AML risk stratification models utilizing ELN-2017 guidelines and additional prognostic factors: a SWOG report.

Background: The recently updated European LeukemiaNet risk stratification guidelines combine cytogenetic abnormalities and genetic mutations to provide the means to triage patients with acute myeloid leukemia for optimal therapies. Despite the identification of many prognostic factors, relatively few have made their way into clinical practice. Methods: In order to assess and improve the performance of the European LeukemiaNet guidelines, we developed novel prognostic models using the biomarkers from the guidelines, age, performance status and select transcript biomarkers. The models were developed separately for mononuclear cells and viable leukemic blasts from previously untreated acute myeloid leukemia patients (discovery cohort, Results: Models using European LeukemiaNet guidelines were significantly associated with clinical outcomes and, therefore, utilized as a baseline for comparisons. Models incorporating age and expression of select transcripts with biomarkers from European LeukemiaNet guidelines demonstrated higher area under the curve and C-statistics but did not show a substantial improvement in performance in the validation cohort. Subset analyses demonstrated that models using only the European LeukemiaNet guidelines were a better fit for younger patients (age \u3c 55) than for older patients. Models integrating age and European LeukemiaNet guidelines visually showed more separation between risk groups in older patients. Models excluding results for Conclusions: While European LeukemiaNet guidelines remain a critical tool for triaging patients with acute myeloid leukemia, the findings illustrate the need for additional prognostic factors, including age, to improve risk stratification

Proteogenomic Characterization of Highly Enriched Viable Leukemic Blasts in Acute Myeloid Leukemia: A SWOG Report

Acknowledgements: This work was funded by the following NIH/NCI/NCTN grant awards: RO1CA190661, R01CA160872, U10CA180888, U10CA180819, U24CA196175. The authors wish to gratefully acknowledge the importantcontributions of the late Dr. Stephen H. Petersdorf to SWOG and to the study S0106. The authors would like to acknowledge that a portion of the specimens were obtained from the Fred Hutch/University of Washington Hematopoietic Disorder Repository. AML is a molecularly heterogenous disease that harbors multiple genomic, epigenomic, and transcriptomic abnormalities. Despite the use of newer therapeutic agents and identification of multiple prognostic markers, most patients with AML still relapse or succumb to their disease. Understanding biological factors that determine relapse is of major clinical interest in AML. Proteins are responsible for much of the functional biology of the cells. However, few studies have examined the global proteome in AML, and, to our knowledge, studies have not previously examined the proteome in highly enriched undifferentiated AML blasts. Therefore, we have developed an integrated approach utilizing mass spectrometry-based proteomics and leveraging next generation RNA sequencing (RNAseq) to identify novel protein biomarkers associated with clinical outcome in a homogeneous population of undifferentiated viable leukemic blasts (uVLBs) from AML patients. Cryopreserved specimens from previously untreated de novo AML patients (n=27) were obtained from the SWOG Leukemia Repository. Patients were treated with dose intensive induction and consolidation as part of SWOG-9031, SWOG-9333, S0106, and S0112 studies. uVLBs were isolated from specimens using fluorescence-activated cell sorting (FACS). Targeted genome sequencing examined for genomic mutations in uVLBs, while global RNA sequencing (RNAseq) and tandem mass tag labelling followed by liquid chromatograph with tandem mass spectrometry (TMT-LC-MS/MS) were used to quantify transcript and protein expression, respectively. Analyses identified 6761 unique proteins, with 238 and 460 proteins significantly associated with complete response (CR) and overall survival (OS), respectively. There was modest overlap between the prognostically significant transcript and protein biomarkers (Figure 1). We also were able to identify and quantify aberrant proteins arising from genomic mutations . Examples of the “neoproteins” detected included proteins harboring NPM1 mutations (Figure 2a) and those harboring frameshift insertions/deletions in the terminal region of RUNX1 (Figure 2b). For validation of prognostic associations, we examined the proteome in an independent population of de novo AML patients (N=27) treated at the Fred Hutch and University of Washington. As with the SWOG patients, pre-treatment specimens were obtained from patients receiving intensive induction and consolidation with curative intent; however, OS data was not available for many of these patients. As such, the validation studies focused on CR. Patients were randomized by CR response into 9 pools (CR=6 and no CR=3 pools), and specimens were sorted for uVLBs. TMT-based LC-MS/MS quantified protein expression across pools, and analyses examined the prognostic significance of the 238 proteins from the SWOG analyses associated with CR. Thirteen of the most promising candidates were significantly associated with CR prognosis (Table 1), many of which are associated with cancer biology. Together, these studies show the feasibility and biological importance of examining the proteome in uVLBs. Studies examining for biomarkers in the proteome may be a powerful tool to uncover novel prognostic biomarkers that would otherwise not be identified by examining the genome or transcriptome. Furthermore, the multi-omics approach can be used to confirm the translation of potential neoantigens into actionable protein targets, which may lead to more cost-effective mechanisms for the development of innovative adoptive immunotherapies

