Using Targeted Transcriptome and Machine Learning of Pre- and Post-Transplant Bone Marrow Samples to Predict Acute Graft-versus-Host Disease and Overall Survival after Allogeneic Stem Cell Transplantation.

Acute graft-versus-host disease (aGvHD) remains a major cause of morbidity and mortality after allogeneic hematopoietic stem cell transplantation (HSCT). We performed RNA analysis of 1408 candidate genes in bone marrow samples obtained from 167 patients undergoing HSCT. RNA expression data were used in a machine learning algorithm to predict the presence or absence of aGvHD using either random forest or extreme gradient boosting algorithms. Patients were randomly divided into training (2/3 of patients) and validation (1/3 of patients) sets. Using post-HSCT RNA data, the machine learning algorithm selected 92 genes for predicting aGvHD that appear to play a role in PI3/AKT, MAPK, and FOXO signaling, as well as microRNA. The algorithm selected 20 genes for predicting survival included genes involved in MAPK and chemokine signaling. Using pre-HSCT RNA data, the machine learning algorithm selected 400 genes and 700 genes predicting aGvHD and overall survival, but candidate signaling pathways could not be specified in this analysis. These data show that NGS analyses of RNA expression using machine learning algorithms may be useful biomarkers of aGvHD and overall survival for patients undergoing HSCT, allowing for the identification of major signaling pathways associated with HSCT outcomes and helping to dissect the complex steps involved in the development of aGvHD. The analysis of pre-HSCT bone marrow samples may lead to pre-HSCT interventions including choice of remission induction regimens and modifications in patient health before HSCT.

Homologous Recombination Abnormalities Associated With BRCA1/2 Mutations as Predicted by Machine Learning of Targeted Next-Generation Sequencing Data.

Background: Homologous recombination deficiency (HRD) is the hallmark of breast cancer gene 1/2 (BRCA1/2)-mutated tumors and the unique biomarker for predicting response to double-strand break (DSB)-inducing drugs. The demonstration of HRD in tumors with mutations in genes other than BRCA1/2 is considered the best biomarker of potential response to these DSB-inducer drugs. Objectives: We explored the potential of developing a practical approach to predict in any tumor the presence of HRD that is similar to that seen in tumors with BRCA1/2 mutations using next-generation sequencing (NGS) along with machine learning (ML). Design: We use copy number alteration (CNA) generated from routine-targeted NGS data along with a modified naïve Bayesian model for the prediction of the presence of HRD. Methods: The CNA from NGS of 434 targeted genes was analyzed using CNVkit software to calculate the log2 of CNA changes. The log2 values of various sequencing reads (bins) were used in ML to train the system on predicting tumors with BRCA1/2 mutations and tumors with abnormalities similar to those detected in BRCA1/2 mutations. Results: Using 31 breast or ovarian cancers with BRCA1/2 mutations and 84 tumors without mutations in any of 12 homologous recombination repair (HRR) genes, the ML demonstrated high sensitivity (90%, 95% confidence interval [CI] = 73%-97.5%) and specificity (98%, 95% CI = 90%-100%). Testing of 114 tumors with mutations in HRR genes other than BRCA1/2 showed 39% positivity for HRD similar to that seen in BRCA1/2. Testing 213 additional wild-type (WT) cancers showed HRD positivity similar to BRCA1/2 in 32% of cases. Correlation with proportional loss of heterozygosity (LOH) as determined using whole exome sequencing of 51 samples showed 90% (95% CI = 72%-97%) concordance. The approach was also validated in an independent set of 1312 consecutive tumor samples. Conclusions: These data demonstrate that CNA when combined with ML can reliably predict the presence of BRCA1/2 level HRD with high specificity. Using BRCA1/2 mutant cases as gold standard, this ML can be used to predict HRD in cancers with mutations in other HRR genes as well as in WT tumors.

Combining cell-free RNA with cell-free DNA in liquid biopsy for hematologic and solid tumors.

