Diagnostic and predictive biomarkers for lymphoma diagnosis and treatment in the era of precision medicine

Comprehensive genomic characterization of hematologic malignancies at a pediatric tertiary care center

Despite the increasing availability of comprehensive next generation sequencing (NGS), its role in characterizing pediatric hematologic malignancies remains undefined. We describe findings from comprehensive genomic profiling of hematologic malignancies at a pediatric tertiary care center. Patients enrolled on a translational research protocol to aid in cancer diagnosis, prognostication, treatment, and detection of cancer predisposition. Disease-involved samples underwent exome and RNA sequencing and analysis for single nucleotide variation, insertion/deletions, copy number alteration, structural variation, fusions, and gene expression. Twenty-eight patients with hematologic malignancies were nominated between 2018-2021. Eighteen individuals received both germline and somatic sequencing; two received germline sequencing only. Germline testing identified patients with cancer predisposition syndromes and non-cancer carrier states. Fifteen patients (15/18, 83%) had cancer-relevant somatic findings. Potential therapeutic targets were identified in seven patients (7/18, 38.9%); three (3/7, 42.9%) received targeted therapies and remain in remission an average of 47 months later.

An Investigation into Cell-Free DNA in Different Common Cancers

Diagnosis is the most important step in different diseases, especially in cancers and blood malignancies. There are different methods in order to better diagnose of cancer, but many of them are invasive and also, some of them are not useful for immediate diagnosis. Cell-free DNA (cfDNA) or liquid biopsy easily accessible in peripheral blood is one of the non-invasive prognostic biomarkers in various areas of cancer management. In fact, amounts of cfDNA in serum or plasma can be used for diagnosis. In this review, we have considered some cancers such as hepatocellular carcinoma, lung cancer, breast cancer, and hematologic malignancies to compare the various methods of cfDNA diagnosis.

Cancer Biomarkers and Precision Oncology: A Review of Recent Trends and Innovations

The discovery of cancer-specific biomarkers has resulted in major advancements in the field of cancer diagnostics and therapeutics, therefore significantly lowering cancer-related morbidity and mortality. Cancer biomarkers can be generally classified as prognostic biomarkers that predict specific disease outcomes and predictive biomarkers that predict disease response to targeted therapeutic interventions. As research in the area of predictive biomarkers continues to grow, precision medicine becomes far more integrated in cancer treatment. This article presents a general overview on the most recent advancements in the area of cancer biomarkers, immunotherapy, artificial intelligence, and pharmacogenomics of the Middle East.

Personalized treatment using predictive biomarkers in solid organ malignancies: A review

In recent years, the influence of specific biomarkers in the diagnosis and prognosis of solid organ malignancies has been increasingly prominent. The relevance of the use of predictive biomarkers, which predict cancer response to specific forms of treatment provided, is playing a more significant role than ever before, as it affects diagnosis and initiation of treatment, monitoring for efficacy and side effects of treatment, and adjustment in treatment regimen in the long term. In the current review, we explored the use of predictive biomarkers in the treatment of solid organ malignancies, including common cancers such as colorectal cancer, breast cancer, lung cancer, prostate cancer, and cancers associated with high mortalities, such as pancreatic cancer, liver cancer, kidney cancer and cancers of the central nervous system. We additionally analyzed the goals and types of personalized treatment using predictive biomarkers, and the management of various types of solid organ malignancies using predictive biomarkers and their relative efficacies so far in the clinical settings.

Applications of Multimodal Artificial Intelligence in Non-Hodgkin Lymphoma B Cells

Given advancements in large-scale data and AI, integrating multimodal artificial intelligence into cancer research can enhance our understanding of tumor behavior by simultaneously processing diverse biomedical data types. In this review, we explore the potential of multimodal AI in comprehending B-cell non-Hodgkin lymphomas (B-NHLs). B-cell non-Hodgkin lymphomas (B-NHLs) represent a particular challenge in oncology due to tumor heterogeneity and the intricate ecosystem in which tumors develop. These complexities complicate diagnosis, prognosis, and therapy response, emphasizing the need to use sophisticated approaches to enhance personalized treatment strategies for better patient outcomes. Therefore, multimodal AI can be leveraged to synthesize critical information from available biomedical data such as clinical record, imaging, pathology and omics data, to picture the whole tumor. In this review, we first define various types of modalities, multimodal AI frameworks, and several applications in precision medicine. Then, we provide several examples of its usage in B-NHLs, for analyzing the complexity of the ecosystem, identifying immune biomarkers, optimizing therapy strategy, and its clinical applications. Lastly, we address the limitations and future directions of multimodal AI, highlighting the need to overcome these challenges for better clinical practice and application in healthcare.

Magnetic Resonance Elastography of Anterior Mediastinal Tumors

BACKGROUND

Preoperative differentiation of the types of mediastinal tumors is essential. Magnetic resonance (MR) elastography potentially provides a noninvasive method to assess the classification of mediastinal tumor subtypes.

PURPOSE

To evaluate the use of MR elastography in anterior mediastinal masses and to characterize the mechanical properties of tumors of different subtypes.

STUDY TYPE

Prospective.

SUBJECTS

189 patients with anterior mediastinal tumors (AMTs) confirmed by histopathology (62 thymomas, 53 thymic carcinomas, 57 lymphomas, and 17 germ cell tumors).

