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COVID-19 is a multi-system disorder with high variability in clinical outcomes among patients who are admitted to hospital. Although some cytokines such as interleukin (IL)-6 are believed to be associated with severity, there are no early biomarkers that can reliably predict patients who are more likely to have adverse outcomes. Thus, it is crucial to discover predictive markers of serious complications.In this retrospective cohort study, we analysed samples from 455 participants with COVID-19 who had had a positive SARS-CoV-2 RT-PCR result between April 14, 2020, and Dec 1, 2020 and who had visited one of three Mayo Clinic sites in the USA (Minnesota, Arizona, or Florida) in the same period. These participants were assigned to three subgroups depending on disease severity as defined by the WHO ordinal scale of clinical improvement (outpatient, severe, or critical). Our control cohort comprised of 182 anonymised age-matched and sex-matched plasma samples that were available from the Mayo Clinic Biorepository and banked before the COVID-19 pandemic. We did a deep profiling of circulatory cytokines and other proteins, lipids, and metabolites from both cohorts. Most patient samples were collected before, or around the time of, hospital admission, representing ideal samples for predictive biomarker discovery. We used proximity extension assays to quantify cytokines and circulatory proteins and tandem mass spectrometry to measure lipids and metabolites. Biomarker discovery was done by applying an AutoGluon-tabular classifier to a multiomics dataset, producing a stacked ensemble of cutting-edge machine learning algorithms. Global proteomics and glycoproteomics on a subset of patient samples with matched pre-COVID-19 plasma samples was also done.We quantified 1463 cytokines and circulatory proteins, along with 902 lipids and 1018 metabolites. By developing a machine-learning-based prediction model, a set of 102 biomarkers, which predicted severe and clinical COVID-19 outcomes better than the traditional set of cytokines, were discovered. These predictive biomarkers included several novel cytokines and other proteins, lipids, and metabolites. For example, altered amounts of C-type lectin domain family 6 member A (CLEC6A), ether phosphatidylethanolamine (P-18:1/18:1), and 2-hydroxydecanoate, as reported here, have not previously been associated with severity in COVID-19. Patient samples with matched pre-COVID-19 plasma samples showed similar trends in muti-omics signatures along with differences in glycoproteomics profile.A multiomic molecular signature in the plasma of patients with COVID-19 before being admitted to hospital can be exploited to predict a more severe course of disease. Machine learning approaches can be applied to highly complex and multidimensional profiling data to reveal novel signatures of clinical use. The absence of validation in an independent cohort remains a major limitation of the study.Eric and Wendy Schmidt.

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Purpose:Myelofibrosis is a hematopoietic stem cell neoplasm characterized by bone marrow reticulin fibrosis, extramedullary hematopoiesis, and frequent transformation to acute myeloid leukemia. Constitutive activation of JAK/STAT signaling through mutations in JAK2, CALR, or MPL is central to myelofibrosis pathogenesis. JAK inhibitors such as ruxolitinib reduce symptoms and improve quality of life, but are not curative and do not prevent leukemic transformation, defining a need to identify better therapeutic targets in myelofibrosis.Experimental Design:A short hairpin RNA library screening was performed on JAK2V617F-mutant HEL cells. Nuclear–cytoplasmic transport (NCT) genes including RAN and RANBP2 were among top candidates. JAK2V617F-mutant cell lines, human primary myelofibrosis CD34+ cells, and a retroviral JAK2V617F-driven myeloproliferative neoplasms mouse model were used to determine the effects of inhibiting NCT with selective inhibitors of nuclear export compounds KPT-330 (selinexor) or KPT-8602 (eltanexor).Results:JAK2V617F-mutant HEL, SET-2, and HEL cells resistant to JAK inhibition are exquisitely sensitive to RAN knockdown or pharmacologic inhibition by KPT-330 or KPT-8602. Inhibition of NCT selectively decreased viable cells and colony formation by myelofibrosis compared with cord blood CD34+ cells and enhanced ruxolitinib-mediated growth inhibition and apoptosis, both in newly diagnosed and ruxolitinib-exposed myelofibrosis cells. Inhibition of NCT in myelofibrosis CD34+ cells led to nuclear accumulation of p53. KPT-330 in combination with ruxolitinib-normalized white blood cells, hematocrit, spleen size, and architecture, and selectively reduced JAK2V617F-mutant cells in vivo.Conclusions:Our data implicate NCT as a potential therapeutic target in myelofibrosis and provide a rationale for clinical evaluation in ruxolitinib-exposed patients with myelofibrosis.

