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.

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.

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.

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 Characterization of Colorectal Cancer Tissue from Patients Identifies Novel Putative Protein Biomarkers.

Colorectal cancer (CRC) is one of the leading causes of cancer-related death over the world. There is a great need for biomarkers capable of early detection and as targets for treatment. Differential protein expression was investigated with two-dimensional gel electrophoresis (2D-PAGE) followed by identification with liquid chromatography-tandem mass spectrometry (LC-MS/MS) in CRC patient tissue from (i) the peripheral part of the tumor, (ii) the central part of the tumor as well as from (iii) a non-involved part of the colorectal tissue. The expression patterns of six identified proteins were further evaluated by one-dimensional Western blot (1D-WB) analysis of the CRC tissue. Proteins that were perturbed in expression level in the peripheral or in the central part of the tumor as compared with the non-involved part included S100A11, HNRNPF, HNRNPH1 or HNRNPH2, GSTP1, PKM and FABP1. These identified markers may have future diagnostic potential or may be novel treatment targets after further evaluation in larger patient cohorts.

Soluble programmed cell death protein 1 (sPD-1) and the soluble programmed cell death ligands 1 and 2 (sPD-L1 and sPD-L2) in lymphoid malignancies.

BACKGROUND: The programmed cell death protein 1 (PD-1) and its ligand 1 and 2 (PD-L1/PD-L2) regulate the immune system, and the checkpoint pathway can be exploited by malignant cells to evade anti-tumor immune response. Soluble forms (sPD-1/sPD-L1/sPD-L2) exist in the peripheral blood, but their biological and clinical significance is unclear. METHOD: Time-resolved immunofluorometric assay (TRIFMA) and enzyme-linked immunosorbent assay (ELISA) were used to measure sPD-1, sPD-L1, and sPD-L2 levels in serum from 131 lymphoma patients and 22 healthy individuals. RESULTS: Patients had higher sPD-1 and sPD-L2 levels than healthy individuals. In diffuse large B-cell lymphoma, patients with high International Prognostic Index score had higher sPD-1 levels and sPD-L2 levels correlated with subtype according to cell of origin. Compared to other lymphoma types, follicular lymphoma displayed higher sPD-1 and lower sPD-L1 levels along with lower ligand/receptor ratios. CONCLUSION: This is the first study to simultaneously characterize pretherapeutic sPD-1, sPD-L1, and sPD-L2 in a variety of lymphoma subtypes. The relation between higher sPD-1 levels and adverse prognostic factors suggests a possible biological role and potential clinical usefulness of sPD-1. Moreover, the reverse expression pattern in follicular lymphoma and T-cell lymphoma/leukemia may reflect biological information relevant for immunotherapy targeting the PD-1 pathway.

Myeloproliferative and lymphoproliferative malignancies occurring in the same patient: a nationwide discovery cohort.

Myeloid and lymphoid malignancies are postulated to have distinct pathogenetic mechanisms. The recent observation that patients with a myeloproliferative neoplasm have an increased risk of developing lymphoproliferative malignancy has challenged this assumption. We collected a nationwide cohort of patients with both malignancies. Patients diagnosed in 1990-2015 were identified through the national Danish Pathology Registry. We identified 599 patients with myeloproliferative neoplasm and a concomitant or subsequent diagnosis of lymphoma. Histopathological review of the diagnostic samples from each patient led to a final cohort of 97 individuals with confirmed dual diagnoses of myeloproliferative neoplasm and lymphoma. The age range at diagnosis was 19-94 years (median: 71 years). To avoid the inclusion of cases of therapy-induced myeloproliferative neoplasm occurring in patients previously treated for lymphoma, only patients with myeloproliferative neoplasm diagnosed unequivocally before the development of lymphoma were included. The average time interval between the diagnoses of the two malignancies was 1.5 years. In the majority of patients (90%) both diagnoses were established within 5 years from each other. Among the lymphoma entities, the frequency of peripheral T-cell lymphomas was markedly increased. Interestingly, all but one of the T-cell lymphomas were of angioimmunoblastic type. These findings suggest that myeloproliferative neoplasm and lymphoproliferative malignancy developing in the same patient may have common pathogenetic events, possibly already at progenitor level. We believe that the molecular characterization of the newly developed biorepository will help to highlight the mechanisms driving the genesis and clonal evolution of these hematopoietic malignancies.

High intratumoural galectin-1 expression predicts adverse outcome in ALK- ALCL and CD30+ PTCL-NOS.