FIELD STRENGTH/SEQUENCE

A gradient echo-based 2D MR elastography sequence and a diffusion-weighted imaging (DWI) sequence at 3.0 T.

ASSESSMENT

Stiffness and apparent diffusion coefficients (ADC) were measured in AMTs using MR elastography-derived elastograms and DWI-derived ADC maps, respectively. The aim of this study is to identify whether MR elastography can differentiate between the histological subtypes of ATMs.

STATISTICAL TESTS

One-way analysis of variance (ANOVA), two-way ANOVA, Pearson's linear correlation coefficient (r), receiver operating characteristic (ROC) curve analysis; P < 0.05 was considered significant.

RESULTS

Lymphomas had significantly lower stiffness than other AMTs (4.0 ± 0.63 kPa vs. 4.8 ± 1.39 kPa). The mean stiffness of thymic carcinomas was significantly higher than that of other AMTs (5.6 ± 1.41 kPa vs. 4.2 ± 0.94 kPa). Using a cutoff value of 5.0 kPa, ROC analysis showed that lymphomas could be differentiated from other AMTs with an accuracy of 59%, sensitivity of 97%, and specificity of 38%. Using a cutoff value of 5.1 kPa, thymic carcinomas could be differentiated from other AMTs with an accuracy of 84%, sensitivity of 67%, and specificity of 90%. However, there was an overlap in the stiffness values of individual thymomas (4.2 ± 0.71; 3.9-4.5), thymic carcinomas (5.6 ± 1.41; 5.0-6.1), lymphomas (4.0 ± 0.63; 3.8-4.2), and germ cell tumors (4.5 ± 1.79; 3.3-5.6).

DATA CONCLUSION

MR elastography-derived stiffness may be used to evaluate AMTs of various histologies.

LEVEL OF EVIDENCE: 4

TECHNICAL EFFICACY

Stage 2.

An evidence based immunohistochemical panel for diagnosing oral lymphoma along with a case series

Oral lymphomas are rare and present a diagnostic challenge. Immunophenotyping is essential to decipher their biology and identify therapeutic targets. Histopathology can prove to be diagnostically difficult to type these lesions, and hence, immunohistochemistry (IHC) proves useful in deciphering their biology. Here, we present an evidence-based approach using a novel immunohistochemical marker panel to diagnose oral lymphomas by discussing four unique cases.

Molecular complexity of diffuse large B-cell lymphoma: a molecular perspective and therapeutic implications

Diffuse large B-cell lymphoma (DLBCL) stands as a formidable challenge in the landscape of non-Hodgkin's lymphomas. This review illuminates the remarkable strides made in comprehending DLBCL's molecular intricacies and devising targeted treatments. DLBCL, the most prevalent non-Hodgkin's lymphoma, has seen transformative progress in its characterization. Genetic investigations, led by high-throughput sequencing, have unveiled recurrent mutations in genes such as MYC, BCL2, and BCL6, casting light on the underlying genetic chaos propelling DLBCL's aggressiveness. A pivotal facet of this understanding centers on cell signaling pathways. Dysregulation of B-cell receptor (BCR) signaling, NF-κB, PI3K/Akt/mTOR, JAK/STAT, Wnt/β-Catenin, and Toll-like receptor pathways plays a critical role in DLBCL pathogenesis, offering potential therapeutic targets. DLBCL's complex tumor microenvironment (TME) cannot be overlooked. The dynamic interplay among tumor cells, immune cells, stromal components, and the extracellular matrix profoundly influences DLBCL's course and response to therapies. Epigenetic modifications, including DNA methylation and histone changes, add another layer of intricacy. Aberrant epigenetic regulation plays a significant role in lymphomagenesis, offering prospects for epigenetic-based therapies. Promisingly, these molecular insights have spurred the development of personalized treatments. Targeted therapies and immunotherapies, guided by genomic profiling and molecular classification, are emerging as game-changers in DLBCL management. In conclusion, this review underscores the remarkable strides in understanding DLBCL's molecular underpinnings, spanning genetics, cell signaling, the tumor microenvironment, and epigenetics. These advances pave the way for more effective, personalized treatments, renewing hope for DLBCL patients.