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PURPOSE Standard therapy for myelofibrosis comprises Janus kinase inhibitors (JAKis), yet spleen response rates of 30%-40%, high discontinuation rates, and a lack of disease modification highlight an unmet need. Pelabresib (CPI-0610) is an investigational, selective oral bromodomain and extraterminal domain inhibitor (BETi). METHODS MANIFEST (ClinicalTrails.gov identifier: NCT02158858 ), a global, open-label, nonrandomized, multicohort, phase II study, includes a cohort of JAKi-naïve patients with myelofibrosis treated with pelabresib and ruxolitinib. The primary end point is a spleen volume reduction of ≥ 35% (SVR35) at 24 weeks. RESULTS Eighty-four patients received ≥ 1 dose of pelabresib and ruxolitinib. The median age was 68 (range, 37-85) years; 24% of patients were intermediate-1 risk, 61% were intermediate-2 risk, and 16% were high risk as per the Dynamic International Prognostic Scoring System; 66% (55 of 84) of patients had a hemoglobin level of < 10 g/dL at baseline. At 24 weeks, 68% (57 of 84) achieved SVR35, and 56% (46 of 82) achieved a total symptom score reduction of ≥ 50% (TSS50). Additional benefits at week 24 included 36% (29 of 84) of patients with improved hemoglobin levels (mean, 1.3 g/dL; median, 0.8 g/dL), 28% (16 of 57) with ≥ 1 grade improvement in fibrosis, and 29.5% (13 of 44) with > 25% reduction in JAK2V617F-mutant allele fraction, which was associated with SVR35 response ( P = .018, Fisher's exact test). At 48 weeks, 60% (47 of 79) of patients had SVR35 response. Grade 3 or 4 toxicities seen in ≥ 10% patients were thrombocytopenia (12%) and anemia (35%), leading to treatment discontinuation in three patients. 95% (80 of 84) of the study participants continued combination therapy beyond 24 weeks. CONCLUSION The rational combination of the BETi pelabresib and ruxolitinib in JAKi-naïve patients with myelofibrosis was well tolerated and showed durable improvements in spleen and symptom burden, with associated biomarker findings of potential disease-modifying activity.

Pro-inflammatory signaling is a hallmark feature of human cancer, including in myeloproliferative neoplasms (MPNs), most notably myelofibrosis (MF). Dysregulated inflammatory signaling contributes to fibrotic progression in MF; however, the individual cytokine mediators elicited by malignant MPN cells to promote collagen-producing fibrosis and disease evolution remain yet to be fully elucidated. Previously we identified a critical role for combined constitutive JAK/STAT and aberrant NF-kB pro-inflammatory signaling in myelofibrosis development. Using single-cell transcriptional and cytokine-secretion studies of primary MF patient cells and the hMPLW515L murine model of myelofibrosis, we extend this previous work and delineate the role of CXCL8/CXCR2 signaling in MF pathogenesis and bone marrow fibrosis progression. MF patient hematopoietic stem/progenitor cells are enriched for a CXCL8/CXCR2 gene signature and display enhanced proliferation and fitness in response to exogenous CXCL8 ligand in vitro. Genetic deletion of Cxcr2 in the hMPLW515L adoptive transfer model abrogates fibrosis and extends overall survival, and pharmacologic inhibition of the CXCR1/2 pathway improves hematologic parameters, attenuates bone marrow fibrosis, and synergizes with JAK inhibitor therapy. Our mechanistic insights provide a rationale for therapeutic targeting of the CXCL8/CXCR2 pathway in MF patients.

Diagnostic criteria for primary myelofibrosis as defined by the 2017 revised World Health Organization (WHO) classification system incorporate clinical and laboratory findings, including driver mutational status (JAK2, MPL, CALR. and triple negative). The WHO emphasized the role of histopathology in making an accurate diagnosis of primary myelofibrosis and successfully incorporated a fibrosis scoring system and scoring schemas for collagen fibrosis and osteosclerosis. These steps represent a significant addition to the standardization of myelofibrosis evaluation and minimize the risk for misdiagnosis. This article reviews important pathologic considerations along with highlights of potentially relevant pitfalls relevant to histopathological diagnosis of myelofibrosis.

BackgroundArtificial intelligence (AI) is rapidly fueling a fundamental transformation in the practice of pathology. However, AI’s clinical integration remains challenging, with no AI algorithms to date enjoying 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.MethodsPerspectives 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 analyzed for consensus; and 3) a repeat survey of items not reaching consensus to obtain further expert consensus.FindingsConsensus 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.InterpretationThis is the first systematic consensus study detailing the expected short/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.FundingThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Myelofibrosis is characterized by splenomegaly, symptoms, cytopenias, and bone marrow (BM) fibrosis. Pelabresib is an investigational, oral, small-molecule BET inhibitor designed to selectively inhibit the BD1 and BD2 bromodomains of BET proteins.Evaluation of pelabresib combined with ruxolitinib in patients with myelofibrosis.In Arm 3 of the Phase 2 MANIFEST study (NCT02158858), JAKi-naïve myelofibrosis patients are treated with pelabresib combined with ruxolitinib. In Arm 2, myelofibrosis patients with suboptimal response to ruxolitinib are treated with pelabresib as 'add-on' to ruxolitinib (Arm 2A: transfusion-dependent [TD]; Arm 2B: non-TD). The primary endpoints are ≥35% spleen volume reduction (SVR35) at Week 24 for Arms 3 and 2B and TD to transfusion independence (TI) in Arm 2A. The key secondary endpoint is ≥50% total symptom score reduction (TSS50) at Week 24; in Arm 2A, SVR35 is an additional key secondary endpoint. BM biopsies to assess BM fibrosis and safety data are also evaluated.As of September 2021, at Week 24 in Arm 3 (N=84), 68% (57/84) of patients achieved SVR35 (median change: -50%), and 56% (46/82) of patients achieved TSS50 (median change: -59%). At Week 24 in Arm 2 (N=86), 20% (16/81; 17% in Arm 2A and 26% in Arm 2B) of patients achieved SVR35 (median change: -18%), and 37% (30/81) of patients achieved TSS50 (median change: -47%). In Arm 2A, the TD to TI rate was 16% (6/38). At Week 24, BM fibrosis improvement ≥ 1 grade was achieved in 28% (16/57) and 26% (12/47) of patients in Arms 3 and 2, respectively. Hematologic treatment-emergent adverse events (TEAEs) included thrombocytopenia, in 52% (≥Grade 3: 12%) and 52% (≥Grade 3: 33%) of patients, and anemia, in 42% (≥Grade 3: 35%) and 27% (≥Grade 3: 19%) of patients in Arms 3 and 2, respectively. Low-grade gastrointestinal TEAEs and respiratory infections were observed but rarely resulted in discontinuation.In ruxolitinib treatment-naïve and previously treated patients with myelofibrosis, pelabresib combined with ruxolitinib resulted in splenic and symptom responses and BM fibrosis improvement and was generally well tolerated. The Phase 3 MANIFEST-2 study is evaluating pelabresib combined with ruxolitinib in JAKi treatment-naïve patients with myelofibrosis (NCT04603495).

