 clinical samples) and their FASTQ files. RESULTS: The sensitivity of the panel when comparing different library preparation and bioinformatic workflows was between 97% and 99% and specificity was 100% when a 5% limit of detection cut-off was applied. To evaluate how the current standards for variant classification of tumours apply to lymphomas, the Association for Molecular Pathology/American Society of Clinical Oncology/CAP and OncoKB classification systems were applied to the panel. The majority of variants were assigned a possibly actionable class or likely pathogenic due to more limited evidence in the literature. CONCLUSIONS: The cross-validation study highlights the benefits of sample and data exchange for clinical validation and provided a framework for reporting the findings in lymphoid malignancies.

Operationalizing Quality Assurance for Clinical Illumina Somatic Next-Generation Sequencing Pipelines.

Quality assurance (QA) is essential for precision oncology workflows, in particular in the clinical setting. However, because of numerous variations in laboratory and bioinformatics pipelines, QA practices remain non-standardized, are often ad hoc, and are lacking longitudinal tracking. A selected review of existing software was performed for quality control of Illumina next-generation sequencing data, focusing specifically on generalizable tools that can be integrated into any bioinformatics workflow to easily develop a QA workflow with longitudinal tracking. Although all implementations need to be integrated, validated, and iterated upon to suit individual operations, providing a base suite of options will enable better validation and use of QA in clinical somatic mutation testing for workflows using Illumina next-generation sequencing and beyond.

"I just wanted more": Hereditary cancer syndromes patients' perspectives on the utility of circulating tumour DNA testing for cancer screening.

Hereditary cancer syndromes (HCS) predispose individuals to a higher risk of developing multiple cancers. However, current screening strategies have limited ability to screen for all cancer risks. Circulating tumour DNA (ctDNA) detects DNA fragments shed by tumour cells in the bloodstream and can potentially detect cancers early. This study aimed to explore patients' perspectives on ctDNA's utility to help inform its clinical adoption and implementation. We conducted a qualitative interpretive description study using semi-structured phone interviews. Participants were purposively sampled adult HCS patients recruited from a Canadian HCS research consortium. Thirty HCS patients were interviewed (n = 19 women, age range 20s-70s, n = 25 were white). Participants were highly concerned about developing cancers, particularly those without reliable screening options for early detection. They "just wanted more" than their current screening strategies. Participants were enthusiastic about ctDNA's potential to be comprehensive (detect multiple cancers), predictive (detect cancers early) and tailored (lead to personalized clinical management). Participants also acknowledged ctDNA's potential limitations, including false positives/negatives risks and experiencing additional anxiety. However, they saw ctDNA's potential benefits outweighing its limitations. In conclusion, participants' belief in ctDNA's potential to improve their care overshadowed its limitations, indicating patients' support for using ctDNA in HCS care.

Spatially Resolved Tumor Microenvironment Predicts Treatment Outcomes in Relapsed/Refractory Hodgkin Lymphoma.

PURPOSE: About a third of patients with relapsed or refractory classic Hodgkin lymphoma (r/r CHL) succumb to their disease after high-dose chemotherapy followed by autologous stem-cell transplantation (HDC/ASCT). Here, we aimed to describe spatially resolved tumor microenvironment (TME) ecosystems to establish novel biomarkers associated with treatment failure in r/r CHL. PATIENTS AND METHODS: We performed imaging mass cytometry (IMC) on 71 paired primary diagnostic and relapse biopsies using a marker panel specific to CHL biology. For each cell type in the TME, we calculated a spatial score measuring the distance of nearest neighbor cells to the malignant Hodgkin Reed Sternberg cells within the close interaction range. Spatial scores were used as features in prognostic model development for post-ASCT outcomes. RESULTS: Highly multiplexed IMC data revealed shared TME patterns in paired diagnostic and early r/r CHL samples, whereas TME patterns were more divergent in pairs of diagnostic and late relapse samples. Integrated analysis of IMC and single-cell RNA sequencing data identified unique architecture defined by CXCR5+ Hodgkin and Reed Sternberg (HRS) cells and their strong spatial relationship with CXCL13+ macrophages in the TME. We developed a prognostic assay (RHL4S) using four spatially resolved parameters, CXCR5+ HRS cells, PD1+CD4+ T cells, CD68+ tumor-associated macrophages, and CXCR5+ B cells, which effectively separated patients into high-risk versus low-risk groups with significantly different post-ASCT outcomes. The RHL4S assay was validated in an independent r/r CHL cohort using a multicolor immunofluorescence assay. CONCLUSION: We identified the interaction of CXCR5+ HRS cells with ligand-expressing CXCL13+ macrophages as a prominent crosstalk axis in relapsed CHL. Harnessing this TME biology, we developed a novel prognostic model applicable to r/r CHL biopsies, RHL4S, opening new avenues for spatial biomarker development.