MicroRNA Expression Profile in Bone Marrow and Lymph Nodes in B-Cell Lymphomas

Hodgkin's lymphomas (HL) and the majority of non-Hodgkin's lymphomas (NHL) derive from different stages of B-cell differentiation. MicroRNA (miRNA) expression profiles change during lymphopoiesis. Thus, miRNA expression analysis can be used as a reliable diagnostic tool to differentiate tumors. In addition, the identification of miRNA's role in lymphopoiesis impairment is an important fundamental task. The aim of this study was to analyze unique miRNA expression profiles in different types of B-cell lymphomas. We analyzed the expression levels of miRNA-18a, -20a, -96, -182, -183, -26b, -34a, -148b, -9, -150, -451a, -23b, -141, and -128 in lymph nodes (LNs) in the following cancer samples: HL (n = 41), diffuse large B-cell lymphoma (DLBCL) (n = 51), mantle cell lymphoma (MCL) (n = 15), follicular lymphoma (FL) (n = 12), and lymphadenopathy (LA) (n = 37), as well as bone marrow (BM) samples: HL (n = 11), DLBCL (n = 42), MCL (n = 14), FL (n = 16), and non-cancerous blood diseases (NCBD) (n = 43). The real-time RT-PCR method was used for analysis. An increase in BM expression levels of miRNA-26b, -150, and -141 in MCL (p < 0.01) and a decrease in BM levels of the miR-183-96-182 cluster and miRNA-451a in DLBCL (p < 0.01) were observed in comparison to NCBD. We also obtained data on increased LN levels of the miR-183-96-182 cluster in MCL (p < 0.01) and miRNA-18a, miRNA-96, and miRNA-9 in FL (p < 0.01), as well as decreased LN expression of miRNA-150 in DLBCL (p < 0.01), and miRNA-182, miRNA-150, and miRNA-128 in HL (p < 0.01). We showed that miRNA expression profile differs between BM and LNs depending on the type of B-cell lymphoma. This can be due to the effect of the tumor microenvironment.

Analysis of Under-Diagnosed Malignancy during Fine Needle Aspiration Cytology of Lymphadenopathies

Fine needle aspiration cytology (FNAC) is a useful tool in the evaluation of lymphadenopathy. It is a safe and minimally invasive procedure that provides preoperative details for subsequent treatment. It can also diagnose the majority of malignant tumors. However, there are some instances where the diagnosis of tumors remains obscure. To address this, we re-analyzed the misinterpreted patients' samples using mRNA sequencing technology and then identified the characteristics of non-Hodgkin's lymphoma that tend to be under-diagnosed. To decipher the involved genes and pathways, we used bioinformatic and biological analysis approaches, identifying the response to oxygen species, inositol phosphate metabolic processes, and peroxisome and PPAR pathways as possibly being involved with this type of tumor. Notably, these analyses identified FOS, ENDOG, and PRKAR2B as hub genes. cBioPortal, a multidimensional cancer genomics database, also confirmed that these genes were associated with lymphoma patients. These results thus point to candidate genes that could be used as biomarkers to minimize the false-negative rate of FNAC diagnosis. We are currently pursuing the development of a gene chip to improve the diagnosis of lymphadenopathy patients with the ultimate goal of improving their prognosis.

Current and potential roles of immuno-PET/-SPECT in CAR T-cell therapy

Chimeric antigen receptor (CAR) T-cell therapies have evolved as breakthrough treatment options for the management of hematological malignancies and are also being developed as therapeutics for solid tumors. However, despite the impressive patient responses from CD19-directed CAR T-cell therapies, ~ 40%-60% of these patients' cancers eventually relapse, with variable prognosis. Such relapses may occur due to a combination of molecular resistance mechanisms, including antigen loss or mutations, T-cell exhaustion, and progression of the immunosuppressive tumor microenvironment. This class of therapeutics is also associated with certain unique toxicities, such as cytokine release syndrome, immune effector cell-associated neurotoxicity syndrome, and other "on-target, off-tumor" toxicities, as well as anaphylactic effects. Furthermore, manufacturing limitations and challenges associated with solid tumor infiltration have delayed extensive applications. The molecular imaging modalities of immunological positron emission tomography and single-photon emission computed tomography (immuno-PET/-SPECT) offer a target-specific and highly sensitive, quantitative, non-invasive platform for longitudinal detection of dynamic variations in target antigen expression in the body. Leveraging these imaging strategies as guidance tools for use with CAR T-cell therapies may enable the timely identification of resistance mechanisms and/or toxic events when they occur, permitting effective therapeutic interventions. In addition, the utilization of these approaches in tracking the CAR T-cell pharmacokinetics during product development and optimization may help to assess their efficacy and accordingly to predict treatment outcomes. In this review, we focus on current challenges and potential opportunities in the application of immuno-PET/-SPECT imaging strategies to address the challenges encountered with CAR T-cell therapies.

Combination of FDG PET/CT Radiomics and Clinical Parameters for Outcome Prediction in Patients with Hodgkin’s Lymphoma

Purpose: The aim of the study is to evaluate the prognostic value of a joint evaluation of PET and CT radiomics combined with standard clinical parameters in patients with HL. Methods: Overall, 88 patients (42 female and 46 male) with a median age of 43.3 (range 21–85 years) were included. Textural analysis of the PET/CT images was performed using freely available software (LIFE X). 65 radiomic features (RF) were evaluated. Univariate and multivariate models were used to determine the value of clinical characteristics and FDG PET/CT radiomics in outcome prediction. In addition, a binary logistic regression model was used to determine potential predictors for radiotherapy treatment and odds ratios (OR), with 95% confidence intervals (CI) reported. Features relevant to survival outcomes were assessed using Cox proportional hazards to calculate hazard ratios with 95% CI. Results: albumin (p = 0.034) + ALP (p = 0.028) + CT radiomic feature GLRLM GLNU mean (p = 0.012) (Area under the curve (AUC): 95% CI (86.9; 100.0)—Brier score: 3.9, 95% CI (0.1; 7.8) remained significant independent predictors for PFS outcome. PET-SHAPE Sphericity (p = 0.033); CT grey-level zone length matrix with high gray-level zone emphasis (GLZLM SZHGE mean (p = 0.028)); PARAMS XSpatial Resampling (p = 0.0091) as well as hemoglobin results (p = 0.016) remained as independent factors in the final model for a binary outcome as predictors of the need for radiotherapy (AUC = 0.79). Conclusion: We evaluated the value of baseline clinical parameters as well as combined PET and CT radiomics in HL patients for survival and the prediction of the need for radiotherapy treatment. We found that different combinations of all three factors/features were independently predictive of the here evaluated endpoints.