Galectin-1 (Gal-1) has been associated with adverse prognosis in several cancers including lymphoma entities with CD30 expression. However, Gal-1 expression has not been systematically assessed in peripheral T-cell lymphomas (PTCL). Specimens from 169 nodal PTCL were assessed for intratumoural Gal-1 expression by immunohistochemistry. Overall survival (OS) in groups exhibiting high and low Gal-1 expression was compared in the cohort and in a subset analysis of CD30-positive PTCL only. Gal-1 expression was also correlated with biomarkers of the tumour microenvironment. No significant difference in OS based on Gal-1 expression was observed in the entire PTCL cohort. However, in the CD30-positive cohort, patients with high Gal-1 levels had significantly poorer outcome (5 years OS 10%, 95% confidence interval CI, 1-36) than their low Gal-1 counterparts (5 years OS 48%, 95% CI, 30-64, P = .021). In univariate analyses age 60 or younger, non-elevated lactate dehydrogenase (LDH), and performance score less than 2 correlated with superior survival but high Gal-1 expression significantly predicted adverse outcome at both univariate (HR 2.5, 95% CI, 1.1-5.7, P = .026) and multivariate levels (HR 3.2, 95% CI, 1.2-8.5, P = .017). Tumours with high Gal-1 had few cytotoxic T cells in the tumour microenvironment. High intratumoural Gal-1 expression before therapeutic intervention correlates with adverse outcome in nodal CD30+ , ALK- PTCL patients.

Proteomic Characterization of Colorectal Cancer Cells versus Normal-Derived Colon Mucosa Cells: Approaching Identification of Novel Diagnostic Protein Biomarkers in Colorectal Cancer.

In the western world, colorectal cancer (CRC) is the third most common cause of cancer-related deaths. Survival is closely related to the stage of cancer at diagnosis striking the clinical need for biomarkers capable of early detection. To search for possible biological parameters for early diagnosis of CRC we evaluated protein expression for three CREC (acronym: Cab45, reticulocalbin, ERC-55, calumenin) proteins: reticulocalbin, calumenin, and ERC-55 in a cellular model consisting of a normal derived colon mucosa cell line, NCM460, and a primary adenocarcinoma cell line of the colon, SW480. Furthermore, this cellular model was analyzed by a top-down proteomic approach, 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) for novel putative diagnostic markers by identification of differentially expressed proteins between the two cell lines. A different colorectal carcinoma cell line, HCT 116, was used in a bottom-up proteomic approach with label-free quantification (LFQ) LC-MS/MS. The two cellular models gave sets of putative diagnostic CRC biomarkers. Various of these novel putative markers were verified with increased expression in CRC patient neoplastic tissue compared to the expression in a non-involved part of the colon, including reticulocalbin, calumenin, S100A6 and protein SET. Characterization of these novel identified biological features for CRC patients may have diagnostic potential and therapeutic relevance in this malignancy characterized by a still unmet clinical need.

Perturbations of urea cycle enzymes during posthepatectomy rat liver failure.

Posthepatectomy liver failure (PHLF) may occur after extended partial hepatectomy (PH). If malignancy is widespread in the liver, the size of PH and hence the size of the future liver remnant (FLR) may limit curability. We aimed to characterize differences in protein expression between different sizes of FLRs and identify proteins specific to the regenerative process of minimal-size FLR (MSFLR), with special focus on postoperative day (POD) 1 when PHLF is present. A total of 104 male Wistar rats were subjected to 30, 70, or 90% PH (MSFLR in rats), sham operation, or no operation. Blood and liver tissue were harvested at POD1, 3, and 5 (n = 8 per group). Protein expression was assessed by proteomic profiling by unsupervised two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) liquid chromatography tandem mass spectrometry (LC-MS/MS), followed by supervised selected reaction monitoring (SRM)-MS/MS. In all, 1,035 protein spots were detected, 54 of which were significantly differentially expressed between groups and identifiable. During PHLF after PH(90%) at POD1, urea cycle and related proteins showed significant perturbations, including the urea cycle flux-regulating enzyme of carbamoyl phosphate synthase-1, ornithine transcarbamylase, and arginase-1, as well as the ornithine aminotransferase and propionyl-CoA carboxylase alpha chain. Plasma-ammonia increased significantly at POD1 after PH(90%), followed by a prompt decrease. At the protein level, we found perturbations of urea cycle and related enzymes in the MSFLR during PHLF. Our results suggest that these perturbations may augment urea cycle function, which may be pivotal for increased ammonia elimination after extensive PHs and potential PHLF.NEW & NOTEWORTHY Posthepatectomy liver failure (PHLF) is associated with high mortality. In a rat model of 90% hepatectomy, PHLF is present. Our results on liver tissue proteomics suggest that the ability of the liver remnant to sufficiently eliminate ammonia may be brought about by perturbation related to urea cycle proteins and that enhancing the urea cycle capacity may play a key role in surviving PHLF.