SUMMARYPro-inflammatory signaling is a hallmark feature of human cancer, including in myeloproliferative neoplasms (MPNs), most notably myelofibrosis (MF). Dysregulated inflammatory signaling contributes to fibrotic progression in MF; however, the individual cytokine mediators elicited by malignant MPN cells to promote collagen-producing fibrosis and disease evolution remain yet to be fully elucidated. Previously we identified a critical role for combined constitutive JAK/STAT and aberrant NF-κB pro-inflammatory signaling in myelofibrosis development. Using single-cell transcriptional and cytokine-secretion studies of primary MF patient cells and two separate murine models of myelofibrosis, we extend this previous work and delineate the role of CXCL8/CXCR2 signaling in MF pathogenesis and bone marrow fibrosis progression. MF patient hematopoietic stem/progenitor cells are enriched in a CXCL8/CXCR2 gene signature and display dose-dependent proliferation and fitness in response to exogenous CXCL8 ligand in vitro. Genetic deletion of Cxcr2 in the hMPLW515L adoptive transfer model abrogates fibrosis and extends overall survival, and pharmacologic inhibition of the CXCR1/2 pathway improves hematologic parameters, attenuates bone marrow fibrosis, and synergizes with JAK inhibitor therapy. Our mechanistic insights provide a rationale for therapeutic targeting of the CXCL8/CXCR2 pathway in MF patients at risk for continued fibrotic progression.

Simple Summary Familiarity with the updated fourth edition WHO classification of lymphoid malignancies released in 2016, and the new terminology introduced, is crucial for oncologists, pathologists and radiologists. It is mandatory to be aware of rare variants of T-cell lymphomas, specifically mature T-cell lymphomas, including clinicopathologic keys and the most common imaging features and sites of involvement for each subtype. Even though some of these disorders may have perceptible clinical and imaging features, they may overlap with more common disorders, causing delay in diagnosis and treatment. Understanding the appropriate clinical setting and imaging findings will help radiologists to include these disorders in their differential diagnosis. Imaging plays a pivotal role in subclassifying these subtypes of MTCLs, affecting prognosis and treatment implications. Many of these disorders if diagnosed early can be potentially treatable, and early, aggressive intervention may be lifesaving. Abstract Understanding the pathogenesis and molecular biology of malignant lymphomas is challenging, given the complex nature and incongruity of these disorders. The classification of lymphoma is continually evolving to account for advances in clinical, pathological, molecular biology and cytogenetic aspects, which impact our understanding of these disorders. The latest fourth edition of the WHO classification of lymphoid malignancies was released in 2016 to account for these changes. Additionally, unlike B-cell lymphomas (BCL), T-cell lymphomas (TCL) are uncommon, and may be sporadically experienced in clinical practice. These disorders are rare, thus early diagnosis is challenging for both physicians and radiologists, owing to the overlap in clinical and imaging features with other, more common disorders. We aim to discuss some rare variants of T-cell lymphomas, including clinicopathologic and imaging features, as well as to give a glimpse of the updates contained within the new 2016 WHO classification.