A Spectrum of Metastases to the Breast: Radiologic-Pathologic Correlation

Metastases to the breast from non-mammary origin are rare. The majority of these lesions appear as secondary manifestations of melanoma and lymphoma, followed by lung carcinomas, gynecological carcinomas, and sarcomas. There has been a steady trend of an increase in diagnosis of intramammary metastases owing to the current advances in imaging technology. Imaging features depend on the type of primary neoplasm and route of dissemination, some of which resemble primary breast cancer and benign breast entities. There are certain imaging features that raise the level of suspicion for metastases in the correct clinical context. However, imaging manifestations of intramammary metastases do not always comply with the known classic patterns. The aim of this review is to clarify these features, emphasizing radiologic-pathologic correlation and a multidisciplinary approach, since most cases are found in patients with advanced disease.

Treatment Resulting Changes in Volumes of High-18F-FDG-Uptake Adipose Tissues over Orbit and Epicardium Correlate with Treatment Response for Non-Hodgkin's Lymphoma

BACKGROUND

A regimen of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) is the standard treatment for non-Hodgkin's lymphoma. Brown adipose tissue possesses anti-cancer potential. This study aimed to explore practical biomarkers for non-Hodgkin's lymphoma by analyzing the metabolic activity of adipose tissue.

METHODS

Twenty patients who received R-CHOP for non-Hodgkin's lymphoma were reviewed. Positron emission tomography/computed tomography (PET/CT) images, lactate dehydrogenase (LDH) levels, and body mass index (BMI) before and after treatment were collected. Regions with a high standardized uptake value (SUV) in epicardial and orbital adipose tissue were selected and analyzed by a PET/CT viewer. The initial measurements and changes in the high SUV of epicardial and orbital adipose tissues, LDH levels, and BMI of treatment responders and non-responders, and complete and partial responders, were compared.

RESULTS

The volumes of high-SUV epicardial and orbital adipose tissues significantly increased in responders after R-CHOP (p = 0.03 and 0.002, respectively). There were significant differences between changes in the high-SUV volumes of epicardial and orbital adipose tissues (p = 0.03 and 0.001, respectively) and LDH levels (p = 0.03) between responders and non-responders. The changes in high-SUV epicardial adipose tissue volumes were greater among complete responders than partial responders (p = 0.04). Poorer treatment responses were observed in patients with lower high-SUV epicardial adipose tissue volumes and higher LDH levels after R-CHOP (p = 0.03 and 0.03, respectively).

CONCLUSIONS

The preliminary results of greater changes in high-SUV epicardial and orbital adipose tissue volumes among responders indicate that brown adipose tissue could be considered a favorable prognostic biomarker.

The Research Advances of Aptamers in Hematologic Malignancies

Currently, research for hematological malignancies is very intensive, with many breakthroughs. Among them, aptamer-based targeted therapies could be counted. Aptamer is a targeting tool with many unique advantages (easy synthesis, low toxicity, easy modification, low immunogenicity, nano size, long stability, etc.), therefore many experts screened corresponding aptamers in various hematological malignancies for diagnosis and treatment. In this review, we try to summarize and provide the recent progress of aptamer research in the diagnosis and treatment of hematologic malignancies. Until now, 29 aptamer studies were reported in hematologic malignancies, of which 12 aptamers were tested in vivo and the remaining 17 aptamers were only tested in vitro. In this case, 11 aptamers were combined with chemotherapeutic drugs for the treatment of hematologic malignancies, 4 aptamers were used in combination with nanomaterials for the diagnosis and treatment of hematologic malignancies, and some studies used aptamers for the targeted transportation of siRNA and miRNA for targeted therapeutic effects. Their research provides multiple approaches to achieve more targeted goals. These findings show promising and encouraging future for both hematological malignancies basic and clinical trials research.

Tackling Mantle Cell Lymphoma in Europe

An expert panel convened by the European Alliance for Personalized Medicine (EAPM) reflected on achievements and outstanding challenges in Europe in mantle cell lymphoma (MCL). Through the prism of member state experience, the panel noted advances in outcomes over the last decade, but highlighted issues constituting barriers to better care. The list notably included availability of newer treatments, infrastructure and funding for related testing, and shortages of relevant skills and of research support. The prospect of improvements was held to reside in closer coordination and cooperation within and between individual countries, and in changes in policy and scale of investment at both national and EU levels.

Clinical Application of Biomarkers for Hematologic Malignancies

Over the last decade, significant advancements have been made in the molecular mechanisms, diagnostic methods, prognostication, and treatment options in hematologic malignancies. As the treatment landscape continues to expand, personalized treatment is much more important.