Comparative proteomic analysis of advanced ovarian cancer tissue to identify potential biomarkers of responders and nonresponders to first-line chemotherapy of carboplatin and paclitaxel

Conventional treatment for advanced ovarian cancer is an initial debulking surgery followed by chemotherapy combination of carboplatin and paclitaxel. Despite initial high response, three-fourths of these women experience disease recurrence with a dismal prognosis. Patients with advanced-stage ovarian cancer who underwent cytoreductive surgery were enrolled and tissue samples were collected. Post surgery, these patients were started on chemotherapy and followed up till the end of the cycle. Fluorescence-based differential in-gel expression coupled with mass spectrometric analysis was used for discovery phase of experiments, and real-time polymerase chain reaction, Western blotting, and pathway analysis were performed for expression and functional validation of differentially expressed proteins. While aldehyde reductase, hnRNP, cyclophilin A, heat shock protein-27, and actin are upregulated in responders, prohibitin, enoyl-coA hydratase, peroxiredoxin, and fibrin-β are upregulated in the nonresponders. The expressions of some of these proteins correlated with increased apoptotic activity in responders and decreased apoptotic activity in nonresponders. Therefore, the proteins qualify as potential biomarkers to predict chemotherapy response

Coordinated mis-splicing of TMEM14C and ABCB7 causes ring sideroblast formation in SF3B1-mutant myelodysplastic syndrome

F3B1 splicing factor mutations are near-universally found in myelodysplastic syndromes (MDS) with ring sideroblasts, a clonal hematopoietic disorder characterized by abnormal erythroid cells with iron-loaded mitochondria. Despite this remarkably strong genotype-to-phenotype correlation, the mechanism by which mutant SF3B1 dysregulates iron metabolism to cause ring sideroblasts (RS) remains unclear due to an absence of physiological models of RS formation. Here, we report an induced pluripotent stem cell (iPSC) model of SF3B1-mutant MDS that for the first time recapitulates robust RS formation during in vitro erythroid differentiation. Mutant SF3B1 induces mis-splicing of ~100 genes throughout erythroid differentiation, including proposed RS driver genes TMEM14C, PPOX, and ABCB7. All three mis-splicing events reduce protein expression, notably occurring via 5' UTR alteration and reduced translation efficiency for TMEM14C. Functional rescue of TMEM14C and ABCB7, but not the non-rate-limiting enzyme PPOX, markedly decreased RS, and their combined rescue nearly abolished RS formation. Our study demonstrates that coordinated mis-splicing of mitochondrial transporters TMEM14C and ABCB7 by mutant SF3B1 sequesters iron in mitochondria, causing ring sideroblast formation

MOESM1 of Identification of potential protein biomarkers for early detection of pregnancy in cow urine using 2D DIGE and label free quantitation

Additional file 1: Figure S1. Supplimentary Table: Total identified proteins revelaed by Max quant Software