Current use of liquid biopsy is based on cell-free DNA (cfDNA) and the evaluation of mutations or methylation pattern. However, expressed RNA can capture mutations, changes in expression levels due to methylation, and provide information on cell of origin, growth, and proliferation status. We developed an approach to isolate cell-free total nucleic acid (cfDNA) and used targeted next generation sequencing to sequence cell-free RNA (cfRNA) and cfDNA as new approach in liquid biopsy. We demonstrate that cfRNA is overall more sensitive than cfDNA in detecting mutations. We show that cfRNA is reliable in detecting fusion genes and cfDNA is reliable in detecting chromosomal gains and losses. cfRNA levels of various solid tumor biomarkers were significantly higher (P < 0.0001) in samples from solid tumors as compared with normal control. Similarly, cfRNA lymphoid markers and cfRNA myeloid markers were all higher in lymphoid and myeloid neoplasms, respectively as compared with control (P < 0.0001). Using machine learning we demonstrate cfRNA was highly predictive of diagnosis (AUC >0.98) of solid tumors, B-cell lymphoid neoplasms, T-cell lymphoid neoplasms, and myeloid neoplasms. In evaluating the host immune system, cfRNA CD4:CD8B and CD3D:CD19 ratios in normal controls were as expected (median: 5.92 and 6.87, respectively) and were significantly lower in solid tumors (P < 0.0002). This data suggests that liquid biopsy combining analysis of cfRNA with cfDNA is practical and may provide helpful information in predicting genomic abnormalities, diagnosis of neoplasms and evaluating both the tumor biology and the host response.

Differential Diagnosis of Hematologic and Solid Tumors Using Targeted Transcriptome and Artificial Intelligence.

Diagnosis and classification of tumors is increasingly dependent on biomarkers. RNA expression profiling using next-generation sequencing provides reliable and reproducible information on the biology of cancer. This study investigated targeted transcriptome and artificial intelligence for differential diagnosis of hematologic and solid tumors. RNA samples from hematologic neoplasms (N = 2606), solid tumors (N = 2038), normal bone marrow (N = 782), and lymph node control (N = 24) were sequenced using next-generation sequencing using a targeted 1408-gene panel. Twenty subtypes of hematologic neoplasms and 24 subtypes of solid tumors were identified. Machine learning was used for diagnosis between two classes. Geometric mean naïve Bayesian classifier was used for differential diagnosis across 45 diagnostic entities with assigned rankings. Machine learning showed high accuracy in distinguishing between two diagnoses, with area under the curve varying between 1 and 0.841. Geometric mean naïve Bayesian algorithm was trained using 3045 samples and tested on 1415 samples, and showed correct first-choice diagnosis in 100%, 88%, 85%, 82%, 88%, 72%, and 72% of acute lymphoblastic leukemia, acute myeloid leukemia, diffuse large B-cell lymphoma, colorectal cancer, lung cancer, chronic lymphocytic leukemia, and follicular lymphoma cases, respectively. The data indicate that targeted transcriptome combined with artificial intelligence are highly useful for diagnosis and classification of various cancers. Mutation profiles and clinical information can improve these algorithms and minimize errors in diagnoses.

Reliability of Cell-Free DNA and Targeted NGS in Predicting Chromosomal Abnormalities of Patients With Myeloid Neoplasms.