Integrating DNA methylation and gene expression data in a single gene network using the iNETgrate package.

Analyzing different omics data types independently is often too restrictive to allow for detection of subtle, but consistent, variations that are coherently supported based upon different assays. Integrating multi-omics data in one model can increase statistical power. However, designing such a model is challenging because different omics are measured at different levels. We developed the iNETgrate package ( https://bioconductor.org/packages/iNETgrate/ ) that efficiently integrates transcriptome and DNA methylation data in a single gene network. Applying iNETgrate on five independent datasets improved prognostication compared to common clinical gold standards and a patient similarity network approach.

Protocol for performing consecutive bone marrow transplants in mice to study the role of marrow niche in supporting hematopoiesis.

Hematopoietic stem and progenitor cells depend on bone marrow (BM) stromal cells for survival. Here, we present a protocol for performing three consecutive BM transplants in mice to study the role of BM niche in supporting hematopoiesis. We describe steps for transplanting cells to condition the marrow of the recipient mice and transplanting wild-type cells to examine the effect of the conditioned marrow in supporting hematopoiesis. We then detail procedures for transplanting into wild-type recipients to measure bone marrow chimerism. For complete details on the use and execution of this protocol, please refer to Gopal et al. (2022).1.

Shift of the insoluble content of the proteome in the aging mouse brain.

During aging, the cellular response to unfolded proteins is believed to decline, resulting in diminished proteostasis. In model organisms, such as Caenorhabditis elegans, proteostatic decline with age has been linked to proteome solubility shifts and the onset of protein aggregation. However, this correlation has not been extensively characterized in aging mammals. To uncover age-dependent changes in the insoluble portion of a mammalian proteome, we analyzed the detergent-insoluble fraction of mouse brain tissue by mass spectrometry. We identified a group of 171 proteins, including the small heat shock protein α-crystallin, that become enriched in the detergent-insoluble fraction obtained from old mice. To enhance our ability to detect features associated with proteins in that fraction, we complemented our data with a meta-analysis of studies reporting the detergent-insoluble proteins in various mouse models of aging and neurodegeneration. Strikingly, insoluble proteins from young and old mice are distinct in several features in our study and across the collected literature data. In younger mice, proteins are more likely to be disordered, part of membraneless organelles, and involved in RNA binding. These traits become less prominent with age, as an increased number of structured proteins enter the pellet fraction. This analysis suggests that age-related changes to proteome organization lead a group of proteins with specific features to become detergent-insoluble. Importantly, these features are not consistent with those associated with proteins driving membraneless organelle formation. We see no evidence in our system of a general increase of condensate proteins in the detergent-insoluble fraction with age.

Current and new frontiers in hereditary cancer surveillance: Opportunities for liquid biopsy.

At least 5% of cancer diagnoses are attributed to a causal pathogenic or likely pathogenic germline genetic variant (hereditary cancer syndrome-HCS). These individuals are burdened with lifelong surveillance monitoring organs for a wide spectrum of cancers. This is associated with substantial uncertainty and anxiety in the time between screening tests and while the individuals are awaiting results. Cell-free DNA (cfDNA) sequencing has recently shown potential as a non-invasive strategy for monitoring cancer. There is an opportunity for high-yield cancer early detection in HCS. To assess clinical validity of cfDNA in individuals with HCS, representatives from eight genetics centers from across Canada founded the CHARM (cfDNA in Hereditary and High-Risk Malignancies) Consortium in 2017. In this perspective, we discuss operationalization of this consortium and early data emerging from the most common and well-characterized HCSs: hereditary breast and ovarian cancer, Lynch syndrome, Li-Fraumeni syndrome, and Neurofibromatosis type 1. We identify opportunities for the incorporation of cfDNA sequencing into surveillance protocols; these opportunities are backed by examples of earlier cancer detection efficacy in HCSs from the CHARM Consortium. We seek to establish a paradigm shift in early cancer surveillance in individuals with HCSs, away from highly centralized, regimented medical screening visits and toward more accessible, frequent, and proactive care for these high-risk individuals.

