Identification of genetic subtypes in follicular lymphoma.

Follicular lymphoma (FL) exhibits considerable variability in biological features and clinical trajectories across patients. To dissect the diversity of FL, we utilized a Bernoulli mixture model to identify genetic subtypes in 713 pre-treatment tumor tissue samples. Our analysis revealed the existence of five subtypes with unique genetic profiles that correlated with clinicopathological characteristics. The clusters were enriched in specific mutations as follows: CS (CREBBP and STAT6), TT (TNFAIP3 and TP53), GM (GNA13 and MEF2B), Q (quiescent, for low mutation burden), and AR (mutations of mTOR pathway-related genes). The subtype Q was enriched for patients with stage I disease and associated with a lower proliferative history than the other subtypes. The AR subtype was unique in its enrichment for IgM-expressing FL cases and was associated with advanced-stage and more than 4 nodal sites. The existence of subtypes was validated in an independent cohort of 418 samples from the GALLIUM trial. Notably, patients assigned to the TT subtype consistently experienced inferior progression-free survival when treated with immunochemotherapy. Our findings offer insight into core pathways distinctly linked with each FL cluster and are expected to be informative in the era of targeted therapies.

Single gene mutations and prognosis in limited-stage follicular lymphoma treated with radiation therapy.

Radiotherapy is routinely used for management of limited-stage follicular lymphoma (FL), yet half of patients ultimately relapse. We hypothesized that the presence of specific gene mutations may predict outcomes. We performed targeted sequencing of a 69-gene panel in 117 limited-stage FL patients treated with radiotherapy and identified recurrently mutated genes. CREBBP was most frequently mutated, and mutated CREBBP was associated with inferior progression-free survival, though not after false discovery rate adjustment. This association failed to validate in an independent cohort. We conclude that recurrent gene mutations do not predict outcomes in this setting. Alternative biomarkers may offer better prognostic insight.

Co-shared genomic alterations within tumors from patients with both myeloproliferative neoplasms and lymphoma.

Not available.

Imaging Flow Cytometry and Convolutional Neural Network-Based Classification Enable Discrimination of Hematopoietic and Leukemic Stem Cells in Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is a heterogenous blood cancer with a dismal prognosis. It emanates from leukemic stem cells (LSCs) arising from the genetic transformation of hematopoietic stem cells (HSCs). LSCs hold prognostic value, but their molecular and immunophenotypic heterogeneity poses challenges: there is no single marker for identifying all LSCs across AML samples. We hypothesized that imaging flow cytometry (IFC) paired with artificial intelligence-driven image analysis could visually distinguish LSCs from HSCs based solely on morphology. Initially, a seven-color IFC panel was employed to immunophenotypically identify LSCs and HSCs in bone marrow samples from five AML patients and ten healthy donors, respectively. Next, we developed convolutional neural network (CNN) models for HSC-LSC discrimination using brightfield (BF), side scatter (SSC), and DNA images. Classification using only BF images achieved 86.96% accuracy, indicating significant morphological differences. Accuracy increased to 93.42% when combining BF with DNA images, highlighting differences in nuclear morphology, although DNA images alone were inadequate for accurate HSC-LSC discrimination. Model development using SSC images revealed minor granularity differences. Performance metrics varied substantially between AML patients, indicating considerable morphologic variations among LSCs. Overall, we demonstrate proof-of-concept results for accurate CNN-based HSC-LSC differentiation, instigating the development of a novel technique within AML monitoring.

Comparative analysis of feature-based ML and CNN for binucleated erythroblast quantification in myelodysplastic syndrome patients using imaging flow cytometry data.

Myelodysplastic syndrome is primarily characterized by dysplasia in the bone marrow (BM), presenting a challenge in consistent morphology interpretation. Accurate diagnosis through traditional slide-based analysis is difficult, necessitating a standardized objective technique. Over the past two decades, imaging flow cytometry (IFC) has proven effective in combining image-based morphometric analyses with high-parameter phenotyping. We have previously demonstrated the effectiveness of combining IFC with a feature-based machine learning algorithm to accurately identify and quantify rare binucleated erythroblasts (BNEs) in dyserythropoietic BM cells. However, a feature-based workflow poses challenges requiring software-specific expertise. Here we employ a Convolutional Neural Network (CNN) algorithm for BNE identification and differentiation from doublets and cells with irregular nuclear morphology in IFC data. We demonstrate that this simplified AI workflow, coupled with a powerful CNN algorithm, achieves comparable BNE quantification accuracy to manual and feature-based analysis with substantial time savings, eliminating workflow complexity. This streamlined approach holds significant clinical value, enhancing IFC accessibility for routine diagnostic purposes.