Introduction: Cytogenetic analysis is important for stratifying patients with various neoplasms. We explored the use of targeted next generation sequencing (NGS) in detecting chromosomal structural abnormalities or copy number variations (CNVs) in patients with myeloid neoplasms. Methods: Plasma cell-free DNA (cfDNA) from 2821 myeloid or lymphoid neoplasm patients were collected. cfDNA was sequenced using a 275 gene panel. CNVkit software was used for analyzing and visualizing CNVs. Cytogenetic data from corresponding bone marrow (BM) samples was available on 89 myeloid samples. Results: Of the 2821 samples, 1539 (54.5%) showed evidence of mutations consistent with the presence of neoplastic clones in circulation. Of these 1539 samples, 906 (59%) showed abnormalities associated with myeloid neoplasms and 633 (41%) with lymphoid neoplasms. Chromosomal structural abnormalities in cfDNA were detected in 146 (16%) myeloid samples and 76 (12%) lymphoid samples. Upon comparison of the myeloid samples with 89 BM patients, NGS testing was able to reliably detect chromosomal gain or loss, except for fusion abnormalities. When cytogenetic abnormalities were classified according to prognostic classes, there was a complete (100%) concordance between cfDNA NGS data and cytogenetic data. Conclusions: This data shows that liquid biopsy using targeted NGS is reliable in detecting chromosomal structural abnormalities in myeloid neoplasms. In specific circumstances, targeted NGS may be reliable and efficient to provide adequate information without the need for BM biopsy considering broad mutation profiling can be obtained through adequate sequencing within the same test. Overall, this study supports the use of liquid biopsy for early diagnosis and monitoring of patients with myeloid neoplasms.

Determining clinical course of diffuse large B-cell lymphoma using targeted transcriptome and machine learning algorithms.

Multiple studies have demonstrated that diffuse large B-cell lymphoma (DLBCL) can be divided into subgroups based on their biology; however, these biological subgroups overlap clinically. Using machine learning, we developed an approach to stratify patients with DLBCL into four subgroups based on survival characteristics. This approach uses data from the targeted transcriptome to predict these survival subgroups. Using the expression levels of 180 genes, our model reliably predicted the four survival subgroups and was validated using independent groups of patients. Multivariate analysis showed that this patient stratification strategy encompasses various biological characteristics of DLBCL, and only TP53 mutations remained an independent prognostic biomarker. This novel approach for stratifying patients with DLBCL, based on the clinical outcome of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone therapy, can be used to identify patients who may not respond well to these types of therapy, but would otherwise benefit from alternative therapy and clinical trials.

Genetic Subtyping and Phenotypic Characterization of the Immune Microenvironment and MYC/BCL2 Double Expression Reveal Heterogeneity in Diffuse Large B-cell Lymphoma.

PURPOSE: Diffuse large B-cell lymphoma (DLBCL) is molecularly and clinically heterogeneous, and can be subtyped according to genetic alterations, cell-of-origin, or microenvironmental signatures using high-throughput genomic data at the DNA or RNA level. Although high-throughput proteomic profiling has not been available for DLBCL subtyping, MYC/BCL2 protein double expression (DE) is an established prognostic biomarker in DLBCL. The purpose of this study is to reveal the relative prognostic roles of DLBCL genetic, phenotypic, and microenvironmental biomarkers. EXPERIMENTAL DESIGN: We performed targeted next-generation sequencing; IHC for MYC, BCL2, and FN1; and fluorescent multiplex IHC for microenvironmental markers in a large cohort of DLBCL. We performed correlative and prognostic analyses within and across DLBCL genetic subtypes and MYC/BCL2 double expressors. RESULTS: We found that MYC/BCL2 double-high-expression (DhE) had significant adverse prognostic impact within the EZB genetic subtype and LymphGen-unclassified DLBCL cases but not within MCD and ST2 genetic subtypes. Conversely, KMT2D mutations significantly stratified DhE but not non-DhE DLBCL. T-cell infiltration showed favorable prognostic effects within BN2, MCD, and DhE but unfavorable effects within ST2 and LymphGen-unclassified cases. FN1 and PD-1-high expression had significant adverse prognostic effects within multiple DLBCL genetic/phenotypic subgroups. The prognostic effects of DhE and immune biomarkers within DLBCL genetic subtypes were independent although DhE and high Ki-67 were significantly associated with lower T-cell infiltration in LymphGen-unclassified cases. CONCLUSIONS: Together, these results demonstrated independent and additive prognostic effects of phenotypic MYC/BCL2 and microenvironment biomarkers and genetic subtyping in DLBCL prognostication, important for improving DLBCL classification and identifying prognostic determinants and therapeutic targets.