"iNETgrate": integrating DNA methylation and gene expression data in a single gene network.

Integrating multi-omics data in one model can increase statistical power. However, designing such a model is challenging because different omics are measured at different levels. We developed the iNETgrate package (https://bioconductor.org/packages/iNETgrate/) that efficiently integrates transcriptome and DNA methylation data in a single gene network. Applying iNETgrate on five independent datasets improved prognostication compared to common clinical gold standards and a patient similarity network approach.

Meis1 establishes the pre-hemogenic endothelial state prior to Runx1 expression.

Hematopoietic stem and progenitor cells (HSPCs) originate from an endothelial-to-hematopoietic transition (EHT) during embryogenesis. Characterization of early hemogenic endothelial (HE) cells is required to understand what drives hemogenic specification and to accurately define cells capable of undergoing EHT. Using Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), we define the early subpopulation of pre-HE cells based on both surface markers and transcriptomes. We identify the transcription factor Meis1 as an essential regulator of hemogenic cell specification in the embryo prior to Runx1 expression. Meis1 is expressed at the earliest stages of EHT and distinguishes pre-HE cells primed towards the hemogenic trajectory from the arterial endothelial cells that continue towards a vascular fate. Endothelial-specific deletion of Meis1 impairs the formation of functional Runx1-expressing HE which significantly impedes the emergence of pre-HSPC via EHT. Our findings implicate Meis1 in a critical fate-determining step for establishing EHT potential in endothelial cells.

Relapse Timing Is Associated With Distinct Evolutionary Dynamics in Diffuse Large B-Cell Lymphoma.

PURPOSE: Diffuse large B-cell lymphoma (DLBCL) is cured in more than 60% of patients, but outcomes remain poor for patients experiencing disease progression or relapse (refractory or relapsed DLBCL [rrDLBCL]), particularly if these events occur early. Although previous studies examining cohorts of rrDLBCL have identified features that are enriched at relapse, few have directly compared serial biopsies to uncover biological and evolutionary dynamics driving rrDLBCL. Here, we sought to confirm the relationship between relapse timing and outcomes after second-line (immuno)chemotherapy and determine the evolutionary dynamics that underpin that relationship. PATIENTS AND METHODS: Outcomes were examined in a population-based cohort of 221 patients with DLBCL who experienced progression/relapse after frontline treatment and were treated with second-line (immuno)chemotherapy with an intention-to-treat with autologous stem-cell transplantation (ASCT). Serial DLBCL biopsies from a partially overlapping cohort of 129 patients underwent molecular characterization, including whole-genome or whole-exome sequencing in 73 patients. RESULTS: Outcomes to second-line therapy and ASCT are superior for late relapse (>2 years postdiagnosis) versus primary refractory (<9 months) or early relapse (9-24 months). Diagnostic and relapse biopsies were mostly concordant for cell-of-origin classification and genetics-based subgroup. Despite this concordance, the number of mutations exclusive to each biopsy increased with time since diagnosis, and late relapses shared few mutations with their diagnostic counterpart, demonstrating a branching evolution pattern. In patients with highly divergent tumors, many of the same genes acquired new mutations independently in each tumor, suggesting that the earliest mutations in a shared precursor cell constrain tumor evolution toward the same genetics-based subgroups at both diagnosis and relapse. CONCLUSION: These results suggest that late relapses commonly represent genetically distinct and chemotherapy-naïve disease and have implications for optimal patient management.

A noncanonical enzymatic function of PIWIL4 maintains genomic integrity and leukemic growth in AML.