A novel view to varicose veins pathogenesis: Proteomic profiling suggests a pivotal role of extracellular matrix degradation.

INTRODUCTION: Although morphological and anatomical studies indicate that venous wall weakening and subendothelial fibrosis characterize varicose veins (VV), the pathogenesis of VV remains poorly understood. The aim of this study is to obtain protein expression profiles in patients with VV and thereby get a step closer to understanding the pathogenesis of VV. METHODS: Specimens were obtained from total of 10 patients, that is, from 5 patients undergoing VV surgical stripping and from 5 non-VV patients undergoing bypass surgery. Specimens were collected from the same layers of venous wall. Proteins were extracted from each specimen and analyzed by ion mobility spectrometry (IMS-MS). In total, 1387 were identified and 486 proteins were identified in all samples. From these, 15 proteins were differentially expressed between VV and non-VV samples (p < .05) and 12 of these showed a fold change >1.5. RESULTS: Interestingly, among the differentially expressed proteins, only two proteins were significantly increased in the VV tissue, that is, GAPDH (p = .028, fold change 2.74), where several proteins involved in maintaining the homeostasis in the extracellular matrix, that is, the CXXC zinc finger protein 5 (CXXC5) and nucleoporin (SEH1) were prominently downregulated (p = .049, fold change 37.8, and p = .040, fold change 3.46). The downregulation in protein expression of CXXC5 and SEH1 as well as upregulation of GAPDH were validated by Western blotting. CONCLUSION: The identified differentially expressed proteins suggest an altered profile of the connective tissue proteins as well as an increased proteolytic enzyme activity which both may be central in the pathophysiology of varicose veins.

Proteomics identifies apoptotic markers as predictors of histological transformation in patients with follicular lymphoma.

Follicular lymphoma (FL) is an indolent lymphoma with a generally favorable prognosis. However, histological transformation (HT) to a more aggressive disease leads to markedly inferior outcomes. This study aims to identify biological differences predictive of HT at the time of initial FL diagnosis. We show differential protein expression between diagnostic lymphoma samples from patients with subsequent HT (subsequently-transforming FL [st-FL]; n = 20) and patients without HT (nontransforming FL [nt-FL]; n = 34) by label-free quantification nano liquid chromatography-tandem mass spectrometry analysis. Protein profiles identified patients with high risk of HT. This was accompanied by disturbances in cellular pathways influencing apoptosis, the cytoskeleton, cell cycle, and immune processes. Comparisons between diagnostic st-FL samples and paired transformed FL (n = 20) samples demonstrated differential protein profiles and disrupted cellular pathways, indicating striking biological differences from the time of diagnosis up to HT. Immunohistochemical analysis of apoptotic proteins, CASP3, MCL1, BAX, BCL-xL, and BCL-rambo, confirmed higher expression levels in st-FL than in nt-FL samples (P < .001, P = .015, P = .003, P = .025, and P = .057, respectively). Moreover, all 5 markers were associated with shorter transformation-free survival (TFS; P < .001, P = .002, P < .001, P = .069, and P = .010, respectively). Notably, combining the expression of these proteins in a risk score revealed increasingly inferior TFS with an increasing number of positive markers. In conclusion, proteomics identified altered protein expression profiles (particularly apoptotic proteins) at the time of FL diagnosis, which predicted later transformation.

Dual intron-targeted CRISPR-Cas9-mediated disruption of the AML RUNX1-RUNX1T1 fusion gene effectively inhibits proliferation and decreases tumor volume in vitro and in vivo.

Oncogenic fusion drivers are common in hematological cancers and are thus relevant targets of future CRISPR-Cas9-based treatment strategies. However, breakpoint-location variation in patients pose a challenge to traditional breakpoint-targeting CRISPR-Cas9-mediated disruption strategies. Here we present a new dual intron-targeting CRISPR-Cas9 treatment strategy, for targeting t(8;21) found in 5-10% of de novo acute myeloid leukemia (AML), which efficiently disrupts fusion genes without prior identification of breakpoint location. We show in vitro growth rate and proliferation reduction by 69 and 94% in AML t(8;21) Kasumi-1 cells, following dual intron-targeted disruption of RUNX1-RUNX1T1 compared to a non t(8;21) AML control. Furthermore, mice injected with RUNX1-RUNX1T1-disrupted Kasumi-1 cells had in vivo tumor growth reduction by 69 and 91% compared to controls. Demonstrating the feasibility of RUNX1-RUNX1T1 disruption, these findings were substantiated in isolated primary cells from a patient diagnosed with AML t(8;21). In conclusion, we demonstrate proof-of-principle of a dual intron-targeting CRISPR-Cas9 treatment strategy in AML t(8;21) without need for precise knowledge of the breakpoint location.