Genomic complexity is associated with epigenetic regulator mutations and poor prognosis in diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is the most common type of lymphoma with high mutation burdens but a low response rate to immune checkpoint inhibitors. In this study, we performed targeted next-generation sequencing and fluorescent multiplex immunohistochemistry, and investigated the clinical significance and immunological effect of mutation numbers in 424 DLBCL patients treated with standard immunochemotherapy. We found that KMT2D and TP53 nonsynonymous mutations (MUT) were significantly associated with increased nonsynonymous mutation numbers, and that high mutation numbers (MUThigh) were associated with significantly poorer clinical outcome in germinal center B-cell-like DLBCL with wild-type TP53. To understand the underlying mechanisms, we identified a gene-expression profiling signature and the association of MUThigh with decreased T cells in DLBCL patients with wild-type TP53. On the other hand, in overall cohort, MUThigh was associated with lower PD-1 expression in T cells and PD-L1 expression in macrophages, suggesting a positive role of MUThigh in immune responses. Analysis in a whole-exome sequencing dataset of 304 patients deposited by Chapuy et al. validated the correlation of MUT-KMT2D with genomic complexity and the significantly poorer survival associated with higher numbers of genomic single nucleotide variants in activated B-cell-like DLBCL with wild-type TP53. Together, these results suggest that KMT2D inactivation or epigenetic dysregulation has a role in driving DLBCL genomic instability, and that genomic complexity has adverse impact on clinical outcome in DLBCL patients with wild-type TP53 treated with standard immunochemotherapy. The oncoimmune data in this study have important implications for biomarker and therapeutic studies in DLBCL.

Diversity of genetic alterations of primary central nervous system lymphoma in Hispanic versus non-Hispanic patients.

PURPOSE: Primary central nervous system lymphoma (PCNSL) is a rare type of non-Hodgkin lymphoma. Previous studies have identified MYD88, CD79b and PIM1 as the most common genetic mutations in PCNSL. The extent to which mutations vary by ethnicity is unknown. The purpose of this study was to describe differences in genetic mutations and survival by Hispanic ethnicity in PCNSL. METHODS: 30 patients with PCNSL were examined for mutations in 275 genes by DNA analysis and 1408 genes by RNA analysis utilizing next generation sequencing. RESULTS: 60% of patients were Hispanic. 125 different mutated genes were detected. The most commonly affected genes were: MYD88 (44%), CARD11 (21%), CD79b (17%), PIM1 (17%) and KMT2D (17%) . MYD88 mutation was less frequent in Hispanic patients (27% vs 66%, P=.02). More Hispanic patients had >3 mutated genes (89% vs 55 %. P=.03). Two-year progression-free survival (PFS) and overall survival (OS) in Hispanic vs. non-Hispanic patients (PFS 60% vs 27%, P=.09), (OS 60% vs 36%, P=.23). MYD88, CARD11, PIM1, and KMT2D were not associated with significant differences in OS or PFS. CD79b mutation correlated with superior 2-yr PFS (P=.04). CONCLUSIONS: We identified highly recurrent genetic alterations in PCNSL. Our data suggest that heterogeneity in some mutations may be related to ethnicity. There was no statistically significant difference in 2-yr PFS and OS in our Hispanic patients. Studies on larger population may further help to describe differences in tumor biology, and outcomes in Hispanic patients.

Prediction of Outcome in Patients With Chronic Lymphocytic Leukemia Treated With Ibrutinib: Development and Validation of a Four-Factor Prognostic Model.