Preclinical Rationale: Myelofibrosis (MF) is a chronic myeloproliferative neoplasm for which there are limited therapies. TGFβ plays a pivotal role in the pathobiology of MF by not only promoting bone marrow fibrosis (BMF) and collagen deposition, but also by enhancing the dormancy of normal but not MF hematopoietic stem cells (HSCs). TGFβ has also previously been reported to inhibit normal megakaryocyte (MK) production (Bruno et al Blood 1998). TGFβ1 promotes the synthesis of collagen by normal human mesenchymal stromal cells (MSCs) and activates the TGFβ receptor I/SMAD pathway as well as non-canonical TGFβ pathways. We generated MKs from MF subject mononuclear cells (MNCs) and showed that they elaborated significantly greater levels of TGFβ1 than TGFβ2/3 TGFβ1 treatment reduced the numbers of hematopoietic colonies generated by normal but not MF MNCs. Treatment of MSCs with AVID200, a potent TGFβ1/3 protein trap, significantly decreased MSC proliferation, phosphorylation of SMAD2, and collagen expression. Robust expression of pSMAD2 was observed in the absence of exogenous TGFβ in normal donor or MF-MKs, Addition of AVID200 to -MKs decreased pSMAD2 without affecting total SMAD2/3, indicating that AVID200 blocks the effects of autocrine TGFβ produced by MKs and led to increased numbers of MKs. Moreover, treatment of primary MF MNCs with AVID200 led to increased numbers of progenitor cells with wild type JAK2 and a reduction of mutated colonies. AVID200 blocked TGFβ1-induced p57Kip2 expression and SMAD2 activation by MF MNCs allowing the normal progenitor cells to preferentially cycle, proliferate, and form hematopoietic colonies. Clinical Trial Design: Based on these findings, a phase 1 trial of AVID200 is ongoing in INT-2/high risk MF subjects resistant or intolerant to ruxolitinib; baseline platelet count of ≥ 25 x 109/L, and grade 2/3 BMF. Subjects received intravenous AVID200 (Lots A and B) in dose cohorts of 180 mg/m2 (A), 550 mg/m2 (A), 180 mg/m2 (B) on Day 1 of a 21 day cycle. Cohorts of 3 subjects with a target toxicity rate of 30% were enrolled to estimate the maximum tolerated dose (MTD). A modified toxicity probability interval design was used. Response was assessed by IWG/ELN criteria after 6 cycles of AVID200. Subjects attaining at least a CI or SD with a decrease in BMF by ≥1 grade, continued AVID200. Clinical Trial Results: 10 subjects were enrolled (1 withdrew before receiving treatment) and 9 were treated with AVID200 and were evaluable for DLT assessment [Table1]. Median time after ruxolitinib discontinuation was 3.5 months (0.5-12.2). No DLTs were observed. Grade 3/4 AEs (regardless of attribution) were observed in 6 (66.7%) subjects. Grade 3/4 non-hematologic AEs observed were epistaxis (1, 11.1%), extraocular muscle paresis (1, 11.1%), fatigue (1, 11.1%) and rash (1, 11.1%). Grade 3/4 hematologic AEs were anemia (3, 33.3%) and thrombocytopenia (2, 22.2%) [Table 2]. The median number of cycles received was 5.7 (range 0 - 12). 5 subjects received 6+ cycles and were evaluable. CI occurred in 2 subjects [anemia, spleen and TSS (n=1); TSS (n=1)] 1 of which is still being treated, 2 subjects had SD, 1 subject with 21% blasts prior to study treatment had progressive MPN-BP. 4 subjects failed to reach response evaluation after 6 cycles, 2 had PD due to increasing splenomegaly, 1 subject received an allogeneic transplant and 1 is still being treated [Cycle 2]. The median platelet count at baseline was 114 (range: 42-290) and 159 after cycle 6 [Figure 1]. Maximum changes in platelets from baseline was +64% [range -73%, 169%] in all subjects. 7 subjects had an increase in platelets from baseline during treatment. 2 subjects normalized their platelet count from thrombocytopenic levels. The effect of AVID200 on BMF is currently being examined. 2 subjects remain on treatment. Conclusions: AVID200 a TGFβ1/3 protein trap is well tolerated in advanced MF subjects. Clinical responses were observed at the 550 mg dose and the expansion efficacy cohorts at doses 2 and 3 are enrolling 12 additional subjects. Furthermore, AVID200 therapy improved thrombocytopenia in MF subjects which may be due to AVID200 inhibiting the effects of TGFβ1 on normal MKpoiesis. Updated subject safety and efficacy data along with correlative data will be presented. Disclosures Mascarenhas: Celgene, Prelude, Galecto, Promedior, Geron, Constellation, and Incyte: Consultancy; Incyte, Kartos, Roche, Promedior, Merck, Merus, Arog, CTI Biopharma, Janssen, and PharmaEssentia: Other: Research funding (institution). Kuykendall:Blueprint Medicines: Research Funding; BMS: Research Funding; Incyte: Research Funding; Novartis: Research Funding. Komrokji:Jazz: Honoraria, Speakers Bureau; Abbvie: Honoraria; Agios: Speakers Bureau; BMS: Honoraria, Speakers Bureau; Geron: Honoraria; Incyte: Honoraria; Acceleron: Honoraria; Novartis: Honoraria. Gerds:Gilead Sciences: Research Funding; Imago Biosciences: Research Funding; Sierra Oncology: Research Funding; Celgene: Consultancy, Research Funding; Roche/Genentech: Research Funding; CTI Biopharma: Consultancy, Research Funding; Apexx Oncology: Consultancy; AstraZeneca/MedImmune: Consultancy; Pfizer: Research Funding; Incyte Corporation: Consultancy, Research Funding. Migliaccio:Novartis: Research Funding. O'Connor-McCourt:Forbius: Current Employment. Tremblay:Forius: Current Employment. Nadler:Forbius: Consultancy; Nadler Pharma Associates: Current Employment; Symphogen: Consultancy; Iksuda Therapeutics: Consultancy; Tessa Therapeutics: Consultancy. Mesa:Celgene: Research Funding; Genetech: Research Funding; Samus: Research Funding; Promedior: Research Funding; CTI: Research Funding; LaJolla Pharma: Consultancy; Incyte: Research Funding; Sierra Onc: Consultancy; Abbvie: Research Funding; Novartis: Consultancy. Hoffman:Forbius: Consultancy; Abbvie: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Dompe: Research Funding; Protagonist: Consultancy.