IDO1 Protein Is Expressed in Diagnostic Biopsies from Both Follicular and Transformed Follicular Patients.

Follicular lymphoma (FL) is a lymphoid neoplasia characterized by an indolent clinical nature. Despite generally favorable prognoses, early progression and histological transformation (HT) to a more aggressive lymphoma histology remain the leading causes of death among FL patients. To provide a basis for possible novel treatment options, we set out to evaluate the expression levels of indoleamine 2,3-dioxygenase 1 (IDO1), an immunoinhibitory checkpoint molecule, in follicular and transformed follicular biopsies. The expression levels of IDO1 were assessed using immunohistochemical staining and digital image analysis in lymphoma biopsies from 33 FL patients without subsequent HT (non-transforming FL, nt-FL) and 20 patients with subsequent HT (subsequently transforming FL, st-FL) as well as in paired high-grade biopsies from the time of HT (transformed FL, tFL). Despite no statistical difference in IDO1 expression levels seen between the groups, all diagnostic and transformed lymphomas exhibited positive expression, indicating its possible role in novel treatment regimens. In addition, IDO1 expression revealed a positive correlation with another immune checkpoint inhibitor, namely programmed death 1 (PD-1). In summary, we report IDO1 expression in all cases of FL and tFL, which provides the grounds for future investigations of anti-IDO1 therapy as a possible treatment for FL patients.

Proteomic Profiling Identifies Specific Leukemic Stem Cell-Associated Protein Expression Patterns in Pediatric AML Patients.

Novel therapeutic tools are warranted to improve outcomes for children with acute myeloid leukemia (AML). Differences in the proteome of leukemic blasts and stem cells (AML-SCs) in AML compared with normal hematopoietic stem cells (HSCs) may facilitate the identification of potential targets for future treatment strategies. In this explorative study, we used mass spectrometry to compare the proteome of AML-SCs and CLEC12A+ blasts from five pediatric AML patients with HSCs and hematopoietic progenitor cells from hematologically healthy, age-matched controls. A total of 456 shared proteins were identified in both leukemic and control samples. Varying protein expression profiles were observed in AML-SCs and leukemic blasts, none having any overall resemblance to healthy counterpart cell populations. Thirty-four proteins were differentially expressed between AML-SCs and HSCs, including the upregulation of HSPE1, SRSF1, and NUP210, and the enrichment of proteins suggestive of protein synthesis perturbations through the downregulation of EIF2 signaling was found. Among others, NUP210 and calreticulin were upregulated in CLEC12A+ blasts compared with HSCs. In conclusion, the observed differences in protein expression between pediatric patients with AML and pediatric controls, in particular when comparing stem cell subsets, encourages the extended exploration of leukemia and AML-SC-specific biomarkers of potential relevance in the development of future therapeutic options in pediatric AML.

Immunophenotypically defined stem cell subsets in paediatric AML are highly heterogeneous and demonstrate differences in BCL-2 expression by cytogenetic subgroups.

In adult acute myeloid leukaemia (AML), immunophenotypic differences enable discrimination of leukaemic stem cells (LSCs) from healthy haematopoietic stem cells (HSCs). However, immunophenotypic stem cell characteristics are less explored in paediatric AML. Employing a 15-colour flow cytometry assay, we analysed the expression of eight aberrant surface markers together with BCL-2 on CD34+ CD38- bone marrow stem cells from 38 paediatric AML patients and seven non-leukaemic, age-matched controls. Furthermore, clonality was investigated by genetic analyses of sorted immunophenotypically abnormal stem cells from six patients. A total of 50 aberrant marker positive (non-HSC-like) subsets with 41 different immunophenotypic profiles were detected. CD123, CLEC12A, and IL1RAP were the most frequently expressed markers. IL1RAP, CD93, and CD25 expression were not restricted to stem cells harbouring leukaemia-associated mutations. Differential BCL-2 expression was found among defined cytogenetic subgroups. Interestingly, only immunophenotypically abnormal non-HSC-like subsets demonstrated BCL-2 overexpression. Collectively, we observed pronounced immunophenotypic heterogeneity within the stem cell compartment of paediatric AML patients. Additionally, certain aberrant markers used in adults seemed to be ineligible for detection of leukaemia-representing stem cells in paediatric patients implying that inference from adult studies must be done with caution.