PURPOSE: Randomized trials established the superiority of ibrutinib-based therapy over chemoimmunotherapy in chronic lymphocytic leukemia. Durability of progression-free survival (PFS) with ibrutinib can vary by patient subgroup. Clinical tools for prognostication and risk-stratification are needed. PATIENTS AND METHODS: Patients treated with ibrutinib in phase II and III trials provided the discovery data set and were subdivided into discovery and internal validation cohorts. An external validation cohort included 84 patients enrolled in our investigator-initiated phase II trial. Univariable analysis of 18 pretreatment parameters was performed using PFS and overall survival (OS) end-points. Multivariable analysis and machine-learning algorithms identified four factors for a prognostic model that was validated in internal and external cohorts. RESULTS: Factors independently associated with inferior PFS and OS were as follows: TP53 aberration, prior treatment, ß-2 microglobulin ≥ 5 mg/L, and lactate dehydrogenase > 250 U/L. Each of these four factors contributed one point to a prognostic model that stratified patients into three risk groups: three to four points, high risk; two points, intermediate risk; zero to one point, low risk. The 3-year PFS rates for all 804 patients combined were 47%, 74%, and 87% for the high-, the intermediate-, and the low-risk group, respectively (P < .0001). The 3-year OS rates were 63%, 83%, and 93%, respectively (P < .0001). The model remained significant when applied to treatment-naïve and relapsed/refractory cohorts individually. For 84 patients in the external cohort, BTK and PLCG2 mutations were tested cross-sectionally and at progression. The cumulative incidences of mutations were strongly correlated with the model. In the external cohort, Richter's transformation occurred in 17% of the high-risk group, and in no patient in the low-risk group. CONCLUSION: Patients at increased risk of ibrutinib failure can be identified at treatment initiation and considered for clinical trials.

Eltrombopag monotherapy can improve hematopoiesis in patients with low to intermediate risk-1 myelodysplastic syndrome.

Myelodysplastic syndromes (MDS) are a group of clonal myeloid disorders characterized by cytopenia and a propensity to develop acute myeloid leukemia (AML). The management of lower-risk (LR) MDS with persistent cytopenias remains suboptimal. Eltrombopag (EPAG), a thrombopoietin receptor agonist, can improve platelet counts in LR-MDS and tri-lineage hematopoiesis in aplastic anemia (AA). We conducted a phase 2 dose modification study to investigate the safety and efficacy of EPAG in LR-MDS. EPAG dose was escalated from 50 mg/day, to a maximum of 150 mg/day over a period of 16 weeks. The primary efficacy endpoint was hematologic response at 16-20 weeks. Eleven of 25 (44%) patients responded; five and six patients had uni- or bi-lineage hematologic responses, respectively. The predictors of response were presence of a PNH clone, marrow hypocellularity, thrombocytopenia with or without other cytopenia, and elevated plasma thrombopoietin levels at study entry. The safety profile was consistent with previous EPAG studies in AA; no patients discontinued drug due to adverse events. Three patients developed reversible grade-3 liver toxicity and one patient had increased reticulin fibrosis. Ten patients discontinued EPAG after achieving a robust response (median time 16 months); four of them reinitiated EPAG due to declining counts, and all attained a second robust response. Six patients had disease progression not associated with expansion of mutated clones and no patient progressed to AML on study. In conclusion, EPAG was well-tolerated and effective in restoring hematopoiesis in patients with low to intermediate-1 risk MDS. This study was registered at clinicaltrials.gov as #NCT00932156.

A refined cell-of-origin classifier with targeted NGS and artificial intelligence shows robust predictive value in DLBCL.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous entity of B-cell lymphoma. Cell-of-origin (COO) classification of DLBCL is required in routine practice by the World Health Organization classification for biological and therapeutic insights. Genetic subtypes uncovered recently are based on distinct genetic alterations in DLBCL, which are different from the COO subtypes defined by gene expression signatures of normal B cells retained in DLBCL. We hypothesize that classifiers incorporating both genome-wide gene-expression and pathogenetic variables can improve the therapeutic significance of DLBCL classification. To develop such refined classifiers, we performed targeted RNA sequencing (RNA-Seq) with a commercially available next-generation sequencing (NGS) platform in a large cohort of 418 DLBCLs. Genetic and transcriptional data obtained by RNA-Seq in a single run were explored by state-of-the-art artificial intelligence (AI) to develop a NGS-COO classifier for COO assignment and NGS survival models for clinical outcome prediction. The NGS-COO model built through applying AI in the training set was robust, showing high concordance with COO classification by either Affymetrix GeneChip microarray or the NanoString Lymph2Cx assay in 2 validation sets. Although the NGS-COO model was not trained for clinical outcome, the activated B-cell-like compared with the germinal-center B-cell-like subtype had significantly poorer survival. The NGS survival models stratified 30% high-risk patients in the validation set with poor survival as in the training set. These results demonstrate that targeted RNA-Seq coupled with AI deep learning techniques provides reproducible, efficient, and affordable assays for clinical application. The clinical grade assays and NGS models integrating both genetic and transcriptional factors developed in this study may eventually support precision medicine in DLBCL.