Objectives To assess and improve the assistive role of a deep, densely connected convolutional neural network (CNN) to hematopathologists in differentiating histologic images of Burkitt lymphoma (BL) from diffuse large B-cell lymphoma (DLBCL). Methods A total of 10,818 images from BL (n = 34) and DLBCL (n = 36) cases were used to either train or apply different CNNs. Networks differed by number of training images and pixels of images, absence of color, pixel and staining augmentation, and depth of the network, among other parameters. Results Cases classified correctly were 17 of 18 (94%), nine with 100% of images correct by the best performing network showing a receiver operating characteristic curve analysis area under the curve 0.92 for both DLBCL and BL. The best performing CNN used all available training images, two random subcrops per image of 448 × 448 pixels, random H&E staining image augmentation, random horizontal flipping of images, random alteration of contrast, reduction on validation error plateau of 15 epochs, block size of six, batch size of 32, and depth of 22. Other networks and decreasing training images had poorer performance. Conclusions CNNs are promising augmented human intelligence tools for differentiating a subset of BL and DLBCL cases.

While our understanding of the biology of CD30 in lymphoma continues to evolve, our need to detect and measure its expression at the protein level remains critically important for diagnosis and patient care. In addition to its diagnostic and prognostic utility, CD30 has emerged as a vehicle for drug targeting through the antibody-drug conjugate brentuximab-vedotin (BV). Given the numerous ways that CD30 is utilized and its emergence as a predictive/prognostic biomarker, pathologists must come to a general consensus on the best reporting structure and methodology to ensure appropriate patient care. In this manuscript, we review the indications for testing, various modalities for testing, technical challenges, pitfalls, and potential standards of reporting. The following questions will try to be addressed in the current review article: What defines a "POSITIVE" level of CD30 expression?; How do we evaluate and report CD30 expression?; What are the caveats in the evaluation of CD30 expression?

Essential thrombocythemia (ET) and polycythemia vera (PV) are myeloproliferative neoplasms (MPNs) characterized by an increased risk of developing venous and arterial thromboses and of evolution to myelofibrosis or acute leukemia (1). MPNs are recognized as a major cause of splanchnic vein thromboses (SVT), which include hepatic, splenic, portal and mesenteric vein thromboses (2). Patients with SVT are at an increased risk of developing bleeding events and arterial thrombotic events (3), as well as recurrent SVT and the use of anticoagulation and cytoreduction do not clearly modify this risk (3–5). Management of SVT in MPN patients remains a challenge and most therapeutic recommendations are based on retrospective analyses (6). Recently, De Stefano reported that hydroxyurea failed to prevent recurrent thromboses in the splanchnic vasculature in patients with a prior SVT (7). We conducted a prospective, open-label, multi-center phase II clinical trial of Pegylated Interferon Alfa-2a (PEG) in 20 subjects with SVT and an MPN, who represented a cohort of patients who participated in the Myeloproliferative Disorders - Research Consortium (MPD-RC) 111 trial (). MPD-RC 111 was a prospective study of patients with high-risk ET/PV who were resistant or intolerant to hydroxyurea (HU), but prior HU therapy was not a requirement for patients to enter the SVT cohort. Here we report the outcomes of the 20 SVT patients who were treated with PEG.

Balanced translocations have diagnostic and prognostic value in B-cell lymphoproliferative disorders (LPDs). Most of these translocations involve the juxtaposition of a strong immunoglobulin (Ig) enhancer to proto-oncogenes, such as BCL2, BCL6, and MYC, leading to their overexpression. These rearrangements generally do not result in mRNA fusions, and fluorescent in situ hybridization (FISH) remains the gold standard for assessing of recurrent translocations in LPDs. With the growing use of massively parallel sequencing for the detection of both point mutations and large structural rearrangements, we aimed at evaluating the utility of this method for the molecular work-up of B-cell LPDs side by side with FISH. We describe a method using solution capture for enrichment of known translocation breakpoints and massively parallel sequencing for the detection of balanced translocation in formalin-fixed tissues with a B-cell LPD. We detected a total of 57 rearrangements with a high concordance of 94.2% when compared to FISH. We detected translocations between BCL2, BCL6, and MYC and the three Ig loci and non-Ig loci, including novel partners for MYC and BCL6. In addition, massively parallel sequencing allowed a detailed analysis of the structure of the resulting chromosomal fusions. Our comparison shows the feasibility of using massively parallel sequencing for detecting balanced translocations in B-cell LPDs and advantages and disadvantages to both methods, and how they can complement each other.

The diagnosis of classic Hodgkin lymphoma requires immunohistochemical confirmation in most cases and one can argue for these studies as standard-of-care in the diagnostic workup. The authors propose a panel of studies for primary identification of CHL to include: CD3, CD20, CD15, CD30 and PAX5. When pattern discordances are identified, additional assessment is recommended. In the case of overexpression of B lineage markers by Hodgkin/Reed-Sternberg cells, or a differential diagnosis that includes large B-cell lymphoma or variants, additional markers recommended are: CD45, OCT2, BOB1, CD79a and MUM1/IRF4. If primary mediastinal large B cell lymphoma is considered in the differential diagnosis, suggested additional markers include: P63, CD23, CD45 and CD79a. When considering a differential diagnosis that includes anaplastic large cell lymphoma we suggest: ALK, CD45, pan T cell antigens (such as CD2, CD5, CD7, and CD43), and cytotoxic markers (granzyme, perforin, and TIA1). If peripheral T cell lymphoma or T cell lymphomas of follicular helper origin are considered in the differential diagnosis, the following panel is recommended: pan T cell antigens, CD4, CD8, one or more follicular dendritic cell markers, and assessment for Epstein-Barr virus (EBV) infection, preferably EBV encoded RNA (EBER) as assessed by in situ hybridization When the differential diagnosis includes nodular lymphocyte predominant Hodgkin lymphoma, recommended additional studies include OCT2, CD21 and/or CD23, PD1, and assessment for EBV infection. The authors recognize that these panels may not be adequate to completely characterize other lymphomas, but these panels will usually be sufficient to distinguish classic Hodgkin lymphoma from other lymphoma types.

