Systems Drug Discovery for Diffuse Large B Cell Lymphoma Based on Pathogenic Molecular Mechanism via Big Data Mining and Deep Learning Method

Diffuse large B cell lymphoma (DLBCL) is an aggressive heterogeneous disease. The most common subtypes of DLBCL include germinal center b-cell (GCB) type and activated b-cell (ABC) type. To learn more about the pathogenesis of two DLBCL subtypes (i.e., DLBCL ABC and DLBCL GCB), we firstly construct a candidate genome-wide genetic and epigenetic network (GWGEN) by big database mining. With the help of two DLBCL subtypes’ genome-wide microarray data, we identify their real GWGENs via system identification and model order selection approaches. Afterword, the core GWGENs of two DLBCL subtypes could be extracted from real GWGENs by principal network projection (PNP) method. By comparing core signaling pathways and investigating pathogenic mechanisms, we are able to identify pathogenic biomarkers as drug targets for DLBCL ABC and DLBCL GCD, respectively. Furthermore, we do drug discovery considering drug-target interaction ability, drug regulation ability, and drug toxicity. Among them, a deep neural network (DNN)-based drug-target interaction (DTI) model is trained in advance to predict potential drug candidates holding higher probability to interact with identified biomarkers. Consequently, two drug combinations are proposed to alleviate DLBCL ABC and DLBCL GCB, respectively.     

Stress-induced DNA damage: a case study in diffuse large B-cell lymphoma

DNA damage is one of the mechanisms of mutagenesis. Sequence integrity may be affected by the action of thermal changes, chemical agents, both endogenous and exogenous, and other environmental issues. Abnormally high mutation rates are referred to as genomic instability: a phenomenon closely related to the onset of cancer. Mutant genotypes may be able to confer some kind of selective advantage on subclonal cell populations, leading them to multiply until dominance in a localized tissue environment that later becomes the tumour. Cellular stress, especially that of oxidative and ionic nature, is a recognized trigger for DNA-damaging processes. A physico-chemical model has shown that high hysteresis rates in DNA denaturation curves may be indicative of dissipative processes inducing DNA damage, thus potentially leading to uncontrolled mutagenesis and genome instability. We here study selectively to what extent this phenomenon may occur by analysing the sequence length and composition effects on the thermodynamic behaviour and the presence of hysteresis in pressure-driven DNA denaturation; pronounced hysteresis in the denaturation/renaturation curves may indicate thermal susceptibility to DNA damage. In particular, we consider highly mutated regions of the genome characterized in diffuse large B-cell lymphoma on a recent whole exome next-generation sequencing effort.     

Nanoscale distribution of CD20 on B‐cell lymphoma tumour cells and its potential role in the clinical efficacy of rituximab

Rituximab is an exciting monoclonal antibody drug approved for treating B‐cell lymphomas and its target is the CD20 antigen which is expressed on the surface of B cells. In recent years, the variable efficacies of rituximab among different lymphoma patients have become an important clinical issue and urgently need to be solved for further development of antibodies with enhanced efficacies. In this work, atomic force microscopy (AFM) was used to investigate the nanoscale distribution of CD20 on the surface of tumour B cells from lymphoma patients to examine its potential role in the clinical therapeutic effects of rituximab. By performing ROR1 fluorescence labelling (ROR1 is a specific tumour cell surface marker) on the bone marrow cells prepared from B‐cell lymphoma patients, the tumour B cells were recognized, and then AFM tips carrying rituximabs via polyethylene glycol crosslinkers were moved to the tumour cells to probe the specific CD20‐rituximab interactions. By applying AFM single‐molecule force spectroscopy (SMFS) at the local areas (500×500 nm²) on the surface of tumour B cells, the nanoscale distributions of CD20 on the surface of tumour B cells were mapped, visually showing that CD20 distributed heterogeneously on the cell surface. Bone marrow cell samples from three clinical B‐cell lymphoma cases were collected to analyze the binding affinity and nanoscale distribution of CD20 on tumour cells. The experimental results showed that CD20 distribution on tumour cells were to some extent related to the clinical therapeutic outcomes while the CD20‐rituximab binding forces did not have distinct effects to the clinical outcomes. These results can provide novel insights in understanding the rituximab's clinical efficacies from the nanoscale distribution of CD20 on the tumour cells at single‐cell and single‐molecule levels.     