A prospective study of a urine and plasma biomarker test for the prediction of gleason ≥3 + 4 prostate cancer in a mixed cohort.

Purpose: Definitive diagnosis of prostate cancer is based on biopsies, a procedure associated with side-effects. The use of biomarkers in blood and urine could potentially help clinicians select patients for whom biopsies are needed. The aim of the study was to test a new urine and plasma biomarker test in detecting medium and high grade prostate cancer.Materials and methods: Blood and urine samples were prospectively collected from 41 patients prior to prostate biopsy or TUR-P and again after 3 months. The cohort included patients with suspicion of prostate cancer and patients with prior prostate cancer diagnosis. The mRNA expression of ten selected genes measured by PCR were used together with clinical data in multiple algorithms for prediction of medium-high grade prostate cancer in prostate biopsies. The testing was originally developed and validated in the USA. The method was transferred to a local Danish laboratory. Medium and high grade cancer was defined as Gleason score ≥ 3 + 4.Results: Using the biomarker test, prior to any prostate procedures, the sensitivity for detecting medium-high grade prostate cancer was 100% and the specificity was 56% and 63%, depending on the cut-off point used. When using the biomarker test, following biopsy or TUR-P, the sensitivity and specificity were reduced to 89% and 28-34% respectively. When comparing results, there was a significant difference (p < 0.05), favoring the test performed prior to the procedures.Conclusions: We were able to predict the presence of medium-high grade prostate cancer, thereby confirming earlier findings of the biomarker test.

Eltrombopag for patients with moderate aplastic anemia or uni-lineage cytopenias.

There is no standard or widely effective treatment of patients with moderate aplastic anemia (MAA) or hypo-productive uni-lineage cytopenias (UC). Eltrombopag (EPAG), a small molecule thrombopoietin mimetic, has previously been shown to result in durable multi-lineage hematologic responses with low toxicity in patients with refractory severe aplastic anemia (SAA). Its safety and efficacy in MAA are unknown. This prospective phase 2 study enrolled previously untreated and treated MAA and UC patients with clinically relevant cytopenias. EPAG was administered at doses escalating from 50 to 300 mg/d. Hematologic responses were assessed at 16 to 20 weeks. Responding patients were continued on EPAG until reaching defined robust or stable blood counts. EPAG was reinstituted for relapse. Thirty-four patients were enrolled between 2012 and 2017, including 31 with MAA and 3 with UC. Seventeen patients responded in at least 1 eligible lineage by the primary end point. A striking improvement in anemia was observed in a patient with Diamond-Blackfan anemia. EPAG was well tolerated, and it was discontinued for robust or stable blood counts in 12 of 17 patients after a median of 8 months. A majority required re-initiation of EPAG for declining counts, and all regained response. Two of 34 patients developed non-chromosome 7 bone marrow cytogenetic abnormalities while taking EPAG, without dysplasia or increased blasts. Somatic mutation allele frequencies in cancer genes did not increase overall on EPAG. EPAG is a well-tolerated oral treatment of cytopenias in patients with MAA/UC. This trial was registered at www.clinicaltrials.gov as #NCT01328587.

Targeted next-generation sequencing of circulating cell-free DNA vs bone marrow in patients with acute myeloid leukemia.