RNA-binding proteins (RBPs) form a large and diverse class of factors, many members of which are overexpressed in hematologic malignancies. RBPs participate in various processes of messenger RNA (mRNA) metabolism and prevent harmful DNA:RNA hybrids or R-loops. Here, we report that PIWIL4, a germ stem cell-associated RBP belonging to the RNase H-like superfamily, is overexpressed in patients with acute myeloid leukemia (AML) and is essential for leukemic stem cell function and AML growth, but dispensable for healthy human hematopoietic stem cells. In AML cells, PIWIL4 binds to a small number of known piwi-interacting RNA. Instead, it largely interacts with mRNA annotated to protein-coding genic regions and enhancers that are enriched for genes associated with cancer and human myeloid progenitor gene signatures. PIWIL4 depletion in AML cells downregulates the human myeloid progenitor signature and leukemia stem cell (LSC)-associated genes and upregulates DNA damage signaling. We demonstrate that PIWIL4 is an R-loop resolving enzyme that prevents R-loop accumulation on a subset of AML and LSC-associated genes and maintains their expression. It also prevents DNA damage, replication stress, and activation of the ATR pathway in AML cells. PIWIL4 depletion potentiates sensitivity to pharmacological inhibition of the ATR pathway and creates a pharmacologically actionable dependency in AML cells.

Targeting BET Proteins Downregulates miR-33a To Promote Synergy with PIM Inhibitors in CMML.

PURPOSE: Preclinical studies in myeloid neoplasms have demonstrated efficacy of bromodomain and extra-terminal protein inhibitors (BETi). However, BETi demonstrates poor single-agent activity in clinical trials. Several studies suggest that combination with other anticancer inhibitors may enhance the efficacy of BETi. EXPERIMENTAL DESIGN: To nominate BETi combination therapies for myeloid neoplasms, we used a chemical screen with therapies currently in clinical cancer development and validated this screen using a panel of myeloid cell line, heterotopic cell line models, and patient-derived xenograft models of disease. We used standard protein and RNA assays to determine the mechanism responsible for synergy in our disease models. RESULTS: We identified PIM inhibitors (PIMi) as therapeutically synergistic with BETi in myeloid leukemia models. Mechanistically, we show that PIM kinase is increased after BETi treatment, and that PIM kinase upregulation is sufficient to induce persistence to BETi and sensitize cells to PIMi. Furthermore, we demonstrate that miR-33a downregulation is the underlying mechanism driving PIM1 upregulation. We also show that GM-CSF hypersensitivity, a hallmark of chronic myelomonocytic leukemia (CMML), represents a molecular signature for sensitivity to combination therapy. CONCLUSIONS: Inhibition of PIM kinases is a potential novel strategy for overcoming BETi persistence in myeloid neoplasms. Our data support further clinical investigation of this combination.

Relapse timing is associated with distinct evolutionary dynamics in DLBCL.

Diffuse large B-cell lymphoma (DLBCL) is cured in over 60% of patients, but outcomes are poor for patients with relapsed or refractory disease (rrDLBCL). Here, we performed whole genome/exome sequencing (WGS/WES) on tumors from 73 serially-biopsied patients with rrDLBCL. Based on the observation that outcomes to salvage therapy/autologous stem cell transplantation are related to time-to-relapse, we stratified patients into groups according to relapse timing to explore the relationship to genetic divergence and sensitivity to salvage immunochemotherapy. The degree of mutational divergence increased with time between biopsies, yet tumor pairs were mostly concordant for cell-of-origin, oncogene rearrangement status and genetics-based subgroup. In patients with highly divergent tumors, several genes acquired exclusive mutations independently in each tumor, which, along with concordance of genetics-based subgroups, suggests that the earliest mutations in a shared precursor cell constrain tumor evolution. These results suggest that late relapses commonly represent genetically distinct and chemotherapy-naïve disease.

Control of focal adhesion kinase activation by RUNX1-regulated miRNAs in high-risk AML.

We recently described a 16-gene expression signature for improved risk stratification of acute myeloid leukemia (AML) patients called the AML Prognostic Score (APS). A subset of APS-high-risk AML patients showed increased levels of focal adhesion kinase (FAK), encoded by the Protein Tyrosine Kinase 2 (PTK2) gene, which was correlated with RUNX1 mutations. RUNX1 mutant cells are more sensitive to PTK2 inhibitors. As we were not able to detect RUNX1-binding sites in the PTK2 promoter, we hypothesized that RUNX1 might regulate micro(mi)RNAs that repress PTK2, such that loss-of-function RUNX1 mutations would result in reduced miRNA expression and derepression of PTK2. Examination of paired RNA-seq and miRNA-seq data from 301 AML cases revealed two miRNAs that positively correlated with RUNX1 expression, contained RUNX1-binding sites in their promoters and were predicted to target PTK2. We show that the hsa-let7a-2-3p and hsa-miR-135a-5p promoters are regulated by RUNX1, and that PTK2 is a direct target of both miRNAs. Even in the absence of RUNX1 mutations, hsa-let7a-2-3p and hsa-miR-135a-5p regulate PTK2 expression, and reduced expression of these two miRNAs sensitizes AML cells to PTK2 inhibition. These data explain how RUNX1 regulates PTK2, and identify potential miRNA biomarkers for targeting AML with PTK2 inhibitors.