Classification and Diagnosis of Lymphoma’s Histopathological Images Using Transfer Learning

Current cancer diagnosis procedure requires expert knowledge and is time-consuming, which raises the need to build an accurate diagnosis support system for lymphoma identification and classification. Many studies have shown promising results using Machine Learning and, recently, Deep Learning to detect malignancy in cancer cells. However, the diversity and complexity of the morphological structure of lymphoma make it a challenging classification problem. In literature, many attempts were made to classify up to four simple types of lymphoma. This paper presents an approach using a reliable model capable of diagnosing seven different categories of rare and aggressive lymphoma. These Lymphoma types are Classical Hodgkin Lymphoma, Nodular Lymphoma Predominant, Burkitt Lymphoma, Follicular Lymphoma, Mantle Lymphoma, Large B-Cell Lymphoma, and T-Cell Lymphoma. Our proposed approach uses Residual Neural Networks, ResNet50, with a Transfer Learning for lymphoma’s detection and classification. The model used results are validated according to the performance evaluation metrics: Accuracy, precision, recall, F-score, and kappa score for the seven multi-classes. Our algorithms are tested, and the results are validated on 323 images of 224 × 224 pixels resolution. The results are promising and show that our used model can classify and predict the correct lymphoma subtype with an accuracy of 91.6%.     

Spatial analysis of air pollution and cancer incidence rates in Haifa Bay, Israel

The Israel National Cancer Registry reported in 2001 that cancer incidence rates in the Haifa area are roughly 20% above the national average. Since Haifa has been the major industrial center in Israel since 1930, concern has been raised that the elevated cancer rates may be associated with historically high air pollution levels. This work tests whether persistent spatial patterns of metrics of chronic exposure to air pollutants are associated with the observed patterns of cancer incidence rates. Risk metrics of chronic exposure to PM₁₀, emitted both by industry and traffic, and to SO₂, a marker of industrial emissions, was developed. Ward-based maps of standardized incidence rates of three prevalent cancers: Non-Hodgkin's lymphoma, lung cancer and bladder cancer were also produced. Global clustering tests were employed to filter out those cancers that show sufficiently random spatial distribution to have a nil probability of being related to the spatial non-random risk maps. A Bayesian method was employed to assess possible associations between the morbidity and risk patterns, accounting for the ward-based socioeconomic status ranking. Lung cancer in males and bladder cancer in both genders showed non-random spatial patterns. No significant associations between the SO₂-based risk maps and any of the cancers were found. Lung cancer in males was found to be associated with PM₁₀, with the relative risk associated with an increase of 1 μg/m³ of PM₁₀ being 12%. Special consideration of wards with expected rates < 1 improved the results by decreasing the variance of the spatially correlated residual log-relative risk.     

Renal involvement of mantle cell lymphona leading to end stage renal disease

Mantle cell lymphoma (MCL), owing to its insensitivity to chemotherapy, has a poor prognosis, with a median survival of 3 years to 4 years. MCL frequently infiltrates other organs. However, reports involving kidney in living patients are rare. Here, we report a case of MCL with renal involvement leading to end stage renal disease that required renal replacement therapy. A 69-year-old man diagnosed with MCL 3 years earlier was admitted to our emergency room due to uremic symptoms. After eight cycles of chemotherapy, he had displayed complete remission, but experienced a recurrence 1.5 years later; after refusing chemotherapy, the patient was lost on follow-up in the final 10 months. On presentation at the emergency room, the patient's serum blood urea nitrogen was 109.5 mg/dL, and creatinine was 11.1 mg/dL. All serological markers for secondary glomerulonephritis were negative. Renal biopsy revealed 50% sclerosis of the glomerulus and small dense lymphocyte infiltration of the tubulo-interstitium. Similar cells were found on the gastric mucosa. Despite our recommendation for chemotherapy, he refused all treatments except for hemodialysis, which was maintained for 12 months until his death. This patient represents the first case report of the renal involvement of MCL leading to end stage renal disease.     