Circulating cell-free DNA (ccfDNA) allows for noninvasive peripheral blood sampling of cancer-associated mutations and has established clinical utility in several solid tumors. We performed targeted next-generation sequencing of ccfDNA and bone marrow at the time of diagnosis and after achieving remission in 22 patients with acute myeloid leukemia (AML). Among 28 genes sequenced by both platforms, a total of 39 unique somatic mutations were detected. Five mutations (13%) were detected only in ccfDNA, and 15 (38%) were detected only in bone marrow. Among the 19 mutations detected in both sources, the concordance of variant allelic frequency (VAF) assessment by both methods was high (R2 = 0.849). Mutations detected in only 1 source generally had lower VAF than those detected in both sources, suggesting that either method may miss small subclonal populations. In 3 patients, sequencing of ccfDNA detected new or persistent leukemia-associated mutations during remission that appeared to herald overt relapse. Overall, this study demonstrates that sequencing of ccfDNA in patients with AML can identify clinically relevant mutations not detected in the bone marrow and may play a role in the assessment of measurable residual disease. However, mutations were missed by both ccfDNA and bone marrow analyses, particularly when the VAF was <10%, suggesting that ccfDNA and bone marrow may be complementary in the assessment and monitoring of patients with AML.

Localized Lichen Myxedematosus With Plasma Cell Light Chain Restriction: Is It the Exception or the Rule?

Lichen myxedematosus is a chronic cutaneous mucinosis that can present on a spectrum from localized cutaneous lesions to systemic disease of scleromyxedema. The clinical presentation of localized cutaneous lichen myxedematosus is waxy lichenoid papules, nodules, and/or plaques that have histopathologic findings of mucin deposition and a variable degree of fibroblast proliferation. There is an absence of serum paraproteins, and there are no other systemic causes of cutaneous mucinosis such as thyroid disease. The pathogenesis of lichen myxedematosus is unknown. We report 3 cases of localized cutaneous lichen myxedematosus with a light chain-restricted plasmacytic component by in situ hybridization. Our findings deliver an insight for disease pathogenesis and highlight for the first time, the significance of plasma cells in lesions of localized cutaneous lichen myxedematosus. We suggest that plasma cell light chain restriction could represent a clue to distinguish localized cutaneous disease from systemic disease.

Recommendations for the assessment and management of measurable residual disease in adults with acute lymphoblastic leukemia: A consensus of North American experts.

Measurable residual disease (MRD) that persists after initial therapy is a powerful predictor of relapse and survival in acute lymphoblastic leukemia (ALL). However, the optimal use of this information to influence therapeutic decisions is controversial. Herein, we comprehensively review the role of MRD assessment in adults with ALL, including methods to quantify residual leukemia cells during remission, prognostic impact of MRD across ALL subtypes, and available therapeutic approaches to eradicate MRD. This review presents consensus statements and provides an evidence-based framework for practicing hematologists and oncologists to use MRD information to make rational treatment decisions in adult patients with ALL.

GATA2 deficiency and human hematopoietic development modeled using induced pluripotent stem cells.

GATA2 deficiency is an inherited or sporadic genetic disorder characterized by distinct cellular deficiency, bone marrow failure, various infections, lymphedema, pulmonary alveolar proteinosis, and predisposition to myeloid malignancies resulting from heterozygous loss-of-function mutations in the GATA2 gene. How heterozygous GATA2 mutations affect human hematopoietic development or cause characteristic cellular deficiency and eventual hypoplastic myelodysplastic syndrome or leukemia is not fully understood. We used induced pluripotent stem cells (iPSCs) to study hematopoietic development in the setting of GATA2 deficiency. We performed hematopoietic differentiation using iPSC derived from patients with GATA2 deficiency and examined their ability to commit to mesoderm, hemogenic endothelial precursors (HEPs), hematopoietic stem progenitor cells, and natural killer (NK) cells. Patient-derived iPSC, either derived from fibroblasts/marrow stromal cells or peripheral blood mononuclear cells, did not show significant defects in committing to mesoderm, HEP, hematopoietic stem progenitor, or NK cells. However, HEP derived from GATA2-mutant iPSC showed impaired maturation toward hematopoietic lineages. Hematopoietic differentiation was nearly abolished from homozygous GATA2 knockout (KO) iPSC lines and markedly reduced in heterozygous KO lines compared with isogenic controls. On the other hand, correction of the mutated GATA2 allele in patient-specific iPSC did not alter hematopoietic development consistently in our model. GATA2 deficiency usually manifests within the first decade of life. Newborn and infant hematopoiesis appears to be grossly intact; therefore, our iPSC model indeed may resemble the disease phenotype, suggesting that other genetic, epigenetic, or environmental factors may contribute to bone marrow failure in these patients following birth. However, heterogeneity of PSC-based models and limitations of in vitro differentiation protocol may limit the possibility to detect subtle cellular phenotypes.