Tumor-Tissue Expression of the Hyaluronic Acid Receptor RHAMM Predicts Histological Transformation in Follicular Lymphoma Patients.

Histological transformation (HT) remains the leading cause of mortality in follicular lymphoma (FL), underlining the need to identify reliable transformation predictors. The hyaluronic acid receptors CD44 and the receptor for hyaluronan mediated motility (RHAMM, also known as HMMR and CD168), have been shown to be involved in the pathogeneses of both solid tumors and hematological malignancies. In an attempt to improve risk stratification, expression of RHAMM and CD44 were evaluated by immunohistochemistry and digital image analysis in pre-therapeutic tumor-tissue biopsies from FL patients, either without (nt-FL, n = 34), or with (st-FL, n = 31) subsequent transformation, and in paired biopsies from the transformed lymphomas (tFL, n = 31). At the time of initial diagnosis, samples from st-FL patients had a higher expression of RHAMM compared with samples from nt-FL patients (p < 0.001). RHAMM expression further increased in tFL samples following transformation (p < 0.001). Evaluation of CD44 expression showed no differences in expression comparing nt-FL, st-FL, and tFL samples. Shorter transformation-free survival was associated with high tumoral and intrafollicular RHAMM expression, as well as with low intrafollicular CD44 expression (p = 0.002, p < 0.001, and p = 0.034, respectively). Our data suggest that high tumor-tissue RHAMM expression predicts the risk of shorter transformation-free survival in FL patients already at initial diagnosis.

Clonal evolution in patients developing therapy-related myeloid neoplasms following autologous stem cell transplantation.

Clonal hematopoiesis (CH) denotes somatic mutations in genes related to myeloid neoplasms present at any variant allele frequency (VAF). Clonal hematopoiesis is associated with increasing age and with a factor 6 increase in the risk of developing therapy-related myeloid neoplasms (tMNs) following autologous stem cell transplantation (ASCT). However, the impact of specific mutations on progression from CH to tMN has yet to be unraveled, and it remains unclear whether mutations directly impact or even drive the development of tMN. We performed deep sequencing in longitudinal samples from a cohort of 12 patients with either multiple myeloma or lymphoma who developed tMN following ASCT. Nine patients had one or more mutations that could be tracked longitudinally. Seven patients had clonal expansion from time of ASCT to diagnosis of tMN. Of these, six patients had CH at VAF < 2% at baseline. The median VAF of non-DNMT3A clones increased from 1% (IQR 0.7%-10.0%) at time of ASCT to 37% (IQR 17%-47%) at tMN diagnosis (P = 0.002), while DNMT3A clones showed quiescent trajectories (P = 0.625). Our data provide evidence to support the hypothesis that the development of tMN following ASCT is likely instigated by CH present at VAFs as low as 0.5%, detectable years before tMN onset.

Classic Hodgkin Lymphoma Refractory for ABVD Treatment Is Characterized by Pathologically Activated Signal Transduction Pathways as Revealed by Proteomic Profiling.

In classic Hodgkin lymphoma (cHL), the tumour microenvironment (TME) is of major pathological relevance. The paucity of neoplastic cells makes it important to study the entire TME when searching for prognostic biomarkers. Cure rates in cHL have improved markedly over the last several decades, but patients with primary refractory disease still show inferior survival. We performed a proteomic comparison of pretreatment tumour tissue from ABVD treatment-refractory versus ABVD treatment-sensitive cHL patients, in order to identify biological differences correlating with treatment outcome. Formalin-fixed paraffin-embedded tumour tissues from 36 patients with cHL, 15 with treatment-refractory disease, and 21 with treatment-sensitive disease, were processed for proteomic investigation. Label-free quantification nano liquid chromatography tandem mass spectrometry was performed on the tissues. A total of 3920 proteins were detected and quantified between the refractory and sensitive groups. This comparison revealed several subtle but significant differences in protein expression which could identify subcluster characteristics of the refractory group. Bioinformatic analysis of the biological differences indicated that a number of pathologically activated signal transduction pathways are disturbed in ABVD treatment-refractory cHL.

Imaging flow cytometry reveals a subset of TdT negative T-ALL blasts with very low forward scatter on conventional flow cytometry.