Computational pathology in 2030: a Delphi study forecasting the role of AI in pathology within the next decade.

BACKGROUND: Artificial intelligence (AI) is rapidly fuelling a fundamental transformation in the practice of pathology. However, clinical integration remains challenging, with no AI algorithms to date in routine adoption within typical anatomic pathology (AP) laboratories. This survey gathered current expert perspectives and expectations regarding the role of AI in AP from those with first-hand computational pathology and AI experience. METHODS: Perspectives were solicited using the Delphi method from 24 subject matter experts between December 2020 and February 2021 regarding the anticipated role of AI in pathology by the year 2030. The study consisted of three consecutive rounds: 1) an open-ended, free response questionnaire generating a list of survey items; 2) a Likert-scale survey scored by experts and analysed for consensus; and 3) a repeat survey of items not reaching consensus to obtain further expert consensus. FINDINGS: Consensus opinions were reached on 141 of 180 survey items (78.3%). Experts agreed that AI would be routinely and impactfully used within AP laboratory and pathologist clinical workflows by 2030. High consensus was reached on 100 items across nine categories encompassing the impact of AI on (1) pathology key performance indicators (KPIs) and (2) the pathology workforce and specific tasks performed by (3) pathologists and (4) AP lab technicians, as well as (5) specific AI applications and their likelihood of routine use by 2030, (6) AI's role in integrated diagnostics, (7) pathology tasks likely to be fully automated using AI, and (8) regulatory/legal and (9) ethical aspects of AI integration in pathology. INTERPRETATION: This systematic consensus study details the expected short-to-mid-term impact of AI on pathology practice. These findings provide timely and relevant information regarding future care delivery in pathology and raise key practical, ethical, and legal challenges that must be addressed prior to AI's successful clinical implementation. FUNDING: No specific funding was provided for this study.

A low carbohydrate diet high in fish oil and soy protein delays inflammation, hematopoietic stem cell depletion, and mortality in miR-146a knock-out mice.

Since our previous studies found a low carbohydrate (CHO) diet containing soy protein and fish oil (15%Amylose/Soy/FO) significantly reduced lung and breast cancer in mice we asked herein if this low CHO diet could also delay the onset of myeloid malignancies. To test this we employed a miR-146a knock-out (KO) mouse model and found the 15%Amylose/Soy/FO diet increased their median lifespan by 8.5 month, compared to these mice on a Western diet. This was associated with increased lymphocytes and reduced monocytes, granulocytes, blood glucose and insulin levels. Inflammatory cytokine/chemokine studies carried out with 6-month-old mice, before any signs of illness, revealed the 15%Amylose/Soy/FO diet significantly reduced pro-inflammatory cytokines. This low CHO diet also led to an increase in plasma ß-hydroxybutyrate and in liver fatty acid synthase levels. This, together with higher liver carnitine palmitoyltransferase I levels suggested that the 15%Amylose/Soy/FO diet was causing a systemic metabolic shift from glucose to fatty acids as an energy source. Lastly, we found the 15%Amylose/Soy/FO diet resulted in significantly higher numbers of primitive hematopoietic stem cells (HSCs) in the bone marrow of 6-month-old mice than those fed a Western diet. Taken together, these results suggest a 15%Amylose/Soy/FO diet reduces chronic inflammation and increases fatty acid oxidation and that this, in turn, may prevent HSC proliferation and exhaustion, thereby delaying myeloid malignancy-induced death of miR-146a KO mice. We suggest a low CHO diet containing soy protein and fish oil could be beneficial in reducing the risk of myeloid malignancies in patients with low miR-146a levels.