With the development of new technologies, more sensitive evaluation of residual disease using flow cytometry and next generation sequencing is possible nowadays. Although some conventional biomarkers preserve their significance, novel potential biomarkers accurately detect the mutational landscape of different cancers, and also, serve as prognostic and predictive biomarkers, which can be used in evaluating therapy responses and relapses. It is likely that we will be able to offer a more targeted and risk-adapted therapeutic approach to patients with hematologic malignancies guided by these potential biomarkers. This chapter summarizes the biomarkers used (or proposed to be used) in the diagnosis and/or monitoring of hematologic neoplasms.;

Identification of technology frontiers of artificial intelligence-assisted pathology based on patent citation network

OBJECTIVES

This paper aimed to identify the technology frontiers of artificial intelligence-assisted pathology based on patent citation network.

METHODS

Patents related to artificial intelligence-assisted pathology were searched and collected from the Derwent Innovation Index (DII), which were imported into Derwent Data Analyzer (DDA, Clarivate Derwent, New York, NY, USA) for authority control, and imported into the freely available computer program Ucinet 6 for drawing the patent citation network. The patent citation network according to the citation relationship could describe the technology development context in the field of artificial intelligence-assisted pathology. The patent citations were extracted from the collected patent data, selected highly cited patents to form a co-occurrence matrix, and built a patent citation network based on the co-occurrence matrix in each period. Text clustering is an unsupervised learning method, an important method in text mining, where similar documents are grouped into clusters. The similarity between documents are determined by calculating the distance between them, and the two documents with the closest distance are combined. The method of text clustering was used to identify the technology frontiers based on the patent citation network, which was according to co-word analysis of the title and abstract of the patents in this field.

RESULTS

1704 patents were obtained in the field of artificial intelligence-assisted pathology, which had been currently undergoing three stages, namely the budding period (1992-2000), the development period (2001-2015), and the rapid growth period (2016-2021). There were two technology frontiers in the budding period (1992-2000), namely systems and methods for image data processing in computerized tomography (CT), and immunohistochemistry (IHC), five technology frontiers in the development period (2001-2015), namely spectral analysis methods of biomacromolecules, pathological information system, diagnostic biomarkers, molecular pathology diagnosis, and pathological diagnosis antibody, and six technology frontiers in the rapid growth period (2016-2021), namely digital pathology (DP), deep learning (DL) algorithms-convolutional neural networks (CNN), disease prediction models, computational pathology, pathological image analysis method, and intelligent pathological system.

CONCLUSIONS

Artificial intelligence-assisted pathology was currently in a rapid development period, and computational pathology, DL and other technologies in this period all involved the study of algorithms. Future research hotspots in this field would focus on algorithm improvement and intelligent diagnosis in order to realize the precise diagnosis. The results of this study presented an overview of the characteristics of research status and development trends in the field of artificial intelligence-assisted pathology, which could help readers broaden innovative ideas and discover new technological opportunities, and also served as important indicators for government policymaking.

Baseline Total Metabolic Tumor Volume is Prognostic for Refractoriness to Immunochemotherapy in DLBCL: Results From GOYA

INTRODUCTION

A good response to initial therapy is key to maximizing survival in patients with diffuse large B-cell lymphoma (DLBCL), but patients with chemorefractory disease and early progression have poor outcomes.

PATIENTS AND METHODS

Data from the GOYA study in patients with DLBCL who received first-line rituximab or obinutuzumab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) were analyzed. Positron emission tomography/computed tomography (PET/CT)-derived characteristics associated with total metabolic tumor volume (TMTV) and clinical risk factors for primary chemorefractory disease and disease progression within 12 months (POD12) were explored.

RESULTS

Of those patients fulfilling the criteria for analysis, 108/1126 (10%) were primary chemorefractory and 147/1106 (13%) had POD12. Primary chemorefractory and POD12 status were strongly associated with reduced overall survival. After multivariable analysis of clinical and imaging-based risk factors by backward elimination, only very high TMTV (quartile [Q] 1 vs. Q4 odds ratio [OR]: 0.45; P = .006) and serum albumin levels (low vs. normal OR of 1.86; P = .004) were associated with primary chemorefractoriness. After additionally accounting for BCL2/MYC translocation in a subset of patients, TMTV and BCL2/MYC double-hit status remained as significant predictors of primary chemorefractoriness (Q1 vs. Q4 OR: 0.32, P = .01 and double-hit vs. no-hit OR of 4.47, P = .02, respectively). Risk factors including very high TMTV, high sum of the product of the longest diameters (SPD), geographic region (Asia), short time since diagnosis, extranodal involvement and low serum albumin were retained for POD12.

CONCLUSION

PET-derived TMTV has prognostic value in identifying patients at risk of early treatment failure.

High-Throughput CRISPR Screening in Hematological Neoplasms

CRISPR is becoming an indispensable tool in biological research, revolutionizing diverse fields of medical research and biotechnology. In the last few years, several CRISPR-based genome-targeting tools have been translated for the study of hematological neoplasms. However, there is a lack of reviews focused on the wide uses of this technology in hematology. Therefore, in this review, we summarize the main CRISPR-based approaches of high throughput screenings applied to this field. Here we explain several libraries and algorithms for analysis of CRISPR screens used in hematology, accompanied by the most relevant databases. Moreover, we focus on (1) the identification of novel modulator genes of drug resistance and efficacy, which could anticipate relapses in patients and (2) new therapeutic targets and synthetic lethal interactions. We also discuss the approaches to uncover novel biomarkers of malignant transformations and immune evasion mechanisms. We explain the current literature in the most common lymphoid and myeloid neoplasms using this tool. Then, we conclude with future directions, highlighting the importance of further gene candidate validation and the integration and harmonization of the data from CRISPR screening approaches.