BACKGROUND: Studies in T-cell acute lymphoblastic leukemia (T-ALL) have shown that leukemic blast populations may display immunophenotypic heterogeneity. In the clinical setting, evaluation of measurable residual disease during treatment and follow-up is highly dependent on knowledge of the diversity of blast subsets. Here, we set out to evaluate whether variation in expression of the blast marker, TdT, in T-ALL blasts could correspond to differences in morphometric features. METHODS: We investigated diagnostic bone marrow samples from six individual T-ALL patients run in parallel on imaging flow cytometry (IFC) and conventional flow cytometry (CFC). RESULTS: Guided by the imagery available in IFC, we identified distinct TdTneg and TdTpos subpopulations with apparent differences in internal complexity. As TdTneg blasts predominantly displayed very low forward scatter (FSC) on CFC, these subsets were initially excluded from routine analysis as debris, elements of small diameter, apoptotic, and/or dead cells. However, IFC-based morphometric analyses demonstrated that cell size and shape of TdTneg blasts were comparable to the TdTpos cells and without morphometric apoptotic hallmarks, supporting that the TdTneg subpopulation corresponded to T-ALL blasts. Fluorescence in situ hybridization analyses substantiated the clinical relevance of TdTneg FSCvery-low cells by retrieving known diagnostic cytogenetic abnormalities at comparable frequencies in purified TdTneg FSCvery-low and TdTpos FSCint subsets. CONCLUSION: We highlight this finding as knowledge of phenotypic heterogeneity is of crucial importance in the clinical setting for delineation and quantification of blast subpopulations of potential biological relevance. We argue that the IFC imagery may allow for visual verification and improvement of applied gating strategies.

IGHV-associated methylation signatures more accurately predict clinical outcomes of chronic lymphocytic leukemia patients than IGHV mutation load.

Currently, no molecular biomarker indices are used in standard care to make treatment decisions at diagnosis of chronic lymphocytic leukemia (CLL). We used Infinium MethylationEPIC array data from diagnostic blood samples of 114 CLL patients and developed a procedure to stratify patients based on methylation signatures associated with mutation load of the IGHV gene. This procedure allowed us to predict the time to treatment with a hazard ratio (HR) of 8.34 (95% confidence interval [CI]: 4.54-15.30), as opposed to a HR of 4.35 (95% CI: 2.60-7.28) using IGHV mutation status. Detailed evaluation of 17 cases for which the two classification procedures gave discrepant results showed that these cases were incorrectly classified using IGHV status. Moreover, methylation-based classification stratified patients with different overall survival (HR=1.82; 95% CI: 1.07-3.09), which was not possible using IGHV status. Furthermore, we assessed the performance of the developed classification procedure using published HumanMethylation450 array data for 159 patients for whom information on time to treatment, overall survival and relapse was available. Despite 450K array methylation data not containing all the biomarkers used in our classification procedure, methylation signatures again stratified patients with significantly better accuracy than did IGHV mutation load regarding all available clinical outcomes. Thus, stratification using IGHV-associated methylation signatures may provide better prognostic power than IGHV mutation status.

Proteomic Profiling Differentiates Lymphoma Patients with and without Concurrent Myeloproliferative Neoplasia.

Myeloproliferative neoplasia (MPN) and lymphoma are regarded as distinct diseases with different pathogeneses. However, patients that are diagnosed with both malignancies occur more frequently in the population than expected. This has led to the hypothesis that the two malignancies may, in some cases, be pathogenetically related. Using a mass spectrometry-based proteomic approach, we show that pre-treatment lymphoma samples from patients with both MPN and lymphoma, either angioimmunoblastic T-cell lymphoma (MPN-AITL) or diffuse large B-cell lymphoma (MPN-DLBCL), show differences in protein expression compared with reference AITL or DLBCL samples from patients without MPN. A distinct clustering of samples from patients with and without MPN was evident for both AITL and DLBCL. Regarding MPN-AITL, a pathway analysis revealed disturbances of cellular respiration as well as oxidative metabolism, and an immunohistochemical evaluation further demonstrated the differential expression of citrate synthase and DNAJA2 protein (p = 0.007 and p = 0.015). Interestingly, IDH2 protein also showed differential expression in the MPN-AITL patients, which contributes to the growing evidence of this protein's role in both myeloid neoplasia and AITL. In MPN-DLBCL, the disturbed pathways included a significant downregulation of protein synthesis as well as a perturbation of signal transduction. These results imply an underlying disturbance of tumor molecular biology, and in turn an alternative pathogenesis for tumors in these patients with both myeloid and lymphoid malignancies.