Purpose: Myelofibrosis is a hematopoietic stem cell neoplasm characterized by bone marrow reticulin fibrosis, extramedullary hematopoiesis, and frequent transformation to acute myeloid leukemia. Constitutive activation of JAK/STAT signaling through mutations in JAK2, CALR, or MPL is central to myelofibrosis pathogenesis. JAK inhibitors such as ruxolitinib reduce symptoms and improve quality of life, but are not curative and do not prevent leukemic transformation, defining a need to identify better therapeutic targets in myelofibrosis. Experimental Design: A short hairpin RNA library screening was performed on JAK2V617F-mutant HEL cells. Nuclear–cytoplasmic transport (NCT) genes including RAN and RANBP2 were among top candidates. JAK2V617F-mutant cell lines, human primary myelofibrosis CD34+ cells, and a retroviral JAK2V617F-driven myeloproliferative neoplasms mouse model were used to determine the effects of inhibiting NCT with selective inhibitors of nuclear export compounds KPT-330 (selinexor) or KPT-8602 (eltanexor). Results: JAK2V617F-mutant HEL, SET-2, and HEL cells resistant to JAK inhibition are exquisitely sensitive to RAN knockdown or pharmacologic inhibition by KPT-330 or KPT-8602. Inhibition of NCT selectively decreased viable cells and colony formation by myelofibrosis compared with cord blood CD34+ cells and enhanced ruxolitinib-mediated growth inhibition and apoptosis, both in newly diagnosed and ruxolitinib-exposed myelofibrosis cells. Inhibition of NCT in myelofibrosis CD34+ cells led to nuclear accumulation of p53. KPT-330 in combination with ruxolitinib-normalized white blood cells, hematocrit, spleen size, and architecture, and selectively reduced JAK2V617F-mutant cells in vivo. Conclusions: Our data implicate NCT as a potential therapeutic target in myelofibrosis and provide a rationale for clinical evaluation in ruxolitinib-exposed patients with myelofibrosis.

BACKGROUND COVID-19 is caused by the SARS-CoV-2 virus and has strikingly heterogeneous clinical manifestations, with most individuals contracting mild disease but a substantial minority experiencing fulminant cardiopulmonary symptoms or death. The clinical covariates and the laboratory tests performed on a patient provide robust statistics to guide clinical treatment. Deep learning approaches on a data set of this nature enable patient stratification and provide methods to guide clinical treatment. OBJECTIVE Here, we report on the development and prospective validation of a state-of-the-art machine learning model to provide mortality prediction shortly after confirmation of SARS-CoV-2 infection in the Mayo Clinic patient population. METHODS We retrospectively constructed one of the largest reported and most geographically diverse laboratory information system and electronic health record of COVID-19 data sets in the published literature, which included 11,807 patients residing in 41 states of the United States of America and treated at medical sites across 5 states in 3 time zones. Traditional machine learning models were evaluated independently as well as in a stacked learner approach by using AutoGluon, and various recurrent neural network architectures were considered. The traditional machine learning models were implemented using the AutoGluon-Tabular framework, whereas the recurrent neural networks utilized the TensorFlow Keras framework. We trained these models to operate solely using routine laboratory measurements and clinical covariates available within 72 hours of a patient’s first positive COVID-19 nucleic acid test result. RESULTS The GRU-D recurrent neural network achieved peak cross-validation performance with 0.938 (SE 0.004) as the area under the receiver operating characteristic (AUROC) curve. This model retained strong performance by reducing the follow-up time to 12 hours (0.916 [SE 0.005] AUROC), and the leave-one-out feature importance analysis indicated that the most independently valuable features were age, Charlson comorbidity index, minimum oxygen saturation, fibrinogen level, and serum iron level. In the prospective testing cohort, this model provided an AUROC of 0.901 and a statistically significant difference in survival (P CONCLUSIONS Our deep learning approach using GRU-D provides an alert system to flag mortality for COVID-19–positive patients by using clinical covariates and laboratory values within a 72-hour window after the first positive nucleic acid test result.

Recent clinical trials have suggested that blockade of interleukin-1 (IL-1) can have a favorable impact on patients with myocardial infarction and heart failure. However, the mechanism of antagonism of this specific cytokine in mediating cardiac disease remains unclear. Hence, we sought to determine the influence of IL-1 blockade on acute hypertensive remodeling.Transverse aortic constriction was performed in C57BL mice with or without intraperitoneal administration of interleukin 1 receptor antagonism (IL-1Ra). Function, structure, and molecular diagnostics were subsequently performed and analyzed.Six weeks after transverse aortic constriction, a progressive decline of ejection fraction and increases in left ventricle mass and dimensions were effectively mitigated with IL-1Ra. Transverse aortic constriction resulted in an expected profile of hypertrophic markers including myosin heavy chain, atrial natriuretic peptide, and skeletal muscle actin, which were all significantly lower in IL-1Ra treated mice. Although trichrome staining 2 weeks after transverse aortic constriction demonstrated similar levels of fibrosis, IL-1ra-reduced expression of collagen-1, tissue inhibitor of metallopeptidase 1, and periostin. Investigating the angiogenic response to pressure overload, similar levels of vascular endothelial growth factor were observed, but IL-1Ra was associated with more stromal cell-derived factor-1. Immune cell infiltration (macrophages and lymphocytes) was also decreased in IL-1Ra treated mice. Similarly, cytokine concentrations of IL-1, IL-18, and IL-6 were all reduced in IL-1Ra-treated animals.Interleukin-1Ra prevents the progression toward heart failure associated with acute pressure overload. This functional response was associated with reductions in mediators of fibrosis, cellular infiltration, and cytokine production. These results provide mechanistic insight into recent clinical trials and could springboard future investigations in patients with pressure-overload-based cardiomyopathies.