Evidence that PKCα inhibition in Dalton's Lymphoma cells augments cell cycle arrest and mitochondrial-dependent apoptosis

Protein kinase Cα (PKCα), belonging to ser/thr protein kinase, perform various biological functions. Overexpression of PKCα has been observed in multiple human malignancies including lymphoma. However, the molecular pathogenesis and involvement of PKCα in Non-Hodgkin lymphoma (NHL) are not clearly understood. Hence, deciphering the role of PKCα in NHL management may provide a better therapeutic option. In the present study, we used selective pharmacological inhibitors Gö6976 and Ro320432 that potentially inhibit PKCα-mediated signaling in DL cells, resulting in the inhibition of cell growth and mitochondrial-dependent apoptosis. PKCα inhibition by these inhibitors also displays cell cycle arrest at the G1 phase and causes growth retardation of DL cells. Our results extended the mechanism of PKCα in NHL, and provided potential implications for its therapy.

Transcriptome integration analysis and specific diagnosis model construction for Hodgkin's lymphoma, diffuse large B-cell lymphoma, and mantle cell lymphoma

Transcriptome differences between Hodgkin's lymphoma (HL), diffuse large B-cell lymphoma (DLBCL), and mantle cell lymphoma (MCL), which are all derived from B cell, remained unclear. This study aimed to construct lymphoma-specific diagnostic models by screening lymphoma marker genes. Transcriptome data of HL, DLBCL, and MCL were obtained from public databases. Lymphoma marker genes were screened by comparing cases and controls as well as the intergroup differences among lymphomas. A total of 9 HL marker genes, 7 DLBCL marker genes, and 4 MCL marker genes were screened in this study. Most HL marker genes were upregulated, whereas DLBCL and MCL marker genes were downregulated compared to controls. The optimal HL-specific diagnostic model contains one marker gene (MYH2) with an AUC of 0.901. The optimal DLBCL-specific diagnostic model contains 7 marker genes (LIPF, CCDC144B, PRO2964, PHF1, SFTPA2, NTS, and HP) with an AUC of 0.951. The optimal MCL-specific diagnostic model contains 3 marker genes (IGLV3-19, IGKV4-1, and PRB3) with an AUC of 0.843. The present study reveals the transcriptome data-based differences between HL, DLBCL, and MCL, when combined with other clinical markers, may help the clinical diagnosis and prognosis.

Real-world evidence of cytomegalovirus reactivation in non-Hodgkin lymphomas treated with bendamustine-containing regimens

Cytomegalovirus (CMV) reactivation during chemotherapy or after organ or hematopoietic stem cell transplantation is a major cause of morbidity and mortality, and the risk of reactivation increases with patients’ age. Bendamustine, an alkylating agent currently used for treatment of indolent and aggressive non-Hodgkin lymphomas, can augment the risk of secondary infections including CMV reactivation. In this real-world study, we described an increased incidence of CMV reactivation in older adults (age >60 years old) with newly diagnosed and relapsed/refractory indolent and aggressive diseases treated with bendamustine-containing regimens. In particular, patients who received bendamustine plus rituximab and dexamethasone were at higher risk of CMV reactivation, especially when administered as first-line therapy and after the third course of bendamustine. In addition, patients with CMV reactivation showed a significant depression of circulating CD4⁺ T cell count and anti-CMV IgG levels during active infection, suggesting an impairment of immune system functions which are not able to properly face viral reactivation. Therefore, a close and early monitoring of clinical and laboratory findings might improve clinical management and outcome of non-Hodgkin lymphoma patients by preventing the development of CMV disease in a subgroup of subjects treated with bendamustine more susceptible to viral reactivation.

Lymphomagenesis predictors and related pathogenesis

Sjögren's syndrome (SS) is a systemic autoimmune disease characterised by a wide range of clinical manifestations and complications, including B-cell lymphoma. This study aims to describe the predictors associated with lymphomagenesis in patients with Sjögren's syndrome, emphasising the pathophysiological bases that support this association. We performed a review of the literature published through a comprehensive search strategy in PubMed/MEDLINE, Scopus, and Web of science. Forty publications describing a total of 45,208 patients with SS were retrieved. The predictors were grouped according to their pathophysiological role in the lymphoproliferation process. Also, some new biomarkers such as MicroRNAs, P2X7 receptor-NLRP3 inflammasome, Thymic stromal lymphopoietin, and Three-prime repair exonuclease 1 (TREX1) were identified. The knowledge of the pathophysiology allows the discrimination of markers that participate in the initial stages. Considering that the lymphoproliferation process includes the progression of lymphoma towards more aggressive subtypes, it is essential to recognise biomarkers associated with a worse prognosis.