A real-world, comparative study of FDA-approved diagnostic assays PD-L1 IHC 28-8 and 22C3 in lung cancer and other malignancies.

AIMS: At the time of analysis, two widely used, drug-specific, tumour-cell programmed death ligand 1 (PD-L1) assays were approved by the US Food and Drug Administration for anti-PD-1 therapies: the Dako PD-L1 immunohistochemistry (IHC) 28-8 pharmDx assay and the Dako PD-L1 IHC 22C3 pharmDx assay. Given that the majority of current PD-L1 testing in US clinical practice is performed at commercial reference laboratories, we aimed to evaluate the concordance of the 28-8 and 22C3 assays in a real-world setting. METHODS: Matched PD-L1 IHC 28-8 and 22C3 results from routine assessment were obtained from 1930 patients, including 412 confirmed to have lung cancer, submitted from hospitals in over 38 US states/territories. Biopsies were stained, reviewed and scored by trained/certified pathologists at a single cancer reference laboratory between 2015 and 2017. Rate of concordance between assay findings was assessed by Bland-Altman analysis; overall per cent agreement (OPA), positive per cent agreement and negative per cent agreement; and Cohen's kappa. RESULTS: PD-L1 IHC 28-8 and 22C3 displayed strong correlation across all samples and in samples with a confirmed lung cancer diagnosis irrespective of biopsy site. The OPA was 97%-98% for all samples, depending on the expression level defining PD-L1 positivity. In the Bland-Altman analysis, the mean difference in percentage of tumour cells positively stained for PD-L1 between the paired assay findings was -0.80% for all samples and -0.93% in samples with a confirmed lung cancer diagnosis. CONCLUSIONS: These data, in conjunction with recent findings, support the analytical concordance of the PD-L1 IHC 28-8 and 22C3 assays for assessing per cent tumour-cell membrane PD-L1 expression.

Immunohistochemistry and alternative FISH testing in breast cancer with HER2 equivocal amplification.

PURPOSE: While HER2 testing is well established in directing appropriate treatment for breast cancer, a small percentage of cases show equivocal results by immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH). Alternative probes may be used in equivocal cases. We present a single community-based institution's experience in further evaluating these cases. PATIENTS AND METHODS: Between 2014 and 2016, 4255 samples were submitted for HER2 amplification testing by alternative probes, TP53, RAI1, and RARA. Of the patients tested by FISH, 505/3908 (12.9%) also had IHC data. RESULTS: Most (73.9%) FISH equivocal cases remained equivocal after IHC testing. However, 50.5% of equivocal cases were classified as HER2 amplified by alternative probes. Most cases were positive by more than one probe: 78% of positive cases by RAI1 and 73.9% by TP53. There was a significant difference between IHC and FISH alternative testing (p < 0.0001) among the equivocal cases by conventional FISH testing, 44% of IHC negative cases became positive while 36% of the positive IHC cases became negative by alternative FISH testing. Available data showed that 41% of patients were treated with palbociclib and were positive by alternative FISH. CONCLUSION: The prevalence of double HER2 equivocal cases and the discrepancy between IHC and alternative FISH testing suggest that FISH alternative testing using both RAI1 and TP53 probes is necessary for conclusive classification. Because almost half of FISH equivocal cases converted to HER2 amplified upon alternative testing, clinical studies to determine the benefit of anti-HER2 therapy in these patients are urgently needed.