Advances in digital pathology have allowed a number of opportunities such as decision support using artificial intelligence (AI). The application of AI to digital pathology data shows promise as an aid for pathologists in the diagnosis of haematological disorders. AI-based applications have embraced benign haematology, diagnosing leukaemia and lymphoma, as well as ancillary testing modalities including flow cytometry. In this review, we highlight the progress made to date in machine learning applications in haematopathology, summarise important studies in this field, and highlight key limitations. We further present our outlook on the future direction and trends for AI to support diagnostic decisions in haematopathology.

Myeloproliferative neoplasms (MPN) that have evolved into accelerated or blast phase disease (MPN-AP/BP) have poor outcomes with limited treatment options and therefore represent an urgent unmet need. We have previously demonstrated in a multicenter, phase 1 trial conducted through the Myeloproliferative Neoplasms Research Consortium that the combination of ruxolitinib and decitabine is safe and tolerable and is associated with a favorable overall survival (OS). In this phase 2 trial, 25 patients with MPN-AP/BP were treated at the recommended phase 2 dose of ruxolitinib 25 mg twice daily for the induction cycle followed by 10 mg twice daily for subsequent cycles in combination with decitabine 20 mg/m2 for 5 consecutive days in a 28-day cycle. Nineteen patients died during the study follow-up. The median OS for all patients on study was 9.5 months (95% confidence interval, 4.3-12.0). Overall response rate (complete remission + incomplete platelet recovery + partial remission) was 11/25 (44%) and response was not associated with improved survival. We conclude that the combination of decitabine and ruxolitinib was well tolerated, demonstrated favorable OS, and represents a therapeutic option for this high-risk patient population. This trial was registered at www.clinicaltrials.gov as #NCT02076191.

Systemic inflammation is a potentially debilitating complication of thoracic surgeries with significant physical and economic morbidity. There is compelling evidence for the role of the central nervous system in regulating inflammatory processes through humoral mechanisms. Activation of the afferent vagus nerve by cytokines triggers anti-inflammatory responses. Peripheral electrical stimulation of the vagus nerve in vivo during lethal endotoxemia in rats inhibited tumor necrosis factor synthesis and prevented shock development. However, the vagal regulatory role of systemic inflammation after lung lobectomy is unknown. One hundred patients who underwent lobectomy via thoracotomy were recruited and equally randomized to treated group or controls. Intermittent stimulation of the auricular branch of vagus nerve in the triangular fossa was applied in the treated group using neurostimulator V (Ducest®, Germany), starting 24 h preoperatively and continued till the 4th postoperative day (POD). Inflammatory interleukins (IL) were analyzed using ELISA preoperatively, on the 1st and 4th POD. On the 1st POD, patients who underwent neurostimulation had reduced serum concentrations of CRP (p = 0.01), IL6 (p = 0.02) but elevated IL10 (p = 0.03) versus controls. On the 4th POD, serum concentrations of CRP, IL6 and IL10 were similar in both groups. Moreover, the treated group was associated with lower incidence of pneumonia (p = 0.04) and shorter hospitalization time (p = 0.04) versus controls. Modulations in the brain stem caused by noninvasive transcutaneous stimulation of the vagus nerve after lung lobectomy attenuate the acute postsurgical inflammatory response by the regulation of IL6 and IL10, resulting in reduced incidence of postoperative pneumonia and short hospitalization time. NCT03204968.

Flow cytometric (FC) immunophenotyping is critical but time-consuming in diagnosing minimal residual disease (MRD). We evaluated whether human-in-the-loop artificial intelligence (AI) could improve the efficiency of clinical laboratories in detecting MRD in chronic lymphocytic leukemia (CLL). We developed deep neural networks (DNN) that were trained on a 10-color CLL MRD panel from treated CLL patients, including DNN trained on the full cohort of 202 patients (F-DNN) and DNN trained on 138 patients with low-event cases (MRD < 1000 events) (L-DNN). A hybrid DNN approach was utilized, with F-DNN and L-DNN applied sequentially to cases. “Ground truth” classification of CLL MRD was confirmed by expert analysis. The hybrid DNN approach demonstrated an overall accuracy of 97.1% (95% CI: 84.7–99.9%) in an independent cohort of 34 unknown samples. When CLL cells were reported as a percentage of total white blood cells, there was excellent correlation between the DNN and expert analysis [r > 0.999; Passing–Bablok slope = 0.997 (95% CI: 0.988–0.999) and intercept = 0.001 (95% CI: 0.000–0.001)]. Gating time was dramatically reduced to 12 s/case by DNN from 15 min/case by the manual process. The proposed DNN demonstrated high accuracy in CLL MRD detection and significantly improved workflow efficiency. Additional clinical validation is needed before it can be fully integrated into the existing clinical laboratory practice.