Protein Carbonylation and Lipid Peroxidation in Hematological Malignancies

Among the different mechanisms involved in oxidative stress, protein carbonylation and lipid peroxidation are both important modifications associated with the pathogenesis of several diseases, including cancer. Hematopoietic cells are particularly vulnerable to oxidative damage, as the excessive production of reactive oxygen species and associated lipid peroxidation suppress self-renewal and induce DNA damage and genomic instability, which can trigger malignancy. A richer understanding of the clinical effects of oxidative stress might improve the prognosis of these diseases and inform therapeutic strategies. The most common protein carbonylation and lipid peroxidation compounds, including hydroxynonenal, malondialdehyde, and advanced oxidation protein products, have been investigated for their potential effect on hematopoietic cells in several studies. In this review, we focus on the most important protein carbonylation and lipid peroxidation biomarkers in hematological malignancies, their role in disease development, and potential treatment implications.

Artificial Intelligence-Driven Structurization of Diagnostic Information in Free-Text Pathology Reports

BACKGROUND

Free-text sections of pathology reports contain the most important information from a diagnostic standpoint. However, this information is largely underutilized for computer-based analytics. The vast majority of NLP-based methods lack a capacity to accurately extract complex diagnostic entities and relationships among them as well as to provide an adequate knowledge representation for downstream data-mining applications.

METHODS

In this paper, we introduce a novel informatics pipeline that extends open information extraction (openIE) techniques with artificial intelligence (AI) based modeling to extract and transform complex diagnostic entities and relationships among them into Knowledge Graphs (KGs) of relational triples (RTs).

RESULTS

Evaluation studies have demonstrated that the pipeline's output significantly differs from a random process. The semantic similarity with original reports is high (Mean Weighted Overlap of 0.83). The precision and recall of extracted RTs based on experts' assessment were 0.925 and 0.841 respectively (P <0.0001). Inter-rater agreement was significant at 93.6% and inter-rated reliability was 81.8%.

CONCLUSION

The results demonstrated important properties of the pipeline such as high accuracy, minimality and adequate knowledge representation. Therefore, we conclude that the pipeline can be used in various downstream data-mining applications to assist diagnostic medicine.

DZNep-mediated apoptosis in B-cell lymphoma is independent of the lymphoma type, EZH2 mutation status and MYC, BCL2 or BCL6 translocations

Enhancer of zeste homolog 2 (EZH2) tri-methylates histone 3 at position lysine 27 (H3K27me3). Overexpression and gain-of-function mutations in EZH2 are regarded as oncogenic drivers in lymphoma and other malignancies due to the silencing of tumor suppressors and differentiation genes. EZH2 inhibition is sought to represent a good strategy for tumor therapy. In this study, we treated Burkitt lymphoma (BL) and diffuse large B-cell lymphoma (DLBCL) cell lines with 3-deazaneplanocin—A (DZNep), an indirect EZH2 inhibitor which possesses anticancer properties both in-vitro and in-vivo. We aimed to address the impact of the lymphoma type, EZH2 mutation status, as well as MYC, BCL2 and BCL6 translocations on the sensitivity of the lymphoma cell lines to DZNep-mediated apoptosis. We show that DZNep inhibits proliferation and induces apoptosis of these cell lines independent of the type of lymphoma, the EZH2 mutation status and the MYC, BCL2 and BCL6 rearrangement status. Furthermore, DZNep induced a much stronger apoptosis in majority of these cell lines at a lower concentration, and within a shorter period when compared with EPZ-6438, a direct EZH2 inhibitor currently in phase II clinical trials. Apoptosis induction by DZNep was both concentration-dependent and time-dependent, and was associated with the inhibition of EZH2 and subsequent downregulation of H3K27me3 in DZNep-sensitive cell lines. Although EZH2, MYC, BCL2 and BCL6 are important prognostic biomarkers for lymphomas, our study shows that they poorly influence the sensitivity of lymphoma cell lines to DZNep-mediated apoptosis.

"Triple hit" lymphomas: A retrospective cytology case series of an uncommon high grade B-cell malignancy with C-MYC, BCL-2 and BCL-6 rearrangements

The Revised fourth Edition World Health Organization (WHO) Classification of Tumors of Hematopoietic and Lymphoid Tissues suggests novel categories, including "high grade B-cell lymphoma with MYC and BCL2 and BCL6 gene rearrangements." These diseases are known colloquially as "double hit" and "triple hit" lymphomas. The "first-hit" in these cases is the harboring of a MYC rearrangement. Concurrent derangements of BCL2 and BCL6 can be the "second-hit" or "third-hit." To our knowledge, this is the first report of "triple-hit" lymphomas in cytology specimens. The files of the Cleveland Clinic (January 2007 through December 2017) were searched for all "triple hit" lymphomas. Four cases met inclusion criteria (cytology slides in files and histologically confirmed "triple hit" lymphoma). All slides were reviewed. The mean age was 65 years, with a male predominance. All patients presented at advanced stage and showed progressive disease despite therapy. FISH studies (histologic sections) confirmed translocations of MYC (8q24), BCL2 (18q21) and BCL6 (3q27) in all patients. All cases were characterized by high cellularity, dispersed cells, presence of stripped nuclei, lymphoglandular bodies, apoptotic bodies, cytomegaly, nucleomegaly, nuclear envelope irregularities, macronucleoli (most often single), recognizable mitoses and presence of cytoplasmic vacuoles (variable). The WHO recommends that all large B-cell lymphomas be investigated using cytogenetic or molecular techniques. Concurrent inhibition of MYC and BCL2 is a potentially effective treatment strategy for triple hit lymphomas, and an expanding literature exists regarding predictive biomarkers and therapeutic regimens. It is our intention to raise awareness of this uncommon mature B-cell neoplasm within the cytodiagnostic community.