Potentiating antilymphoma efficacy of chemotherapy using a liposome for integration of CD20 targeting,ultra-violet irradiation polymerizing,and controlled drug delivery

Unlike most malignancies, chemotherapy but not surgery plays the most important role in treating non-Hodgkin lymphoma (NHL). Currently, liposomes have been widely used to encapsulate chemotherapeutic drugs in treating solid tumors. However, higher in vivo stability owns a much more important position for excellent antitumor efficacy in treating hematological malignancies. In this study, we finely fabricated a rituximab Fab fragment-decorated liposome based on 1,2-bis(10,12-tricosadiynoyl)-sn-glycero-3-phosphocholine (DC8,9PC), which can form intermolecular cross-linking through the diacetylenic group by ultra-violet (UV) irradiation. Our experimental results demonstrated that after the UV irradiation, the liposomes exhibit better serum stability and slower drug release with a decreased mean diameter of approximately 285 nm. The cellular uptake of adriamycin (ADR) by this Fab-navigated liposome was about four times of free drugs. Cytotoxicity assays against CD20⁺ lymphoma cells showed that the half maximal (50%) inhibitory concentration (IC50) of ADR-loaded immunoliposome was only one fourth of free ADR at the same condition. In vivo studies were evaluated in lymphoma-bearing SCID mice. With the high serum stability, finely regulated structure, active targeting strategy via antigen-antibody reaction and passive targeting strategy via enhanced permeability and retention (EPR) effect, our liposome exhibits durable and potent antitumor activities both in the disseminated and localized human NHL xeno-transplant models.     

Metabolic assessement of spleen infiltration by non-Hodgkin lymphoma using ^18F-FDG PET/CT： Preliminary clinical results

infiltration without morphology changes, which may not be diagnosed exactly by conventional image.     

Cyclin D1和bcl-2在B细胞淋巴瘤中的表达及其在鉴别诊断中的意义

B细胞淋巴瘤根据免疫表型可分为不同亚型,且不同亚型侵袭度不同,预后也有很大差异.Cyclin D1是已被证实与肿瘤有最直接关系的细胞周期蛋白,在大多B细胞淋巴瘤[套细胞淋巴瘤(MCL)、慢性淋巴细胞白血病(CLL)、边缘区淋巴瘤(MZL)、弥漫大B细胞淋巴瘤(DLBCL)等」中均有表达.多数B细胞淋巴瘤[滤泡性淋巴瘤(FL)、DLBCL等]都能可见易位活化的bcl-2表达增强.Cyclin D1及bcl-2作为B细胞淋巴瘤重要的细胞周期蛋白及抗凋亡基因,在淋巴瘤的鉴别诊断中起重要作用,其检测及检测手段的灵敏度和特异度具有重要的临床价值.     

原发性纵隔大B细胞淋巴瘤研究进展

原发性纵隔大B细胞淋巴瘤(PMBCL)是弥漫大B细胞淋巴瘤(DLBCL)的一种特殊类型,具有独特的临床表现及病理学、分子生物学特征.目前尚无标准的治疗方案,回顾性分析表明第三代的化疗方案优于CHOP方案,利妥昔单抗的应用缓解了这种差异,是否需要接受联合放疗尚无定论.未来将脱氧葡萄糖-正电子发射计算机断层显像(FDG-PET)用于PMBCL的疗效评估,如果能提供可靠的预后信息,就可以减轻治疗强度.