Multiple myeloma (MM) is a neoplasm characterized by proliferation of clonal plasma cells (PCs) and a combination of clinical manifestations. Flow cytometry is an important method for diagnosing and monitoring of MM. Cytogenetic profiling of neoplastic PCs provides important prognostic information. Although stem cell transplantation (SCT) has significantly improved the overall survival of patients with MM, most SCT recipients relapse. We have studied the immunophenotypic and cytogenetic dissimilarities in the neoplastic PCs before SCT and after relapse in patients with initial complete remission, and investigated a possible influence of such dissimilarities on the patients’ survival. We retrospectively reviewed results of flow cytometric studies of bone marrow specimens from 46 patients with MM who underwent SCT, demonstrated a complete initial response, but subsequently relapsed. In nine of these patients, fluorescence in situ hybridization (FISH) studies were performed both pre-SCT and post-relapse. We have shown a significant flow cytometric and cytogenetic diversity of the neoplastic PCs in relapsed MM post-SCT. Such changes were detected in a considerable number of cases (47.8% and 44.4%, respectively). The most frequent cytogenetic changes indicate an emergence of possibly a more aggressive PC clone, known to be associated with worse prognosis and poorer outcome. Our study has demonstrated that the acquisition of immunophenotypic changes predicts worse overall survival.

Background: Breast tumor subtyping has failed to provide impact in susceptibility genetics. The PAM50 assay categorizes breast tumors into: Luminal A, Luminal B, HER2-enriched and Basal-like. However, tumors are often more complex than simple categorization can describe. The identification of heritable tumor characteristics has potential to decrease heterogeneity and increase power for gene finding. Methods: We used 911 sporadic breast tumors with PAM50 expression data to derive tumor dimensions using principal components (PC). Dimensions in 238 tumors from high-risk pedigrees were compared with the sporadic tumors. Proof-of-concept gene mapping, informed by tumor dimension, was performed using Shared Genomic Segment (SGS) analysis. Results: Five dimensions (PC1-5) explained the majority of the PAM50 expression variance: three captured intrinsic subtype, two were novel (PC3, PC5). All five replicated in 745 TCGA tumors. Both novel dimensions were significantly enriched in the high-risk pedigrees (intrinsic subtypes were not). SGS gene-mapping in a pedigree identified a 0.5 Mb genome-wide significant region at 12q15. This region segregated through 32 meioses to 8 breast cancer cases with extreme PC3 tumors (P = 2.6 × 10−8). Conclusions: PC analysis of PAM50 gene expression revealed multiple independent, quantitative measures of tumor diversity. These tumor dimensions show evidence for heritability and potential as powerful traits for gene mapping. Impact: Our study suggests a new approach to describe tumor expression diversity, provides new avenues for germline studies, and proposes a new breast cancer locus. Similar reparameterization of expression patterns may inform other studies attempting to model the effects of tumor heterogeneity. Cancer Epidemiol Biomarkers Prev; 27(6); 644–52. ©2018 AACR.

Given the frequent and largely incurable occurrence of multiple myeloma, identification of germline genetic mutations that predispose cells to multiple myeloma may provide insight into disease etiology and the developmental mechanisms of its cell of origin, the plasma cell (PC). Here, we identified familial and early-onset multiple myeloma kindreds with truncating mutations in lysine-specific demethylase 1 (LSD1/KDM1A), an epigenetic transcriptional repressor that primarily demethylates histone H3 on lysine 4 and regulates hematopoietic stem cell self-renewal. In addition, we found higher rates of germline truncating and predicted deleterious missense KDM1A mutations in patients with multiple myeloma unselected for family history compared with controls. Both monoclonal gammopathy of undetermined significance (MGUS) and multiple myeloma cells have significantly lower KDM1A transcript levels compared with normal PCs. Transcriptome analysis of multiple myeloma cells from KDM1A mutation carriers shows enrichment of pathways and MYC target genes previously associated with myeloma pathogenesis. In mice, antigen challenge followed by pharmacologic inhibition of KDM1A promoted PC expansion, enhanced secondary immune response, elicited appearance of serum paraprotein, and mediated upregulation of MYC transcriptional targets. These changes are consistent with the development of MGUS. Collectively, our findings show that KDM1A is the first autosomal-dominant multiple myeloma germline predisposition gene providing new insights into its mechanistic roles as a tumor suppressor during post-germinal center B-cell differentiation. Significance: KDM1A is the first germline autosomal dominant predisposition gene identified in multiple myeloma and provides new insights into multiple myeloma etiology and the mechanistic role of KDM1A as a tumor suppressor during post-germinal center B-cell differentiation. Cancer Res; 78(10); 2747–59. ©2018 AACR.

April 12, 2017 marked a significant day in the evolution of digital pathology in the United States, when the US Food and Drug Administration announced its approval of the Philips IntelliSite Pathology Solution for primary diagnosis in surgical pathology. Although this event is expected to facilitate more widespread adoption of whole slide imaging for clinical applications in the United States, it also raises a number of questions as to the means by which pathologists might choose to incorporate this technology into their clinical practice. This article from the College of American Pathologists Digital Pathology Committee reviews frequently asked questions on this topic and provides answers based on currently available information.