Relationship of intratumoural protein expression patterns to age and Epstein-Barr virus status in classical Hodgkin lymphoma.

In Western countries, the age distribution of Hodgkin lymphoma (HL) follows a characteristic bimodal curve showing an early and a late peak at approximately 35 and 70 yr, respectively. Furthermore, the presence of latent Epstein-Barr virus (EBV) genome in the Hodgkin Reed-Sternberg cells, the tumour cell population of classical HL (cHL), has been found to have adverse prognostic impact in elderly, but not in younger cHL patients. We have characterised the protein expression in tumour tissue samples from younger (≤ 55 yr) and elderly (>55 yr) cHL patients and correlated the findings with EBV status. Differentially expressed proteins according to patients' age as well as tumoural EBV status belonged to different biological functional domains, such as apoptosis, cytoskeletal organisation, response to oxygen levels and regulation of catabolic/metabolic processes. The differential expression of selected proteins, cytosolic aminopeptidase, heterogeneous nuclear ribonucleoprotein K, serotransferrin and alpha-1-antitrypsin was further validated by Western blot analysis. Discovery-based proteomics characterising biological features distinctive for subsets of cHL patients may be useful for the identification of novel biomarkers with potential therapeutic relevance. An evaluation of the prognostic impact of protein expression pattern in general and individually expressed proteins in particular is warranted.

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.

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.

Characterization of the genomic landscape of HIV-associated lymphoma reveals heterogeneity across histological subtypes.

OBJECTIVE: Individuals with human immunodeficiency virus (HIV) experience an increased risk of lymphoma, making this an important cause of death among people with HIV. Nevertheless, little is known regarding the underlying genetic aberrations, which we therefore set out to characterize. DESIGN: We conducted next-generation panel sequencing to explore the mutational status of diagnostic lymphoma biopsies from 18 patients diagnosed with lymphoma secondary to HIV infection. METHODS: Ion Torrent next-generation sequencing was performed with an AmpliSeq panel on diagnostic lymphoma biopsies from HIV-associated B-cell lymphomas (n = 18), comprising diffuse large B-cell lymphoma (n = 9), classic Hodgkin lymphoma (n = 6), Burkitt lymphoma (n = 2), follicular lymphoma (n = 1), and marginal zone lymphoma (n = 1). The panel comprised 69 lymphoid- and/or myeloid-relevant genes, in which either the entire coding sequence or a hotspot region was sequenced. RESULTS: Among the 18 lymphomas, we detected 213 variants. The number of detected mutations ranged from 4 to 41 per tumor distributed among 42 genes, including both exonic and intronic regions. The most frequently mutated genes included KMT2D (67%), TNFAIP3 (50%), and TP53 (61%). Notably, no gene was found to harbor variants across all the HIV-associated lymphomas, nor did we find subtype-specific variants. While some variants were shared among patients, most were unique to the individual patient and were often not reported as malignant genetic variants in databases. CONCLUSION: Our findings demonstrate genetic heterogeneity across histological subtypes of HIV-associated lymphomas and thus help elucidate the genetics and pathophysiological mechanisms underlying the disease.

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.

Proteomic analysis identifies galectin-1 as a predictive biomarker for relapsed/refractory disease in classical Hodgkin lymphoma.

Considerable effort has been spent identifying prognostic biomarkers in classic Hodgkin lymphoma (cHL). The aim of our study was to search for possible prognostic parameters in advanced-stage cHL using a proteomics-based strategy. A total of 14 cHL pretreatment tissue samples from younger, advanced-stage patients were included. Patients were grouped according to treatment response. Proteins that were differentially expressed between the groups were analyzed using 2D-PAGE and identified by liquid chromatography mass spectrometry. Selected proteins were validated using Western blot analysis. One of the differentially expressed proteins, the carbohydrate-binding protein galectin-1 (Gal-1), was further analyzed using immunohistochemistry HC and its expression was correlated with clinicopathologic and outcome parameters in 143 advanced-stage cHL cases. At the univariate level, high Gal-1 expression in the tumor microenvironment was correlated with poor event-free survival (P = .02). Among younger (≤ 61 years) patients, high Gal-1 was correlated with poorer overall and event-free survival (both P = .007). In this patient group and at the multivariate level, high Gal-1 expression retained a significant predictive impact on event-free survival. Therefore, in addition to its functional role in cHL-induced immunosuppression, Gal-1 is also associated with an adverse clinical outcome in this disease.