[Study of the evolution in the activity of a Department of Pathology from a third level hospital in the last decade (2007-2016)]

OBJECTIVE

To study the evolution of variables of interest in a department of pathology from a third level hospital during the last decade and to evaluate the impact on these of the hospital relocation in 2014.

MATERIAL AND METHOD

Retrospective observational study in which the recorded samples (biopsies, cytology specimens, FNA, autopsies, intraoperative) as well as the complementary techniques (IHC, Histochemistry, IF and FISH) and portfolio of services were analyzed during the years 2007-2016 inclusive. For the statistical analysis, the five-year periods 2007-2011 and 2012-2016 were compared.

RESULTS

The following variables were statistically significant: cytology (34055.8±1994.0 vs 26590.4±2938.3, p=0.002), autopsies (156.2±27.3 vs 122.0±14.78, p=0.039), immunohistochemistry (17855.4±3424.2 vs 28559.2±4734.7, p=0.003), histochemistry (11117.8±2300.9 vs 6225.0±1330.5, p=0.003) and immunofluorescence (610.2±185.3 vs. 1205.4±154.0, p=0.001). Statistical correlations of interest among variables have been identified. In 2014, it was observed that the variables of greater specific weight (biopsies, cytology, IHQ and histochemistry) in the work load of the Department showed an average decrease of 12.5%. A generalized increase in the panel of available samples has been identified, the largest increase being seen in the number of antibodies (78.7%), histochemistry (38.7%) and FISH (400%).

CONCLUSION

Relevant variations in work volume, as well as the service portfolio, have been identified, especially in the techniques aimed at improving diagnostic accuracy (IHQ and FI), and a significant decrease in the number of cytology specimens, autopsies and histochemistry. In the year 2014 a decrease of more than 12% in the main variables of the study was observed.

EMT- and MET-related processes in nonepithelial tumors: importance for disease progression, prognosis, and therapeutic opportunities

The epithelial-to mesenchymal (EMT) process is increasingly recognized for playing a key role in the progression, dissemination, and therapy resistance of epithelial tumors. Accumulating evidence suggests that EMT inducers also lead to a gain in mesenchymal properties and promote malignancy of nonepithelial tumors. In this review, we present and discuss current findings, illustrating the importance of EMT inducers in tumors originating from nonepithelial/mesenchymal tissues, including brain tumors, hematopoietic malignancies, and sarcomas. Among these tumors, the involvement of mesenchymal transition has been most extensively investigated in glioblastoma, providing proof for cell autonomous and microenvironment-derived stimuli that provoke EMT-like processes that regulate stem cell, invasive, and immunogenic properties as well as therapy resistance. The involvement of prominent EMT transcription factor families, such as TWIST, SNAI, and ZEB, in promoting therapy resistance and tumor aggressiveness has also been reported in lymphomas, leukemias, and sarcomas. A reverse process, resembling mesenchymal-to-epithelial transition (MET), seems particularly relevant for sarcomas, where (partial) epithelial differentiation is linked to less aggressive tumors and a better patient prognosis. Overall, a hybrid model in which more stable epithelial and mesenchymal intermediates exist likely extends to the biology of tumors originating from sources other than the epithelium. Deeper investigation and understanding of the EMT/MET machinery in nonepithelial tumors will shed light on the pathogenesis of these tumors, potentially paving the way toward the identification of clinically relevant biomarkers for prognosis and future therapeutic targets.

Cytologic perspectives on neoteric B-cell lymphoproliferative disorders

The 2008 World Health Organization (WHO) classification of hematopoietic and lymphoid tissues has been recently revised, and publication of the updated 2016 version is expected soon. Given that cytopathologists are often involved in the diagnosis of primary, recurrent, and transformed lymphoproliferative disorders, knowledge of updates to the WHO lymphoma classification, including terminology, pathogenesis, ancillary techniques, and targeted therapies is necessary. Herein, we reference the last decade of cytology specific literature for seven newer B-cell disorders and provide illustrative examples of each entity from our files.

Detection of single cell heterogeneity in cancer

Single cell heterogeneity has already been highlighted in cancer classification, diagnosis, and treatment. Recent advanced technologies have gained more ability to reveal the heterogeneity on single cell level. In this review, we listed various detection targets applied in single cell study, including tumor tissue cells, circulating tumor cells (CTCs), disseminated tumor cells (DTCs), circulating tumor DNA (ctDNA), cell-free DNA (cfDNA), and cancer stem cells (CSCs). We further discussed and compared detection methods using these detection targets in different fields to reveal single cell heterogeneity in cancer. We focused not only on the methods that have already been established and validated, but also on newly developed methods. In morphology and phenotype, the methods mainly included cell imaging and immune-staining. In genomics and proteomics, the main methods were single cell sequencing and single cell western blotting. Collectively, from using these methods, we can have a better understanding of the single cell variation, as well as what kind of variation it is and how the variation works. Our observations imply that study on single cell heterogeneity in cancer is an important step to precision medicine. The development of technologies in detection of single cell heterogeneity will be sure to improve the diagnosis and treatment in cancer.